research articles on evolutionary genetics

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Evolutionary genetics articles from across Nature Portfolio

Evolutionary genetics is the study of how genetic variation leads to evolutionary change. It includes topics such as the evolution of genome structure, the genetic basis of speciation and adaptation, and genetic change in response to selection within populations.

Tissue specificity follows gene duplication

A comparative transcriptomic analysis of eight tissue types in twenty bilaterian species reveals the long-lasting effects of genome duplication on the evolution of novel tissue-specific gene-expression patterns.

• Anamaria Necsulea

Latest Research and Reviews

Unveiling the A-to-I mRNA editing machinery and its regulation and evolution in fungi

A-to-I editing in animals is catalyzed by enzymes of the Adenosine Deaminase Acting on RNA family, orthologues of which do not exist in fungi. Here, Feng et al. characterise the enzymes involved in A-to-I mRNA editing in Fusarium graminearum .

• Chanjing Feng
• Huiquan Liu

Centralized industrialization of pork in Europe and America contributes to the global spread of Salmonella enterica

By analysing the genome of over 9,000 pig-associated isolates, this study shows that modernized agricultural systems have favoured the acquisition of antimicrobial resistance genes, population expansion and global transmission of pig-enriched Salmonella over the past century.

• Zhemin Zhou

Mutation characteristics and molecular evolution of ovarian metastasis from gastric cancer and potential biomarkers for paclitaxel treatment

‘Gastric cancer metastasis to the ovary is difficult to treat and is not fully understood. Here, the authors characterized mutations in a cohort of matched primary and metastatic disease, and found mutations, including in CLDN18, could predict treatment response to paclitaxel.

• Xiangdong Cheng

Chromosome-level genome assembly of the bethylid ectoparasitoid wasp Sclerodermus sp. ‘alternatusi’

Positive selection in the genomes of two Papua New Guinean populations at distinct altitude levels

This study explores selection signals of Papua New Guinean highlanders and lowlanders using 128 new whole genome sequences. It highlights two genetic variants associated with blood traits that also influence the heart rate of these populations.

• Mathilde André
• Nicolas Brucato
• François-Xavier Ricaut

Emergence of enhancers at late DNA replicating regions

Here the authors report that enhancers appear more often in late-replicating DNA regions and are enriched for mutations affecting TF binding. This relationship with DNA replication time is seen in species evolution and cancer, suggesting a fundamental principle of genome evolution.

• Paola Cornejo-Páramo
• Veronika Petrova
• Emily S. Wong

News and Comment

An updated framework for SARS-CoV-2 variants reflects the unpredictability of viral evolution

The World Health Organization framework for tracking SARS-CoV-2 variants has been updated to reflect the continued evolution of the virus; this framework could be adapted for other emerging respiratory diseases with epidemic and pandemic potential.

• Lorenzo Subissi
• James Richard Otieno
• Maria D. Van Kerkhove

Understanding human uniqueness in the pre-genomic era

In this Journal Club article, Jenny Tung reflects on a 1975 paper from King and Wilson that emphasized the importance of gene regulatory changes in human evolution.

Building a catalogue of short tandem repeats in diverse populations

Reflecting on the importance of short tandem repeats (STRs) in population genetics, Ning Xie highlights a 2023 publication that characterized genome-wide STR variation in global human genomes to expand our understanding of STR genetic diversity within and across populations.

Comparative genomics uncover the evolutionary history of butterfly and moth chromosomes

Using over 200 chromosomal genomes to reconstruct 250 million years of evolutionary history, we define the 32 linkage groups (Merian elements) that were present in the ancestor of Lepidoptera. We chart the dynamics of chromosome fusion and fission that accompanied the global diversification of Lepidoptera.

Rapid evolution of body plans

Within-species adaptation of locomotor capacity in deer mice and defensive structures in stickleback fish is associated with changes in Hox gene regulation.

• Michael A. White

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Showing 1 - 13 of 1,369

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Corynebacterium glutamicum strains">Comprehensive analysis of genomic variation, pan-genome and biosynthetic potential of Corynebacterium glutamicum strains

Md. Shahedur Rahman, Md. Ebrahim Khalil Shimul, Md. Anowar Khasru Parvez

Implications of gene tree heterogeneity on downstream phylogenetic analyses: A case study employing the Fair Proportion index

Kristina Wicke, Md. Rejuan Haque, Laura Kubatko

Larus dominicanus ) populations from Patagonia">Population structure and connectivity among coastal and freshwater Kelp Gull ( Larus dominicanus ) populations from Patagonia

Tatiana Kasinsky, Natalia Rosciano,  [ ... ], Leonardo Campagna

DUF1216 gene family in Brassicaceae ">Lineage-specific gene duplication and expansion of DUF1216 gene family in Brassicaceae

Zai-Bao Zhang, Tao Xiong,  [ ... ], Zi-Yi Ye

Assessing the emergence time of SARS-CoV-2 zoonotic spillover

Stéphane Samson, Étienne Lord, Vladimir Makarenkov

Modeling the influence of lime on the unconfined compressive strength of reconstituted graded soil using advanced machine learning approaches for subgrade and liner applications

Xinghuang Guo, Cesar Garcia,  [ ... ], Shadi Hanandeh

Caenorhabditis elegans ">Reproductive system, temperature, and genetic background effects in experimentally evolving populations of Caenorhabditis elegans

Joanna K. Baran, Paulina Kosztyła,  [ ... ], Zofia M. Prokop

Salmonella serovars—Infantis, Senftenberg, and Alachua isolated from food animal sources in the United States">The spread of pESI-mediated extended-spectrum cephalosporin resistance in Salmonella serovars—Infantis, Senftenberg, and Alachua isolated from food animal sources in the United States

Cong Li, Heather Tate,  [ ... ], Errol A. Strain

Automated code development based on genetic programming in graphical programming language: A pilot study

Pavel Kodytek, Alexandra Bodzas, Jan Zidek

Somatic genome architecture and molecular evolution are decoupled in “young” linage-specific gene families in ciliates

Xyrus X. Maurer-Alcalá, Auden Cote-L’Heureux, Sergei L. Kosakovsky Pond, Laura A. Katz

Echinolaelaps fukienensis provide insights into phylogeny and rearrangement in the superfamily Dermanyssoidea">The complete mitochondrial genome of Echinolaelaps fukienensis provide insights into phylogeny and rearrangement in the superfamily Dermanyssoidea

Gangxian He, Wei Li, Bili Yuan, Wenge Dong

Adaptive evidence of mitochondrial genes in Pteromalidae and Eulophidae (Hymenoptera: Chalcidoidea)

Ning Kang, Hongying Hu

An improved gene expression programming algorithm for function mining of map-reduce job execution in catenary monitoring systems

Jin Ding, Tianyu Jiang,  [ ... ], Youtong Fang

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Articles on Evolutionary genetics

Displaying 1 - 20 of 34 articles.

Neanderthals died out 40,000 years ago, but there has never been more of their DNA on Earth

Peter C. Kjærgaard , University of Copenhagen ; Mark Maslin , UCL , and Trine Kellberg Nielsen , Aarhus University

Slime is all around and inside you – new research on its origins offers insight into genetic evolution

Omer Gokcumen , University at Buffalo

Meet the world’s largest plant: a single seagrass clone stretching 180 km in Western Australia’s Shark Bay

Elizabeth Sinclair , The University of Western Australia ; Gary Kendrick , The University of Western Australia ; Jane Edgeloe , The University of Western Australia , and Martin Breed , Flinders University

Wild animals are evolving faster than anybody thought

Timothée Bonnet , Australian National University

There’s more than one way to grow a baby

Charles Foster , UNSW Sydney ; Camilla Whittington , University of Sydney , and James Van Dyke , La Trobe University

A taste for sweet – an anthropologist explains the evolutionary origins of why you’re programmed to love sugar

Stephen Wooding , University of California, Merced

Genetic GPS system of animal development explains why limbs grow from torsos and not heads

Ethan Bier , University of California, San Diego

Evolutionary study suggests prehistoric human fossils ‘hiding in plain sight’ in Southeast Asia

João Teixeira , University of Adelaide and Kristofer M. Helgen , Australian Museum

Fruit bats are the only bats that can’t (and never could) use echolocation. Now we’re closer to knowing why

Camilo López-Aguirre , UNSW Sydney and Laura A. B. Wilson , Australian National University

Dire wolves went extinct 13,000 years ago but thanks to new genetic analysis their true story can now be told

Kieren Mitchell , University of Adelaide ; Alice Mouton , Université de Liège ; Angela Perri , Durham University , and Laurent Frantz , Ludwig Maximilian University of Munich

Coronavirus new variant – genomics researcher answers key questions

Lucy van Dorp , UCL

How a Queensland sea sponge is helping scientists unravel a 700-million - year-old mystery of evolution

Emily S Wong , UNSW Sydney

Homosexuality may have evolved for social, not sexual reasons

Andrew Barron , Macquarie University

Fast evolution explains the tiny stature of extinct ‘Hobbit’ from Flores Island

José Alexandre Felizola Diniz-Filho , Universidade Federal de Goiás (UFG) and Pasquale Raia , University of Naples Federico II

Galapagos giant tortoises make a comeback, thanks to innovative conservation strategies

James P. Gibbs , State University of New York College of Environmental Science and Forestry

Study tracing ancestor microorganisms suggests life started in a hydrothermal environment

Jeff Errington , Newcastle University

Why did sex evolve? Researchers edge closer to solving longstanding mystery

Laurence D. Hurst , University of Bath

Why is the X chromosome so odd? Traffic analogy helped us crack the mystery

Laurence D. Hurst , University of Bath and Lukasz Huminiecki , Uppsala University

How DNA is helping us fight back against pest invasions

Steven Bourne , University of Southampton

It takes two: how mutualisms evolve in a world of selfish genes

Alex Jordan , The University of Texas at Austin

Related Topics

• Climate change
• Evolutionary biology
• Homosexuality
• Human evolution
• Natural selection

Top contributors

Professor of Evolutionary Genetics at The Milner Centre for Evolution, University of Bath

Winthrop Professor, Oceans Institute, The University of Western Australia

Distinguished Professor of Genetics and Vice Chancellor's Fellow, La Trobe University

Head, Metabolic Genetic Diseases Research Laboratory, Deakin University

Senior Research Fellow, The University of Western Australia

Associate Professor, Human Molecular Nutrition, University of Newcastle

Senior Lecturer in Genetics, University of Adelaide

(Formerly) Senior Research Specialist, Johns Hopkins University

Postdoctoral research fellow, The University of Western Australia

Professor of Natural Sciences, UCL

Professor, Macquarie University

Lecturer in Evolutionary Biology and Zoology, Queensland University of Technology

Professor of Ecology and Evolutionary Biology, University of Toronto

Postdoctoral Fellow, Department of Zoology, University of Otago

Science Communicator, University of Sydney

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Human Genetics

Genome Biology and Evolution is proud to have a vital role in creating a hub where the development and dissemination of cutting-edge human genetics research can be facilitated. 

This virtual issue features a collection of recent high-impact research that focuses on human genetics. Follow the links below and explore the innovative research that is helping to transform the field of evolutionary genomics.

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Who are we? Where did we come from? How did we get here? Throughout the ages, humans have sought answers to these questions, pursuing wisdom through religion, philosophy, and eventually science. Evolutionary analyses published by  Genome Biology and Evolution ( GBE ) allow us to peer into the mirror and better understand ourselves as a species, bringing us closer than ever to uncovering the...

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Study reveals insights into protein evolution

by Marcy de Luna, Rice University

Rice University's Peter Wolynes and his research team have unveiled a breakthrough in understanding how specific genetic sequences, known as pseudogenes, evolve. Their paper was published May 13 in the Proceedings of the National Academy of Sciences .

Led by Wolynes, the D.R. Bullard-Welch Foundation Professor of Science, professor of chemistry, biosciences and physics and astronomy and co-director of the Center for Theoretical Biological Physics (CTBP), the team focused on deciphering the complex energy landscapes of de-evolved, putative protein sequences corresponding to pseudogenes.

Pseudogenes are segments of DNA that once encoded proteins but have since lost their ability to do so due to sequence degradation—a phenomenon referred to as devolution. Here, devolution represents an unconstrained evolutionary process that occurs without the usual evolutionary pressures that regulate functional protein-coding sequences.

Despite their inactive state, pseudogenes offer a window into the evolutionary journey of proteins.

"Our paper explains that proteins can de-evolve," Wolynes said. "A DNA sequence can, by mutations or other means, lose the signal that tells it to code for a protein. The DNA continues to mutate but does not have to lead to a sequence that can fold."

The researchers studied junk DNA in a genome that has de-evolved. Their research revealed that a mutation accumulation in pseudogene sequences typically disrupts the native network of stabilizing interactions, making it challenging for these sequences, if they were to be translated, to fold into functional proteins.

However, the researchers observed instances where certain mutations unexpectedly stabilized the folding of pseudogenes at the cost of altering their previous biological functions.

They identified specific pseudogenes, such as cyclophilin A, profilin-1 and small ubiquitin-like modifier 2 protein, where stabilizing mutations occurred in regions crucial for binding to other molecules and other functions, suggesting a complex balance between protein stability and biological activity .

Moreover, the study highlights the dynamic nature of protein evolution as some previously pseudogenized genes may regain their protein-coding function over time despite undergoing multiple mutations.

Using sophisticated computational models, the researchers interpreted the interplay between physical folding landscapes and the evolutionary landscapes of pseudogenes. Their findings provide evidence that the funnel-like character of folding landscapes comes from evolution.

"Proteins can de-evolve and have their ability to fold compromised over time due to mutations or other means," Wolynes said. "Our study offers the first direct evidence that evolution is shaping the folding of proteins."

Along with Wolynes, the research team includes lead author and applied physics graduate student Hana Jaafari; CTBP postdoctoral associate Carlos Bueno; University of Texas at Dallas graduate student Jonathan Martin; Faruck Morcos, associate professor in the Department of Biological Sciences at UT-Dallas; and CTBP biophysics researcher Nicholas P. Schafer.

The implications of this research extend beyond theoretical biology with potential applications in protein engineering, Jaafari said.

"It would be interesting to see if someone at a lab could confirm our results to see what happens to the pseudogenes that were more physically stable," Jaafari said. "We have an idea based on our analysis, but it'd be compelling to get some experimental validation."

Journal information: Proceedings of the National Academy of Sciences

Provided by Rice University

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May. 13, 2024

Rice study reveals insights into protein evolution.

Rice University’s Peter Wolynes and his research team have unveiled a breakthrough in understanding how specific genetic sequences, known as pseudogenes, evolve. Their paper was published May 13 by the Proceedings of the National Academy  of Sciences of the United States of America Journal.

Led by Wolynes, the D.R. Bullard-Welch Foundation Professor of Science, professor of chemistry, biosciences and physics and astronomy and co-director of the Center for Theoretical Biological Physics (CTBP), the team focused on deciphering the complex energy landscapes of de-evolved, putative protein sequences corresponding to pseudogenes.

Pseudogenes are segments of DNA that once encoded proteins but have since lost their ability to do so due to sequence degradation — a phenomenon referred to as devolution. Here, devolution represents an unconstrained evolutionary process that occurs without the usual evolutionary pressures that regulate functional protein-coding sequences.

Despite their inactive state, pseudogenes offer a window into the evolutionary journey of proteins.

“Our paper explains that proteins can de-evolve,” Wolynes said. “A DNA sequence can, by mutations or other means, lose the signal that tells it to code for a protein. The DNA continues to mutate but does not have to lead to a sequence that can fold.”

The researchers studied junk DNA in a genome that has de-evolved. Their research revealed that a mutation accumulation in pseudogene sequences typically disrupts the native network of stabilizing interactions, making it challenging for these sequences, if they were to be translated, to fold into functional proteins.

However, the researchers observed instances where certain mutations unexpectedly stabilized the folding of pseudogenes at the cost of altering their previous biological functions.

They identified specific pseudogenes, such as cyclophilin A, profilin-1 and small ubiquitin-like modifier 2 protein, where stabilizing mutations occurred in regions crucial for binding to other molecules and other functions, suggesting a complex balance between protein stability and biological activity.

Moreover, the study highlights the dynamic nature of protein evolution as some previously pseudogenized genes may regain their protein-coding function over time despite undergoing multiple mutations.

Using sophisticated computational models, the researchers interpreted the interplay between physical folding landscapes and the evolutionary landscapes of pseudogenes. Their findings provide evidence that the funnellike character of folding landscapes comes from evolution.

“Proteins can de-evolve and have their ability to fold compromised over time due to mutations or other means,” Wolynes said. “Our study offers the first direct evidence that evolution is shaping the folding of proteins.”

Along with Wolynes, the research team includes lead author and applied physics graduate student Hana Jaafari ; CTBP postdoctoral associate Carlos Bueno ; University of Texas at Dallas graduate student Jonathan Martin; Faruck Morcos, associate professor in the Department of Biological Sciences at UT-Dallas; and CTBP biophysics researcher Nicholas P. Schafer.

The implications of this research extend beyond theoretical biology with potential applications in protein engineering, Jaafari said.

“It would be interesting to see if someone at a lab could confirm our results to see what happens to the pseudogenes that were more physically stable,” Jaafari said. “We have an idea based on our analysis, but it’d be compelling to get some experimental validation.”

Characterization of ZmSnRK1 genes and their response to aphid feeding, drought and cold stress

• Research Article
• Open access
• Published: 12 May 2024

Cite this article

You have full access to this open access article

• M. Aydın Akbudak 1 ,
• Kubra Yildiz 1 ,
• Durmus Cetin 1 ,
• Ertugrul Filiz 2 ,
• Utku Yukselbaba 3 &
• Vibha Srivastava 4 , 5  

The SnRK1 complex in plants regulates metabolism in response to environmental stresses and glucose depletion, for stress adaptation and energy homeostasis. Through phosphorylation of various targets, SnRK1 orchestrates intricate regulatory mechanisms involved in autophagy, nutrient remobilization, and TOR activity inhibition, showcasing its pivotal role in coordinating plant metabolism and stress responses. The present study aimed to identify members of the SnRK1 gene family in the maize genome and characterize them using bioinformatics and expression analyses under aphid feeding, drought, and cold stress. The focus of the study was to conduct a comprehensive analysis towards determining gene diversity of ZmSnRK1 genes, constructing intricate 3D structures, and identifying stress-related cis -elements. Four SnRK1 genes were identified, which were named ZmSnRK1.1 , ZmSnRK1 . 2 , ZmSnRK1 . 3 , and ZmSnRK1 . 4 . The SnRK1 proteins were found to have a distribution of conserved motifs; however, the distinction between monocots and dicots in the phylogenetic tree was clearly demonstrated. Analysis of the promoter region revealed that the ZmSnRK1 genes contain stress-related cis -elements. Compared to the control, ZmSnRK1.3 significantly upregulated in response to aphid feeding and cold stress, while ZmSnRK1.2 showed elevated expression under drought conditions. The expression of the other two genes under these treatments was generally unperturbed. The findings of this study are poised to establish a valuable scientific foundation for future research on the roles of the SnRK1 gene family in plants, providing valuable insights for enhancing genetic resilience to stress and optimizing yield traits.

Avoid common mistakes on your manuscript.

Introduction

Plants adjust their metabolisms when exposed to biotic and abiotic environmental stresses (Wurzinger et al. 2018 ) The process of phosphorylation and dephosphorylation of proteins is crucial for plants to transmit the environmental stress signals into biological effects (Cohen 1988 ). Research shows that protein kinases, through membrane receptor proteins, are important regulators that perceive environmental signals and activate different protein phosphorylation pathways (Hunter 1995 ). The AMPK/SNF1/SnRK1 complex, known as an essential component of the evolutionarily conserved energy management network, is one of the important protein kinases that mediates the regulation of cellular energy metabolism (Alderson et al. 1991 ; Broeckx et al. 2016 ; Celenza and Carlson 1986 ). In higher eukaryotes, AMPK/SNF1/SnRK1 protein kinases (PK) function as key cellular energy sensors initiating adaptive changes necessary to maintain the energy homeostasis (Broeckx et al. 2016 ). SNF1, also known as Sucrose Non-Fermenting 1, was found in Saccharomyces cerevisiae and characterized as the Ser/Thr kinase (Carlson et al. 1981 ). SnRK1 is widely reported in plants as the ortholog of SNF1, along with its paralogs such as SnRK2 and SnRK3 (Halford and Grahame 1998 ; Hrabak et al. 2003 ).

SnRK1 kinases function as heterotrimeric complexes consisting of highly conserved catalytic α subunits and regulatory β and γ subunits (Celenza and Carlson 1986 ; Polge and Thomas 2007 ). It is rapidly activated in response to decreasing levels of glucose, a preferred carbon (C) source that can be rapidly fermented (Hedbacker and Carlson 2008 ). In mammals, the AMPK, once activated by energy shortage, restores energy homeostasis by activating ATP-generating catabolic pathways such as glycolysis and fatty acid oxidation, while inhibiting ATP-consuming biosynthetic and other growth processes (Hardie et al. 2012a , b ). Similarly, in plants and yeast, SnRK1 and SNF1 kinases, respectively, emerge as a central energy sensor in the metabolic signaling network controlling important events such as plant growth, development and stress tolerance (Hulsmans et al. 2016 ; Lastdrager et al. 2014 ; Pathak et al. 2022 ; Smeekens et al. 2010 ; Xiong and Sheen 2015 ). SnRK1 can be activated under aphid feeding, drought or cold conditions that directly or indirectly cause energy deficit, affecting processes like photosynthesis, respiration or carbon allocation (Broeckx et al. 2016 ). Additionally, SnRK1 triggers autophagy and nutrient remobilization by phosphorylating ATG1 (Chen et al. 2017 ), and inhibits TOR activity, another energy sensor that responds to the availability of nutrients, by phosphorylating RAPTOR (Rodriguez et al. 2019 ). These intricate regulatory mechanisms underscore SnRK1’s multifaceted role in plant metabolism, growth, development, and stress responses. Furthermore, it acts as a central regulator, activating metabolic pathways crucial for maintaining metabolic balance, especially in stress conditions (Halford and Hey 2009 ).

Given the substantial role of SnRK1 in regulating metabolic and stress signaling pathways, our study focused on identifying SnRK1 members in maize. We have conducted comprehensive analyses including determining gene diversity levels of ZmSnRK1 genes, analyzing their domain structures, constructing intricate 3D structures with cavity pockets, and identifying stress-related cis-elements. It extends beyond the typical scope of research by encompassing all varieties of maize SnRK genes (Feng et al. 2022 ). Notably, SnRK1 kinases serve as crucial metabolic sensors, orchestrating responses to various stressors and maintaining energy balance through direct phosphorylation of key metabolic enzymes and regulatory proteins, alongside extensive transcriptional reprogramming. Hence, we detected SnRK1 expression profiles under aphid feeding, drought, or cold stress, offering valuable insights for enhancing genetic resilience to stress and optimizing yield traits.

Materials and methods

Genome-wide identification of zmsnrk1 genes.

First, the UniProtKB database ( https://www.uniprot.org/ ) was used to obtain SnRK1 protein sequences from Arabidopsis thaliana (Q38997: SNRK1.1 and P92958: SNRK1.2) and Oryza sativa (Q852Q2: SNRK1A and Q852Q1: SNRK1B). These reference sequences were then used to find orthologs of the SnRK1 genes in the maize genome by means of blastp analyses in the Phytozome v13 database ( https://phytozome-next.jgi.doe.gov/ ). The reliability of the retrieved maize SnRK1 sequences was further checked by domain analysis using the SMART ( http://smart.embl-heidelberg.de/ ) and the InterPro ( https://www.ebi.ac.uk/interpro/search/sequence/ ) online servers.

Sequence analyses

The physico-chemical features of the SnRK1 protein sequences were predicted by ProtParam tool ( http://web.expasy.org/protparam/ ; Gasteiger et al. 2005 ), and the subcellular localization was predicted by WoLF PSORT (advanced protein subcellular localization prediction tool) ( https://wolfpsort.hgc.jp/ ) (Horton et al. 2007 ). Exon–intron structures of SnRK1 genes were obtained using the Phytozome database v13 ( https://phytozome-next.jgi.doe.gov/ ), and percent identity (%) was calculated using blastp tool in NCBI ( https://www.ncbi.nlm.nih.gov/ ). ZmSnRK1 gene diversity level and Tajima’s D were calculated using the MEGA11 software (Tamura et al. 2021 ).

Conserved motif and phylogenetic analyses

The conserved motif structures of the SnRK1 sequences were found using the multiple em for motif elicitation (MEME) tool v5.5.5 ( http://meme-suite.org/tools/meme ) with the following parameter settings: maximum number of motifs to find as 10; minimum motif width as 6, and maximum motif width as 50 (Bailey et al. 2009 ). The phylogenetic tree was generated by MEGA11 (Tamura et al. 2021 ) using Neighbor-Joining (NJ) method for 1000 bootstraps to infer evolutionary history. Evolutionary distances were calculated using the Poisson correction method. All ambiguous positions were removed for each sequence pair (pairwise deletion option).

Co-expression network and cis ‑acting elements analyses

The co-expression network analyses of maize SnRK1 genes were constructed using the MaizeNet web server ( http://www.inetbio.org/maizenet ). MaizeNet is a genome-scale co-functional network of maize genes (Lee et al. 2019 ). A 2000 bp upstream sequence from the ATG start codon, obtained from the Phytozome database v13, was used as the putative promoter region. Cis -acting regulatory elements (CAREs) were examined in the putative promoter sequences using the PLACE database v30 ( https://www.dna.affrc.go.jp/PLACE/?action=newplace ) (Higo et al. 1999 ).

Protein modeling and topology analyses

The putative 3D models of the SnRK1 were generated using the Phyre2 (protein homology/analogy recognition engine v2.0) web tool ( http://www.sbg.bio.ic.ac.uk/phyre2/html/page.cgi?id=index ), which uses advanced remote homology recognition methods to generate 3D models at intensive mode (Kelley et al. 2015 ). The topological properties were evaluated using the CASTp v3.0 web server ( http://sts.bioe.uic.edu/castp/calculation.html ) (Tian et al. 2018 ).

Plant materials and stress treatments

F1 seeds of the maize ( Zea mays ) cultivar ‘Albayrak’ (Tarex Co., Turkiye) were utilized in this study. These seeds were planted individually in 8 × 8 × 9 cm 3 pots filled with a peat–perlite mixture (3:1), and grown in a greenhouse under 28 ± 1 °C, 12:12-h photoperiod without the use of any insecticides. The plants were irrigated with tap water every second day.

For the induction of drought stress, 21-day-old plants were subjected to withholding of water supply for a duration of 7 days. On the other hand, control plants received irrigation according to the regular schedule, i.e., every other day. After the 7-day water withholding period, all plant leaves and roots were collected and preserved at −80 °C for subsequent analyses.

Cold stress was imposed by subjecting the plants to a temperature of + 4 °C for 24 h. Meanwhile, control plants were maintained in the greenhouse under standard conditions. After the cold exposure, all plant leaves and roots were harvested for RNA isolation.

The population of corn leaf aphid ( Rhopalosiphum maidis ) employed in the experiments was cultivated on maize plants in growth chambers at a temperature of 26 ± 1 °C, relative humidity of 60 ± 10% in 16:8-h photoperiod within plexiglass cages. Weekly checks were conducted on the plants inside the cages, which were watered every other day. Additionally, once a week, dried plants were replaced with fresh ones. A total of 15 aphids were placed on the second true leaf (V2) of the 3-week-old plant (Pingault et al. 2021 ; Tzin et al. 2015 ). The plants were exposed to aphid feeding for 2, 4 or 8 h, and the V2 leaves and roots were harvested for RNA isolation at each time point.

RNA isolation and gene expression analysis

Total RNA was isolated from leaf and root tissues using the NucleoZOL kit (Macherey–Nagel, Germany) following manufacturer’s guidelines. Subsequently, Turbo DNase (Thermo Fisher, USA) treatment was performed on the samples. Evaluation of RNA integrity and potential DNA contamination was done through gel electrophoresis, and quantification was carried out using the Qubit system (Invitrogen, USA). Real time-quantitative PCR (RT-qPCR) was conducted on Rotor-Gene Q (Qiagen, USA) using 10 ng DNase-treated RNA with Luna Universal One-Step RT-qPCR Kit (NEB, USA). The primers for RT-qPCR analysis are given in Table  1 . The MEP (Membrane protein PB1A10.07c) gene served as an endogenous control (Manoli et al. 2012 ) in the gene expression analysis using the ΔΔC T method (Livak and Schmittgen 2001 ), in which the average C T values were derived from a minimum of four biological and three technical replicates for each ZmSnRK1 gene.

MDA (Malondialdehyde) and H 2 O 2 assays

The MDA content of plants was assayed using a method modified from Ohkawa et al. ( 1979 ). Grounded in liquid nitrogen, 0.2 g of leaf tissues were suspended in 2 ml of 5% trichloroacetic acid (TCA). The homogenates were transferred into clean 2 ml microfuge tubes and centrifuged at 12,000 rpm at room temperature. Equal amounts of lysate and freshly prepared 0.5% thiobarbituric acid (TBA) in 20% TCA were mixed, then incubated at 96 °C for 25 min. The tubes were chilled on ice until they reached room temperature, then centrifuged at 10,000 rpm for 5 min. The absorbances of the supernatants were measured at 532 nm and 600 nm wavelengths to eliminate non-specific reflections due to turbidity. A freshly prepared 0.5% TBA in 20% TCA solution was used as a blank. The MDA content of the samples was assayed using an absorbance coefficient of 155 mM −1  cm −1 .

The H 2 O 2 (hydrogen peroxide) contents were assayed using the method developed by Sergiev et al. ( 1997 ). After grounding in liquid nitrogen, 0.5 g of a plant sample was homogenized in 5 ml of 0.1% trichloroacetic acid (TCA). Following centrifugation at 12,000 g for 15 min, 0.5 ml of supernatants were transferred into clean 1.5 ml microfuge tubes, and 0.5 ml of 10 mM potassium phosphate buffer (pH 7.0) and 1 ml of 1 M potassium iodide (KI) were added. The absorbances of the supernatants were measured at 390 nm. The H 2 O 2 contents of the samples were calculated using a standard curve prepared according to known H 2 O 2 concentrations.

Identification of ZmSnRK1 genes and sequence analysis

In this study, four putative SnRK1 genes were identified in the maize genome (Table  2 ). The number of exons in the SnRK1 genes varied between 10 and 12, and the protein length ranged from 375 to 653 amino acid residues. The molecular weight of the SnRK1 proteins ranged from 42.61 to 72.28 kDa, and the pI values ranged from 7.02 to 9.09. Subcellular localization analyses predicted that SnRK1 proteins are generally found in the cytoplasm.

Domain analysis using the InterPro database revealed the presence of the conserved AMPK/SnRK1 domains in the ZmSnRK1 proteins (Fig.  1 ): the catalytic domain of the α subunit of the Ser/Thr Kinase (cd14079), the C-terminal regulatory domain of the 5′-AMP-activated protein kinase (AMPK) α catalytic subunit (cd12122), the UBA domain found in the plant sucrose nonfermenting-1-related kinase (SnRK1) proteins (cd14335), and the protein kinase domain profile (PS50011).

Conserved domains of putative ZmSnRK1 proteins. STKc_AMPK_alpha, the catalytic domain of the α subunit of the Ser/Thr Kinase; UBA_SnRK1, UBA domain of the plant sucrose nonfermenting-1-related kinase (SnRK1); AMPKA_C, AMP-activated protein kinase; protein_kinase_dom

Further, ZmSnRK1 proteins were found to have 69.60–82.20% identify with the Arabidopsis SnRK1 orthologs, KIN1 and KIN2, and 73.36–90.03% identify with the rice SnRK1A and SnRK1B. As expected, the similarity ratios of ZmSnRK1 proteins with the rice SnRK1 orthologs were higher than with the Arabidopsis SnRK1 orthologs (Table  3 ).

To get more insights about ZmSnRK1 gene diversity level, nucleotide pairwise distance analyses were performed, and values were found to range from 0.217 to 0.447 with an overall average of 0.319. The number of segregating sites (S) and nucleotide diversity were found to be 651 and 0.134, respectively. The Tajima test statistic was also found to be −1.45.

Phylogenetic and conserved motif analyses

The phylogenetic tree topology clearly showed the separation of SnRK1 proteins in monocots and dicots (groups A and B, respectively). When the monocot–dicot phylogenetic groups were analyzed, it was found that monocots, especially, grouped with stronger bootstrap values (Fig.  2 A). Within group A, maize and rice SnRK1 proteins were found to group together (OsSnRK1B and ZmSnRK1.1) with a 100% bootstrap value. Additionally, OsSnRK1A and ZmSnRK1.4 proteins were found to group with a 99% bootstrap value. These results support the strong conservation of SnRK1 genes, especially among monocots. A total of seven different plant species, five dicots and two monocots, were analyzed, and 10 conserved motifs were found (Fig.  2 B), namely motif 1 through 10: DGHFLKTSCGSPNYAAPEVISGKLYAGPEVDVWSCGVILYALLCGTLPFD (motif 1), DIYVVMEYVKSGELFDYIVEKGRLQEDEARRFFQQIISGVEYCHRNMVVH (motif 2), IPNLFKKIKGGIYTLPSHLSPGARDLIPRMLVVDPMKRITIPEIRZHPWF (motif 3), QFPVERKWALGLQSRAHPREIMTEVLKALQELNVCWKKIGHYNMKCRWVP (motif 4), SFGKVKIAEHILTGHKVAIKILNRRKIKNMEMEEKVRREIKILRLFMHPH (motif 5), YLAVPPPDTAQQAKKIDEEILQEVVKMGFDKNQLIESLRNRLQNEATVAY (motif 6), KSPNVVKFEIQLYKTRDEKYLLDLQRVQGPQLLFLDLCAAFLTQLRVL (motif 7), PENLLLDSKCNVKIADFGLSN (motif 8), YLLLDNRFRATSGYLGAEFQESMESSFNQIAS (motif 9), and GAGRVENPLPNYKJGKTLGIG (motif 10). Except for the ZmSnRK1.1 and ZmSnRK1.3 proteins, these 10 motifs were detected in all monocot and dicot SnRK1 proteins.

The phylogenetic relationship of SnRK1 proteins from different plant species. A Phylogenetic relationship of maize, Arabidopsis , rice, poplar, cucumber, tobacco and pepper SnRK1 proteins, B the conserved motif analyses of each SnRK1 protein

AMPK, SNF1 and SnRK1 undergo activation through T-loop phosphorylation at Thr residue, mediated by upstream kinases (Crozet et al. 2014 ). The presence of the T-loop motif (LKTS) was confirmed through multiple sequence alignment of ZmSnRK1 genes. In rice, the T-loop is positioned at Thr173; in wheat, at Thr170; and in Arabidopsis, at Thr175. Similarly, the position of the T-loop was discerned at Thr170 and Thr173 in ZmSnRK1.2 and ZmSnRK1.4, respectively, and at Thr234 and Thr383 in ZmSnRK1.1 and ZmSnRK1.2, respectively.

Cis -element analysis of the ZmSnRK1 promoter regions in maize

To understand the regulation of the four ZmSnRK1 genes, 2000 bp upstream regions of each gene were analyzed for the presence of stress-related cis -elements using the PLACE database (Table  4 ). Of the 10 different stress-related cis -elements examined by the program, only the SARE (salicylic acid responsive cis -acting element) motif (CC(A/T)6GG) was absent in the four ZmSnRK1 gene promoter regions. The rest were all found at different frequency in one or more ZmSnRK1 gene. The most found cis -element was the MYC motif (CACGTG) with 56 occurrences, followed by the W-box (TTGACY) (52), the CG-box (ACCGCC or GCCGAC) (25) and the ABRE (ACGTGG/TC) (24). When comparing the total number of cis -elements in the promoter regions of each gene, the highest number was found in the ZmSnRK1.1 with 58 cis -elements, followed by ZmSnRK1.3 with 52, ZmSnRK1.2 with 49, and ZmSnRK1.4 with 37 cis -elements.

Co-expression network analysis of ZmSnRK1 genes

Gene co-expression network analysis on the MaizeNet web server revealed 440 genes directly linked to ZmSnRK1.1 (Zm00001eb013270), ZmSnRK1.2 (Zm00001eb094400), and ZmSnRK1.3 (Zm00001eb293240) (Fig.  3 ). The database did not contain ZmSnRK1.4 ; therefore, this analysis focused only on the three ZmSnRK1 genes. The 10 genes with the highest score are as follows: GRMZM5G845175 (Zm00001d025300), GRMZM2G041312 (Zm00001d003864), GRMZM2G064725 (Zm00001d047594), GRMZM2G138814 (Zm00001d028946), GRMZM2G027632 (Zm00001d041849), GRMZM2G130950 (Zm00001d022545), GRMZM2G047774 (Zm00001d034896), GRMZM2G014170 (Zm00001d012817), GRMZM2G135073 (Zm00001d052051), and GRMZM2G143213 (Zm00001d048497).

In particular, the following four genes showed the highest score in the network: AtSNF4 , a homolog of yeast sucrose nonfermenting 4; 5′-AMP-activated protein kinase beta-2 subunit; A-type cyclin-dependent kinase; and protein kinase superfamily protein (Table  5 ). Therefore, ZmSnRK1 genes were generally associated with SnRK, cyclin-dependent kinase and protein kinase.

Co-expression network of ZmSnRK1.1 , ZmSnRK1.2 and ZmSnRK1.3 (dark blue) with 440 candidate genes using the MaizeNet web server

Predicted 3D structure of ZmSnRK1 proteins

The putative 3D models and charges of ZmSnRK1 proteins were modelled using the Phyre2 server (Fig.  4 ). These predicted 3D models showed that the topology of protein structures and charges differed between the four ZmSnRK1 proteins, which may be related to their functional diversity. The percentage of structural overlap of the predicted 3D models ranged from 22.28 to 84.17% for the four ZmSnRK1 proteins. The lowest percentage of overlap was found between ZmSnRK1 and ZmSnRK3 (22.28%) and the highest between ZnSnRK2 and ZmSnRK4 (84.17%). Analyses of the surface topography revealed variations in the surface pocket areas, which may be related to substrate binding, and therefore, a specific function of the protein.

The predicted 3D structures of ZmSnRK1 proteins from the Phyre2 web portal (pictures at the top). The color indicates the charge (isoelectric point), where red is positive, blue is negative and white is neutral. The images below show the surface topography of the same proteins using the CASTp 3.0 server. Red areas on the protein models indicate surface pockets

Morphological and physiological analyses

To evaluate the impact of aphid feeding, drought and cold stress on the maize plants, we employed both morphological observations and physiological assays. Following a 7-day period of drought stress, visible wilting occurred due to water deficit (Fig.  5 a). Likewise, exposure to cold temperature for 24 h led to the loss of turgor in leaves and wilting of older leaves (Fig.  5 b). However, short-term exposure to aphid feeding, lasting a maximum of 8 h, did not result in discernible morphological changes in the plants (Fig.  5 c).

Effects of drought ( a ), cold ( b ) and aphid ( c ) stresses on maize plants. C: Control plant S: Stressed plant

MDA formation, a result of lipid membrane peroxidation by ROS, serves as a marker for stress-induced cellular damage (Łukasik and Goławska 2021 ; Sun et al. 2022 ; Turk et al. 2020 ). H 2 O 2 , a byproduct of plant aerobic metabolism, is another commonly utilized indicator of oxidative stress. Elevated levels of H 2 O 2 have been noted in plants subjected to aphid feeding, drought, and cold stress, including maize (Hussain et al. 2020 ; Pant and Huang 2021 ; Ramazan et al. 2021 ). Thus, assessing the levels of MDA and H 2 O 2 in plants confirms the effect of the stress at physiological level (Akbudak et al. 2020 ; 2022 ).

The accumulation of MDA and H 2 O 2 in leaf tissues of drought-stressed plants indicates considerable impact of drought on maize plants (Fig.  6 ). In contrast, there was no significant change in MDA and H 2 O 2 contents in the leaves of plants exposed to aphid feeding or cold stress (Fig.  6 a, b). Therefore, physiological effects of the short duration of aphid feeding or cold stress were not detected by these markers, but the lengthy period of drought stress resulted in the production of MDA and H 2 O 2 , indicating lipid membrane peroxidation by ROS.

Effects of aphid, drought and cold stress on the a MDA (nmol / g FW b H 2 O 2 (μmol / g FW) contents of maize plants. The histograms represent the means of four biological and three technical replicates. The error bars depict the standard errors of the mean (sdom; n = 3)

Expression profiles of ZmSnRK1 genes under aphid feeding, drought and cold stress

A differential pattern of expression was found for ZmSnRK1.1 , ZmSnRK1.2 , ZmSnRK1.3 and ZmSnRK1.4 under aphid feeding, drought or cold stress (Fig.  7 ).

Expression profiles of ZmSnRK1 genes in maize leaves and roots under aphid feeding, drought and cold stress. Control represents the expression of each gene in untreated maize plants. Histograms represent means of four biological and three technical replicates. The error bars indicate the standard error (sdom; n = 3)

The aphid feeding resulted in the upregulation of ZmSnRK1.3 in the leaves, which increased approximately 15-fold within 2 h of stress compared to the control. After 4 h of aphid feeding, a slight upregulation was also observed in the expression of ZmSnRK1.1 , ZmSnRK1.2 , and ZmSnRK1.4 in leaves, although their expression levels returned to baseline after 8 h. While the expression levels of ZmSnRK1 genes in roots generally exhibited minimal variation compared to control plants under aphid feeding, a noteworthy upregulation of the ZmSnRK1.3 gene was observed, showing an increase of up to threefold after four hours of exposure.

Drought stress predominantly affected the expression of ZmSnRK1.2 , which exhibited a 5.5-fold upregulation in leaves compared to the control, while the expression of other ZmSnRK1 genes fluctuated within a narrow range (0.81–1.71). Drought stress prompted the upregulation of ZmSnRK1.1 and ZmSnRK1.2 genes in roots by up to 1.76-fold, concurrently with a significant downregulation of ZmSnRK1.3 and a slight decrease in ZmSnRK1.4 expression.

Cold stress had a minimal impact on the expression of ZmSnRK1 genes in leaves, except for ZmSnRK1.3 , which demonstrated a remarkable 11-fold increase compared to control plants. Cold stress similarly induced a significant 23-fold upregulation in the expression of the ZmSnRK1.3 gene in maize roots, while the other three ZmSnRK1 genes experienced downregulation. Notably, ZmSnRK1.3 emerged as the primary gene significantly upregulated in both maize leaves and roots under cold stress, delineating its pivotal role in maize’s response to aphid feeding and cold stress across different plant tissues. However, its involvement in drought stress appeared less pronounced.

This study identified four paralogs of SnRK1 α-subunit genes in the maize genome, referred to as ZmSnRK1 that contain the canonical catalytic domain of the Ser/Thr kinase, the UBA domain, and the C-terminal domain. Additionally, T-loop motif in each of the four ZmSnRK1 was identified. These domains are conserved in SnRK1α genes across yeast, human and plants (Jamsheer et al. 2021 ), and phosphorylation of Thr in the T-loop is critical in the activation of SnRK1 (Crozet et al. 2016 ). Phylogenetic analysis showed ZmSnRK1 grouped with rice and diverged from Arabidopsis, indicating dicot and monocot separation of the protein sequences. The genes identified in this study align with the maize SnRK1 genes found by Feng et al. ( 2022 ). Nonetheless, the predicted subcellular localization differs from that in our analysis. Feng et al. ( 2022 ) reported nuclear localization of ZmSnRK1.1 and mitochondrial localization for ZmSnRK1.3 and ZmSnRK1.4. Whereas our study found cytoplasmic or plasma membrane localization for ZmSnRK1s. Similarly, in Arabidopsis, SnRK1 proteins are localized in the cytoplasm or plasma membrane. However, nuclear localization and possibly also mitochondrial localization, occurs in specific tissues under specific conditions (Bitrián et al. 2011 ). Thus, while subcellular targeting of SnRK1 is certainly possible, it appears to be highly regulated by the environmental signals.

Co-expression analysis of ZmSnRK1 genes found a strong hit with the homologs of the regulatory subunits: Arabidopsis β-subunit and the βγ-subunit also called AtSNF4. These regulatory subunits interact with the α-subunit to form the heterotrimeric AMPK/SNF1/SnRK1 complex. Next, ZmSnRK1 is co-expressed with the homolog of Arabidopsis A-type cyclin dependent kinase (CDKA) that regulates cell cycle progression. While SnRK1-CDKA interaction has not been reported thus far, it is fair to assume that SnRK1 regulates cell cycle progression to allow stress adaptation. Notably, Arabidopsis SnRK1, KIN10, interacts with CDKE1 in the nucleus, and this complex is possibly involved in retrograde signaling (Ng et al. 2013 ).

Initially identified as a sensor of low nutrients, SnRK1 is also involved in stress signaling by regulating a common set of stress-responsive genes (Rodrigues et al. 2013 ). Accordingly, several cis-elements that serve as the binding sites for the well-known transcription factors were identified in 5′-region of ZmSnRK1 genes. The most abundant cis-element was the MYC-binding site with 56 occurrences in the four ZmSnRK1 genes. MYC2 is the most characterized plant MYC TF that regulates plant development and stress response through jasmonate signaling (Song et al. 2022 ; Thompson and Goggin 2006 ), and the maize homolog of MYC2, ZmMYC7 was found to be involved in the resistance to pathogenic fungi (Cao et al. 2023 ). Since plant response to aphid feeding is also regulated by JA signaling (Morkunas et al. 2011 ), ZmSnRK1 could play a broader role in regulating biotic stress responses. Similarly, W-box and ABRE occur frequently in ZmSnRK1 genes, indicating their role in regulating ABA signaling and WRKY mediated stress pathways, respectively. Overall, ZmSnRK1 gene expression is controlled by numerous transcription factors, which in turn regulate developmental and stress-induced pathways.

We analyzed ZmSnRK1 gene expression in response to aphid feeding, drought or cold treatments. Interestingly, ZmSnRK1.3 was upregulated during aphid feeding that contained 21 W-boxes. It is tempting to speculate that this upregulation occurs through WRKY TFs that are strongly induced by aphid feeding (Annacondia et al. 2021 ; Gao et al. 2010 ; Kuśnierczyk et al. 2008 ). Accordingly, ZmSnRK1.3 was upregulated throughout the duration of the experiment (up to 8 h). A stochastic upregulation was also observed in the roots at 4 h post feeding. Further, ZmSnRK1.1 and ZmSnRK1.2 were upregulated in the leaves and roots in the drought condition and ZmSnRK1.3 was strongly upregulated under cold condition in both roots and leaves. Drought and cold treatments broadly encompass dehydration stress that are regulated by DREB TFs (Yamaguchi-Shinozaki and Shinozaki 2006 ). However, recent transcriptomic analyses found important roles of WRKY and MYC TFs in regulating dehydration stress (Berchembrock et al. 2022 ; Singh and Laxmi 2015 ). Thus, differential expression of ZmSnRK1 genes under drought or cold treatments is likely determined by the cis-elements and their interaction with the TFs. In summary, ZmSnRK1 genes represent the a-subunits of the evolutionarily conserved AMPK/SNF1/SnRK1 family of protein kinases that interact with regulatory subunits to form the SnRK1 complex. Like Arabidopsis and rice SnRK1s, ZmSnRK1 appears to play a central role in energy sensing and the response to environmental signals such as abiotic and biotic stress.

SnRK1 genes play crucial roles in signaling pathways, including responses to both biotic and abiotic stresses in plants. This present study analyzed SnRK1 gene family in Zea mays , covering phylogenetic relationships, gene structures, protein motifs and promoter cis-elements. Four ZmSnRK1 genes were characterized, and the dynamic responses of ZmSnRK1 genes have been elucidated through expression profiling under diverse stress conditions such as aphid feeding, drought and cold stress. Our findings contribute to understanding the subcellular localization of ZmSnRK1 proteins, despite discrepancies with previous research regarding their localization. Notably, we observed significant upregulation of ZmSnRK1.3 under aphid feeding and cold stress and ZmSnRK1.2 under drought stress, shedding light on their potential roles in stress response mechanisms. These results underscore the importance of further investigating the functional roles of ZmSnRK1 genes, laying a foundation for future research in plant stress physiology and biotechnology.

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Acknowledgements

This study was supported by Akdeniz University Scientific Research Projects Coordination Unit competitive grant # FBA-2023-6290 to MAA. MAA is thankful for the financial support provided by the Fulbright Visiting Scholar grant from the Turkish Fulbright Commission.

Open access funding provided by the Scientific and Technological Research Council of Türkiye (TÜBİTAK). Funding was provided by Akdeniz Üniversitesi (Grant number: FBA-2023-6290).

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M. Aydın Akbudak, Kubra Yildiz & Durmus Cetin

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MAA: Conceptualization, Writing—Original Draft, Writing—Review and Editing, Supervision, Project administration, Funding acquisition. KY and DC: Investigation. EF: Investigation, Formal Analysis. UY: Resources, Validation. VS: Data curation, Writing—Review and Editing.

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Akbudak, M.A., Yildiz, K., Cetin, D. et al. Characterization of ZmSnRK1 genes and their response to aphid feeding, drought and cold stress. Genet Resour Crop Evol (2024). https://doi.org/10.1007/s10722-024-02006-2

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The formation and evolution of flower coloration in brassica crops.

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The flower coloration of Brassica crops possesses significant application and economic value, making it a research hotspot in the field of genetics and breeding. In recent years, great progress has been made in the research on color variation and creation of Brassica crops. However, the underlying molecular mechanisms and evolutional processes of flower colors are poorly understood. In this paper, we present a comprehensive overview of the mechanism of flower color formation in plants, emphasizing the molecular basis and regulation mechanism of flavonoids and carotenoids. By summarizing the recent advances on the genetic mechanism of flower color formation and regulation in Brassica crops, it is clearly found that carotenoids and anthocyanins are major pigments for flower color diversity of Brassica crops. Meantime, we also explore the relationship between the emergence of white flowers and the genetic evolution of Brassica chromosomes, and analyze the innovation and multiple utilization of Brassica crops with colorful flowers. This review aims to provide theoretical support for genetic improvements in flower color, enhancing the economic value and aesthetic appeal of Brassica crops.

Keywords: Flower coloration, Brassica crops, Carotenoids, Flavonoids, formation, evolution

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* Correspondence: Mingmin Zheng, Jiangxi Provincial Institute of Traditional Chinese Medicine, Nanchang, China Qingqin Gan, Jiangxi Provincial Institute of Traditional Chinese Medicine, Nanchang, China Jiang Long, Jiangxi Provincial Institute of Traditional Chinese Medicine, Nanchang, China Xiaoqing Wang, Jiangxi Provincial Institute of Traditional Chinese Medicine, Nanchang, China Zhilin Guan, Wuhan Botanical Garden, Chinese Academy of Sciences (CAS), Wuhan, 430074, Hubei Province, China

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Intraspecific and interspecific variations in the synonymous codon usage in mitochondrial genomes of 8 pleurotus strains

• Wei Gao 1 ,
• Xiaodie Chen 2 ,
• Jing He 2 ,
• Ajia Sha 2 ,
• Yingyong Luo 2 ,
• Wenqi Xiao 2 ,
• Zhuang Xiong 2 &
• Qiang Li 2 , 3  

BMC Genomics volume  25 , Article number:  456 ( 2024 ) Cite this article

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In this study, we investigated the codon bias of twelve mitochondrial core protein coding genes (PCGs) in eight Pleurotus strains, two of which are from the same species. The results revealed that the codons of all Pleurotus strains had a preference for ending in A/T. Furthermore, the correlation between codon base compositions and codon adaptation index (CAI), codon bias index (CBI) and frequency of optimal codons (FOP) indices was also detected, implying the influence of base composition on codon bias. The two P. ostreatus species were found to have differences in various base bias indicators. The average effective number of codons (ENC) of mitochondrial core PCGs of Pleurotus was found to be less than 35, indicating strong codon preference of mitochondrial core PCGs of Pleurotus . The neutrality plot analysis and PR2-Bias plot analysis further suggested that natural selection plays an important role in Pleurotus codon bias. Additionally, six to ten optimal codons (ΔRSCU > 0.08 and RSCU > 1) were identified in eight Pleurotus strains, with UGU and ACU being the most widely used optimal codons in Pleurotus . Finally, based on the combined mitochondrial sequence and RSCU value, the genetic relationship between different Pleurotus strains was deduced, showing large variations between them. This research has improved our understanding of synonymous codon usage characteristics and evolution of this important fungal group.

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Introduction

Codon bias indicates the non-uniform or biased usage of synonymous codons that encode the same amino acid in a gene or genome [ 1 ]. The genetic information contained in DNA is transferred to the sequence of 20 amino acids through transcription and translation steps [ 2 ]. Among the 64 triplet codon arrangements contained in DNA, 61 triplets can encode 20 standard amino acids, while the other three are translation termination codons. Among the 20 amino acids encoded, 18 amino acids are encoded by multiple different codons, while tryptophan and methionine are encoded by only one codon in most species. The degeneration of the genetic code allows the same amino acid to be encoded by synonymous codons or different codons [ 3 , 4 ]. However, in most cases, the probability of synonymous codons being used is not random or equal. This common phenomenon is called codon usage bias (CUB) [ 5 , 6 , 7 ]. This phenomenon of synonymous codons appearing with different frequencies is often observed in different genes, different organisms, or even the same gene from different species [ 8 , 9 , 10 ]. CUB is mainly caused by mutations in the gene coding region, especially mutations in the second or third nucleotides of the codon in the gene coding region [ 11 , 12 , 13 ]. A synonymy mutation or “silent mutation” will lead to the variability of synonymous codons in organisms during evolution [ 14 , 15 ]. Since some codons are more prone to mutation than others, selection can sustain this bias [ 16 ]. As a result of GC heterogeneity and GC biased gene transformation (gBGC), codon usage bias may also be a result of local recombination rate-based codon usage bias [ 17 , 18 , 19 ]. Consequently, synonymous codons evolve through a combination of mutation, natural selection, and genetic drift of gene translation efficiency, which may play a significant role in genome evolution [ 20 , 21 ]. There is a mutation mechanism that explains the interspecific differences in codon usage by explaining codon bias by the rate or repair of nucleotide bias or point mutations [ 22 , 23 ]. Furthermore, the theory of natural selection assumes that synonymous mutations that affect biological adaptability will be favored or suppressed throughout the evolutionary process, leading to changes in the use of codons in genomes or genes [ 24 , 25 ].

Several cellular processes can be affected by codon bias, including transcription, translation efficiency and accuracy, mRNA stability, protein expression, structure, function, and folding during cotranslation [ 26 , 27 , 28 ]. Codon bias affects transcription by altering chromatin structure and mRNA folding, which then affects translation efficiency by affecting translation elongation rate [ 29 , 30 ]. Therefore, codon bias arises as the result of genome adaptation to transcription and translation mechanisms. The study of molecular evolution of genes benefits from selecting genes that do not change amino acids. The codon bias analysis can reveal evolutionary relationships between closely related organisms because codons are used similarly by closely related organisms [ 31 , 32 ]. Most highly expressed proteins are encoded by genes with the best codons. With the rapid development of high-throughput sequencing technology, codon bias analysis is now essential for understanding species evolution, environmental adaptation, and genetics, etc [ 33 , 34 , 35 ]. In fungal species, particularly in large higher fungi, however, genetic characteristics of codon bias remain unknown [ 36 ].

Pleurotus is one of the largest cultivated edible fungi in the world, which has rich species diversity [ 37 , 38 , 39 , 40 ]. Some species of Pleurotus are delicious edible fungi, which are widely welcomed by consumers [ 37 , 38 , 41 ]. In addition, Pleurotus species also contain a variety of bioactive ingredients, with anti-tumor, antioxidant, anti-inflammatory, anti-virus and other effects [ 42 , 43 , 44 , 45 ]. Mitochondrial genome, known as the second genome of eukaryotes, plays an important role in maintaining the energy supply of eukaryotic cells [ 46 ]. Most fungi have 15 core protein coding genes (PCGs), including atp6 , atp8 , atp9 , cob , cox1 , cox2 , cox3 , nad1 , nad2 , nad3 , nad4 , nad4L , nad5 , nad6 , and rps3 [ 47 , 48 ]. The variation of mitochondrial genome has an important impact on the homeostasis, stress resistance and tolerance, development of eukaryotic cells [ 49 , 50 , 51 ]. Our previous research found that the mitochondrial genomes of different Pleurotus species had undergone large-scale gene rearrangement, indicating that Pleurotus species had undergone significant genetic differentiation [ 52 ]. However, the codon bias, genetic characteristics, and evolution of the mitochondrial core PCGs of Pleurotus within and between species are still unknown.

In this study, we analyzed and compared the usage characteristics of synonymous codons of mitochondrial core PCGs within and between 8 Pleurotus strains, including P. citrinopileatus , P. cornucopiae , P. eryngii , P. giganteus , P. ostreatus P51, P. ostreatus , P. platypus , and P. pulmonarius . We also deduced the phylogenetic relationship of different Pleurotus strains based on relative synonymous codon usage (RSCU) data and compared it with the phylogenetic relationship based on mitochondrial genome sequence inference. This study is the first report to analyze the intraspecific and interspecific synonymous codon usage characteristics of important cultivated edible fungi, which will promote the understanding of the evolution, genetics, and species differentiation of Pleurotus species and other related species.

Materials and methods

Sequence processing.

A total of 8 complete Pleurotus mitochondrial genomes have been published in the National Center for Biotechnology Information (NCBI) database, 2 of which were reported by our previous studies [ 52 ]. The 8 Pleurotus mitochondrial genomes were first downloaded from the NCBI database under the accession numbers NC_036998, NC_038091, NC_033533, NC_062374, OX344747, NC_009905, NC_036999, and NC_061177 [ 53 , 54 , 55 , 56 , 57 ]. We further obtained the core protein coding sequence of the mitochondrial genomes of 8 Pleurotus strains. Those core protein coding genes whose sequence length is less than 300 bp were excluded from subsequent analysis [ 14 ]. Finally, we obtained 12 core protein coding genes in each Pleurotus strains for subsequent analysis, including atp6 , cob , cox1 , cox2 , cox3 , nad1 , nad2 , nad3 , nad4 , nad5 , nad6 , and rps3 .

Codon usage indices

The GC3s parameter is used to measure the amount of codons with guanine and cytosine at the third synonymous position, with the exception of Met, Trp, and termination codons [ 58 ]. The third base of a codon, which is often the least conserved and most variable position. The codon adaptation index (CAI) is a measure of the bias towards codons that are commonly found in highly expressed genes [ 59 ]. CAI reflects the adaptation of a gene’s codon usage to the tRNA pool of the organism, which affects translational efficiency. It is a numerical value ranging from 0 to 1.0, with larger values indicating a greater frequency of synonymous codon usage. The Codon Bias Index (CBI) is a metric for evaluating gene expression, which quantifies the deviation from a random or uniform distribution of codons encoding the same amino acid. The Frequency of Optimal Codons (FOP) is determined by dividing the amount of optimal codons by the total number of synonymous codons in a gene, which provides a direct measure of how often a gene uses the “best” or most efficiently translated codons. The Effective Number of Codons (ENC) is a measure of the number of codons used in a gene, ranging from 20 to 61. A value of 20 indicates that only one codon is used for each amino acid, while 61 indicates that each codon is used on average. A low ENC value (below 35) indicates a strong codon usage preference, while a higher value (above 35) indicates a weak preference. The Relative Synonymous Codon Usage (RSCU) value is calculated by dividing the amino acids encoded by the same codons and their probability of appearing in the same codons, which provides a direct comparison of codon usage across genes or species, accounting for differences in codon composition due to amino acid composition. A value greater than 1 indicates a positive codon bias, while a value less than 1 indicates a negative codon bias. The General Average Hydropathicity (GRAVY) value is determined by summing the hydropathy values of all of the amino acids in the polymerase gene sequences and multiplying them by the number of residues in the gene sequences, which provides insights into the potential membrane-spanning or intracellular localization of a protein. GRAVY values range from − 2 to 2, with positive and negative values representing hydrophobic and hydrophilic proteins, respectively. The Aromaticity (AROMO) value is an indicator of the frequency of aromatic amino acids (Phe, Tyr, and Trp). Aromatic amino acids have a unique chemical structure that confers stability and specific interactions with other molecules. The aromaticity of a protein can affect its structure, function, and interactions with other molecules. GRAVY and AROMO values are also indicators of amino acid usage, and changes in amino acid composition will also affect the results of codon usage analysis. All of these codon usage indicators can be calculated using CodonW1.4.2 [ 60 ] or CAIcal server [ 61 ].

Neutrality plot analysis

The neutrality plot (GC12 vs. GC3) can be used to analyze the balance between mutation and selection when codon bias is formed. GC12 represents the average GC content in the first and second positions of the codon (GC1 and GC2), while GC3 represents the GC content in the third position. Neutral evolution theory assumes that mutations occur randomly and have no effect on the fitness of the organism. However, selection pressure can introduce biases in the observed mutation frequencies, leading to deviations from neutrality [ 62 ]. A strong statistical correlation between GC12 and GC3 indicates that the species is mainly driven by mutation, whereas a lack of correlation implies the main driving force is natural selection.

ENC-GC3s plot analysis

The ENC-GC3s plot (ENC vs. GC3s) is typically employed to assess whether the codon usage of a particular gene is impacted solely by mutation or other factors, such as natural selection. This diagram consists of the ordinate ENC value and abscissa GC3s value, with an expected curve calculated via a specific formula [ 63 ]. If the corresponding points are distributed around the expected curve, mutation pressure is an independent force in the formation of codon bias. However, if the points are significantly lower or distant from the expected curve, some other factors, such as natural selection, likely play a key role in the formation of codon bias.

The ENC Ratio value reflects the variation range between the expected value and the actual value of ENC.

PR2-Bias plot analysis

Additionally, the Parity Rule 2 bias (PR2-Bias) plot analysis based on [A3/(A3 + U3) vs. G3/(G3 + C3)] can be utilized to determine the degree and direction of the gene bias. The center point in the plot is A = T and C = G, meaning the codon has no usage bias.

Correspondence analysis

Correspondence analysis (COA) is a widely accepted multivariate statistical analysis method used to identify codon usage patterns. All genes were placed in a 59-dimensional hyperspace, taking into account the 59 sense codons (Met and Trp excluded). This method can detect the main trends in codon usage in the core CDS of Pleurotus and arrange codons along the axis according to the RSCU value.

Determination of optimal codons

The genes were ordered from highest to lowest expression according to the ENC value, and 10% of the genes from the front and rear ends were selected to form a high- and low-expression gene dataset. The D-value between the RSCU of the two datasets (ΔRSCU) was then calculated, with ΔRSCU values greater than 0.08 being defined as codons with high expression. Codons with RSCU values greater than 1 were considered high-frequency codons. A codon with ΔRSCU > 0.08 and RSCU > 1 was defined as the optimal codon.

Phylogenetic analysis

The phylogenetic relationships of Pleurotus strains were compared between codon usage-based and mitochondrial sequence-based methods. Using the RSCU values of the 8 Pleurotus strains, SPSS v19.0 software was employed to generate a hierarchical clustering method to illustrate the relationship tree between the different species. We employed the method described in our previous studies [ 48 , 64 ] to construct phylogenetic trees of the 8 Pleurotus strains using the combined mitochondrial gene datasets. To do this, individual mitochondrial genes were aligned using MAFFT v7.037 [ 65 ], and then the aligned sequences were combined into a single set using Sequence Matrix v1.7.8 [ 66 ]. Potential phylogenetic conflicts between different mitochondrial genes were identified through a partition homogeneity test. Partition Finder 2.1.1 [ 67 ] was used to determine the most suitable model of partitioning and evolution for the combined mitochondrial gene set. The phylogenetic tree was constructed using the Bayesian inference (BI) method with MrBayes v3.2.6 [ 68 ]. Two independent runs with four chains (three heated and one cold) were conducted for 2 × 10 6 generations, with samples taken every 100 generations. The first 25% of samples were discarded as burn-in, and the remaining trees were used to calculate Bayesian posterior probabilities (BPP) in a 50% majority-rule consensus tree. Ganoderma lingzhi was set as the outgroup [ 69 , 70 ].

Nucleotide composition of Pleurotus core PCGs

The codon usage analysis of 12 mitochondrial core PCGs from 8 Pleurotus strains revealed that the average length of these genes ranged from 370 bp to 2262 bp, with the nad3 gene having the shortest average length and the rps3 gene having the longest. Out of these 12 core PCGs, 10 genes had varying sequence lengths among the different Pleurotus species, while the cox2 and nad6 genes had the same gene length across all 8 strains. The rps3 gene showed the greatest length variation, with a maximum difference of 318 bp. Different Pleurotus species show great differences in base composition, even between the same species ( P. ostreatus ). The base composition of these 12 core PCGs was found to be rich in T base, with an average content of 41.80%, followed by A base, with an average content of 31.70%. The G and C base contents were relatively low, with an average of 13.59% and 12.92%, respectively. The average GC content of core PCGs ranged from 19.36 to 33.57%, with the rps3 gene having the lowest GC content and the cox1 gene having the highest.

Codon usage analysis

The GC1, GC2 and GC3 contents of the 12 core PCGs in the 8 Pleurotus strains were 34.23%, 34.31% and 11.08%, respectively (Fig.  1 ). The average GC3s value of these 12 PCGs was 9.44%, indicating that the mitochondrial core PCGs of Pleurotus tend to end with an A or T base. Additionally, the indices of A3s, T3s, G3s, and C3s of the 12 core PCGs of Pleurotus species showed that the codons were more likely to end with A, followed by T, C and G, with values of 54.80%, 54.65%, 7.53%, and 2.27%, respectively. We conducted an analysis of the codon bias of 12 core PCGs in 8 Pleurotus strains. The CAI values of the core PCGs ranged from 0.12 to 0.20, with nad2 having the lowest value and nad3 having the highest. P. giganteus had the highest CAI value, while P. citrinopileatus and P. pulmonarius had the lowest, indicating that they had a strong codon bias. The CBI values of the 8 Pleurotus strains ranged from − 0.164 to -0.173, with P. giganteus having the lowest value and P. ostreatus having the highest. The average FOP values of the 12 core PCGs ranged from 0.25 to 0.37, with nad1 having the lowest value and nad3 having the highest. P. ostreatus and P. platypus had the lowest FOP value, while P. giganteus had the largest. The GRAVY values of the 12 core PCGs were mostly positive, indicating that they were likely hydrophobic proteins, with the exception of rps3 , which was considered hydrophilic. The AROMO values of the PCGs ranged from 0.08 to 0.17, with rps3 having the highest value and cox3 having the lowest. The AROMO values of the 8 Pleurotus strains were relatively similar, with an average of 0.14. The two P. ostreatus species showed differences in various base bias indicators, among which P. ostreatus P51 had high CBI, FOP, ENC, GC3s and Aromo values, while P. ostreatus had higher CAI and Gravy indicators, indicating that the frequency of base synonymous codon usage also changed within Pleurotus species.

Codon usage indicators of 12 mitochondrial core protein coding genes in different Pleurotus strains

Codon usage correlation analysis

A significant correlation was observed between the GC1 content of mitochondrial codons and GC2, GC3, GC3s, and AROMO values in all eight Pleurotus strains ( P  < 0.05) (Fig.  2 ). Furthermore, a significant correlation was found between the GC2 content and GC content and AROMO values ( P  < 0.05). GC3 content was significantly correlated with GC3s and GC content ( P  < 0.05), and it was also found to affect codon bias in two Pleurotus species ( P. citrinopileatus , and P. giganteus ). GC3s and GC content were significantly correlated in all eight Pleurotus strains ( P  < 0.05). Additionally, the GC content was found to be significantly correlated with the AROMO values in all Pleurotus strains ( P  < 0.01). Furthermore, the CAI index of mitochondrial codons was significantly correlated with the FOP index and CBI index in seven out of eight Pleurotus strains ( P  < 0.05). Lastly, a negative correlation was observed between the ENC value and GRAVY value in P. giganteus ( P  < 0.01).

Pearson’s correlation analysis heatmap of different codon usage indicators of 8 Pleurotus strains. The color of the color block changes from green to red, indicating that the correlation index is increasing. One asterisk indicates a significant correlation between the two indicators at the P  < 0.05 level, while two asterisks indicate a significant correlation between the two indicators at the P  < 0.01 level. The 8 Pleurotus species are P. citrinopileatus , P. cornucopiae , P. eryngii , P. giganteus , P. ostreatus P51, P. ostreatus , P. platypus , and P. pulmonarius , from left to right and from top to bottom

We calculated the relationships between GC12 and GC3 based on neutrality plot analysis (Fig.  3 ). The GC12 content varied from 23.29 to 41.25%, and the GC3 content varied from 6.37 to 20.53%. The analysis between GC12 and GC3 content in mitochondrial codons of Pleurotus revealed a weak positive correlation, with the regression coefficient ranging from 0.55 to 0.95 and the R 2 value ranging from 0.2219 to 0.4458. Statistical analysis showed that there was no significant correlation between GC12 and GC3 values ( P  > 0.05), indicating that natural selection played a major role in codon bias of Pleurotus .

Neutrality plot analysis of GC12 and the third codon position (GC3) for the entire coding DNA sequence of 8 Pleurotus strains. a, P. citrinopileatus ; b, P. cornucopiae ; c, P. eryngii ; d, P. giganteus ; e, P. ostreatus P51; f, P. ostreatus ; g, P. platypus ; h, P. pulmonarius

The average ENC value of all 12 core PCGs detected was found to be 29.86, which is lower than 35, indicating a strong codon usage preference (Fig.  1 ). Moreover, the ENC values of 8 Pleurotus strains ranged from 29.58 to 30.74, further confirming the strong codon usage preference of Pleurotus species. The ENC plot showed that all Pleurotus genes were below the expected ENC-plot curve (Fig.  4 ), indicating that factors other than mutation pressure, such as natural selection, play a role in codon bias formation.

Additionally, the ENC Ratio values for all core PCGs ranged from 18.59 to 20.55%, indicating that the expected values were greater than the actual values (Fig. S1 ). This demonstrates that GC3s have an important influence on the formation of codon bias. In conclusion, it can be inferred that natural selection is a major factor determining the formation of Pleurotus codon bias.

ENC-GC3 plot analysis of 12 core PCGs in 8 Pleurotus strains. The solid line represents the expected curve when codon usage bias is affected only by mutation pressure. a, P. citrinopileatus ; b, P. cornucopiae ; c, P. eryngii ; d, P. giganteus ; e, P. ostreatus P51; f, P. ostreatus ; g, P. platypus ; h, P. pulmonarius

We conducted a Parity Rule 2 (PR2) plot analysis to investigate whether Pleurotus mitochondrial genes have any biases (Fig.  5 ). Both axes were centered on 0.5 to divide the plot into four quadrants. The results showed that the third base of the mitochondrial codon of Pleurotus had a strong preference for T over A and C over G. Most of the dots were found to be distributed in the third quadrant, while six out of the eight strains were not distributed in the fourth quadrant (preferring A to T and C to G), with P. citrinopileatus and P. giganteus being the exception. All the 8 Pleurotus strains were not distributed in the first quadrant (preferring A to T and G to C). This suggests that strong codon usage preference exist in Pleurotus species.

Parity Rule 2 (PR2) plot analysis of 12 core PCGs in 8 Pleurotus strains. a, P. citrinopileatus ; b, P. cornucopiae ; c, P. eryngii ; d, P. giganteus ; e, P. ostreatus P51; f, P. ostreatus ; g, P. platypus ; h, P. pulmonarius

To further analyze codon biases in Pleurotus , we conducted a correspondence analysis (COA) based on the RSCU values of mitochondrial genes from the 8 Pleurotus strains (Fig.  6 ). Axis 1, Axis 2, Axis 3 and Axis 4 are the main contributors to variance, with average contribution rates of 45.61%, 15.62%, 8.24% and 6.30%, respectively. The results showed that Axis 1 was the largest contributor to variance. Pearson correlation analysis showed that Axis 1 had significant correlation with CAI and ENC values. Additionally, we observed large variation in the rps3 gene and other core PCGs, indicating the differentiation of synonymous codon usage of core PCGs.

Correspondence analysis (COA) based on the relative synonymous codon usage (RSCU) values of 12 mitochondrial genes from 8 Pleurotus strains. Purple represents the cox gene, red represents the nad gene, green represents the atp6 gene, blue represents the cob gene, and yellow represents the rps3 gene. a, P. citrinopileatus ; b, P. cornucopiae ; c, P. eryngii ; d, P. giganteus ; e, P. ostreatus P51; f, P. ostreatus ; g, P. platypus ; h, P. pulmonarius

Optimal codon analysis

Analysis of the Relative Synonymous Codon Usage (RSCU) of eight Pleurotus strains revealed 27 high-frequency codons in six species ( P. citrinopileatus , P. cornucopiae , P. eryngii , P. ostreatus P51, P. platypus and P. pulmonarius ), with P. giganteus containing 26 and P. ostreatus containing 28 (Fig.  7 ). AUA was found to be used at a low frequency in P. citrinopileatus and P. giganteus , but used at a high frequency in other Pleurotus species. Of the 28 frequently used codons, 15 ended in T, 11 in A, and only 2 in G, indicating a preference for codons ending in A/T. In addition, 22, 15, 23, 30, 19, 28, 28, and 20 highly expressed codons (ΔRSCU > 0.08) were identified in the 8 Pleurotus strains, including P. citrinopileatus , P. cornucopiae , P. eryngii , P. giganteus , P. ostreatus P51, P. ostreatus P. platypus , and P. pulmonarius , respectively (Fig.  8 ). Comparative analysis revealed that 6, 6, 7, 7, 10, 9, 8, and 6 optimal codons (ΔRSCU > 0.08 and RSCU > 1) were found in P. citrinopileatus , P. cornucopiae , P. eryngii , P. giganteus , P. ostreatus P51, P. ostreatus P. platypus , and P. pulmonarius , respectively. All of these optimal codons ended with A/T, with UGU and ACU being the most widely used, followed by GGA, AUU, and UUU, which were used as the optimal codons of five strains. GCA, GCU, AAU, UCU, UAA, and ACA were each used as the optimal codons of one species. Furthermore, P. ostreatus P51 and P. ostreatus showed great differences in the use of optimal codons. AAU, GGU, AUA, UUA, UAA, and GUA were used as the optimal codons in P. ostreatus P51, while GCA, GGA, AUU, CCU, and GUU were used as the optimal codons in P. ostreatus .

Relative synonymous codon usage (RSCU) analysis of 12 mitochondrial genes from 8 Pleurotus strains. The color blocks with different colors on the bottom vertical axis represent different codons in the image above. a, P. citrinopileatus ; b, P. cornucopiae ; c, P. eryngii ; d, P. giganteus ; e, P. ostreatus P51; f, P. ostreatus ; g, P. platypus ; h, P. pulmonarius

Optimal codons of 8 Pleurotus strains (ΔRSCU > 0.08 and RSCU > 1), which are marked in purple. Highly expressed codons (ΔRSCU > 0.08) were marked in yellow and high-frequency codons (RSCU > 1) were marked in green

The Bayesian inference (BI) method was employed to construct phylogenetic trees of 8 Pleurotus strains based on the combined mitochondrial gene set (Fig.  9 ). The results demonstrated that P. giganteus and P. citrinopileatus had diverged from the Pleurotus population earlier. P. cornucopiae was identified as the sister species of P. platypus . Furthermore, two P. ostreatus strains were grouped in the same evolutionary clade, which indicated their close phylogenetic relationship. In contrast to the phylogenetic relationship inferred from sequences, the species relationship inferred from RSCU had some discrepancies, such as the phylogenetic status of P. ostreatus , P. eryngii , and P. pulmonarius . Nevertheless, the RSCU-based species relationship also clearly revealed the close relationship between P. platypus and P. cornucopiae , as well as the early divergence of P. giganteus and P. citrinopileatus from the Pleurotus population.

Relationship inference of different Pleurotus strains based on the Bayesian inference (BI) ( a ) method and relative synonymous codon usage (RSCU) hierarchical clustering ( b )

The development of sequencing technology has enabled researchers to gain access to the genetic sequences of various species and types of genomes, including the nuclear genome, chloroplast genome and mitochondrial genome [ 71 , 72 , 73 ]. Through the analysis of genetic information, it has been observed that the usage of synonymous codons varies among different species, with some codons being used more frequently than others [ 74 ]. This codon usage bias is mainly affected by several factors, such as gene base composition, gene length, gene expression level, tRNA abundance, amino acid hydrophobicity, aromaticity, mutation, and selection, with mutation and selection being the most influential [ 75 , 76 ]. Examining the codon bias characteristics of different species can help to understand the genetic structure and evolution trend of species [ 77 , 78 ]. However, the codon usage of important organelle genomes of higher fungi has not been thoroughly studied.

The mitochondrial genome is often referred to as the ‘second genome’ of eukaryotes. In this study, it was found that the length and base composition of mitochondrial core PCGs of different Pleurotus strains varied significantly, even within the same Pleurotus species, indicating the differentiation of Pleurotus mitochondrial genes. The differences in synonymous codons were mainly reflected in the third codon. Additionally, it was observed that all core PCGs of Pleurotus species tend to end with A/T, which is in line with the rule of mitochondrial codon usage in many eukaryotes [ 79 , 80 ]. The majority of high-frequency codons parsed by RSCU also end with A/T, further confirming the tendency of using the third codon of Pleurotus . Moreover, variations in base usage were observed among different species and genes. The two P. ostreatus species also showed differences in various base bias indicators, including CAI, CBI, FOP, ENC, and GC3s values, indicating that the frequency of base synonymous codon usage also changed in the within Pleurotus species. Furthermore, correlations were detected between codon base composition and GC3s, CAI, CBI, and FOP, suggesting the influence of base composition on codon bias. An ENC value lower than 35 indicates a strong codon preference [ 81 , 82 ]. The average ENC value of the mitochondrial core PCGs of Pleurotus was found to be 29.86, which indicates strong codon preference. Furthermore, the expected and actual ENC values showed significant differences (18.59-20.55%). Neutrality plot analysis and PR2-Bias plot analysis also showed evidence of natural selection in Pleurotus codon bias. This is consistent with the results seen in the mitochondrial genomes of other species [ 83 , 84 , 85 ]. The findings of this study revealed that, despite some discrepancies in codon usage indicators between different Pleurotus species, they all experienced strong natural selection on their mitochondrial PCGs.

Mitochondria are believed to have been obtained from bacteria by the ancestors of eukaryotes [ 86 ], and most mitochondrial genes have since been transferred to the nuclear genome [ 87 ]. While most eukaryotes still retain some core PCGs, some tRNA genes and rRNA genes for energy metabolism [ 88 , 89 ], which can be used as a molecular marker for phylogeny. As such, the mitochondrial genome is considered a useful tool for inferring phylogenetic relationships of species [ 90 , 91 , 92 ]. In this study, the genetic relationship of different Pleurotus species was analyzed based on a combined mitochondrial gene set and high support rates were found for each evolutionary clade. Additionally, the relationship between different Pleurotus species was determined based on their RSCU values, which differed from the sequence-based relationships. The phylogenetic tree constructed with RSCU values can serve as a supplement and reference for constructing mitochondrial gene phylogenetic trees, which agreed with previous research [ 93 , 94 ]. Codon bias, the non-uniform usage of synonymous codons, plays a role in species biodiversity, physiology, morphology, and nutrition of fungi. It can contribute to species-specific genetic signatures, influence translational efficiency and protein expression levels, potentially affect protein structure and function related to morphology, and influence the ability of a species to utilize different nutrients. However, the precise mechanisms and causal relationships between codon bias and these biological characteristics remain incompletely understood [ 95 , 96 ]. Consequently, this research enhanced the comprehension of codon usage characteristics and genetic evolution of this higher fungal group.

Data availability

All data generated or analyzed during this study are included in this published article [and its supplementary information files].

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This work was supported by National Natural Science Foundation of China (No. 82102738).

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Q.L and W.G designed the experiment; X.C., J.H., A.S., Y.L., W.X., and Z.X. analyzed the data; Q.L and W.G wrote and review the manuscript; Q.L. managed the project. All authors reviewed the manuscript.

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Gao, W., Chen, X., He, J. et al. Intraspecific and interspecific variations in the synonymous codon usage in mitochondrial genomes of 8 pleurotus strains. BMC Genomics 25 , 456 (2024). https://doi.org/10.1186/s12864-024-10374-3

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Environmental specificity of karst cave habitats evidenced by diverse symbiotic bacteria in Opiliones

• Likun Zhao 1 , 2   na1 ,
• Ruoyi Xiao 1   na1 ,
• Shanfeng Zhang 1 ,
• Chao Zhang 1 , 3 &
• Feng Zhang 1 , 3  

BMC Ecology and Evolution volume  24 , Article number:  58 ( 2024 ) Cite this article

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Metrics details

Karst caves serve as natural laboratories, providing organisms with extreme and constant conditions that promote isolation, resulting in a genetic relationship and living environment that is significantly different from those outside the cave. However, research on cave creatures, especially Opiliones, remains scarce, with most studies focused on water, soil, and cave sediments.

The structure of symbiotic bacteria in different caves were compared, revealing significant differences. Based on the alpha and beta diversity, symbiotic bacteria abundance and diversity in the cave were similar, but the structure of symbiotic bacteria differed inside and outside the cave. Microorganisms in the cave play an important role in material cycling and energy flow, particularly in the nitrogen cycle. Although microbial diversity varies inside and outside the cave, Opiliones in Beijing caves and Hainan Island exhibited a strong similarity, indicating that the two environments share commonalities.

Conclusions

The karst cave environment possesses high microbial diversity and there are noticeable differences among different caves. Different habitats lead to significant differences in the symbiotic bacteria in Opiliones inside and outside the cave, and cave microorganisms have made efforts to adapt to extreme environments. The similarity in symbiotic bacteria community structure suggests a potential similarity in host environments, providing an explanation for the appearance of Sinonychia martensi in caves in the north.

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Introduction

Symbiotic bacteria play an important role in the life activities of many organisms, including insects and animals [ 1 ]. These bacteria reside in the host’s intestinal tract, epidermis and various organs, and jointly regulate each other’s life activities. The number of symbiotic bacteria even far exceeds the number of cells of the organism itself, and the diversity and the functions of symbiotic bacteria are vast, ranging from digestion and absorption [ 2 , 3 , 4 ] to detoxification, metabolism [ 5 , 6 ], controlling the growth and reproduction of the host [ 7 , 8 ], and adaptation to the environment [ 9 , 10 , 11 ].

Karst caves are a unique environment characterized by low air mobility, long-term darkness, high humidity, malnutrition, and isolation from the external environment. Researchers have studied microbial communities in small habitats such as cave rock walls [ 12 ], sediments [ 13 ], water and air [ 14 ]. The dominant phyla in these communities were Proteobacteria, Actinobacteria, and Firmicutes, although their relative abundance varied greatly among different caves [ 14 ]. Cave-dwelling organisms are also isolated from the outside world for a long time, which leads to the development of unique structures and habits. As a result, the cave-dwelling creatures differ from their counterparts outside the cave, both in their living environment and genetic relationships [ 15 , 16 ]. In recent years, there have been a few studies on cave symbiotic bacteria. One study compared the symbiotic bacteria of Oculina patagonica obtained from bleached, cave and healthy corals and found a significant change in bacterial population in the absence of light [ 17 ]. Another study investigated cave calcium bodies in terrestrial isopod crustaceans Titanethes albus and Hyloniscus riparius [ 18 ].

Most studies on symbiotic bacteria of arachnids focus on the effects of endosymbiont on spiders [ 19 , 20 ], mites [ 21 ], pseudoscorpions [ 22 , 23 ] and other arachnids. However, relatively few studies have examined the entire bacterial community. One study of Marpiss magister found that endosymbionts are not the only microflora in spiders, and there are other bacterial groups in their bacterial communities [ 24 ]. Opiliones (harvestmen, shepherd spiders, daddy longlegs, etc.) are one of the most abundant and the oldest Arachnida. They are often widely distributed in ecosystems, independent Cardinium groups have been found in them. Some scholars use Opiliones as a control while studying Wolbachia and Cardinium infection of Araneae [ 25 , 26 , 27 , 28 ]. So far, studies on the symbiotic bacteria of Opiliones have mainly focused on single endosymbiont. To the best of our knowledge, no reports have been found on Opiliones-related bacteria based on different habitats and their effects on the growth, evolution and reproduction of the host. Opiliones have become an ideal subject for studying biological habitats due to their limited activity and narrow distribution areas [ 29 , 30 ].

In this study, high-throughput technology (16S ribosomal RNA [rRNA] gene sequencing method) was used to analyze the relative abundance and diversity of symbiotic bacteria in different habitats of Opiliones and other arachnids, provide a basis for revealing the special material cycle in the cave environment, especially the nitrogen cycle. A variety of symbiotic bacteria have reproductive regulation and even co-evolution on the host. The comparison of symbiotic bacteria in Opiliones from different karst caves and habitats provided insights into the role of bacteria in the development and evolution of Opiliones and their distribution of the host.

Materials and methods

Sample collection.

During the period from October 2021 to July 2022, five species of Opiliones were collected in Beijing and Hainan Island: Sinonychia martensi (Arachnida: Opiliones: Laniatores), Euepedanus flavimaculatus (Arachnida: Opiliones: Laniatores), Plistobunus columnarius (Arachnida: Opiliones: Laniatores), Himalphalangium palpalis (Arachnida: Opiliones: Eupnoi), Homolophus serrulatus (Arachnida: Opiliones: Eupnoi). Additionally, other Arachnida, including Pimoa clavata (Arachnida: Araneae), Spelaeochthonius sp. (Arachnida: Pseudoscorpionida) and Draconarius sp. (Arachnida: Araneae) were collected from various sections of Siyu Cave in Fangshan District (Fig.  1 ; Table  1 ). All samples were identified using traditional morphological classification (Fig.  2 ) and preserved in 95% ethanol.

Sampling sites in Beijing and Hainan Island. The location number corresponds to the first letters of the sample number

Photographs of some Opiliones. ( A, B ) Sinonychia martensi , Laniatores; ( C, D ) Homolophus serrulatus , Eupnoi; ( E, F ) Euepedanus flavimaculatus , Laniatores. ( A, C, E ) dorsal view, ( B, D, F ) ventral view

Sample processing and DNA extraction

The collected samples were thoroughly rinsed with sterile water 2–3 times, followed by sequential sterilization using 75% ethanol and hypochlorite, and finally washed again with sterile water. The processed samples were then stored at a temperature of -80℃ until DNA extraction. The extracted DNA was quantified using Nanodrop, and the quality of the extracted DNA was verified by running it through 1.2% agarose gel electrophoresis. The obtained DNA was stored at -20℃ for future use.

Amplicon and library preparation

The 16S rRNA gene library construction and sequencing were performed by Personalbio Technology Company (Shanghai, China). The V3-V4 regions of the 16S rRNA gene were amplified using the primer pair 338 F/806R (5′-ACTCCTACGGGAGGCAGCA-3′ and 5′-GGACTACHVGGGTWTCTAAT-3′). PCR products were quantified using the PicoGreen dsDNA Assay Kit (Invitrogen, Carlsbad, USA), and samples were mixed according to the corresponding proportion based on the fluorescence quantitative results. The sequencing library was prepared using the TruSeq Nano DNA LT Library Prep Kit of the Illumina platform (Illumina, USA), and before sequencing, the library was checked. The qualified sequencing libraries were diluted, mixed, and denatured for computer sequencing.

Data processing and analysis

The original sequences were quality screened and divided into libraries and samples according to index and Barcode information, and the barcode sequences were removed. The primer fragments were removed using qiime cutadapt trim-paired sequence, and unmatched primers were discarded. The qiime dada2 denoise-paired was used for quality control, denoising, splicing and de-chimerism. After denoising, all libraries, the ASVs feature sequence and the ASV table were merged, and singletons ASVs (ASV with a total sequence of only 1 in all samples) were removed [ 31 , 32 ]. Annotation information was obtained using different algorithms and parameters in different databases, including the Silva database ( http://www.arb-silva.de ), nt database (http://ftp://ftp.ncbi.nih.gov/blast/db/), nr database (http://ftp://ftp.ncbi.nih.gov/blast/db/), based on the feature sequence of ASVs [ 33 ].

The composition and relative abundance of bacterial groups in each sample at different taxonomic levels were obtained by QIIME2 software (2019.4) [ 34 ]. The richness and diversity of bacteria in different samples were analyzed using alpha diversity indices (including Chao1 richness estimator, Observed_species, Shannon diversity index, and Simpson index) [ 35 ]. Beta diversity analysis was performed to analyze differences in bacterial community composition structure among different samples, and beta diversity was evaluated by PCoA and Non-metric multidimensional scaling (NMDS) based on the weighted Bray-Curtis distance algorithm [ 35 , 36 ]. According to the abundance data of ASVs in all samples, the Wenn diagram was made according to the grouping of samples and calculating the relationship between each set. Indicator groups in different habitats were obtained by the LEfSe (the least discriminant analysis effect size) method with the LDA (linear discriminant analysis) threshold set to 4.0 [ 37 ]. The similarity between samples was shown in the form of hierarchical tree, and the clustering effect was measured by the branch length of the clustering tree. The heat map was used to analyze the species composition and displayed the species abundance distribution trend of each sample.

PICRUSt2 (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) was utilized to predict the functional abundance of samples based on the sequence abundance of marker genes in these samples [ 38 ]. FAPROTAX (Functional Annotation of Prokaryotic Taxa) is a functional annotation database specifically designed for prokaryotic taxa, enabling the functional prediction of bacterial communities [ 39 ]. It can be employed to evaluate bacterial metabolism and other ecologically related functions in cave environments, particularly focusing on the cycling function of sulfur, carbon, hydrogen and nitrogen.

Diversity of the bacteria in Opiliones among different karst caves

A study was conducted to investigate the diversity of bacteria in Sinonychia martensi , a species of harvestmen found in karst caves in Beijing. The results revealed significant differences in community structure and relative abundance of bacteria among different caves. In S. martensi inhabiting caves, the dominant phylum was Proteobacteria, with a much higher relative abundance compared to other bacteria. Proteobacteria accounted for an extremely high relative abundance of 98.06% in the samples from the You Cave (YOM) (Fig.  3 a, Table S1 ). The relative abundance of Firmicutes in the Siyu Cave was 21.90%, second only to Proteobacteria, compared to the Bianfu Cave and You Cave. The three most abundance phyla accounted for more than 93% of the total microflora of S. martensi from the Bianfu Cave (BOM): Proteobacteria (48.10%), Bacteroidetes (29.01%), Actinobacteria (16.22%). At the genus level, Pseudomonas was the dominant bacteria in S. martensi from the You Cave (YOM), with a relative abundance as high as 95.17% (Fig.  3 b, Table S1 ). The relative abundance of Chryseobacterium and Delftia in the samples from the Bianfu Cave (BOM) was 27.00% and 18.37%, respectively.

Relative abundance of S. martensi in Siyu, Bianfu and You Cave. ( A ) The relative abundance of phylum level in S. martensi . It shows the top 15. ( B ) Relative abundance of genus level in S. martensi . It shows the top 30. The relative abundance of other species merged and classified as Others

The alpha diversity of bacteria in different caves was assessed by Chao 1, Observed_species, Shannon and Simpson indices (Fig.  4 a). A Kruskal–Wallis test revealed a significant difference in alpha diversities among the caves ( P  ≤ 0.05). According to the Dunn’s post hoc test, the diversity and richness of S. martensi from the Siyu Cave (SOM) were significantly higher than those from You Cave (YOM) ( P  < 0.05). The beta diversity was evaluated by principal coordinate analysis (PCoA) based on the weighted Bray-Curtisdistance algorithm, showing that Opiliones samples were loosely clustered (Fig.  4 b). In the first dimension, the community composition of the Opiliones samples from Siyu Cave (SOM) was similar to that of the Bianfu Cave (BOM). It was more similar for symbiotic bacteria from You Cave (YOM) and Bianfu Cave (BOM) in the second dimension. These findings suggest that caves, as unique and enclosed habitats, harbor distinct symbiotic bacteria across different caves

Comparison of microbial diversity in different cave samples. ( A ) Alpha-diversity analysis of S. martensi microbiome. Species richness and diversity were measured by Shannon, Simpson, Chao1 and Observed_species. Each panel corresponds to an alpha-diversity index, which is identified in the gray area at its top. In each panel, the abscissa is the grouping label, and the ordinate is the value of the corresponding alpha diversity index. The number under the diversity index label is the P value of the Kruskal-Wallis test. ( B ) Principal coordinate analysis (PCoA) of microbiome based on Bray-Curtis distances

Caves represent unique habitats with distinct energy flows and material circulations compared to the outside environment, and each creature has adapted unique behaviors to survive. To understand the function of bacteria in different caves, PICRUSt2 software [ 18 ] was used to predict and analyze the symbionts. The KEGG (Kyoto Encyclopedia of Genes and Genomes) database was used to identify six functional modules, including cellular processes, environmental information processing, genetic information processing, human diseases, metabolism, and organismal systems. The metabolism module was found to be the most abundant functional module in all samples (Fig.  5 a), which might include the glycolysis pathway, pentose phosphate pathway, nitrogen metabolism, sulfur metabolism, methane metabolism and multiple carbon sequestration pathways (Fig.  5 b). The relative abundance of pathways was in different caves and samples. The COG (clusters of orthologs groups) database was used to predict key enzymes in multiple reaction pathways (Table S2 ), including Hexokinase [EC:2.7.1.1], glyceraldehyde 3-phosphate dehydrogenase [EC:1.2.1.12] and pyruvate kinase [EC:2.7.1.40] involved in the glycolysis pathway. Glucose-6-phosphate isomerase [EC:5.3.1.9] is involved in the pentose phosphate pathway. Nitrite reductase [EC1.7.2.1] catalyzes the reduction of nitrite (NIT), a crucial enzyme in the nitrogen cycle in nature. Chemoheterotrophy and aerobic chemoheterotrophy were found to be the most abundant functions based on the predictions made by FAPROTAX analyses (Fig.  6 a). Among the top 20 predicted functions, nine were related to the nitrogen cycle, including nitrate reduction, nitrogen respiration, nitrate respiration, ureolysis, nitrification, nitrite respiration, nitrate denitrification, nitrite denitrification and nitrous oxide denitrification. Specifically, the SOM samples showed high abundance in the functions related to the nitrogen cycle and the BOM samples were positively correlated with the degradation function of organic compounds (Fig.  6 b). These findings indicate that different caves employ different strategies in the nutrient cycle

Predicted bacterial function in cave samples using PICRUSt2. ( A ) Predicted function of bacteria among the five samples. The first level of the KEGG pathway was represented by different colors. ( B ) The second level of the KEGG pathway was shown in the heatmap. It included only carbohydrate metabolism and energy metabolism pathways

Predicted bacterial function in cave samples using FAPROTAX. It showed the top 20 functions predicted. ( A ) Abundance of the main metabolisms in the whole set of cave samples. ( B ) Heatmap of the FAPROTAX analysis revealed the differences among samples

Differences in the symbiotic bacteria between Opiliones inside and outside the cave

The sequencing results of Himalphalangium palpalis and Homolophus serrulatus outside the caves and S. martensi inside the cave revealed differences in the bacteria structure of symbiotic bacteria inside and outside the cave were different. LEfSe analysis was performed to compare bacterial communities to find the specialized bacterial groups within each type of the sample (Fig.  7 a). The cladogram showed that 2 phyla, 3 classes, 12 orders, 17 families, and 20 genera were significantly variable across the five samples. When the LDA value was set to 4, the number of differentially abundant bacterial groups in the five samples were 11 (BOM), 8 (JOS),18 (SOM), 5 (TOP), 8 (TOS)and 4 (YOM), respectively (Fig.  7 b). At the phylum level, Proteobacteria was the main dominant group in cave Opiliones, accounting for 98.06%, 48.10% and 45.80% in the three caves, respectively (Fig.  8 a, Table S3 ). In contrast, Actinobacteria and Proteobacteria were differentially distributed in samples outside the cave, with Actinobacteria having the highest relative abundance in Homolophus serrulatus (TOS and JOS), and Proteobacteria being dominant in Himalphalangium palpalis (TOP). The NMDS plots based on Bray-Curtis distances clearly distinguished the Opiliones inside the cave from those outside the cave (Fig.  8 b).

Results of LEfSe analysis. ( A ) Cladograms indicating the phylogenetic distribution of bacterial lineages associated with Opiliones inside and outside the cave. ( B ) Indicator bacterial group significantly differentiated across the three sample types with LDA values was 4

Diversity of symbiotic bacteria from Opiliones inside and outside caves in Beijing. ( A ) Relative abundance of Opiliones inside and outside caves. It showed the top 15 phyla and the relative abundance of other species merged and classified as Others. ( B ) Non-metric multidimensional scaling (NMDS) plots of microbiome difference at ASV level based on Bray-Curtis distances. The stress was 0.0797

Effect of cave environment on symbiotic bacteria of Arachnida

A study was conducted to investigate the effect of the cave environment on the symbiotic bacteria of three different Arachnida species: S. martensi (Opiliones), P. clavata (Araneae) and Spelaeochthonius sp. (Pseudoscorpionida) inside the Siyu Cave. The results showed that the bacteria structure in the samples was similar. Proteobacteria, Firmicutes, Bacteroidetes and Actinobacteria were consistently prevalent phyla among all species inside the cave, accounting for a comparable proportion (Figure S1 a, Table S4 ). Draconarius sp. (Arachnida: Araneae) collected outside the cave differs from that inside. The relative abundance of Proteobacteria in the SAS was 85.10%, which was significantly higher than that inside the cave. At the genus level, the relative abundance of Wolbachia and Rickettsia in SAS was 49.52% and 23.82% respectively, whereas other bacteria were less than 1.5% (Figure S1 b, Table S4 ). The diversity and richness of the symbiotic bacteria inside the cave were higher than those outside the cave (Figure S1 c). The Venn diagram revealed that there were differences in ASVs among the four samples. A total of 465 ASVs were shared among all four samples and the cave samples shared 237 ASVs. The number of ASVs unique to spiders outside the Siyu Cave (SAS) was 2628 (Fig.  9 a). The members of SAS were loosely clustered, which was confirmed in the hierarchical clustering diagram based on Bray-Curtis distance level and histograms of species composition (Fig.  9 b).

Comparative microbial diversity of Arachnida in Siyu Cave using bate-diversity analysis. ( A ) Venn diagram of Siyu Cave samples. ( B ) Hierarchical clustering analysis of the similarity between samples of Siyu Cave. The hierarchical clustering analysis was utilized to demonstrate the similarity between the samples, represented by a hierarchical tree in the left panel. The samples were clustered based on their similarity, with shorter branch lengths indicating greater similarity. The right panel shows the top 10 phyla in a stacked histogram

Some similarities in environment between karst caves and Hainan Island

We conducted a comparison of symbiotic diversity between Opiliones from Hainan Island and those inside Beijing caves. To reflect their similarity, we utilized Opiliones outside the Beijing caves as a control group. At the phylum level, Proteobacteria was the dominant bacteria across all samples, with relative abundances of 98.06%, 92.36% and 78.18% in YOM, HOF and TOP, respectively (Figure S2 a, Table S5 ). However, Actinobacteria was the main dominant bacteria in JOS and TOS, with lower levels in other classifications. Firmicutes emerged as the secondary dominant bacteria in HOF, WOC and SOM, with the relative abundance of 6.31%, 20.17%, and 21.90% respectively.

The taxonomic alpha-diversities measured by Simpson indicated significant differences in the diversity of symbiotic bacteria among different groups ( P  < 0.05). Furthermore, Shannon, Chao1 and Observed_species indicated significant differences in diversity and richness ( P  ≤ 0.01). Notably, Chao1 and Observed_species indicated differences between HOF and SOM, and significant diversity differences were observed between YOM and TOS (Figure S2 b).

The population structure and alpha-diversity analyses revealed similarities between Opiliones from Hainan Island and those inhabiting the Beijing cave. Therefore, beta analysis methods, indicated distinct symbiont structures among Opiliones living in different regions, with symbiotic bacteria in Opiliones from Hainan Island and the Beijing caves showing greater similarities. Cluster analysis based on the Bray-Curtis distance level grouped BOM and WOC together (Fig.  10 a). Similarly, JOS, TOP and TOS were clustered into a group, except that TOP3 was independent of them. Additionally, WOC, BOM, HOF, YOM and SOM clustered together in the heat map of UPGMA clustering based on the Euclidean distance of species composition data (Fig.  10 b). Specifically, WOC and BOM were positively correlated with Bacillus , Rodentibacter , Ralstonia and Chryseobacterium , Delftia respectively, and clustered together. Pseudomonas , which belonged to YOM, also clustered with the aforementioned groups. The results confirmed that the symbiotic bacteria of Opiliones from Hainan Island and Beijing caves were more similar than those outside the cave.

Comparative microbial diversity of Opiliones in Beijing caves and Hainan using bate-diversity analysis. ( A ) Hierarchical clustering analysis of the similarity between samples in the form of the hierarchical tree. ( B ) Heatmap of the microbial composition and relative abundance of Opiliones

Karst caves are unique habitats that are characterized by specific environmental conditions, such as almost constant temperature and humidity, permanent darkness and limited energy and nutrient sources [ 40 ]. These conditions exert a profound influence on the diversity and composition of cave ecosystems [ 41 ]. In addition, caves are mostly located in remote areas and are less disturbed by human activities, which makes them ideal locations for studying the underground biosphere. However, the cave environment is limited by many factors, such as restricted access to nutrition, low temperatures, unique air pressure conditions, connectivity with groundwater, variations in light and humidity, limited surface interaction, anthropogenic or animal influences and geological mineral compositions [ 42 , 43 , 44 ]. So each cave is unique in its biological, chemical and physical characteristics, and these factors cause differences within and between caves [ 45 ]. These disparities elucidate the variations in symbiotic diversity observed among Opiliones inhabiting different caves and those residing outside cave systems in this study.

Karst caves are relatively closed environments, there are obvious differences among different caves. The cave habitat serves as a critical factor influencing the survival and community structure of microorganisms, with these organisms occupying diverse niches in space and time. It is worth noting that each cave has a unique microbial community, which emphasizes the important role of the cave niche in shaping microbial diversity [ 46 ]. Moreover, the cave environment exerts a strong impact on the organisms inhabiting the cave, with up to five distinct zones identified in caves, including the entrance, twilight, transition, deep, and stagnant air zones, each harboring a distinct biological community. The transition zone, characterized by complete darkness and variable abiotic environment [ 16 ], and the deep zone, completely dark with high humidity and constant temperature, are of particular interest. S. martensi (Fig.  2 a, b) observed in this study is found, which is adapted to the completely lightless deep zone of the cave, displays body coloration varying from yellowish white to pale yellow, greatly reduced ocular size, and complete absence of eyes and retinae, indicating long-term adaptation to the cave environment [ 47 ]. Although the Opiliones from Siyu Cave, Bianfu Cave and You Cave share the same appearance and molecule, their different environments lead to distinct symbiotic bacteria structures (Fig.  3 a, b). Furthermore, significant differences were observed in symbiotic diversity among Opiliones from the three caves (Fig.  4 a, b).

The unique environment of karst caves, characterized by darkness and nutrient limitation, results in distinct energy flow and material circulation compared to the external environment. Predictive functional analysis using PICRUSt2 revealed that despite variations among different cave environments, symbiotic bacteria in Opiliones from three caves exhibit similar functions, focusing on metabolic activities such as the synthesis and metabolism of various organic compounds (Fig.  5 a). Symbiotic bacteria rely on the host for various life activities, including even simple metabolic functions. The results suggest that S. martensi and its symbiotic bacteria play direct or indirect roles in the material cycle within the cave, particularly in the carbon cycle, which involves crucial metabolic processes like carbon fixation, methane metabolism, and carbon degradation. Annotation by KEGG and COG databases indicated that most symbiotic bacteria in Opiliones participate in diverse carbon fixation pathways, such as the glycolysis pathway, tricarboxylic acid cycle, and pentose phosphate pathway, facilitated by relevant enzymes (Fig.  5 b, Table S2 ). Additionally, Opiliones are omnivores, with their diet primarily comprising invertebrates in caves, along with plants and fungi [ 48 , 49 ]. Following the ingestion of animal and plant residues and other organic matter into the Opiliones’ intestinal tract, enzymatic decomposition within the digestive tract, coupled with interactions with intestinal symbiotic bacteria, facilitates the return of organic matter to the cave environment in the form of feces. This process enhances the utilization of other plants and microorganisms within the cave ecosystem.

Nitrogen is a vital element in organisms, playing a crucial role in many biochemical cycles within cave ecosystems. The symbiotic relationship between S. martensi and its associated bacteria contributes significantly to the nitrogen cycle within caves. Firstly, they actively participate in biological nitrogen fixation, a process where nitrogen-fixing bacteria convert atmospheric nitrogen into biologically available ammonia. The prevalence of Proteobacteria in the samples suggests their key role in the nitrogen cycle within the cave environment [ 50 ]. Several genera of Pseudomonadales, known for their association with nitrogen fixation, particularly Pseudomonas , are abundant in Opiliones samples from the You Cave (YOM) [ 51 , 52 ]. Additionally, Actinobacteria, which are abundant in all samples, also contribute to the nitrogen cycle in various ecosystems [ 53 , 54 ]. The presence of nitrogenase molybdenum-iron (MoFe) protein and other nitrogenases further supports biological nitrogen fixation (Table S2 ).

Secondly, S. martensi and its symbiotic bacteria facilitate denitrification, a critical aspect of the nitrogen cycle. Predictive analysis using FAPROTAX revealed that denitrification accounts for a significant proportion of nitrogen-related functions (Fig.  6 a). Denitrification establishes a loop between atmospheric and ecological water bodies, with the process involving key enzymes such as nitrate reductase (Nar), nitrite reductase (Nir), nitric oxide reductase (Nor), and nitrous oxide reductase (Nos). These enzymes are present in the symbiotic bacteria of Opiliones from all three caves (Table S2 ). Aerobic denitrifying bacteria such as Comamonas , Acinetobacter , and Pseudomonas , known to facilitate denitrification, exhibit high abundance in Opiliones samples from various caves, particularly Pseudomonas [ 55 , 56 ] (Fig.  3 b).

The karst cave represents a terrestrial oligotrophic extreme underground ecosystem characterized by limited sources of total organic carbon and nitrogen. Within this environment, Opiliones and their symbiotic bacteria play integral roles in the unique energy and material cycles. Operating amidst constant darkness and low energy availability, they contribute significantly to the ecosystem’s functioning. These findings underscore the importance of investigating microbial communities within cave ecosystems to gain insights into their ecological processes and biogeochemical cycles. Understanding the dynamics of these symbiotic relationships and their impact on nutrient cycling sheds light on the intricate balance of life in these remote and often overlooked environments.

Many differences between the environment inside and outside the cave, and the community composition of symbiotic bacteria is also obviously different. The environment inside the cave remains relatively constant. This makes it worthwhile to study the unique community structure of symbiotic bacteria in comparison to the Opiliones living outside the cave, especially in the north where there are obvious changes in the four seasons. We conducted a comparison between S. martensi inside the cave and the Himalphalangium palpalis and Homolophus serrulatus outside the cave and found that there was a significant difference between them. At the phylum level, although most of the samples had Proteobacteria, Actinobacteria and Bacteroidetes as the dominant group, the abundance of symbiotic bacteria varied across different environmental samples (Fig.  8 a). Comparing the Opiliones inside and outside of the cave, and a significant difference was found not only in the composition of the community but also in the species of dominant bacteria (Fig.  8 a, b).

Two potential explanations may account for this phenomenon. First, the genetic relationship between S. martensi and Himalphalangium palpalis , Homolophus serrulatus is relatively distant. S. martensi belongs to the Laniatores group, characterized by robust tentacles (Fig.  2 a, b, e, f) and a diet primarily consisting of other insects, while Himalphalangium palpalis and Homolophus serrulatus belong to the Eupnoi group, lacking strong tentacles (Fig.  2 c, d) and capable of feeding on fungi, plants and animals. Previous studies have shown that genetic relationships can have a great influence on the structure of symbiotic bacteria in animals. In addition to the co-evolution of primary endosymbionts with the host [ 57 , 58 ], there are also symbiotic bacteria that are vertically transmitted from parents and give priority to transmission to closely related hosts [ 19 ]. Genes can regulate the body structure of different species, creating distinct internal environments and resulting in different dominant phyla. Secondly, differences in cave environment compared to outside conditions also contribute to this disparity. The cave environment remains constant, rarely disturbed by external temperature, and the temperature is maintained at more than ten degrees Celsius all year round. Opiliones inhabiting caves are thus unaffected by cold winters and remain active throughout the year. In contrast, Beijing experiences distinct four seasons, with temperature dropping significantly below zero in winter. The breeding, feeding and activities of Opiliones living outside Beijing caves are greatly limited by climate change.

Based on the two points mentioned above, which has more influence? We collected different samples (harvestmen, spiders and pseudoscorpions) from Siyu Cave and compared them. According to the results, we found that Proteobacteria, Actinobacteria, Firmicutes, and Bacteroidetes were the main constituent phyla of the species in the cave, and they each accounted for a similar proportion (Figure S1 a, b). Although they belong to different orders and have completely different feeding methods (spiders inject digestive juices into their prey, while harvestmen chew directly), there was no significant difference in the structure of symbiotic bacteria (Figure S1 c).

Afterward, we studied the spiders outside the Siyu Cave (SAS). To reduce the impact of the external environment and geographical location, we collected samples near the entrance, where there is light and climate change, significantly differs from that in the cave. From inside the cave to the outside, there were obvious changes in the structure of microflora in spiders from different environments (Figure S1 a, b). Compared with the spiders in the cave (SAC), the proportion of Proteobacteria in the symbiotic bacteria outside the cave (SAS) increased significantly at the phylum level, and at the genus level, Wolbachia and Rickettsia became the dominant flora. Both the diversity and richness of symbiotic bacteria in cave spiders were much higher than those outside the cave (Figure S1 c). Although the spiders, harvestmen and pseudoscorpions in the same cave environment have obvious differences in genetic relationship, their symbiotic bacteria are highly similar. Compared with harvestmen and pseudoscorpions, spiders inside and outside the cave are significantly closer in genetic relationship and feeding methods, but there are significant differences in the community structure of symbiotic bacteria. Therefore, compared with heredity, the effect of the cave environment on symbiotic bacteria is more obvious.

Symbiotic bacteria are not fixed, and there are many factors affecting them, among which the environment plays an important role. Most of the microbes found in organisms are acquired from the surrounding environment during the growth process, either directly or indirectly. Significant seasonal fluctuations of microbial communities are observed in wild mice [ 59 ] and hibernating ground squirrels ( Ictidomys tridecemlineatus and Urocitellus parryii ) every year [ 60 , 61 ]. Organisms residing in deep-sea hydrothermal regions characterized by high pressure, hypoxia, high levels of toxic substances, sulfides, and heavy metals, as well as being dark, are doubly symbiotic with two gammaproteobacterial endosymbionts: a sulfur oxidizer and a methane oxidizer [ 62 , 63 ]. High temperatures can denature proteins, causing physiological and developmental problems [ 10 ]. Endosymbiosis with heat shock tolerance can reduce the impact of high temperature on the survival and development of the host [ 11 ]. Various factors such as season, altitude, diet and photoperiod impact the diversity of animal microbial communities [ 9 ]. The community composition of larvae of Aedes aegypti , Aedes albopictus and Culex quinquefasciatus from different areas varied greatly, while strong similarities were found among larvae of different species developing in the same site [ 64 ]. These findings, along with previous studies, suggest that the environment exerts a more significant influence on symbiotic bacteria than heredity. However, in this study, arachnids were the subjects, and their genetic relationships were relatively close. If we take more closely related animals from different phyla or classes as samples, it remains uncertain whether the environment would still play such a significant role. Furthermore, due to residing in the cave for an extended period, Araneae, Opiliones and Pseudoscorpionida have undergone convergent evolution to some extent, exhibiting similar morphological features, such as the lack of eyes and a light body color. Could this similarity also affect the symbiotic structure of these three groups, making them more alike? Further studies are necessary to verify this hypothesis.

It is indeed interesting that the symbiotic bacteria richness of cave organisms surpasses found that outside the cave despite the challenging environment. This suggests that the cave environment may provide a unique niche for symbiotic bacteria to thrive. The caves in this study are located in the north of the Taihang Mountains, within the center of the North China Craton (NCC). This area is known for its abundance of mineral deposits [ 65 , 66 ]. Phyllobacterium , previously isolated from plant roots in mines, exhibits the capability to oxidize Mn (II) [ 67 ]. The abundance of Phyllobacterium in cave species (Table S5 ) may be due to its tolerance to heavy metals [ 68 , 69 ], which are often present in mineral-rich cave environments. The joint action of nutrition, rock and other factors may contribute to the richness of symbiotic bacteria in caves [ 70 , 71 ], and may also explain the observed difference in symbiotic bacteria between cave and non-cave organisms. Further studies are needed to fully understand the mechanisms underlying these observations.

Sinonychia martensi found in Beijing caves in this study is a highly adapted species to cave life, and the first superfamily Travunioidea discovered in China [ 72 ]. Currently, the Travunioidea are distributed across the Holarctic, in the temperate regions of central Europe, southern British Columbia, eastern and western United States, Japan, and South Korea [ 73 ]. Although Sinonychia is closely related to Speleonychia and shares some morphological similarities, it is considered a new genus. Interestingly, Speleonychia , closely related to Sinonychia , is mainly located in the Pacific Northwest of North America, across the Pacific Ocean from the Sinonychia [ 72 ]. The Laniatores, the order to which Sinonychia belongs, are mainly distributed in the tropical and temperate regions of the southern hemisphere [ 74 ] with more common occurrences in Hainan and Sichuan, situated in the south of China [ 75 , 76 , 77 ]. Therefore, it raises the question of why S. martensi , the only Travunioidea found in China, appears in caves in the north.

Two main hypotheses are generally proposed to explain the shift from surface to underground habitats. The first hypothesis suggests that the colonization of underground habitats is the result of the active expansion and colonization by a founder [ 78 ], rather than accidental stranding and persistence in lightless areas [ 79 , 80 ]. The second hypothesis proposes that species may be forced to adapt to cave life due to environmental changes that make the surface uninhabitable [ 81 , 82 , 83 ]. The Opiliones in this study exhibit obvious characteristics of cave life, indicating that they have been forced to move underground and have lived at the bottom of the cave for many years. Therefore, S. martensi , being the first of its kind found in China, likely originated from the same southern family with a warm and humid climate rather than migrating all the way to the north.

Some similarities in symbiotic bacteria of Opiliones from Hainan Island and karst caves suggest that karst caves can serve as an alternative habitat for species thriving in warm and humid climates. However, does this imply that the cave environment is comparable to its natural habitat? Hainan Island, a typical tropical region in China, is home to a significant number of Laniatores species. In this study, E. flavimaculatus and P. columnarius were collected from Haikou City and Wuzhishan City of Hainan Island respectively, and compared with S. martensi from Beijing caves. To provide a clearer comparison, Himalphalangium palpalis and Homolophus serrulatus , also found outside the cave in Beijing, were included in the study. The results showed that the symbiotic structure of S. martensi was more similar to that of Opiliones from Hainan Island compared to Opiliones outside the cave in Beijing. The relative abundance of Proteobacteria in Homolophus serrulatus was only 21.44% and 37.07%, whereas it was the highest in other Opiliones (Figure S2 a, Table S5 ). The relative abundance of Firmicutes in SOM, HOF, and WOC was 21.90%, 6.30% and 20.17% respectively, ranking second. Cluster analysis of symbiotic bacteria in each sample revealed that the species composition of Opiliones from Hainan Island and Beijing caves were more similar (Fig.  10 a, b). Therefore, the study suggests that the environment of the caves in Beijing may be similar to that in Hainan Island, and provides insights into the origin of S. martensi .

The cave can be thought of as an independent “small world” with constant temperature and humidity, permanent darkness and limited food resources. Unlike terrestrial vertebrates, which have high diffusivity, terrestrial cave invertebrates are usually confined to small geographical areas and are the main components of cave fauna [ 40 ]. S. martensi has lived for a long time in isolated caves, with limited interaction with external biota, particularly from the south to the north. In addition, the northern climate is not fixed, with the onset of the monsoon climate from the Oligocene-Miocene boundary [ 84 ], East Asia has experienced seasonality of lower average temperature and humidity in winter [ 85 ]. Due to the relatively stable microclimate, caves may serve as a refuge for numerous organisms, and their surface counterparts tend to become extinct under adverse climatic conditions, which means some local cave biota remain [ 86 ]. This also explains why this study was unable to collect any other Sinonychia or even Laniatores closely related to S. martensi outside the cave from Beijing, only other harvestmen of the Eupnoi. A spider study suggested that climate change during the middle Miocene period facilitated the development of underground lifestyles in the middle latitudes of Asia [ 87 ]. The seasonality may have contributed to the extinction of surface species, and caves with relatively stable temperatures and humidity may have provided an ideal refuge for local species. In addition to climate change, human-made environmental destruction has impacted the distribution of S. martensi . With the decrease in temperature and humidity, reduction in surface trees, and destruction of the ecosystem, some Opiliones on the surface sought refuge underground and adapted to the stable cave environment, leading to changes in their morphology. With the passage of time and adaptation to the caves, their posture changed. The other part disappeared from the surface forever. Conversely, Laniatores, which are still found in the tropics and subtropics, have managed to survive until today.

This study focused on the Opiliones in karst caves in Beijing, comparing them to those found outside the caves as well as to other organisms such as harvestmen, spiders and pseudoscorpions within the same cave. The results showed that the environment plays a more important role in determining symbiotic bacteria diversity than heredity. S. martensi , a unique species belonging to the Travunioidea and first discovered in China, adds to the mystery of caves that are both geographically isolated and have a unique environment. The symbiotic bacteria structure also reflects the characteristics of the host environment and the symbiotic community composition of Opiliones in caves in Beijing is similar to those found in Hainan Island, suggesting that the cave environment may resemble that found in the tropics. This finding explains the occurrence of S. martensi in caves in the north, and helps explore the role of symbiotic bacteria in host distribution and evolution, and in explaining the biological characteristics of the host.

Data availability

The sequence data generated and analyzed in this study are available at NCBI ( https://www.ncbi.nlm.nih.gov ) under accession numbers (PRJNA985231).

Abbreviations

Polymerase Chain Reaction

Amplicon Sequence Variants

Principal Coordinate Analysis

Non-Metric Multidimensional Scaling

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Acknowledgements

We thank Zhao JJ (Hebei University) for her help in collecting these specimens during the fieldwork. This work was supported by the Natural Science Foundation of Hebei Province (No. C2021201030).

This work was supported by the Natural Science Foundation of Hebei Province (No. C2021201030).

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Likun Zhao, Ruoyi Xiao, Shanfeng Zhang, Chao Zhang & Feng Zhang

The Key Laboratory of Microbial Diversity Research and Application of Hebei Province, Baoding, 071002, P. R. China

The Key Laboratory of Zoological Systematics and Application of Hebei Province, Baoding, 071002, P. R. China

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Zhao, L., Xiao, R., Zhang, S. et al. Environmental specificity of karst cave habitats evidenced by diverse symbiotic bacteria in Opiliones. BMC Ecol Evo 24 , 58 (2024). https://doi.org/10.1186/s12862-024-02248-9

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The idea involves a gene variant called APOE4. Scientists have long known that inheriting one copy of the variant increases the risk of developing Alzheimer’s, and that people with two copies, inherited from each parent, have vastly increased risk.

The new study , published in the journal Nature Medicine, analyzed data from over 500 people with two copies of APOE4, a significantly larger pool than in previous studies. The researchers found that almost all of those patients developed the biological pathology of Alzheimer’s, and the authors say that two copies of APOE4 should now be considered a cause of Alzheimer’s — not simply a risk factor.

The patients also developed Alzheimer’s pathology relatively young, the study found. By age 55, over 95 percent had biological markers associated with the disease. By 65, almost all had abnormal levels of a protein called amyloid that forms plaques in the brain, a hallmark of Alzheimer’s. And many started developing symptoms of cognitive decline at age 65, younger than most people without the APOE4 variant.

“The critical thing is that these individuals are often symptomatic 10 years earlier than other forms of Alzheimer’s disease,” said Dr. Reisa Sperling, a neurologist at Mass General Brigham in Boston and an author of the study.

She added, “By the time they are picked up and clinically diagnosed, because they’re often younger, they have more pathology.”

People with two copies, known as APOE4 homozygotes, make up 2 to 3 percent of the general population, but are an estimated 15 to 20 percent of people with Alzheimer’s dementia, experts said. People with one copy make up about 15 to 25 percent of the general population, and about 50 percent of Alzheimer’s dementia patients.

The most common variant is called APOE3, which seems to have a neutral effect on Alzheimer’s risk. About 75 percent of the general population has one copy of APOE3, and more than half of the general population has two copies.

Alzheimer’s experts not involved in the study said classifying the two-copy condition as genetically determined Alzheimer’s could have significant implications, including encouraging drug development beyond the field’s recent major focus on treatments that target and reduce amyloid.

Dr. Samuel Gandy, an Alzheimer’s researcher at Mount Sinai in New York, who was not involved in the study, said that patients with two copies of APOE4 faced much higher safety risks from anti-amyloid drugs.

When the Food and Drug Administration approved the anti-amyloid drug Leqembi last year, it required a black-box warning on the label saying that the medication can cause “serious and life-threatening events” such as swelling and bleeding in the brain, especially for people with two copies of APOE4. Some treatment centers decided not to offer Leqembi, an intravenous infusion, to such patients.

Dr. Gandy and other experts said that classifying these patients as having a distinct genetic form of Alzheimer’s would galvanize interest in developing drugs that are safe and effective for them and add urgency to current efforts to prevent cognitive decline in people who do not yet have symptoms.

“Rather than say we have nothing for you, let’s look for a trial,” Dr. Gandy said, adding that such patients should be included in trials at younger ages, given how early their pathology starts.

Besides trying to develop drugs, some researchers are exploring gene editing to transform APOE4 into a variant called APOE2, which appears to protect against Alzheimer’s. Another gene-therapy approach being studied involves injecting APOE2 into patients’ brains.

The new study had some limitations, including a lack of diversity that might make the findings less generalizable. Most patients in the study had European ancestry. While two copies of APOE4 also greatly increase Alzheimer’s risk in other ethnicities, the risk levels differ, said Dr. Michael Greicius, a neurologist at Stanford University School of Medicine who was not involved in the research.

“One important argument against their interpretation is that the risk of Alzheimer’s disease in APOE4 homozygotes varies substantially across different genetic ancestries,” said Dr. Greicius, who cowrote a study that found that white people with two copies of APOE4 had 13 times the risk of white people with two copies of APOE3, while Black people with two copies of APOE4 had 6.5 times the risk of Black people with two copies of APOE3.

“This has critical implications when counseling patients about their ancestry-informed genetic risk for Alzheimer’s disease,” he said, “and it also speaks to some yet-to-be-discovered genetics and biology that presumably drive this massive difference in risk.”

Under the current genetic understanding of Alzheimer’s, less than 2 percent of cases are considered genetically caused. Some of those patients inherited a mutation in one of three genes and can develop symptoms as early as their 30s or 40s. Others are people with Down syndrome, who have three copies of a chromosome containing a protein that often leads to what is called Down syndrome-associated Alzheimer’s disease .

Dr. Sperling said the genetic alterations in those cases are believed to fuel buildup of amyloid, while APOE4 is believed to interfere with clearing amyloid buildup.

Under the researchers’ proposal, having one copy of APOE4 would continue to be considered a risk factor, not enough to cause Alzheimer’s, Dr. Fortea said. It is unusual for diseases to follow that genetic pattern, called “semidominance,” with two copies of a variant causing the disease, but one copy only increasing risk, experts said.

The new recommendation will prompt questions about whether people should get tested to determine if they have the APOE4 variant.

Dr. Greicius said that until there were treatments for people with two copies of APOE4 or trials of therapies to prevent them from developing dementia, “My recommendation is if you don’t have symptoms, you should definitely not figure out your APOE status.”

He added, “It will only cause grief at this point.”

Finding ways to help these patients cannot come soon enough, Dr. Sperling said, adding, “These individuals are desperate, they’ve seen it in both of their parents often and really need therapies.”

Pam Belluck is a health and science reporter, covering a range of subjects, including reproductive health, long Covid, brain science, neurological disorders, mental health and genetics. More about Pam Belluck

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