Random genetic drift sets an upper limit on mRNA splicing accuracy in metazoans

Most eukaryotic genes undergo alternative splicing (AS), but the overall functional significance of this process remains a controversial issue. It has been noticed that the complexity of organisms (assayed by the number of distinct cell types) correlates positively with their genome-wide AS rate. This has been interpreted as evidence that AS plays an important role in adaptive evolution by increasing the functional repertoires of genomes. However, this observation also fits with a totally opposite interpretation: given that ‘complex’ organisms tend to have small effective population sizes (N e), they are expected to be more affected by genetic drift, and hence more prone to accumulate deleterious mutations that decrease splicing accuracy. Thus, according to this “drift barrier” theory, the elevated AS rate in complex organisms might simply result from a higher splicing error rate. To test this hypothesis, we analyzed 3,496 transcriptome sequencing samples to quantify AS in 53 metazoan species spanning a wide range of N e values. Our results show a negative correlation between N e proxies and the genome-wide AS rates among species, consistent with the drift barrier hypothesis. This pattern is dominated by low abundance isoforms, which represent the vast majority of the splice variant repertoire. We show that these low abundance isoforms are depleted in functional AS events, and most likely correspond to errors. Conversely, the AS rate of abundant isoforms, which are relatively enriched in functional AS events, tends to be lower in more complex species. All these observations are consistent with the hypothesis that variation in AS rates across metazoans reflects the limits set by drift on the capacity of selection to prevent gene expression errors.

[1]  Christopher W. J. Smith,et al.  Alternative splicing as a source of phenotypic diversity , 2022, Nature Reviews Genetics.

[2]  Jianzhi Zhang,et al.  Gene product diversity: adaptive or not? , 2022, Trends in genetics : TIG.

[3]  Jukka-Pekka Verta,et al.  The role of alternative splicing in adaptation and evolution. , 2021, Trends in ecology & evolution.

[4]  Gloria M. Sheynkman,et al.  Full-length transcript sequencing of human and mouse cerebral cortex identifies widespread isoform diversity and alternative splicing , 2021, Cell reports.

[5]  Pooja Singh,et al.  The importance of alternative splicing in adaptive evolution , 2021, Molecular ecology.

[6]  Sheeba John,et al.  Regulation of alternative splicing in response to temperature variation in plants , 2021, Journal of experimental botany.

[7]  P. Khaitovich,et al.  Alternative splicing during mammalian organ development , 2021, Nature Genetics.

[8]  M. Lynch,et al.  Universally high transcript error rates in bacteria , 2020, eLife.

[9]  J. Romiguier,et al.  Relaxation of purifying selection suggests low effective population size in eusocial Hymenoptera and solitary pollinating bees , 2020, bioRxiv.

[10]  M. Zavolan,et al.  A different perspective on alternative cleavage and polyadenylation , 2019, Nature Reviews Genetics.

[11]  Steven L Salzberg,et al.  Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype , 2019, Nature Biotechnology.

[12]  J. Baker,et al.  Gene expression across mammalian organ development , 2019, Nature.

[13]  Jianzhi Zhang,et al.  Evidence that alternative transcriptional initiation is largely nonadaptive , 2019, PLoS biology.

[14]  H. Ellegren,et al.  GC-biased gene conversion conceals the prediction of the nearly neutral theory in avian genomes , 2019, Genome Biology.

[15]  H. Ellegren,et al.  GC-biased gene conversion conceals the prediction of the nearly neutral theory in avian genomes , 2019, Genome Biology.

[16]  Alexey M. Kozlov,et al.  RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference , 2018, bioRxiv.

[17]  Jianzhi Zhang,et al.  Alternative Polyadenylation of Mammalian Transcripts Is Generally Deleterious, Not Adaptive. , 2018, Cell systems.

[18]  P. Pavlidis,et al.  Systematic evaluation of isoform function in literature reports of alternative splicing , 2018, BMC Genomics.

[19]  Jianzhi Zhang,et al.  Human C‐to‐U Coding RNA Editing Is Largely Nonadaptive , 2018, Molecular biology and evolution.

[20]  Jianzhi Zhang,et al.  Most m6A RNA Modifications in Protein‐Coding Regions Are Evolutionarily Unconserved and Likely Nonfunctional , 2018, Molecular biology and evolution.

[21]  Evan Bolton,et al.  Database resources of the National Center for Biotechnology Information , 2017, Nucleic Acids Res..

[22]  M. Tress,et al.  Most Alternative Isoforms Are Not Functionally Important. , 2017, Trends in biochemical sciences.

[23]  B. Blencowe The Relationship between Alternative Splicing and Proteomic Complexity. , 2017, Trends in biochemical sciences.

[24]  L. Duret,et al.  Unbiased Estimate of Synonymous and Nonsynonymous Substitution Rates with Nonstationary Base Composition , 2017, bioRxiv.

[25]  L. Duret,et al.  The fitness cost of mis-splicing is the main determinant of alternative splicing patterns , 2017, Genome Biology.

[26]  M. Tress,et al.  Alternative Splicing May Not Be the Key to Proteome Complexity. , 2017, Trends in biochemical sciences.

[27]  Araxi O. Urrutia,et al.  Alternative splicing and the evolution of phenotypic novelty , 2016, Philosophical Transactions of the Royal Society B: Biological Sciences.

[28]  Michael Lynch,et al.  Genetic drift, selection and the evolution of the mutation rate , 2016, Nature Reviews Genetics.

[29]  Jay P. McEntee,et al.  Drift Barriers to Quality Control When Genes Are Expressed at Different Levels , 2016, Genetics.

[30]  R. Waples Life-history traits and effective population size in species with overlapping generations revisited: the importance of adult mortality , 2016, Heredity.

[31]  H. Ellegren,et al.  Life History Traits, Protein Evolution, and the Nearly Neutral Theory in Amniotes. , 2016, Molecular biology and evolution.

[32]  H. Ochman,et al.  Conserved rates and patterns of transcription errors across bacterial growth states and lifestyles , 2016, Proceedings of the National Academy of Sciences.

[33]  Evgeny M. Zdobnov,et al.  BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs , 2015, Bioinform..

[34]  Gabor T. Marth,et al.  A global reference for human genetic variation , 2015, Nature.

[35]  Alfonso Valencia,et al.  Alternatively Spliced Homologous Exons Have Ancient Origins and Are Highly Expressed at the Protein Level , 2015, PLoS Comput. Biol..

[36]  J. Rinehart,et al.  Transcriptional responses to fluctuating thermal regimes underpinning differences in survival in the solitary bee Megachile rotundata , 2015, The Journal of Experimental Biology.

[37]  Lewis Y. Geer,et al.  Database resources of the National Center for Biotechnology Information , 2014, Nucleic Acids Res..

[38]  E. Makeyev,et al.  Emerging functions of alternative splicing coupled with nonsense-mediated decay. , 2014, Biochemical Society transactions.

[39]  R. Gibbs,et al.  Natural variation in genome architecture among 205 Drosophila melanogaster Genetic Reference Panel lines , 2014, Genome research.

[40]  Araxi O. Urrutia,et al.  Correcting for Differential Transcript Coverage Reveals a Strong Relationship between Alternative Splicing and Organism Complexity , 2014, Molecular biology and evolution.

[41]  Jianzhi Zhang,et al.  Human coding RNA editing is generally nonadaptive , 2014, Proceedings of the National Academy of Sciences.

[42]  M. Lynch,et al.  Large-scale detection of in vivo transcription errors , 2013, Proceedings of the National Academy of Sciences.

[43]  Wolfgang Huber,et al.  Drift and conservation of differential exon usage across tissues in primate species , 2013, Proceedings of the National Academy of Sciences.

[44]  Nicolas C. Rochette,et al.  Bio++: efficient extensible libraries and tools for computational molecular evolution. , 2013, Molecular biology and evolution.

[45]  J. Harrow,et al.  Transcriptome analysis of human tissues and cell lines reveals one dominant transcript per gene , 2013, Genome Biology.

[46]  C. Burge,et al.  Evolutionary Dynamics of Gene and Isoform Regulation in Mammalian Tissues , 2012, Science.

[47]  Jonathan Romiguier,et al.  Efficient selection of branch-specific models of sequence evolution. , 2012, Molecular biology and evolution.

[48]  Kevin R. Thornton,et al.  The Drosophila melanogaster Genetic Reference Panel , 2012, Nature.

[49]  Lior Pachter,et al.  Identification of novel transcripts in annotated genomes using RNA-Seq , 2011, Bioinform..

[50]  Jonathan M. Mudge,et al.  The Origins, Evolution, and Functional Potential of Alternative Splicing in Vertebrates , 2011, Molecular biology and evolution.

[51]  J. Masel,et al.  Evolution of molecular error rates and the consequences for evolvability , 2011, Proceedings of the National Academy of Sciences.

[52]  Joseph K. Pickrell,et al.  Noisy Splicing Drives mRNA Isoform Diversity in Human Cells , 2010, PLoS genetics.

[53]  Hideaki Sugawara,et al.  The Sequence Read Archive , 2010, Nucleic Acids Res..

[54]  K. J. Hertel,et al.  Spliceosomes walk the line: Splicing errors and their impact on cellular function , 2009, RNA biology.

[55]  J. Plotkin,et al.  The Population Genetics of dN/dS , 2008, PLoS genetics.

[56]  J. Dutheil,et al.  Non-homogeneous models of sequence evolution in the Bio++ suite of libraries and programs , 2008, BMC Evolutionary Biology.

[57]  Nicholas J. McGlincy,et al.  Alternative splicing resulting in nonsense-mediated mRNA decay: what is the meaning of nonsense? , 2008, Trends in biochemical sciences.

[58]  A. Löytynoja,et al.  Phylogeny-Aware Gap Placement Prevents Errors in Sequence Alignment and Evolutionary Analysis , 2008, Science.

[59]  M. Lynch The frailty of adaptive hypotheses for the origins of organismal complexity , 2007, Proceedings of the National Academy of Sciences.

[60]  M. Lynch The origins of eukaryotic gene structure. , 2006, Molecular biology and evolution.

[61]  Terrence S. Furey,et al.  The UCSC Genome Browser Database: update 2006 , 2005, Nucleic Acids Res..

[62]  M. Lynch,et al.  The Origins of Genome Complexity , 2003, Science.

[63]  Peer Bork,et al.  Alternative splicing and evolution. , 2003, BioEssays : news and reviews in molecular, cellular and developmental biology.

[64]  D. Bell,et al.  Sequence context at human single nucleotide polymorphisms: overrepresentation of CpG dinucleotide at polymorphic sites and suppression of variation in CpG islands. , 2003, Journal of molecular biology.

[65]  M. Pagel,et al.  Phylogenetic Analysis and Comparative Data: A Test and Review of Evidence , 2002, The American Naturalist.

[66]  B. Graveley Alternative splicing: increasing diversity in the proteomic world. , 2001, Trends in genetics : TIG.

[67]  R. Nielsen,et al.  Synonymous and nonsynonymous rate variation in nuclear genes of mammals , 1998, Journal of Molecular Evolution.

[68]  T. Ohta Slightly Deleterious Mutant Substitutions in Evolution , 1973, Nature.

[69]  Random genetic drift sets an upper limit on mRNA splicing accuracy in metazoans , 2023 .

[70]  Mosè Manni,et al.  BUSCO: Assessing Genome Assembly and Annotation Completeness. , 2019, Methods in molecular biology.

[71]  Matthew S. DiStefano,et al.  ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI , 2014 .

[72]  Michael D. Wilson,et al.  The Evolutionary Landscape of Alternative Splicing in Vertebrate Species , 2013 .

[73]  J. Morata,et al.  Alternative Splicing as a Source of Phenotypic Differences Between Species: Protein-Level Mechanisms , 2012 .

[74]  T. Scheper,et al.  Transcriptome analysis. , 2012, Advances in biochemical engineering/biotechnology.

[75]  J. R. Lobry,et al.  SeqinR 1.0-2: A Contributed Package to the R Project for Statistical Computing Devoted to Biological Sequences Retrieval and Analysis , 2007 .

[76]  F. THE MUTATION LOAD IN SMALL POPULATIONS , 2022 .