Descobertas Genéticas em C. elegans: Mecanismos da Variação Natural - Artigo Científico

From QTL to gene C elegans facilitates discoveries of the genetic mechanisms underlying natural variation Kathryn S Evans125 Marijke H van Wijk35 Patrick T McGrath4 Erik C Andersen1 Mark G Sterken3 1Molecular Biosciences Northwestern University Evanston IL 60208 USA 2Interdisciplinary Biological Sciences Program Northwestern University Evanston IL 60208 USA 3Laboratory of Nematology Wageningen University and Research 6708 PB Wageningen The Netherlands 4School of Biological Sciences Georgia Institute of Technology Atlanta GA 30332 USA 5These authors contributed equally to this work Abstract Although many studies have examined quantitative trait variation across many species only a small number of genes and thereby molecular mechanisms have been discovered Without these data we can only speculate about evolutionary processes that underlie trait variation Here we review how quantitative and molecular genetics in the nematode Caenorhabditis elegans led to the discovery and validation of 37 quantitative trait genes over the past 15 years Using these data we can start to make inferences about evolution from these quantitative trait genes including the roles that coding versus noncoding variation gene family expansion common versus rare variants pleiotropy and epistasis play in trait variation across this species Discovering the mechanisms of trait variation one gene at a time Over the past two decades the pace of discoveries of the genes and mechanisms underlying trait variation has increased because of advances in wholegenome sequencing and mixed effects model approaches in quantitative genetics Studies have identified the number and effects of loci that impact diverse traits measured in livestock crops model species and humans but only a small number of genes and molecular mechanisms have been validated in any species This limitation exists because it is difficult or impossible to experimentally validate the roles of genes in quantitative traits in many species despite compelling evidence for numerous candidate genes These data can help elucidate models for how traits change Correspondence erikandersennorthwesternedu EC Andersen and marksterkenwurnl MG Sterken Declaration of interests No interests are declared Supplemental information Supplemental information associated with this article can be found online at httpsdoiorg101016jtig202106005 Resources HHS Public Access Author manuscript Trends Genet Author manuscript available in PMC 2022 February 23 Published in final edited form as Trends Genet 2021 October 3710 933947 doi101016jtig202106005 Author Manuscript Author Manuscript Author Manuscript Author Manuscript over time and the evolutionary principles underlying these changes Therefore researchers interested in evolution need to identify the genes and mechanisms that cause phenotypic differences across populations However most species have high levels of genetic diversity that make the mapping of many small effect loci and validation of specific genes difficult if not impossible 1 Additionally the literature is filled with numerous examples of quantitative trait loci QTL see Glossary that have been identified but specific genes and alleles have not been validated using precise genomic manipulations making inferences about the molecular mechanisms of trait variation guesses at best Several species can mitigate these limitations and enable discoveries of the genes and mechanisms contributing significant progress towards understanding the causes of trait variation across populations A little more than a decade ago the roundworm nematode Caenorhabditis elegans emerged as a powerhouse for the discovery of genes and variants that underlie quantitative trait variation 2 As of the writing of this review 37 quantitative trait genes QTGs have been discovered and validated using precise genomic edits in defined genetic backgrounds From that significant list researchers have gone even further to define 24 quantitative trait variants QTVs elucidating the molecular mechanisms of quantitative trait variation Table 1 Key table Figure 1 Key figure and Table S1 in the supplemental information online Genetic experiments testing the role of a gene in a quantitative trait must be performed to make this connection from phenotypic variation to a QTG The C elegans hermaphroditic mating system and selfing lifestyle facilitate these types of experiments because genomewide variation is relatively low and homozygous strains are easy to construct Additionally C elegans are easily grown in the laboratory and have a compact and defined genome in contrast to most other metazoan species Importantly recent advances in CRISPRCas9 genome editing enabled the creation of edits to specific genomic sites 3 These edited strains are often paired with sensitive highthroughput assays to measure subtle effects on phenotype 46 making genetic causality definable in a metazoan model Beyond genome editing other methods are made easier by selfing and further enable rapid gene identification and testing including fine mapping the phenotypic variation using additional genetic markers and narrowing mapped intervals using near isogenic lines NILs Recent discoveries of the species origins the structure of the genome and inferences of its natural niche 710 have set the context to help understand how evolution has shaped this species The confluence of these advantages have brought C elegans to the forefront of quantitative genetics The C elegans community has identified numerous QTL Table 1 and Table S1 in the supplemental information online that underlie life history traits such as reproduction 511 21 lifespan and aging 182236 body size and development 51215171821273237 49 and abundances of gene transcripts 245059 proteins 60 and metabolites 61 Behavioral traits studied include pathogen responses 176265 stress responses 4 614343655566580 responses to environmental perturbations such as food 268183 oxygen 8485 pheromones 394486 and temperature 121331384652568789 and other nematode behaviors 2390107 In addition to these traits genomic features such as telomere length 108 and transposable elements 109 as well as geographical 8110 and climate variables 110 have been used as quantitative traits for QTL mapping In this Evans et al Page 2 Trends Genet Author manuscript available in PMC 2022 February 23 Author Manuscript Author Manuscript Author Manuscript Author Manuscript review we will focus on how the strains and methods of C elegans quantitative genetics have defined 37 genes that underlie quantitative trait variation and how these data can answer fundamental questions about evolution at the molecular level Innovations in linkage mapping drive the discovery of genes and variants Quantitative genetics mappings use three complementary approaches linkage mapping bulksegregant analysis BSA and genomewide association GWA mapping Although BSA has been shown to be a fast powerful and effective tool to identify QTL 2049739598 linkage mapping is the most popular method for the detection of QTL in C elegans In this approach investigators leverage statistical power to detect QTL using a large number of recombinant lines generated from a cross between two or more phenotypically and genotypically diverse strains In the past 10 years 59 linkage mapping studies discovered 22 genes underlying differences in one or more quantitative traits Table 1 and Figure 1 Many of the underlying datasets are available using WormQTL2i 111 The rapid accumulation of QTGs over the past 10 years highlights the growth in the C elegans quantitative genetics field and the application of genomeediting technologies Many QTGs were discovered using three recombinant panels derived from the laboratoryadapted Bristol strain N2 and the genetically diverse Hawaiian strain CB4856 55291 The first panel of 80 recombinant inbred lines RILs was generated in 2006 52 which led to the discovery of the first C elegans QTG 38 A few years later a second panel of 239 recombinant inbred advanced intercross lines RIAILs was created this intercrossing scheme created more recombination events and thereby enhanced mapping resolution 91112 However after the generation of this RIAIL panel researchers discovered that many of these lines contain the N2 allele at the peel1 zeel1 incompatibility locus on chromosome I 113114 Additionally multiple studies found that the laboratoryderived N2 alleles of the genes npr1 glb5 nath10 and col182 have strong pleiotropic effects Box 1 49115 To reduce the effects of the genetic incompatibility between the N2 and CB4856 strains and the large pleiotropic effect of the N2 npr1 allele Andersen and colleagues generated a second RIAIL panel in which all 359 lines harbor the natural npr1 allele from CB4856 and a transposon insertion into the peel1 gene 5 Besides these RIL and RIAIL panels a number of NIL panels were constructed using the N2 and CB4856 strains as parental lines 2388102 and used to map QTL 2223454656638890 QTL can be validated and fine mapped using NILs and genetic causality can be tested using CRISPRCas9 genome editing of candidate genes Box 2 Together all of these N2xCB4856 panels led to the discovery of 16 QTGs 6173849636567687576818485909396104113 that underlie traits such as toxin responses 66567687576 nictation 93 and RNAi sensitivity 103104 Table 1 and Figure 1 Other strains have also been used to generate RIL panels to investigate natural variation that can be independent of the N2 and CB4856 variation 1420363742448692 Table 2 These panels were often made from strains that are divergent in a particular trait and i wwwbioinformaticsnlWormQTL2 Evans et al Page 3 Trends Genet Author manuscript available in PMC 2022 February 23 Author Manuscript Author Manuscript Author Manuscript Author Manuscript have led to the discovery of the role of nath10 in vulval induction 37 plep1 in plugging behavior 92 srx43 and srx44 in pheromone sensitivity 86 and set24 in temperature induced sterility 20 Additionally custommade recombinant panels can harbor a particular mutation in a genetic background allowing for the identification of modifier loci Box 3 375092 Regardless of the strain composition linkage mapping continues to be an extremely powerful method for identifying QTGs in C elegans An expanding wild isolate panel facilitates investigations of population wide trait variation Although linkage mapping and BSA have proven invaluable tools for C elegans quantitative geneticists the major innovation of the past decade was the introduction of GWA mapping 91 GWA mapping takes advantage of the breadth of natural genetic diversity that exists among genetically distinct individuals Like other mapping techniques GWA mapping aims to identify functional variants that contribute to phenotypic diversity The strength of this approach is in its ability to leverage the breadth of phenotypic variation present across the species to identify common QTVs The C elegans Natural Diversity Resource CeNDR 10116 catalogues and distributes all wild strains and genomewide variation data CeNDRii remains a vital resource for the C elegans community to facilitate GWA mappings and population genomic analyses Performing GWA mapping studies in C elegans requires an understanding of the genetic composition of the specieswide population Early studies to characterize the genetic variation in C elegans at a global scale discovered large blocks of shared haplotypes across four of the six chromosomes likely explained by one or more recent strong selective sweeps 8 Extensive linkage disequilibrium particularly in the center of chromosomes limits QTL resolution using GWA mapping Additionally many strains are genetically similar and can be grouped into distinct isotypes GWA mapping analysis with several strains from the same isotype inappropriately increases the effects of these nearly genetically identical strains Largescale collection efforts over the past decade have led to a specieswide collection of 1378 strains comprising 540 distinct isotypes Along with these additional strains the catalogued genetic diversity has increased particularly in strains collected from the Hawaiian islands and the neighboring Pacific region 710 However this increased genetic diversity decreases linkage disequilibrium making the localization of QTL more difficult particularly in punctuated regions of the genome with extreme genetic diversity 117 In total association mapping led to the discovery of nine QTGs including seven with QTVs that underlie quantitative trait variation Table 1 and Figure 1 In one such example a natural deletion in the pheromone receptor gene srg37 was found to cause variation in the dauer pheromone response 93 In a study of Orsay virus sensitivity a locus in the center of chromosome IV was linked to variation in viral load This locus was later finemapped to a natural deletion in the gene drh1 a homolog of the mammalian RIGI gene family 101 ii wwwelegansvariationorg Evans et al Page 4 Trends Genet Author manuscript available in PMC 2022 February 23 Author Manuscript Author Manuscript Author Manuscript Author Manuscript These examples and others provide important insights into the pathways and molecular mechanisms that cause natural variation across wild populations Although linkage mapping BSA and GWA mapping have each had considerable success mapping QTL and QTGs each mapping approach has its drawbacks when used in isolation In some studies a combination of both linkage and GWA mapping has been used to narrow genomic intervals by analyzing QTL that overlap between methods 665677576 Alternatively multiparent recombinant inbred line mpRIL panels Figure 2A have become important quantitative genetic tools in other model organisms such as mice 118119 Drosophila melanogaster 120 and Arabidopsis thaliana 121 These populations capture genetic diversity within the species without sacrificing the power of recombinants to detect and localize QTL In C elegans two mpRIL panels have been developed the CeMEE and the mpRIL panel 1527122 The CeMEE panel is a 16parent experimental evolution panel that after crossing was exposed to more than 100 generations of experimental evolution and subsequent inbreeding 15122 Alternatively the mpRIL panel was generated from four parental strains with genotypic and phenotypic variation 123 isolated in close geographic proximity 27 In addition to simply mapping more QTL across a variety of traits wider adoption and generation of new mpRIL could help to address several outstanding questions in quantitative trait variation and the evolution of diverse phenotypes Validated QTGs and QTVs provide insights into evolution Each of the 37 C elegans QTGs discovered in the past 15 years Table 1 and Figure 1 individually reveal molecular mechanisms for how phenotypic diversity is shaped offering clues into how this species has evolved Together this set of experimentally validated QTGs give researchers numerous examples to connect quantitative trait variation to understanding evolutionary principles The high confidence in these QTGs ensures that any conclusions drawn from these data are not influenced by false positive QTL or wishful thinking By investigating these genes we can begin to make suppositions about the variants most commonly underlying trait variation important for evolutionary change Validated QTVs confer fitness advantages in specific environments Most validated QTVs fall into two groups common variants with small effects or rare variants with large effects 124 Of the 24 QTVs identified in C elegans 11 are common or present in more than 5 of isotypes CeNDR Table S1 in the supplemental information online Of these 11 QTVs three were identified using GWA mapping alone four using linkage mapping alone and four using both mapping methods For example multiple common alleles have been correlated with toxin response differences 6657476101 This result suggests that these alleles have been maintained over many generations and the predicted fitness costs of harboring such alleles are likely to be small The remaining 13 QTVs are rare alleles across the C elegans population and were identified exclusively using linkage mapping which fits expectations about the power to detect these loci when parent strains harbor rare variants These rare QTVs fall into two groups nine laboratoryderived alleles Box 1 and four alleles detected in wild populations The wild rare alleles are Evans et al Page 5 Trends Genet Author manuscript available in PMC 2022 February 23 Author Manuscript Author Manuscript Author Manuscript Author Manuscript associated with severe detrimental effects on lifehistory traits For example males with the mab23e2518 allele are unable to reproduce 4748 and the set24mfP23 allele causes sterility after prolonged exposure to 25C 20 It is possible that their fitness effects are only present in specific environments eg the rare variant eak3 confers fitness advantages under stressful conditions by increasing dauer formation suggesting that these alleles might have been selected in specific environments 41 as illustrated by the rare laboratoryderived QTVs that confer fitness advantages in that environment Box 4 Overall we still need more research into the natural ecology of C elegans to understand how any discovered alleles or genes are influenced by selection 125 Most validated QTGs are members of gene families It has been hypothesized that paralogous genes or genes that are part of a functionally redundant gene family might offer a source of variation across populations because the genes can diverge without strongly affecting function 126 Because of the evergrowing collection of C elegans strains 10116 the rapidly increasing availability of highquality nematode genomes 127 and recent developments in evolutionary biology and comparative genomics 128 we can begin to determine how often quantitative trait variation is caused by differences in gene families Of the 37 QTGs identified in C elegans 27 genes had one or more paralogs Table S1 in the supplemental information online 129130 providing strong empirical data that as genes increase in copy number they can functionally diverge and cause trait variation By contrast it is estimated that about 6000 genes or 32 of the genome have at least one paralog 131 indicating a highly significant enrichment of QTGs belonging to a gene family Fishers exact test P 000001 This result supports the duplicationdivergence model where new genes come from copies of preexisting genes 132 In one example researchers mapped variation in propionate sensitivity to a putative glucuronosyltransferase that is part of an expanded gene family specific to C elegans 74 Importantly new results show that hyperdivergent regions of the C elegans genome contain environmentalresponse genes that are genes not found in the N2 reference genome and members of C elegans specific expanded gene families 10 The validated QTGs that are members of gene families suggest that quantitative trait variation is likely focused in hyperdivergent regions and must be characterized using longread genome sequencing to define strain or speciesspecific genes As studies into the natural ecology of C elegans continue it will be important to investigate how these expanded and variable gene families contribute to fitness in the niche Noncoding variation is responsible for organismlevel trait differences Most known QTVs are largeeffect proteincoding variants that cause phenotypic differences Table 1 However noncoding variation might be more evolutionarily important 133135 Numerous studies across several species suggest that genetic variation impacts gene expression 136137 However it is often unclear how these gene expression differences translate to trait variation Again C elegans offers six examples eak3 exp1 prg1 scb1 srx43 and tyra3 in which noncoding variation is stated to be correlated with trait differences 41676881869093 Furthermore several gene expression QTL eQTL studies have discovered thousands of differentially expressed genes that are largely Evans et al Page 6 Trends Genet Author manuscript available in PMC 2022 February 23 Author Manuscript Author Manuscript Author Manuscript Author Manuscript controlled by genetic factors 2451565859 Colocalization of eQTL and organismlevel QTL could suggest that a single genetic variant underlies both 6175168 Techniques such as mediation analysis can make statistical connections between genetic variation variation in an intermediate trait such as gene expression and variation in complex organismlevel phenotypes Figure 2B This technique was successfully used to suggest that scb1 affects responses to several chemotherapeutics 68 and that sqst5 affects differential responses to exogenous zinc 6 The effects of both loci were subsequently validated using genome editing In addition to providing another resource for candidate gene prioritization within a QTL interval separate from evaluating proteincoding variation mediation analysis can help to identify the mechanism by which genetic variation causes trait variation This technique is especially powerful to establish candidate genes whose expression is controlled by loci far from the regulated gene as most finemapping techniques only consider genes within the QTL confidence interval In the case of tyra3 and exp1 8190 phenotypic differences could be explained by gene expression but eQTL for neither gene are detected suggesting that wholeorganism gene expression data might not always be sufficient to identify expression differences at singlecell resolution 59 To date most eQTL datasets in C elegans have been generated from twoparent recombinant lines specifically N2xCB4856 recombinants Therefore a genomewide analysis of gene expression in wild isolates or other mpRILs could provide an unprecedented resource for studying the role of regulatory variation in quantitative traits 58 C elegans mapping studies are just beginning to define the complexity of many quantitative traits Although many early quantitative genetics studies in C elegans identified mostly single largeeffect loci 2138 technological advancements coupled with the collection of more genetically distinct wild isolates led to increases in the power to detect more QTL with ever smaller effects Many quantitative traits map to at least two independent loci and some traits have five or more QTL One largescale QTL mapping study of nematode responses to 16 diverse toxins identified 82 QTL from 47 traits a third of these traits mapped to two or more loci 69 Strikingly most of these QTL had small effect sizes explaining less than 10 of the phenotypic variation in the mapping panel Several studies used NILs to validate smalleffect loci demonstrating that small effects can be studied in C elegans with the right tools and a sensitive assay 666982 Current mapping populations and studies detect some of the loci underlying quantitative trait variation but we can use estimates of heritability to understand the levels of complexity for most traits The total fraction of trait variation explained by genetic variation in a population can be estimated by calculating broadsense heritability When compared with an estimate of narrowsense heritability which accounts for all additive effects the socalled missing heritability can be estimated as the difference between the total genetic effect and the additive effects 1 One explanation for this discrepancy can be explained by nonadditive effects including epistasis For C elegans only five studies have estimated both broad and narrowsense heritability 1539697476 and most trait variation is additive as observed in yeast 139 To more broadly impact our understanding of quantitative trait variation these estimates should be calculated for every quantitative trait mapping and the data organized Evans et al Page 7 Trends Genet Author manuscript available in PMC 2022 February 23 Author Manuscript Author Manuscript Author Manuscript Author Manuscript in a central repository In this way we can make more significant inferences about the loci underlying quantitative trait variation Central data repositories like WormQTL2i and CeNDRii can facilitate these analyses 111116 Genetic architectures of quantitative traits can be affected when a single gene underlies multiple trait differences pleiotropy 140 and the varying contributions of genetic interactions among QTL epistasis In C elegans we have evidence of pleiotropic QTGs in amx2 mab23 nath10 nict1 npr1 nurf1 scb1 and top2 17183741485051687593141 Many of these pleiotropic genes affect life history traits or toxin responses The gene scb1 for example underlies variation in responses to amsacrine bleomycin carmustine and cisplatin demonstrating that a single gene can affect sensitivities to multiple chemotherapeutics 6768 Effects of epistatic loci on phenotypic variation are more difficult to define as most of the QTL detected so far appear to be largely additive 5456666980 Although this result is consistent with what is observed in many other species 139142146 most mapping panels are underpowered to detect epistatic loci Despite this obstacle several cases of epistasis have been reported in C elegans 195661636667828487104 Although the current tools available to the quantitative genetics community are still best suited to identify single largeeffect QTVs 138 these examples of more complex architectures suggest that we are beginning to fill in the gap in our understanding of quantitative trait variation Additionally as the number of QTGs and QTVs grow we can apply these results to investigations of the C elegans natural ecology and niche to understand better the roles and tradeoffs that pleiotropy and epistasis have on evolution of this species Concluding remarks Better tools and newer technologies have led to an increase in the number of QTL detected and QTVs validated in C elegans over the past decade These discoveries have led to a better understanding of the molecular mechanisms underlying quantitative trait variation Importantly by synthesizing a large experimentally validated dataset of QTGs and QTVs we can begin to learn more about how traits can evolve in natural populations see Outstanding questions Although we can gain significant insights from studying C elegans it remains to be investigated how and if these conclusions can be applied more broadly to nonselfing species that lack the strong influence of genetic drift and linkage disequilibrium caused by selfing Furthermore we need to learn more about the ecological context of this species so we can also learn to emulate the natural conditions in the laboratory and test the effects of natural alleles empirically 125147 The applications of QTGs and QTVs to knowledge about its niche and direct sources of selection will be critical to understand the tempo and mode of evolution at a mechanistic level Regardless in the continuing quest to connect QTL to specific QTVs the implementation of newer more powerful mapping methods like BSA and mpRILs will likely add to our current knowledge of the molecular mechanisms underlying quantitative trait variation Supplementary Material Refer to Web version on PubMed Central for supplementary material Evans et al Page 8 Trends Genet Author manuscript available in PMC 2022 February 23 Author Manuscript Author Manuscript Author Manuscript Author Manuscript Acknowledgments We would like to thank Jan Kammenga Lisa van Sluijs Robyn Tanny and Sam Widmayer for helpful comments on the manuscript ECA and KSE received support from the NSFSimons Center for Quantitative Biology at Northwestern University awards Simons FoundationSFARI 597491RWC and the National Science Foundation 1764421 ECA also received support from a National Science Foundation CAREER Award KSE also received support from the Cell and Molecular Basis of Disease Training grant T32GM008061 PTM received support from NIH R01GM114170 MHW was supported by NIH R01AA026658 MGS was supported by NWO domain Applied and Engineering Sciences VENI grant 17282 Glossary Broadsense heritability the total fraction of trait variation explained by genetic variation in a test population Bulksegregant analysis BSA a QTL mapping method in which pools of recombinant individuals are wholegenome sequenced after phenotypic selection to identify loci using allele frequency skews Epistasis interactions between alleles that cause phenotypic effects greater than observed for the individual alleles alone Expression QTL eQTL transcript abundances are quantitative traits that can be mapped in recombinant or natural populations These QTL can be divided into two types by whether the physical position gene in the expression trait is nearby local or far away distant from the QTL position Genomewide association GWA mapping a quantitative trait mapping method where genetic markers segregating across a wild population are correlated with phenotypic variation in that same population Genetic causality experimental determination of a direct role between a genetic difference and a phenotypic difference Haplotype a genomic region with linked allelic variation Isotype a collection of wild strains typically from the same geographic location that share greater than 9997 of their genetic variants Linkage mapping a quantitative trait mapping method where genetic markers segregating across a recombinant line panel are correlated with phenotypic variation in that same panel Mediation analysis Evans et al Page 9 Trends Genet Author manuscript available in PMC 2022 February 23 Author Manuscript Author Manuscript Author Manuscript Author Manuscript determination of a role of an intermediate variable mediator in a direct effect process eg the mediating role of gene expression variation in the direct effect of genetic variation on phenotypic variation in a different trait Multiparent recombinant inbred lines mpRIL a collection of homozygous strains generated after inbreeding recombinants from a cross between more than two genetically divergent parent strains Can be used for linkage mapping Narrowsense heritability the fraction of trait variation explained by additive genetic variation in a test population Nearisogenic line NIL a strain that harbors a region of the genomes from one genetic background in the presence of a different genetic background Pleiotropy the effect of a single allele on multiple distinct traits Quantitative trait gene QTG a gene in which genetic variation has been shown to directly impact phenotypic variation Quantitative trait locus QTL a genomic interval in which genetic variation has been shown to be correlated with phenotypic variation Quantitative trait variant QTV a variant eg singlenucleotide or insertiondeletion variant that has been shown to directly impact phenotypic variation Recombinant inbred lines RILs a collection of 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biologists use model organisms in laboratory experiments Typically once individuals are isolated from the wild reference strains are defined and grown in the laboratory for many generations Although laboratory environments are created to optimize growth this novel environment nevertheless is a strong selective force that can confound interpretations of experiments relevant to evolutionary biologists typically interested in natural traits Therefore it is useful to identify the beneficial QTVs that are responsible for adaptation to the laboratory so that their influence can be controlled Additionally these QTVs can be used to study the molecular mechanisms of adaptive evolution In C elegans many of these genetic changes can be identified because of a lucky historical accident 115 The reference strain N2 which is used by the majority of C elegans researchers was grown in the lab for hundreds of generations over the decade before methods of longterm cryopreservation were developed and N2 was cryopreserved Before that time a culture of the N2 ancestor strain was grown independently for over five decades and eventually cryopreserved as the strain called LSJ2 Because of the selffertilizing reproduction mode each of the laboratory mutations that occurred in the N2 or LSJ2 lineages were readily fixed and can be identified by sequencing these strains Approximately 300 variants distinguish these two strains These two strains were used to demonstrate that a QTV in the npr1 gene originally identified as a natural genetic variant that regulates feeding behavior arose after isolation from the wild and increased the fitness of the N2 strain in laboratory conditions 84 Mapping of phenotypic differences between the N2 and LSJ2 strains using a RIL panel generated between these two strains led to the identification of a number of additional beneficial QTVs in the glb5 nurf1 rcan1 srg36 and srg37 genes 18448495141148 These QTVs affect a number of behavioral developmental and reproductive traits from feeding behaviors on bacterial lawns to behavioral and developmental responses to pheromones to reproductive output and lifespan This work demonstrates the immense effects laboratory growth can have on animals and is important to consider when using laboratory strains to map natural trait differences Evans et al Page 18 Trends Genet Author manuscript available in PMC 2022 February 23 Author Manuscript Author Manuscript Author Manuscript Author Manuscript Box 2 From QTL to validated QTG or QTV Most quantitative genetics mappings detect QTL but progress often stops when QTL cannot be narrowed nor validated to discover specific QTG Although this process to determine genetic causality is not easy several genetic tools have enabled many C elegans QTL to be validated at the level of QTG and even QTV for a variety of quantitative traits see Table 1 and Figure 1 in main text Most C elegans studies validate and narrow QTL using NILs 417203436374042445061636567697174 768184868790929395100101104149 Any differences in phenotype between the NIL and the parental strain with the same genetic background can be attributed to the introgression of the QTL or the interaction of the introgression with the genetic background from the opposite genotype If a NIL validates the QTL effect several approaches exist to narrow the interval to a list of candidate genes to test for genetic causality First knowledge about predicted gene functions is commonly used to identify candidate genes 63941657586101108 Second researchers often prioritize genes with variants in the coding sequence that are predicted to have an impact on gene function 61820374165677076929398101150 Finally genes with expression variation even if there are no variants in the coding sequence can be prioritized as candidate genes 6676873 Because causal relationships between genetic variation and phenotypic variation require empirical tests of necessity and sufficiency specific genes or variants must be tested Although it is tempting to use gene deletions or RNAi in the laboratory strain background to test for phenocopy of a quantitative trait these techniques are biased towards the N2 strain background and assume that lossoffunction variation has caused the trait difference With the establishment of CRISPRCas9 genome editing genespecific deletions can be created for quantitative complementation or reciprocal hemizygosity tests to establish a causal QTG 61867 Alternatively allele replacement experiments can be used to edit a single nucleotide in any genetic background and identify a causal QTV 1867707476100 see Table 1 and Figure 1 in main text Evans et al Page 19 Trends Genet Author manuscript available in PMC 2022 February 23 Author Manuscript Author Manuscript Author Manuscript Author Manuscript Box 3 Fixed mutations in mapping panels One of the benefits of C elegans is the availability of a plethora of defined mutant strains covering most of known N2 reference genome genes from the Caenorhabditis Genetics Center 151 These characterized mutations can be used to create a RIL population to discover modifier loci present in genetic backgrounds different from the laboratory reference strain as reviewed by 152 This strategy has been successfully applied to create populations used to identify glb5 as a modifier of npr1dependent trait differences 85 nath10 as a modifier of vulval induction and germ line development differences 37 amx2 as a modifier of Ras pathway signaling differences 50 and plep1 as a modifier of malemale copulatory plugging differences 92 The use of fixed mutations in different genetically diverse strains has shown that the effects of a mutation are dependent on genetic background This result suggests that genetic modifiers are common across different natural strains For example it was shown that the AB1 strain was less sensitive to Ras pathway perturbations than the commonly used laboratory strain N2 153 This trait difference was mapped to nath10 where further validation in the N2 strain showed that a sensitizing mutation alone did not affect vulval induction but the effect could be revealed only in the presence of a receptor tyrosine kinase let23sy1 mutation 37 Evans et al Page 20 Trends Genet Author manuscript available in PMC 2022 February 23 Author Manuscript Author Manuscript Author Manuscript Author Manuscript Box 4 Experimental evolution and QTVs Experimental evolution uses controlled laboratory manipulations to investigate evolutionary processes It can test the role of selection and genetic drift on changes in allele frequencies under specific environmental conditions C elegans is particularly useful for experimental evolution because its short generation time approximately 3 days and high brood size greater than 200 offspring per individual enables multiple generation experiments with large population sizes After identification of a QTV one common use of experimental evolution in C elegans is to test the role of selection in the spread or loss of QTVs in a population 1837708695141148154156 Typically two strains with homozygous genotypes for alternate alleles compete against each other for multiple generations in specific environments By measuring the change in allele frequencies over the course of an experiment the relative fitness of the two strains can be estimated Such experiments have been used to demonstrate that mutations that are fixed during laboratory growth increase the fitness of reference strains in laboratory environments Box 1 These measurements can also be used to study the role that environment plays on fitness effects of QTVs By comparing the relative fitness of two strains in different environments empirical evidence can support the role of selection in the spread of alleles For example these experiments have been used to show that the increased use of anthelmintic drugs are responsible for the spread of resistance alleles 70154 Similar experiments have provided evidence that balancing selection could maintain different alleles that explain alternative foraging strategies induced by pheromones released by conspecifics 86 By modifying the distribution of food a QTV could either be beneficial or detrimental leading the authors to propose that environmental heterogeneity in C elegans natural environments creates balancing selection at this locus Interestingly many regions of the C elegans genome show signatures of balancing selection suggesting many loci could follow similar patterns 10 Additionally genetic manipulation can be used in these experiments to test specific evolutionary hypotheses One elegant example took advantage of genotypes with different outcrossing rates 157 exposing C elegans strains to pathogens that killed their hosts in a matter of days Although the QTVs responsible for resistance to these pathogens were not identified these and subsequent experiments 158159 provided support that recombination between QTVs is important for adaptation to novel conditions The combination of highthroughput sequencing with competition experiments also known as evolve and resequence has been widely used in other species to identify regions of the genome with adaptive alleles The use of evolve and resequence has lagged in C elegans likely because of its partially selfing mating system but recent work has spurred development of this approach in Caenorhabditis nematodes reviewed in 160161 Recently a technique called ceXQTL was developed to map QTVs that affect fitness in specific conditions 73 The ceXQTL technique uses bulk selection on Evans et al Page 21 Trends Genet Author manuscript available in PMC 2022 February 23 Author Manuscript Author Manuscript Author Manuscript Author Manuscript millions of recombinant animals that compete against each other for multiple generations QTVs that segregate between two strains of C elegans and influence fitness in laboratory conditions were identified This technique and other types of evolve and resequence approaches will likely become more popular with C elegans researchers in the future Evans et al Page 22 Trends Genet Author manuscript available in PMC 2022 February 23 Author Manuscript Author Manuscript Author Manuscript Author Manuscript Outstanding questions Can larger and more diverse cross panels improve our understanding of trait variation across natural populations What is the contribution of regulatory variation to quantitative trait variation Will mapping intermediate phenotypic traits eg metabolites and gene expression in combination with techniques such as mediation analysis define more QTG and lead to specific regulatory variant discovery How large is the role of epistasis in quantitative trait variation and can these results impact estimates of missing heritability Are pleiotropic loci common and how strongly do they influence evolutionary processes What is the role of specific environments niches and functional redundancy in expanded gene families in the selection of QTGs How can QTGs and QTVs be combined with the ecological context and niche to understand evolutionary processes Do the evolutionary conclusions inferred from C elegans hold true for other nonselfing species Evans et al Page 23 Trends Genet Author manuscript available in PMC 2022 February 23 Author Manuscript Author Manuscript Author Manuscript Author Manuscript Highlights Innovations in quantitative trait loci mapping and genome editing have led to the discovery and validation of 37 genes and variants underlying phenotypic variation in C elegans Numerous recombinant panels and a large collection of wild strains make C elegans a formidable model to understand quantitative trait variation Most of the identified quantitative trait genes have paralogs providing evidence that gene duplication events are important for shaping quantitative traits Pleiotropy is relatively common among C elegans quantitative trait genes Evans et al Page 24 Trends Genet Author manuscript available in PMC 2022 February 23 Author Manuscript Author Manuscript Author Manuscript Author Manuscript Figure 1 Key figure Overview of quantitative trait gene QTG chromosome positions The colors represent the mapping techniques that were used for quantitative trait loci QTL mapping bulksegregant analysis BSA orange linkage mapping pink genome wide association GWA mapping green linkage and GWA mapping purple The genes in italics represent the QTGs and genes in bold italics represent the QTVs ppw1 was also mapped using linkage mapping 104 set24 was detected by combining linkage mapping and BSA 20 The role of piRNAs was tested using a prg1 deletion 93 srg37 was also mapped using GWA mapping 39 Figure was created using ggplot2 in R Evans et al Page 25 Trends Genet Author manuscript available in PMC 2022 February 23 Author Manuscript Author Manuscript Author Manuscript Author Manuscript Figure 2 Powerful approaches to quickly identify the genes and molecular mechanisms underlying quantitative trait variation A A schematic of a hypothetical multiparent recombinant cross is shown The eight colored nematodes along the outside represent the parental strains in the cross The genome of one hypothetical line is shown in the center of the cross with bars to represent chromosomes colored by the genetic background retained from each parental strain B A mediation model where phenotypic variation animal size between strains color can be explained by variation in gene expression caused by a genetic variant This figure was created using BioRendercom Evans et al Page 26 Trends Genet Author manuscript available in PMC 2022 February 23 Author Manuscript Author Manuscript Author Manuscript Author Manuscript Author Manuscript Author Manuscript Author Manuscript Author Manuscript Evans et al Page 27 Key Table Table 1 List of QTGs and QTVs discovered in C elegans a Phenotype Mapping type QTG QTV Refs Natural wild isolate alleles Genetic perturbation vulval induction gene expression Linkage mapping amx2 NA 5051 PolyQ aggregation Linkage mapping atg5 NA 150 Drug response albendazole Association mapping ben1 NA 70 Drug response arsenic trioxide Association mapping linkage mapping dbt1 C78S 76 Orsay virus sensitivity Association mapping drh1 Deletion 101 Dauer formation Linkage mapping eak3 Deletion 41 Aggregation bordering Linkage mapping exp1 NA 90 Drug response abamectin pathogen response Streptomyces avermitilis Association mapping linkage mapping glc1 Deletion 865 Drug response proprionate Association mapping glct3 G19stop F19fs 74 Matricidal hatching Linkage mapping kcnl1 V530L 100 Male tail morphology Linkage mapping mab23 C38F 4748 Embryonic lethality Linkage mapping peel1 zeel1 Deletion 113 Nictation Linkage mapping piRNA NA 93 Malemale plugging behavior Linkage mapping plep1 V278D 92 Copulatory plugging embryonic lethality Linkage mapping plg1 TE insertion 96 Telomere length Association mapping pot2 NA 108 RNAi sensitivity BSA linkage mapping ppw1 NA 103104 Competitive fitness BSA rcan1 CNV 95 Drug response amsacrine bleomycin bortezomib carmustine cisplatin etoposide puromycin silver gene expression Linkage mapping scb1 NA 6768 Temperatureinduced sterility BSA linkage mapping set24 Deletion 20 Drug response zinc Association mapping linkage mapping sqst5 Deletion 6 Pheromone response dauer formation Association mapping srg37 Deletion 39 Pheromone sensitivity Linkage mapping srx43 NA 86 Drug response abamectin stress resistance H2O2 fitness gene expression BSA sti1 NA 73 Embryonic lethality BSA sup35 pha1 NA 98 Drug response etoposide amsacrine Association mapping linkage mapping top2 Q797M 75 Temperature response body size Linkage mapping tra3 F96L 38 Food foraging response Linkage mapping tyra3 NA 81 Laboratoryadapted alleles Trends Genet Author manuscript available in PMC 2022 February 23 Author Manuscript Author Manuscript Author Manuscript Author Manuscript Evans et al Page 28 Phenotype Mapping type QTG QTV Refs Genetic perturbation movement body size Linkage mapping col182 Deletion 49 Oxygen sensing oxygen response Linkage mapping glb5 Insertion 8485 Vulval induction Linkage mapping nath10 I746M 37 Clumping pathogen avoidance Pseudomonas aeruginosa Staphylococcus aureus pathogen response Bacillus thuringiensis fecundity body size oxygen response Linkage mapping npr1 V215F 176364848594 Reproductive timing lifespan dauer formation growth rate fecundity Linkage mapping nurf1 Deletion 1819 Competitive fitness BSA rcan1 CNV 95 Dauer formation Linkage mapping scd2 G985R G1174E 43 Dauer formation Linkage mapping srg36 srg37 Deletion 44 aAbbreviations BSA bulksegregant analysis CNV copy number variation NA not available QTG quantitative trait genes QTV quantitative trait variants TE transposable elements Trends Genet Author manuscript available in PMC 2022 February 23 Author Manuscript Author Manuscript Author Manuscript Author Manuscript Evans et al Page 29 Table 2 Overview of QTL mapping populations a Genetic background Parental strains Refs Recombinant inbred lines RILs N2xBO N2xBO 28 RC301xBO RC301xBO 35 CB4857xBO DR1345xRW7000 33 N2xCB4856 N2xCB4856 5272 N2xCB4853 N2xDR1350 14 N2xCB4856 AX613xCB4856 85 N2xCB4856 CB5362xCB4856 tra2ar221 xol1y9 105 N2xLSJ2 CX12311xLSJ2 44 N2xAB1 JU605xJU606 37 AB2xCB4856 QG5xQX1199 92 N2xCB4856 MT2124xCB4856 50 MY14xCX12311 MY14xCX12311 86 N2xLSJ2 CX12311xLSJ2 18 MY10xJU1395 MY10xJU1395 20 N2xMY16 N2xMY16 42 JU1200xJU751 JU1200xJU751 41 Recombinant inbred advanced intercross lines RIAILs N2xCB4856 N2xCB4856 91113 N2xCB4856 QX1430xCB4856 5 Multiparent recombinant inbred lines mpRILs CeMEE CeMEE RILs 15 JU1511xJU1926xJU1931xJU1941 JU1511xJU1926xJU1931xJU1941 27 Introgression line populations NILs CB4856 N2 N2xCB4856 23 NILs CB4856 N2 QG613xQG590 QG614xQG591 102 CSS CB4856 N2 N2xCB4856 88 NILs BO CB4857 DR1345xRW7000 34 Wild isolates NA NA 10116 aAbbreviations CSS chromosome substitution strain NA not available QTL quantitative trait loci NIL nearisogenic line Trends Genet Author manuscript available in PMC 2022 February 23 From QTL to gene C elegans facilitates discoveries of the genetic mechanisms underlying natural variation Do QTL ao gene C elegans facilita as descobertas dos mecanismos genéticos subjacentes à variação natural Resumo Embora muitos estudos tenham examinado a variação de características quantitativas em muitas espécies apenas um pequeno número de genes e portanto mecanismos moleculares foram descobertos Sem esses dados podemos apenas especular sobre os processos evolutivos subjacentes à variação de características Aqui revisamos como a genética quantitativa e molecular no nematóide Caenorhabditis elegans levou à descoberta e validação de 37 genes de características quantitativas nos últimos 15 anos Usando esses dados podemos começar a fazer inferências sobre a evolução desses genes de traços quantitativos incluindo os papéis que codificam versus variações não codificantes expansão da família de genes variantes comuns versus raras pleiotropia e epistasia desempenham na variação de traços nesta espécie Descobrindo os mecanismos de variação de característica um gene de cada vez Já identificados diversos locis cujos efeitos diversas características medidas em gado plantações espéciesmodelo e humanos mas apenas um pequeno número de genes e mecanismos moleculares foram validados em qualquer espécie a literatura está repleta de numerosos exemplos de loci de traços quantitativos QTL que foram identificados mas genes e alelos específicos não foram validados usando manipulações genômicas precisas fazendo inferências sobre os mecanismos moleculares de suposições de variação de traços na melhor das hipóteses Há pouco mais de uma década o nematóide da lombriga Caenorhabditis elegans emergiu como uma potência para a descoberta de genes e variantes subjacentes à variação quantitativa de características 37 genes de traços quantitativos QTGs foram descobertos e validados usando edições genômicas precisas em origens genéticas definidas 24 variantes de traços quantitativos QTVs elucidando os mecanismos moleculares da variação de traços quantitativos Por que Celegans o O sistema de acasalamento hermafrodita o Estilo de vida de autofecundação o Variação em todo o genoma é relativamente baixa e as cepas homozigóticas são fáceis de construir o Facilmente cultivado em laboratório e possui um genoma compacto e definido em contraste com a maioria das outras espécies de metazoários Descobertas recentes das origens das espécies a estrutura do genoma e inferências de seu nicho natural definiram o contexto para ajudar a entender como a evolução moldou essa espécie A confluência dessas vantagens trouxe C elegans à vanguarda da genética quantitativa Inovações no mapeamento de ligação impulsionam a descoberta de genes e variantes Os mapeamentos genéticos quantitativos usam três abordagens complementares mapeamento de ligação análise bulksegregant BSA e mapeamento de associação ampla do genoma GWA BSA ferramenta rápida poderosa e eficaz para identificar QTL Mapeamento de ligação método mais popular para a detecção de QTL em C elegans GWAs mapeamento de associação ampla do genoma Nessa abordagem os investigadores aproveitam o poder estatístico para detectar QTL usando um grande número de linhagens recombinantes geradas a partir de um cruzamento entre duas ou mais cepas fenotipicamente e genotipicamente diversas Muitos QTGs foram descobertos usando três painéis recombinantes derivados da cepa Bristol adaptada em laboratório N2 e da cepa havaiana geneticamente diversa CB4856 O primeiro painel de 80 linhagens endogâmicas recombinantes RILs levou à descoberta do primeiro C elegans QTG em 2006 segundo painel de 239 linhagens intercruzadas avançadas endogâmicas recombinantes RIAILs foi criado esse esquema de intercruzamento criou mais eventos de recombinação e assim melhorou a resolução do mapeamento No entanto após a geração deste painel RIAIL os pesquisadores descobriram que muitas dessas linhagens contêm o alelo N2 no locus de incompatibilidade peel1 zeel1 no cromossomo I Além disso vários estudos descobriram que os alelos N2 derivados de laboratório dos genes npr1 glb5 nath10 e col182 têm fortes efeitos pleiotrópicos Para reduzir os efeitos da incompatibilidade genética entre as cepas N2 e CB4856 e o grande efeito pleiotrópico do alelo N2 npr1 Andersen e colegas geraram um segundo painel RIAIL no qual todas as 359 linhagens abrigam o alelo natural npr1 de CB4856 e uma inserção de transposon no gene peel1 Slide da figura 1 Nos últimos 10 anos 59 estudos de mapeamento de ligação descobriram 22 genes subjacentes a diferenças em uma ou mais características quantitativas O QTL pode ser validado e mapeado com precisão usando NILs e a causalidade genética pode ser testada usando a edição do genoma CRISPRCas9 de genes candidatos Juntos todos esses painéis N2xCB4856 levaram à descoberta de 16 QTGs 13 que fundamentam as características tais como respostas a toxinas nictação e sensibilidade a RNAi Um painel de isolado selvagem em expansão facilita as investigações da variação de características em toda a população Embora o mapeamento de ligação e o BSA tenham se mostrado ferramentas inestimáveis para os geneticistas quantitativos de C elegans a principal inovação da última década foi a introdução do mapeamento GWA O mapeamento GWA aproveita a amplitude da diversidade genética natural que existe entre indivíduos geneticamente distintos Como outras técnicas de mapeamento o mapeamento GWA visa identificar variantes funcionais que contribuem para a diversidade fenotípica A força dessa abordagem está em sua capacidade de alavancar a amplitude da variação fenotípica presente nas espécies para identificar QTVs comuns Um painel de isolado selvagem em expansão facilita as investigações da variação de características em toda a população O C elegans Natural Diversity Resource CeNDR cataloga e distribui todas as cepas selvagens e dados de variação do genoma O CeNDR continua sendo um recurso vital para a comunidade C elegans para facilitar os mapeamentos GWA e as análises genômicas populacionais A realização de estudos de mapeamento GWA em C elegans requer uma compreensão da composição genética da população de toda a espécie Os primeiros estudos para caracterizar a variação genética em C elegans em escala global descobriram grandes blocos de haplótipos compartilhados em quatro dos seis cromossomos O extenso desequilíbrio de ligação particularmente no centro dos cromossomos limita a resolução do QTL usando o mapeamento GWA O mapeamento de associação levou à descoberta de nove QTGs incluindo sete com QTVs que fundamentam a variação quantitativa do traço Em um desses exemplos uma deleção natural no gene do receptor de feromônio srg37 causou variação na resposta do feromônio dauer Esses exemplos e outros fornecem informações importantes sobre os caminhos e mecanismos moleculares que causam variação natural nas populações selvagens Slide da figura 2A Embora o mapeamento de ligação mapeamento BSA e GWA tenham tido um sucesso considerável mapeando QTL e QTGs cada abordagem de mapeamento tem suas desvantagens quando usada isoladamente Em alguns estudos uma combinação de mapeamento de ligação e GWA foi usada para estreitar intervalos genômicos analisando QTL que se sobrepõem entre os métodos Alternativamente os painéis de linha pura recombinante multiparental mpRIL Figura 2A tornaramse ferramentas genéticas quantitativas importantes em outros organismos modelo como camundongos Drosophila melanogaster e Arabidopsis thaliana QTGs e QTVs validados fornecem informações sobre a evolução Cada um dos 37 QTGs de C elegans descobertos nos últimos 15 anos revela individualmente mecanismos moleculares de como a diversidade fenotípica é moldada oferecendo pistas sobre como essa espécie evoluiu QTGs validados experimentalmente fornecem exemplos para conectar a variação de traços quantitativos à compreensão dos princípios evolutivos A alta confiança nesses QTGs garante que quaisquer conclusões tiradas desses dados não sejam influenciadas por falsos positivos QTL Ao investigar esses genes podemos começar a fazer suposições sobre as variantes mais comumente subjacentes à variação de características importantes para a mudança evolutiva QTVs validados conferem vantagens de adequação em ambientes específicos Variantes comuns Dos 24 QTVs identificados em C elegans 11 são comuns ou estão presentes em mais de 5 dos isotipos Desses 11 QTVs três foram identificados usando apenas o mapeamento GWA quatro usando apenas o linkage mapping e quatro usando os dois métodos de mapeamento Por exemplo vários alelos comuns foram correlacionados com diferenças de resposta a toxinas Este resultado sugere que esses alelos foram mantidos ao longo de muitas gerações e os custos de aptidão previstos para abrigar tais alelos provavelmente serão pequenos Variantes raras Os 13 QTVs restantes são alelos raros na população de C elegans e foram identificados exclusivamente por meio de linkage mapping o que atende às expectativas sobre o poder de detectar esses loci quando as cepas parentais abrigam variantes raras Esses QTVs raros se enquadram em dois grupos nove alelos derivados de laboratório e quatro alelos detectados em populações selvagens Os alelos raros selvagens são associados a efeitos prejudiciais graves em traços de história de vida A maioria dos QTGs validados são agrupados em famílias gênicas Foi levantada a hipótese de que genes parálogos ou genes que fazem parte de uma família de genes funcionalmente redundantes podem oferecer uma fonte de variação entre as populações porque os genes podem divergir sem afetar fortemente a função Devido à coleção sempre crescente de cepas de C elegans a disponibilidade rapidamente crescente de genomas de nematoides de alta qualidade e desenvolvimentos recentes em biologia evolutiva e genômica comparativa podemos começar a determinar com que frequência a variação de característica quantitativa é causada por diferenças nas famílias de genes Dos 37 QTGs identificados em C elegans 27 genes tinham um ou mais parálogos fornecendo fortes dados empíricos de que à medida que os genes aumentam em número de cópias eles podem divergir funcionalmente e causar características variação Em contraste estimase que cerca de 6000 genes ou 32 do genoma tenham pelo menos um parálogo indicando um enriquecimento altamente significativo de QTGs pertencentes a uma família de genes Este resultado suporta o modelo de divergência de duplicação onde novos genes vêm de cópias de genes préexistentes Os QTGs validados que são membros de famílias de genes sugerem que a variação de características quantitativas provavelmente está focada em regiões hiperdivergentes e deve ser caracterizada usando sequenciamento de genoma de leitura longa para definir genes específicos de cepas ou espécies Variações não codificantes são responsáveis pelas diferenças de características no nível do organismo Os QTVs mais conhecidos são variantes de codificação de proteínas de grande efeito que causam diferenças fenotípicas No entanto a variação não codificante pode ser mais importante evolutivamente Muitas vezes não está claro como essas diferenças de expressão gênica se traduzem em variação de característica C elegans oferece seis exemplos eak3 exp1 prg1 scb1 srx43 e tyra3 nos quais a variação não codificante é declarada correlacionada com diferenças de características Estudos de expressão gênica de QTL eQTL descobriram milhares de genes diferencialmente expressos que são amplamente controlados por fatores genéticos Slide figura 2B Técnicas como análise de mediação podem fazer conexões estatísticas entre variação genética variação em uma característica intermediária como expressão gênica e variação em fenótipos complexos em nível de organismo Figura 2B Esta técnica foi usada com sucesso para sugerir que o scb1 afeta as respostas a vários quimioterápicos e que o sqst5 afeta as respostas diferenciais ao zinco exógeno Essa técnica é especialmente poderosa para estabelecer genes candidatos cuja expressão é controlada por loci distantes do gene regulado já que a maioria das técnicas de mapeamento fino considera apenas genes dentro do intervalo de confiança do QTL Portanto uma análise de todo o genoma da expressão gênica em isolados selvagens ou outros mpRILs poderia fornecer um recurso sem precedentes para estudar o papel da variação regulatória em características quantitativas Os estudos de mapeamento de C elegans estão apenas começando a definir a complexidade de muitos traços quantitativos Embora muitos estudos genéticos quantitativos iniciais em C elegans identificassem principalmente loci únicos e de grande efeito os avanços tecnológicos juntamente com a coleta de isolados selvagens mais geneticamente distintos levaram a aumentos no poder de detectar mais QTL com efeitos cada vez menores Muitos traços quantitativos mapeiam pelo menos dois loci independentes e alguns traços têm cinco ou mais QTL Um estudo de mapeamento de QTL em grande escala de respostas de nematóides a 16 toxinas diversas identificou 82 QTL de 47 características um terço dessas características mapeadas para dois ou mais loci Surpreendentemente a maioria desses QTL teve tamanhos de efeito pequenos explicando menos de 10 da variação fenotípica no painel de mapeamento Vários estudos usaram NILs para validar loci de pequeno efeito demonstrando que pequenos efeitos podem ser estudados em C elegans com as ferramentas certas e um ensaio sensível A fração total de variação de característica explicada pela variação genética em uma população pode ser estimada calculandose a herdabilidade de sentido amplo Quando comparada com uma estimativa de herdabilidade de sentido restrito que responde por todos os efeitos aditivos a chamada herdabilidade ausente pode ser estimada como a diferença entre o efeito genético total e os efeitos aditivos Uma explicação para essa discrepância pode ser explicada por efeitos não aditivos incluindo epistasia Para impactar mais amplamente nossa compreensão da variação de característica quantitativa essas estimativas devem ser calculadas para cada mapeamento de característica quantitativa e os dados organizados em um repositório central As arquiteturas genéticas de características quantitativas podem ser afetadas quando um único gene é a base de múltiplas diferenças de características pleiotropia 140 e as contribuições variadas de interações genéticas entre QTL epistasis Em C elegans temos evidências de QTGs pleiotrópicos em amx2 mab23 nath10 nict1 npr1 nurf1 scb1 e top2 Muitos desses genes pleiotrópicos afetam características da história de vida ou respostas a toxinas Os efeitos dos loci epistáticos na variação fenotípica são mais difíceis de definir pois a maioria dos QTL detectados até agora parecem ser amplamente aditivos Embora esse resultado seja consistente com o que é observado em muitas outras espécies a maioria dos painéis de mapeamento tem pouca capacidade para detectar loci epistáticos Apesar desse obstáculo vários casos de epistasia foram relatados em C elegans À medida que o número de QTGs e QTVs cresce podemos aplicar esses resultados às investigações da ecologia natural e do nicho de C elegans para entender melhor os papéis e compensações que a pleiotropia e a epistasia têm na evolução dessa espécie Conclusões Melhores ferramentas e novas tecnologias levaram a um aumento no número de QTLs detectados e QTVs validados em C elegans na última década Essas descobertas levaram a uma melhor compreensão dos mecanismos moleculares subjacentes à variação de traços quantitativos É importante ressaltar que ao sintetizar um grande conjunto de dados validado experimentalmente de QTGs e QTVs podemos começar a aprender mais sobre como as características podem evoluir em populações naturais Embora possamos obter insights significativos com o estudo de C elegans resta investigar como e se essas conclusões podem ser aplicadas de forma mais ampla a espécies não autofecundadas que carecem da forte influência da deriva genética e do desequilíbrio de ligação causado pela autofecundação Além disso precisamos aprender mais sobre o contexto ecológico dessa espécie para que também possamos aprender a emular as condições naturais em laboratório e testar empiricamente os efeitos dos alelos naturais As aplicações de QTGs e QTVs ao conhecimento sobre seu nicho e fontes diretas de seleção serão fundamentais para entender o ritmo e o modo de evolução em nível mecanicista Independentemente disso na busca contínua de conectar QTL a QTVs específicos a implementação de métodos de mapeamento mais novos e poderosos como BSA e mpRILs provavelmente aumentará nosso conhecimento atual dos mecanismos moleculares subjacentes à variação de traços quantitativos NOME DO ALUNO NOME DA DISCIPLINA Dezembro de 2022 Introdução C elegans Diversos QTL quantiative trait loci intervalo genômico no qual a variação genética demonstrou estar correlacionada com a variação fenotípica com efeitos diversas espécies Nº de genes e mecanismos moleculares validados 37 QTGs quantitative trait gene genes de características quantitativas descobertos e validados em Celegans sendo 24 QTVs quantitative trait variant uma variante que demonstrou afetar diretamente a variação fenotípica Inferências sobre a evolução desses genes de traços quantitativos Objetivo Revisar como a genética molecular e quantitativa aplicadas ao nematoide Caenorhabditis elegans C elegans levaram a descoberta e validação de 37 genes de traços quantitativos nos últimos 15 anos Inovações no mapeamento de ligação impulsionam a descoberta de genes e variantes Mapeamento de ligação O método mais popular para a detecção de QTL em C elegans Bulksegregant Analysis BSA Ferramenta rápida poderosa e eficaz para identificar QTLs Genomewide Association GWA Mapping Visa identificar variantes funcionais que contribuem para a diversidade fenotípica Inovações no mapeamento de ligação impulsionam a descoberta de genes e variantes Primeiro painel de 80 linhagens endogâmicas recombinantes 2006 2009 Painel de 239 linhagens intercruzadas avançadas endogâmicas recombinantes RIAILs 2015 2º painel RIAIL 359 linhagens com alelo natural npr1 e inserção de transposon em peel1 É possível detectar QTLs usando um grande número de linhagens recombinantes geradas a partir de um cruzamento entre duas ou mais cepas fenotipicamente e genotipicamente diversas Muitos QTGs foram descobertos usando três painéis recombinantes derivados da cepa Bristol adaptada em laboratório N2 e da cepa havaiana geneticamente diversa CB4856 Figurachave visão geral das posições cromossômicas do gene de traço quantitativo QTG As cores representam as técnicas de mapeamento que foram usadas para o mapeamento de locos de características quantitativas QTL análise bulksegregant BSA laranja mapeamento de ligação rosa mapeamento de associação ampla do genoma GWA verde ligação e mapeamento GWA roxo Os genes em itálico representam os QTGs e os genes em negrito e itálico representam os QTVs ppw1 também foi mapeado usando mapeamento de ligação 104 set24 foi detectado combinando mapeamento de ligação e BSA 20 O papel dos piRNAs foi testado usando uma deleção prg1 93 srg37 também foi mapeado usando mapeamento GWA 39 A figura foi criada usando ggplot2 em R Um painel de isolado selvagem em expansão facilita as investigações da variação de características em toda a população A principal inovação da última década foi a introdução do mapeamento GWA Um painel de isolados selvagens em expansão facilita as investigações da variação de características em toda a população cataloga e distribui todas as cepas selvagens e dados de variação do genoma Os primeiros estudos para caracterizar a variação genética em C elegans em escala global descobriram grandes blocos de haplótipos compartilhados em quatro dos seis cromossomos O extenso desequilíbrio de ligação particularmente no centro dos cromossomos limita a resolução do QTL usando o mapeamento GWA O mapeamento de associação levou à descoberta de nove QTGs incluindo sete com QTVs que fundamentam a variação quantitativa do traço Em um desses exemplos uma deleção natural no gene do receptor de feromônio srg37 causou variação na resposta do feromônio dauer Esses exemplos e outros fornecem informações importantes sobre os caminhos e mecanismos moleculares que causam variação natural nas populações selvagens A Um esquema de um hipotético cruzamento recombinante multiparental é mostrado Os oito nematóides coloridos ao longo do lado de fora representam as cepas parentais no cruzamento O genoma de uma linha hipotética é mostrado no centro da cruz com barras para representar os cromossomos coloridos pelo background genético retido de cada cepa parental Figura 2 Abordagens poderosas para identificar rapidamente os genes e mecanismos moleculares subjacentes à variação quantitativa de características QTGs e QTVs validados fornecem informações sobre a evolução Cada um dos 37 QTGs de C elegans descobertos nos últimos 15 anos revela individualmente mecanismos moleculares de como a diversidade fenotípica é moldada oferecendo pistas sobre como essa espécie evoluiu QTGs validados experimentalmente fornecem exemplos para conectar a variação de traços quantitativos à compreensão dos princípios evolutivos A alta confiança nesses QTGs garante que quaisquer conclusões tiradas desses dados não sejam influenciadas por falsos positivos QTL QTVs validados conferem vantagens de adequação em ambientes específicos Variantes comuns com pequenos efeitos Dos 24 QTVs 11 são comuns ou estão presentes em mais de 5 dos isótipos 3 identificados com GWAS apenas 4 identificados com linkage mapping apenas 4 identificados com ambos os métodos Variantes rara com grandes efeitos 13 QTVs são alelos raros Identificados com linkage mapping apenas 9 alelos derivados de laboratório 4 alelos detectados em populações selvagens A maioria dos QTGs validados são agrupados em famílias gênicas Foi levantada a hipótese de que genes parálogos ou genes que fazem parte de uma família de genes funcionalmente redundantes podem oferecer uma fonte de variação entre as populações É possicvel começar a determinar com que frenquência as QTVs são causadas por diferença nas famílias gênicas o Nº de cepas de C elegans o Disponibilidade de genomas de nematoides de alta qualidade o Desenvolvimentos recentes em biologia evolutiva e genômica comparativa Dos 37 QTGs identificados em C elegans 27 genes tinham um ou mais parálogos Estimase que cerca de 6000 genes ou 32 do genoma tenham pelo menos um parálogo Este resultado suporta o modelo de divergência de duplicação onde novos genes vêm de cópias de genes préexistentes Variações não codificantes são responsáveis pelas diferenças de características no nível do organismo Os QTVs mais conhecidos são variantes de codificação de proteínas de grande efeito que causam diferenças fenotípicas muitas vezes não está claro como essas diferenças de expressão gênica se traduzem em variação de característica C elegans oferece seis exemplos eak3 exp1 prg1 scb1 srx43 e tyra3 nos quais a variação não codificante é declarada correlacionada com diferenças de características Estudos de expressão gênica de QTL eQTL descobriram milhares de genes diferencialmente expressos que são amplamente controlada por fatores genéticos B Um modelo de mediação onde a variação fenotípica tamanho do animal entre cepas cor pode ser explicada pela variação na expressão gênica causada por uma variante genética Esta figura foi criada usando BioRendercom Figura 2 Abordagens poderosas para identificar rapidamente os genes e mecanismos moleculares subjacentes à variação quantitativa de características Os estudos de mapeamento de C elegans estão apenas começando a definir a complexidade de muitos traços quantitativos Os avanços tecnológicos juntamente com a coleta de isolados selvagens mais geneticamente distintos levaram a aumentos no poder de detectar mais QTL com efeitos cada vez menores Um estudo de mapeamento de QTL em grande escala de respostas de nematóides a 16 toxinas diversas identificou 82 QTL de 47 características um terço dessas características mapeadas para dois ou mais loci A fração total de variação de característica explicada pela variação genética em uma população pode ser estimada calculandose a herdabilidade de sentido amplo As arquiteturas genéticas de características quantitativas podem ser afetadas quando um único gene é a base de múltiplas diferenças de características pleiotropia Muitos desses genes pleiotrópicos afetam características da história de vida ou respostas a toxinas A maioria dos painéis de mapeamento tem pouca capacidade para detectar loci epistáticos Destaques Inovações no mapeamento quantitativo de loci de características e edição do genoma levaram à descoberta e validação de 37 genes e variantes subjacentes à variação fenotípica em C elegans Numerosos painéis recombinantes e uma grande coleção de cepas selvagens fazem de C elegans um modelo formidável para compreender a variação de características quantitativas A maioria dos genes de traços quantitativos identificados tem parálogos fornecendo evidências de que os eventos de duplicação de genes são importantes para moldar os traços quantitativos A pleiotropia é relativamente comum entre os genes de características quantitativas de C elegans