Correlations of Genotype with Climate Parameters Suggest <i>Caenorhabditis elegans</i> Niche Adaptations

Evans, Kathryn; Zhao, Yuehui; Brady, Shannon C.; Long, Lijiang; McGrath, Patrick T.; Andersen, Erik C.

doi:10.1534/g3.116.035162

Cited by 30 publications

(23 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Especially the genome-wide N2 x CB4856 IL panel, and a set of chromosome-substitution lines have been used (30, 103). Currently, the C. elegans field increasingly makes use of Genome-Wide Association Studies (GWAS) and wild isolates (32,33,40,91). WormQTL2 is currently developing links to genetic variants in QTL regions through the C. elegans Natural Diversity Resource (CeNDR) (33).…”

Section: Discussionmentioning

confidence: 99%

WormQTL2: an interactive platform for systems genetics inCaenorhabditis elegans

Snoek

Sterken

Hartanto

et al. 2019

Preprint

View full text Add to dashboard Cite

18Quantitative genetics provides the tools for linking polymorphic loci (QTLs) to trait 19 variation. Linkage analysis of gene expression is an established and widely applied 20 method, leading to the identification of expression quantitative trait loci (eQTLs). (e)QTL 21 detection facilitates the identification and understanding of the underlying molecular 22 components and pathways, yet (e)QTL data access and mining often is a bottleneck. Here 23 we present WormQTL2 (www.bioinformatics.nl/WormQTL2/), a database and platform 24 for comparative investigations and meta-analyses of published (e)QTL datasets in the 25 model nematode worm C. elegans. WormQTL2 integrates six eQTL studies spanning 11 26 conditions as-well-as over 1000 traits from 32 studies and allows experimental results to 27 be compared, reused, and extended upon to guide further experiments and conduct 28 systems-genetic analyses. For example, one can easily screen a locus for specific cis-eQTLs 29 that could be linked to variation in other traits, detect gene-by-environment interactions 30 by comparing eQTLs under different conditions, or find correlations between QTL 31 profiles of classical traits and gene expression.32 100 (2,3,13,23,30,34,41,47,49,(53)(54)(55)(56)(57)(58)(59)61,76,(80)(81)(82)(83)(84)(85)(86)(87)(88)(89)(90) (Table 2). In this paper, we present WormQTL2 101 and showcase its use by presenting short research scenarios. 102 Results 103 104 eQTL studies in WormQTL2 105WormQTL2 is a browser-based interactive platform and database for investigating expression 106 and other Quantitative Trait Locus (QTL) studies conducted in C. elegans (Figure 1). It enables 107 access to the mapping data of six previously published eQTL studies (Table 1) (28,50,(76)(77)(78)(79). 108Together, these studies cover over 700 samples, including expression measurements of 109 approximately 20,000 different genes across different life stages and environmental conditions. 110The effect of genetic variation on gene expression is presented in 11 genome-wide sets of 111 eQTLs from three different RIL populations. The three populations consist of two different 112 CB4856 x N2 populations, recombinant inbred lines (RILs) (28) and recombinant inbred 113 advanced intercross lines (RIAILs) (91,92) and a mutation introgressed RIL population 114 resulting from a cross between a let-60 gain-of-function mutant in an N2 background, MT2124, 115 with CB4856 (11,50). For the Li et al. 2006, Viñuela & Snoek et al. 2010 and Li et al. 2010 116 Figure 1: WormQTL2 Homepage. On the top of the page the navigation bar can be found. This includes the WormQTL2 logo, which functions as a home button. It also includes a fast link to the Correlation and Locus overviews as well as links for help, data download, and visual examples. The search box is located in the centre, in which genes, phenotypes and GO terms can be entered. Shown in the blue middle square are the buttons for the investigations of single traits, correlating QTL profiles, QTLs at a specific locus, all eQTLs of an expe...

show abstract

Section: Discussionmentioning

confidence: 99%

WormQTL2: an interactive platform for systems genetics inCaenorhabditis elegans

Snoek

Sterken

Hartanto

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…C . elegans populations are globally distributed and inhabit many different niches [46, 47], thereby providing many opportunities for balancing selection to act upon antagonistically pleiotropic genes. A number of genetic regions appear to be under ancient balancing selection in C .…”

Section: Discussionmentioning

confidence: 99%

Modeling of a negative feedback mechanism explains antagonistic pleiotropy in reproduction in domesticated Caenorhabditis elegans strains

et al. 2017

View full text Add to dashboard Cite

Most biological traits and common diseases have a strong but complex genetic basis, controlled by large numbers of genetic variants with small contributions to a trait or disease risk. The effect-size of most genetic variants is not absolute and is instead dependent upon multiple factors such as the age and genetic background of an organism. In order to understand the mechanistic basis of these changes, we characterized heritable trait differences between two domesticated strains of C. elegans. We previously identified a major effect locus, caused in part by a mutation in a component of the NURF chromatin remodeling complex, that regulates reproductive output in an age-dependent manner. The effect-size of this locus changes from positive to negative over the course of an animal’s reproductive lifespan. Here, we use a previously published macroscale model of the egg-laying rate in C. elegans to show that time-dependent effect-size is explained by an unequal use of sperm combined with negative feedback between sperm and ovulation rate. We validate key predictions of this model with controlled mating experiments and quantification of oogenesis and sperm use. Incorporation of this model into QTL mapping allows us to identify and partition new QTLs into specific aspects of the egg-laying process. Finally, we show how epistasis between two genetic variants is predicted by this modeling as a consequence of the unequal use of sperm. This work demonstrates how modeling of multicellular communication systems can improve our ability to predict and understand the role of genetic variation on a complex phenotype. Negative autoregulatory feedback loops, common in transcriptional regulation, could play an important role in modifying genetic architecture in other traits.

show abstract

“…the National Climatic Data Center to measure the variation in seasonal temperatures for locations close to 450 the sites were isotypes were collected (Evans et al, 2017). We found that the Hawaiian populations 451 experienced less seasonal variability in temperature than any of the non-Hawaiian populations 452 (Supplemental Figure 10).…”

mentioning

confidence: 86%

Deep sampling of HawaiianCaenorhabditis elegansreveals high genetic diversity and admixture with global populations

Crombie¹,

Zdraljevic²,

Cook³

et al. 2019

Preprint

View full text Add to dashboard Cite

37 Recent efforts to understand the natural niche of the keystone model organism Caenorhabditis elegans have 38 suggested that this species is cosmopolitan and associated with rotting vegetation and fruits. However, most 39 of the strains isolated from nature have low genetic diversity likely because recent chromosome-scale 40 selective sweeps contain alleles that increase fitness in human-associated habitats. Strains from the Hawaii 41 Islands are highly divergent from non-Hawaiian strains. This result suggests that Hawaiian strains might 42contain ancestral genetic diversity that was purged from most non-Hawaiian strains by the selective sweeps. 43To characterize the genetic diversity and niche of Hawaiian C. elegans, we sampled across the Hawaiian 44Islands and isolated 100 new C. elegans strains. We found that C. elegans strains are not associated with 45any one substrate but are found in cooler climates at high elevations. These Hawaiian strains are highly 46 Page 2 of 23 diverged compared to the rest of the global population. Admixture analysis identified 11 global populations, 47 four of which are from Hawaii. Surprisingly, one of the Hawaiian populations shares recent ancestry with non-48Hawaiian populations, including portions of globally swept haplotypes. This discovery provides the first 49 evidence of gene flow between Hawaiian and non-Hawaiian populations. Most importantly, the high levels of 50 diversity observed in Hawaiian strains might represent the complex patterns of ancestral genetic diversity in 51 the C. elegans species before human influence. 52 53Introduction 54Over the last 50 years, the nematode Caenorhabditis elegans has been central to many important 55 discoveries in the fields of developmental, cellular, and molecular biology. The vast majority of these insights 56 came from the study of a single laboratory-adapted strain collected in Bristol, England known as N2 (Brenner, 57

show abstract

Correlations of Genotype with Climate Parameters Suggest Caenorhabditis elegans Niche Adaptations

Cited by 30 publications

References 29 publications

WormQTL2: an interactive platform for systems genetics inCaenorhabditis elegans

WormQTL2: an interactive platform for systems genetics inCaenorhabditis elegans

Modeling of a negative feedback mechanism explains antagonistic pleiotropy in reproduction in domesticated Caenorhabditis elegans strains

Deep sampling of HawaiianCaenorhabditis elegansreveals high genetic diversity and admixture with global populations

Contact Info

Product

Resources

About