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Natural variation in fecundity is correlated with species-wide levels of divergence in Caenorhabditis elegans.

Gaotian Zhang | Jake D Mostad | Erik C Andersen
G3 (Bethesda, Md.) | 2021

Life history traits underlie the fitness of organisms and are under strong natural selection. A new mutation that positively impacts a life history trait will likely increase in frequency and become fixed in a population (e.g., a selective sweep). The identification of the beneficial alleles that underlie selective sweeps provides insights into the mechanisms that occurred during the evolution of a species. In the global population of Caenorhabditis elegans, we previously identified selective sweeps that have drastically reduced chromosomal-scale genetic diversity in the species. Here, we measured the fecundity of 121 wild C. elegans strains, including many recently isolated divergent strains from the Hawaiian islands and found that strains with larger swept genomic regions have significantly higher fecundity than strains without evidence of the recent selective sweeps. We used genome-wide association (GWA) mapping to identify three quantitative trait loci (QTL) underlying the fecundity variation. In addition, we mapped previous fecundity data from wild C. elegans strains and C. elegans recombinant inbred advanced intercross lines that were grown in various conditions and detected eight QTL using GWA and linkage mappings. These QTL show the genetic complexity of fecundity across this species. Moreover, the haplotype structure in each GWA QTL region revealed correlations with recent selective sweeps in the C. elegans population. North American and European strains had significantly higher fecundity than most strains from Hawaii, a hypothesized origin of the C. elegans species, suggesting that beneficial alleles that caused increased fecundity could underlie the selective sweeps during the worldwide expansion of C. elegans.

Pubmed ID: 33983439

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PLINK (tool)

RRID:SCR_001757

Open source whole genome association analysis toolset, designed to perform range of basic, large scale analyses in computationally efficient manner. Used for analysis of genotype/phenotype data. Through integration with gPLINK and Haploview, there is some support for subsequent visualization, annotation and storage of results. PLINK 1.9 is improved and second generation of the software.

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R Project for Statistical Computing (tool)

RRID:SCR_001905

Software environment and programming language for statistical computing and graphics. R is integrated suite of software facilities for data manipulation, calculation and graphical display. Can be extended via packages. Some packages are supplied with the R distribution and more are available through CRAN family.It compiles and runs on wide variety of UNIX platforms, Windows and MacOS.

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