Polygenicity and epistasis underlie fitness-proximal traits in the Caenorhabditis elegans multiparental experimental evolution (CeMEE) panel

Luke M. Noble, Ivo Chelo, Thiago Guzella, Bruno Afonso, David D. Riccardi, Patrick Ammerman, Adel Dayarian, Sara Carvalho, Anna Crist, Ania Pino-Querido, Boris Shraiman, Matthew V. Rockman, Henrique Teotónio

Research output: Contribution to journalArticle

Abstract

Understanding the genetic basis of complex traits remains a major challenge in biology. Polygenicity, phenotypic plasticity, and epistasis contribute to phenotypic variance in ways that are rarely clear. This uncertainty can be problematic for estimating heritability, for predicting individual phenotypes from genomic data, and for parameterizing models of phenotypic evolution. Here, we report an advanced recombinant inbred line (RIL) quantitative trait locus mapping panel for the hermaphroditic nematode Caenorhabditis elegans, the C. elegans multiparental experimental evolution (CeMEE) panel. The CeMEE panel, comprising 507 RILs at present, was created by hybridization of 16 wild isolates, experimental evolution for 140–190 generations, and inbreeding by selfing for 13–16 generations. The panel contains 22% of single-nucleotide polymorphisms known to segregate in natural populations, and complements existing C. elegans mapping resources by providing fine resolution and high nucleotide diversity across > 95% of the genome. We apply it to study the genetic basis of two fitness components, fertility and hermaphrodite body size at time of reproduction, with high broad-sense heritability in the CeMEE. While simulations show that we should detect common alleles with additive effects as small as 5%, at gene-level resolution, the genetic architectures of these traits do not feature such alleles. We instead find that a significant fraction of trait variance, approaching 40% for fertility, can be explained by sign epistasis with main effects below the detection limit. In congruence, phenotype prediction from genomic similarity, while generally poor (r2 < 10%), requires modeling epistasis for optimal accuracy, with most variance attributed to the rapidly evolving chromosome arms.

Original languageEnglish (US)
Pages (from-to)1663-1685
Number of pages23
JournalGenetics
Volume207
Issue number4
DOIs
StatePublished - Dec 2017

Keywords

  • Body size
  • Complex trait
  • Epistasis
  • Experimental evolution
  • Fertility
  • GWAS
  • Genetic architecture
  • Heritability
  • MPP
  • Multiparent advanced Generation Inter-Cross (MAGIC)
  • Multiparental populations
  • Polygenicity
  • QTL
  • Quantitative trait
  • Selfing

ASJC Scopus subject areas

  • Genetics

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