Association mapping across a multitude of traits collected in diverse environments in maize

Mural, Ravi V.; Sun, Guangchao; Grzybowski, Marcin; Tross, Michael C.; Jin, Hongyu; Smith, Christine; Newton, Linsey; Andorf, Carson M.; Woodhouse, Margaret R.; Thompson, Addie M.; Sigmon, Brandi; Schnable, James C.

doi:10.1093/gigascience/giac080

Association mapping across a multitude of traits collected in diverse environments in maize

Journal Article · Tue Aug 23 00:00:00 EDT 2022 · GigaScience

DOI:https://doi.org/10.1093/gigascience/giac080· OSTI ID:1882997

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Abstract

Classical genetic studies have identified many cases of pleiotropy where mutations in individual genes alter many different phenotypes. Quantitative genetic studies of natural genetic variants frequently examine one or a few traits, limiting their potential to identify pleiotropic effects of natural genetic variants. Widely adopted community association panels have been employed by plant genetics communities to study the genetic basis of naturally occurring phenotypic variation in a wide range of traits. High-density genetic marker data—18M markers—from 2 partially overlapping maize association panels comprising 1,014 unique genotypes grown in field trials across at least 7 US states and scored for 162 distinct trait data sets enabled the identification of of 2,154 suggestive marker-trait associations and 697 confident associations in the maize genome using a resampling-based genome-wide association strategy. The precision of individual marker-trait associations was estimated to be 3 genes based on a reference set of genes with known phenotypes. Examples were observed of both genetic loci associated with variation in diverse traits (e.g., above-ground and below-ground traits), as well as individual loci associated with the same or similar traits across diverse environments. Many significant signals are located near genes whose functions were previously entirely unknown or estimated purely via functional data on homologs. This study demonstrates the potential of mining community association panel data using new higher-density genetic marker sets combined with resampling-based genome-wide association tests to develop testable hypotheses about gene functions, identify potential pleiotropic effects of natural genetic variants, and study genotype-by-environment interaction.

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Research Organization:: Michigan State University, East Lansing, MI (United States); University of Nebraska, Lincoln, NE (United States)

Sponsoring Organization:: National Science Foundation (NSF); US Department of Agriculture (USDA); USDOE; USDOE Advanced Research Projects Agency - Energy (ARPA-E)

Grant/Contract Number:: AR0001064; AR0001367

OSTI ID:: 1882997

Alternate ID(s):: OSTI ID: 1904192

Journal Information:: GigaScience, Journal Name: GigaScience Vol. 11; ISSN 2047-217X

Publisher:: Oxford University PressCopyright Statement

Country of Publication:: United Kingdom

Language:: English

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Association mapping across a multitude of traits collected in diverse environments in maize

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