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A SNP-based genetic dissection of versatile traits in bread wheat (Triticum aestivum L.).

Mian Abdur Rehman ArifSajid ShokatJörg PlieskeMartin GanalUlrike LohwasserYuriy V ChesnokovNataliya V KocherinaPawan KulwalNeeraj KumarPatrick E McGuireMark E SorrellsCalvin O QualsetAndreas Börner
Published in: The Plant journal : for cell and molecular biology (2021)
The continuous increase in global population prompts increased wheat production. Future wheat (Triticum aestivum L.) breeding will heavily rely on dissecting molecular and genetic bases of wheat yield and related traits which is possible through the discovery of quantitative trait loci (QTLs) in constructed populations, such as recombinant inbred lines (RILs). Here, we present an evaluation of 92 RILs in a bi-parental RIL mapping population (the International Triticeae Mapping Initiative Mapping Population [ITMI/MP]) using newly generated phenotypic data in 3-year experiments (2015), older phenotypic data (1997-2009), and newly created single nucleotide polymorphism (SNP) marker data based on 92 of the original RILs to search for novel and stable QTLs. Our analyses of more than 15 unique traits observed in multiple experiments included analyses of 46 traits in three environments in the USA, 69 traits in eight environments in Germany, 149 traits in 10 environments in Russia, and 28 traits in four environments in India (292 traits in 25 environments) with 7584 SNPs (292 × 7584 = 2 214 528 data points). A total of 874 QTLs were detected with limit of detection (LOD) scores of 2.01-3.0 and 432 QTLs were detected with LOD > 3.0. Moreover, 769 QTLs could be assigned to 183 clusters based on the common markers and relative proximity of related QTLs, indicating gene-rich regions throughout the A, B, and D genomes of common wheat. This upgraded genotype-phenotype information of ITMI/MP can assist breeders and geneticists who can make crosses with suitable RILs to improve or investigate traits of interest.
Keyphrases
  • genome wide
  • dna methylation
  • copy number
  • electronic health record
  • high resolution
  • high density
  • small molecule
  • deep learning
  • middle aged
  • genome wide association study
  • real time pcr
  • transcription factor