PeerJ (Nov 2022)

Identification of quantitative trait loci of agronomic traits in bread wheat using a Pamyati Azieva × Paragon mapping population harvested in three regions of Kazakhstan

  • Akerke Amalova,
  • Kanat Yermekbayev,
  • Simon Griffiths,
  • Saule Abugalieva,
  • Adylkhan Babkenov,
  • Elena Fedorenko,
  • Aigul Abugalieva,
  • Yerlan Turuspekov

DOI
https://doi.org/10.7717/peerj.14324
Journal volume & issue
Vol. 10
p. e14324

Abstract

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Background Although genome-wide association studies (GWAS) are an increasingly informative tool in the mining of new quantitative trait loci (QTLs), a classical biparental mapping approach is still a powerful, widely used method to search the unique genetic factors associated with important agronomic traits in bread wheat. Methods In this study, a newly constructed mapping population of Pamyati Azieva (Russian Federation) × Paragon (UK), consisting of 94 recombinant inbred lines (RILs), was tested in three different regions of Kazakhstan with the purpose of QTL identification for key agronomic traits. The RILs were tested in 11 environments of two northern breeding stations (Petropavlovsk, North Kazakhstan region, and Shortandy, Aqmola region) and one southeastern station (Almalybak, Almaty region). The following eight agronomic traits were studied: heading days, seed maturation days, plant height, spike length, number of productive spikes, number of kernels per spike, thousand kernel weight, and yield per square meter. The 94 RILs of the PAxP cross were genotyped using Illumina’s iSelect 20K single nucleotide polymorphism (SNP) array and resulted in the identification of 4595 polymorphic SNP markers. Results The application of the QTL Cartographer statistical package allowed the identification of 53 stable QTLs for the studied traits. A survey of published studies related to common wheat QTL identification suggested that 28 of those 53 QTLs were presumably novel genetic factors. The SNP markers for the identified QTLs of the analyzed agronomic traits of common wheat can be efficiently applied in ongoing breeding activities in the wheat breeding community using a marker-assisted selection approach.

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