Genome wide association mapping of yield and other agronomic traits in rice: Narrative literature review
1 Department of Bioscience & Technology, Khwaja Fareed University of Engineering & Information Technology, Punjab, Pakistan.
2 Department of Botany, University of Agriculture Faisalabad, Punjab, Pakistan
3 Genomics and Computational Biology Laboratory, COMSATS University Islamabad, Sahiwal Campus, Punjab, Pakistan.
4 Department of Bioscience & Technology, Khwaja Fareed University of Engineering & Information Technology, Punjab, Pakistan.
5 Department of Chemistry, Khwaja Fareed University of Engineering & Information Technology, Punjab, Pakistan.
Review Article
World Journal of Advanced Research and Reviews, 2021, 12(03), 354–367
Article DOI: 10.30574/wjarr.2021.12.3.0695
Publication history:
Received on 09 November 2021; revised on 18 December 2021; accepted on 20 December 2021
Abstract:
Based on previous recombination actions and LD (linkage disequilibrium) throughout the genome, genome wide association mapping studies often are employed to find Quantitative trait locus in varied collections of crop germplasm. Generally, diverse panel’s genotyped using high density Single nucleotide polymorphism (SNP) panels are used to test a broad variety of haplotypes and alleles, as well as to track recombination divisions throughout the genome. GWAS, on the other hand, have rarely been used in breeding populations. We studied association mapping for agricultural parameters such as yield and its constituents in a breeding inhabitants of top irrigated tropical rice progenies so that the findings could be used to breeding more directly than those from a diverse panel. GWAS was undertaken with the specific purpose of accelerating selection in the breeding population, and the sample was genotyped with 71,710 Single nucleotide polymorphisms using genotyping-by-sequencing. We found 52 Quantitative trait locus QTL for 11 agronomic characteristics using this breeding panel, including substantial impact Quantitative trait loci (QTLs) for flowering period as well as grain width, grain length, grain length-breadth ratio. Furthermore we discovered haplotypes that may be applied to choose plants for our population with smaller stature (plant height), fast blooming time, with high yield, demonstrating the value of association mapping for advising breeding choices in breeding populations. Furthermore, we explore at how genomic-assisted selection models might be built using the newly discovered important Single nucleotide polymorphisms (SNPs) and deep insight into the genetic structure of these quantitative traits.
Keywords:
Rice; Genome wide association; SNPs; NGS; QTLs; Bioinformatics
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Copyright © 2021 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0