Triticeae Genomics and Genetics, 2024, Vol.15, No.4, 185-195 http://cropscipublisher.com/index.php/tgg 185 Research Article Open Access Quantitative Trait Loci Analysis in Triticeae: Implications for Breeding and Genetics Guiping Zhang, Renxiang Cai Institute of Life Science, Jiyang College of Zhejiang A&F University, Zhuji, 311800, Zhejiang, China Corresponding author: rxcai@sina.com Triticeae Genomics and Genetics, 2024, Vol.15, No.4 doi: 10.5376/tgg.2024.15.0018 Received: 28 May, 2024 Accepted: 05 Jul., 2024 Published: 18 Jul., 2024 Copyright © 2024 Zhang and Cai, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Zhang G.P., and Cai R.X., 2024, Quantitative trait loci analysis in Triticeae: implications for breeding and genetics, Triticeae Genomics and Genetics, 15(4): 185-195 (doi: 10.5376/tgg.2024.15.0018) Abstract Quantitative Trait Loci (QTL) analysis has become a pivotal tool in understanding the genetic basis of complex traits in Triticeae, with significant implications for breeding and genetics. This study retrospects various methodologies and findings in QTL mapping, highlighting the advancements and applications in crop improvement. Multiple interval mapping (MIM) has been shown to enhance the precision and power of QTL detection, allowing for the estimation of epistasis, genotypic values, and heritabilities. Comparative genomic analysis has identified stable QTLs for grain yield, quality traits, and micronutrient contents in wheat, consolidating QTLs into meta-QTLs (MQTLs) and reducing confidence intervals, thus facilitating marker-assisted selection (MAS). The integration of linkage and association mapping has further dissected the genetic architecture of complex traits, revealing the importance of environment-specific QTLs and the need for advanced statistical strategies in the era of next-generation sequencing. Additionally, QTL mapping under stress conditions, such as salinity, has identified key genomic regions contributing to stress tolerance, which can be exploited for breeding resilient varieties. ThFe development of multiparental populations and the use of whole-genome resequencing (QTL-seq) have accelerated the identification of QTLs, providing a robust framework for genetic dissection and crop improvement. This study underscores the critical role of QTL analysis in advancing our understanding of genetic variation and enhancing breeding programs inTriticeae. Keywords Quantitative trait loci (QTL); Marker-assisted selection (MAS); Triticeae; Genetic mapping; Crop improvement 1 Introduction The Triticeae tribe, which includes economically significant cereals such as wheat, barley, and rye, is fundamental to global agriculture. These crops are cultivated extensively for their grain, which serves as a staple food source for a large portion of the world's population. The genetic diversity within Triticeae is vast, encompassing numerous species and varieties that have adapted to a wide range of environmental conditions. This diversity is a valuable resource for breeding programs aimed at improving crop yield, disease resistance, and stress tolerance. Quantitative Trait Loci (QTL) are regions of the genome that are associated with the variation of quantitative traits, which are typically influenced by multiple genes and environmental factors. QTL mapping is a powerful tool used to identify these genomic regions and understand the genetic architecture of complex traits. Traditional QTL mapping involves the use of biparental populations, but recent advancements have seen the development of multiparental cross designs, which offer broader genetic bases and higher mapping resolution (Crepieux et al., 2004; Milner et al., 2016). Techniques such as Bayesian mapping and composite interval mapping have further enhanced the precision and power of QTL detection (Jiang and Zeng, 1995; Yi and Xu, 2001; Takagi et al., 2013). These methodologies are crucial for dissecting the genetic basis of traits such as yield, stress tolerance, and nutrient content in crops (Ilyas et al., Zhanget al., 2010; Shariatipour et al., 2021). The study conducts a comprehensive QTL analysis in Triticeae, with a focus on identifying loci associated with key agronomic traits. By leveraging advanced QTL mapping techniques and multiparental populations, this research aims to uncover the genetic factors that contribute to trait variation and their interactions with environmental conditions. The findings will have significant implications for breeding programs, providing valuable insights for the development of improved Triticeae varieties with enhanced performance and resilience.
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