Safdar Luqman Bin, Andleeb Tayyaba, Latif Sadia, Umer Muhammad Jawad, Tang Minqiang, Li Xiang, Liu Shengyi, Quraishi Umar Masood
Key Laboratory of Biology and Genetics Improvement of Oil Crops, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Ministry of Agriculture and Rural Affairs, Wuhan, China.
Department of Plant Sciences, Quaid-i-Azam University, Islamabad, Pakistan.
Front Plant Sci. 2020 Feb 18;11:70. doi: 10.3389/fpls.2020.00070. eCollection 2020.
Potassium use efficiency, a complex trait, directly impacts the yield potential of crop plants. Low potassium efficiency leads to a high use of fertilizers, which is not only farmer unfriendly but also deteriorates the environment. Genome-wide association studies (GWAS) are widely used to dissect complex traits. However, most studies use single-locus one-dimensional GWAS models which do not provide true information about complex traits that are controlled by multiple loci. Here, both single-locus GWAS (MLM) and multi-locus GWAS (pLARmEB, FASTmrMLM, mrMLM, FASTmrEMMA) models were used with genotyping from 90 K Infinium SNP array and phenotype derived from four normal and potassium-stress environments, which identified 534 significant marker-trait associations (MTA) for agronomic and potassium related traits: pLARmEB = 279, FASTmrMLM = 213, mrMLM = 35, MLM = 6, FASTmrEMMA = 1. Further screening of these MTA led to the detection of eleven stable loci: and . Moreover, Meta-QTL (MQTL) analysis of four independent QTL studies for potassium deficiency in bread wheat located 16 MQTL on 13 chromosomes. One locus identified in this study () colocalized with an MQTL ( ), while the other ten loci were novel associations. Gene ontology of these loci identified 20 putative candidate genes encoding functional proteins involved in key pathways related to stress tolerance, sugar metabolism, and nutrient transport. These findings provide potential targets for breeding potassium stress resistant wheat cultivars and advocate the advantages of multi-locus GWAS models for studying complex traits.
钾利用效率是一个复杂性状,直接影响作物的产量潜力。低钾效率导致肥料的大量使用,这不仅对农民不利,还会使环境恶化。全基因组关联研究(GWAS)被广泛用于剖析复杂性状。然而,大多数研究使用单基因座一维GWAS模型,这些模型无法提供由多个基因座控制的复杂性状的真实信息。在这里,单基因座GWAS(MLM)和多基因座GWAS(pLARmEB、FASTmrMLM、mrMLM、FASTmrEMMA)模型与来自90K Infinium SNP芯片的基因分型以及来自四种正常和钾胁迫环境的表型一起使用,共鉴定出534个与农艺和钾相关性状的显著标记-性状关联(MTA):pLARmEB = 279个,FASTmrMLM = 213个,mrMLM = 35个,MLM = 6个,FASTmrEMMA = 1个。对这些MTA的进一步筛选导致检测到11个稳定基因座:以及。此外,对面包小麦钾缺乏的四项独立QTL研究进行的Meta-QTL(MQTL)分析在13条染色体上定位了16个MQTL。本研究中鉴定出的一个基因座()与一个MQTL()共定位,而其他十个基因座是新的关联。这些基因座的基因本体分析鉴定出20个推定的候选基因,这些基因编码参与与胁迫耐受性、糖代谢和营养物质运输相关关键途径的功能蛋白。这些发现为培育抗钾胁迫小麦品种提供了潜在靶点,并表明了多基因座GWAS模型在研究复杂性状方面的优势。