Department of Agricultural Biotechnology, Assam Agricultural University (AAU), Jorhat, Assam, 785013, India.
Department of Biotechnology-North East Centre for Agricultural Biotechnology (DBT-NECAB), AAU, Jorhat, Assam, 785013, India.
Mol Biol Rep. 2023 Aug;50(8):6349-6359. doi: 10.1007/s11033-023-08550-x. Epub 2023 Jun 14.
Drought stress is a major constraint for rice production worldwide. Reproductive stage drought stress (RSDS) leads to heavy yield losses in rice. The prospecting of new donor cultivars for identification and introgression of QTLs of major effect (Quantitative trait locus) for drought tolerance is crucial for the development of drought-resilient rice varieties.
Our study aimed to map QTLs associated with yield and its related traits under RSDS conditions. A saturated linkage map was constructed using 3417 GBS (Genotyping by sequencing) derived SNP (Single nucleotide polymorphism) markers spanning 1924.136 cM map length with an average marker density of 0.56 cM, in the F mapping population raised via cross made between the traditional ahu rice cultivar, Koniahu (drought tolerant) and a high-yielding variety, Disang (drought susceptible). Using the Inclusive composite interval mapping approach, 35 genomic regions governing yield and related traits were identified in pooled data from 198 F and F segregating lines evaluated for two consecutive seasons under both RSDS and irrigated control conditions. Of the 35 QTLs, 23 QTLs were identified under RSDS with LOD (Logarithm of odds) values ranging between 2.50 and 7.83 and PVE (phenotypic variance explained) values of 2.95-12.42%. Two major QTLs were found to be linked to plant height (qPH1.29) and number of filled grains per panicle (qNOG5.12) under RSDS. Five putative QTLs for grain yield namely, qGY2.00, qGY5.05, qGY6.16, qGY9.19, and qGY10.20 were identified within drought conditions. Fourteen QTL regions having ≤ 10 Mb QTL interval size were further analysed for candidate gene identification and a total of 4146 genes were detected out of these 2263 (54.63%) genes were annotated to at least one gene ontology (GO) term.
Several QTLs associated with grain yield and yield components and putative candidate genes were identified. The putative QTLs and candidate genes identified could be employed to augment drought resilience in rice after further validation through MAS strategies.
干旱胁迫是全球范围内水稻生产的主要制约因素。生殖期干旱胁迫（RSDS）导致水稻严重减产。寻找新的供体品种，鉴定和导入对耐旱性有重大影响的数量性状基因座（QTL），对于培育耐旱水稻品种至关重要。
本研究旨在绘制与 RSDS 条件下产量及其相关性状相关的 QTL 图谱。利用通过传统的 ahu 水稻品种 Koniahu（耐旱）和高产品种 Disang（耐旱）杂交产生的 F 作图群体，构建了一个基于 3417 个 GBS（测序基因型）衍生 SNP（单核苷酸多态性）标记的饱和连锁图谱，图谱长度为 1924.136 cM，平均标记密度为 0.56 cM。利用包容性复合区间作图方法，在两个连续季节的 RSDS 和灌溉对照条件下，对 198 个 F 和 F 分离群体进行评价，共鉴定出 35 个控制产量和相关性状的基因组区域。在 RSDS 下，35 个 QTL 中有 23 个 QTL 被鉴定出来，LOD（对数优势）值在 2.50 到 7.83 之间，表型方差解释值（PVE）在 2.95 到 12.42%之间。在 RSDS 下，发现与株高（qPH1.29）和每穗实粒数（qNOG5.12）相关的两个主要 QTL。在干旱条件下，共鉴定出 5 个与粒重相关的 QTL，分别为 qGY2.00、qGY5.05、qGY6.16、qGY9.19 和 qGY10.20。进一步分析了 14 个 QTL 区域，这些区域的 QTL 间隔大小均≤10 Mb，共检测到 4146 个基因，其中 2263 个（54.63%）基因至少被注释到一个基因本体（GO）术语。
鉴定出与粒重和产量构成相关的多个 QTL 和假定候选基因。通过 MAS 策略进一步验证后，这些假定的 QTL 和候选基因可用于提高水稻的耐旱性。
