Department of Genetics and Plant Breeding, Rajiv Gandhi University, Rono Hills, Itanagar, India.
Department of Genetics-Plant Breeding and Biotechnology, Dr K. S. Gill, Akal College of Agriculture, Eternal University, Baru Sahib, Sirmour, India.
Sci Rep. 2024 Jun 7;14(1):13083. doi: 10.1038/s41598-024-63924-w.
In bread wheat, a literature search gave 228 QTLs for six traits, including resistance against spot blotch and the following five other related traits: (i) stay green; (ii) flag leaf senescence; (iii) green leaf area duration; (iv) green leaf area of the main stem; and (v) black point resistance. These QTLs were used for metaQTL (MQTL) analysis. For this purpose, a consensus map with 72,788 markers was prepared; 69 of the above 228 QTLs, which were suitable for MQTL analysis, were projected on the consensus map. This exercise resulted in the identification of 16 meta-QTLs (MQTLs) located on 11 chromosomes, with the PVE ranging from 5.4% (MQTL7) to 21.8% (MQTL5), and the confidence intervals ranging from 1.5 to 20.7 cM (except five MQTLs with a range of 36.1-57.8 cM). The number of QTLs associated with individual MQTLs ranged from a maximum of 17 in MQTL3 to 8 each in MQTL5 and MQTL8 and 5 each in MQTL7 and MQTL14. The 16 MQTLs, included 12 multi-trait MQTLs; one of the MQTL also overlapped a genomic region carrying the major spot blotch resistance gene Sb1. Of the total 16 MQTLs, 12 MQTLs were also validated through marker-trait associations that were available from earlier genome-wide association studies. The genomic regions associated with MQTLs were also used for the identification of candidate genes (CGs) and led to the identification of 516 CGs encoding 508 proteins; 411 of these proteins are known to be associated with resistance against several biotic stresses. In silico expression analysis of CGs using transcriptome data allowed the identification of 71 differentially expressed CGs, which were examined for further possible studies. The findings of the present study should facilitate fine-mapping and cloning of genes, enabling Marker Assisted Selection.
在小麦中，通过文献检索发现了 228 个与 6 个性状相关的 QTL，包括对斑点叶枯病的抗性以及以下 5 个其他相关性状：（i）保持绿色；（ii）旗叶衰老；（iii）绿叶面积持续时间；（iv）主茎绿叶面积；和（v）抗黑斑病。这些 QTL 用于元 QTL（MQTL）分析。为此，准备了一张带有 72788 个标记的共识图谱；将上述 228 个 QTL 中的 69 个适合 MQTL 分析的 QTL 投射到共识图谱上。这项研究确定了 16 个位于 11 条染色体上的元 QTL（MQTL），其 PVE 范围从 5.4%（MQTL7）到 21.8%（MQTL5），置信区间范围从 1.5 到 20.7 cM（除了 5 个 MQTL 的范围为 36.1-57.8 cM）。与单个 MQTL 相关的 QTL 数量从 MQTL3 的最大值 17 个到 MQTL5 和 MQTL8 的每个 8 个，以及 MQTL7 和 MQTL14 的每个 5 个不等。这 16 个 MQTL 包括 12 个多性状 MQTL；其中一个 MQTL 还与携带主要斑点叶枯病抗性基因 Sb1 的基因组区域重叠。在总共 16 个 MQTL 中，有 12 个 MQTL 通过之前全基因组关联研究中可用的标记-性状关联得到了验证。与 MQTL 相关的基因组区域也用于候选基因（CGs）的鉴定，导致鉴定出 516 个编码 508 种蛋白质的 CGs；其中 411 种蛋白质与多种生物胁迫的抗性有关。使用转录组数据对 CGs 进行的基因表达分析允许鉴定出 71 个差异表达的 CGs，这些 CGs 将进一步进行可能的研究。本研究的结果应有助于精细图谱绘制和基因克隆，从而实现标记辅助选择。
