National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, and Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural University, Wuhan, 430070, China.
Hubei Hongshan laboratory, Wuhan, 430070, China.
Genome Biol. 2021 Jun 24;22(1):185. doi: 10.1186/s13059-021-02377-0.
Drought threatens the food supply of the world population. Dissecting the dynamic responses of plants to drought will be beneficial for breeding drought-tolerant crops, as the genetic controls of these responses remain largely unknown.
Here we develop a high-throughput multiple optical phenotyping system to noninvasively phenotype 368 maize genotypes with or without drought stress over a course of 98 days, and collected multiple optical images, including color camera scanning, hyperspectral imaging, and X-ray computed tomography images. We develop high-throughput analysis pipelines to extract image-based traits (i-traits). Of these i-traits, 10,080 were effective and heritable indicators of maize external and internal drought responses. An i-trait-based genome-wide association study reveals 4322 significant locus-trait associations, representing 1529 quantitative trait loci (QTLs) and 2318 candidate genes, many that co-localize with previously reported maize drought responsive QTLs. Expression QTL (eQTL) analysis uncovers many local and distant regulatory variants that control the expression of the candidate genes. We use genetic mutation analysis to validate two new genes, ZmcPGM2 and ZmFAB1A, which regulate i-traits and drought tolerance. Moreover, the value of the candidate genes as drought-tolerant genetic markers is revealed by genome selection analysis, and 15 i-traits are identified as potential markers for maize drought tolerance breeding.
Our study demonstrates that combining high-throughput multiple optical phenotyping and GWAS is a novel and effective approach to dissect the genetic architecture of complex traits and clone drought-tolerance associated genes.
干旱威胁着世界人口的粮食供应。解析植物对干旱的动态响应将有助于培育耐旱作物,因为这些响应的遗传控制在很大程度上尚不清楚。
在这里,我们开发了一种高通量多光学表型系统,在 98 天的时间内对 368 个有或没有干旱胁迫的玉米基因型进行非侵入性表型分析,并收集了多个光学图像,包括彩色相机扫描、高光谱成像和 X 射线计算机断层扫描图像。我们开发了高通量分析管道来提取基于图像的特征(i-trait)。在这些 i-trait 中,有 10080 个是玉米外部和内部干旱响应的有效且可遗传的指标。基于 i-trait 的全基因组关联研究揭示了 4322 个显著的基因-性状关联,代表了 1529 个数量性状位点(QTL)和 2318 个候选基因,其中许多与先前报道的玉米抗旱响应 QTL 共定位。表达 QTL(eQTL)分析揭示了许多控制候选基因表达的局部和远程调控变体。我们使用遗传突变分析验证了两个新基因 ZmcPGM2 和 ZmFAB1A,它们调节 i-trait 和耐旱性。此外,候选基因作为耐旱性遗传标记的价值通过基因组选择分析得到了揭示,并且鉴定出 15 个 i-trait 作为玉米耐旱性育种的潜在标记。
我们的研究表明,结合高通量多光学表型和 GWAS 是解析复杂性状遗传结构和克隆耐旱相关基因的一种新颖而有效的方法。