Maize-RGB&CT&HSI-data
收藏NIAID Data Ecosystem2026-03-12 收录
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https://figshare.com/articles/dataset/Maize-RGB_CT_HSI-data/14412572
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资源简介:
Background : Drought threatens the food supply of the world population. Dissecting
the dynamic responses to drought and revealing their genetic architectures will be
beneficial for breeding drought-tolerant crops. However, the dynamic responses of
plant to drought, both external and internal, and the genetic controls of these
responses remain largely unknown.
Results : Here we developed a high-throughput multiple optical phenotyping system to
non-invasively phenotype 368 maize genotypes with or without drought stress over a
course of 98 days, and collected ~14 terabytes of multiple optical images, including
color (red, green, blue) camera scanning (RGB), hyperspectral imaging (HSI) and x-ray
computed tomography (CT) images. High-throughput analysis pipelines were
developed to extract 26,910 the image-based traits (i-traits). Of these i-traits, 10,080
were effective and heritable indicators of maize external (RGB i-traits) and internal (HSI
and CT i-traits) drought responses and selected for further genetic study. A total of
4,322 significant locus-trait associations were identified via i-trait-based genome wide
association study (GWAS), which represent 1,529 quantitative trait loci (QTLs) and
2,318 candidate genes. Of these QTLs, 1,092 (71.4%) co-localized with previously
reported maize drought responsive QTLs. Expression QTL (eQTL) analysis uncovered
many local and distant regulatory variants that control the exp ression of the candidate
genes. Thirty-four hotspot genes associated with multiple i-traits were identified. We
further used genetic mutation analysis to validate two new genes, ZmcPGM2 and
ZmFAB1A that regulated i-traits and drought tolerance. Moreover, the value of the
candidate genes as drought-tolerant genetic markers was revealed by genome
selection analysis, and 15 i-traits were identified as potential markers for maize drought
tolerance breeding.
Conclusion : 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.
创建时间:
2021-04-14



