摘要
Deciphering the genetic mechanisms underlying agronomic traits is of great importance for crop improvement. Most of these traits are controlled by multiple quantitative trait loci (QTLs), and identifying the underlying genes by conventional QTL fine-mapping is time-consuming and labor-intensive. Here, we devised a new method, named quantitative trait gene sequencing (QTG-seq), to accelerate QTL fine-mapping. QTGseq combines QTL partitioning to convert a quantitative trait into a near-qualitative trait, sequencing of bulked segregant pools from a large segregating population, and the use of a robust new algorithm for identifying candidate genes. Using QTG-seq, we fine-mapped a plant-height QTL in maize (Zea mays L.), qPH7, to a 300-kb genomic interval and verified that a gene encoding an NF-YC transcription factor was the functional gene. Functional analysis suggested that qPH7-encoding protein might influence plant height by interacting with a CO-like protein and an AP2 domain-containing protein. Selection footprint ana卜 ysis indicated that qPH7 was subject to strong selection during maize improvement. In summary, QTG-seq provides an efficient method for QTL fine-mapping in the era of “big data".
基金
the National Key Research and Development Program of China (2016YFD0100404)
the National Basic Research Program of China (2014CB138200)
the National Natural Science Foundation of China (91735305,1571268)
the Fundamental Research Funds of the Central Non-profit Scientific Institution (Y2018LM04)
the Xinjiang Key R&D Program (2018B01006-3)
and the Huazhong Agricultural University Scientific & Technological Self-innovation Foundation (2662016PY096
014RC020).This research was also partly supported by the open funds of the National Key Laboratory of Crop Genetic Improvement.
