| Literature DB >> 30597214 |
Hongwei Zhang1, Xi Wang2, Qingchun Pan2, Pei Li3, Yunjun Liu4, Xiaoduo Lu5, Wanshun Zhong2, Minqi Li2, Linqian Han2, Juan Li2, Pingxi Wang4, Dongdong Li4, Yan Liu4, Qing Li2, Fang Yang2, Yuan-Ming Zhang6, Guoying Wang7, Lin Li8.
Abstract
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. QTG-seq 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 analysis 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".Entities:
Keywords: QTL; QTL fine-mapping; plant height; quantitative trait locus; whole genome sequencing
Mesh:
Year: 2018 PMID: 30597214 DOI: 10.1016/j.molp.2018.12.018
Source DB: PubMed Journal: Mol Plant ISSN: 1674-2052 Impact factor: 13.164