Flowering time regulation model revisited by pooled sequencing of mass selection populations. (March 2021)

• Record Type: Journal Article
• Authors: Yang, Yuxin; Sang, Zhiqin; Du, Qingguo; Guo, Zifeng; Li, Zhiwei; Kong, Xiuying; Xu, Yunbi; Zou, Cheng
• Is Part Of: Plant science. Volume 304(2021)
• Publication Date: 2021-03
• Subjects: WGCNA weighted gene coexpression network analysis -- GWAS genome-wide association study -- NCBI national center for biotechnology -- PCR polymerase chain reaction -- MLM mixed linear model -- DTA days to anthesis -- DTS days to silk -- DTT days to tassel -- ASI anthesis-silk interval -- PR-DTA photoperiod response of day to anthesis -- PR-DTT photoperiod response of day to tassel -- PR-DTS photoperiod response of day to silk -- PR-ASI photoperiod response of anthesis silk interval -- GO gene ontology -- RPKM reads per kilobase of region per million mapped reads -- FPKM fragments per kilobase of transcript per million mapped reads -- CTAB cetyl trimethyl ammonium bromide; Maize -- Adaption improvement -- Allele frequency change -- Flowering time genes -- Weighted gene co-expression network analysis; Botany -- Periodicals; Botanique -- Périodiques; 580
• DOI: 10.1016/j.plantsci.2020.110797
• Languages: English
• ISSNs: 0168-9452

Abstract

Highlights: Mass selection is an effective method for population improvement. Based on the allele frequency changes can detect the selected genes during the population improvement. Flowering time changes during the mass-selection process is mainly due to the allele frequency changes. Combine the bulked sample sequencing and weight gene co-expression network analysis methods can identify the genetic locus that controlling the flowering time. We identified the candidate genes that are significantly associated with flowering time. Abstract: Maize is one of the most broadly cultivated crops throughout the world, and flowering time is a major adaptive trait for its diffusion. The biggest challenge in understanding maize flowering genetic architecture is that the trait is confounded with population structure. To eliminate the effect, we revisited the flower time genetic network by using a tropical maize population Pop32, which was under mass selection for adaptation to early flowering time in China for six generations from tropical to temperate regions. The days to anthesis (DTA) of the initial (Pop32C0), intermedia (Pop32C3), and final population (Pop32C5) was 90.77, 84.63, and 79.72 days on average, respectively. To examine the genetic mechanism and identify the genetic loci underlying this rapid change in flowering time of Pop32, we bulked 30 individuals from C0, C3, and C5 to conduct the whole genome sequencing. And we finally identified 4, 973, 810 high-quality single nucleotide polymorphisms (SNPs) and 6, 517 genes with allele frequency significantly changed during the artificial improvement process. We speculate that these genes might participate in the adaptive improvement process and control flowering time. To identify the candidate genes for flowering time from the gene set with allele frequency changed, we carried out weighted gene co-expression network analysis (WGCNA), and identified four co-expression modules that highly associated with the flowering time development, as well as constructed the co-expression network of key flowering time genes. Gene Ontology (GO) enrichment analysis revealed that the GO terms photosynthesis/light reaction, carbohydrate binding, auxin mediated signaling pathway, response to temperature stimulus that are closely connected with flowering time. Furthermore, targeted GWAS revealed the genes are significantly connected with the flowering time. qRT-PCR of four candidate genes GRMZM2G019879, GRMZM2G055905, GRMZM2G058158, and GRMZM2G171365 showed that their expression level is similar to the flowering time genes, which playing a key role in maize flowering time transition. This study revealed that the changes of flowering time in mass selection process may be strongly associated with the variations of allele frequency changes, and we identified some important candidate genes for flowering time, which will provide a new insight for the rapid improvement of maize important agronomic traits and promote the gene cloning of maize flowering time.