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On the basis of growing environment, maize can largely be classified into temperate and tropical groups, leaving extensive genetic variation and evolutionary signatures in the maize genome. To identify candidate genes governing flowering time and photoperiod sensitivity, selective signature analysis and SNP- and haplotype-based GWAS were performed using 39,350 high-quality SNP markers in temperate and tropical maize groups consisting of 410 inbred lines phenotyped in three representative experiments in different latitudes. Selective signature analysis revealed 106 selective-sweep regions containing 423 candidate genes involved mainly in biological regulation and biosynthesis pathways. Among these genes, 25 overlapped with known genes governing flowering time and photoperiod sensitivity and 37 were also detected by GWAS for days to tassel, anthesis-silk interval, and photoperiod sensitivity measured by days to silking. Only two of the candidate genes governing flowering time overlapped selective signals. Most haplotype alleles within significant haplotype loci showed the same direction of effect on flowering time and photoperiod sensitivity. The inbred lines carrying GATT at HapL499 (haplotype locus 499) on chromosome 1 had relatively short flowering times. Lines carrying CA at HapL4054 on chromosome 10, TA at HapL4055 on chromosome 10, and GTTGT at HapL978 on chromosome 2 were less sensitive to photoperiod than lines carrying other haplotype alleles. Haplotype loci associated with flowering time and photoperiod sensitivity explained respectively 17.5%–18.6% and 11.2%–15.5% of phenotypic variation. Candidate genes and favorable haplotypes identified in this study may support the more efficient utilization of maize germplasm groups. Keywords: Selective signature analysis, GWAS, Maize, Flowering time, Photoperiod sensitivity

Genotyping platforms, as critical supports for genomics, genetics, and molecular breeding, have been well implemented at national institutions/universities in developed countries and multinational seed companies that possess high-throughput, automatic, large-scale, and shared facilities. In this study, we integrated an improved genotyping by target sequencing (GBTS) system with capture-in-solution (liquid chip) technology to develop a multiple single-nucleotide polymorphism (mSNP) approach in which mSNPs can be captured from a single amplicon. From one 40K maize mSNP panel, we developed three types of markers (40K mSNPs, 251K SNPs, and 690K haplotypes), and generated multiple panels with various marker densities (1K–40K mSNPs) by sequencing at different depths. Comparative genetic diversity analysis was performed with genic versus intergenic markers and di-allelic SNPs versus non-typical SNPs. Compared with the one-amplicon-one-SNP system, mSNPs and within-mSNP haplotypes are more powerful for genetic diversity detection, linkage disequilibrium decay analysis, and genome-wide association studies. The technologies, protocols, and application scenarios developed for maize in this study will serve as a model for the development of mSNP arrays and highly efficient GBTS systems in animals, plants, and microorganisms., This study reports the development of high-resolution multiple-SNP (mSNP) arrays, which can capture multiple SNPs from single amplicons, through integrating an improved genotyping by target sequencing approach with liquid chip technology. From a 40K maize mSNP panel, multiple panels with 1K–40K mSNPs (including up to 251K SNPs and 690 haplotypes) were generated by sequencing at different depths, then tested in various genetic analyses using a large number of maize inbred lines. The technical protocol can be widely used in other organisms.

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.