GWAS unveils features between early- and late-�owering pearl millets

Background: Pearl millet, a nutritious food for around 100 million people in Africa and India, displays extensive genetic diversity and a high degree of admixture with wild relatives. Two major morphotypes can be distinguished in Senegal: early-�owering Souna and late-�owering Sanio. Phenotypic variabilities related to �owering time play an important role in the adaptation of pearl millet to climate variability. A better understanding of the genetic makeup of these variabilities would make it possible to breed pearl millet to suit regions with different climates. The aim of this study was to characterize the genetic basis of these phenotypic differences. Results: We de�ned a core collection that captures most of the diversity of cultivated pearl millets in Senegal and includes 60 early-�owering Souna and 31 late-�owering Sanio morphotypes. Sixteen agro-morphological traits were evaluated in the panel in the 2016 and 2017 rainy seasons. Phenological and phenotypic traits related with yield, �owering time, and biomass helped differentiate early- and late-�owering morphotypes. Further, using genotyping-by-sequencing (GBS), 21,663 single nucleotide polymorphisms (SNPs) markers with more than 5% of minor allele frequencies were discovered. Sparse non-negative matrix factorization (sNMF) analysis con�rmed the genetic structure in two gene pools associated with differences in �owering time. Two chromosomal regions on linkage groups (LG 3) (~89.7Mb) and (LG 6) (~68.1Mb) differentiated two clusters among the early-�owering Souna. A genome-wide association study (GWAS) was used to link phenotypic variation to the SNPs, and 18 genes were linked to �owering time, plant height, tillering, and biomass (P-value (cid:0) 2.3E-06). Conclusions: The diversity of early- and late-�owering pearl millet morphotypes in Senegal was captured using a heuristic approach. Key phenological and phenotypic traits, SNPs, and candidate genes underlying �owering time, tillering, biomass yield and plant height of pearl millet were identi�ed. Chromosome rearrangements in early- and late-�owering morphotypes may have occurred after the domestication of pearl millet (at least 4,900 years ago), as a consequence of a center of specialization developing across the Sahel belt. This hypothesis is supported by previous reports of migrations, exchanges and gene �ow that led to wider genetic diversity as an adaptive mechanism [4, 14]. These �ndings and this assumption mean the clusters identi�ed among the early-�owering Souna and late-�owering Sanio are genuine heterotic groups that can be used to breed for earliness and biomass, respectively. maximization sampling technique, called heuristic, was performed based on phenotypic and genotypic data from these 392 landraces using PowerCore v 1.0 software [25]. This algorithm removes duplicates and retains only a limited number of landraces in multiple analyses [25]. From this heuristic approach, 91 landraces were retained, consisting of 60 early-�owering Souna and 31 late-�owering Sanio, that were �eld-evaluated at ISRA-Nioro in the 2016 and 2017 rainy seasons. The experimental design for each trial was a 7 x 13 alpha lattice with three repetitions. Each of the landraces tested was grown in a single row comprising eight hills in each repetition and the measurements were taken on three hills. The genetic variability of the panel was assessed using the signi�cance of differences between the Nei genetic index of core collection and a Student’s t-test at α=0.05 [26]. To assess whether the core collection captured the diversity of the whole dataset, we calculated the percentage of mean difference (%MD) and the percentage of variance difference (%VD), the coincidence rate (%CR), and variable rate (%VR) according to [25]. The core collection was considered to be representative of the total collection when no more than 20% of the traits had different means (signi�cant at α=0.05) in the de�ned core collection and in the total collected landraces, and the coincidence rate CR% retained by the core collection was no less than 80%. Analysis of variance was performed on the different phenotypic parameters using the Plant Breeding Tools v with the formula: Discriminant analysis of principal components (DAPC) was also used through the adegenet v 2.1. 1 package [27]. The choice of the number of axes (PCs) retained for the DAPC was made using a cross-validation method, performed on the data set subdivided into two training sets of respectively 90% and 10% [32]. A test comprising 30 repetitions was performed to preselect a limited number of PCs. At each repetition, the validation and training sets were randomly allocated. A second test comprising 1,000 repetitions was carried out on the preselected PCs to select the number of PCs that enabled the highest proportion of correct predictions with the lowest error rate. This analysis was carried out using the R software adegenet package [27]. GWAS Association analyses were conducted with a mixed linear model (MLM) correcting for population structure and kinship using Tassel v 5.2. 48. Q-Q and Manhattan plots illustrating the results of GWAS were produced using the qqman package v 0.1. 4 in R [33]. The signi�cance threshold (α) of the association of SNP markers with the different traits was calculated using Bonferroni correction [34]. SNPs signi�cantly associated with agro-morphological traits were localized in the pearl millet genome intervals. Locating was performed with the valR package v 0.5. 0 [35] in R. Pearl millet genome annotation was used to identify these genes.