Genomic signatures of adaptation to Sahelian and Soudanian climates in sorghum landraces of Senegal

Abstract

Uncovering the genomic basis of climate adaptation in traditional crop varieties can provide insight into plant evolution and facilitate breeding for climate resilience. In the African cereal sorghum (Sorghum bicolor L. [Moench]), the genomic basis of adaptation to the semiarid Sahelian zone versus the subhumid Soudanian zone is largely unknown. To address this issue, we characterized a large panel of 421 georeferenced sorghum landrace accessions from Senegal and adjacent locations at 213,916 single‐nucleotide polymorphisms (SNPs) using genotyping‐by‐sequencing. Seven subpopulations distributed along the north‐south precipitation gradient were identified. Redundancy analysis found that climate variables explained up to 8% of SNP variation, with climate collinear with space explaining most of this variation (6%). Genome scans of nucleotide diversity suggest positive selection on chromosome 2, 4, 5, 7, and 10 in durra sorghums, with successive adaptation during diffusion along the Sahel. Putative selective sweeps were identified, several of which colocalize with stay‐green drought tolerance (Stg) loci, and a priori candidate genes for photoperiodic flowering and inflorescence morphology. Genome‐wide association studies of photoperiod sensitivity and panicle compactness identified 35 and 13 associations that colocalize with a priori candidate genes, respectively. Climate‐associated SNPs colocalize with Stg3a, Stg1, Stg2, and Ma6 and have allelic distribution consistent with adaptation across Sahelian and Soudanian zones. Taken together, the findings suggest an oligogenic basis of adaptation to Sahelian versus Soudanian climates, underpinned by variation in conserved floral regulatory pathways and other systems that are less understood in cereals.

Evaluation of genetic diversity, agronomic traits, and anthracnose resistance in the NPGS Sudan Sorghum Core collection

“…Previous studies showed that core collections based on either genotypic profiles or random selection could represent the genetic diversity of the entire collection [3]. The number of rare alleles (MAF < 0.05) in the Sudan core set (22%) was lower than that observed in the NPGS Ethiopia core set (60% [22]; and NPGS Senegal collection (32% [40];. Thus, the high frequency of the Durra genetic background and high frequency of rare alleles in Sudanese populations 1 and 2 suggests that both of these populations originated from Ethiopia.…”

“…Genome scans based on nucleotide polymorphism pattern, environmental variables, selection signature, and candidate gene approach may provide insights into the genetic control of these traits in the Sudanese germplasm [47]. For instance, variation in the photoperiod sensitivity and panicle compactness of the NPGS Senegal collection was associated with several known sorghum genes [40]. Allele frequency distribution of the SNP S4_ 62,316,207 located in the Tan1 gene (Sobic.004 g280800 [48]; indicated that genetic variation was limited to the Sudanese populations 1 and 2.…”

A Genomics Resource for Genetics, Physiology, and Breeding of West African Sorghum

“…Genetic diversity and structure of the WASAP were compared with the global diversity panel (GDP) that consists of 692 worldwide sorghum accessions (excluding accessions from Americas) with available sequencing data, including West African accessions in the GDP (hereafter named WAS-GDP) (Morris et al , 2013;Lasky et al , 2015). WASAP accessions were also compared to previously genotyped West African accessions from USDA-GRIN (hereafter named WAS-GRIN), originating from Niger (NiGRIN), Senegal (SnGRIN; including a few accessions from neighboring Gambia and Mauritania), and Nigeria (NGrGRIN) Olatoye et al , 2018;Faye et al , 2019).…”

“…Background effect was accounted for using ADMIXTURE ancestry fractions used as fixed effect covariates. Candidate gene colocalization with QTL was carried out using an a priori candidate genes/loci list, including known sorghum genes and orthologs of rice and maize for adaptive traits, previously described (Faye et al , 2019). The Sorghum QTL Atlas (Mace et al , 2019) was used to compare QTLs identified in the current study to QTLs from previous studies.…”

“…Sorghum genetic studies have identified population structure by botanical type and geographic region at regional scale (Deu et al , 2006;Bouchet et al , 2012;Morris et al , 2013;Wang et al , 2019) and at country level in the Senegal and Niger germplasm (Deu et al , 2008;Faye et al , 2019). The genetic diversity of the WASAP was structured by botanical type within each country of origin ( Fig.…”