ABSTRACT
Due to evolutionary divergence, sorghum race populations exhibit significant genetic and morphological variation. A k-mer-based sorghum race sequence comparison identified the conserved k-mers of all 272 accessions from sorghum and the race-specific genetic signatures identified the gene variability in 10,321 genes (PAVs). To understand sorghum race structure, diversity and domestication, a deep learning-based variant calling approach was employed in a set of genotypic data derived from a diverse panel of 272 sorghum accessions. The data resulted in 1.7 million high-quality genome-wide SNPs and identified selective signature (both positive and negative) regions through a genome-wide scan with different (iHS and XP-EHH) statistical methods. We discovered 2,370 genes associated with selection signatures including 179 selective sweep regions distributed over 10 chromosomes. Co-localization of these regions undergoing selective pressure with previously reported QTLs and genes revealed that the signatures of selection could be related to the domestication of important agronomic traits such as biomass and plant height. The developed k-mer signatures will be useful in the future to identify the sorghum race and for trait and SNP markers for assisting in plant breeding programs.
ABSTRACT
Livestock provides an additional source of income for marginal cropping farmers, but crop residues that are used as a main source of animal feed are characteristically low in digestibility and protein content. This reduces the potential livestock product yield and quality. The key trait, which influences the quality and the cost of animal feed, is digestibility. In this study, we demonstrate that sorghum breeding can be directed to achieve genetic gains for both fodder biomass and digestibility without any trade-offs. The genotypic variance has shown significant differences for biomass across years (13,035 in 2016 and 3,395 in 2017) while in vitro organic matter digestibility (IVOMD) showed significant genotypic variation in 2016 (0.253) under drought. A range of agronomic and fodder quality traits was found to vary significantly in the population within both the control and drought conditions and across both years of the study. There was significant genotypic variance (σg2) and genotypic × treatment variance (σgxt2) in dry matter production in a recombinant inbred line (RIL) population in both study years, while there was only significant σg2 and σgxt2 in IVOMD under the control conditions. There was no significant correlation identified between biomass and digestibility traits under the control conditions, but there was a positive correlation under drought. However, a negative relation was observed between digestibility and grain yield under the control conditions, while there was no significant correlation under drought population, which was genotyped using the genotyping-by-sequencing (GBS) technique, and 1,141 informative single nucleotide polymorphism (SNP) markers were identified. A linkage map was constructed, and a total of 294 quantitative trait loci (QTLs) were detected, with 534 epistatic interactions, across all of the traits under study. QTL for the agronomic traits fresh and dry weight, together with plant height, mapped on to the linkage group (LG) 7, while QTL for IVOMD mapped on to LG1, 2, and 8. A number of genes previously reported to play a role in nitrogen metabolism and cell wall-related functions were found to be associated with these QTL.
ABSTRACT
Pearl millet is a crucial nutrient-rich staple food in Asia and Africa and adapted to the climate of semi-arid topics. Since the genomic resources in pearl millet are very limited, we have developed a brand-new mid-density 4K SNP panel and demonstrated its utility in genetic studies. A set of 4K SNPs were mined from 925 whole-genome sequences through a comprehensive in-silico pipeline. Three hundred and seventy-three genetically diverse pearl millet inbreds were genotyped using the newly-developed 4K SNPs through the AgriSeq Targeted Genotyping by Sequencing technology. The 4K SNPs were uniformly distributed across the pearl millet genome and showed considerable polymorphism information content (0.23), genetic diversity (0.29), expected heterozygosity (0.29), and observed heterozygosity (0.03). The SNP panel successfully differentiated the accessions into two major groups, namely B and R lines, through genetic diversity, PCA, and structure models as per their pedigree. The linkage disequilibrium (LD) analysis showed Chr3 had higher LD regions while Chr1 and Chr2 had more low LD regions. The genetic divergence between the B- and R-line populations was 13%, and within the sub-population variability was 87%. In this experiment, we have mined 4K SNPs and optimized the genotyping protocol through AgriSeq technology for routine use, which is cost-effective, fast, and highly reproducible. The newly developed 4K mid-density SNP panel will be useful in genomics and molecular breeding experiments such as assessing the genetic diversity, trait mapping, backcross breeding, and genomic selection in pearl millet.
ABSTRACT
Sorghum (Sorghum bicolor L.) is a staple food crops in the arid and rainfed production ecologies. Sorghum plays a critical role in resilient farming and is projected as a smart crop to overcome the food and nutritional insecurity in the developing world. The development and characterisation of the sorghum pan-genome will provide insight into genome diversity and functionality, supporting sorghum improvement. We built a sorghum pan-genome using reference genomes as well as 354 genetically diverse sorghum accessions belonging to different races. We explored the structural and functional characteristics of the pan-genome and explain its utility in supporting genetic gain. The newly-developed pan-genome has a total of 35,719 genes, a core genome of 16,821 genes and an average of 32,795 genes in each cultivar. The variable genes are enriched with environment responsive genes and classify the sorghum accessions according to their race. We show that 53% of genes display presence-absence variation, and some of these variable genes are predicted to be functionally associated with drought adaptation traits. Using more than two million SNPs from the pan-genome, association analysis identified 398 SNPs significantly associated with important agronomic traits, of which, 92 were in genes. Drought gene expression analysis identified 1,788 genes that are functionally linked to different conditions, of which 79 were absent from the reference genome assembly. This study provides comprehensive genomic diversity resources in sorghum which can be used in genome assisted crop improvement.
ABSTRACT
BACKGROUND: Production of biofuels from lignocellulosic crop biomass is an alternative to reduce greenhouse gas emissions. The biofuel production involves collecting biomass, breaking down cell wall components followed by the conversion of sugars to ethanol. The lingo-cellulosic biomass comprises 40-50% cellulose, 20-30% hemicellulose, and 10-25% lignin. Sorghum is a widely adapted energy crop for biofuel production. Biomass with low lignin, high cellulose, and high hemicellulose contents are exploited to attain maximum biofuel production efficiency. Resistance to lodging, pest, disease, and abiotic stresses related to cell wall components is well documented, and quantitative trait loci were identified to understand these traits' genetic correlation. Selection for reduced lignin and increased cellulose content in stover can increase the ethanol yield. The Genome-Wide Association Studies (GWAS) is a complementary approach to evaluating the marker and phenotype associations among large diversity panels. Single nucleotide polymorphisms were scanned to identify loci associated with the traits of interest. In this study, the GWAS was performed on 245 sorghum minicore genotypes to analyze agronomic traits (days to 50%flowering, fresh biomass yield, dry biomass yield) and cell wall components (cellulose, hemicellulose, and lignin). Further, in-silico validation of the candidate genes was performed in a global gene expression data from large-scale RNA sequencing studies in sorghum available in the NCBI GEO database was used. OBJECTIVE: The objectives of this study are to evaluate native variations in biofuel related agronomic traits and stalk cell wall components and to identify significant SNPs or loci related to the cell wall components. METHODS: In this article, an association mapping panel, comprising of 245 sorghum minicore germplasm accessions, was evaluated during two post rainy seasons of 2013 and 2014, and observations were recorded on the whole plot- for days to 50% flowering, fresh biomass yield (tha-1, and dry biomass yield (tha-1). The biomass of sun-dried plants from both seasons was collected separately, chopped, dried, and ground to powder. The cellulose, hemicellulose, and lignin contents were determined in the powdered. The content of each of these three components in sorghum was expressed in percent of dry matter. The data on agronomic traits and composition analysis was subjected to Analysis of Variance. For the current study, we remapped the raw GBS data with the sorghum assembly version v3.1. A total of 27,589 SNPs were obtained with a minor allele frequency (MAF) >1% and missing data <50%. The GWAS was performed in a single minicore population using FarmCPU, in R software. The synteny positions of the identified significant SNPs between sorghum and other model crop species viz., maize, switchgrass, and Arabidopsis were represented using CIRCOS software for traits viz., dry biomass yield, cellulose, hemicellulose, and lignin. The transcriptome dataset from where sorghum gene atlas studies of grain, sweet, and bioenergy sorghums are available through NCBI's Gene Expression Omnibus (GEO) under accession number GSE49879, was used to cross-validate the identified SNPs for cellulose, hemicellulose, and lignin through GWAS. RESULTS: High broad-sense heritability was exhibited for all the traits in individual seasons along with significant genotype × environment interaction across seasons except lignin. Association mapping with a P < 1×10-4 revealed genomic regions associated with the- (i) agronomic traits (days to 50% flowering, fresh and dry biomass), and (ii) biochemical traits (cellulose, hemicellulose, and lignin) associated with biofuels production, in individual seasons. Twelve significant SNPs for flowering time, 30 fresh biomass yields, and 24 for dry biomass yield, 25 for cellulose, 7 for hemicellulose, and 21 for lignin were identified. CIRCOS plot was constructed to identify and analyze similarities and differences while comparing the sorghum genome with different crops. For cellulose high similarity of >80% was observed for all sorghum gene sequences with the maize homologs. The overall similarity of sorghum homologs with foxtail millet was >65%, for Arabidopsis from 30.6% to 48.6%, and rice from 28.2% to 92.8%. SNPs for hemicellulose displayed maximum similarity to foxtail millet followed by maize. The sequence similarity of lignin SNPs in sorghum was highest with the maize genome followed by Arabidopsis. Both rice and foxtail millet showed >55% similarity to the sorghum genome. CONCLUSION: This study reports large variability for agronomic and biofuel traits in the sorghum minicore collection with high heritability. The genetic architecture of cell wall components using the GWAS approach was studied and candidate genes for each component were annotated. These results give a better understanding of the genetic basis of the sorghum cell wall composition. The association analysis identified regions of the genome that could be targeted to enhance the quality of biomass and yield along with the desired composition promoting breeding efficiency for enhanced biofuel yield.
