Exploring the sorghum race level diversity utilizing 272 sorghum accessions genomic resources.

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.

Genetic Dissection and Quantitative Trait Loci Mapping of Agronomic and Fodder Quality Traits in Sorghum Under Different Water Regimes.

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.

Sorghum Pan-Genome Explores the Functional Utility for Genomic-Assisted Breeding to Accelerate the Genetic Gain.

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.

Nitrogen Use Efficiency in Sorghum: Exploring Native Variability for Traits Under Variable N-Regimes.

Exploring the natural genetic variability and its exploitation for improved Nitrogen Use Efficiency (NUE) in sorghum is one of the primary goals in the modern crop improvement programs. The integrated strategies include high-throughput phenotyping, next generation sequencing (NGS)-based genotyping technologies, and a priori selected candidate gene studies that help understand the detailed physiological and molecular mechanisms underpinning this complex trait. A set of sixty diverse sorghum genotypes was evaluated for different vegetative, reproductive, and yield traits related to NUE in the field (under three N regimes) for two seasons. Significant variations for different yield and related traits under 0 and 50% N confirmed the availability of native genetic variability in sorghum under low N regimes. Sorghum genotypes with distinct genetic background had interestingly similar NUE associated traits. The Genotyping-By-Sequencing based SNPs (>89 K) were used to study the population structure, and phylogenetic groupings identified three distinct groups. The information of grain N and stalk N content of the individuals covered on the phylogenetic groups indicated randomness in the distribution for adaptation under variable N regimes. This study identified promising sorghum genotypes with consistent performance under varying environments, with buffer capacity for yield under low N conditions. We also report better performing genotypes for varied production use-grain, stover, and dual-purpose sorghum having differential adaptation response to NUE traits. Expression profiling of NUE associated genes in shoot and root tissues of contrasting lines (PVK801 and HDW703) grown in varying N conditions revealed interesting outcomes. Root tissues of contrasting lines exhibited differential expression profiles for transporter genes [ammonium transporter (SbAMT), nitrate transporters (SbNRT)]; primary assimilatory (glutamine synthetase (SbGS), glutamate synthase (SbGOGAT[NADH], SbGOGAT[Fd]), assimilatory genes [nitrite reductase (SbNiR[NADH]3)]; and amino acid biosynthesis associated gene [glutamate dehydrogenase (SbGDH)]. Identification and expression profiling of contrasting sorghum genotypes in varying N dosages will provide new information to understand the response of NUE genes toward adaptation to the differential N regimes in sorghum. High NUE genotypes identified from this study could be potential candidates for in-depth molecular analysis and contribute toward the development of N efficient sorghum cultivars.

Genome-Wide Association Study for Major Biofuel Traits in Sorghum Using Minicore Collection.

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.

A sorghum practical haplotype graph facilitates genome-wide imputation and cost-effective genomic prediction.

Successful management and utilization of increasingly large genomic datasets is essential for breeding programs to accelerate cultivar development. To help with this, we developed a Sorghum bicolor Practical Haplotype Graph (PHG) pangenome database that stores haplotypes and variant information. We developed two PHGs in sorghum that were used to identify genome-wide variants for 24 founders of the Chibas sorghum breeding program from 0.01x sequence coverage. The PHG called single nucleotide polymorphisms (SNPs) with 5.9% error at 0.01x coverage-only 3% higher than PHG error when calling SNPs from 8x coverage sequence. Additionally, 207 progenies from the Chibas genomic selection (GS) training population were sequenced and processed through the PHG. Missing genotypes were imputed from PHG parental haplotypes and used for genomic prediction. Mean prediction accuracies with PHG SNP calls range from .57-.73 and are similar to prediction accuracies obtained with genotyping-by-sequencing or targeted amplicon sequencing (rhAmpSeq) markers. This study demonstrates the use of a sorghum PHG to impute SNPs from low-coverage sequence data and shows that the PHG can unify genotype calls across multiple sequencing platforms. By reducing input sequence requirements, the PHG can decrease the cost of genotyping, make GS more feasible, and facilitate larger breeding populations. Our results demonstrate that the PHG is a useful research and breeding tool that maintains variant information from a diverse group of taxa, stores sequence data in a condensed but readily accessible format, unifies genotypes across genotyping platforms, and provides a cost-effective option for genomic selection.

Fine-Mapping of Sorghum Stay-Green QTL on Chromosome10 Revealed Genes Associated with Delayed Senescence.

This study was conducted to dissect the genetic basis and to explore the candidate genes underlying one of the important genomic regions on an SBI-10 long arm (L), governing the complex stay-green trait contributing to post-flowering drought-tolerance in sorghum. A fine-mapping population was developed from an introgression line cross-RSG04008-6 (stay-green) × J2614-11 (moderately senescent). The fine-mapping population with 1894 F2 was genotyped with eight SSRs and a set of 152 recombinants was identified, advanced to the F4 generation, field evaluated with three replications over 2 seasons, and genotyped with the GBS approach. A high-resolution linkage map was developed for SBI-10L using 260 genotyping by sequencing-Single Nucleotide Polymorphism (GBS-SNPs). Using the best linear unpredicted means (BLUPs) of the percent green leaf area (%GL) traits and the GBS-based SNPs, we identified seven quantitative trait loci (QTL) clusters and single gene, mostly involved in drought-tolerance, for each QTL cluster, viz., AP2/ERF transcription factor family (Sobic.010G202700), NBS-LRR protein (Sobic.010G205600), ankyrin-repeat protein (Sobic.010G205800), senescence-associated protein (Sobic.010G270300), WD40 (Sobic.010G205900), CPK1 adapter protein (Sobic.010G264400), LEA2 protein (Sobic.010G259200) and an expressed protein (Sobic.010G201100). The target genomic region was thus delimited from 15 Mb to 8 genes co-localized with QTL clusters, and validated using quantitative real-time (qRT)-PCR.

Introgression of Shoot Fly (Atherigona soccata L. Moench) Resistance QTLs into Elite Post-rainy Season Sorghum Varieties Using Marker Assisted Backcrossing (MABC).

Shoot fly (Atherigona soccata L. Moench) is a serious pest in sorghum production. Management of shoot fly using insecticides is expensive and environmentally un-safe. Developing host-plant resistance is the best method to manage shoot fly infestation. Number of component traits contribute for imparting shoot fly resistance in sorghum and molecular markers have been reported which were closely linked to QTLs controlling these component traits. In this study, three QTLs associated with shoot fly resistance were introgressed into elite cultivars Parbhani Moti (= SPV1411) and ICSB29004 using marker assisted backcrossing (MABC). Crosses were made between recurrent parents and the QTL donors viz., J2658, J2614, and J2714. The F1s after confirmation for QTL presence were backcrossed to recurrent parents and the resultant lines after two backcrosses were selfed thrice for advancement. The foreground selection was carried out in F1 and BCnF1 generations with 22 polymorphic markers. Forty-three evenly distributed simple sequence repeat markers in the sorghum genome were used in background selection to identify plants with higher recurrent parent genome recovery. By using two backcrosses and four rounds of selfing, six BC2F4 progenies were selected for ICSB29004 × J2658, five BC2F4 progenies were selected for ICSB29004 × J2714 and six BC2F4 progenies were selected for Parbhani Moti × J2614 crosses. Phenotyping of these lines led to the identification of two resistant lines for each QTL region present on chromosome SBI-01, SBI-07 and SBI-10 in ICSB 29004 and Parbhani Moti. All the introgression lines (ILs) showed better shoot fly resistance than the recurrent parents and their agronomic performance was the same or better than the recurrent parents. Further, the ILs had medium plant height, desirable maturity with high yield potential which makes them better candidates for commercialization. In the present study, MABC has successfully improved the shoot fly resistance in sorghum without a yield penalty. This is the first report on the use of MABC for improving shoot fly resistance in post-rainy season sorghum.

Genetic Variability, Genotype × Environment Interaction, Correlation, and GGE Biplot Analysis for Grain Iron and Zinc Concentration and Other Agronomic Traits in RIL Population of Sorghum (Sorghum bicolor L. Moench).

The low grain iron and zinc densities are well documented problems in food crops, affecting crop nutritional quality especially in cereals. Sorghum is a major source of energy and micronutrients for majority of population in Africa and central India. Understanding genetic variation, genotype × environment interaction and association between these traits is critical for development of improved cultivars with high iron and zinc. A total of 336 sorghum RILs (Recombinant Inbred Lines) were evaluated for grain iron and zinc concentration along with other agronomic traits for 2 years at three locations. The results showed that large variability exists in RIL population for both micronutrients (Iron = 10.8 to 76.4 mg kg-1 and Zinc = 10.2 to 58.7 mg kg-1, across environments) and agronomic traits. Genotype × environment interaction for both micronutrients (iron and zinc) was highly significant. GGE biplots comparison for grain iron and zinc showed greater variation across environments. The results also showed that G × E was substantial for grain iron and zinc, hence wider testing needed for taking care of G × E interaction to breed micronutrient rich sorghum lines. Iron and zinc concentration showed high significant positive correlation (across environment = 0.79; p < 0.01) indicating possibility of simultaneous effective selection for both the traits. The RIL population showed good variability and high heritabilities (>0.60, in individual environments) for Fe and Zn and other traits studied indicating its suitability to map QTL for iron and zinc.

Population Genetics and Structure of a Global Foxtail Millet Germplasm Collection.

Foxtail millet [Setaria italica (L.) P. Beauv.] is one among the most ancient crops of dryland agriculture. It is the second most important crop among millets grown for grains or forage. Foxtail millet germplasm resources provide reservoirs of novel alleles and genes for crop improvement that have remained mostly unexplored. We genotyped a set of 190 foxtail millet germplasm accessions (including 155 accessions of the foxtail millet core collection) using genotyping-by-sequencing (GBS) for rapid single nucleotide polymorphisms (SNP) characterization to study population genetics and structure, which enable allele mining through association mapping approaches. After filtering a total 350,000 raw SNPs identified across 190 germplasm accessions for minor allele frequency (MAF), coverage for samples and coverage for sites, we retained 181 accessions with 17,714 high-quality SNPs with ≥5% MAF. Genetic structure analyses revealed that foxtail millet germplasm accessions are structured along both on the basis of races and geographic origin, and the maximum proportion of variation was due to among individuals within populations. Accessions of race indica were less diverse and are highly differentiated from those of maxima and moharia. Genome-wide linkage disequilibrium (LD) analysis showed on an average LD extends up to ∼150 kbp and varied with individual chromosomes. The utility of the data for performing genome-wide association studies (GWASs) was tested with plant pigmentation and days to flowering and identified significant marker-trait associations. This SNP data provides a foundation for exploration of foxtail millet diversity and for mining novel alleles and mapping genes for economically important traits.

Population genomic and genome-wide association studies of agroclimatic traits in sorghum.

Accelerating crop improvement in sorghum, a staple food for people in semiarid regions across the developing world, is key to ensuring global food security in the context of climate change. To facilitate gene discovery and molecular breeding in sorghum, we have characterized ~265,000 single nucleotide polymorphisms (SNPs) in 971 worldwide accessions that have adapted to diverse agroclimatic conditions. Using this genome-wide SNP map, we have characterized population structure with respect to geographic origin and morphological type and identified patterns of ancient crop diffusion to diverse agroclimatic regions across Africa and Asia. To better understand the genomic patterns of diversification in sorghum, we quantified variation in nucleotide diversity, linkage disequilibrium, and recombination rates across the genome. Analyzing nucleotide diversity in landraces, we find evidence of selective sweeps around starch metabolism genes, whereas in landrace-derived introgression lines, we find introgressions around known height and maturity loci. To identify additional loci underlying variation in major agroclimatic traits, we performed genome-wide association studies (GWAS) on plant height components and inflorescence architecture. GWAS maps several classical loci for plant height, candidate genes for inflorescence architecture. Finally, we trace the independent spread of multiple haplotypes carrying alleles for short stature or long inflorescence branches. This genome-wide map of SNP variation in sorghum provides a basis for crop improvement through marker-assisted breeding and genomic selection.

Stay-green quantitative trait loci's effects on water extraction, transpiration efficiency and seed yield depend on recipient parent background.

A stay-green phenotype enhances the adaptation of sorghum (Sorghum bicolor (L.) Moench) to terminal drought, although the mechanisms leading to its expression remain unclear. Differences in tillering and leaf area at anthesis, transpiration efficiency (TE), water extraction, harvest index (HI) and yield under terminal drought and fully irrigated conditions were assessed in 29 introgression lines (IL) targeting stay-green quantitative trait loci (QTLs) Stg1, Stg2, Stg3, Stg4, StgA and StgB in an S35 background, and 16 IL targeting Stg1, Stg3, Stg4 and StgB in an R16 background. TE was increased by StgB in the R16 background, whereas there was no effect in the S35 background. Water extraction was increased by Stg1 in the S35 background but not in R16. StgB modified the proportion of water extracted before and after anthesis in the S35 background. While tillering and leaf area at anthesis were decreased by Stg1 and Stg3 in S35, there was no effect in R16. Yield data under fully irrigated conditions showed higher tiller grain yield in Stg1, Stg2 and Stg3 ILs. Although yield differences were mostly explained by HI variation, the yield variation unexplained by HI was closely related to TE in S35 (R2=0.29) and R16 (R2=0.72), and was closely related to total water extracted in S35 (R2=0.41) but not in R16. These data indicate the potential for several stay-green QTLs to affect traits related to plant water use. However, these effects depend on the interaction between the genetic background and individual QTLs.