Functional genomic effects of indels using Bayesian genome-phenome wide association studies in sorghum

High-throughput genomic and phenomic data have enhanced the ability to detect genotype-to-phenotype associations that can resolve broad pleiotropic effects of mutations on plant phenotypes. As the scale of genotyping and phenotyping has advanced, rigorous methodologies have been developed to accommodate larger datasets and maintain statistical precision. However, determining the functional effects of associated genes/loci is expensive and limited due to the complexity associated with cloning and subsequent characterization. Here, we utilized phenomic imputation of a multi-year, multi-environment dataset using PHENIX which imputes missing data using kinship and correlated traits, and we screened insertions and deletions (InDels) from the recently whole-genome sequenced Sorghum Association Panel for putative loss-of-function effects. Candidate loci from genome-wide association results were screened for potential loss of function using a Bayesian Genome-Phenome Wide Association Study (BGPWAS) model across both functionally characterized and uncharacterized loci. Our approach is designed to facilitate in silico validation of associations beyond traditional candidate gene and literature-search approaches and to facilitate the identification of putative variants for functional analysis and reduce the incidence of false-positive candidates in current functional validation methods. Using this Bayesian GPWAS model, we identified associations for previously characterized genes with known loss-of-function alleles, specific genes falling within known quantitative trait loci, and genes without any previous genome-wide associations while additionally detecting putative pleiotropic effects. In particular, we were able to identify the major tannin haplotypes at the Tan1 locus and effects of InDels on the protein folding. Depending on the haplotype present, heterodimer formation with Tan2 was significantly affected. We also identified major effect InDels in Dw2 and Ma1, where proteins were truncated due to frameshift mutations that resulted in early stop codons. These truncated proteins also lost most of their functional domains, suggesting that these indels likely result in loss of function. Here, we show that the Bayesian GPWAS model is able to identify loss-of-function alleles that can have significant effects upon protein structure and folding as well as multimer formation. Our approach to characterize loss-of-function mutations and their functional repercussions will facilitate precision genomics and breeding by identifying key targets for gene editing and trait integration

Sorghum Association Panel whole-genome sequencing establishes cornerstone resource for dissecting genomic diversity

Association mapping panels represent foundational resources for understanding the genetic basis of phenotypic diversity and serve to advance plant breeding by exploring genetic variation across diverse accessions. We report the whole-genome sequencing (WGS) of 400 sorghum (Sorghum bicolor (L.) Moench) accessions from the Sorghum Association Panel (SAP) at an average coverage of 38× (25–72×), enabling the development of a high-density genomic marker set of 43 983 694 variants including single-nucleotide polymorphisms (approximately 38 million), insertions/deletions (indels) (approximately 5 million), and copy number variants (CNVs) (approximately 170 000). We observe slightly more deletions among indels and a much higher prevalence of deletions among CNVs compared to insertions. This new marker set enabled the identification of several novel putative genomic associations for plant height and tannin content, which were not identified when using previous lower-density marker sets. WGS identified and scored variants in 5-kb bins where available genotyping-by-sequencing (GBS) data captured no variants, with half of all bins in the genome falling into this category. The predictive ability of genomic best unbiased linear predictor (GBLUP) models was increased by an average of 30% by using WGS markers rather than GBS markers. We identified 18 selection peaks across subpopulations that formed due to evolutionary divergence during domestication, and we found six Fst peaks resulting from comparisons between converted lines and breeding lines within the SAP that were distinct from the peaks associated with historic selection. This population has served and continues to serve as a significant public resource for sorghum research and demonstrates the value of improving upon existing genomic resources

Discovering useful genetic variation in the seed parent gene pool for sorghum improvement

Multi-parent populations contain valuable genetic material for dissecting complex, quantitative traits and provide a unique opportunity to capture multi-allelic variation compared to the biparental populations. A multi-parent advanced generation inter-cross (MAGIC) B-line (MBL) population composed of 708 F6 recombinant inbred lines (RILs), was recently developed from four diverse founders. These selected founders strategically represented the four most prevalent botanical races (kafir, guinea, durra, and caudatum) to capture a significant source of genetic variation to study the quantitative traits in grain sorghum [Sorghum bicolor (L.) Moench]. MBL was phenotyped at two field locations for seven yield-influencing traits: panicle type (PT), days to anthesis (DTA), plant height (PH), grain yield (GY), 1000-grain weight (TGW), tiller number per meter (TN) and yield per panicle (YPP). High phenotypic variation was observed for all the quantitative traits, with broad-sense heritabilities ranging from 0.34 (TN) to 0.84 (PH). The entire population was genotyped using Diversity Arrays Technology (DArTseq), and 8,800 single nucleotide polymorphisms (SNPs) were generated. A set of polymorphic, quality-filtered markers (3,751 SNPs) and phenotypic data were used for genome-wide association studies (GWAS). We identified 52 marker-trait associations (MTAs) for the seven traits using BLUPs generated from replicated plots in two locations. We also identified desirable allelic combinations based on the plant height loci (Dw1, Dw2, and Dw3), which influences yield related traits. Additionally, two novel MTAs were identified each on Chr1 and Chr7 for yield traits independent of dwarfing genes. We further performed a multi-variate adaptive shrinkage analysis and 15 MTAs with pleiotropic effect were identified. The five best performing MBL progenies were selected carrying desirable allelic combinations. Since the MBL population was designed to capture significant diversity for maintainer line (B-line) accessions, these progenies can serve as valuable resources to develop superior sorghum hybrids after validation of their general combining abilities via crossing with elite pollinators. Further, newly identified desirable allelic combinations can be used to enrich the maintainer germplasm lines through marker-assisted backcross breeding

Exchange Bias in Fe@Cr Core–Shell Nanoparticles

We have used X-ray magnetic circular dichroism and magnetometry to study isolated Fe@Cr core−shell nanoparticles with an Fe core diameter of 2.7 nm (850 atoms) and a Cr shell thickness varying between 1 and 2 monolayers. The addition of Cr shells significantly reduces the spin moment but does not change the orbital moment. At least two Cr atomic layers are required to stabilize a ferromagnetic/antiferromagnetic interface and generate the associated exchange bias and increase in coercivity

Identification of pleiotropic loci mediating structural and non-structural carbohydrate accumulation within the sorghum bioenergy association panel using high-throughput markers

Molecular characterization of diverse germplasm can contribute to breeding programs by increasing genetic gain for sorghum [Sorghum bicolor (L.) Moench] improvement. Identifying novel marker-trait associations and candidate genes enriches the existing genomic resources and can improve bioenergy-related traits using genomic-assisted breeding. In the current scenario, identifying the genetic loci underlying biomass and carbon partitioning is vital for ongoing efforts to maximize each carbon sink’s yield for bioenergy production. Here, we have processed a high-density genomic marker (22 466 550) data based on whole-genome sequencing (WGS) using a set of 365 accessions from the bioenergy association panel (BAP), which includes ~19.7 million (19 744 726) single nucleotide polymorphism (SNPs) and 2.7 million (~2 721 824) insertion deletions (indels). A set of high-quality filtered SNP (~5.48 million) derived markers facilitated the assessment of population structure, genetic diversity, and genome-wide association studies (GWAS) for various traits related to biomass and its composition using the BAP. The phenotypic traits for GWAS included seed color (SC), plant height (PH), days to harvest (DTH), fresh weight (FW), dry weight (DW), brix content % (BRX), neutral detergent fiber (NDF), acid detergent fiber (ADF), non-fibrous carbohydrate (NFC), and lignin content. Several novel loci and candidate genes were identified for bioenergy-related traits, and some well-characterized genes for plant height (Dw1 and Dw2) and the YELLOW SEED1 locus (Y1) were validated. We further performed a multi-variate adaptive shrinkage analysis to identify pleiotropic QTL, which resulted in several shared marker-trait associations among bioenergy and compositional traits. Significant marker-trait associations with pleiotropic effects can be used to develop molecular markers for trait improvement using a marker-assisted breeding approach. Significant nucleotide diversity and heterozygosity were observed between photoperiod-sensitive and insensitive individuals of the panel. This diverse bioenergy panel with genomic resources will provide an excellent opportunity for further genetic studies, including selecting parental lines for superior hybrid development to improve biomass-related traits in sorghum

Table_1_Identification of pleiotropic loci mediating structural and non-structural carbohydrate accumulation within the sorghum bioenergy association panel using high-throughput markers.xlsx

Molecular characterization of diverse germplasm can contribute to breeding programs by increasing genetic gain for sorghum [Sorghum bicolor (L.) Moench] improvement. Identifying novel marker-trait associations and candidate genes enriches the existing genomic resources and can improve bioenergy-related traits using genomic-assisted breeding. In the current scenario, identifying the genetic loci underlying biomass and carbon partitioning is vital for ongoing efforts to maximize each carbon sink’s yield for bioenergy production. Here, we have processed a high-density genomic marker (22 466 550) data based on whole-genome sequencing (WGS) using a set of 365 accessions from the bioenergy association panel (BAP), which includes ~19.7 million (19 744 726) single nucleotide polymorphism (SNPs) and 2.7 million (~2 721 824) insertion deletions (indels). A set of high-quality filtered SNP (~5.48 million) derived markers facilitated the assessment of population structure, genetic diversity, and genome-wide association studies (GWAS) for various traits related to biomass and its composition using the BAP. The phenotypic traits for GWAS included seed color (SC), plant height (PH), days to harvest (DTH), fresh weight (FW), dry weight (DW), brix content % (BRX), neutral detergent fiber (NDF), acid detergent fiber (ADF), non-fibrous carbohydrate (NFC), and lignin content. Several novel loci and candidate genes were identified for bioenergy-related traits, and some well-characterized genes for plant height (Dw1 and Dw2) and the YELLOW SEED1 locus (Y1) were validated. We further performed a multi-variate adaptive shrinkage analysis to identify pleiotropic QTL, which resulted in several shared marker-trait associations among bioenergy and compositional traits. Significant marker-trait associations with pleiotropic effects can be used to develop molecular markers for trait improvement using a marker-assisted breeding approach. Significant nucleotide diversity and heterozygosity were observed between photoperiod-sensitive and insensitive individuals of the panel. This diverse bioenergy panel with genomic resources will provide an excellent opportunity for further genetic studies, including selecting parental lines for superior hybrid development to improve biomass-related traits in sorghum.</p

DataSheet_1_Identification of pleiotropic loci mediating structural and non-structural carbohydrate accumulation within the sorghum bioenergy association panel using high-throughput markers.pdf

Molecular characterization of diverse germplasm can contribute to breeding programs by increasing genetic gain for sorghum [Sorghum bicolor (L.) Moench] improvement. Identifying novel marker-trait associations and candidate genes enriches the existing genomic resources and can improve bioenergy-related traits using genomic-assisted breeding. In the current scenario, identifying the genetic loci underlying biomass and carbon partitioning is vital for ongoing efforts to maximize each carbon sink’s yield for bioenergy production. Here, we have processed a high-density genomic marker (22 466 550) data based on whole-genome sequencing (WGS) using a set of 365 accessions from the bioenergy association panel (BAP), which includes ~19.7 million (19 744 726) single nucleotide polymorphism (SNPs) and 2.7 million (~2 721 824) insertion deletions (indels). A set of high-quality filtered SNP (~5.48 million) derived markers facilitated the assessment of population structure, genetic diversity, and genome-wide association studies (GWAS) for various traits related to biomass and its composition using the BAP. The phenotypic traits for GWAS included seed color (SC), plant height (PH), days to harvest (DTH), fresh weight (FW), dry weight (DW), brix content % (BRX), neutral detergent fiber (NDF), acid detergent fiber (ADF), non-fibrous carbohydrate (NFC), and lignin content. Several novel loci and candidate genes were identified for bioenergy-related traits, and some well-characterized genes for plant height (Dw1 and Dw2) and the YELLOW SEED1 locus (Y1) were validated. We further performed a multi-variate adaptive shrinkage analysis to identify pleiotropic QTL, which resulted in several shared marker-trait associations among bioenergy and compositional traits. Significant marker-trait associations with pleiotropic effects can be used to develop molecular markers for trait improvement using a marker-assisted breeding approach. Significant nucleotide diversity and heterozygosity were observed between photoperiod-sensitive and insensitive individuals of the panel. This diverse bioenergy panel with genomic resources will provide an excellent opportunity for further genetic studies, including selecting parental lines for superior hybrid development to improve biomass-related traits in sorghum.</p

The impacts of season and livestock management strategy on the quality of diets selected by goats and sheep in the semi-arid rangelands of Namaqualand, South Africa

Access to good-quality forages is one of the major limitations to livestock production in semi-arid pastoral systems. This study aimed to determine whether there are differences in the nutritional quality of diets selected by herded and free-ranging goat and sheep flocks utilising Namaqualand Granite Renosterveld vegetation during the wet and dry seasons. Plant samples collected along the grazing routes of livestock were dried and analysed for their fibre, condensed tannin, total phenolic and mineral nutrient contents. The study showed that a large variety of forages were on offer and livestock groups selected different diets of which some were different to the total diet on offer. In general, significant deficiencies in phosphate, protein and energy in the diets selected by herded and free-ranging goats and sheep were observed in both wet and dry season. The quality of the diets selected by herded and free-ranging livestock was also found to be different from each other, with herded livestock generally selecting more nutrient-dense diets. Herding, therefore, allows livestock to access better-quality forage in the Namaqualand Granite Renosterveld rangeland, where it is generally poor.Keywords: herding, Namaqualand Granite Renosterveld, pastoral livestock, protein deficiencies, small stock nutritio