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Kresovich, S.

Publications and source records attributed to Kresovich, S..

7 recordsLinked to original sources

Developing future resilience from signatures of adaptation across the sorghum pangenome

While the green revolution adapted a handful of crops to homogenous and high-input industrialized agriculture, much of the global population still relies on local food production from low-input smallholder farms that grow highly variable crop cultivars. The high diversity of the grain and bioenergy crop sorghum 1-4, and many other crops that were not homogenized during the green revolution 5, not only provides the raw materials for breeders to make substantial gains in cultivar improvement, but also constrains breeding efforts due to highly specialized locally adapted plant phenotypes 6. Here, we construct a 33-member pangenome and identify trait-associated variants in 1,988 cultivars and landraces. We then apply these resources to explore the complex interplay between historical contingency, ongoing adaptation, and the potential for future gains through climate-aware genome-enabled breeding. Specifically, our analyses conclusively demonstrate that multiple nested, deeply diverged, and previously uncharacterized structural variants in the domestication gene SHATTERING1 distinguish the previously established multicentric origin of sorghum. We then apply landscape genomics tests to reveal how gene flow, adaptation, and secondary contact created the complex genetic mosaic in current global breeding networks. Further analysis of climate-gene associations highlights candidate loci underlying adaptation, including the biosynthetic gene cluster for the cyanogenic glucoside dhurrin. Combined, the pangenome-informed variants developed here will enable both trait discovery and subsequent marker assays to accelerate breeding and provide a framework for similar applications in other diverse and non-model crops.

genomics↗

Dissecting the Genetic Architecture of Carbon Partitioning in Sorghum using Multiscale Phenotypes

Carbon partitioning in plants may be viewed as a dynamic process composed of the many interactions between sources and sinks. The accumulation and distribution of fixed carbon is not dictated simply by the sink strength and number but is dependent upon the source, pathways, and interactions of the system. As such, the study of carbon partitioning through perturbations to the system or through focus on individual traits may fail to produce actionable developments or a comprehensive understanding of the mechanisms underlying this complex process. Using the recently published sorghum carbon-partitioning panel, we collected both macroscale phenotypic characteristics such as plant height, above-ground biomass, and dry weight along with microscale compositional traits to deconvolute the carbon-partitioning pathways in this multipurpose crop. Multivariate analyses of traits resulted in the identification of numerous loci associated with several distinct carbon-partitioning traits, which putatively regulate sugar content, manganese homeostasis, and nitrate transportation. Using a multivariate adaptive shrinkage approach, we identified several loci associated with multiple traits suggesting that pleiotropic and/or interactive effects may positively influence multiple carbon-partitioning traits, or these overlaps may represent molecular switches mediating basal carbon allocating or partitioning networks. Conversely, we also identify a carbon tradeoff where reduced lignin content is associated with increased sugar content. The results presented here support previous studies demonstrating the convoluted nature of carbon partitioning in sorghum and emphasize the importance of taking a holistic approach to the study of carbon partitioning by utilizing multiscale phenotypes.

plant biology↗

Sorghum Association Panel Whole-Genome Sequencing Establishes Pivotal 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 with distinct histories of evolutionary divergence and local adaptation. 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 38X (25X-72X), enabling the development of a high-density genomic-marker set of 43,983,694 variants including SNPs (~ 38 million), indels (~ 5 million), and CNVs (170,000). We observe slightly more deletions among indels and a much higher prevalence of deletions among copy number variants compared to insertions. This new marker set enabled the identification of several putatively novel 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 been and continues to serve as a significant public resource for sorghum research and demonstrates the value of improving upon existing genomic resources. Author summary

plant biology↗

Variation in root exudate composition influences soil microbiome membership and function

Root exudation is one of the primary processes that mediate interactions between plant roots, microorganisms, and the soil matrix. Previous research has shown that plant root exudate profiles vary between species and genotypes which can likely support different microbial associations. Here, utilizing distinct sorghum genotypes as a model system, we characterized the chemical heterogeneity between root exudates and the effects of that variability on soil microbial membership and metabolisms. Distinct exudate chemical profiles were quantified and used to formulate synthetic root exudate treatments, a High Organic acid Treatment (HOT) and a High Sugar Treatment (HST). Root exudate treatments were added to laboratory soil reactors and 16S rRNA gene profiling illustrated distinct microbial membership in response to HST or HOT amendments. Alpha and beta diversity metrics were significantly different between treatments, (Shannons, p < 0.0001, mrpp = 0.01, respectively). Exometabolite production was highest in the HST, with increased production of key organic acids, non-proteinogenic amino acids, and three plant growth-promoting phytohormones (benzoic acid, salicylic acid, indole-3-acetic acid), suggesting plant-derived sugars fuel microbial carbon metabolism and contribute to phytohormone production. Linking the metabolic capacity of metagenome-assembled genomes in the HST to the exometabolite patterns, we identified potential plant growth-promoting microorganisms that could produce these phytohormones. Our findings emphasize the tractability of high-resolution multi-omics tools to investigate soil microbiomes, opening the possibility of manipulating native microbial communities to improve specific soil microbial functions and enhance crop production. ImportanceUnderstanding interactions between plant root exudates and the soil microbiome provides an avenue for a more comprehensive appreciation for how plant roots modulate their microbial counterparts to promote an environment favorable to plant fitness. Although these dynamics are appreciated as indispensable, mechanisms controlling specific rhizobiome membership and complexity are not fully understood. In this study, we investigate how variability in root exudation, modeled after differences observed between distinct sorghum genotypes, contributes to altered microbial membership and metabolisms. The results demonstrate how microbial diversity is influenced by root exudates of differing chemical composition and how changes in microbial membership correspond to modifications in carbon utilization and enhance production of plant-relevant metabolites. Our findings suggest carbon substrate preferences among bacteria in semi-arid climate soils and mechanisms for root exudate utilization. These findings provide new information on plant-soil environments useful for the development of efficient and precise microbiota management strategies in agricultural systems.

plant biology↗

Meta-Analysis Identifies Pleiotropic Loci Controlling Phenotypic Trade-offs in Sorghum

Community association populations are composed of phenotypically and genetically diverse accessions. Once these populations are genotyped, the resulting marker data can be reused by different groups investigating the genetic basis of different traits. Because the same genotypes are observed and scored for a wide range of traits in different environments, these populations represent a unique resource to investigate both pleiotropy and genotype by environment interactions. Here we assembled a set of 234 separate trait datasets for the Sorghum Association Panel, a group of 406 sorghum genotypes widely employed by the sorghum genetics community. Comparison of genome wide association studies conducted with two independently generated marker sets for this population demonstrate that existing genetic marker sets do not saturate the genome and likely capture only 35-43% of potentially detectable loci controlling variation for traits scored in this population. While limited evidence for pleiotropy was apparent in cross-GWAS comparisons, a multivariate adaptive shrinkage approach recovered both known pleiotropic effects of existing loci and new pleiotropic effects, particularly significant impacts of known dwarfing genes on root architecture. In addition, we identified new loci with pleiotropic effects consistent with known trade-offs in sorghum development. These results demonstrate the potential for mining existing trait datasets from widely used community association populations to enable new discoveries from existing trait datasets as new, denser genetic marker datasets are generated for existing community association populations.

plant biology↗

Multi-trait regressor stacking increased genomic prediction accuracy of sorghum grain composition

Cereal grains, primarily composed of starch, protein, and fat, are major source of staple for human and animal nutrition. Sorghum, a cereal crop, serves as a dietary staple for over half a billion people in the semi-arid tropics of Africa and South Asia. Genomic prediction has enabled plant breeders to estimate breeding values of unobserved genotypes and environments. Therefore, the use of genomic prediction will be extremely valuable for compositional traits for which phenotyping is labor-intensive and destructive for most accurate results. We studied the potential of Bayesian multi-output regressor stacking (BMORS) model in improving prediction performance over single trait single environment (STSE) models using a grain sorghum diversity panel (GSDP) and a biparental recombinant inbred lines (RILs) population. A total of five highly correlated grain composition traits: amylose, fat, gross energy, protein and starch, with genomic heritability ranging from 0.24 to 0.59 in the GSDP and 0.69 to 0.83 in the RILs were studied. Average prediction accuracies from the STSE model were within a range of 0.4 to 0.6 for all traits across both populations except amylose (0.25) in the GSDP. Prediction accuracy for BMORS increased by 41% and 32% on average over STSE in the GSDP and RILs, respectively. Predicting whole environments by training with remaining environments in BMORS yielded higher average prediction accuracy than from STSE model. Our results show regression stacking methods such as BMORS have potential to accurately predict unobserved individuals and environments, and implementation of such models can accelerate genetic gain.

genomics↗

Comparative Analysis of In Vitro Responses and Regeneration Between Diverse Bioenergy Sorghum Genotypes

Sorghum has been considered a recalcitrant plant in vitro, and suffers from a lack of regeneration protocols that function broadly and efficiently across a range of genotypes. This study was initiated to identify differential genotype-in vitro protocol responses across a range of bioenergy sorghum bioenergy parental lines, in order to characterize response profiles for use in future genetic studies. Seven bioenergy sorghum genotypes were compared, along with the common grain sorghum genotype Tx430, for their in vitro regeneration responses using two different in vitro protocols, LG and WU. All genotypes displayed some level of response during in vitro culture with both protocols. Distinct genotype-protocol responses were observed, with the WU protocol significantly better for plantlet regeneration. All bioenergy genotypes, with the exception of Chinese Amber, performed as well, if not better than Tx430, with Rio and PI329311 the top regenerating lines. Genotypes displayed protocol-dependent, differential phenolic exudation responses, as indicated by medium browning. During the callus induction phase, genotypes prone to medium browning exhibited a response on WU medium which was either equal or greater than on LG medium, with Pink Kafir and PI329311 the most prone to medium browning. Genotype- and protocol-dependent albino plantlet regeneration was also noted, with three of the bioenergy genotypes showing albino plantlet regeneration. Grassl, Rio and Pink Kafir were susceptible to albino plantlet regeneration, with the response strongly associated with the WU protocol. Pink Kafir displayed the highest albino formation, with close to 25% of regenerating explants forming albino plantlets.

plant biology↗