Browsing by Author "Mason, Esten, committee member"

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Open Access
An NLR gene likely underlying RMES1 provides global sorghum resistance bolstered by RMES2
(Colorado State University. Libraries, 2023) VanGessel, Carl, author; Morris, Geoffrey, advisor; Nalam, Vamsi, committee member; Roberts, Robyn, committee member; Mason, Esten, committee member
Breeding for aphid host plant resistance in sorghum has been an area of interest since the emergence of Melanaphis sorghi in North America a decade ago. In order to develop durable sorghum aphid resistance, breeders must be equipped with tools (trait package) and knowledge (molecular mechanisms) of host plant resistance. In this dissertation, I characterize the current state of sorghum aphid breeding and propose a genotype to phenotype map for the major source of global resistance, Resistance to Melanaphis sorghi 1. Relying on near-isogenic lines, I demonstrate that RMES1 is applying selection pressure to sorghum aphid through reduction in fecundity that discriminates among aphid species. In global sorghum lines, RMES1 is rare whereas a second resistance source, RMES2, is common and present in historic breeding germplasm. I mapped RMES2 in Haitian breeding populations where it contributes fitness increases while lacking antagonistic pleiotropy and is selected for alongside RMES1. These results suggest breeding programs may unknowingly be deploying both sources of resistance which in combination are reducing the likelihood of M. sorghi biotype shifts to overcome RMES1. As aphid resistance may rely on phytochemical and/or induction with extended phenotypes regarding aphid populations, I used pan-genomic, transcriptomic, and metabolomic resources to describe the molecular mechanism of RMES1. Structural variation at the Chr06 locus underlies presence/absence variation of several nucleotide-binding leucine-rich repeat receptor (NLR) genes. Two of these candidate genes, SbPI276837.06G016400 and SbPI276837.06G016600, are representatives of two orthologous NLR groups which have genomic and transcriptomic evidence of underlying RMES1 resistance. The PAL branch of the salicylic acid pathway is the primary phytohormone pathway responsible for RMES1-induced resistance. Finally, metabolome reorganization mirroring transcriptome changes suggest RMES1 is inducing multiple downstream mechanisms responsible for reducing aphid fecundity. While the causal gene underlying RMES1 remains to be cloned and the eliciting aphid factor is unknown, this research suggests that gene-for-gene dynamics could lead to resistance-breaking biotype shifts and combining RMES1 with additional resistance genes e.g. RMES2, will help achieve durability.
Open Access
Developing a strategy for identifying genetically important animals
(Colorado State University. Libraries, 2023) Wilson, Carrie S., author; Speidel, Scott, advisor; Enns, R. Mark, advisor; Lewis, Ronald, committee member; Mason, Esten, committee member
Livestock researchers often need to sample animals within a breed to serve as a representative sample of the breed. Identifying the most relevant animals to include in research for genotyping, building a reference population, or inclusion in a gene bank is a complex issue. A suboptimal sampling strategy can lead to biased results, the need for additional sampling, and can be costly. When using public funds (e.g., federal grant or federal appropriations) or member fees (e.g., breed association funds), we have a responsibility to efficiently spend these investments in a wise manner, optimizing which animals are sampled before the research, genotyping, or gene banking begins. The first objective was to develop a sampling strategy to maximize the genetic diversity captured for the sampled animals. Simulated data is ideal for this type of study as there is no limitation to the testing parameters. The primary benefit of simulation with this research was the opportunity to have known genotypes for every animal in the population. Since genotypes will almost never be available for the entire population in the real world, and identifying animals to genotype may in fact be the purpose of the sampling, pedigree-based sampling methods were chosen. Sampling methods tested included optimal contribution selection (OCS) and the genetic conservation index (GCI). The OCS selects parents based on constraining their co-ancestry rather than minimizing inbreeding. GCI seeks to maximize the number of founders in an animal's pedigree. The sampling strategy developed in Objective 1 was used to identify a subset of 100, 50, and 25 animals from each breed and the genetic diversity captured by each sampling method was assessed using both quantitative and molecular methods. AlphaSimR was used to simulate the population for sampling. After an initial randomly mating founder population was developed, an additional 15 years of selection for phenotypic weaning weight was simulated and resulted in a fully genotyped population with 13,662 animals per year. The simulation was designed to represent a sheep population. After the sampling strategies were applied to the simulated population, they were next applied to Suffolk sheep and Simmental beef populations for further assessment of their ability to capture genetic diversity. To assess population structure based on molecular data, the Suffolk and Simmental populations were limited to genotyped animals and their ancestors. The simulated population represented a large purebred population (n=204,930) with a moderate number of markers (n=53,901). The Suffolk population represented a small population (n=1,565) with many markers (n=606,006). Lastly, the Simmental population represented a large, admixed population (n=54,790) with a moderate number of markers (n=29,449). For the second objective, the population structure of the full populations, comprised of genotyped animals, was assessed, and compared to the population structure of the animals from each sampling strategy. Each sampling strategy selected 100, 50, and 25 animals. The measure of success of capturing the genetic diversity of the population was a molecular-based measure defined by capturing the available alleles in the population. Other population structure measures included a comparison of a phenotypic trait, breeding values, inbreeding levels, heterozygosity, minor allele frequency (MAF) category classification, runs of homozygosity (ROH), Ne, and model-based population structure to visualize subpopulations. While both sampling strategies were effective at capturing the available alleles in the population, OCS was more successful than GCI when comparing the same sample size. Success of capturing alleles decreased as sample size decreased from 100 to 50 to 25. Overall, OCS with a sample of 100 animals (OCS 100) was the most successful at capturing the available alleles in the population, capturing 96.5, 99.3, and 99.9 percent of the alleles for the simulated, Suffolk, and Simmental populations, respectively. For a sampling strategy to be useful, it needs to be effective across a variety of species and breeds with a variety of breed histories and population sizes. The third objective was to compare the three populations evaluated in this research and compare the effectiveness of the sampling strategies across these populations. Population structure was compared for the three populations. Then, the effectiveness of OCS 100 was compared. The three populations differed in population size and the amount of admixture present. The simulated population was characterized by a large number of low frequency alleles (n=5,339) that proved difficult to capture. The Suffolk population was small and consisted of 14 distinct subpopulations. The Simmental population had high levels of heterozygosity and less distinct subpopulation structure. Despite disparate populations, OCS 100 was the most robust across the three populations, consistently capturing the highest percentage of available alleles compared to the other sampling strategies. In summary, OCS 100 was the most effective sampling strategy across three different populations. A low-cost pedigree-based sampling strategy can be used to capture the genetic diversity in a population. Researchers will need to weigh the risk of a greater loss of alleles when selecting a smaller population size. Risk could be further reduced by increasing the selected population size. Knowledge of the prevalence of low frequency alleles in the population and the value of capturing them should be considered.
Open Access
Development of molecular breeding resources for increased pro-vitamin A carotenoids in sorghum grain
(Colorado State University. Libraries, 2022) Cruet-Burgos, Clara María, author; Rhodes, Davina, advisor; Mason, Esten, committee member; Prenni, Jessica, committee member; Pressoir, Gael, committee member
Vitamin A deficiency (VAD) affects millions of people in countries in Africa and South-East Asia, contributing to decreased immune response and increased morbidity and mortality from common infections. Sorghum [Sorghum bicolor L. (Moench)] is a staple cereal crop in these regions, thus, sorghum carotenoid biofortification is a potential method to improve the vitamin A status of these communities. The overall aim of this research was to determine the feasibility of biofortification breeding for sorghum grain carotenoids, and to develop genomic tools to assist in molecular breeding. Global sorghum germplasm collections were evaluated for pro-vitamin A carotenoids, and concentrations were found to be below target values. Due to the low number of accessions with above average pro-vitamin A content, the genetic diversity of the high carotenoid lines in the global germplasm was assessed. High carotenoid accessions were found to be highly related, hence, to increase genetic diversity for breeding, a genomic prediction model was used to identify additional germplasm with potentially high concentrations of pro-vitamin A carotenoids. Through a genome-wide association study, it was confirmed that carotenoid variation in sorghum grain is oligogenic, but there was also evidence of a polygenic component. Therefore both marker-assisted selection (MAS) and genomic selection (GS) may be effective in accelerating breeding efforts. KASP markers in linkage with genomic regions associated with carotenoid concentrations were developed and validated in six F2:3 populations. Two markers in the intronic region of the carotenoid pathway β-OH gene were identified as good candidates to use for MAS due to their predictive ability. A marker inside the coding sequence of the carotenoid pathway ZEP gene was also identified as a good marker for MAS. An RNA-seq experiment identified additional genes in the MEP, carotenoid biosynthesis and carotenoid degradation pathways that could be used for MAS. The results of these studies provide a foundation for vitamin A biofortification through genomics-assisted breeding.
Open Access
Phenotyping tools and genetic knowledge to facilitate breeding of dhurrin content and cyanogenic potential in sorghum
(Colorado State University. Libraries, 2023) Johnson, Kristen, author; Morris, Geoffrey, advisor; Mason, Esten, committee member; Prenni, Jessica, committee member
Cyanogenic glucosides are important secondary compounds found in plants serving roles such as plant defense, pollinator attraction, nitrogen (N) sources, and drought tolerance. Sorghum (S. bicolor [L.] Moench), an important grain crop predominantly grown in drought-prone environments, contains a cyanogenic glucoside known as dhurrin where it functions as a source of hydrogen cyanide (HCN) after the leaf tissue is disrupted. Dhurrin has been hypothesized to serve as an osmoprotectant, N turnover source, and sorghum aphid resistance mechanism. In addition, dhurrin concentrations can vary due to growth stage, environment, and genotype, and this variability can cause limitations for effective dhurrin phenotyping. To facilitate the breeding of dhurrin and HCNp, we developed a semi-quantitative phenotyping method to detect HCNp and investigated the genetics of dhurrin and HCN variation in global sorghum germplasm. In the first study, we developed a simple, semi-quantitative, high-throughput phenotyping method to detect HCNp in sorghum leaf tissue. Biochemical methods have been used to determine dhurrin content quantitatively, however these methods are laborious and costly. As a result, we developed a semi-quantitative phenotypic assay using commercial test strip paper to measure HCNp utilizing a F13 Stg Recombinant Inbred Line (RIL) population with previously reported dhurrin concentrations. We found that later sampling time improved the detection of HCNp variation with broad-sense heritability (H2) values highest at flowering. In addition, we found that other covariates such as leaf number may play a role in effective phenotyping. Altogether this assay can be used to screen a sorghum breeding population in both a greenhouse and field setting for smallholder breeding programs looking to advance their breeding generations more efficiently. In the second study we sought to understand the genetics underlying HCN and dhurrin variability, as well as investigate the relationship between drought and dhurrin using diverse sorghum landraces. We found no direct correlation between dhurrin and drought, but the slight positive correlation could suggest other environmental factors, such as pest pressures, are driving HCN and dhurrin variation. To further understand the biological relationship between dhurrin and HCN, we conducted a genome-wide association study (GWAS) for HCNp and dhurrin. We identified several significant associations between HCNp and known dhurrin biosynthetic and catabolic genetic markers, but major biosynthesis loci were not all significantly associated with HCNp. In addition, we performed a GWAS on dhurrin and found peaks associated with the dhurrin biosynthetic gene cluster, as well as other unknown loci that could contribute to dhurrin variation. This suggests that genetic variation for genes in the dhurrin biosynthesis, catabolism, and recycling pathway contributes to HCNp variability, and they are not direct proxies for each other. As a result, breeders should de-couple phenotyping methods for dhurrin and HCNp depending on the trait of interest.