Biology subjects

Mason, E.

Publications and source records attributed to Mason, E..

7 recordsLinked to original sources

bioRxiv2023

HaploCatcher: An R Package for Prediction of Haplotypes

Wheat (Triticum aestivum L.) is crucial to global food security, but is often threatened by diseases, pests, and environmental stresses. Wheat stem sawfly (Cephus cinctus Norton) poeses a major threat to food security in the United States, and solid-stem varieties, which carry the stem-solidness locus (Sst1), are the main source of genetic resistance against sawfly. Marker-assisted selection uses molecular markers to identify lines possessing beneficial haplotypes, like that of the Sst1 locus. In this study, an R package titled "HaploCatcher" was developed to predict specific haplotypes of interest in genome-wide genotyped lines. A training population of 1,056 lines genotyped for the Sst1 locus, known to confer stem solidness, and genome-wide markers was curated to make predictions of the Sst1 haplotypes for 292 lines from the Colorado State University wheat breeding program. Predicted Sst1 haplotypes were compared to marker derived haplotypes. Our results indicated that the training set was substantially predictive, with kappa scores of 0.83 for k-nearest neighbors and 0.88 for random forest models. Forward validation on newly developed breeding lines demonstrated that a random forest model, trained on the total available training data, had comparable accuracy between forward and cross-validation. Estimated group means of lines classified by haplotypes from PCR-derived markers and predictive modeling did not significantly differ. The HaploCatcher package is freely available and may be utilized by breeding programs, using their own training populations, to predict haplotypes for whole genome sequenced early generation material. CORE IDEASO_LIIdentification, introgression, and frequency increase of large effect loci are important for cultivar development. C_LIO_LIThe Sst1 locus has a significant effect on cutting score in fields exposed to sawfly infestation. C_LIO_LIHistorical genetic information can be utilized to predict haplotypes for lines which have genome-wide genetic data. C_LIO_LIAn R package, HaploCatcher, has been developed to facilitate this analysis in other programs. C_LI

plant biology↗

bioRxiv2023

Phenomic vs Genomic Prediction - A Comparison of Prediction Accuracies for Grain Yield in Hard Winter Wheat Lines

Common bread wheat (Triticum aestivum L.) is a key component of global diets, but the genetic improvement of wheat is not keeping pace with the growing demands of the worlds population. To increase efficiency and reduce costs, breeding programs are rapidly adopting the use of unoccupied aerial vehicles (UAVs) to conduct high-throughput spectral analyses. This study examined the effectiveness of multispectral indices in predicting grain yield compared to genomic prediction. Multispectral data were collected on advanced generation yield nursery trials during the 2019-2021 growing seasons in the Colorado State University Wheat Breeding Program. Genome-wide genotyping was performed on these advanced generations and all plots were harvested to measure grain yield. Two methods were used to predict grain yield: genomic estimated breeding values (GEBVs) generated by a genomic best linear unbiased prediction (gBLUP) model and phenomic phenotypic estimates (PPEs) using only spectral indices via multiple linear regression (MLR), k-nearest neighbors (KNN), and random forest (RF) models. In cross-validation, PPEs produced by MLR, KNN, and RF models had higher prediction accuracy ([r]: 0.41 [≤][r] [≤] 0.48) than GEBVs produced by gBLUP ([r] = 0.35). In leave-one-year-out forward validation using only multispectral data for 2020 and 2021, PPEs from MLR and KNN models had higher prediction accuracy of grain yield than GEBVs of those same lines. These findings suggest that a limited number of spectra may produce PPEs that are more accurate than or equivalently accurate as GEBVs derived from gBLUP, and this method should be evaluated in earlier development material where sequencing is not feasible.

plant biology↗

bioRxiv2023

Multi-target genome editing reduces polyphenol oxidase activity in wheat (Triticum aestivum L.) grains

Polyphenol oxidases (PPO) are dual activity metalloenzymes that catalyse the production of quinones. In plants, PPO activity may contribute to biotic stress resistance and secondary metabolism but is undesirable for food producers because it causes the discolouration and changes in flavour profiles of products during post-harvest processing. In wheat (Triticum aestivum L.), PPO released from the aleurone layer of the grain during milling results in the discolouration of flour, dough, and end-use products, reducing their value. Loss-of-function mutations in the PPO1 and PPO2 paralogous genes on homoeologous group 2 chromosomes confer reduced PPO activity in the wheat grain but limited natural variation and small intergenic distances between these genes complicates the selection of extremely low-PPO wheat varieties by recombination. In the current study, a CRISPR/Cas9 construct with one single guide RNA (sgRNA) targeting a conserved copper binding domain was used to edit all seven PPO1 and PPO2 genes in the spring wheat cultivar Fielder. Five of the seven edited T1 lines exhibited significant reductions in PPO activity, and T2 lines had PPO activity up to 86.7% lower than wild-type controls. In the elite winter wheat cultivars Guardian and Steamboat, which have five PPO1 and PPO2 genes, PPO activity was reduced by >90% in both T1 and T2 lines. This study demonstrates that multi-target editing at late stages of variety development could complement selection for beneficial alleles in crop breeding programmes by inducing novel variation in loci inaccessible to recombination.

plant biology↗

bioRxiv2023

UTILIZATION OF A PUBLICLY AVAILABLE DIVERSITY PANEL IN GENOMIC PREDICTION OF FUSARIUM HEAD BLIGHT RESISTANCE TRAITS IN WHEAT

Fusarium head blight (FHB) is an economically and environmentally concerning disease of wheat (Triticum aestivum L). A two-pronged approach of marker assisted selection (MAS) coupled with genomic selection (GS) has been suggested when breeding for FHB resistance. An historical dataset comprised of entries in the Southern Uniform Winter Wheat Scab Nursery (SUWWSN) from 2011-2021 was partitioned and used in genomic prediction. Two traits were curated from 2011-2021 in the SUWWSN: percent Fusarium damaged kernels (FDK) and Deoxynivalenol (DON) content. Heritability was estimated for each trait-by-environment combination. A consistent set of check lines was drawn from each year in the SUWWSN, and K-means clustering was performed across environments to assign environments into clusters. Two clusters were identified for FDK and three for DON. Cross-validation on SUWWSN data from 2011-2019 indicated no outperforming training population in comparison to the combined dataset. Forward validation for FDK on the SUWWSN 2020 and 2021 data indicated a predictive accuracy r {approx} 0.58 and r {approx} 0.53, respectively. Forward validation for DON indicated a predictive accuracy of r {approx} 0.57 and r {approx} 0.45, respectively. Forward validation using environments in cluster one for FDK indicated a predictive accuracy of r {approx} 0.65 and r {approx} 0.60, respectively. Forward validation using environments in cluster one for DON indicated a predictive accuracy of r {approx} 0.67 and r {approx} 0.60, respectively. These results indicated that selecting environments based on check performance may produce higher forward prediction accuracies. This work may be used as a model to create a public resource for genomic prediction of FHB resistance traits across public wheat breeding programs. CORE IDEASO_LIThe data from the Southern Uniform Winter Wheat Nursery may be used for genomic prediction. C_LIO_LICreating training populations based on like-check performance improves forward genomic predictive accuracies. C_LIO_LIFiltering out locations with low genomic, per-plot, narrow-sense heritability may improve predictive accuracies. C_LI

plant biology↗

bioRxiv2021

INDUCED MUTATIONS IN TaASN-A2 REDUCE FREE ASPARAGINE CONCENTRATION IN THE WHEAT GRAIN

Acrylamide is a neurotoxin and probable carcinogen formed as a processing contaminant during baking and production of different foodstuffs, including bread products. The amino acid asparagine is the limiting substrate in the Maillard reaction that produces acrylamide, so developing wheat varieties with low free asparagine concentrations in the grain is a promising approach to reduce dietary acrylamide exposure. A candidate gene approach was used to identify chemically-induced genetic variation in ASPARAGINE SYNTHETASE 2 (ASN2) genes that exhibit a grain-specific expression profile. In field trials, durum and common wheat lines carrying asn-a2 null alleles exhibited reductions in free asparagine concentration in their grains of between 9 and 34% compared to wild-type sister lines. These plants showed no significant differences in spikelet number, grain size and weight, germination or baking quality traits. These non-transgenic variants can be deployed without restriction in elite wheat germplasm to reduce acrylamide-forming potential with no negative impacts on quality or agronomic performance. Core ideasO_LIThree wheat ASPARAGINE SYNTHETASE 2 knockout alleles were characterized in field experiments. C_LIO_LIMutant alleles conferred significant reductions in grain free asparagine concentration. C_LIO_LIThe alleles did not affect quality or agronomic traits. C_LIO_LIThese non-transgenic alleles can be deployed without restriction in wheat breeding programs. C_LI

genetics↗

bioRxiv2021

Development of the Wheat Practical Haplotype Graph Database as a Resource for Genotyping Data Storage and Genotype Imputation

To improve the efficiency of high-density genotype data storage and imputation in bread wheat (Triticum aestivum L.), we applied the Practical Haplotype Graph (PHG) tool. The wheat PHG database was built using whole-exome capture sequencing data from a diverse set of 65 wheat accessions. Population haplotypes were inferred for the reference genome intervals defined by the boundaries of the high-quality gene models. Missing genotypes in the inference panels, composed of wheat cultivars or recombinant inbred lines genotyped by exome capture, genotyping-by-sequencing (GBS), or whole-genome skim-seq sequencing approaches, were imputed using the wheat PHG database. Though imputation accuracy varied depending on the method of sequencing and coverage depth, we found 93% imputation accuracy with 0.01x sequence coverage, which was only slightly lower than the accuracy obtained using the 0.5x sequence coverage (96.9%). Compared to Beagle, on average, PHG imputation was ~4% (p-value = 0.00027) more accurate, and showed 27% higher accuracy at imputing a rare haplotype introgressed from a wild relative into wheat. The reduced accuracy of imputation with GBS data (90.4%) is likely associated with the small overlap between GBS markers and the exome capture dataset, which was used for constructing PHG. The highest imputation accuracy was obtained with exome capture for the wheat D genome, which also showed the highest levels of linkage disequlibrium and proportion of identity-by-descent regions among accessions in our reference panel. We demonstrate that genetic mapping based on genotypes imputed using PHG identifies SNPs with a broader range of effect sizes that together explain a higher proportion of genetic variance for heading date and meiotic crossover rate compared to previous studies.

genomics↗

bioRxiv2018

Dynamic interplay of innate and adaptive immunity during sterile retinal inflammation: Insights from the transcriptome

The pathogenesis of many retinal degenerations, such as age-related macular degeneration (AMD), is punctuated by an ill-defined network of sterile inflammatory responses. The delineation of innate and adaptive immune milieu amongst the broad leukocyte infiltrate, and the gene networks which construct these responses, are poorly described in the eye. Using photo-oxidative damage in a rodent model of subretinal inflammation, we employed a novel RNA-sequencing framework to map the global gene network signature of retinal leukocytes. This revealed a previously uncharted interplay of adaptive immunity during subretinal inflammation, including prolonged enrichment of myeloid and lymphocyte migration, antigen presentation, and the alternative arm of the complement cascade involving Factor B. We demonstrate Factor B-deficient mice are protected against macrophage infiltration and subretinal inflammation. Suppressing the drivers of retinal leukocyte proliferation, or their capacity to elicit complement responses, may help preserve retinal structure and function during sterile inflammation in diseases such as AMD.

neuroscience↗