Genetic analysis of seed traits in Sorghum bicolor that affect the human gut microbiome

Biologically meaningful genome interpretation models to address data underdetermination for the leaf and seed ionome prediction in Arabidopsis thaliana

Genome interpretation (GI) encompasses the computational attempts to model the relationship between genotype and phenotype with the goal of understanding how the first leads to the second. While traditional approaches have focused on sub-problems such as predicting the effect of single nucleotide variants or finding genetic associations, recent advances in neural networks (NNs) have made it possible to develop end-to-end GI models that take genomic data as input and predict phenotypes as output. However, technical and modeling issues still need to be fixed for these models to be effective, including the widespread underdetermination of genomic datasets, making them unsuitable for training large, overfitting-prone, NNs. Here we propose novel GI models to address this issue, exploring the use of two types of transfer learning approaches and proposing a novel Biologically Meaningful Sparse NN layer specifically designed for end-to-end GI. Our models predict the leaf and seed ionome in A.thaliana, obtaining comparable results to our previous over-parameterized model while reducing the number of parameters by 8.8 folds. We also investigate how the effect of population stratification influences the evaluation of the performances, highlighting how it leads to (1) an instance of the Simpson's Paradox, and (2) model generalization limitations.

Increased Dietary Trp, Thr, and Met Supplementation Improves Performance, Health, and Protein Metabolism of Weaned Piglets under Mixed Management and Poor Housing Conditions

A sanitary challenge was carried out to induce suboptimal herd health while investigating the effect of amino acids supplementation on piglet responses. Weaned piglets of high sanitary status (6.33 ± 0.91 kg of BW) were distributed in a 2 × 2 factorial arrangement into two similar facilities with contrasting sanitary conditions and two different diets. Our results suggest that increased Trp, Thr, and Met dietary supplementation could support the immune systems of piglets under a sanitary challenge. In this manner, AA+ supplementation improved the performance and metabolism of piglets under mixed management and poor sanitary conditions. No major temporal microbiome changes were associated with differences in performance regardless of sanitary conditions or diets. Since piglets often become mixed in multiple-site production systems and facility hygiene is also often neglected, this study suggests that increased Trp, Thr, and Met (AA+) dietary supplementation could contribute to mitigating the side effects of these harmful risk factors in modern pig farms.

A dual-functional single-atom Fe nanozyme-based sensitive colorimetric sensor for tannins quantification in brandy

Traditional methods of tannins detection suffer from complex pretreatment, long detection time, and limited sensitivity. Modern techniques like liquid chromatography require expertise, involve tedious result processing, and lack effective data visualization. Therefore, there is a need for an alternative detection method that simplifies pretreatment and detection steps, reduces analysis time, and provides visualized results. In this study, a novel colorimetric sensor based on single-atom Fe nanozyme (Fe@CN-20) was developed for tannins detection. Fe@CN-20 exhibited laccase-like and oxidase-like activities, enabling simultaneous oxidation of tannins and a substrate called TMB. Tannins competed with TMB, allowing quantification of tannins content. The Fe@CN-20/TMB system provided a detection range of 5-100 mg/L tannic acid, with a detection limit of 0.13 mg/L (S/N = 3). Analysis time was approximately 30 min. The platform successfully quantified tannins in brandy, showing less than 5% deviation compared to the standard method. The sensor was simple, sensitive, rapid, and provided strong visualization.

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 cuticular waxes influence host plant selection by aphids

Quantification of cuticular waxes coupled with insect bioassays and feeding behavior analysis demonstrate that long-chain C₃₂ fatty alcohol impacts host plant selection by aphids. Cuticular waxes constitute the first point of contact between plants and their environment, and it also protect plants from external stresses. However, the role of waxes in Sorghum bicolor (sorghum) against sugarcane aphid (Melanaphis sacchari), a relatively new and devastating pest of sorghum in the U.S., is not fully understood. In this study, we monitored sugarcane aphid behavior on two genotypes of young sorghum plants with different wax chemistry: a wild-type plant (bloom) with lower C₃₂ alcohol cuticular wax, and a mutant plant (bloomless) with 1.6 times the amount of wax compared to wild-type plants. No-choice aphid bioassays revealed that sugarcane aphid reproduction did not vary between wild-type and the bloomless plants. Electrical Penetration Graph (EPG) monitoring indicated that the sugarcane aphids spent comparable amount of time feeding from the sieve elements of the wild-type and bloomless plants. However, aphids spent more time feeding on the xylem sap of the bloomless plants compared to the wild-type plants. Furthermore, aphid choice assays revealed that the sugarcane aphids preferred to settle on bloomless compared to wild-type plants. Overall, our results suggest that cuticular waxes on young sorghum leaves play a critical role in influencing host plant selection by sugarcane aphids.