Genetic architecture of adult-plant resistance to stripe rust in bread wheat (Triticum aestivum L.) association panel

Stripe rust, caused by Puccinia striiformis f. sp. tritici, is a severe disease in wheat worldwide, including Ethiopia, causing up to 100% wheat yield loss in the worst season. The use of resistant cultivars is considered to be the most effective and durable management technique for controlling the disease. Therefore, the present study targeted the genetic architecture of adult plant resistance to yellow rust in 178 wheat association panels. The panel was phenotyped for yellow rust adult-plant resistance at three locations. Phonological, yield, yield-related, and agro-morphological traits were recorded. The association panel was fingerprinted using the genotyping-by-sequencing (GBS) platform, and a total of 6,788 polymorphic single nucleotide polymorphisms (SNPs) were used for genome-wide association analysis to identify effective yellow rust resistance genes. The marker-trait association analysis was conducted using the Genome Association and Prediction Integrated Tool (GAPIT). The broad-sense heritability for the considered traits ranged from 74.52% to 88.64%, implying the presence of promising yellow rust resistance alleles in the association panel that could be deployed to improve wheat resistance to the disease. The overall linkage disequilibrium (LD) declined within an average physical distance of 31.44 Mbp at r2 = 0.2. Marker-trait association (MTA) analysis identified 148 loci significantly (p = 0.001) associated with yellow rust adult-plant resistance. Most of the detected resistance quantitative trait loci (QTLs) were located on the same chromosomes as previously reported QTLs for yellow rust resistance and mapped on chromosomes 1A, 1B, 1D, 2A, 2B, 2D, 3A, 3B, 3D, 4A, 4B, 4D, 5A, 5B, 6A, 6B, 7A, and 7D. However, 12 of the discovered MTAs were not previously documented in the wheat literature, suggesting that they could represent novel loci for stripe rust resistance. Zooming into the QTL regions in IWGSC RefSeq Annotation v1 identified crucial disease resistance-associated genes that are key in plants' defense mechanisms against pathogen infections. The detected QTLs will be helpful for marker-assisted breeding of wheat to increase resistance to stripe rust. Generally, the present study identified putative QTLs for field resistance to yellow rust and some important agronomic traits. Most of the discovered QTLs have been reported previously, indicating the potential to improve wheat resistance to yellow rust by deploying the QTLs discovered by marker-assisted selection.

Genome-wide association studies of 27 accelerometry-derived physical activity measurements identified novel loci and genetic mechanisms

Physical inactivity (PA) is an important risk factor for a wide range of diseases. Previous genome-wide association studies (GWAS), based on self-reported data or a small number of phenotypes derived from accelerometry, have identified a limited number of genetic loci associated with habitual PA and provided evidence for involvement of central nervous system in mediating genetic effects. In this study, we derived 27 PA phenotypes from wrist accelerometry data obtained from 88,411 UK Biobank study participants. Single-variant association analysis based on mixed-effects models and transcriptome-wide association studies (TWAS) together identified 5 novel loci that were not detected by previous studies of PA, sleep duration and self-reported chronotype. For both novel and previously known loci, we discovered associations with novel phenotypes including active-to-sedentary transition probability, light-intensity PA, activity during different times of the day and proxy phenotypes to sleep and circadian patterns. Follow-up studies including TWAS, colocalization, tissue-specific heritability enrichment, gene-set enrichment and genetic correlation analyses indicated the role of the blood and immune system in modulating the genetic effects and a secondary role of the digestive and endocrine systems. Our findings provided important insights into the genetic architecture of PA and its underlying mechanisms.

Novel loci and potential mechanisms of major depressive disorder, bipolar disorder, and schizophrenia

Different psychiatric disorders share genetic relationships and pleiotropic loci to certain extent. We integrated and analyzed datasets related to major depressive disorder (MDD), bipolar disorder (BIP), and schizophrenia (SCZ) from the Psychiatric Genomics Consortium using multitrait analysis of genome-wide association analysis (MTAG). MTAG significantly increased the effective sample size from 99,773 to 119,754 for MDD, from 909,061 to 1,450,972 for BIP, and from 856,677 to 940,613 for SCZ. We discovered 7, 32, and 43 novel lead single nucleotide polymorphisms (SNPs) and 1, 6, and 3 novel causal SNPs for MDD, BIP, and SCZ, respectively, after fine-mapping. We identified rs8039305 in the FURIN gene as a novel pleiotropic locus across the three disorders. We performed marker analysis of genomic annotation (MAGMA) and Hi-C-coupled MAGMA (H-MAGMA) based gene-set analysis and identified 101 genes associated with the three disorders, which were enriched in the regulation of postsynaptic membranes, postsynaptic membrane dopaminergic synapses, and Notch signaling pathway. Next, we performed Mendelian randomization analysis using different tools and detected a causal effect of BIP on SCZ. Overall, we demonstrated the usage of combined genome-wide association studies summary statistics for exploring potential novel mechanisms of the three psychiatric disorders, providing an alternative approach to integrate publicly available summary data.