Salt stress, a major plant environmental stress, is a critical constraint for rice productivity. Dissecting the genetic loci controlling salt tolerance in rice for improving productivity, especially at the flowering stage, remains challenging. Here, we conducted a genome-wide association study (GWAS) of salt tolerance based on exome sequencing of the Thai rice accessions. Photosynthetic parameters and cell membrane stability under salt stress at the flowering stage; and yield-related traits of 104 Thai rice (Oryza sativa L.) accessions belonging to the indica subspecies were evaluated. The rice accessions were subjected to exome sequencing, resulting in 112,565 single nucleotide polymorphisms (SNPs) called with a minor allele frequency of at least 5%. LD decay analysis of the panel indicates that the average LD for SNPs at 20 kb distance from each other was 0.34 (r²), which decayed to its half value (~ 0.17) at around 80 kb. By GWAS performed using mixed linear model, two hundred loci containing 448 SNPs on exons were identified based on the salt susceptibility index of the net photosynthetic rate at day 6 after salt stress; and the number of panicles, filled grains and unfilled grains per plant. One hundred and forty six genes, which accounted for 73% of the identified loci, co-localized with the previously reported salt quantitative trait loci (QTLs). The top four regions that contained a high number of significant SNPs were found on chromosome 8, 12, 1 and 2. While many are novel, their annotation is consistent with potential involvement in plant salt tolerance and in related agronomic traits. These significant SNPs greatly help narrow down the region within these QTLs where the likely underlying candidate genes can be identified. Insight into the contribution of potential genes controlling salt tolerance from this GWAS provides further understanding of salt tolerance mechanisms of rice at the flowering stage, which can help improve yield productivity under salinity via gene cloning and genomic selection.

Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75–10.05, p = 5.41x10^-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.

Unfavourable environmental conditions, including soil salinity, lead to decreased rice (Oryza sativa L.) productivity, especially at the reproductive stage. In this study, we examined 30 rice varieties, which revealed significant differences in the photosynthetic performance responses under salt stress conditions during the reproductive stage, which ultimately affected yield components after recovery. In rice with a correlation between net photosynthetic rate (P_N) and intercellular CO₂ concentration (C_i) under salt stress, P_N was found to be negatively correlated with filled grain number after recovery. Applying stringent criteria, we identified 130,317 SNPs and 15,396 InDels between two “high-yield rice” varieties and two “low-yield rice” varieties with contrasting photosynthesis and grain yield characteristics. A total of 2089 genes containing high- and moderate-impact SNPs or InDels were evaluated by gene ontology (GO) enrichment analysis, resulting in over-represented terms in the apoptotic process and kinase activity. Among these genes, 262 were highly expressed in reproductive tissues, and most were annotated as receptor-like protein kinases. These findings highlight the importance of variations in signaling components in the genome and these loci can serve as potential genes in rice breeding to produce a variety with salt avoidance that leads to increased yield in saline soil.

Rice (Oryza sativa L.) is the main source of energy for humans and a staple food of high cultural significance for much of the world’s population. Rice with highly resistant starch (RS) is beneficial for health and can reduce the risk of disease, especially type II diabetes. The identification of loci affecting starch properties will facilitate breeding of high-quality and health-supportive rice. A genome-wide association study (GWAS) of 230 rice cultivars was used to identify candidate loci affecting starch properties. The apparent amylose content (AAC) among rice cultivars ranged from 7.04 to 33.06%, and the AAC was positively correlated with RS (R² = 0.94) and negatively correlated with rapidly available glucose (RAG) (R² = −0.73). Three loci responsible for starch properties were detected on chromosomes 1, 6, and 11. On chromosome 6, the most significant SNP corresponded to LOC_Os06g04200 which encodes granule-bound starch synthase I (GBSSI) or starch synthase. Two novel loci associated with starch traits were LOC_Os01g65810 and LOC_Os11g01580, which encode an unknown protein and a sodium/calcium exchanger, respectively. The markers associated with GBSSI and LOC_Os11g01580 were tested in two independent sets of rice populations to confirm their effect on starch properties. The identification of genes associated with starch traits will further the understanding of the molecular mechanisms affecting starch in rice and may be useful in the selection of rice varieties with improved starch.

Methods that collapse information across genetic markers when searching for association signals are gaining momentum in the literature. Although originally developed to achieve a better balance between retaining information and controlling degrees of freedom when performing multimarker association analysis, these methods have recently been proven to be a powerful tool for identifying rare variants that contribute to complex phenotypes. The information among markers can be collapsed at the genotype level, which focuses on the mean of genetic information, or the similarity level, which focuses on the variance of genetic information. The aim of this work is to understand the strengths and weaknesses of these two collapsing strategies. Our results show that neither collapsing strategy outperforms the other across all simulated scenarios. Two factors that dominate the performance of these strategies are the signal-to-noise ratio and the underlying genetic architecture of the causal variants. Genotype collapsing is more sensitive to the marker set being contaminated by noise loci than similarity collapsing. In addition, genotype collapsing performs best when the genetic architecture of the causal variants is not complex (e.g., causal loci with similar effects and similar frequencies). Similarity collapsing is more robust as the complexity of the genetic architecture increases and outperforms genotype collapsing when the genetic architecture of the marker set becomes more sophisticated (e.g., causal loci with various effect sizes or frequencies and potential non-linear or interactive effects). Because the underlying genetic architecture is not known a priori, we also considered a two-stage analysis that combines the two top-performing methods from different collapsing strategies. We find that it is reasonably robust across all simulated scenarios.

Genetic diversity is important for developing salt‐tolerant rice ( Oryza sativa L.) cultivars. Certain Thai rice accessions display salt tolerance at the adult or reproductive stage, but their response to salinity at the seedling stage is unknown. In this study, a total of 10 rice cultivars/line, including eight Thai cultivars and standard salt‐tolerant cultivar and susceptible line, were screened using a hydroponic system to identify salt‐tolerant genotypes at the seedling stage. Different morphophysiological indicators were used to classify tolerant and susceptible genotypes. Phylogenetic analyses were performed to determine the evolutionary relationships between the cultivars. Results showed that ‘Lai Mahk’, ‘Jao Khao’, ‘Luang Pratahn’, and ‘Ma Gawk’ exhibited salt stress tolerance comparable with the standard salt‐tolerance check ‘Pokkali’. Whole‐exome single‐nucleotide polymorphism (SNP)‐based phylogenetic analysis showed that the Thai rice cultivars were monophyletic and distantly related to Pokkali and IR29. Lai Mahk and Luang Pratahn were found closely related when using the whole‐exome SNPs for the analysis. This is also the case for the analysis of SNPs from 164 salt‐tolerance genes and transcription regulatory genes. The tolerant cultivars shared the same haplotype for 16 genes. Overall, the findings of this study identified four salt‐stress‐tolerant Thai rice cultivars, which could be used in rice breeding programs for salinity tolerance.