Quantitative Trait Loci Research Articles

Integrative pan-cancer analysis reveals a common architecture of dysregulated transcriptional networks characterized by loss of enhancer methylation

Aberrant DNA methylation contributes to gene expression deregulation in cancer. However, these alterations’ precise regulatory role and clinical implications are still not fully understood. In this study, we performed expression-methylation Quantitative Trait Loci (emQTL) analysis to identify deregulated cancer-driving transcriptional networks linked to CpG demethylation pan-cancer. By analyzing 33 cancer types from The Cancer Genome Atlas, we identified and confirmed significant correlations between CpG methylation and gene expression (emQTL) in cis and trans, both across and within cancer types. Bipartite network analysis of the emQTL revealed groups of CpGs and genes related to important biological processes involved in carcinogenesis including proliferation, metabolism and hormone-signaling. These bipartite communities were characterized by loss of enhancer methylation in specific transcription factor binding regions (TFBRs) and the CpGs were topologically linked to upregulated genes through chromatin loops. Penalized Cox regression analysis showed a significant prognostic impact of the pan-cancer emQTL in many cancer types. Taken together, our integrative pan-cancer analysis reveals a common architecture where hallmark cancer-driving functions are affected by the loss of enhancer methylation and may be epigenetically regulated.

Disruption of the OsWRKY71 transcription factor gene results in early rice seed germination under normal and cold stress conditions

Abstract Background Early seed germination in crops can confer a competitive advantage against weeds and reduce the time to maturation and harvest. WRKY transcription factors regulate many aspects of plant development including seed dormancy and germination. Both positive and negative regulators of seed germination have been reported in many plants such as rice and Arabidopsis. Using a transient expression system, we previously demonstrated that OsWRKY71 is a negative regulator of gibberellin (GA) signaling in aleurone cells and likely forms a “repressosome” complex with other transcriptional repressors. Hence, it has the potential to impact seed germination properties. Results In this study, we demonstrate that OsWRKY71, a Group IIa WRKY gene, appeared at the same time as seed-bearing plants. Rice mutants lacking OsWRKY71 have seeds and embryos that germinate earlier than wildtype controls. In oswrky71 aleurone layers, α-amylase activity was hypersensitive to stimulation by GA3 and hyposensitive to inhibition by abscisic acid (ABA). Early germination in oswrky71 intact seeds was also hyposensitive to ABA. Transcriptomic profiling during embryo germination and early post-germination growth demonstrates that OsWRKY71 influences the expression of 9–17% of genes in dry and imbibing embryos. Compared to wildtype embryos, the mutant transcriptomes have large temporal shifts at 4, 8 and 12 h after imbibition (HAI). Importantly, many genes involved in the ABA-dependent inhibition of seed germination were downregulated in oswrky71-1. This mutant also displayed altered expression of multiple ABA receptors (OsPYLs/RCARs) that control ABA signaling and the VP1-SDR4-DOG1L branch of ABA signaling that promotes seed dormancy. Association studies reveal an OsWRKY71-containing quantitative trait locus involved in low-temperature seed germinability, qLTG-2. Indeed, oswrky71 seeds germinated early at 15 °C. Conclusions Rice Group-IIa WRKY transcription factor OsWRKY71 is a master regulator of germination that influences the expression of 9–17% of genes in dry and imbibing embryos. It is also most likely the primary candidate of low-temperature seed germinability QTL, qLTG-2. We propose that knockouts of OsWRKY71 can generate rice varieties with improved germination properties under normal or low-temperature conditions.

Causal association of obesity-related anthropometric traits with myopia and the mediating role of educational attainment: a Mendelian randomization study

AIM: To study the causal relationship between obesity-related anthropometric traits and myopia and the mediating role of educational attainment (EA). METHODS: Univariable Mendelian randomization (UVMR) was performed to evaluate the causal association between body mass index (BMI), height, waist-hip ratio (WHR, adjusted for BMI), and mean spherical equivalent (MSE). BMI was divided into fat and fat-free mass and included in multivariable Mendelian randomization (MVMR) to explore the roles of different BMI components in the causal relationship between BMI and MSE. A mediation analysis based on two-step Mendelian randomization (MR) was carried out. Specifically, UVMR was conducted to estimate the causal effect of BMI on EA. The direct effect of EA on MSE was estimated from MVMR. The mediation effect of EA in the BMI-EA-MSE model was calculated by the product of coefficients method. Expression quantitative trait loci (eQTL)-MR, reverse MR, and Linkage Disequilibrium Score Regression (LDSC) were performed to assess the robustness. RESULTS: Genetically predicted higher BMI had a positive total effect on MSE (βIVW=0.26 D, 95%CI=0.14 to 0.37 D, P<0.001), whereas there was no significant association between height, WHR, and MSE. Fat mass was found to play a significant role in the effect of body mass on MSE (βIVW=0.50 D, 95%CI=0.21 to 0.78 D, P=0.001), but there was no significant association between fat-free mass and MSE. The causal effect of BMI on EA was -0.14 (95%CI=-0.16 to -0.11, P<0.001), and the direct effect of EA on MSE was -0.63 D (95%CI=-0.81 to -0.44 D, P<0.001). The mediating effect of EA in the BMI-EA-MSE model was 0.09 D (95%CI=0.06 to 0.12 D), with a mediation proportion of 33% (95%CI=22.1% to 44.6%). No reverse causal associations were detected except for BMI on EA. The results of eQTL-MR and LDSC were consistent with each MR analysis. CONCLUSION: Genetically predicted higher BMI decreases the degree of myopia with a 33% mediation proportion by EA, and fat mass provides a dominant protective role in body mass-myopia. As a supplement to previous observational studies, it provides strong evidence for the relationship between anthropometric traits and refractive errors and offers a theoretical basis for future measures to prevent and control myopia.

Cadmium (Cd) Tolerance and Phytoremediation Potential in Fiber Crops: Research Updates and Future Breeding Efforts

Heavy metal pollution is one of the most devastating abiotic factors, significantly damaging crops and human health. One of the serious problems it causes is a rise in cadmium (Cd) toxicity. Cd is a highly toxic metal with a negative biological role, and it enters plants via the soil–plant system. Cd stress induces a series of disorders in plants’ morphological, physiological, and biochemical processes and initiates the inhibition of seed germination, ultimately resulting in reduced growth. Fiber crops such as kenaf, jute, hemp, cotton, and flax have high industrial importance and often face the issue of Cd toxicity. Various techniques have been introduced to counter the rising threats of Cd toxicity, including reducing Cd content in the soil, mitigating the effects of Cd stress, and genetic improvements in plant tolerance against this stress. For decades, plant breeders have been trying to develop Cd-tolerant fiber crops through the identification and transformation of novel genes. Still, the complex mechanism of Cd tolerance has hindered the progress of genetic breeding. These crops are ideal candidates for the phytoremediation of heavy metals in contaminated soils. Hence, increased Cd uptake, accumulation, and translocation in below-ground parts (roots) and above-ground parts (shoots, leaves, and stems) can help clean agricultural lands for safe use for food crops. Earlier studies indicated that reducing Cd uptake, detoxification, reducing the effects of Cd stress, and developing plant tolerance to these stresses through the identification of novel genes are fruitful approaches. This review aims to highlight the role of some conventional and molecular techniques in reducing the threats of Cd stress in some key fiber crops. Molecular techniques mainly involve QTL mapping and GWAS. However, more focus has been given to the use of transcriptome and TFs analysis to explore the potential genomic regions involved in Cd tolerance in these crops. This review will serve as a source of valuable genetic information on key fiber crops, allowing for further in-depth analyses of Cd tolerance to identify the critical genes for molecular breeding, like genetic engineering and CRISPR/Cas9.

Identification of Genetic Loci Associated with Bolting Time in Radish (Raphanus sativus L.) by QTL Mapping and GWAS

Bolting time is a critical trait that affects crop yield, adaptability, and overall productivity, making its regulation vital for agricultural success. In this study, we explored the genetic mechanisms controlling flowering time in radish (Raphanus sativus) via a combination of quantitative trait locus (QTL) analysis and genome-wide association study (GWAS). By developing an F2 population from a cross between the relatively late-bolting variety ‘L432’ and the early-bolting variety ‘L285’, we identified 12 QTLs associated with bolting time. Furthermore, a GWAS performed on 60 East Asian radish accessions revealed 14 candidate genes potentially involved in flowering and bolting regulation. FLOWERING LOCUS C (FLC2) was the major candidate gene explaining the early and late bolting types. One locus was commonly detected from QTL and GWAS on chromosome 4, where CONSTANS-like (COL4) is located. To validate these findings, SNP markers were designed and applied to F2 populations, revealing a correlation between marker presence and bolting phenotypes. These results offer valuable insights into the molecular control of bolting time in radish and identify candidate genes for use in marker-assisted breeding. These findings could enhance breeding efforts for optimizing bolting time in various radish markets.

The role of the rhizobiome recruited by root exudates in plant disease resistance: current status and future directions.

Root exudates serve as a bridge connecting plant roots and rhizosphere microbes, playing a key role in influencing the assembly and function of the rhizobiome. Recent studies have fully elucidated the role of root exudates in recruiting rhizosphere microbes to enhance plant performance, particularly in terms of plant resistance to soil-borne pathogens; however, it should be noted that the composition and amount of root exudates are primarily quantitative traits regulated by a large number of genes in plants. As a result, there are knowledge gaps in understanding the contribution of the rhizobiome to soil-borne plant disease resistance and the ternary link of plant genes, root exudates, and disease resistance-associated microbes. Advancements in technologies such as quantitative trait loci (QTL) mapping and genome-wide association studies (GWAS) offer opportunities for the identification of genes associated with quantitative traits. In the present review, we summarize recent studies on the interactions of plant and rhizosphere microbes through root exudates to enhance soil-borne plant disease resistance and also highlight methods for quantifying the contribution of the rhizobiome to plant disease resistance and identifying the genes responsible for recruiting disease resistance-associated microbes through root exudates.

Predicting cell type-specific epigenomic profiles accounting for distal genetic effects.

Understanding how genetic variants affect the epigenome is key to interpreting GWAS, yet profiling these effects across the non-coding genome remains challenging due to experimental scalability. This necessitates accurate computational models. Existing machine learning approaches, while progressively improving, are confined to the cell types they were trained on, limiting their applicability. Here, we introduce Enformer Celltyping, a deep learning model which incorporates distal effects of DNA interactions, up to 100,000 base-pairs away, to predict epigenetic signals in previously unseen cell types. Using DNA and chromatin accessibility data for epigenetic imputation, Enformer Celltyping outperforms current best-in-class approaches and generalises across cell types and biological regions. Moreover, we propose a framework for evaluating models on genetic variant effect prediction using regulatory quantitative trait loci mapping studies, highlighting current limitations in genomic deep learning models. Despite this, Enformer Celltyping can also be used to study cell type-specific genetic enrichment of complex traits.

Quantitative Trait Locus Mapping and Candidate Gene Analysis of the Contents of Three Tanshinone Components in Salvia miltiorrhiza Bunge.

Tanshinones are abietane diterpenoid quinone compounds with diverse biological activities and pharmacological effects found in Salvia miltiorrhiza. Leveraging the high-density genetic map established through our prior research endeavors, we conducted a quantitative trait locus (QTL) analysis pertaining to the concentrations of three major tanshinone components, cryptotanshinone, tanshinone I, and tanshinone IIA, in S. miltiorrhiza. This extensive investigation was conducted across three distinct planting environments, ultimately identifying a comprehensive repertoire of 27 discernible QTLs. These QTLs were mapped onto four distinct linkage groups (LG), namely LG1, LG5, LG6, and LG7, which explained 3.11%-37.85% phenotypic variation. Candidate genes were projected based on consistent QTLs detected for each active ingredient in three environments. Nineteen putative candidate genes involved in the regulation of tanshinone biosynthesis were identified. These genes participate in primary metabolic and multiple branching terpenoid biosynthesis pathways, forming a complex regulatory network. Our findings have the potential to offer novel insights into advancing the understanding of the regulatory mechanisms governing tanshinone biosynthesis. Furthermore, these results establish crucial groundwork for gene discovery, marker-assisted selection breeding, and map-based cloning of functional genes associated with tanshinone content in S. miltiorrhiza.

Whole-genome sequencing of copy number variation analysis in Ethiopian cattle reveals adaptations to diverse environments.

Genomic structural variations (GSVs), notably copy number variations (CNVs), significantly shape genetic diversity and facilitate adaptation in cattle populations. Despite their importance, the genome-wide characterization of CNVs in indigenous Ethiopian cattle breeds-Abigar, Fellata, and Gojjam-Highland remains largely unexplored. In this study, we applied a read-depth approach to whole genome sequencing (WGS) data to conduct the first comprehensive analysis of CNVs in these populations. We identified 3,893 CNV regions (CNVRs) covering 19.15Mb (0.71% of the cattle genome). These CNVRs ranged from 1.60kb to 488.0kb, with an average size of 4.92kb. These CNVRs included deletions (1713), duplications (1929), and mixed events (251) showing notable differences in distribution among the breeds. Four out of five randomly selected CNVRs were successfully validated using real time polymerase chain reaction (qPCR). Further analyses identified candidate genes associated with high-altitude adaptation (GBE1 and SOD1), heat stress adaptation (HSPA13, DNAJC18, and DNAJC8) and resistance to tick infestations (BoLA and KRT33A). In addition, variance stabilizing transformation (VST) statistics highlighted population-specific CNVRs, emphasizing the unique genetic signatures of high-altitude adaptation in the Gojjam-Highland cattle breed. Among the detected CNVRs, 4.93% (192 out of 3,893) overlapped with 520 quantitative traits loci (QTLs) associated with six economically important trait categories suggesting that these CNVRs may significantly contribute to the genetic variation underlying these traits. Our comprehensive analysis reveals significant CNVRs associated with key adaptive traits in Ethiopian cattle breeds highlighting their genetic diversity and resilience. These findings offer valuable insights into the genetic basis of adaptability and can inform sustainable breeding practices and conservation efforts. Future research should prioritize the functional validation of these CNVRs and their integration into breeding programs to enhance traits such as disease resistance and environmental adaptability.

Identification and validation of two quantitative trait loci showing pleiotropic effect on multiple grain-related traits in bread wheat (Triticum aestivum L.).

QKl/Tgw/Gns.yaas-2D associates with KL, TGW, and GNS, and QKl/Tgw.yaas-5A associates with KL and TGW. Significantly pleiotropic and additive effects of these two QTL were validated. The YM5 allele both at QKl/Tgw/Gns.yaas-2D and QKl/Tgw.yaas-5A was proved to be the best allelic combination for improving yield potential. Kernel length (KL), kernel width (KW), thousand grain weight (TGW), and grain number per spike (GNS) play important roles in the yield improvement of wheat. In this study, one recombinant inbred line (RIL) derived from a cross between Yangmai 5 (YM5) and Yanzhan 1 (YZ1) was used to identify quantitative trait loci (QTL) associated with KL, KW, TGW, and GNS across three years. Two pleiotropic QTL namely QKl/Tgw/Gns.yaas-2D and QKl/Tgw.yaas-5A were located in two genomic regions on chromosomes 2D and 5A, respectively. Breeder-friendly Kompetitive Allele-Specific PCR (KASP) markers for QKl/Tgw/Gns.yaas-2D and QKl/Tgw.yaas-5A were developed and validated in a set of 246 wheat cultivars/lines. Analysis of allelic combinations indicated that the YM5 allele both at QKl/Tgw/Gns.yaas-2D and QKl/Tgw.yaas-5A is probably the best one to promote TGW, GNS, and grain weight per spike. Based on the analysis of gene annotation, sequence variations, expression patterns, and GO enrichment, twenty-five and twenty-four candidate genes of QKl/Tgw/Gns.yaas-2D and QKl/Tgw.yaas-5A, respectively, were identified. These results provide the basis of fine-mapping the target QTL and marker-assisted selection in wheat yield-breeding programs.

Quantitative trait locus mapping and OsFLOq12 identification for rice grain hardness: towards improved rice flour for wheat substitution.

Recent shifts in consumer dietary preferences have led to a significant decline in rice consumption in Korea, resulting in surplus rice production. To address this issue, rice flour has been proposed as a substitute for wheat flour. However, the physical, chemical and structural differences between rice and wheat, particularly in grain hardness, pose challenges in using rice flour as an alternative. Understanding the genetic factors that influence rice grain hardness is crucial for improving the milling process and producing high-quality rice flour suitable for wheat flour substitution. In this study, various grain traits, including length, width, thickness, length-to-width ratio and hardness, were measured in a population of brown and milled rice. Quantitative trait locus (QTL) analysis revealed a significant association between grain hardness and thickness, with QTLs for grain hardness mapped on chromosomes 1 and 12 for brown and milled rice, respectively. A total of 20 candidate genes related to grain hardness were identified through QTL analysis. Among them, OsFLOq12 (LOC_Os12g43550) was identified as a key gene influencing grain hardness, which encodes a Ras small GTPase. Phenotypic analysis showed differences in endosperm appearance and particle size between lines with low and high grain hardness. The genetic analysis of OsFLOq12 revealed a single nucleotide polymorphism associated with grain hardness. This study provides valuable insights into the genetic background of grain hardness, offering a foundation for breeding rice varieties optimized for flour production as a viable substitute for wheat flour. © 2024 Society of Chemical Industry.

Ferroptosis regulates hemolysis in stored murine and human red blood cells.

Red blood cell (RBC) metabolism regulates hemolysis during aging in vivo and in the blood bank. However, the genetic underpinnings of RBC metabolic heterogeneity and extravascular hemolysis at population scale are incompletely understood. Based on the breeding of 8 founder strains with extreme genetic diversity, the Jackson laboratory diversity outbred population can capture the impact of genetic heterogeneity in like fashion to population-based studies. RBCs from 350 outbred mice, either fresh or stored for 7 days, were tested for post-transfusion recovery, as well as metabolomics and lipidomics analyses. Metabolite and lipid Quantitative Trait Loci (QTL) mapped >400 gene-metabolite associations, which we collated into an online interactive portal. Relevant to RBC storage, we identified a QTL hotspot on chromosome 1, mapping on the region coding for the ferrireductase Steap3, a transcriptional target to p53. Steap3 regulated post-transfusion recovery, contributing to a ferroptosis-like process of lipid peroxidation, as validated via genetic manipulation in mice. Translational validation of murine findings in humans, STEAP3 polymorphisms were associated with RBC iron content, lipid peroxidation and in vitro hemolysis in 13,091 blood donors from the Recipient Epidemiology and Donor Evaluation Study. QTL analyses in humans identified a network of gene products (FADS1/2, EPHX2, LPCAT3, SLC22A16, G6PD, ELOVL, PLA2G6) associated with lower levels of oxylipins. These polymorphisms were prevalent in donors of African descent and were linked to allele frequency of hemolysis-linked polymorphisms for Steap3 or p53. These genetic variants were also associated with lower hemoglobin increments in thousands of single-unit transfusion recipients from the vein-to-vein database.

Identification of a novel locus qGW12/OsPUB23 regulating grain shape and weight in rice (Oryza sativa L.).

Key message A major quantitative trait locus (qGW12) for grain shape and weight has been isolated in rice, corresponding to LOC_Os12g17900/OsPUB23, and its encoded protein interacts with OsMADS1. Grain shape in rice is an important trait that influences both yield and quality. The primary determinants of grain shape are quantitative trait loci (QTLs) inherited from natural variation in crops. In recent years, much attention has been paid to the molecular role of QTLs in regulating grain shape and weight. In this study, we report the cloning and characterization of qGW12, a major QTL regulating grain shape and weight in rice, using a series of chromosome fragment substitution lines (CSSLs) derived from Oryza sativa indica cultivar 9311 (acceptor) and Oryza rufipogon Griff (donor). One CSSL line, Q187, harboring the introgression of qGW12, exhibited a significant decrease in grain-shape-related traits (including grain length and width) and thousand-grain weight compared to the cultivar 9311. Subsequent backcrossing of Q187 with 9311 resulted in the generation of secondary segregating populations, which were used to fine-map qGW12 to a 24-kb region between markers Seq-44 and Seq-48. Our data indicated that qGW12 encodes a previously unreported U-box type E3 ubiquitin ligase, designated OsPUB23, which exhibited E3 ubiquitin ligase activity. Overexpression of OsPUB23 in rice resulted in higher plant yield than the wild type due to an increase in grain size and weight. Conversely, loss of OsPUB23 function resulted in the opposite tendency. Yeast two-hybrid screening and split luciferase complementation assays revealed that OsPUB23 interacts with OsMADS1. The functional characterization of OsPUB23 provides new genetic resources for improving of grain yield and quality in crops.

Genome-wide association of an organic naked barley diversity panel identified quantitative trait loci for disease resistance.

Foliar fungal diseases are a major limitation in organic naked barley (Hordeum vulgare L.) production. The lack of conventional fungicides in organic systems increases reliance on genetic resistance. We evaluated the severity of barley stripe rust (Puccinia striiformis f.sp. hordei Westend), leaf rust (Puccina hordei sp. hordei), spot blotch (Cochliobolus sativus, anamorph Bipolaris sorokiniana (S. Ito & Kurib.) Drechsler ex Dastur), and scald (Rhynchosporium commune Zaffarano, McDonald and Linde sp. November) on a naked barley diversity panel of 350 genotypes grown in 13 environments to identify quantitative trait loci associated with disease resistance. Genome-wide association analyses across and within environments found 10 marker trait associations for barley stripe rust, four marker trait associations for leaf rust, one marker trait association for scald, and five marker trait associations for spot blotch. Structure analysis identified six Ward groups based on genotypic diversity. Resistance to susceptible allele ratios were high for stripe rust and spot blotch, moderate for leaf rust, and low for scald. Combined phenotypic analysis values for each disease overlayed by a principal component analysis found distinct resistance and susceptibility patterns for barley stripe rust and scald. Most significant marker trait associations were previously identified in the literature, providing confirmation and potential new sources of disease resistance for genetic improvement of naked barley germplasm.

Genetic Dissection of Milled Rice Grain Shape by Using a Recombinant Inbred Line Population and Validation of qMLWR11.1 and qMLWR11.2

Grain shape in rice (Oryza sativa L.) is a complex trait governed by multiple quantitative trait loci (QTLs). To dissect the genetic basis of rice shape, QTL analysis was conducted for milled rice grain width (MGW), milled rice grain length (MGL), and milled rice length-to-width ratio (MLWR) using a recombinant inbred line (RIL) population of F10 and F11 generations derived from a cross between Yuexiangzhan and Shengbasimiao. A high-density genetic map consisting of 2412 bins was constructed by sequencing 184 RILs, spanning a total length of 2376.46 cM. A total of 19 QTLs related to MGL, MGW, and MLWR were detected under two environments. The range of phenotypic variation attributed to individual QTL ranged from 1.67% to 32.08%. Among those, a novel locus for MGL, MGW and MLWR, designated as qMLWR3.2, was pinpointed within a specific ~0.96-Mb region. Two novel loci for MGW and MLWR, qMLWR11.1 and qMLWR11.2, were verified within ~1.22-Mb and ~0.52-Mb regions using three RIL-developed populations, respectively. These findings lay the foundation for further map-based cloning and molecular design breeding in rice.

QTL mapping and genome-wide association analysis reveal genetic loci and candidate gene for resistance to gray leaf spot in tropical and subtropical maize germplasm.

Using QTL mapping and GWAS, two candidate genes (Zm00001d051039 and Zm00001d051147) were consistently identified across the three different environments and BLUP values. GWAS analysis identified the candidate gene, Zm00001d044845. These genes were subsequently validated to exhibit a significant association with maize gray leaf spot (GLS) resistance. Gray leaf spot (GLS) is a major foliar disease of maize (Zea mays L.) that causes significant yield losses worldwide. Understanding the genetic mechanisms underlying gray leaf spot resistance is crucial for breeding high-yielding and disease-resistant varieties. In this study, eight tropical and subtropical germplasms were crossed with the temperate germplasm Ye107 to develop a nested association mapping (NAM) population comprising 1,653 F2:8 RILs, consisting of eight recombinant inbred line (RIL) subpopulations, using the single-seed descent method. The NAM population was evaluated for GLS resistance in three different environments, and genotyping by sequencing of the NAM population generated 593,719 high-quality single-nucleotide polymorphisms (SNPs). Linkage analysis and genome-wide association studies (GWASs) were conducted to identify candidate genes regulating GLS resistance in maize. Both analyses identified 25 QTLs and 149 SNPs that were significantly associated with GLS resistance. Candidate genes were screened 20Kb upstream and downstream of the significant SNPs, and three novel candidate genes (Zm00001d051039, Zm00001d051147, and Zm00001d044845) were identified. Zm00001d051039 and Zm00001d051147 were located on chromosome 4 and co-localized in both linkage (qGLS4-1 and qGLS4-2) and GWAS analyses. SNP-138,153,206 was located 0.499kb downstream of the candidate gene Zm00001d051039, which encodes the protein IN2-1 homolog B, a homolog of glutathione S-transferase (GST). GSTs and protein IN2-1 homolog B scavenge reactive oxygen species under various stress conditions, and GSTs are believed to protect plants from a wide range of biotic and abiotic stresses by detoxifying reactive electrophilic compounds. Zm00001d051147 encodes a probable beta-1,4-xylosyltransferase involved in the biosynthesis of xylan in the cell wall, enhancing resistance. SNP-145,813,215 was located 2.69kb downstream of the candidate gene. SNP-5,043,412 was consistently identified in three different environments and BLUP values and was located 8.788kb downstream of the candidate gene Zm00001d044845 on chromosome 9. Zm00001d044845 encodes the U-box domain-containing protein 4 (PUB4), which is involved in regulating plant immunity. qRT-PCR analysis showed that the relative expression levels of the three candidate genes were significantly upregulated in the leaves of the TML139 (resistant) parent, indicating that these three candidate genes could be associated with resistance to GLS. The findings of this study are significant for marker-assisted breeding aimed at enhancing resistance to GLS in maize and lay the foundation for further elucidation of the genetic mechanisms underlying resistance to gray leaf spot in maize and breeding of new disease-resistant varieties.

DNA methylation biomarkers and myopia: a multi-omics study integrating GWAS, mQTL and eQTL data.

This study aimed to identify DNA methylation biomarkers associated with myopia using summary-data-based Mendelian randomization (SMR). A systematic search of the PubMed, Web of Science, Cochrane Library, and Embase databases was conducted up to March 27, 2024. SMR analyses were performed to integrate genome-wide association study (GWAS) with methylation quantitative trait loci (mQTL) and expression quantitative trait loci (eQTL) studies. The heterogeneity in the dependent instrument (HEIDI) test was utilized to distinguish pleiotropic associations from linkage disequilibrium. The systematic review identified 26 DNA methylation biomarkers in five studies, with no overlap observed among those identified by different studies. After integrating GWAS with multi-omics data of mQTL and eQTL, six genes were significantly associated with myopia: PRMT6 (cg00944433 and cg15468180), SH3YL1 (cg03299269, cg11361895, and cg13354988), ZKSCAN4 (cg01192291), GATS (cg17830204), NPAT (cg04826772), and UBE2I (cg03545757 and cg08025960). We identified six methylation biomarkers associated with the risk of myopia that may be helpful to elucidate the etiology mechanisms of myopia. Further experimental validation studies are required to corroborate these findings.

Common protein-altering variant in GFAP is associated with white matter lesions in the older Japanese population.

The genetic architecture of white matter lesions (WMLs) in Asian populations has not been well-characterized. Here, we performed a genome-wide association study (GWAS) to identify loci associated with the WML volume. Brain MRI and DNA samples were collected from 9479 participants in the Japan Prospective Studies Collaboration for Aging and Dementia (JPSC-AD). The GWAS confirmed three known WML-associated loci (SH3PXD2A, GFAP, and TRIM47). The lead variant of GFAP was a common missense variant (p.D295N) in East Asians. Meta-GWAS using the publicly available summary statistics of UK Biobank identified one previously unreported locus 6q23.2 (SLC2A12). Integration with expression quantitative trait locus data implied the newly identified locus affects SLC2A12 expression. The effect sizes of 20 lead variants at the WML-associated loci were moderately correlated between JPSC-AD and UK Biobank. These results indicate that the alteration in GFAP protein caused by the common missense variant in East Asians influences the WML volume.

Abstract 4118735: Interpretable deep learning translation of GWAS findings for drug repurposing in Atrial Fibrillation

Introduction: Translating human genetic findings, such as genome-wide association studies (GWAS) to pathobiology and the discovery of therapeutic target remains a major challenge for Atrial Fibrillation (AF). We previously published a network topology-based deep learning framework to identify disease-associated genes (NETTAG). Hypothesis: By using a deep learning framework, we can efficiently identify AF risk genes, druggable targets, and candidates of repurposable drugs. Aims: To identify potential AF related genes and repurposable drug candidates using our deep learning framework. Methods: First, we collected the reported quantitative trait loci (QTLs) for AF from human heart tissues. Then, we identified the overlaps between the QTLs and the previously reported 150 AF GWAS loci in the latest meta-analysis. We previously built a comprehensive human protein-protein interactome using 18 publicly available databases, containing 351,444 unique PPIs and 17,706 proteins. Using the human protein-protein interactome and the overlaps between AF GWAS hits and QTLs, we prioritized genes and defined the genes with the top 1 % predicted score as AF risk genes (afRGs) using the NETTAG. Then, we assembled drugs from the Drugbank database relating 2,938 FDA-approved drugs or clinically investigated molecules. Using network proximity approaches to evaluate the closest distance between afRGs and a drug’s targets within the human protein-protein interactome, we computationally predicted drugs for AF using Z scores <-2.0. Results: We first collected the overlaps between AF GWAS hits and QTLs, which constituted 27 expression and 12 splicing QTLs. Via NETTAG, we identified 176 afRGs. Among the 176 predicted afRGs, 12 proteins (gene products of afRGs) have been identified as known drug targets with FDA-approved medicines. In total, 1,275 targets have been widely investigated as therapeutic targets for treating AF. Using the closest-based network proximity approach, we computationally identified 49 candidate drugs. These included drugs both reportedly potentially treating AF, such as Pioglitazone (Z=2.29), Telmisartan (Z=-2.52), Sildenafil (Z=-2.86), and those have never been reported before, such as Balsalazide (Z=-2.32). Conclusion: Using a deep learning methodology that utilized GWAS and QTL findings, we identified risk genes and repurposing drug candidates for AF.

Glycine soja, PI424025, is a valuable genetic resource to improve soybean seed-protein content and composition.

Soybean seed-protein content and composition is important because it contributes over half the value of this $61 billion crop. Historic negative correlation between seed-protein content and oil have been reported. Similarly, negative correlation between seed-protein content and yield have been reported but may be at least in part mitigated by increasing the genetic diversity of the elite soybean germplasm. Improvements in amino acid composition of seed-protein would increase the value of soybean meal and protein for animal and human consumption. We have identified a genetic resource in wild soybean germplasm, PI424025B, with elevated seed-protein, elevated cysteine in the seed and increased sulfur content in the seed. We have developed a population of Recombinant Inbred Lines derived from a cross between NC-Raleigh and PI424025B. We evaluated the carbon, nitrogen and sulfur (C, N and S) content of seeds from the progeny, the parents and other high-seed protein soybean lines. N content and C/N (ratio of C to N) were well correlated with protein content measured by NIR. PI424025B had a N content comparable to high-protein soybean lines and a superior N/S. These traits were inherited by some of the progeny. Quantitative Trait Loci (QTL) associated with high-seed protein were identified on chr2, chr20 and chr15 and colocalizes with well characterized loci on chr 15 and chr 20 known to affect seed-protein content and quality. A potentially unique QTL was identified on Chr15. Unlike the chr20 QTL, the chr15 QTL improved S content relative to N content and was superior to other high seed-protein phenotypes tested. These data indicate that PI424025B is a valuable resource to diversify the genetics of soybean while improving soybean seed-protein content and composition.