Quantitative Trait Loci Research Articles

Identification of genetic loci for powdery mildew resistance in common wheat.

Powdery mildew (PM) poses an extreme threat to wheat yields and quality. In this study, 262 recombinant inbred lines (RILs) of Doumai and Shi 4185 cross were used to map PM resistance genes across four environments. High-density genetic linkage map of the Doumai/Shi 4185 RIL population was constructed using the wheat Illumina iSelect 90K single-nucleotide polymorphism (SNP) array. In total, four stable quantitative trait loci (QTLs) for PM resistance, QPm.caas-2AS, QPm.caas-4AS, QPm.caas-4BL, and QPm.caas-6BS, were detected and explained 5.6%-15.6% of the phenotypic variances. Doumai contributed all the resistance alleles of QPm.caas-2AS, QPm.caas-4AS, QPm.caas-4BL, and QPm.caas-6BS. Among these, QPm.caas-4AS and QPm.caas-6BS overlapped with the previously reported loci, whereas QPm.caas-2AS and QPm.caas-4BL are potentially novel. In addition, six high-confidence genes encoding the NBS-LRR-like resistance protein, disease resistance protein family, and calcium/calmodulin-dependent serine/threonine-kinase were selected as the candidate genes for PM resistance. Three kompetitive allele-specific PCR (KASP) markers, Kasp_PMR_2AS for QPm.caas-2AS, Kasp_PMR_4BL for QPm.caas-4BL, and Kasp_PMR_6BS for QPm.caas-6BS, were developed, and their genetic effects were validated in a natural population including 100 cultivars. These findings will offer valuable QTLs and available KASP markers to enhance wheat marker-assisted breeding for PM resistance.

Screening Germplasms and Detecting Quantitative Trait Loci for High Sucrose Content in Soybean

Sucrose is a desirable component of processed soybean foods and animal feed, and thus, its content is used as an important characteristic for assessing the quality of soybean seeds. However, few studies have focused on the quantitative trait loci (QTLs) associated with sucrose regulation in soybean seeds. This study aims to measure the sucrose content of 1014 soybean accessions and identify genes related to high sucrose levels using QTL analysis. Colorimetric analysis based on the enzymatic reaction of invertase (INV) and glucose oxidase (GOD) was employed to test the germplasms. A total of six high-sucrose genetic resources (IT186230, IT195321, IT263138, IT263276, IT263286, and IT276521) and two low-sucrose genetic resources (IT025668 and IT274054) were identified. Two F2:3 populations, IT186230 × IT025668 and Ilmi × IT186230, were then established from these germplasms. QTL analysis identified four QTLs (qSUC6.1, qSUC11.1, qSUC15.1, and qSUC17.1), explaining 7.3–27.6% of the phenotypic variation in the sugar content. Twenty candidate genes were found at the four QTLs. Notably, Glyma.17G152300, located in the qSUC17.1 QTL region, exhibited a 17-fold higher gene expression in the high-sucrose germplasm IT186230 compared to the control germplasm Ilmi, confirming its role as a major gene regulating the sucrose content in soybean. These results may assist in marker-assisted selection for breeding programs that aim to develop soybean lines with a higher sucrose content.

Mining of Oil Content Genes in Recombinant Maize Inbred Lines with Introgression from Temperate and Tropical Germplasm.

The oil content of maize kernels is essential to determine its nutritional and economic value. A multiparent population (MPP) consisting of five recombinant inbred line (RIL) subpopulations was developed to elucidate the genetic basis of the total oil content (TOC) in maize. The MPP used the subtropical maize inbred lines CML312 and CML384, along with the tropical maize inbred lines CML395, YML46, and YML32 as the female parents, and Ye107 as the male parent. A genome-wide association study (GWAS) was performed using 429 RILs of the multiparent population across three environments, employing 584,847 high-quality single nucleotide polymorphisms (SNPs). Furthermore, linkage analysis was performed in the five subpopulations to identify quantitative trait loci (QTL) linked to TOC in maize. Through QTL mapping and GWAS, 18 QTLs and 60 SNPs that were significantly associated with TOC were identified. Two novel candidate genes, Zm00001d029550 and Zm00001d029551, related to TOC in maize and located on chromosome 1 were reported, which have not been previously reported. These genes are involved in biosynthesis, lipid signal transduction, plant development and metabolism, and stress responses, potentially influencing maize TOC. Haplotype analysis of Zm00001d029550 and Zm00001d029551 revealed that Hap3 could be considered a superior haplotype for increasing TOC in maize. A co-located SNP (SNP-75791466) on chromosome 1, located 5648 bp and 11,951 bp downstream of the candidate genes Zm00001d029550 and Zm00001d029551, respectively, was found to be expressed in various maize tissues. The highest expression was observed in embryos after pollination, indicating that embryos are the main tissue for oil accumulation in maize. This study provides a theoretical basis for understanding the genetic mechanisms underlying maize TOC and developing high-quality, high-oil maize varieties.

Association of circulating cytokine levels and tissue-infiltrating myeloid cells with achalasia: results from Mendelian randomization and validation through clinical characteristics and single-cell RNA sequencing.

Achalasia is a rare motility disorder of the esophagus often accompanied by immune dysregulation, yet specific underlying mechanisms remain poorly understood. We utilized Mendelian randomization (MR) to explore the causal effects of cytokine levels on achalasia, with cis-expression/protein quantitative trait loci (cis-eQTLs/pQTLs) for 47 cytokines selected from a genome-wide association study (GWAS) meta-analysis and GWAS data for achalasia obtained from FinnGen. For cytokines significantly linked to achalasia, we analyzed their plasma concentrations and expression differences in the lower esophageal sphincter (LES) using enzyme-linked immunosorbent assay and single-cell RNA sequencing (scRNA-seq) profiling, respectively. We further employed bioinformatics approaches to investigate underlying mechanisms. We revealed positive associations of circulating Eotaxin, macrophage inflammatory protein-1b (MIP1b), soluble E-selectin (SeSelectin) and TNF-related apoptosis-inducing ligand (TRAIL) with achalasia. When combining MR findings with scRNA-seq data, we observed upregulation of TRAIL (OR = 2.70, 95% CI, 1.20-6.07), encoded by TNFSF10, in monocytes and downregulation of interleukin-1 receptor antagonist (IL-1ra) (OR = 0.70, 95% CI 0.59-0.84), encoded by IL1RN, in FOS_macrophages in achalasia. TNFSF10high monocytes in achalasia displayed activated type I interferon signaling, and IL1RNlow FOS_macrophages exhibited increased intercellular communications with various lymphocytes, together shaping the proinflammatory microenvironment of achalasia. We identified circulating Eotaxin, MIP1b, SeSelectin and TRAIL as potential drug targets for achalasia. TNFSF10high monocytes and IL1RNlow macrophages may play a role in the pathogenesis of achalasia.

Natural variation in MdNAC5 contributes to fruit firmness and ripening divergence in apple

Abstract Fruit firmness is an important trait for characterizing the quality and value of apple. It is also serves as an indicator of fruit maturity, as it is a complex trait regulated by multiple genes. Re-sequencing techniques can be employed to elucidate variations in such complex fruit traits. Here, the whole genomes of 294 F1 hybrids of ‘Fuji’ and ‘Cripp's Pink’ were re-sequenced, and a high-density bin-map was constructed using 5,014 bin markers with a total map distance of 2,213.23 cM and an average map distance of 0.44 cM. Quantitative trait loci (QTLs) of traits related to fruit were mapped, and an A-T allele variant identified in the coding region of MdNAC5 was found to potentially regulate fruit firmness and ripening. The overexpression of MdNAC5A resulted in higher production of methionine and 1-aminocyclopropanecarboxylic acid compared to MdNAC5T, leading to reduced fruit firmness and accelerated ripening in apples and tomatoes. Furthermore, the activities of MdNAC5A and MdNAC5T were enhanced through their differential binding to the promoter regions of MdACS1 and MdERF3. Spatial variations in MdNAC5A and MdNAC5T caused changes in MdACS1 expression following their interaction with MdERF3. Ultimately, utilizing different MdNAC5 alleles offers a strategy to manipulate fruit firmness in apple breeding.

GWAS of multiple neuropathology endophenotypes identifies new risk loci and provides insights into the genetic risk of dementia.

Genome-wide association studies (GWAS) have identified >80 Alzheimer's disease and related dementias (ADRD)-associated genetic loci. However, the clinical outcomes used in most previous studies belie the complex nature of underlying neuropathologies. Here we performed GWAS on 11 ADRD-related neuropathology endophenotypes with participants drawn from the following three sources: the National Alzheimer's Coordinating Center, the Religious Orders Study and Rush Memory and Aging Project, and the Adult Changes in Thought study (n = 7,804 total autopsied participants). We identified eight independent significantly associated loci, of which four were new (COL4A1, PIK3R5, LZTS1 and APOC2). Separately testing known ADRD loci, 19 loci were significantly associated with at least one neuropathology after false-discovery rate adjustment. Genetic colocalization analyses identified pleiotropic effects and quantitative trait loci. Methylation in the cerebral cortex at two sites near APOC2 was associated with cerebral amyloid angiopathy. Studies that include neuropathology endophenotypes are an important step in understanding the mechanisms underlying genetic ADRD risk.

Marker assisted selection and genome recovery for heat tolerance in segregants of rice (Oryza sativa L.)

Abstract In the present global warming scenario, it is urgent to impart heat tolerance into the popular high yielding rice (Oryza sativa L.) varieties to reduce yield loss to a great extent. Uma (a prevalent red-grained rice variety in Kerala) was crossed with Nagina 22 (N22), the popular donor for heat tolerance. From the seven promising heat-tolerant F3 plants previously identified through marker assisted selection and field screening, F4 lines (58 nos.) were raised and characterised morphologically. Heat tolerance was scored under natural heat stress during hot summer months in field conditions. Among the evaluated F4 progenies, 26 promising plants registered >75% spikelet fertility. Double panicles were observed in some of the tillers of fourteen F4 plants. During the selection with reported polymorphic markers between parents, all the 26 F4 plants produced the corresponding amplicon for RM5749 (linked marker for heat tolerance in the parental cross Uma x N22) and also for RM9, RM201, RM208, RM225, RM242, RM495, RM3586, RM6100, RM6836, and RM26212, corresponding to the heat tolerant parent N22. Genomic analysis revealed 64% recovery of the Uma genome in seven F4 plants, with maximum genomic regions of Uma on the chromosomes 3 and 5. These promising F4 plants could be forwarded to generate stable and high yielding heat tolerant rice varieties. The identified markers could be used for linkage analysis and QTL mapping in future. Keywords: Heat stress; Rice; spikelet fertility; SSR; QTL

Profiling genetically driven alternative splicing across the Indonesian archipelago

One of the regulatory mechanisms influencing the functional capacity of genes is alternative splicing (AS). Previous studies exploring the splicing landscape of human tissues have shown that AS has contributed to human biology, especially in disease progression and the immune response. Nonetheless, this phenomenon remains poorly characterized across human populations, and it is unclear how genetic and environmental variation contribute to AS. Here, we examine a set of 115 Indonesian samples from three traditional island populations spanning the genetic ancestry cline that characterizes Island Southeast Asia. We conduct a global AS analysis between islands to ascertain the degree of functionally significant AS events and their consequences. Using an event-based statistical model, we detected over 1,500 significant differential AS events across all comparisons. Additionally, we identify over 6,000 genetic variants associated with changes in splicing (splicing quantitative trait loci [sQTLs]), some of which are driven by Papuan-like genetic ancestry, and only show partial overlap with other publicly available sQTL datasets derived from other populations. Computational predictions of RNA binding activity reveal that a fraction of these sQTLs directly modulate the binding propensity of proteins involved in the splicing regulation of immune genes. Overall, these results contribute toward elucidating the role of genetic variation in shaping gene regulation in one of the most diverse regions in the world.

Machine vision-assisted genomic prediction and genome-wide association of spleen-related traits in large yellow croaker infected with visceral white-nodules disease

High-resolution and high-throughput genotype-to-phenotype studies in fish are rapidly advancing, driven by innovative technologies that aim to address the challenges of modern breeding models. In recent years, machine vision and deep learning techniques, particularly convolutional neural networks (CNNs), have achieved significant success in image recognition and segmentation. Moreover, qualitative and quantitative analysis of disease resistance has always been a crucial field of research in genetics. This motivation has led us to investigate the potential of large yellow croaker visceral white-nodules disease (VWND) in encoding information on disease resistance for the task of accession classification. In this study, we proposed an image segmentation framework for the feature extraction of the spleen after VWND infection based on machine vision. We utilized deep CNNs and threshold segmentation for automatic feature learning and object segmentation. This approach eliminates subjectivity and enhances work efficiency compared to using hand-crafted features. Additionally, we employed spleen-related traits to conduct genome-wide association analysis (GWAS), which led to the identification of 24 significant SNPs and 10 major quantitative trait loci. The results of function enrichment analysis on candidate genes also indicated potential relationships with immune regulation mechanisms. Furthermore, we explored the use of genomic selection (GS) technology for phenotype prediction of extreme individuals, which further supports the predictability of spleen-related phenotypes for VWND resistance in large yellow croakers. Our findings demonstrate that artificial intelligence (AI)-based phenotyping approaches can deliver state-of-the-art performance for genetics research. We hope this work will provide a paradigm for applying deep learning and machine vision to phenotyping in aquaculture species.

Lipid-lowering drugs and risk of rapid renal function decline: a mendelian randomization study.

Chronic kidney disease (CKD) patients face the risk of rapid kidney function decline leading to adverse outcomes like dialysis and mortality. Lipid metabolism might contribute to acute kidney function decline in CKD patients. Here, we utilized the Mendelian Randomization approach to investigate potential causal relationships between drug target-mediated lipid phenotypes and rapid renal function decline. In this study, we utilized two methodologies: summarized data-based Mendelian randomization (SMR) and inverse variance-weighted Mendelian randomization (IVW-MR), to approximate exposure to lipid-lowering drugs. This entailed leveraging expression quantitative trait loci (eQTL) for drug target genes and genetic variants proximal to drug target gene regions, which encode proteins associated with low-density lipoprotein (LDL) cholesterol, as identified in genome-wide association studies. The objective was to investigate causal associations with the progression of rapid kidney function decline. The SMR analysis revealed a potential association between high expression of PCSK9 and rapid kidney function decline (OR = 1.11, 95% CI= [1.001-1.23]; p = 0.044). Similarly, IVW-MR analysis demonstrated a negative association between LDL cholesterol mediated by HMGCR and kidney function decline (OR = 0.74, 95% CI = 0.60-0.90; p = 0.003). Genetically predicted inhibition of HMGCR is linked with the progression of kidney function decline, while genetically predicted PCSK9 inhibition is negatively associated with kidney function decline. Future research should incorporate clinical trials to validate the relevance of PCSK9 in preventing kidney function decline.

Global Epidemiological Impact of PNPLA3 I148M on Liver Disease.

The prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) has increased exponentially over the past three decades, in parallel with the global rise in obesity and type 2 diabetes. It is currently the most common cause of liver-related morbidity and mortality. Although obesity has been identified as a key factor in the increased prevalence of MASLD, individual differences in susceptibility are significantly influenced by genetic factors. PNPLA3 I148M (rs738409 C>G) is the variant with the greatest impact on the risk of developing progressive MASLD and likely other forms of steatotic liver disease. This variant is prevalent across the globe, with the risk allele (G) frequency exhibiting considerable variation. Here, we review the contribution of PNPLA3 I148M to global burden and regional differences in MASLD prevalence, focusing on recent evidence emerging from population-based sequencing studies and prevalence assessments. We calculated the population attributable fraction (PAF) as a means of quantifying the impact of the variant on MASLD. Furthermore, we employ quantitative trait locus (QTL) analysis to ascertain the associations between rs738409 and a range of phenotypic traits. This analysis suggests that these QTLs may underpin pleiotropic effects on extrahepatic traits. Finally, we outline potential avenues for further research and identify key areas for investigation in future studies.

Molecular and genetic basis of plant architecture in soybean.

Plant architecture determines canopy coverage, photosynthetic efficiency, and ultimately productivity in soybean (Glycine max). Optimizing plant architecture is a major goal of breeders to develop high yield soybean varieties. Over the past few decades, the yield per unit area of soybean has not changed significantly; however, rice and wheat breeders have succeeded in achieving high yields by generating semi-dwarf varieties. Semi-dwarf crops have the potential to ensure yield stability in high-density planting environments because they can significantly improve responses to fertilizer input, lodging resistance, and enhance resistance to various abiotic and biotic stresses. Soybean has a unique plant architecture, with leaves, inflorescences, and pods growing at each node; internode number greatly affects the final yield. Therefore, producing high-yielding soybean plants with an ideal architecture requires the coordination of effective node formation, effective internode formation, and branching. Dozens of quantitative trait loci (QTLs) controlling plant architecture have been identified in soybean, but only a few genes that control this trait have been cloned and characterized. Here, we review recent progress in understanding the genetic basis of soybean plant architecture. We provide our views and perspectives on how to breed new high-yielding soybean varieties.

Causal relationship between antihypertensive drugs and Hashimoto's thyroiditis: a drug-target Mendelian randomization study.

Recent studies have indicated a potential association of hypertension with Hashimoto's thyroiditis (HT) and other autoimmune diseases, yet the impact of antihypertensive drugs on HT risk is not well understood. We employed a drug-target Mendelian randomization approach to investigate the prolonged impact of 9 classes of antihypertensive medications on HT susceptibility in European and Asian populations. Genetic variants close to or within genes associated with the drug targets and systolic blood pressure (SBP) were utilized to mimic the effects of antihypertensive medications. We focused on drugs linked to a lower risk of coronary artery disease for our main analysis. We gathered genetic data on SBP and HT risk from comprehensive genome-wide association studies available for European and Asian groups. For a supplementary analysis, we used expression quantitative trait loci (eQTLs) related to drug target genes as proxies. Our analysis revealed that the use of calcium channel blockers (CCBs) is linked to a reduced risk of HT in both European (OR [95% CI]: 0.96 [0.95 to 0.98] per 1 mmHg decrease in SBP; p = 3.51×10-5) and Asian populations (OR [95% CI]: 0.28 [0.12, 0.66]; p = 3.54×10-3). Moreover, genetically mimicking the use of loop diuretics (OR [95% CI]: 0.94 [0.91, 0.97]; p = 3.57×10-5) and thiazide diuretics (0.98 [0.96, 0.99]; p = 3.83×10-3) showed a significant association with a decreased risk of HT only in European population. These outcomes were confirmed when eQTLs were employed to represent the effects of antihypertensive medications. The study suggests that CCBs and diuretics could potentially reduce the risk of HT in different populations. Additional research is needed to assess the feasibility of repurposing antihypertensive medications for the prevention of HT.

Genetically Supported Drug Targets and Dental Traits: A Mendelian Randomization Study

Current interventions for oral/dental diseases heavily rely on operative/surgical procedures, while the discovery of novel drug targets may enable access to noninvasive pharmacotherapy. Therefore, this study aims to leverage large-scale data and Mendelian randomization (MR) techniques, utilizing genetic variants as instruments, to identify potential therapeutic targets for oral and dental diseases supported by genetic evidence. By intersecting 4,302 druggable genes with expression quantitative trait loci from 31,684 blood samples, we identified 2,580 druggable targets as exposures. Single nucleotide polymorphisms associated with dental disease/symptom traits were collected from FinnGen R9, the Gene–Lifestyle Interactions in Dental Endpoints consortium, and the UK Biobank to serve as outcomes for both discovery and replication purposes. Through MR analysis, we identified 43 druggable targets for various dental disease/symptom traits. To evaluate the viability of these targets, we replicated the analysis using circulating protein quantitative trait loci as exposures. Additionally, we conducted sensitivity, colocalization, Gene Ontology/Kyoto Encyclopedia of Genes and Genomes annotation, protein–protein interaction analyses, and validated dental trait–associated druggable gene expression in animal models. Among these targets, IL12RB1 (odds ratio [OR], 1.01; 95% confidence interval [CI], 1.01–1.01) and TNF (OR, 0.98; 95% CI, 0.97–0.99) exhibited therapeutic promise for oral ulcers, whereas CXCL10 (OR, 0.84; 95% CI, 0.76–0.91) was for periodontitis. Through a rigorous quality control and validation pipeline, our study yields compelling evidence for these druggable targets, which may enhance the clinical prognosis by developing novel drugs or repurposing existing ones.

Integrated approach of machine learning, Mendelian randomization and experimental validation for biomarker discovery in diabetic nephropathy.

To identify potential biomarkers and explore the mechanisms underlying diabetic nephropathy (DN) by integrating machine learning, Mendelian randomization (MR) and experimental validation. Microarray and RNA-sequencing datasets (GSE47184, GSE96804, GSE104948, GSE104954, GSE142025 and GSE175759) were obtained from the Gene Expression Omnibus database. Differential expression analysis identified the differentially expressed genes (DEGs) between patients with DN and controls. Diverse machine learning algorithms, including least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and random forest, were used to enhance gene selection accuracy and predictive power. We integrated summary-level data from genome-wide association studies on DN with expression quantitative trait loci data to identify genes with potential causal relationships to DN. The predictive performance of the biomarker gene was validated using receiver operating characteristic (ROC) curves. Gene set enrichment and correlation analyses were conducted to investigate potential mechanisms. Finally, the biomarker gene was validated using quantitative real-time polymerase chain reaction in clinical samples from patients with DN and controls. Based on identified 314 DEGs, seven characteristic genes with high predictive performance were identified using three integrated machine learning algorithms. MR analysis revealed 219 genes with significant causal effects on DN, ultimately identifying one co-expressed gene, carbonic anhydrase II (CA2), as a key biomarker for DN. The ROC curves demonstrated the excellent predictive performance of CA2, with area under the curve values consistently above 0.878 across all datasets. Additionally, our analysis indicated a significant association between CA2 and infiltrating immune cells in DN, providing potential mechanistic insights. This biomarker was validated using clinical samples, confirming the reliability of our findings in clinical practice. By integrating machine learning, MR and experimental validation, we successfully identified and validated CA2 as a promising biomarker for DN with excellent predictive performance. The biomarker may play a role in the pathogenesis and progression of DN via immune-related pathways. These findings provide important insights into the molecular mechanisms underlying DN and may inform the development of personalized treatment strategies for this disease.

Integrative multi-omics analysis reveals genetic and heterotic contributions to male fertility and yield in potato.

The genetic analysis of potato is hampered by the complexity of tetrasomic inheritance. An ongoing effort aims to transform the clonally propagated tetraploid potato into a seed-propagated diploid crop, which would make genetic analyses much easier owing to disomic inheritance. Here, we construct and report the large-scale genetic and heterotic characteristics of a diploid F2 potato population derived from the cross of two highly homozygous inbred lines. We investigate 20,382 traits generated from multi-omics dataset and identify 25,770 quantitative trait loci (QTLs). Coupled with gene expression data, we construct a systems-genetics network for gene discovery in potatoes. Importantly, we explore the genetic basis of heterosis in this population, especially for yield and male fertility heterosis. We find that positive heterotic effects of yield-related QTLs and negative heterotic effects of metabolite QTLs (mQTLs) contribute to yield heterosis. Additionally, we identify a PME gene with a dominance heterotic effect that plays an important role in male fertility heterosis. This study provides genetic resources for the potato community and will facilitate the application of heterosis in diploid potato breeding.

Targeting RAC1 might be a potential therapeutic strategy for diabetic kidney disease: a Mendelian randomization study.

This study aimed to ascertain the causal association between Ras-related C3 botulinum toxin substrate 1 (RAC1) and the incidence and progression of diabetic kidney disease (DKD) through Mendelian randomization analysis. RAC1 expression, evaluated using expression quantitative trait loci data from the eQTLGen Consortium, was served as the exposure variable. Outcomes encompassed the risk of DKD, end-stage renal disease (ESRD), albuminuria assessed by the urinary albumin-to-creatinine ratio (ACR), and estimated glomerular filtration rate (eGFR) among individuals with diabetes. Causal associations were computed using the inverse variance weighted (IVW), weighted median, and MR-PRESSO models. Additionally, we conducted analyses for heterogeneity, horizontal pleiotropy, and sensitivity. This study revealed a causal association between the genetic activation of RAC1 and an elevated risk of DKD among individuals with diabetes [IVW, odds ratio (OR) = 1.28, 95% confidence intervals (CI) 1.08-1.51, P = 0.004]. Furthermore, increased expression of RAC1 was linked to a higher risk of ESRD (IVW, OR = 1.20, 95% CI 1.02-1.43, P = 0.032). Excessive RAC1 expression was causally associated with elevated ACR (IVW, β = 0.052, 95% CI 0.003-0.100, P = 0.036). However, the analysis regarding RAC1 and eGFR showed significant heterogeneity and pleiotropy, with no discernible causal relationship. These findings suggested a positive correlation between the genetic activation of RAC1 and the incidence of DKD, the risk of ESRD, and exacerbated albuminuria among individuals with diabetes. Targeting RAC1 might potentially serve as a therapeutic strategy for DKD.

6715 Short Adult Height in Childhood Cancer Survivors: Prevalence, Risk Factors, and Genetic Contribution

Abstract Disclosure: T. Yoshida: None. J. Baedke: None. F. Wang: None. W. Moon: None. Y. Sapkota: None. J. Miguel Martínez: None. T.E. Merchant: None. C.L. Wilson: None. K.K. Ness: None. M.M. Hudson: None. Y. Yasui: None. A. Delaney: None. Background: Survivors of childhood cancer are at elevated risk for short adult height (SAH) due to cancer and/or its treatment. In the general population, height is a highly polygenic trait; heritability is estimated to be 70-80%. However, the contribution of genetic factors to SAH among childhood cancer survivors is unknown. In addition, the contribution of chemotherapy agents to risk of SAH among survivors has not been established. We assessed: 1) prevalence of SAH; 2) contribution of genetic factors; and 3) impact of cancer therapy including chemotherapy, on SAH in a large cohort of childhood cancer survivors. Methods: Participants included 4461 childhood cancer survivors aged ≥18 years (female 47.5%, mean age 33.2 years old) with measured height information. SAH was defined as height <3rd percentile for age and sex based on the Centers for Disease Control growth charts. Cancer and treatment history were extracted from medical records. We calculated multi-ancestry height polygenic score (PGS) using the latest methodology developed from 5.4 million individuals of diverse ancestries with more than 1 million variants, where lower score associates with shorter height. With a random sample of 75% of survivors, we fit a multivariable logistic regression model for SAH with the PGS, chemotherapy exposures/doses, corticosteroid exposures/doses, and established risk factors for SAH (e.g., age at cancer diagnosis, radiotherapy exposure) as covariates (main model). The remaining 25% of survivors served for validation of the main model and for the calculation of the population attributable fractions (PAF) of the PGS and cancer treatments. Results: The prevalence of SAH was 8.9% among all survivors (9.3% in males; 8.5% in females) and differed widely by primary cancer diagnosis. SAH was associated with lower PGS [odds ratio (OR) 0.47, 95% confidence interval (CI) 0.40-0.55 for a one standard deviation increase], alkylating agent exposure of >12000 mg/m2 (OR 2.19, 95% CI 1.41-3.38, vs. non-exposure), and spinal radiotherapy (OR 3.65, 95% CI 2.23-6.00, vs. non-exposure). Radiotherapy exposure to the hypothalamic-pituitary region and younger age at cancer diagnosis was also associated with SAH in a dose-response manner. The area under the ROC curve of the main model in the validation dataset was 0.80 (95% CI 0.74-0.87), suggesting good predictive ability for SAH by the model. The PAF of SAH calculated from the multiplicative logistic regression model of SAH was 85.7% for cancer treatments and 30.2% and 60.2% for having PGS below the median and the 90th percentile, respectively. Conclusions: Cancer treatments are the primary contributor to SAH risk among survivors with a PAF of 85.7%. Exposure to high-dose alkylating agents contributes to this along with radiotherapy. Inherited genetic factors also affect SAH among survivors but to a much lesser degree than cancer treatments. Presentation: 6/3/2024

Natural variation at the cotton HIC locus increases trichome density and enhances resistance to aphids.

Plant trichomes are an excellent model for studying cell differentiation and development, providing crucial defenses against biotic and abiotic stresses. There is a well-established inverse relationship between trichome density and aphid prevalence, indicating that higher trichome density leads to reduced aphid infestations. Here we present the cloning and characterization of a dominant quantitative trait locus, HIC (hirsute cotton), which significantly enhances cotton trichome density. This enhancement leads to markedly improved resistance against cotton aphids. The HIC encodes an HD-ZIP IV transcriptional activator, crucial for trichome initiation. Overexpression of HIC leads to a substantial increase in trichome density, while knockdown of HIC results in a marked decrease in density, confirming its role in trichome regulation. We identified a variant in the HIC promoter (-810 bp A to C) that increases transcription of HIC and trichome density in hirsute cotton compared with Gossypium hirsutum cultivars with fewer or no trichomes. Interestingly, although the -810 variant in the HIC promoter is the same in G. barbadense and hirsute cotton, the presence of a copia-like retrotransposon insertion in the coding region of HIC in G. barbadense causes premature transcription termination. Further analysis revealed that HIC positively regulates trichome density by directly targeting the EXPANSIN A2 gene, which is involved in cell wall development. Taken together, our results underscore the pivotal function of HIC as a primary regulator during the initial phases of trichome formation, and its prospective utility in enhancing aphid resistance in superior cotton cultivars via selective breeding.

Identification and functional analysis of GmPsaL regulating pod color in vegetable soybean

BackgroundVegetable soybean is rich in nutrients and has a unique flavor. It is highly preferred by people because of its pharmacological activities, including those that regulate the intestines and lower blood pressure. The pod color of vegetable soybeans is an important quality that indicates their freshness and has a significant impact on their commercialization.ResultsIn this study, pod color was evaluated in 301 vegetable soybean accessions collected from various regions. Genome-wide association analysis was carried out using the Mixed linear model (MLM), a total of 18 quantitative trait loci including 117 SNPs were detected. Two significant QTLs located on chromosomes 6 (qGPCL4 /qGPCa1/qGPCb2) and 18 (qGPCL10/qGPCb3) were consistently detected across different variables. Based on gene functional annotation, 30 candidate genes were identified in these two candidate intervals. Combined with transcriptome analysis, Glyma.18g241700 has been identified as a candidate gene for regulating pod color in vegetable soybeans. Glyma.18g241700 encodes a chlorophyll photosystem I subunit XI. which localizes to the chloroplast named GmPsaL, qRT-PCR analysis showed that GmPsaL was specifically highly expressed in developing pods. Furthermore, overexpression of GmPsaL in transgenetic Arabidopsis plants produced dark green pods.ConclusionsThese findings may be useful for clarifying the genetic basis of the pod color of vegetable soybeans. The identified candidate genes may be useful for the genetic improvement of the appearance quality of vegetable soybeans.