Quantitative Trait Loci Research Articles

Yr29 combined with QYr.nwafu-4BL.3 confers durable resistance to stripe rust in wheat cultivar Jing 411.

The combination of a QTL on chromosome arm 4BL and Yr29 provides durable resistance with no significant yield penalty. Wheat stripe rust or yellow rust (YR), caused by Puccinia striiformis f. sp. tritici (Pst), causes substantial yield reductions globally, but losses can be minimized by using resistance genes. Chinese wheat cultivar Jing 411 (J411) has continued to display an acceptable level of adult-plant resistance (APR) to YR in varied field conditions since its release in the 1990s. A recombinant inbred line (RIL) population comprising 187 lines developed from a cross of J411 and Kenong 9204 (KN9204) was evaluated in multiple environments to identify genomic regions carrying genes for YR resistance. A total of five quantitative trait loci (QTL) on chromosome arm 1BL, 3BS, 4BL, 6BS, and 7BL from J411 and two QTL on 3DS and 7DL from KN9204 were detected using inclusive composite interval mapping with the wheat 660K SNP array. QYr.nwafu-1BL.5 and QYr.nwafu-4BL.3 from J411 were robust and showed similar effects in all environments. QYr.nwafu-1BL.5 was likely the pleiotropic gene of Yr29/Lr46. QYr.nwafu-4BL.3 was located within a 1.0cM interval delimited by KASP markers AX-111609222 and AX-89755491. Based on haplotype analysis, Yr29 and QYr.nwafu-4BL.3 were identified as genetic components of quantitative resistance in a number of wheat cultivars. Moreover, RILs with Yr29 and QYr.nwafu-4BL.3 individually or when combined showed higher resistance to YR in rust nurseries compared with RILs without them, and there was no negative effect of their presence on agronomic traits under rust-free conditions. These results suggest that effective polymerization strategy is important for breeding high yielding and durable resistance cultivars.

Insights into trait-association of selection signatures and adaptive eQTL in indigenous African cattle

BackgroundAfrican cattle represent a unique resource of genetic diversity in response to adaptation to numerous environmental challenges. Characterising the genetic landscape of indigenous African cattle and identifying genomic regions and genes of functional importance can contribute to targeted breeding and tackle the loss of genetic diversity. However, pinpointing the adaptive variant and determining underlying functional mechanisms of adaptation remains challenging.ResultsIn this study, we use selection signatures from whole-genome sequence data of eight indigenous African cattle breeds in combination with gene expression and quantitative trait loci (QTL) databases to characterise genomic targets of artificial selection and environmental adaptation and to identify the underlying functional candidate genes. In general, the trait-association analyses of selection signatures suggest the innate and adaptive immune system and production traits as important selection targets. For example, a large genomic region, with selection signatures identified for all breeds except N’Dama, was located on BTA27, including multiple defensin DEFB coding-genes. Out of 22 analysed tissues, genes under putative selection were significantly enriched for those overexpressed in adipose tissue, blood, lung, testis and uterus. Our results further suggest that cis-eQTL are themselves selection targets; for most tissues, we found a positive correlation between allele frequency differences and cis-eQTL effect size, suggesting that positive selection acts directly on regulatory variants.ConclusionsBy combining selection signatures with information on gene expression and QTL, we were able to reveal compelling candidate selection targets that did not stand out from selection signature results alone (e.g. GIMAP8 for tick resistance and NDUFS3 for heat adaptation). Insights from this study will help to inform breeding and maintain diversity of locally adapted, and hence important, breeds.

Plasma genome-wide mendelian randomization identifies potentially causal genes in idiopathic pulmonary fibrosis

BackgroundIdiopathic pulmonary fibrosis (IPF) is a complex lung disease with a very poor prognosis. Existing drugs for the treatment of IPF are still insufficient. Therefore, there is still a need to explore new drug targets for preventing and treating IPF.MethodsWe included quantitative trait loci (QTL) for genes, DNA methylation, and proteins in plasma, as well as the summary statistics for IPF. Genetic variants located within 500 kb of the gene and strongly associated with plasma exposure were used as instrumental variables. The causal association between plasma exposures and IPF was primarily estimated using summary-data-based Mendelian randomization (SMR) analysis. Five other MR methods and sensitivity analyses were employed to validate the SMR results. Bayesian tests for colocalization between QTL and IPF risk loci further strengthen the MR results.ResultsWe identified three genes and five DNA methylation sites causally associated with IPF by SMR analysis, validation of MR analysis, sensitivity analysis, and colocalization analysis. BTRC and LINC01252 were negatively associated with IPF risk (OR: 0.30, 95% CI: 0.17–0.54, FDRSMR = 0.029; OR: 0.85, 95% CI: 0.78–0.92, FDRSMR = 0.043), and RIPK4 was positively associated with IPF risk (OR: 2.60, 95% CI: 1.64–4.12, FDRSMR = 0.031). cg00045227 (OR8U8, OR: 1.16, 95% CI: 1.08–1.24, FDRSMR = 0.010), cg00577578 (GBAP1, OR: 1.23, 95% CI: 1.12–1.36, FDRSMR = 0.014), cg14222479 (ARPM1, OR: 3.17, 95% CI: 1.98–5.08, FDRSMR = 0.001), and cg19263494 (PMF1, OR: 1.20, 95% CI: 1.10–1.30, FDRSMR = 0.012) were positively associated with the risk of IPF, whereas cg07163735 (MAPT, OR: 0.22, 95% CI: 0.11–0.45, FDRSMR = 0.013) was negatively correlated with the risk of IPF.ConclusionsThis study demonstrated that genetically determined plasma levels of the BTRC, RIPK4, and LINC01252 genes, as well as methylation levels of cg00045227 (OR8U8), cg00577578 (GBAP1), cg07163735 (MAPT), cg14222479 (ARPM1), and cg19263494 (PMF1), have causal influences on the risk of IPF.

Importance and variability of the paternal component in sow reproductive traits.

Reproductive traits are an integral part of the goals of the breeding programs that contribute to the economic success of production. Reproductive phenotypes such as litter size, number of piglets born alive, or litter weight at birth are mainly attributed to females. Thus, the maternal components can be found by default in quantitative genetics' animal models. Still, paternal contribution to variance components should not be discarded. In this review, we indicate the importance of paternal effects in pig breeding by describing both the biology and genetics of boars' traits, the use of (non-)genetic service sire effects in quantitative genetic models for traits measured on females, and genes involved in male reproduction. We start by describing the important biological traits of boars that have the most important effect on their reproductive abilities, i.e., sexual maturity, sperm quality, and testes parameters. Then we move to the possible environmental effects that could affect those traits of boars (e.g., feed, temperature). The main part of the review in detail describes the genetics of boars' reproductive traits (i.e., heritability) and their direct effect on reproductive traits of females (i.e., genetic correlations). We then move to the use of both genetic and non-genetic service sire effects in quantitative models estimated as their percentage in the total variance of traits, which vary depending on the breed from 1 to 4.5% or from 1 to 2%, respectively. Finally, we focus on the description of candidate genes and confirmed mutations affecting male reproduction success: IGF2, Tgm8, ESR1, ZSWIM7, and ELMO1. In conclusion, the observed variance of paternal effects in female reproduction traits might come from various attributes of boars including biological and genetic aspects. Those attributes of boars should not be neglected as they contribute to the success of female reproductive traits.

Building a community-driven bioinformatics platform to facilitate Cannabis sativa multi-omics research.

The web portal can be accessed at www.icgrc.info.

ScTWAS Atlas: an integrative knowledgebase of single-cell transcriptome-wide association studies.

Single-cell transcriptome-wide association studies (scTWAS) is a new method for conducting TWAS analysis at the cellular level to identify gene-trait associations with higher precision. This approach helps overcome the challenge of interpreting cell-type heterogeneity in traditional TWAS results. As the field of scTWAS rapidly advances, there is a growing need for additional database platforms to integrate this wealth of data and knowledge effectively. To address this gap, we present scTWAS Atlas (https://ngdc.cncb.ac.cn/sctwas/), a comprehensive database of scTWAS information integrating literature curation and data analysis. The current version of scTWAS Atlas amasses 2,765,211 associations encompassing 34 traits, 30 cell types, 9 cell conditions and 16,470 genes. The database features visualization tools, including an interactive knowledge graph that integrates single-cell expression quantitative trait loci (sc-eQTL) and scTWAS associations to build a multi-omics level regulatory network at the cellular level. Additionally, scTWAS Atlas facilitates cross-cell-type analysis, highlighting cell-type-specific and shared TWAS genes. The database is designed with user-friendly interfaces and allows for easy browsing, searching, and downloading of relevant information. Overall, scTWAS Atlas is instrumental in exploring the genetic regulatory mechanisms at the cellular level and shedding light on the role of various cell types in biological processes, offering novel insights for human health research.

Phosphodiesterase 5 and its inhibitors with ischemic heart disease: a Mendelian randomization analysis and a real-world study.

Accumulating studies reported that several phosphodiesterases (PDEs) inhibitors might have cardiovascular benefits. This study aimed to explore the relationship between genetically-predicted PDEs and ischemia heart disease via drug target Mendelian randomization (MR) approach, and then examine the effect of inhibitors of identified target on the outcomes by using real-world data. In the two-sample MR study, the expression of genes encoding PDEs was used to proxy the level of PDEs and available expression quantitative trait loci (eQTLs) for each target gene were identified as the genetic instruments. The outcomes included coronary heart disease (CHD) and myocardial infarction (MI). In the real-world study, a retrospective cohort was conducted to compare the incidence of outcomes between PDE5 inhibitors and alprostadil use by linking Swedish nationwide registers. MR analyses identified two types of PDEs, PDE5 and PDE8, genetically-predicted expression in blood of the encoded genes was significantly associated with the risk of CHD (ORPDE5A=1.22,95% CI=1.06-1.40; ORPDE8A=1.26,95% CI=1.07-1.49) and MI (ORPDE5A=1.27,95% CI=1.09-1.48; ORPDE8A=1.24,95% CI=1.04-1.48). Notably, the highest expression of PDE5A was observed in artery aorta, which was also positively related to CHD (OR=1.17,95% CI=1.05-1.32) and MI (OR=1.15,95% CI=1.02-1.30). Real-world study provided supportive evidence that as compared to alprostadil use, PDE5 inhibitors use significantly reduced the incidence of CHD (adjusted HR=0.70,95% CI=0.66-0.73) and MI (adjusted HR=0.79,95% CI=0.73-0.84). This study provided observational and genetic evidence about the protective role of PDE5 inhibition against ischemic heart disease, indicating the potential of these drugs to be repurposed for ischemia heart disease prevention and treatment.

Circulating RAC1 contributed to steroid-sensitive nephrotic syndrome: Mendelian randomization, single-cell RNA-sequencing, proteomic, and experimental evidence

Objectives The small GTPase Rac1 (RAC1) has been linked to podocyte disorders and steroid-sensitive nephrotic syndrome (SSNS). The aim of this study was to explore and validate the potential causal association between circulating RAC1 and SSNS. Methods The association between circulating RAC1 and SSNS at both gene expression and proteomic levels was investigated using Mendelian randomization analysis, and further validated by single-cell RNA-sequencing, proteomic analysis, and experimental studies. The genetic instruments comprised cis-expression quantitative trait loci (cis-eQTLs) associated with RAC1 gene expression and protein QTLs correlated with plasma RAC1 protein levels. Causal associations were estimated utilizing the inverse variance weighted and MR-PRESSO methods. Validation of RAC1 expression was conducted through single-cell RNA-sequencing of peripheral blood mononuclear cells from patients with SSNS and healthy controls. Proteomic analysis was performed among patients with minimal change nephrotic syndrome. Experimental validation was conducted using a puromycin aminonucleoside (PAN)-induced nephrosis model. Results Increased expression of RAC1 was associated with a higher risk of SSNS (gene expression level: odds ratio [OR], 1.53; 95% confidence interval [CI], 1.02–2.28; protein level: OR, 1.82; 95% CI, 1.05–3.17). The results of MR-PRESSO were consistent (gene expression level: OR, 1.49; 95% CI, 1.17–1.92; protein level: OR, 1.81; 95% CI, 1.16–2.85). Single-cell RNA sequencing and proteomic analysis confirmed elevated RAC1 expression in patients with SSNS compared to healthy controls. Experimental data further supported increased RAC1 expression in PAN-induced nephropathy. Conclusions Increased expression of RAC1 might be causally associated with SSNS, suggesting that targeting RAC1 might represent a potential therapeutic strategy for SSNS.

Application of large-scale and multicohort plasma proteomics data to discover novel causal proteins in gastric cancer

PurposesGastric cancer (GC) is one of the most common malignant tumors threatening human beings and has a poor prognosis. Therefore, exploring unveiled biomarkers or therapeutic targets for the diagnosis and treatment of GC is crucial.MethodsA total of 5772 protein quantitative trait loci (pQTL) were aggregated from four latest large-scale proteomics cohorts. Two-sample Mendelian randomization (two-sample MR) was utilized to identify the causal effect of blood plasma proteins on GC. Heterogeneity, pleiotropy, and directionality analyses were employed to evaluate proteins identified via two-sample MR. The robustness of results was further validated via colocalization. The drug targets of proteins were evaluated to reveal the compounds that can interfere with these proteins.ResultsTen proteins with potential causations in relation to GC were identified: LY6D, SLURP1, MLN, PSCA, THSD1, CFTR, PPM1B, KDM3A, TSC1, and HCG22. Among these proteins, LY6D, SLURP1, and THSD1 were considered as the most reliable biomarkers of GC due to their significant H4 posterior probabilities in colocalization analysis and absence of pleiotropy. Compound 35, nitrosamide, and 0175029-0000 were potential drugs or small molecules targeting LY6D, SLURP1, and THSD1, respectively.ConclusionThis study identified several plasma proteins as potential biomarkers of GC and provided data support and new insights into the early diagnosis, intervention, and therapeutic targets of GC.

Genetic architecture of Cercospora leaf spot response in table beet with implications for other Beta vulgaris crop types

AbstractTable beet (Beta vulgaris subsp. vulgaris) production is threatened by the fungal disease Cercospora leaf spot (CLS). Infections are common across table beet's closest relatives, including Swiss chard, sugar beet, and fodder beet (all B. v. subsp. vulgaris). This study was conducted to characterize the genetic architecture underlying CLS response in table beet. A secondary objective was to test whether CLS‐associated loci in table beet perform similarly across B. vulgaris crops. A diversity panel comprised of 168 table beet accessions and with an additional 70 accessions from all close relatives of table beet was screened for CLS response in replicated and inoculated field trials. Results from a genome‐wide association study of additive effects revealed seven quantitative trait loci mapped to chromosomes 1, 3, 7, and 9 to explain 30% of the phenotypic variation for CLS response in table beet. When the performance of these loci was compared between a table beet background and a background of Swiss chard, sugar beet, and fodder beet, two loci exhibited significantly different responses. Among the B. vulgaris crops, these loci may be unique to table beet germplasm and could be useful for the improvement of CLS resistance in other crop types. For the improvement of CLS resistance in table beet, this study identified the cultivar Winter Keeper as a potentially valuable source of resistance. The architecture of CLS response points to recurrent selection and backcross methods as effective strategies for the improvement of CLS resistance in table beet.

Mapping of quantitative trait loci (QTL) in Brassica napus L. for tolerance to water stress.

Brassica napus L. plants are sensitive to water stress conditions throughout their life cycle from seed germination to seed setting. This study aims at identifying quantitative trait loci (QTL) linked to B. napus tolerance to water stress mimicked by applications of 10% polyethylene glycol-6000 (PEG-6000). Two doubled haploid populations, each consisting of 150 genotypes, were used for this research. Plants at the two true leaf stage of development were grown in the absence (control) or presence (stress) of PEG-6000 under controlled environmental conditions for 48h, and the drought stress index was calculated for each genotype. All genotypes, along with their parents, were genotyped using the Brassica Infinium 90K SNP BeadChip Array. Inclusive composite interval mapping was used to identify QTL. Six QTL and 12 putative QTL associated with water stress tolerance were identified across six chromosomes (A2, A3, A4, A9, C3, and C7). Collectively, 2154 candidate genes for water stress tolerance were identified for all the identified QTL. Among them, 213 genes were identified as being directly associated with water stress (imposed by PEG-6000) tolerance based on nine functional annotations. These results can be incorporated into future breeding initiatives to select plant material with the ability to cope effectively with water stress.

Combined BSA-Seq and RNA-Seq Analysis to Identify Candidate Genes Associated with Aluminum Toxicity in Rapeseed (Brassica napus L.).

Exchangeable aluminum (Al) ions released from acidic soils with pH < 5.5 inhibit root elongation of crops, ultimately leading to yield reduced. It is necessary to identify the quantitative trait locus (QTLs) and candidate genes that confer toxicity resistance to understand the mechanism and improve tolerance of rapeseed. In this study, an F2 segregating population was derived from a cross between Al-tolerance inbred line FDH188 (R178) and -sensitive inbred line FDH152 (S169), and the F2:3 were used as materials to map QTLs associated with the relative elongation of taproot (RET) under Al toxicity stress. Based on bulked segregant analysis sequencing (BSA-seq), three QTLs (qAT-A07-1, qAT-A07-2, and qAT-A09-1) were detected as significantly associated with RET, and 656 candidate genes were screened. By combined BSA and RNA-seq analysis, 55 candidate genes showed differentially expressed, including genes encoding ABC transporter G (ABCG), zinc finger protein, NAC, ethylene-responsive transcription factor (ERF), etc. These genes were probably positive factors in coping with Al toxicity stress in rapeseed. This study provides new insight into exploring the QTLs and candidate genes' response to Al toxicity stress by combined BSA-seq and RNA-seq and is helpful to further research on the mechanism of Al resistance in rapeseed.

A major falling number locus on chromosome 4B governs resistance to pre-harvest sprouting in bread wheat line Soru#1

Pre-harvest sprouting (PHS) is a serious threat to wheat quality and occurs when maturing seeds on plants encounter substantial rain before harvest. In the present study, the genetics of PHS resistance were studied using a population of 131 recombinant inbred lines (RILs) from a cross between Soru#1 and Naxos. The population was genotyped with the Illumina 90 K and Axiom 35 K wheat SNP arrays and tested in field trials across two locations in Norway and one in China. Seed dormancy as a measure of sprouting damage was evaluated using germination index (GI) and falling number (FN). Days to heading, days to maturity, and plant height were also recorded to evaluate their potential impact on PHS. Thirteen PHS-related quantitative trait loci (QTL) were detected. The most consistent QTL for FN, contributed by Soru#1, on the long arm of chromosome 4B explained 10.0–19.2% of the phenotypic variation across trials. Other important PHS resistance QTL from Soru#1 detected on chromosome arms 2AL, 2BL, and 4BS, affected both GI and FN. Naxos carried favorable QTL alleles for PHS resistance on chromosome arm 4AS and the Phs1 allele on 4AL. The reduced height Rht-D1 and vernalization Vrn-A1 alleles were the major determinants of plant height and earliness; however, these traits had minimal impact on the genetic control of PHS resistance in this population. Thus, both parents contributed valuable alleles for improving PHS resistance in breeding programs.

Evaluating the causal effect of circulating proteome on the glycemic traits: Evidence from Mendelian randomization.

Exploring the mechanisms underlying abnormal glycemic traits is important for deciphering type 2 diabetes and characterizing novel drug targets. This study aimed to decipher the causal associations of circulating proteins with fasting glucose (FG), 2-h glucose after an oral glucose challenge (2hGlu), fasting insulin (FI), and glycated hemoglobin (HbA1c) using large-scale proteome-wide Mendelian randomization (MR) analyses. Genetic data on plasma proteomes were obtained from ten proteomic genome-wide association studies (GWAS). Both cis- and cis+trans-protein quantitative trait loci (pQTLs) MR analyses were conducted. Bayesian colocalization, Steiger filtering analysis, assessment of protein-altering variants, and mapping expression quantitative trait loci to protein quantitative trait loci were performed to investigate the reliability of the MR findings. Protein-protein interaction, pathway enrichment analysis, and evaluation of drug targets were performed. Thirty-three proteins were identified with causal effects on FG, FI, or HbA1c but not 2hGlu in the cis-pQTLs analysis, and 93 proteins had causal effects on glycemic traits in the cis+trans-pQTLs analysis. Most proteins were either considered druggable or drug targets. In conclusion, many novel circulating protein biomarkers were identified to be causally associated with glycemic traits. These biomarkers enhance the understanding of molecular etiology and provide insights into the screening, monitoring, and treatment of diabetes.

Pangenome Data Analysis Reveals Characteristics of Resistance Gene Analogs Associated with Sclerotinia sclerotiorum Resistance in Sunflower

The sunflower, an important oilseed crop and food source across the world, is susceptible to several pathogens, which cause severe losses in sunflower production. The utilization of genetic resistance is the most economical, effective measure to prevent infectious diseases. Based on the sunflower pangenome, in this study, we explored the variability of resistance gene analogs (RGAs) within the species. According to a comparative analysis of RGA candidates in the sunflower pangenome using the RGAugury pipeline, a total of 1344 RGAs were identified, comprising 1107 conserved, 199 varied, and 38 rare RGAs. We also identified RGAs associated with resistance against Sclerotinia sclerotiorum (S. sclerotiorum) in sunflower at the quantitative trait locus (QTL). A total of 61 RGAs were found to be located at four quantitative trait loci (QTLs). Through a detailed expression analysis of RGAs in one susceptible and two tolerant sunflower inbred lines (ILs) across various time points post inoculation, we discovered that 348 RGAs exhibited differential expression in response to Sclerotinia head rot (SHR), with 17 of these differentially expressed RGAs being situated within the QTL regions. In addition, 15 RGA candidates had gene introgression. Our data provide a better understanding of RGAs, which facilitate genomics-based improvements in disease resistance in sunflower.

Population-wide DNA methylation polymorphisms at single-nucleotide resolution in 207 cotton accessions reveal epigenomic contributions to complex traits.

DNA methylation plays multiple regulatory roles in crop development. However, the relationships of methylation polymorphisms with genetic polymorphisms, gene expression, and phenotypic variation in natural crop populations remain largely unknown. Here, we surveyed high-quality methylomes, transcriptomes, and genomes obtained from the 20-days-post-anthesis (DPA) cotton fibers of 207 accessions and extended the classical framework of population genetics to epigenetics. Over 287 million single methylation polymorphisms (SMPs) were identified, 100 times more than the number of single nucleotide polymorphisms (SNPs). These SMPs were significantly enriched in intragenic regions while depleted in transposable elements. Association analysis further identified a total of 5,426,782 cis-methylation quantitative trait loci (cis-meQTLs), 5078 cis-expression quantitative trait methylation (cis-eQTMs), and 9157 expression quantitative trait loci (eQTLs). Notably, 36.39% of cis-eQTM genes were not associated with genetic variation, indicating that a large number of SMPs associated with gene expression variation are independent of SNPs. In addition, out of the 1715 epigenetic loci associated with yield and fiber quality traits, only 36 (2.10%) were shared with genome-wide association study (GWAS) loci. The construction of multi-omics regulatory networks revealed 43 cis-eQTM genes potentially involved in fiber development, which cannot be identified by GWAS alone. Among these genes, the role of one encoding CBL-interacting protein kinase 10 in fiber length regulation was successfully validated through gene editing. Taken together, our findings prove that DNA methylation data can serve as an additional resource for breeding purposes and can offer opportunities to enhance and expedite the crop improvement process.

EQTL in diseased colon tissue identifies novel target genes associated with IBD.

Genome-wide association studies (GWAS) have identified over 300 loci associated with the inflammatory bowel diseases (IBD), but putative causal genes for most are unknown. We conducted the largest disease-focused expression quantitative trait loci (eQTL) analysis using colon tissue from 252 IBD patients to determine genetic effects on gene expression and potential contribution to IBD. Combined with two non-IBD colon eQTL studies, we identified 194 potential target genes for 108 GWAS loci. eQTL in IBD tissue were enriched for IBD GWAS loci colocalizations, provided novel evidence for IBD-associated genes such as ABO and TNFRSF14 , and identified additional target genes compared to non-IBD tissue eQTL. IBD-associated eQTL unique to diseased tissue had distinct regulatory and functional characteristics with increased effect sizes. Together, these highlight the importance of eQTL studies in diseased tissue for understanding functional consequences of genetic variants, and elucidating molecular mechanisms and regulation of key genes involved in IBD.

A regulatory variant rs9379874 in T1D risk region 6p22.2 affects BTN3A1 expression regulating T cell function.

Genome-wide association studies (GWAS) have identified that 6p22.2 region is associated with type 1 diabetes (T1D) risk in the Chinese Han population. This study aims to reveal associations between this risk region and T1D subgroups and related clinical features, and further identify causal variant(s) and target gene(s) in this region. 2608 T1D and 4814 healthy controls were recruited from East, Central, and South China. Baseline data and genotyping for rs4320356 were collected. The most likely causal variant and gene were identified by bioinformatics analysis, dual-luciferase reporter assays, expression quantitative trait loci (eQTL), and functional annotation of the non-coding region within the 6p22.2 region. The leading variant rs4320356 in the 6p22.2 region was associated with T1D risk in the Chinese and Europeans. However, this variant was not significantly associated with islet function or autoimmunity. In silico analysis suggested rs9379874 was the most potential causal variant for T1D risk among thymus, spleen, and T cells, overlapping with the enhancer-related histone mark in multiple T cell subsets. Dual luciferase reporter assay and eQTL showed that the T allele of rs9379874 increased BTN3A1 expression by binding to FOXA1. Public single-cell RNA sequencing analysis indicated that BTN3A1 was related to T-cell activation, ATP metabolism, and cytokine metabolism pathways, which might contribute to T1D development. This study indicates that a functional variant rs9379874 regulates BTN3A1 expression, expanding the genomic landscape of T1D risk and offering a potential target for developing novel therapies.

Enhancing rice aroma through innovative approaches

Aromatic rice is used extensively in many different cuisines around the world for its wonderful aroma and cooking qualities. Aromatic rice varieties such as Basmati and non-Basmati fragrant rice have gained popularity in both domestic and foreign markets, despite their origins being predominantly in Southeast Asia and the Indian subcontinent. The primary gene responsible for rice aroma is the fgr/Badh2/Os2-AP, situated on chromosome 8 and encodes betaine aldehyde dehydrogenase 2 (Badh2). Key aroma compounds are attributed to over 500 volatiles. The primary aromatic molecule in rice, 2-acetyl-1-pyrroline (2-AP), accumulates as a result of mutations in this gene and gives rice its distinctive scent. Aroma is not decided by single compound rather it is decided by volatile profile and also by environmental factors. The identification of Quantitative Trait Loci (QTLs) linked to fragrance features on different chromosomes has improved our comprehension of the genetic processes behind rice scent. Advances in genetic engineering, particularly CRISPR/Cas9 and TALEN have facilitated the manipulation of the Badh2 gene, enhancing aroma profiles in rice. Additionally, gene silencing and introgression techniques have also proven in increasing 2-AP content. The review explores the biochemical properties and advancement of aromatic rice, emphasizing its complex inheritance patterns and potential for breeding improvement.

Genetic variations in NER pathway gene polymorphisms and Wilms tumor risk: A six-center case-control study in East China.

The nucleotide excision repair (NER) system is one of the main ways to protect organisms from DNA damage caused by endogenous and exogenous carcinogens. NER deficiency increases genome mutations, chromosomal aberrations, and cancer viability. However, the genetic association between Wilms tumor and NER pathway gene polymorphisms needs to be further validated. We assessed the associations between 19 NER gene polymorphisms and Wilms tumor susceptibility in 416 cases and 936 controls from East China via the TaqMan method. We found that xeroderma pigmentosum group D (XPD) rs238406 and rs13181 significantly decreased the risk of Wilms tumor [adjusted odds ratio (OR) = 0.59, 95% confidence interval (CI) = 0.46-0.75, p <.0001; adjusted OR = 0.63, 95% CI = 0.44-0.89, p = .009, respectively]. Furthermore, the rs751402 and rs2296147 polymorphisms in the xeroderma pigmentosum group G (XPG) gene were significantly correlated with an increased risk for Wilms tumor (adjusted OR = 1.47, 95% CI = 1.03-2.09, p = .034; adjusted OR = 2.14, 95% CI = 1.29-3.56, p = .003, respectively). Expression quantitative trait loci (eQTL) analysis revealed that these four polymorphisms may affect the expression of genes that are adjacent to XPD and XPG. Our study provides evidence that XPD and XPG gene polymorphisms are associated with Wilms tumor risk. Nonetheless, these findings should be confirmed in a larger sample size.