Quantitative Trait Loci Analysis Research Articles

QTL analysis of divergent floral morphology traits between Gilia yorkii and G. capitata.

Speciation is a complex process typically accompanied by significant genetic and morphological differences between sister populations. In plants, divergent floral morphologies and pollinator differences can result in reproductive isolation between populations. Here, we explore floral trait differences between two recently diverged species, Gilia yorkii and G. capitata. The distributions of floral traits in parental, F1, and F2 populations are compared, and groups of correlated traits are identified. We describe the genetic architecture of floral traits through a quantitative trait locus (QTL) analysis using an F2 population of 187 individuals. While all identified QTLs were of moderate (10-25%) effect, interestingly, most QTL intervals were non-overlapping, suggesting that, in general, traits do not share a common genetic basis. Our results provide a framework for future identification of genes involved in the evolution of floral morphology.

QTL mapping reveals malt barley quality improvement in two dryland environments associated with extended grain fill and seminal root traits

AbstractTo achieve malt grade and receive full price, barley (Hordeum vulgare L.) crops must meet standards for certain quality traits including percent plump and protein. Terminal drought stress reduces quality and is projected to worsen in barley cultivation areas, underscoring the need for varieties that maintain good malt production with unreliable precipitation. The stay‐green trait extends the grain fill phase between heading and maturity and has been linked to stable quality under dry conditions. However, this relationship can be inconsistent and is not well understood. To effectively leverage a longer grain fill phenotype for drought adaptation, a better grasp of its genetics and environmental interaction is needed. Stay‐green root system differences have been observed and could be at play. We performed correlation and quantitative trait locus (QTL) analysis on grain fill duration, grain quality, and seminal root traits using a recombinant inbred line (RIL) population segregating for stay‐green. Agronomic data were collected in four field trials at two distinct semiarid locations, and roots were measured in a greenhouse assay. Earlier heading and later maturity led to improved quality in both locations and more consistent quality between locations. Earlier heading had a greater influence on quality in the drier environment, while later maturity was more impactful in the less dry environment. We observed co‐locations of seminal root trait QTLs with grain fill duration and grain quality. These QTLs lay the groundwork for further investigation into root phenotypes associated with stay‐green and the deployment of these traits in breeding for drought adaptation.

Genotyping-by-sequencing-based high-resolution mapping reveals a single candidate gene for the grapevine veraison locus Ver1.

Veraison marks the transition from berry growth to berry ripening and is a crucial phenological stage in grapevine (Vitis vinifera): the berries become soft and begin to accumulate sugars, aromatic substances, and, in red cultivars, anthocyanins for pigmentation, while the organic acid levels begin to decrease. These changes determine the potential quality of wine. However, rising global temperatures lead to earlier flowering and ripening, which strongly influence wine quality. Here, we combined genotyping-by-sequencing with a bioinformatics pipeline on ∼150 F1 genotypes derived from a cross between the early ripening variety 'Calardis Musqué' and the late-ripening variety 'Villard Blanc'. Starting from 20,410 haplotype-based markers, we generated a high-density genetic map and performed a quantitative trait locus analysis based on phenotypic datasets evaluated over 20 years. Through locus-specific-marker-enrichment and recombinant screening of ∼1000 additional genotypes, we refined the originally postulated 5 Mb veraison locus, Ver1, on chromosome 16 to only 112 kb, allowing us to pinpoint the ethylene response factor (ERF) VviERF027 (VCost.v3 gene ID: Vitvi16g00942, CRIBIv1 gene ID: VIT_16s0100g00400) as veraison candidate gene. Furthermore, the early veraison allele could be traced back to a clonal 'Pinot' variant first mentioned in the 17th century. 'Pinot Precoce Noir' passed this allele over 'Madeleine Royale' to the maternal grandparent 'Bacchus Weiss' and, ultimately, to the maternal parent 'Calardis Musqué'. Our findings are crucial for ripening time control, thereby improving wine quality, and for breeding grapevines adjusted to climate change scenarios that have a major impact on agro-ecosystems in altering crop plant phenology.

Different control of resistance to two Colletotrichum orbiculare pathogenic races 0 and 1 in cucumber (Cucumis sativus L.).

Quantitative trait locus analysis identified independent novel loci in cucumbers responsible for resistance to races 0 and 1 of the anthracnose fungal pathogen Colletotrichum orbiculare. Cucumbers have been reported to be vulnerable to Colletotrichum orbiculare, causing anthracnose disease with significant yield loss under favorable conditions. The deployment of a single recessive Cssgr gene in cucumber breeding for anthracnose resistance was effective until a recent report on high-virulent strains infecting cucumbers in Japan conquering the resistance. QTL mapping was conducted to identify the resistance loci in the cucumber accession Ban Kyuri (G100) against C. orbiculare strains 104-T and CcM-1 of pathogenic races 0 and 1, respectively. A single dominant locus An5 was detected in the disease resistance hotspot on chromosome 5 for resistance to 104-T. Resistance to CcM-1 was governed by three loci with additive effects located on chromosomes 2 (An2) and 1 (An1.1 and An1.2). Molecular markers were developed based on variant calling between the corresponding QTL regions in the de novo assembly of the G100 genome and the publicly available cucumber genomes. Multiple backcrossed populations were deployed to fine-map An5 locus and narrow the region to approximately 222 kbp. Accumulation of An2 and An1.1 alleles displayed an adequate resistance to CcM-1 strain. This study provides functional molecular markers for pyramiding resistance loci that confer sufficient resistance against anthracnose in cucumbers.

Sex affects transcriptional associations with schizophrenia across the dorsolateral prefrontal cortex, hippocampus, and caudate nucleus

Schizophrenia is a complex neuropsychiatric disorder with sexually dimorphic features, including differential symptomatology, drug responsiveness, and male incidence rate. Prior large-scale transcriptome analyses for sex differences in schizophrenia have focused on the prefrontal cortex. Analyzing BrainSeq Consortium data (caudate nucleus: n = 399, dorsolateral prefrontal cortex: n = 377, and hippocampus: n = 394), we identified 831 unique genes that exhibit sex differences across brain regions, enriched for immune-related pathways. We observed X-chromosome dosage reduction in the hippocampus of male individuals with schizophrenia. Our sex interaction model revealed 148 junctions dysregulated in a sex-specific manner in schizophrenia. Sex-specific schizophrenia analysis identified dozens of differentially expressed genes, notably enriched in immune-related pathways. Finally, our sex-interacting expression quantitative trait loci analysis revealed 704 unique genes, nine associated with schizophrenia risk. These findings emphasize the importance of sex-informed analysis of sexually dimorphic traits, inform personalized therapeutic strategies in schizophrenia, and highlight the need for increased female samples for schizophrenia analyses.

Unraveling the genetic basis of superior traits in Gossypium barbadense: From phenotype to genotype

G. barbadense is renowned for its high-quality fiber and is highly regarded as a natural material in the textile industry. However, research on cotton has mainly focused on G. hirsutum, and progress in sea island cotton has been relatively slow. There was limited understanding of the genetic loci and transcriptional regulatory mechanisms of important traits, and the genetic basis for the development of superior traits remains unclear. In this study, a recombinant inbred line (RIL) population was constructed using two sea island cotton parents from different cotton regions. The phenotypic characteristics of the two parents and the RIL population, as well as the phenotypic correlations, heritability, and genetic models of the RIL population, were comprehensively analyzed. The RIL population was genotyped using whole-genome resequencing technology, and a high-density intraspecific linkage map was constructed, consisting of 5295 bin markers and a total genetic map distance of 2721.79 centimorgans (cM). Phenotypic data collected from five different environments were used to detect 169 quantitative trait loci (QTLs) using the composite interval mapping method. Among these QTLs, 30 were related to agronomic traits, 61 were related to yield traits, and 78 were related to fiber quality traits. Additionally, 17 QTL clusters were detected, and the additive effects of these clusters explained the correlation between different phenotypic traits. Candidate genes for stable QTLs related to agronomic and yield traits were identified through variant annotation and functional prediction. Two bin markers associated with lint percentage (LP) were validated as potential breeding markers. Furthermore, using RNA-seq data of cotton fiber from the RIL population parents, the dynamic changes in gene expression during different developmental stages of cotton fiber were revealed, and important differentially expressed genes in the secondary cell wall development and metabolism network of fibers were identified. Importantly, through the combined analysis of fiber trait QTLs and transcriptomes, eight candidate genes involved in regulating fiber quality traits were predicted, and the genetic basis of the excellent allele site qFL_D04_1 in the breeding history of Chinese sea island cotton was elucidated. In summary, this study provides new genetic resources and potential breeding markers for cotton variety improvement, valuable theoretical information for understanding the genetic basis of important traits in sea island cotton, and effectively promotes the development of cotton biotechnology breeding.

African ancestry-derived APOL1 risk genotypes show proximal epigenetic associations

Apolipoprotein L1 (APOL1) coding variants, termed G1 and G2, are established genetic risk factors for a growing spectrum of diseases, including kidney disease, in individuals of African ancestry. Evidence suggests that the risk variants, which show a recessive mode of inheritance, lead to toxic gain-of-function changes of the APOL1 protein. Disease occurrence and presentation vary, likely due to modifiers or second hits. To understand the role of the epigenetic landscape in relation to APOL1 risk variants, we performed methylation quantitative trait locus (meQTL) analysis to identify differentially methylated CpGs influenced by APOL1 risk variants in 611 African American individuals. We identified five CpGs that were significantly associated with APOL1 risk alleles in discovery and replication studies, and one CpG-APOL1 association was independent of other genomic variants. Our study highlights proximal DNA methylation alterations that may help explain the variable disease risk and clinical manifestation of APOL1 variants.

Novel putative causal mutations associated with fat traits in Nellore cattle uncovered by eQTLs located in open chromatin regions

Intramuscular fat (IMF) and backfat thickness (BFT) are critical economic traits impacting meat quality. However, the genetic variants controlling these traits need to be better understood. To advance knowledge in this area, we integrated RNA-seq and single nucleotide polymorphisms (SNPs) identified in genomic and transcriptomic data to generate a linkage disequilibrium filtered panel of 553,581 variants. Expression quantitative trait loci (eQTL) analysis revealed 36,916 cis-eQTLs and 14,408 trans-eQTLs. Association analysis resulted in three eQTLs associated with BFT and 24 with IMF. Functional enrichment analysis of genes regulated by these 27 eQTLs revealed noteworthy pathways that can play a fundamental role in lipid metabolism and fat deposition, such as immune response, cytoskeleton remodeling, iron transport, and phospholipid metabolism. We next used ATAC-Seq assay to identify and overlap eQTL and open chromatin regions. Six eQTLs were in regulatory regions, four in predicted insulators and possible CCCTC-binding factor DNA binding sites, one in an active enhancer region, and the last in a low signal region. Our results provided novel insights into the transcriptional regulation of IMF and BFT, unraveling putative regulatory variants.

Collaborative Cross mice have diverse phenotypic responses to infection with Methicillin-resistant Staphylococcus aureus USA300.

Staphylococcus aureus (S. aureus) is an opportunistic pathogen causing diseases ranging from mild skin infections to life threatening conditions, including endocarditis, pneumonia, and sepsis. To identify host genes modulating this host-pathogen interaction, we infected 25 Collaborative Cross (CC) mouse strains with methicillin-resistant S. aureus (MRSA) and monitored disease progression for seven days using a surgically implanted telemetry system. CC strains varied widely in their response to intravenous MRSA infection. We identified eight 'susceptible' CC strains with high bacterial load, tissue damage, and reduced survival. Among the surviving strains, six with minimal colonization were classified as 'resistant', while the remaining six tolerated higher organ colonization ('tolerant'). The kidney was the most heavily colonized organ, but liver, spleen and lung colonization were better correlated with reduced survival. Resistant strains had higher pre-infection circulating neutrophils and lower post-infection tissue damage compared to susceptible and tolerant strains. We identified four CC strains with sexual dimorphism: all females survived the study period while all males met our euthanasia criteria earlier. In these CC strains, males had more baseline circulating monocytes and red blood cells. We identified several CC strains that may be useful as new models for endocarditis, myocarditis, pneumonia, and resistance to MRSA infection. Quantitative Trait Locus (QTL) analysis identified two significant loci, on Chromosomes 18 and 3, involved in early susceptibility and late survival after infection. We prioritized Npc1 and Ifi44l genes as the strongest candidates influencing survival using variant analysis and mRNA expression data from kidneys within these intervals.

Genome-wide QTL and eQTL mapping reveal genes associated with growth rate trait of the Pacific white shrimp (Litopenaeus vannamei)

BackgroundGrowth rate is a crucial economic trait for farmed animals, but the genetic regulation of this trait is largely unknown in non-model organisms such as shrimp.ResultsIn this study, we performed genome-wide phenotypic quantitative trait loci (QTL) and expression quantitative trait loci (eQTL) mapping analyses to identify genes affecting the growth rate of Pacific white shrimp (Litopenaeus vannamei), which is the most commercially-farmed crustacean worldwide. We used RNA-sequencing of 268 individuals in a mapping population, and subsequently validated our findings through gene silencing and shrimp growth experiments. We constructed a high-density genetic linkage map comprising 5533 markers spanning 44 linkage groups, with a total distance of 6205.75 cM and an average marker interval of 1.12 cM. Our analyses identified 11 QTLs significantly correlated with growth rate, and 117,525 eQTLs. By integrating QTL and eQTL data, we identified a gene (metalloreductase STEAP4) highly associated with shrimp growth rate. RNA interference (RNAi) analysis and growth experiments confirmed that STEAP4 was significantly correlated with growth rate in L. vannamei.ConclusionsOur results indicate that the comprehensive analysis of QTL and eQTL can effectively identify genes involved in complex animal traits. This is important for marker-assisted selection (MAS) of animals. Our work contributes to the development of shrimp breeding and available genetic resources.

Multi-ancestry genome-wide association study of kidney cancer identifies 63 susceptibility regions.

Here, in a multi-ancestry genome-wide association study meta-analysis of kidney cancer (29,020 cases and 835,670 controls), we identified 63 susceptibility regions (50 novel) containing 108 independent risk loci. In analyses stratified by subtype, 52 regions (78 loci) were associated with clear cell renal cell carcinoma (RCC) and 6 regions (7 loci) with papillary RCC. Notably, we report a variant common in African ancestry individuals ( rs7629500 ) in the 3' untranslated region of VHL, nearly tripling clear cell RCC risk (odds ratio 2.72, 95% confidence interval 2.23-3.30). In cis-expression quantitative trait locus analyses, 48 variants from 34 regions point toward 83 candidate genes. Enrichment of hypoxia-inducible factor-binding sites underscores the importance of hypoxia-related mechanisms in kidney cancer. Our results advance understanding of the genetic architecture of kidney cancer, provide clues for functional investigation and enable generation of a validated polygenic risk score with an estimated area under the curve of 0.65 (0.74 including risk factors) among European ancestry individuals.

An integrated omics approach highlights how epigenetic events can explain and predict response to neoadjuvant chemotherapy and bevacizumab in breast cancer.

Treatment with the anti-angiogenic drug bevacizumab in addition to chemotherapy has shown efficacy for breast cancer in some clinical trials, but better biomarkers are needed to optimally select patients for treatment. Here, we present an omics approach where DNA methylation profiles are integrated with gene expression and results from proteomic data in breast cancer patients to predict response to therapy and pinpoint response-related epigenetic events. Fresh-frozen tumor biopsies taken before, during, and after treatment from human epidermal growth factor receptor 2 negative non-metastatic patients receiving neoadjuvant chemotherapy with or without bevacizumab were subjected to molecular profiling. Here, we report that DNA methylation at enhancer CpGs related to cell cycle regulation can predict response to chemotherapy and bevacizumab for the estrogen receptor positive subset of patients (AUC = 0.874), and we validated this observation in an independent patient cohort with a similar treatment regimen (AUC = 0.762). Combining the DNA methylation scores with the scores from a previously published protein signature resulted in a slight increase in the prediction performance (AUC = 0.784). We also show that tumors receiving the combination treatment underwent more extensive epigenetic alterations. Finally, we performed an integrative expression-methylation quantitative trait loci analysis on alterations in DNA methylation and gene expression levels, showing that the epigenetic alterations that occur during treatment are different between responders and non-responders and that these differences may be explained by the proliferation-epithelial-to-mesenchymal transition axis through the activity of grainyhead like transcription factor 2. Using tumor purity computed from copy number data, we developed a method for estimating cancer cell-specific methylation to confirm that the association to response reflects DNA methylation in cancer cells. Taken together, these results support the potential for clinical benefit of the addition of bevacizumab to chemotherapy when administered to the correct patients.

Analysis of blood methylation quantitative trait loci in East Asians reveals ancestry-specific impacts on complex traits.

Methylation quantitative trait loci (mQTLs) are essential for understanding the role of DNA methylation changes in genetic predisposition, yet they have not been fully characterized in East Asians (EAs). Here we identified mQTLs in whole blood from 3,523 Chinese individuals and replicated them in additional 1,858 Chinese individuals from two cohorts. Over 9% of mQTLs displayed specificity to EAs, facilitating the fine-mapping of EA-specific genetic associations, as shown for variants associated with height. Trans-mQTL hotspots revealed biological pathways contributing to EA-specific genetic associations, including an ERG-mediated 233 trans-mCpG network, implicated in hematopoietic cell differentiation, which likely reflects binding efficiency modulation of the ERG protein complex. More than 90% of mQTLs were shared between different blood cell lineages, with a smaller fraction of lineage-specific mQTLs displaying preferential hypomethylation in the respective lineages. Our study provides new insights into the mQTL landscape across genetic ancestries and their downstream effects on cellular processes and diseases/traits.

Construction of high-density genetic map based on SLAF-seq and QTL analysis of major traits in sweetpotato [Ipomoea batatas (L.) Lam.]

Sweetpotato, Ipomoea batatas (L.) Lam., is an important worldwide crop used as feed, food, and fuel. However, its polyploidy, high heterozygosity and self-incompatibility makes it difficult to study its genetics and genomics. Longest vine length (LVL), yield per plant (YPP), dry matter content (DMC), starch content (SC), soluble sugar content (SSC), and carotenoid content (CC) are some of the major agronomic traits being used to evaluate sweetpotato. However limited research has actually examined how these traits are inherited. Therefore, after selecting 212 F1 from a Xin24 × Yushu10 crossing as the mapping population, this study applied specific-locus amplified fragment sequencing (SLAF-seq), at an average sequencing depth of 26.73 × (parents) and 52.25 × (progeny), to detect single nucleotide polymorphisms (SNPs). This approach generated an integrated genetic map of length 2441.56 cM and a mean distance of 0.51 cM between adjacent markers, encompassing 15 linkage groups (LGs). Based on the linkage map, 26 quantitative trait loci (QTLs), comprising six QTLs for LVL, six QTLs for YPP, ten QTLs for DMC, one QTL for SC, one QTL for SSC, and two QTLs for CC, were identified. Each of these QTLs explained 6.3–10% of the phenotypic variation. It is expected that the findings will be of benefit for marker-assisted breeding and gene cloning of sweetpotato.

Differential QTL underlie wheat grain physical quality when measured using image‐based versus traditional laboratory methods

AbstractBACKGROUNDThe marketing value of wheat (Triticum aestivum L.) is determined, in parts, by the grain's physical characteristics as they directly or indirectly influence milling performance and baking quality. These characteristics have been measured manually in the past, but now, digital image analysis (DIA) is increasingly being used to replace the slow phenotyping system. Here, we asked whether this could lead to the identification of the same or different genes, when compared to the traditional phenotyping methods.RESULTSWe measured grain physical quality on 142 wheat doubled haploids grown in the field over two years and using quantitative trait locus (QTL) mapping approach we found that (1) for wheat grain weight, the use of DIA provided genetic information that mostly conformed to those obtained using the traditional phenotyping methods, with heritability estimates that were identical across both methods. Majority of the QTL detected were consistent between the traditional versus digital phenotyping methods; (2) a more complex architecture, however, arose from QTL analyses of hectolitre weight (HLW) and percentage of shrivelled grains (SCR). The estimates for heritability varied by as much as 0.24 across methods and more significantly, many of the detected QTL for both traits were method‐specific; (3) though method‐specific, identified QTL mapped to genomic regions known to harbour genes for grain physical traits.CONCLUSIONSTGW is robust to phenotyping method, but a different genetic system underlie HLW and SCR, when these were measured using traditional versus digital image analysis. For these traits, heritability estimates were larger when phenotyped using traditional methods relative to digital image analysis, suggesting that further refinements are required to better correlate digital image analysis with the traditional phenotyping methods.This article is protected by copyright. All rights reserved.

Genetic insights into superior grain number traits: a QTL analysis of wheat-Agropyron cristatum derivative pubing3228

BackgroundAgropyron cristatum (L.) is a valuable genetic resource for expanding the genetic diversity of common wheat. Pubing3228, a novel wheat-A. cristatum hybrid germplasm, exhibits several desirable agricultural traits, including high grain number per spike (GNS). Understanding the genetic architecture of GNS in Pubing3228 is crucial for enhancing wheat yield. This study aims to analyze the specific genetic regions and alleles associated with high GNS in Pubing3228.MethodsThe study employed a recombination inbred line (RIL) population derived from a cross between Pubing3228 and Jing4839 to investigate the genetic regions and alleles linked to high GNS. Quantitative Trait Loci (QTL) analysis and candidate gene investigation were utilized to explore these traits.ResultsA total of 40 QTLs associated with GNS were identified across 16 chromosomes, accounting for 4.25–17.17% of the total phenotypic variation. Five QTLs (QGns.wa-1D, QGns.wa-5 A, QGns.wa-7Da.1, QGns.wa-7Da.2 and QGns.wa-7Da.3) accounter for over 10% of the phenotypic variation in at least two environments. Furthermore, 94.67% of the GNS QTL with positive effects originated from Pubing3228. Candidate gene analysis of stable QTLs identified 11 candidate genes for GNS, including a senescence-associated protein gene (TraesCS7D01G148000) linked to the most significant SNP (AX-108,748,734) on chromosome 7D, potentially involved in reallocating nutrients from senescing tissues to developing seeds.ConclusionThis study provides new insights into the genetic mechanisms underlying high GNS in Pubing3228, offering valuable resources for marker-assisted selection in wheat breeding to enhance yield.

Control of false discoveries in grouped hypothesis testing for eQTL data

BackgroundExpression quantitative trait locus (eQTL) analysis aims to detect the genetic variants that influence the expression of one or more genes. Gene-level eQTL testing forms a natural grouped-hypothesis testing strategy with clear biological importance. Methods to control family-wise error rate or false discovery rate for group testing have been proposed earlier, but may not be powerful or easily apply to eQTL data, for which certain structured alternatives may be defensible and may enable the researcher to avoid overly conservative approaches.ResultsIn an empirical Bayesian setting, we propose a new method to control the false discovery rate (FDR) for grouped hypotheses. Here, each gene forms a group, with SNPs annotated to the gene corresponding to individual hypotheses. The heterogeneity of effect sizes in different groups is considered by the introduction of a random effects component. Our method, entitled Random Effects model and testing procedure for Group-level FDR control (REG-FDR), assumes a model for alternative hypotheses for the eQTL data and controls the FDR by adaptive thresholding. As a convenient alternate approach, we also propose Z-REG-FDR, an approximate version of REG-FDR, that uses only Z-statistics of association between genotype and expression for each gene-SNP pair. The performance of Z-REG-FDR is evaluated using both simulated and real data. Simulations demonstrate that Z-REG-FDR performs similarly to REG-FDR, but with much improved computational speed.ConclusionOur results demonstrate that the Z-REG-FDR method performs favorably compared to other methods in terms of statistical power and control of FDR. It can be of great practical use for grouped hypothesis testing for eQTL analysis or similar problems in statistical genomics due to its fast computation and ability to be fit using only summary data.

Critical gene signature and immunological characterization in peripheral vascular atherosclerosis: novel insights from mendelian randomization and transcriptomics.

Peripheral vascular atherosclerosis (PVA) is a chronic inflammatory disease characterized by lipid accumulation in blood vessel walls, leading to vessel narrowing and inadequate blood supply. However, the molecular mechanisms underlying PVA remain poorly understood. In this study, we employed a combination of Mendelian randomization (MR) analysis and integrated transcriptomics to identify the critical gene signature associated with PVA. This study utilized three public datasets (GSE43292, GSE100927 and GSE28829) related to peripheral vascular atherosclerosis obtained from the Gene Expression Omnibus database. Instrumental variables (IVs) were identified through expression quantitative trait loci (eQTL) analysis, and two-sample MR analysis was performed using publicly available summary statistics. Disease critical genes were identified based on odds ratios and intersected with differentially expressed genes in the disease dataset. GSE28829 dataset was used to validate the screened disease critical genes. Functional enrichment analysis, GSEA analysis, and immune cell infiltration analysis were performed to further characterize the role of these genes in peripheral vascular atherosclerosis. A total of 26,152 gene-related SNPs were identified as IVs, and 242 disease-associated genes were identified through MR analysis. Ten disease critical genes (ARHGAP25, HCLS1, HVCN1, RBM47, LILRB1, PLAU, IFI44L, IL1B, IFI6, and CFL2) were significantly associated with peripheral vascular atherosclerosis. Functional enrichment analysis using KEGG pathways revealed enrichment in the NF-kappa B signaling pathway and osteoclast differentiation. Gene set enrichment analysis further demonstrated functional enrichment of these genes in processes related to vascular functions and immune system activation. Additionally, immune cell infiltration analysis showed differential ratios of B cells and mast cells between the disease and control groups. The correlations analysis highlights the intricate interplay between disease critical genes and immune cells associated with PVA. In conclusion, this study provides new insights into the molecular mechanisms underlying PVA by identifying ten disease critical genes associated with the disease. These findings, supported by differential expression, functional enrichment, and immune system involvement, emphasize the role of these genes in vascular function and immune cell interactions in the context of PVA. These findings contribute to a better understanding of PVA pathogenesis and offer potential targets for further mechanistic exploration and therapeutic interventions.

Fine Mapping of Five Grain Size QTLs Which Affect Grain Yield and Quality in Rice.

Grain size is a quantitative trait with a complex genetic mechanism, characterized by the combination of grain length (GL), grain width (GW), length to width ration (LWR), and grain thickness (GT). In this study, we conducted quantitative trait loci (QTL) analysis to investigate the genetic basis of grain size using BC1F2 and BC1F2:3 populations derived from two indica lines, Guangzhan 63-4S (GZ63-4S) and TGMS29 (core germplasm number W240). A total of twenty-four QTLs for grain size were identified, among which, three QTLs (qGW1, qGW7, and qGW12) controlling GL and two QTLs (qGW5 and qGL9) controlling GW were validated and subsequently fine mapped to regions ranging from 128 kb to 624 kb. Scanning electron microscopic (SEM) analysis and expression analysis revealed that qGW7 influences cell expansion, while qGL9 affects cell division. Conversely, qGW1, qGW5, and qGW12 promoted both cell division and expansion. Furthermore, negative correlations were observed between grain yield and quality for both qGW7 and qGW12. Nevertheless, qGW5 exhibited the potential to enhance quality without compromising yield. Importantly, we identified two promising QTLs, qGW1 and qGL9, which simultaneously improved both grain yield and quality. In summary, our results laid the foundation for cloning these five QTLs and provided valuable resources for breeding rice varieties with high yield and superior quality.

Genetic linkage mapping and quantitative trait locus (QTL) analysis of sweet basil (Ocimum basilicum L.) to identify genomic regions associated with cold tolerance and major volatiles.

Chilling sensitivity is one of the greatest challenges affecting the marketability and profitability of sweet basil (Ocimum basilicum L.) in the US and worldwide. Currently, there are no sweet basils commercially available with significant chilling tolerance and traditional aroma profiles. This study was conducted to identify quantitative trait loci (QTLs) responsible for chilling tolerance and aroma compounds in a biparental mapping population, including the Rutgers advanced breeding line that served as a chilling tolerant parent, 'CB15', the chilling sensitive parent, 'Rutgers Obsession DMR' and 200 F2 individuals. Chilling tolerance was assessed by percent necrosis using machine learning and aroma profiling was evaluated using gas chromatography (GC) mass spectrometry (MS). Single nucleotide polymorphism (SNP) markers were generated from genomic sequences derived from double digestion restriction-site associated DNA sequencing (ddRADseq) and converted to genotype data using a reference genome alignment. A genetic linkage map was constructed and five statistically significant QTLs were identified in response to chilling temperatures with possible interactions between QTLs. The QTL on LG24 (qCH24) demonstrated the largest effect for chilling response and was significant in all three replicates. No QTLs were identified for linalool, as the population did not segregate sufficiently to detect this trait. Two significant QTLs were identified for estragole (also known as methyl chavicol) with only qEST1 on LG1 being significant in the multiple-QTL model (MQM). QEUC26 was identified as a significant QTL for eucalyptol (also known as 1,8-cineole) on LG26. These QTLs may represent key mechanisms for chilling tolerance and aroma in basil, providing critical knowledge for future investigation of these phenotypic traits and molecular breeding.