Quantitative Trait Loci Analysis Research Articles

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

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

The study of Alzheimer's disease risk diagnosis based on natural killer cell marker genes in the multi-omics data.

Alzheimer's disease (AD) is a common neurodegenerative disorder, currently lacking effective early diagnostic methods. However, natural killer (NK) cells may play a potential role in AD pathogenesis. This study aims to identify AD-related feature genes from NK cell markers to construct a diagnostic model and explore their potential biological mechanisms in AD. Single-cell RNA sequencing data was used to identify NK cell markers. A novel feature selection algorithm, adaptive dynamic graph convolutional network (ADGCN), was proposed to extract AD-related feature genes and construct a diagnostic model. Differential, correlation and enrichment analyses were performed to understand the biological mechanisms of these genes. Immune infiltration analysis compared the immune microenvironment between AD and controls. Two regulatory networks explored interactions between feature genes, transcription factors and microRNAs. The association between SNPs and feature genes' expression was examined through expression quantitative trait loci analysis. Differential CpG sites were identified to analyze their association with the NK cell markers' expression. We developed an optimal diagnostic model (ADGCN-XGBoost) with 17 feature genes, demonstrating high diagnostic effectiveness across datasets. These genes were primarily related to macromolecule biosynthesis, cytoplasmic translation biological processes and ribosome pathway, and potentially modulated immune infiltration of AD patients. We predicted 27 target miRNAs and 21 transcription factors influencing these genes. Multimodal analysis identified 57 significant SNP-gene associations and seven CpG-gene pairs. This study proposed a novel feature selection algorithm and developed a diagnostic model based on 17 feature genes, providing new potential biomarkers for AD diagnosis.

Landscape of structural variants reveals insights for local adaptations in the Asian corn borer

Capturing the genetic diversity of different wild populations is crucial for unraveling the mechanisms of adaptation and establishing links between genome evolution and local adaptation. The Asian corn borer (ACB) moth has undergone natural selection during its adaptative evolution. However, structural variants (SVs), which play significant roles in these adaptation processes, have not been previously identified. Here, we constructed a multi-assembly graph pan-genome to highlight the importance of SVs in local adaptation. Our analysis revealed that the graph pan-genome contained 176.60 Mb (∼37.33%) of unique sequences. Subsequently, we performed an analysis of expression quantitative trait loci (QTLs) to explore the impact of SVs on gene expression regulation. Notably, through QTL mapping analysis, we identified the FTZ-F1 gene as a potential candidate gene associated with the traits of larval development rate. In sum, we explored the impact of SVs on the local adaptation of pests, therefore facilitating accelerated pest management strategies.

Protein quantitative trait loci identifies genetic biomarkers of proteins associated with measures of myocardial fibrosis in new-onset, treatment naive rheumatoid arthritis

Abstract Introduction The excess risk of cardiovascular disease (CVD) in patients with rheumatoid arthritis (RA) compared to the general population is attributed to chronic inflammation. Identifying the underlying mechanisms and shared inflammatory pathways more precisely would enable tailored treatment. Purpose To identify genetic variants associated with the cardio-metabolic-inflammatory proteomic signature in patients with early, treatment-naïve RA and low CVD risk. Methods The Coronary Artery Disease Evaluation in RA (CADERA) study was a bolt-on to a RCT of patients with early, treatment-naïve RA and low CVD risk profile (maximum of 1 traditional CVD risk factor and no diabetes mellitus). Normalised expression of 334 proteins from 75 CADERA patients who underwent cardiovascular magnetic resonance imaging (CMR) was measured using the Olink Proximity Extension Immunoassay across Inflammation, Cardiovascular II, III and Cardiometabolic panels. Genome-wide single nucleotide polymorphism (SNP) data were generated using the Illumina Global Screening Array and was imputed and checked for data quality using standard approaches. Proteins associated with CMR parameters were identified using Bayesian mixed effects linear regression. Protein quantitative trait locus (pQTL) analysis was then performed using linear regression models adjusted for age, gender, and systolic blood pressure. Cis-pQTLs were defined as SNPs within 1Mb of the protein-encoding gene, and significance threshold was set at 1e-5. Due to sample size, trans-pQTLs were not considered in this analysis. Linkage disequilibrium (LD) clumping was performed using PLINK software to identify index SNPs defined as the most significant variant in LD (r2 <0.5) within a region of +/- 250Kb. Results Following quality control 318 proteins and 5,971,781 SNPs were available for analysis in 75 CADERA patients. The median age was 51 years [inter-quartile range (IQR) 40 - 61] with 52/75 (69%) females, 40/75 (53%) current/ex-smokers, and median body mass index (BMI) 26.4kg/m2 (IQR 23.3 - 28). Participants had a median RA symptom duration of 21.9 weeks (IQR 14.4 - 32.7). Only 8/75 (10%) reported a history of hypertension, hypercholesteroaemia or family history of CVD. 54 out of 318 proteins were associated with CMR measures of myocardial fibrosis and/or vascular stiffness. 460 cis-pQTLs were identified for 20 out of the 318 proteins. LD clumping revealed 40 cis-pQTLs independently associated with these 20 proteins. Of these, NOTCH3 (rs34763630) was positively associated with extracellular volume, and SELPLG (rs7980427) was negatively associated with late gadolinium enhancement as detected on CMR (table 1). No other proteins with genetic support were associated with CMR measures. Conclusion This study for the first time, implicates genetic markers associated with two proteins as putative candidate biomarkers of CMR-identified myocardial fibrosis in new-onset RA that now warrant validation in an independent cohort.

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.

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.

The Tetratricopeptide repeat protein TaTPR-B1 regulates spike compactness in bread wheat.

Spike compactness (SC) is strongly associated with wheat (Triticum aestivum L.) grain yield. In this study, we conducted a quantitative trait locus (QTL) analysis using a doubled haploid (DH) population derived from a cross between two common wheat varieties with contrasting spike morphology, revealing 16 stable QTLs associated with SC. The effect of a major QTL, QSc.cau-6B.1, was validated in 231 F7 recombinant inbred lines (RILs) derived from the same cross as the DH population. Using two residual heterozygous lines (RHLs), we delimited QSc.cau-6B.1 to an approximately 0.5-Mbp physical interval containing four high-confidence genes. The tetratricopeptide repeat-TraesCS6B03G1214400 (TaTPR-B1) was the priority candidate gene according to sequence and expression variations between near-isogenic lines. Accordingly, TaTPR-B1 knockout in the common wheat variety 'CB037' significantly increased SC compared to the wild type (WT). Conversely, TaTPR-B1 overexpression in the common wheat variety 'Fielder' significantly decreased SC compared to the WT. Moreover, we developed a PCR-based marker targeting the 32-bp insertion/deletion (InDel) between the two TaTPR-B1 alleles, which could be practical and valuable in modern wheat breeding programs for diagnostic purposes. Collectively, these findings provide insight into the genetic basis of SC in common wheat and present a valuable target with a breeder-friendly diagnostic marker for gene pyramid breeding.

CRISPR/Cas9 and Anther Culture for Precision Double Haploid Line Production in Controlled Environments

ABSTRACTThe development of mapping populations and quantitative trait loci (QTL) analysis face constraints, in crops exhibiting male sterility and self‐incompatibility under field conditions. Addressing these challenges requires the integration of advanced techniques, including the temporal alteration or excision of centromere histone H3 (CENH3) protein and the use of gene editing tools such as MATRILINEAL (MTL) knockout. Specifically, this can be achieved through Cas9/gRNA‐mediated mutagenesis or Cas9/gRNA‐driven promoter expression systems. These technologies offer efficient means to advance mapping populations and QTL analysis in male sterile and self‐incompatible crops within controlled ecosystems. The doubled haploid (DH) mapping population, traditionally requiring 3 years of generation time via anther culture method, can now be expedited to 2–3 years of generation time using gene editing techniques within controlled environmental systems. Notably, DH mapping populations can be efficiently generated in various crops, including rice, wheat, maize, barley and oats by leveraging gene editing tools. Among these tools, the novel approach of CENH3 protein temporal alteration/excision emerges as highly efficient compared to MTL knockout using Cas9/gRNA‐mediated mutation or Cas9/gRNA promoter expression. However, further investigation is warranted to optimise the regeneration of double haploid populations and enhance QTL analysis in male sterile and self‐incompatible crops under controlled systems.

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.

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.

Genetic variants of LRRC8C, OAS2, and CCL25 in the T cell exhaustion-related genes are associated with non-small cell lung cancer survival.

T cell exhaustion is a state in which T cells become dysfunctional and is associated with a decreased efficacy of immune checkpoint inhibitors. Lung cancer has the highest mortality among all cancers. However, the roles of genetic variants of the T cell exhaustion-related genes in the prognosis of non-small cell lung cancer (NSCLC) patients has not been reported. We conducted a two-stage multivariable Cox proportional hazards regression analysis with two previous genome-wide association study (GWAS) datasets to explore associations between genetic variants in the T cell exhaustion-related genes and survival of NSCLC patients. We also performed expression quantitative trait loci analysis for functional validation of the identified variants. Of all the 52,103 single nucleotide polymorphisms (SNPs) in 672 T cell exhaustion-related genes, 1,721 SNPs were found to be associated with overall survival (OS) of 1185 NSCLC patients of the discovery GWAS dataset from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial, and 125 of these 1,721 SNPs remained significant after validation in an additional independent replication GWAS dataset of 984 patients from the Harvard Lung Cancer Susceptibility (HLCS) Study. In multivariable stepwise Cox model analysis, three independent SNPs (i.e., LRRC8C rs10493829 T>C, OAS2 rs2239193 A>G, and CCL25 rs3136651 T>A) remained significantly associated with OS with hazards ratios (HRs) of 0.86 (95% confidence interval (CI) = 0.77-0.96, P = 0.008), 1.48 (95% CI = 1.18-1.85, P < 0.0001) and 0.78 (95% CI = 0.66-0.91, P = 0.002), respectively. Further combined analysis for these three SNPs suggested that an unfavorable genotype score was associated with a poor OS and disease-specific survival. Expression quantitative trait loci analysis suggested that the LRRC8C rs10493829 C allele was associated with elevated LRRC8C mRNA expression levels in normal lymphoblastoid cells, lung tissue, and whole blood. Our findings suggested that these functional SNPs in the T cell exhaustion-related genes may be prognostic predictors for survival of NSCLC patients, possibly via a mechanism of modulating corresponding gene expression.

The critical involvement of monocytes/macrophages in the pathogenesis of primary Sjögren's syndrome: New evidence from Mendelian randomization and single-cell sequencing

BackgroundPrimary Sjögren's syndrome (pSS) stands as a chronic autoimmune disease characterized by an elusive pathogenesis. The synergy of single-cell RNA sequencing and Mendelian randomization (MR) analysis provides an opportunity to comprehensively unravel the contributory role of monocytes/macrophages in the intricate pathogenesis of pSS. MethodsDifferentially expressed genes (DEGs) of various types of immune cells were analyzed after annotating single-cell RNA sequencing (scRNA-seq) data. MR analysis of expression quantitative trait loci (eQTL) and protein quantitative trait loci (pQTL) was conducted to search for key pathogenic genes and proteins. Cellular localization of pathogenic genes was performed based on scRNA-seq data. Variations in signaling pathways between immune cells were further analyzed. ResultsA total of 1434 significant DEGs were identified. Among these, 60 genes exhibited strong relevance to the occurrence of pSS, of which 32 genes differentially expressed in monocytes/macrophages. CTSS was found to be a significant risk protein with a p-value of 0.001 and an odds ratio of 1.384 (1.147–1.669), showing pronounced expression in monocytes/macrophages. Furthermore, monocytes/macrophages displayed heightened expression levels of MXD1, AMPD2, TNFSF10, FTL, UBXN11, CSF3R, and LILRA5. The analysis of intercellular signaling revealed increased signal intensity in both incoming and outgoing signals in monocytes/macrophages. The signaling interactions between monocytes/macrophages, B cells, and T cells exhibited varying degrees of deviation. ConclusionsThis study highlights the significant involvement of monocytes/macrophages in the pathogenesis of pSS, as evidenced by MR analysis and scRNA-seq analysis. This suggests monocytes/macrophages as a focal point for pathogenesis research and potential therapeutic targeting in pSS.

Multi-omics analysis of the molecular response to glucocorticoids - insights into shared genetic risk from psychiatric to medical disorders

BackgroundAlterations in the effects of glucocorticoids have been implicated in mediating some of the negative health effects associated with chronic stress, including increased risk for psychiatric disorders as well as cardiovascular and metabolic diseases. This study investigates how genetic variants influence gene expression and DNA methylation (DNAm) in response to glucocorticoid receptor (GR)-activation, and their association with disease risk. MethodsWe measured DNAm (n=199) and gene expression (n=297) in peripheral blood before and after GR-activation with dexamethasone, with matched genotype data available for all samples. A comprehensive molecular quantitative trait locus (QTL) analysis was conducted, mapping GR-response methylation (me)QTLs, GR-response expression (e)QTLs, and GR-response expression quantitative trait methylation (eQTM). A multi-level network analysis was employed to map the complex relationships between the transcriptome, epigenome, and genetic variation. ResultsWe identified 3,772 GR-response meCpGs corresponding to 104,828 local GR-response meQTLs that did not strongly overlap with baseline meQTLs. eQTM and eQTL analyses revealed distinct genetic influences on gene expression and DNAm. Multi-level network analysis uncovered GR-response network trio QTLs, characterized by SNP-CpG-transcript combinations where meQTLs act as both eQTLs and eQTMs. GR-response trio variants were enriched in GWAS for psychiatric, respiratory, autoimmune and cardiovascular diseases and conferred a higher relative heritability per SNP than GR-response meQTL and baseline QTL SNP. ConclusionsGenetic variants modulating the molecular effects of glucocorticoids are associated with psychiatric as well as medical diseases and not uncovered in baseline QTL analyses.

Genetic Variants in METTL16 Affect the Risk of Non-Syndromic Orofacial Clefts.

N6-methyladenosine (m6A) is the most prevalent modification of RNA in eukaryotes which is associated with many cellular processes and diseases. Here, our objective is to explore whether genetic variants in m6A modification genes are associated with the risk of non-syndrome orofacial clefts (NSOCs). The transmission disequilibrium test (TDT) was performed to calculate the association between single nucleotide polymorphisms (SNPs) in m6A modification genes and NSOCs risk in 944 case-parent trios. The function of SNP was predicted by HaploReg, RegulomeDB and histone enrichment data. The expression quantitative trait locus (eQTL) analysis was examined using Genotype-Tissue Expression (GTEx) and eQTLGen. The role of gene in the development of NSOCs was assessed with correlation and enrichment analysis based on gene expression data in mice craniofacial tissue and zebrafish embryo. We identified that rs8078195 (A > C) in METTL16 was suggestively associated with the increased risk of NSOCs (OR = 1.32, p = 1.80E - 03). The region surrounding rs8078195 was subjected to deoxyribonuclease hypersensitivity and enriched with multiple histone modifications. In addition, it had a significant eQTL effect with METTL16 in skin tissue and human peripheral blood, which played an important role in NSOCs development. Bioinformatic analysis indicated that METTL16 contributed to the development of NSOCs probably by regulating cell cycle process. Rs8078195 in METTL16 was associated with the occurrence of NSOCs.

Compiling molecular evidence from a tetraploid rose genome into a near-saturated map for the identification of pigment-related genes

With their high economic value and cultural significance, modern roses are one of the most important ornamental plants. Because of their complicated genetic background and tetraploid nature, the creation of high-density genetic maps of roses has been a challenge that has slowed the pace of molecular breeding for modern roses. The current construction of tetraploid genetic maps based on existing diploid rose genomes could lead to inaccurate marker information and genotyping results. Therefore, we generated the first high-quality tetraploid genome of Rosa chinensis ‘Yunzheng Xiawei.’ Utilizing Illumina, PacBio, and Hi-C sequencing technologies, we assembled a genome of 858.59 Mb with 14 pseudo-chromosomes. Mode of inheritance analysis using PolyOrigin indicated that modern roses show both quadrivalent and bivalent pairing. Based on this reference genome, high-density genetic maps were constructed using MSTmap with nearly saturated markers. Quantitative trait locus (QTL) analysis was conducted using WinQTLCart and R/qtl for flavonoids and carotenoids, and 11 QTL clusters were identified. By combining the genome annotation, phylogenetic analyses, and gene expression analyses, we were able to identify several key genes related to flavonoid and carotenoid biosynthesis. This study provides the basis for further genetic analyses of highly heterozygous tetraploid roses and could facilitate the progress of marker-assisted selection in modern roses.

QTL analysis to identify genes involved in the trade-off between silk protein synthesis and larva-pupa transition in silkworms

BackgroundInsect-based food and feed are increasingly attracting attention. As a domesticated insect, the silkworm (Bombyx mori) has a highly nutritious pupa that can be easily raised in large quantities through large-scale farming, making it a highly promising source of food. The ratio of pupa to cocoon (RPC) refers to the proportion of the weight of the cocoon that is attributed to pupae, and is of significant value for edible utilization, as a higher RPC means a higher ratio of conversion of mulberry leaves to pupa. In silkworm production, there is a trade-off between RPC and cocoon shell ratiao(CSR), which refers the ratio of silk protein to the entire cocoon, during metamorphosis process. Understanding the genetic basis of this balance is crucial for breeding edible strains with a high RPC and further advancing its use as feed.ResultsUsing QTL-seq, we identified a quantitative trait locus (QTL) for the balance between RPC and CSR that is located on chromosome 11 and covers a 9,773,115-bp region. This locus is an artificial selection hot spot that contains ten non-overlapping genomic regions under selection that were involved in the domestication and genetic breeding processes. These regions include 17 genes, nine of which are highly expressed in the silk gland, which is a vital component in the trade-off between RPC and CSR. These genes are annotate with function related with epigenetic modifications and the regulation of DNA replication et al. We identified one and two single nucleotide polymorphisms (SNPs) in the exons of teh KWMTBOMO06541 and KWMTBOMO06485 genes that result in amino acid changes in the protein domains. These SNPs have been strongly selected for during the domestication process. The KWMTBOMO06485 gene encodes the Bombyx mori (Bm) tRNA methyltransferase (BmDnmt2) and its knockout results in a significant change in the trade-off between CSR and RPC in both sexes.ConclusionsTaken together, our results contribute to a better understanding of the genetic basis of RPC and CSR. The identified QTL and genes that affect RPC can be used for marker-assisted and genomic selection of silkworm strains with a high RPC. This will further enhance the production efficiency of silkworms and of closely-related insects for edible and feed purposes.

Identification and fine mapping of a QTL-rich region for yield-and quality-related traits on chromosome 4BS in common wheat (Triticum aestivum L.).

Yield and quality are important for plant breeding. To better understand the genetic basis underlying yield- and quality-related traits in wheat (Triticum aestivum L.), we conducted the quantitative trait locus (QTL) analysis using recombinant inbred lines (RILs) and a high-density genetic linkage map with a 90K array. In this study, a total of 117 QTLs were detected for spike number per area (SNPA), thousand grain weight (TGW), grain number per spike (GNS), plant height (PH), spike length (SL), total spikelet number (TSN), spikelet density (SD), grain protein content (GPC), and grain starch content (GSC). Among these QTLs, 30 environmentally stable QTLs for yield- and quality-related traits were detected. Notably, five QTL-rich regions (Qrr) for yield-and/or quality-related traits were identified, including the QTL-rich region on chromosome 4BS (QQrr.cau-4B) for eight traits (SNPA, GNS, PH, SL, TSN, SD, GPC, and GSC). The stable QTL-rich region QQrr.cau-4B was delimited into a physical interval of approximately 2.47Mb. Based on the annotation information of the Chinese spring wheat genome v1.0 and parental re-sequencing results, the interval included twelve genes with sequence variations. Taken together, these results contribute to further understanding of the genetic basis of SNPA, GNS, PH, SL, TSN, SD, GPC, and GSC, and fine mapping of QQrr.cau-4B will be beneficial for gene cloning and marker-assisted selection in the genetic improvement of wheat varieties.

Genetic Variation and Regulation of MICA Alters Natural Killer Cell-Mediated Immunosurveillance in Early-Onset Colorectal Cancer.

The incidence of colorectal cancer (CRC) among individuals under age 50, or early-onset CRC (EOCRC), has been rising over the past few decades for unclear reasons, and the etiology of the disease remains largely unknown. Known genetic risk factors do not explain this increase, pointing to possible environmental and as-yet unidentified genetic contributors and their interactions. Previous research linked genetic variation on chromosome 6 to increased CRC risk. This region harbors multiple immune genes, including the gene encoding Major Histocompatibility Complex (MHC) class I polypeptide-related sequence A (MICA). MICA is a polygenic ligand for the Natural Killer Group 2D receptor (NKG2D), a receptor expressed on Natural Killer (NK) cells and other lymphocytes. Given that intra-tumoral NK cell infiltration correlates with favorable CRC outcomes, we hypothesized that germline genetic variation in MICA could influence CRC risk. In a discovery set of 40,125 cases and controls, we show that the minor G allele at Chr6:31373718C>G (hg19) is associated with increased risk for CRC (odds ratio (OR) = 1.09, 95% confidence interval (CI) 1.04 - 1.15, p = 0.0009). The effect is stronger in EOCRC (OR = 1.26, 95% CI 1.08 - 1.44, p = 0.0023) than in those 50 and over (OR = 1.07, 95% CI 1.02 - 1.13; p = 0.012) (Ratio of ORs = 1.32, 95% CI 1.14 - 1.52, p = 0.0002). In an independent validation set of 77,983 cases and controls, the adjusted interaction by age-of-onset was significant at OR = 1.15 (95% CI 1.03 - 1.34, p = 0.0150) with a higher risk in EOCRC. Expression quantitative trait locus analysis in normal colonic epithelia showed that MICA RNA expression decreases linearly with each additional copy of the minor G allele (p = 3.345 × 10e-18). Bulk RNA analysis of the tumor immune microenvironment revealed that tumors from patients with CG or GG genotypes have lower resting and activated NK cell infiltration as compared to tumors from patients with CC genotype. Multiplex immunofluorescence analysis demonstrated that patients with a G allele (i.e. CG or GG genotype, but not CC genotype) have a statistically significant decrease in the number of NK cells in tumor compared to adjacent normal colonic mucosa. Taken together, population-based epidemiologic, molecular, genetic, cellular and immunologic evidence demonstrate that MICA genotype is associated with increased risk of EOCRC and reduced number of NK cells in colorectal tumors, suggesting that patients with a G allele have altered NK cell-mediated immunosurveillance. These novel findings suggest that EOCRC may have a previously unrecognized innate immune-mediated etiology which merits further investigation.

Analysis of CNS autoimmunity in genetically diverse mice reveals unique phenotypes and mechanisms.

Multiple sclerosis (MS) is a complex disease with significant heterogeneity in disease course and progression. Genetic studies have identified numerous loci associated with MS risk, but the genetic basis of disease progression remains elusive. To address this, we leveraged the Collaborative Cross (CC), a genetically diverse mouse strain panel, and experimental autoimmune encephalomyelitis (EAE). The thirty-two CC strains studied captured a wide spectrum of EAE severity, trajectory, and presentation, including severe-progressive, monophasic, relapsing remitting, and axial rotary (AR)-EAE, accompanied by distinct immunopathology. Sex differences in EAE severity were observed in six strains. Quantitative trait locus analysis revealed distinct genetic linkage patterns for different EAE phenotypes, including EAE severity and incidence of AR-EAE. Machine learning-based approaches prioritized candidate genes for loci underlying EAE severity (Abcc4 and Gpc6) and AR-EAE (Yap1 and Dync2h1). This work expands the EAE phenotypic repertoire and identifies novel loci controlling unique EAE phenotypes, supporting the hypothesis that heterogeneity in MS disease course is driven by genetic variation.

Potentially functional variants of PARK7 and DDR2 in ferroptosis-related genes predict survival of non-small cell lung cancer patients.

Ferroptosis, a form of regulated cell death, is characterized by iron-dependent lipid peroxidation. It is recognized increasingly for its pivotal role in both cancer development and the response to cancer treatments. We assessed associations between 370,027 single-nucleotide polymorphisms (SNPs) within 467 ferroptosis-related genes and survival of non-small cell lung cancer (NSCLC) patients. Data from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial served as our discovery dataset, while the Harvard Lung Cancer Susceptibility Study used as our validation dataset. For SNPs that remained statistically significantly associated with overall survival (OS) in both datasets, we employed a multivariable stepwise Cox proportional hazards regression model with the PLCO dataset. Ultimately, two independent SNPs, PARK7 rs225120 C>T and DDR2 rs881127 T>C, were identified with adjusted hazard ratios of 1.32 (95% confidence interval = 1.15-1.52, p = .0001) and 1.34 (95% confidence interval = 1.09-1.64, p = .006) for OS, respectively. We aggregated these two SNPs into a genetic score reflecting the number of unfavorable genotypes (NUG) in further multivariable analysis, revealing a noteworthy association between increased NUG and diminished OS (ptrend = .001). Additionally, an expression quantitative trait loci analysis indicated that PARK7 rs225120T genotypes were significantly associated with higher PARK7 mRNA expression levels in both whole blood and normal lung tissue. Conversely, DDR2 rs881127C genotypes were significantly associated with lower DDR2 mRNA expression levels in normal lung tissue. Our findings suggest that genetic variants in the ferroptosis-related genes PARK7 and DDR2 are associated with NSCLC survival, potentially through their influence on gene expression levels.