Quantitative Trait Loci Effects Research Articles

Quantitative Trait Loci Mapping and Candidate Gene Analysis for Fiber Quality Traits in Upland Cotton

Superior fiber quality is one of the most important objectives in cotton breeding. To detect the genetic basis underlying fiber quality, an F2 population containing 413 plants was constructed by crossing Jifeng 914 and Jifeng 173, both of which have superior fiber quality, with Jifeng 173 being better. Five fiber quality traits were investigated in the F2, F2:3, F2:4, and F2:5 populations. Quantitative trait loci (QTL) mapping was conducted based on a high-density genetic map containing 11,488 single nucleotide polymorphisms (SNPs) and spanning 4202.12 cM in length. Transgressive segregation patterns and complex correlations in the five tested traits were observed. A total of 108 QTLs were found, including 13 major effect QTLs that contributed more than 10% toward phenotypic variation (PV) and 9 stable QTLs that could be repeatedly mapped in different generations. Chromosome A7 contained 12 QTL, ranking the first. No QTL was found on chromosomes D1 and D11. Two QTLs could be repeatedly detected in three populations, including qFL-D3-2 in F2, F2:4, and F2:5 with 9.18–21.45% of PV and qFS-A11-1 in F2:3, F2:4, and F2:5 with 6.05–10.41% of PV. Another seven stable QTLs could be detected in two populations, including four major effect QTLs: qFL-A12-3, qFS-D10-2, qMC-D6-2, and qMC-D8-1. Fourteen QTL-overlapping regions were found, which might explain the complex correlations among the five phenotypic traits. Four regions on chromosome A11, D3, D6, and D10 covered by both stable and major effect QTLs are promising for further fine mapping. The genomic regions of the two QTLs detected in three populations and the four major effect QTLs contain 810 genes. Gene functional analysis revealed that the annotated genes are mainly involved in protein binding and metabolic pathways. Fifteen candidate genes in the qFL-D3-2 region are highly expressed in fiber or ovules during fiber initiation, elongation, secondary cell wall thickening, or maturation stages. qRT-PCR revealed that Ghir_D03G005440.1 and Ghir_D03G011310.1 may play a role in promoting fiber initiation, while Ghir_D03G006470.1 may be beneficial for promoting fiber elongation. This study provides more information for revealing the molecular genetic basis underlying cotton fiber quality.

Genetic drivers of age-related changes in urinary magnesium excretion.

Although age-dependent alterations in urinary magnesium (Mg2+) excretion have been described, the underlying mechanism remains elusive. As heritability significantly contributes to variations in urinary Mg2+excretion, we measured urinary Mg2+ excretion at different ages in a cohort of genetically variable Diversity Outbred (DO) mice. Compared to animals aged 6 months, an increase in Mg2+ excretion was observed at 12 and 18 months. Quantitative trait locus (QTL) analysis revealed an association of a locus on chromosome 10 with Mg2+ excretion at 6 months of age, with Oit3 (encoding oncoprotein-induced transcript 3; OIT3) as our primary candidate gene. To study the possible role of OIT3 in renal Mg2+ handling, we generated and characterized Oit3 knockout (Oit3-/-) mice. Although a slightly lower serum Mg2+ concentration was present in male Oit3-/- mice, this effect was not observed in female Oit3-/- mice. Additionally, urinary Mg2+ excretion and the expression of renal magnesiotropic genes was unaltered in Oit3-/- mice. For animals aged 12 and 18 months, QTL analysis revealed an association with a locus on chromosome 19, which contains the gene encoding TRPM6, a known Mg2+ channel involved in renal Mg2+ reabsorption. Comparison with RNAseq data revealed that Trpm6 mRNA expression is inversely correlated with the QTL effect, implying that TRPM6 may be involved in age-dependent changes in urinary Mg2+ excretion in mice. In conclusion, we show here that variants in Oit3 and Trpm6 are associated with urinary Mg2+ excretion at distinct periods in life, although OIT3 is unlikely to affect renal Mg2+ handling.

Unraveling genetic threads: Identifying novel therapeutic targets for allergic rhinitis through Mendelian randomization

BackgroundAllergic rhinitis (AR) is a pervasive global health issue, and currently, there is a scarcity of targeted drug therapies available. This study aims to identify potential druggable target genes for AR using Mendelian randomization (MR) analysis. MethodsMR analysis was conducted to assess the causal effect of expression quantitative trait loci (eQTL) in the blood on AR. Data on AR were collected from 2 datasets: FinnGen(R9) (11,009 cases and 359,149 controls) and UK Biobank (25,486 cases and 87,097 controls). Colocalization analysis was utilized to assess the common causal genetic variations between the identified drug target genes and AR. We also employed available genome-wide association studies (GWAS) data to gauge the impact of druggable genes on AR biomarkers and other allergic diseases. ResultsThis study employs MR to analyze the relationship between 3410 druggable genes and AR. After Bonferroni correction, 10 genes were found to be significantly associated with AR risk (P < 0.05/3410). Colocalization analysis revealed a significant causal relationship between the expression variation of CFL1 and EFEMP2 genes and AR, sharing direct causal variants (colocalization probability PP.H3 + PP.H4 > 0.8), highlighting their importance as potential therapeutic targets for AR. The CFL1 gene showed a causal link with levels of thymic stromal lymphopoietin (TSLP), eosinophil count, and interleukin-13 (IL-13) (P = 0.016, 7.45E-16, 0.00091, respectively). EFEMP2 was also causally related to eosinophil count, IL-13, and interleukin-17 (IL-17) (P = 0.00012, 0.00091, 0.032, respectively). PheWAS analysis revealed significant associations of CFL1 with asthma, whereas EFEMP2 showed associations with both asthma and eczema. Protein-Protein Interaction (PPI) network analysis further unveiled the direct interactions of EFEMP2 and CFL1 with proteins related to immune regulation and inflammatory responses, with 77.64% of the network consisting of direct bindings, indicating their key roles in modulating AR-related immune and inflammatory responses. Notably, there was an 8.01% significant correlation between immune-related pathways and genes involved in inflammatory responses. ConclusionThese genes present notable associations with AR biomarkers and other autoimmune diseases, offering valuable targets for developing new AR therapies.

Strawberry phenotypic plasticity in flowering time is driven by the interaction between genetic loci and temperature

Abstract Flowering time (FT), which determines when fruits or seeds can be harvested, is subject to phenotypic plasticity, that is, the ability of a genotype to display different phenotypes in response to environmental variation. Here, we investigated how the environment affects the genetic architecture of FT in cultivated strawberry (Fragaria × ananassa) and modifies its quantitative trait locus (QTL) effects. To this end, we used a bi-parental segregating population grown for 2 years at widely divergent latitudes (five European countries) and combined climatic variables with genomic data (Affymetrix SNP array). Examination, using different phenological models, of the response of FT to photoperiod, temperature, and global radiation indicated that temperature is the main driver of FT in strawberry. We next characterized in the segregating population the phenotypic plasticity of FT by using three statistical approaches that generated plasticity parameters including reaction norm parameters. We detected 25 FT QTLs summarized as 10 unique QTLs. Mean values and plasticity parameter QTLs were co-localized in three of them, including the major 6D_M QTL whose effect is strongly modulated by temperature. The design and validation of a genetic marker for the 6D_M QTL offers great potential for breeding programs, for example selecting early-flowering strawberry varieties well adapted to different environmental conditions.

Based on systematic druggable genome-wide Mendelian randomization identifies therapeutic targets for diabetes.

Diabetes and its complications cause a heavy burden of disease worldwide. In recent years, Mendelian randomization (MR) has been widely used to discover the pathogenesis and epidemiology of diseases, as well as to discover new therapeutic targets. Therefore, based on systematic "druggable" genomics, we aim to identify new therapeutic targets for diabetes and analyze its pathophysiological mechanisms to promote its new therapeutic strategies. We used double sample MR to integrate the identified druggable genomics to evaluate the causal effect of quantitative trait loci (eQTLs) expressed by druggable genes in blood on type 1 and 2 diabetes (T1DM and T2DM). Repeat the study using different data sources on diabetes and its complications to verify the identified genes. Not only that, we also use Bayesian co-localization analysis to evaluate the posterior probabilities of different causal variations, shared causal variations, and co-localization probabilities to examine the possibility of genetic confounding. Finally, using diabetes markers with available genome-wide association studies data, we evaluated the causal relationship between established diabetes markers to explore possible mechanisms. Overall, a total of 4,477 unique druggable genes have been gathered. After filtering using methods such as Bonferroni significance (P<1.90e-05), the MR Steiger directionality test, Bayesian co-localization analysis, and validation with different datasets, Finally, 7 potential druggable genes that may affect the results of T1DM and 7 potential druggable genes that may affect the results of T2DM were identified. Reverse MR suggests that C4B may play a bidirectional role in the pathogenesis of T1DM, and none of the other 13 target genes have a reverse causal relationship. And the 7 target genes in T2DM may each affect the biomarkers of T2DM to mediate the pathogenesis of T2DM. This study provides genetic evidence supporting the potential therapeutic benefits of targeting seven druggable genes, namely MAP3K13, KCNJ11, REG4, KIF11, CCNE2, PEAK1, and NRBP1, for T2DM treatment. Similarly, targeting seven druggable genes, namely ERBB3, C4B, CD69, PTPN22, IL27, ATP2A1, and LT-β, has The potential therapeutic benefits of T1DM treatment. This will provide new ideas for the treatment of diabetes and also help to determine the priority of drug development for diabetes.

High-density linkage to physical mapping in a unique Tall × Dwarf coconut (Cocos nucifera L.) outbred F2 uncovers a major QTL for flowering time colocalized with the FLOWERING LOCUS T (FT).

The coconut tree crop (Cocos nucifera L.) provides vital resources for millions of people worldwide. Coconut germplasm is largely classified into 'Tall' (Typica) and 'Dwarf' (Nana) types. While Tall coconuts are outcrossing, stress tolerant, and late flowering, Dwarf coconuts are inbred and flower early with a high rate of bunch emission. Precocity determines the earlier production of a plantation and facilitates management and harvest. A unique outbred F2 population was used, generated by intercrossing F1 hybrids between Brazilian Green Dwarf from Jiqui (BGDJ) and West African Tall (WAT) cultivars. Single-nucleotide polymorphism (SNP) markers fixed for alternative alleles in the two varieties, segregating in an F2 configuration, were used to build a high-density linkage map with ~3,000 SNPs, anchored to the existing chromosome-level genome assemblies, and a quantitative trait locus (QTL) mapping analysis was carried out. The linkage map established the chromosome numbering correspondence between the two reference genome versions and the relationship between recombination rate, physical distance, and gene density in the coconut genomes. Leveraging the strong segregation for precocity inherited from the Dwarf cultivar in the F2, a major effect QTL with incomplete dominance was mapped for flowering time. FLOWERING LOCUS T (FT) gene homologs of coconut previously described as putatively involved in flowering time by alternative splice variant analysis were colocalized within a ~200-kb window of the major effect QTL [logarithm of the odds (LOD) = 11.86]. Our work provides strong phenotype-based evidence for the role of the FT locus as the putative underlying functional variant for the flowering time difference between Dwarf and Tall coconuts. Major effect QTLs were also detected for developmental traits of the palm, plausibly suggesting pleiotropism of the FT locus for other precocity traits. Haplotypes of the two SNPs flanking the flowering time QTL inherited from the Dwarf parent BGDJ caused a reduction in the time to flower of approximately 400 days. These SNPs could be used for high-throughput marker-assisted selection of early-flowering and higher-productivity recombinant lines, providing innovative genetic material to the coconut industry.

Genome-wide association analysis of the resistance to infectious hematopoietic necrosis virus in two rainbow trout aquaculture lines confirms oligogenic architecture with several moderate effect quantitative trait loci

Infectious hematopoietic necrosis (IHN) is a disease of salmonid fish that is caused by the IHN virus (IHNV), which can cause substantial mortality and economic losses in rainbow trout aquaculture and fisheries enhancement hatchery programs. In a previous study on a commercial rainbow trout breeding line that has undergone selection, we found that genetic resistance to IHNV is controlled by the oligogenic inheritance of several moderate and many small effect quantitative trait loci (QTL). Here we used genome wide association analyses in two different commercial aquaculture lines that were naïve to previous exposure to IHNV to determine whether QTL were shared across lines, and to investigate whether there were major effect loci that were still segregating in the naïve lines. A total of 1,859 and 1,768 offspring from two commercial aquaculture strains were phenotyped for resistance to IHNV and genotyped with the rainbow trout Axiom 57K SNP array. Moderate heritability values (0.15–0.25) were estimated. Two statistical methods were used for genome wide association analyses in the two populations. No major QTL were detected despite the naïve status of the two lines. Further, our analyses confirmed an oligogenic architecture for genetic resistance to IHNV in rainbow trout. Overall, 17 QTL with notable effect (≥1.9% of the additive genetic variance) were detected in at least one of the two rainbow trout lines with at least one of the two statistical methods. Five of those QTL were mapped to overlapping or adjacent chromosomal regions in both lines, suggesting that some loci may be shared across commercial lines. Although some of the loci detected in this GWAS merit further investigation to better understand the biological basis of IHNV disease resistance across populations, the overall genetic architecture of IHNV resistance in the two rainbow trout lines suggests that genomic selection may be a more effective strategy for genetic improvement in this trait.

Improving selection decisions with mating information by accounting for Mendelian sampling variances looking two generations ahead

BackgroundBreeding programs are judged by the genetic level of animals that are used to disseminate genetic progress. These animals are typically the best ones of the population. To maximise the genetic level of very good animals in the next generation, parents that are more likely to produce top performing offspring need to be selected. The ability of individuals to produce high-performing progeny differs because of differences in their breeding values and gametic variances. Differences in gametic variances among individuals are caused by differences in heterozygosity and linkage. The use of the gametic Mendelian sampling variance has been proposed before, for use in the usefulness criterion or Index5, and in this work, we extend existing approaches by not only considering the gametic Mendelian sampling variance of individuals, but also of their potential offspring. Thus, the criteria developed in this study plan one additional generation ahead. For simplicity, we assumed that the true quantitative trait loci (QTL) effects, genetic map and the haplotypes of all animals are known.ResultsIn this study, we propose a new selection criterion, ExpBVSelGrOff, which describes the genetic level of selected grand-offspring that are produced by selected offspring of a particular mating. We compare our criterion with other published criteria in a stochastic simulation of an ongoing breeding program for 21 generations for proof of concept. ExpBVSelGrOff performed better than all other tested criteria, like the usefulness criterion or Index5 which have been proposed in the literature, without compromising short-term gains. After only five generations, when selection is strong (1%), selection based on ExpBVSelGrOff achieved 5.8% more commercial genetic gain and retained 25% more genetic variance without compromising inbreeding rate compared to selection based only on breeding values.ConclusionsOur proposed selection criterion offers a new tool to accelerate genetic progress for contemporary genomic breeding programs. It retains more genetic variance than previously published criteria that plan less far ahead. Considering future gametic Mendelian sampling variances in the selection process also seems promising for maintaining more genetic variance.

O03 Genetic impacts on the skin methylome

Abstract Introduction and aims DNA methylation at CpG dinucleotides is a dynamic epigenetic mechanism that has been linked to numerous skin phenotypes and diseases. Previous studies in blood show that a substantial proportion of the human DNA methylome exhibits evidence for genetic influence, and that 15–17% of narrow-sense methylation heritability is explained by genetic variants, or methylation quantitative trait loci (meQTLs). However, no genome-wide meQTL studies have previously been performed in skin. The primary purpose of this work was to identify the genetic basis of DNA methylation levels in whole skin. Methods Utilizing a twin-based heritability model, we estimated DNA methylation heritability using 414 bulk skin tissue samples from healthy older female twins from the TwinsUK cohort, profiled using the Illumina Infinium HumanMethylation450 BeadChip (Illumina, San Diego, CA, USA). We then integrated genomic data for 394 of these twins to perform genome-wide meQTL analyses. Finally, we integrated these meQTL Results with skin eQTL Results from an overlapping sample (N = 664). Results Over 8.2% of measured CpG sites showed evidence for strong heritability (h2 &amp;gt; 0.4), with a mean additive heritability estimate of 11.07% across all tested sites. We identified 76 442 CpG sites (18.8% of measured CpG sites) associated with a meQTL in cis (&amp;lt; 1 MB variant-CpG distance) and 1438 (0.35%) in trans. Both CpG sites under meQTL effects, and genetic variants underlying these meQTL effects in skin, are enriched in regions previously identified from genome-wide and epigenome-wide association studies for skin-related phenotypes, including psoriasis, melanoma and vitiligo. Additionally, some meQTLs influence gene expression via mediation of expression quantitative trait loci effects in skin, including in genes linked to melanoma and psoriasis. Conclusions Our study is the first genome-wide DNA methylation heritability and meQTL analysis of whole skin, giving insights into the regulatory landscape of epigenomic variation in skin.

Unraveling genetic underpinnings of purine content in pork

The significance of purine base content as an important nutrition indicator in foods arises from its potential to trigger hyperuricemia or gout via high-purine diet. Livestock meats, including pork, generally contain moderate to high total purine content (TP). Recent research revealed substantial variations within and across pig breeds, implying genetic factors influencing this trait. Thus, this study aimed to unravel the genetic underpinnings governing purine base content in pork. The heritability estimates (h2) for the four purine traits ranged from 0.14 to 0.35. A total of 14, 36, 19 and 25 quantitative trait loci (QTLs) were identified for guanine, adenine, hypoxanthine, and TP, respectively. Our comprehensive gene set enrichment analysis and gene network analysis revealed 15 promising candidate genes intricately interwoven within diverse purine metabolism pathways, such as purine ribonucleotide metabolic process, purine nucleotide metabolism and transport, and purine salvage pathways, all contributing to TP. Strikingly, most genetic variants significantly associated with TP displayed analogous effects on multiple purine bases. Two distinct and highly significant QTLs (P < 10-12) emerged on Sus Scrofa chromosome (SSC) 12: one impacting guanine content and the other concurrently influencing adenine and hypoxanthine levels. The peak of the guanine QTL on SSC12 resided 1.1 kb downstream of the transmembrane protein 238 like (TMEM238L) gene and is encapsulated within a genomic segment characterized by the histone modification H3K27me3. Focused fine-mapping for the SSC12 QTL associated with adenine and hypoxanthine levels narrowed its scope to around 172 kb, encompassing the growth arrest specific 7 (GAS7) and myosin heavy chain 13 (MYH13) genes. However, the observed QTL effect was not attributed to any missense mutations within the two genes. This pioneering study unveils the genetic variations and candidate genes associated with purine content in livestock, laying a robust foundation for the selective breeding of pig lines with reduced purine base content.

Genome-Wide Association Study of Early Vigour-Related Traits for a Rice (Oryza sativa L.) japonica Diversity Set Grown in Aerobic Conditions.

Aerobic rice production is a relatively new system in which rice is direct-seeded and grown in non-flooded but well-watered conditions to improve water productivity. Early vigour-related traits are likely to be important in aerobic conditions. This study aimed to identify quantitative trait loci (QTL) and candidate genes associated with early vigour-related traits in aerobic conditions using a japonica rice diversity set. Field experiments and glasshouse experiments conducted under aerobic conditions revealed significant genotypic variation in early vigour-related traits. Genome-wide association analysis identified 32 QTL associated with early vigour-related traits. Notably, two QTL, qAEV1.5 and qAEV8, associated with both early vigour score and mesocotyl length, explained up to 22.1% of the phenotypic variance. In total, 23 candidate genes related to plant growth development and abiotic stress response were identified in the two regions. This study provides novel insights into the genetic basis of early vigour under aerobic conditions. Validation of identified QTL and candidate genes in different genetic backgrounds is crucial for future studies. Moreover, testing the effect of QTL on yield under different environments would be valuable. After validation, these QTL and genes can be considered for developing markers in marker-assisted selection for aerobic rice production.

Pangenome-Wide Association Study and Transcriptome Analysis Reveal a Novel QTL and Candidate Genes Controlling both Panicle and Leaf Blast Resistance in Rice

Cultivating rice varieties with robust blast resistance is the most effective and economical way to manage the rice blast disease. However, rice blast disease comprises leaf and panicle blast, which are different in terms of resistance mechanisms. While many blast resistant rice cultivars were bred using genes conferring resistance to only leaf or panicle blast, mining durable and effective quantitative trait loci (QTLs) for both panicle and leaf blast resistance is of paramount importance. In this study, we conducted a pangenome-wide association study (panGWAS) on 9 blast resistance related phenotypes using 414 international diverse rice accessions from an international rice panel. This approach led to the identification of 74 QTLs associated with rice blast resistance. One notable locus, qPBR1, validated in a F4:5 population and fine-mapped in a Heterogeneous Inbred Family (HIF), exhibited broad-spectrum, major and durable blast resistance throughout the growth period. Furthermore, we performed transcriptomic analysis of 3 resistant and 3 sensitive accessions at different time points after infection, revealing 3,311 differentially expressed genes (DEGs) potentially involved in blast resistance. Integration of the above results identified 6 candidate genes within the qPBR1 locus, with no significant negative effect on yield. The results of this study provide valuable germplasm resources, QTLs, blast response genes and candidate functional genes for developing rice varieties with enduring and broad-spectrum blast resistance. The qPBR1, in particular, holds significant potential for breeding new rice varieties with comprehensive and durable resistance throughout their growth period.

Mapping QTLs for blight resistance and morpho-phenological traits in inter-species hybrid families of chestnut (Castanea spp.).

Chestnut blight (caused by Cryphonectria parasitica), together with Phytophthora root rot (caused by Phytophthora cinnamomi), has nearly extirpated American chestnut (Castanea dentata) from its native range. In contrast to the susceptibility of American chestnut, many Chinese chestnut (C. mollissima) genotypes are resistant to blight. In this research, we performed a series of genome-wide association studies for blight resistance originating from three unrelated Chinese chestnut trees (Mahogany, Nanking and M16) and a Quantitative Trait Locus (QTL) study on a Mahogany-derived inter-species F2 family. We evaluated trees for resistance to blight after artificial inoculation with two fungal strains and scored nine morpho-phenological traits that are the hallmarks of species differentiation between American and Chinese chestnuts. Results support a moderately complex genetic architecture for blight resistance, as 31 QTLs were found on 12 chromosomes across all studies. Additionally, although most morpho-phenological trait QTLs overlap or are adjacent to blight resistance QTLs, they tend to aggregate in a few genomic regions. Finally, comparison between QTL intervals for blight resistance and those previously published for Phytophthora root rot resistance, revealed five common disease resistance regions on chromosomes 1, 5, and 11. Our results suggest that it will be difficult, but still possible to eliminate Chinese chestnut alleles for the morpho-phenological traits while achieving relatively high blight resistance in a backcross hybrid tree. We see potential for a breeding scheme that utilizes marker-assisted selection early for relatively large effect QTLs followed by genome selection in later generations for smaller effect genomic regions.

Identification of Two Novel QTL for Fusarium Head Blight Resistance in German Wheat Cultivar Centrum.

Fusarium head blight (FHB) is a devastating disease that occurs in warm and humid environments. The German wheat 'Centrum' has displayed moderate to high levels of FHB resistance in the field for many years. In this study, an F6:8 recombinant inbred line (RIL) population derived from cross 'Centrum' × 'Xinong 979' was evaluated for FHB response following point inoculation in five environments. The population and parents were genotyped using the GenoBaits Wheat 16 K Panel. Stable quantitative trait loci (QTL) associated with FHB resistance in 'Centrum' were mapped on chromosome arms 2DS and 5BS. The most effective QTL, located in 2DS, was identified as a new chromosome region represented by a 1.4 Mb interval containing 17 candidate genes. Another novel QTL was mapped in chromosome arm 5BS of a 5BS to 7BS translocation chromosome. In addition, two environmentally sensitive QTL were mapped on chromosome arms 2BL from 'Centrum' and 5AS from 'Xinong 979'. Polymorphisms of flanking phenotypic variance explained (PVE) markers (allele-specific quantitative PCR [AQP]) AQP-6 for QFhb.nwafu-2DS and 16K-13073 for QFhb.nwafu-5BS were validated in a panel of 217 cultivars and breeding lines. These markers could be useful for marker-assisted selection (MAS) of FHB resistance and provide a starting point for fine mapping and marker-based cloning of the resistance genes.

Integrative multi-omics analysis identifies genetically supported druggable targets and immune cell specificity for myasthenia gravis

BackgroundMyasthenia gravis (MG) is a chronic autoimmune disorder characterized by fluctuating muscle weakness. Despite the availability of established therapies, the management of MG symptoms remains suboptimal, partially attributed to lack of efficacy or intolerable side-effects. Therefore, new effective drugs are warranted for treatment of MG.MethodsBy employing an analytical framework that combines Mendelian randomization (MR) and colocalization analysis, we estimate the causal effects of blood druggable expression quantitative trait loci (eQTLs) and protein quantitative trait loci (pQTLs) on the susceptibility of MG. We subsequently investigated whether potential genetic effects exhibit cell-type specificity by utilizing genetic colocalization analysis to assess the interplay between immune-cell-specific eQTLs and MG risk.ResultsWe identified significant MR results for four genes (CDC42BPB, CD226, PRSS36, and TNFSF12) using cis-eQTL genetic instruments and three proteins (CTSH, PRSS8, and CPN2) using cis-pQTL genetic instruments. Six of these loci demonstrated evidence of colocalization with MG susceptibility (posterior probability > 0.80). We next undertook genetic colocalization to investigate cell-type-specific effects at these loci. Notably, we identified robust evidence of colocalization, with a posterior probability of 0.854, linking CTSH expression in TH2 cells and MG risk.ConclusionsThis study provides crucial insights into the genetic and molecular factors associated with MG susceptibility, singling out CTSH as a potential candidate for in-depth investigation and clinical consideration. It additionally sheds light on the immune-cell regulatory mechanisms related to the disease. However, further research is imperative to validate these targets and evaluate their feasibility for drug development.

Inheritance and genetic mapping of the first CPMMV tolerance locus in common bean

AbstractAlthough cowpea mild mottle virus (CPMMV) has been reported in Brazil since 1983, it has only become a significant concern for researchers and farmers in recent years. The objective of this work was to investigate the genetic basis of CPMMV tolerance, mapping and reporting the first loci associated with this trait in common bean (cv. BRS Sublime). Phenotypic assays were carried out on 180 individual plants (F2 generation) and 180 F2:3 progenies comprising 12 plants per family and their parents (BRS Sublime, tolerant parent × CNFCT 16207, susceptible parent). CPMMV was mechanically inoculated and symptoms were evaluated at 35 days after inoculation, using a 1–5 scoring scale. A linkage map was constructed using 1695 single‐nucleotide polymorphism (SNP) and SilicoDArT markers that segregated in the F2 and F2:3 generations as expected. Markers were distributed across 11 common bean chromosomes, resulting in a total length of 2864 cM, with an average distance between markers of 1.8 cM. Phenotypic observations revealed that tolerance in cv. BRS Sublime is controlled by a single dominant gene. The main effect quantitative trait locus (QTL; CPMMV.Pv08) associated with CPMMV tolerance was identified in the terminal region on chromosome 8 (Pv08). This QTL explained approximately 77% of phenotypic variation, indicating that the inheritance of tolerance to CPMMV is monogenic, controlled by a major locus. As far as we know, this study represents the first investigation into the inheritance and genetic mapping of CPMMV tolerance in common bean, with potential for the development of elite lines with multiple virus resistance/tolerance.

Quantitative trait loci and genomic prediction for grain sugar and mineral concentrations of cowpea [Vigna unguiculata (L.) Walp.

Development of high yielding cowpea varieties coupled with good taste and rich in essential minerals can promote consumption and thus nutrition and profitability. The sweet taste of cowpea grain is determined by its sugar content, which comprises mainly sucrose and galacto-oligosaccharides (GOS) including raffinose and stachyose. However, GOS are indigestible and their fermentation in the colon can produce excess intestinal gas, causing undesirable bloating and flatulence. In this study, we aimed to examine variation in grain sugar and mineral concentrations, then map quantitative trait loci (QTLs) and estimate genomic-prediction (GP) accuracies for possible application in breeding. Grain samples were collected from a multi-parent advanced generation intercross (MAGIC) population grown in California during 2016-2017. Grain sugars were assayed using high-performance liquid chromatography. Grain minerals were determined by inductively coupled plasma-optical emission spectrometry and combustion. Considerable variation was observed for sucrose (0.6-6.9%) and stachyose (2.3-8.4%). Major QTLs for sucrose (QSuc.vu-1.1), stachyose (QSta.vu-7.1), copper (QCu.vu-1.1) and manganese (QMn.vu-5.1) were identified. Allelic effects of major sugar QTLs were validated using the MAGIC grain samples grown in West Africa in 2017. GP accuracies for minerals were moderate (0.4-0.58). These findings help guide future breeding efforts to develop mineral-rich cowpea varieties with desirable sugar content.

Characterization of adaptation mechanisms in sorghum using a multireference back-cross nested association mapping design and envirotyping.

Identifying the genetic factors impacting the adaptation of crops to environmental conditions is of key interest for conservation and selection purposes. It can be achieved using population genomics, and evolutionary or quantitative genetics. Here we present a sorghum multireference back-cross nested association mapping population composed of 3,901 lines produced by crossing 24 diverse parents to 3 elite parents from West and Central Africa-back-cross nested association mapping. The population was phenotyped in environments characterized by differences in photoperiod, rainfall pattern, temperature levels, and soil fertility. To integrate the multiparental and multi-environmental dimension of our data we proposed a new approach for quantitative trait loci (QTL) detection and parental effect estimation. We extended our model to estimate QTL effect sensitivity to environmental covariates, which facilitated the integration of envirotyping data. Our models allowed spatial projections of the QTL effects in agro-ecologies of interest. We utilized this strategy to analyze the genetic architecture of flowering time and plant height, which represents key adaptation mechanisms in environments like West Africa. Our results allowed a better characterization of well-known genomic regions influencing flowering time concerning their response to photoperiod with Ma6 and Ma1 being photoperiod-sensitive and the region of possible candidate gene Elf3 being photoperiod-insensitive. We also accessed a better understanding of plant height genetic determinism with the combined effects of phenology-dependent (Ma6) and independent (qHT7.1 and Dw3) genomic regions. Therefore, we argue that the West and Central Africa-back-cross nested association mapping and the presented analytical approach constitute unique resources to better understand adaptation in sorghum with direct application to develop climate-smart varieties.

Interaction molecular QTL mapping discovers cellular and environmental modifiers of genetic regulatory effects

Bulk-tissue molecular quantitative trait loci (QTLs) have been the starting point for interpreting disease-associated variants, and context-specific QTLs show particular relevance for disease. Here, we present the results of mapping interaction QTLs (iQTLs) for cell type, age, and other phenotypic variables in multi-omic, longitudinal data from the blood of individuals of diverse ancestries. By modeling the interaction between genotype and estimated cell-type proportions, we demonstrate that cell-type iQTLs could be considered as proxies for cell-type-specific QTL effects, particularly for the most abundant cell type in the tissue. The interpretation of age iQTLs, however, warrants caution because the moderation effect of age on the genotype and molecular phenotype association could be mediated by changes in cell-type composition. Finally, we show that cell-type iQTLs contribute to cell-type-specific enrichment of diseases that, in combination with additional functional data, could guide future functional studies. Overall, this study highlights the use of iQTLs to gain insights into the context specificity of regulatory effects.

Multi-omics Mendelian randomization integrating GWAS, eQTL, and mQTL data identified genes associated with breast cancer.

Breast cancer (BC) remains a major disease posing a threat to women's health, but the underlying biological interpretation remains largely unknown. Here, we aimed to identify genes associated with breast cancer and analyze their pathophysiological mechanisms based on multi-omics Mendelian randomization (MR). Summary-data-based MR (SMR) was performed to estimate the causal effects of blood and breast mammary tissue expression quantitative trait loci (eQTLs) on BC. External validation analysis was used to validate the identified genes. Integration analyses BC GWAS summaries with eQTLs and DNA methylation QTLs (mQTLs) from the blood were conducted using SMR to prioritize putative blood genes and their regulatory elements associated with BC risk. Finally, two prior genes (ATG10 and RCCD1) from blood tissue reached significant levels in both BCAC (ATG10: ORBRCR = 0.91, PBRCR = 1.29 × 10-11; RCCD1: ORBRCR = 0.90, PBRCR = 3.72 × 10-15) and FinnGen cohorts (ATG10: ORFinnGen = 0.89, PFinnGen = 8.55 × 10-5; RCCD1: ORFinnGen = 0.89, PFinnGen = 2.38 × 10-8). Additionally, those two genes from breast tissues also replicated in both BCAC (ATG10: ORBRCR = 0.95, PBRCR = 1.02 × 10-9; RCCD1: ORBRCR = 0.87, PBRCR = 4.70 × 10-10) and FinnGen cohorts (ATG10: ORFinnGen = 0.93, PFinnGen = 2.38 × 10-4; RCCD1: ORFinnGen = 0.85, PFinnGen = 3.81 × 10-6). Sensitive analysis and external validation analysis validated those two identified genes. Multi-omics MR analysis showed that the SNP signals associated with ATG10 and RCCD1 were significant across the data from BC Genome-wide association study (GWAS), eQTL, and mQTL studies. In conclusion, we identified two priority genes that are potentially associated with BC. These findings improve our limited understanding of the mechanism of BC and shed light on the development of therapeutic agents for treating BC.