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PubMed2025

Dissecting seed composition QTL from wild soybean: fine-mapping, candidate gene identification, and evaluation of introgression effects on agronomic performance.

Seed composition QTL from wild soybean were confirmed and validated in two genetic backgrounds across multiple environments, candidate genes were identified, and agronomic performance of backcross introgression lines was evaluated. Through selection for soybean yield, breeders have inadvertently reduced seed protein content and increased oil due to phenotypic and genetic correlations between these three traits. Therefore, identifying alleles that increase protein without adversely affecting oil and yield is of interest for breeders and the entire soybean value chain. Previously, a G. max × G. soja population was used to map a protein-associated region to ~ 4.6 Mbp on chromosome (Chr) 14. The G. soja allele significantly increased protein 6.5-7.2 g kg-1, without significantly decreasing oil. Additionally, two oil quantitative trait loci (QTL) were reported on Chrs 8 and 14. In this study, we aimed to confirm the Chr 14 protein QTL, evaluate QTL effects on seed composition and agronomic performance, and further fine-map to identify candidate genes. We validated and fine-mapped the Chr 14 protein QTL to a 0.6 Mbp region in a different genetic background, where the G. soja allele significantly increased protein by 9.3 g kg-1. Further, we confirmed the Chr 14 oil QTL linked to the protein QTL and the Chr 8 oil QTL. Chr 14 protein QTL effects on agronomic traits were evaluated in a backcross population across eight environments. The QTL significantly increased protein content, without significantly impacting oil, maturity, or plant height. While the QTL impacted yield and lodging, its effect and significance varied within environments. The candidate genes identified for these three validated seed composition QTL, along with additional molecular markers developed, offer valuable resources for improving seed composition in soybean breeding programs.

Quantitative Trait Loci↗

PubMed2024

Complementation testing identifies genes mediating effects at quantitative trait loci underlying fear-related behavior.

Knowing the genes involved in quantitative traits provides an entry point to understanding the biological bases of behavior, but there are very few examples where the pathway from genetic locus to behavioral change is known. To explore the role of specific genes in fear behavior, we mapped three fear-related traits, tested fourteen genes at six quantitative trait loci (QTLs) by quantitative complementation, and identified six genes. Four genes, Lamp, Ptprd, Nptx2, and Sh3gl, have known roles in synapse function; the fifth, Psip1, was not previously implicated in behavior; and the sixth is a long non-coding RNA, 4933413L06Rik, of unknown function. Variation in transcriptome and epigenetic modalities occurred preferentially in excitatory neurons, suggesting that genetic variation is more permissible in excitatory than inhibitory neuronal circuits. Our results relieve a bottleneck in using genetic mapping of QTLs to uncover biology underlying behavior and prompt a reconsideration of expected relationships between genetic and functional variation.

Animals↗

PubMed2026

Diploids derived from polyploids: genetic characteristics of four novel interspecific Sorghum populations.

Polyploidy has repeatedly shaped grass evolution, yet direct observations of how polyploid-derived chromosomes behave when returned to diploidy remain rare. Interspecific crosses between diploid Sorghum bicolor and tetraploid hybrids derived from Sorghum halepense generate mixed-ploidy progeny, providing an opportunity to examine chromosome transmission during the early stages of diploidization. Using genome-wide SNP markers, we characterized chromosomal inheritance patterns in 2 diploid and 2 tetraploid families derived from these crosses. Genotype-dosage profiles alone distinguished diploids from tetraploids with complete accuracy, reflecting strong ploidy-dependent differences in dosage-class distributions. Although diploid progeny retained much of the halepense-derived genomic background, several genomic intervals exhibited extended, nonrandom runs of S. bicolor homozygosity that remained polymorphic in corresponding tetraploid populations. These patterns, together with recurrent segregation distortion across independent families, suggest that the transition from tetraploidy to diploidy can expose allelic combinations that differ in transmission or viability. Analyses of flowering time further indicated that diploid and tetraploid derivatives possess distinct genomic architectures, with major association peaks occurring in different chromosomal regions across ploidy levels. Collectively, these results indicate that early diploidization involves nonrandom retention and loss of parental haplotypes shaped by both selective and structural constraints. The diploid extractions characterized here provide a rare empirical system for investigating the early stages of diploidization and a practical framework for studying and eventually mobilizing polyploid-derived variation for sorghum germplasm development. However, broader integration into elite breeding programs will require additional evaluation of cross-fertility, meiotic behavior, and chromosomal stability across diverse breeding backgrounds.

Sorghum↗

PubMed2026

Multi-omics analysis identifies key genes and functional loci affecting teat number in American Large White and Landrace pigs and their application in optimizing genomic selection models.

BACKGROUND: Teat number is a crucial economic trait in pigs. It directly affects the ability of sows to lactate, which in turn influences the survival and health of piglets. The teat number of French Large White pigs is close to 16, while the teat number of American Large White and Landrace pigs is about 14. In order to improve the teat number of American Landrace and Large White pigs through molecular approaches and precise breeding techniques, we genotyped 2,131 American Landrace and 4,564 American Large White with teat number phenotype using a 50 K SNP chip. Then, the SNP-chip data was imputed to the level of whole-genome sequencing (iWGS). Based on iWGS data, we conducted GWAS to identify novel, significant SNPs associated with teat number and to incorporate them into genomic selection. RESULTS: In Landrace pigs, significant SNPs for TTN mapped to SSC2, SSC7, SSC8, and SSC14; the SSC8 and SSC14 effects are novel. LTN mapped to SSC7, RTN to SSC7 and SSC8. The lead SSC7 SNP explained 2.60% of TTN phenotypic variance. In Large White pigs, significant SNPs were detected on SSC7 and SSC10 for TTN; SSC7, SSC10, and SSC12 for LTN; and SSC7 and SSC10 for RTN. The most significant locus on SSC7 accounted for 2.99% of the phenotypic variance in TTN. Additionally, a multi-population meta-analysis detected significant novel SNPs for LTN on SSC1 and SSC8. By utilizing Bayesian fine mapping, the most precise QTL confidence interval on SSC7 for both TTN and RTN in Large White pigs was reduced to 40 kb. By integrating functional gene annotation with RNA-seq and ATAC-seq data from Erhualian and Bamaxiang pigs mammary placodes at embryonic day 26, we prioritized PTPN13, TRPV3, ZDHHC13, and BRD2 as novel candidate genes for teat number. We then incorporated the significant SNPs to GBLUP and benchmarked genomic-selection accuracy. In both breeds, fitting the top SNP as fixed maximized prediction for TTN and RTN, whereas treating all significant loci as an additional random effect optimized LTN. CONCLUSIONS: Our findings provide a theoretical basis for dissecting new key genes affecting teat number and for advancing molecular breeding of teat number in pigs.

Animals↗

PubMed2026

Exploring genomic regions regulating the liver transcriptome and energy homeostasis in pigs.

In pigs, energy homeostasis has an impact on meat quality and health. In a Duroc pig population, 30 quantitative trait locus (QTL) regions associated with fatty acid (FA) composition in adipose tissue, plasma, liver and muscle were previously identified. Mapping of expression quantitative trait locus (eQTL) regions will provide a molecular hypothesis for genotype-phenotype interactions and may allow the identification of shared causal variants, key to increasing our understanding of the genetic regulation of FA composition and energy homeostasis. However, gene expression is impacted by environmental factors, while individual-level allelic imbalance (AI) can be more reliable and can be surveyed via allelic-specific expression (ASE) analysis. Furthermore, treatment of ASE as a quantitative trait allows the identification of allele-specific expression quantitative trait loci (aseQTLs), which are variants whose heterozygosity is linked to the AI of a nearby single-nucleotide polymorphism (SNP), pointing to regulatory elements. In this study, liver was selected as a key metabolic hub with an important role in the regulation of energy homeostasis, and 310 liver RNA sequencing samples were analysed using a combination of (1) eQTL mapping, (2) ASE analysis, and (3) aseQTL mapping methods. A total of 2 188 eQTL regions were identified, mostly cis-eQTL regions (73.17%). ASE analysis reported 1 964 ASE SNPs, associated with 633 genes. Finally, aseQTL mapping reported 64 172 aseQTL, associated with the AI of 31 genes. Colocalisation analysis combined with ASE analysis showed that the expression of FADS1 and FADS2 genes is associated with the polyunsaturated FA composition in several tissues, where microRNA regulation may be present. Finally, in the DGAT2 gene, annotated in a QTL region associated with multiple FAs in adipose tissue, ASE revealed allelic imbalance in the 3' untranslated region (UTR) of this gene. Allelic differential expression can be caused by a 13-bp insertion affecting messenger RNA stability, previously described, exemplifying how allelic imbalance is caused by a post-transcriptional regulatory mechanism undetectable by eQTL mapping. Furthermore, aseQTLs were associated with this gene, linked to a previously identified copy number variant not yet associated with DGAT2 expression. These results demonstrate how ASE analysis and aseQTL mapping can complement eQTL mapping, as they resolved a complex region affected by allelic heterogeneity, a main confounding effect of QTL mapping. In conclusion, the combination of eQTL mapping, ASE analysis and aseQTL mapping allowed the characterisation of the regulation of liver gene expression, improving our understanding of the genetic determinism of energy homeostasis.

Allele-specific expression↗

PubMed2025

Genetic basis and role of exotic accessions in cultivated cotton fiber quality improvement.

Exotic Gossypium accessions still harbor QTL‑validated alleles that, combined with CRISPR pyramiding and genomic selection, can break the entrenched fiber length-strength trade‑off. Cotton's four independent domestications twice in diploids and twice in allotetraploids offer a natural experiment in fiber improvement. Synthesizing three decades of data, we chart how polyploidy, selection and modern breeding have repeatedly reshaped the Gossypium genome. More than 15,000 quantitative trait locus (QTL) and genome wide association mapping studies (GWAS) hits converge on a handful of chromosomal "hotspots"; new MAGIC, NAM, NIL and long-read resources now narrow these peaks to < 200 kb, resolving causal genes such as GhHOX3, GhZF14 and GhMYB7. Multi-omics evidence links auxin, ethylene, gibberellin, brassinosteroid and strigolactone signaling to HDZIP IV, MYB, bHLH/HLH and ERF networks that drive fiber initiation, extreme cell elongation and cellulose deposition. Population genomics shows that ~ 40% of favorable fiber alleles are fixed in elite Gossypium hirsutum, yet wild diploids and landraces still harbor variants that could break the length strength trade-off. We propose a three-step roadmap genomic selection, CRISPR gene pyramiding and accelerated introgression to expand cotton's genetic base and deliver fibers suited to sustainable textile demands.

Gossypium↗

PubMed2026

Genetic diversity of Collaborative Cross mice implicates FFAR3 as a target for ILC2 anti-inflammatory reprogramming.

Pulmonary group 2 innate lymphoid cells (ILC2s) are key drivers of Type 2 inflammation in diseases like asthma, yet the molecular mechanisms regulating their function are incompletely understood. Using the genetically diverse Collaborative Cross (CC) mouse panel, we mapped a quantitative trait locus (QTL) that governs ILC2 prevalence in the lung after aeroallergen exposure. This QTL induces a large population of ILC2s in the lung that are resistant to activation and have diminished Type 2 effector function. We identified free-fatty acid receptor 3 (Ffar3) as a gene responsible for this effect and demonstrated that FFAR3 signaling reprograms ILC2s to an anti-inflammatory state by promoting their survival, reducing Type 2 cytokine production, and enhancing IL-10 expression. This anti-inflammatory state is dependent on IL-2 signaling, is characterized by decreased ST2 expression, and is distinct from previously described IL-10-producing ILC2 phenotypes. FFAR3-dependent reprogramming is mediated by epidermal growth factor receptor (EGFR) upregulation, and FFAR3's anti-inflammatory effect is partially conserved in human ILC2s.

Animals↗

PubMed2026

Meta-QTL Analysis Reveals Consensus Genomic Regions and Candidate Genes for Resistance to Sudden Death Syndrome in Soybean.

Sudden death syndrome (SDS), caused by Fusarium virguliforme, is one of the most economically important diseases limiting soybean production worldwide. Although numerous quantitative trait loci (QTL) associated with SDS resistance have been reported, inconsistencies among mapping populations, marker systems, and experimental conditions have hindered the identification of robust resistance loci for soybean improvement. In this study, a comprehensive meta-analysis was conducted to integrate published QTL and identify stable consensus genomic regions associated with SDS resistance. After a systematic literature survey and data curation, 153 QTL derived from 14 linkage-mapping studies were analyzed using a custom R-based workflow, resulting in the identification of 23 consensus meta-QTL (MQTL) distributed across 17 chromosomes. Several MQTL, particularly those located on chromosomes 6, 8, 18, and 20, were supported by multiple independent studies and represented major genomic hotspots for SDS resistance. Physical localization and functional annotation of these MQTL identified 217 candidate genes, including genes predicted to be involved in plant defense, signal transduction, transcriptional regulation, and secondary metabolism. Gene Ontology enrichment analysis identified response to salicylic acid as the only biological process that remained significant after FDR correction, whereas Kyoto Encyclopedia of Genes and Genomes pathway analysis did not identify significantly enriched pathways. Independent support using five published genome-wide association studies further supported several MQTL, especially those on chromosomes 6, 18, and 20, thereby increasing confidence in these genomic regions. The identified MQTL and prioritized candidate genes provide potential genomic resources for future marker development, improvement applications, and functional validation aimed at improving soybean resistance to SDS.

Fusarium virguliforme↗

PubMed2026

First genomic insights into the introgression of almond PPV-Marcus resistance into peach.

AIM: Sharka, caused by Plum pox virus (PPV), is one of the most damaging viral diseases of stone fruit crops, with peach among the most susceptible cultivated Prunus species. Almond is a promising source of resistance, but its genetic architecture and expression in a peach genetic background remain largely unknown. This study aimed to construct parental genetic linkage maps and identify genomic regions associated with PPV response in almond × peach interspecific populations. METHODS: Progenies derived from the almond cultivars 'Del Cid', 'Garrigues', and 'Mono' were evaluated by RT-PCR after graft inoculation with the PPV-Marcus (PPV-M) strain over consecutive infection cycles. Phenotypic data were summarized for each genotype using best linear unbiased estimates (BLUEs). High-density SNP almond and peach arrays were used to construct parental maps for 'Garrigues' and 'Mono' and perform quantitative trait locus (QTL) analysis. RESULTS: Phenotypic variation was observed among and within families. 'Del Cid'-derived progenies showed the greatest resistance, 'Garrigues'-derived progenies displayed intermediate responses, and 'Mono'-derived progenies showed greater susceptibility and variability. The parental maps covered 546.69 cM in 'Mono' and 521.72 cM in 'Garrigues', with average intervals of 0.61 and 1.26 cM per unique marker position, respectively, and showed strong collinearity with the reference genome. QTL associated with PPV-M response were detected on linkage groups (LG) 1 and 6 in 'Garrigues' and LG2 in 'Mono'. The main QTL in 'Garrigues' peaked near 22.39 Mb on LG1, whereas the 'Mono' QTL was located at 22.27-22.62 Mb on LG2; a weaker QTL was detected near 25.38 Mb on LG6 in 'Garrigues'. The results support a quantitative and genetic-background-dependent architecture of PPV resistance. CONCLUSION: This study provides the first evidence of genomic regions associated with PPV-Marcus response in almond × peach populations. The detected QTLs provide an initial basis to support the introgression of almond-derived resistance into peach breeding material.

Prunus↗

PubMed2025

Candidate genes at the Rmi1 locus for resistance to Meloidogyne incognita in soybean.

The RKN resistance locus Rmi1 was fine-mapped to two genes on chromosome 10, a glycosyl hydrolase family 9 β-1,4-endoglucanase gene and a type I pectin methylesterase gene. Root-knot nematodes (Meloidogyne spp.) are a serious threat to soybean production in the southeast USA, with yield losses of more than $165 million in 2023. Development and deployment of resistant soybean cultivars is the most effective strategy for managing these nematode pests; however, the identity of the resistance genes and underlying mechanism of resistance remains obscure. An additive resistance gene, Resistance to M. incognita-1 (Rmi1), to the predominant species, was first identified in soybean cultivar Forrest but never mapped to a genomic region. Multiple mapping studies have identified a major quantitative trait locus (QTL) with additive action on chromosome 10. In this study, a population consisting of 170 F2:3 families derived from a cross of Bossier (susceptible) × Forrest (resistant) was initially used to confirm that Rmi1 is in the chromosome 10 QTL. Subsequently, 884 F5:6 recombinant inbred lines (RILs) derived from the same cross were used to fine-map the Rmi1 causal gene(s) to two genes - a β-1,4-endoglucanase (Glyma.10G017000, EG) and a pectin methylesterase/methylesterase inhibitor (Glyma.10G017100, PME1). Both gene candidates have the potential to play a role in the resistance response to M. incognita. Both gene promoters harbor SNPs and indels and the encoded proteins exhibit amino acid polymorphisms, including a premature stop in PME1 of resistant soybeans. Additionally, both genes show a higher expression level in susceptible roots compared to resistant roots in the absence of infection. This suggests that Rmi1 may confer one or more pre-existing differences related to cell wall modification in soybean roots, ultimately leading to a decrease in susceptibility.

Tylenchoidea↗

PubMed2025

Genome wide association study unveils the genetic basis of Orobanche crenata resistance in pea.

GWAS using DArTseq markers identified novel resistance sources against parasitic broomrape in pea, elucidating candidate genes for marker-selected breeding as leverage for cultivar development and efficient disease control to enhance food security. Crenate broomrape (Orobanche crenata) is an important obligate root parasitic weed that causes severe yield losses in pea (Pisum sativum) production. O. crenata is difficult to eradicate in pea fields due to its high resilience and prolific seed boom capable of hibernating in soils for decades. Existing control strategies are not cost effective in low input legumes like pea. The most efficient ecofriendly mode of control is using resistant cultivars. Quantitative trait loci (QTL) studies based on bi-parental mapping has guided O. crenata resistance discovery, albeit their deployment in pea breeding is hindered by low marker resolution and large genetic distance. This study presents the first genome-wide association study (GWAS) on O. crenata resistance in pea, utilizing 324 diverse accessions and 26,045 diversity array technology sequence (DArTseq) markers. Phenotyping was performed over four seasons under field conditions using alpha lattice design. Results showed a strong phenotypic variation with an environmental influence on O. crenata infection. Novel resistance sources were identified mainly within the wild Pisum fulvum and P. sativum subsp. elatius. GWAS with two models yielded a total of 73 marker-trait associations with Chromosome 5 as major hotspot. Interestingly, some linked markers were detected in close proximity to four previous O. crenata resistance QTL. DArTseq markers identified 24 putative candidate genes participating in different cellular processes, including vesicle trafficking and transports, deoxyribonucleic acid transcription regulation, and defense including some leucine rich repeat receptor-like kinases. These results provide a valuable genetic resource for O. crenata resistance and a step toward its effective sustainable management-to enhance genetic diversity and cultivar improvement for food security.

Pisum sativum↗

PubMed2026

Selection of GhTT2-A07 promoter enhances fiber quality in improved cotton varieties.

Modern cultivated cotton fibers are predominantly white with enhanced quality compared to their wild ancestors. However, the molecular mechanisms and evolutionary drivers linking fiber color to quality remain least focused. In this study, we identified FQC1 (Fiber Quality and Color 1), a major quantitative trait locus (QTL) on chromosome A07 that concurrently regulates both fiber quality and pigmentation. Through map-based cloning, we revealed that Gossypium hirsutum TRANSPARENT TESTA2-A07 (GhTT2-A07), an R2R3-MYB transcription factor, resides within this locus. GhTT2-A07 modulates fiber development by directly activating genes in the general phenylpropanoid pathway, thereby promoting the metabolic flux toward downstream secondary metabolites. Variations in the GhTT2-A07 promoter led to its reduced expression in modern white cotton cultivars. This down-regulation suppresses the accumulation of S/G/H-type lignin monomers and proanthocyanidins, resulting in altered secondary cell wall composition and ultimately enhancing the quality of mature white fibers. Population genetic analyses further indicate that the white-fiber allele GhTT2-A07W has been fixed in modern breeding genotypes, underscoring the impact of artificial selection during cotton domestication. Overall, our study elucidates the biochemical and molecular mechanisms underlying fiber quality and pigmentation in cotton, clarifies the selection criteria for high-quality white fibers in modern cultivars, and provides a theoretical basis for future targeted genetic improvement of cotton fibers.

Alleles↗

PubMed2026

Quantitative trait loci mapping of gene expression and chromatin accessibility in primary fibroblasts reveals shared allelic effects between Latin American and European ancestries.

BACKGROUND: Quantitative Trait Locus (QTL) analysis of molecular data has identified genetic variants associated with traits such as gene expression, and colocalization of these functional QTL with GWAS risk loci has offered insights into the genetic basis of human disease. We employed gene expression (RNA-seq) and chromatin accessibility (ATAC-seq) obtained from human primary fibroblasts to investigate quantitative trait loci (QTLs) in cohorts ascertained for bipolar disorder of European (n = 150) and Latin American (n = 96) ancestries. RESULTS: Leveraging data from three countries of origin (The Netherlands, Colombia, Costa Rica) within our cohort, we characterized differences among individuals at the SNP, gene, and accessible-chromatin levels to compute ancestry-specific expression (e)QTLs and chromatin-accessibility (ca)QTLs. Across ancestries, we observed R2 ≥ 0.93 for eQTL effect sizes and R2 ≥ 0.95 for caQTLs, indicating a high degree of concordance. Integrating chromatin data with expression and genotype information enabled precise fine-mapping of eQTLs, yielding 203 genes with high-confidence (posterior probability > 90%) candidate regulatory pathways. In downstream analyses, transcriptome-wide (TWAS) and chromatin-wide (CWAS) association studies with brain- and skin-related GWAS identified 36 TWAS-significant genes and 77 CWAS-significant open chromatin regions. CONCLUSIONS: These findings underscore the shared genetic regulatory mechanisms across European and Latin American ancestries, while demonstrating that ancestry-specific reference panels enhance the accuracy of TWAS and CWAS in diverse populations. More broadly, this study highlights the value of paired multi-omic datasets from diverse cohorts for interpreting disease-associated genetic variation.

Humans↗

PubMed2025

Development of recombinant inbred lines and QTL analysis of plant height and fruit shape-related traits in Cucurbita pepo L.

UNLABELLED: Zucchini (Cucurbita pepo subsp. pepo) stands as an economically vital crop in China. In zucchini breeding, plant architectural patterns and fruit morphological characteristics serve as pivotal traits. In this study, we employed quantitative trait locus (QTL) analysis using recombinant inbred lines (RILs) derived from two distinct inbred lines, JinGL (subsp. ovifera) and HM-S2 (subsp. pepo), in conjunction with a high-density genetic map. Our investigation focused on ten QTLs associated with six horticulturally significant traits, including hypocotyl length (HL), plant height (PH), and four fruit-related traits: fruit length (FL), fruit diameter (FD), fruit shape index (FSI), and fruit weight (FW). The QTLs governing HL and PH were mapped to Chr03/LG10 and named qhl3.1 and qph3.1, respectively. The candidate gene Cp4.1LG10g05910/CpDw for qph3.1 was successfully identified. Additionally, three novel QTLs related to fruit size and shape were discovered. Among them, qfsi8.1/qfl8.1, demarcated by Marker238258 and Marker240069 on Chromosome 08/Linkage group 17 (Chr08/LG17), is a new major QTL regulating the fruit shape of zucchini. Through genomic insertion-deletion (InDel) and qRT-PCR analyses, we predicted genes within the qfsi8.1/qfl8.1 candidate interval, uncovering Cp4.1LG17g02030/CpIAA12 and Cp4.1LG17g02010/CpCalB as potential candidate genes. We developed molecular markers tightly linked to qph3.1 and qfl8.1 and validated them in 171 and 224 Cucurbita pepo germplasms, achieving accuracy rates of 96% and 100%, respectively. This study deepens our understanding of the genetic basis of key traits and provides valuable references for molecular breeding in Cucurbita pepo. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11032-025-01592-y.

Cucurbita pepo↗

PubMed2026

The MexMAGIC population reveals the genetic architecture of traits exhibiting clinal variation in Mexican native maize.

Defining the genetic basis of local adaptation is a key goal of evolutionary biology and crop improvement. Theory predicts that when selective pressures follow differences in the environment, a cline will be established. Clines can be exploited to uncover adaptive variation by association of alleles with the environment. However, monotonic phenotypic change over a cline is not necessarily mirrored in the behavior of genetic variants and population structure can further complicate analysis. To study genetic and phenotypic variation across the environment, we developed a multi-parent advanced generation inter-cross (MAGIC) population using eight Mexican native maize (Zea mays L. ssp. mays) varieties sourced from distinct agroecological zones. We evaluated the population in a common garden in Mexico and mapped tassel branching and flowering time, two traits that exhibit clinal variation. Variation in tassel branching was dominated by a single QTL with allele effects aligning to a negative elevational cline. By contrast, allele effects associated with 11 identified flowering time QTL were not consistently correlated with any one source environmental factor. Our observations support the prediction that genotype-environment association will be strongest under simple genetic architecture, although, even then, analysis in native populations may be confounded by population structure.

MAGIC↗

PubMed2004

Use of a dense single nucleotide polymorphism map for in silico mapping in the mouse.

Rapid expansion of available data, both phenotypic and genotypic, for multiple strains of mice has enabled the development of new methods to interrogate the mouse genome for functional genetic perturbations. In silico mapping provides an expedient way to associate the natural diversity of phenotypic traits with ancestrally inherited polymorphisms for the purpose of dissecting genetic traits. In mouse, the current single nucleotide polymorphism (SNP) data have lacked the density across the genome and coverage of enough strains to properly achieve this goal. To remedy this, 470,407 allele calls were produced for 10,990 evenly spaced SNP loci across 48 inbred mouse strains. Use of the SNP set with statistical models that considered unique patterns within blocks of three SNPs as an inferred haplotype could successfully map known single gene traits and a cloned quantitative trait gene. Application of this method to high-density lipoprotein and gallstone phenotypes reproduced previously characterized quantitative trait loci (QTL). The inferred haplotype data also facilitates the refinement of QTL regions such that candidate genes can be more easily identified and characterized as shown for adenylate cyclase 7.

Adenylyl Cyclases↗

PubMed2025

Quantitative trait loci for Globodera pallida resistance derived from wild potato species Solanum gourlayi.

Globodera pallida is a major pest that is responsible for huge losses in potato yields worldwide. Expanding the gene pool of cultivated potatoes with clones resistant to this pest is made possible by searching for resistance genes in wild Solanum species. The aim of this study was to identify quantitative trait loci (QTLs) for potato resistance to Globodera pallida derived from Solanum gourlayi. A resistant diploid potato clone, Sg 2/7 (Solanum gourlayi, accession CGN17592), was crossed with a susceptible potato hybrid clone, DW 94-4235, to generate an F1 mapping population. All clones were tested for nematode resistance using G. pallida, pathotypes Pa2 and Pa3, in 2 or 3 years (2017-2019), respectively. Diversity Array Technology (DArTseq) was used for genotyping and genetic map construction. QTLs for nematode resistance were identified on potato chromosomes II, IV, V, VI, VII, X, XI, and XII, explaining from 10.1 to 21.5% of phenotypic variance. The most significant QTL for resistance to G. pallida pathotype Pa2 was identified on chromosome XII, explaining 20.9% of the phenotypic variance in the dataset from 2017. The most significant QTL for resistance to the G. pallida Pa3 pathotype was identified on chromosome VI, with a CAPS marker Exp928 in its peak, explaining 21.5% of the phenotypic variance in the dataset from 2017. The novel QTLs for resistance to S. gourlayi may be useful for breeding resistant potato cultivars, further studies of candidate genes, and host responses of potato to G. pallida infection.

Quantitative Trait Loci↗

PubMed2026

Multi-omics Mendelian Randomization Prioritizes Neutrophil Extracellular Trap-related Genes Associated with Atrial Fibrillation Risk.

BACKGROUND: Neutrophil extracellular traps (NETs) participate in thrombosis, inflammation, and cardiovascular remodeling, yet whether NET-related genes (NRGs) are associated with atrial fibrillation (AF) risk across multiple molecular layers remains unclear. This study used a multiomics Mendelian randomization framework to prioritize NRGs supported by methylation, expression, and protein quantitative trait loci (QTL) data. METHODS: Genome-wide significant cis instruments (P < 5 × 10-8) were obtained for 90 methylation QTLs (mQTLs), 100 expression QTLs (eQTLs), and 38 protein QTLs (pQTLs) mapped to 137 literature- curated NRG entries. Summary-data-based Mendelian randomization (SMR) coupled with the heterogeneity in dependent instruments (HEIDI) test was applied using whole-blood mQTL data (n = 1,980), eQTLGen blood eQTL data (n = 31,684), and deCODE plasma pQTL data (n = 35,559). AF outcome data were obtained from a meta-analysis including 60,620 cases and 970,216 controls of European ancestry. RESULTS: At the methylation level, 21 CpG-feature associations across 13 genes remained significant after HEIDI filtering and false discovery rate (FDR) correction. Expression-level analysis identified eight significant gene-AF associations, whereas protein-level analysis identified seven significant features representing five unique proteins. Cross-omics integration prioritized C3, MAPK3, and STAT3 as Tier 1 genes, CTSC, LPAR3, and THBD as Tier 2 genes, and fourteen additional genes as Tier 3 candidates. C3 showed risk-increasing protein-level associations together with multiple significant CpG signals, whereas MAPK3 and STAT3 showed directionally protective expression/protein or methylation/protein patterns. DISCUSSION: The cross-omics convergence on C3, MAPK3, and STAT3 is consistent with complement activation, immune-fibrotic signaling, and cytokine-regulatory pathways implicated in AF biology, but the findings should be interpreted as genetic prioritization rather than definitive intervention-ready causality. CpG-level heterogeneity at the C3 locus and the blood/plasma origin of the QTL resources further support a cautious interpretation. Modest colocalization support and the unresolved possibility of pQTL sample overlap further support this cautious, hypothesis-generating interpretation. CONCLUSION: Multi-omics SMR prioritizes C3, MAPK3, and STAT3 as the most consistently supported NET-related genes associated with AF risk. These findings provide a framework for atrialtissue replication and mechanistic validation of NET-related pathways in AF.

Atrial fibrillation↗