Dataset Information

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

ABSTRACT: Bulk tissue molecular quantitative trait loci (QTLs) have been the starting point for interpreting disease-associated variants, while 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 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. The interpretation of age iQTLs, however, warrants caution as the moderation effect of age on the genotype and molecular phenotype association may 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, may guide future functional studies. Overall, this study highlights iQTLs to gain insights into the context-specificity of regulatory effects.

SUBMITTER: Kasela S

PROVIDER: S-EPMC10326995 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Kasela Silva S Aguet François F Kim-Hellmuth Sarah S Brown Brielin C BC Nachun Daniel C DC Tracy Russell P RP Durda Peter P Liu Yongmei Y Taylor Kent D KD Craig Johnson W W Berg David Van Den DVD Gabriel Stacey S Gupta Namrata N Smith Joshua D JD Blackwell Thomas W TW Rotter Jerome I JI Ardlie Kristin G KG Manichaikul Ani A Rich Stephen S SS Graham Barr R R Lappalainen Tuuli T

bioRxiv : the preprint server for biology 20230629

Bulk tissue molecular quantitative trait loci (QTLs) have been the starting point for interpreting disease-associated variants, while 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 blood of individuals of diverse ancestries. By modeling the interaction between genotype and estimated cell type proportions, we demonstrate that cell ...[more]

PMID: 37425716

Similar Datasets

Project description:Autosomal recessive polycystic kidney disease (ARPKD) is caused by mutations in the PKHD1 gene in both humans and the orthologous PCK rat model. Although ARPKD results solely from PKHD1 mutations, the disease onset and severity are highly variable, indicating that other unknown genetic risk factor(s) modify ARPKD-associated phenotypes. To identify genetic modifiers of ARPKD severity, we created two genetically distinct Pkhd1 congenic rat strains on the Fawn-Hooded Hypertensive (FHH) and the Dahl S (SS) rat backgrounds (denoted FHH.Pkhd1 and SS.Pkhd1, respectively) that harbor the PCK-derived Pkhd1 allele. The FHH.Pkhd1 and SS.Pkhd1 strains had lower renal cyst formation at 30 days-of-age (5±2% and 8±2% cystic, respectively; P<0.001) compared to the PCK kidneys (26±4% cystic), which coincided with significantly reduced kidney weights in the FHH.Pkhd1 and SS.Pkhd1. Liver cyst formation and liver weight did not differ between PCK, FHH.Pkhd1, and SS.Pkhd1. These data indicated that the PCK genome harbors genetic modifier(s) of ARPKD severity that are not present in the FHH and SS genomes. Using high density SNP array genotyping and microarray expression analysis, we identified 50 potential modifiers of ARPKD severity in the PCK rat. Of these candidates, a damaging nonsynonymous variant in Nphp4 stood out as the most likely candidate based on variant segregation, protein modeling, network analysis, and gene ontology. Nphp4 is widely associated with the autosomal recessive cilliopathy and nephronopthisis, but had not been previously implicated in the molecular or cellular pathophysiology of ARPKD. Collectively, these data provide genetic evidence of disease modifier(s) in the PCK model of ARPKD and prioritized multiple candidates, including NPHP4, for further investigation in ARPKD pathogenesis. In this study, we used microarray to analyze transcript expression in the kidneys of 30 day old SD (n=4), PCK (n=4), FHH (n=4), FHH.Pkhd1 (n=4), SS (n=4), and SS.Pkhd1 (n=4). Samples were pooled and the pooled samples were run in triplicate. The 30 day timepoint was chosen because the differences in renal cyst formation between PCK, FHH.Pkhd1, and SS.Pkhd1 were greatest at this timepoint. To account for genetic strain differences that do not contribute to ARPKD severity, gene expression of each cystic rat strain was compared to its parental strain.

Project description:Colletotrichum lindemuthianum is a hemibiotrophic fungal pathogen that causes anthracnose disease in common bean. Despite the genetics of anthracnose resistance has been studied for a long time, few quantitative trait loci (QTLs) studies have been conducted on this species. The present work examines the genetic basis of quantitative resistance to races 23 and 1545 of C. lindemuthianum in different organs (stem, leaf and petiole). A population of 185 recombinant inbred lines (RIL) derived from the cross PMB0225 × PHA1037 was evaluated for anthracnose resistance under natural and artificial photoperiod growth conditions. Using multi-environment QTL mapping approach, 10 and 16 main effect QTLs were identified for resistance to anthracnose races 23 and 1545, respectively. The homologous genomic regions corresponding to 17 of the 26 main effect QTLs detected were positive for the presence of resistance-associated gene cluster encoding nucleotide-binding and leucine-rich repeat (NL) proteins. Among them, it is worth noting that the main effect QTLs detected on linkage group 05 for resistance to race 1545 in stem, petiole and leaf were located within a 1.2 Mb region. The NL gene Phvul.005G117900 is located in this region, which can be considered an important candidate gene for the non-organ-specific QTL identified here. Furthermore, a total of 39 epistatic QTL (E-QTLs) (21 for resistance to race 23 and 18 for resistance to race 1545) involved in 20 epistatic interactions (eleven and nine interactions for resistance to races 23 and 1545, respectively) were identified. None of the main and epistatic QTLs detected displayed significant environment interaction effects. The present research provides essential information not only for the better understanding of the plant-pathogen interaction but also for the application of genomic assisted breeding for anthracnose resistance improvement in common bean through application of marker-assisted selection (MAS).

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets