ArticleBMC genomics2018
Comparing allele specific expression and local expression quantitative trait loci and the influence of gene expression on complex trait variation in cattle.
Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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26 citing papers in PubMed, 44 citations in OpenAlex.
- Article
- Comprehensive Multi-omics Analysis of Regulatory Variants for Body Weight in Cattle.Genomics, proteomics & bioinformatics · 2025Article
- Characterizing differences in the muscle transcriptome between cattle with alternative LCORL-NCAPG haplotypes.BMC genomics · 2025Article
- Genome-wide allele-specific expression in multi-tissue samples from healthy male baboons reveals the transcriptional complexity of mammals.Cell genomics · 2025Article
- A comprehensive analysis of allele-specific expression and transcriptomic profiling in pig limbic and endocrine tissues.Frontiers in molecular neuroscience · 2025Article
- Integrating multi-layered biological priors to improve genomic prediction accuracy in beef cattle.Biology direct · 2024Article
- Article
- Calpain 1 gene expression in liver tissue and the association of novel calpain 1 single-nucleotide polymorphisms (SNPs) with meat quality in Bali cattle.Archives animal breeding · 2024Article
- Whole genome sequencing identified genomic diversity and candidated genes associated with economic traits in Northeasern Merino in China.Frontiers in genetics · 2024Article
- An organism-wide ATAC-seq peak catalog for the bovine and its use to identify regulatory variants.Genome research · 2023Article
- Article
- Genetic variation in histone modifications and gene expression identifies regulatory variants in the mammary gland of cattle.BMC genomics · 2022Article
- Cis-eQTL Analysis and Functional Validation of Candidate Genes for Carcass Yield Traits in Beef Cattle.International journal of molecular sciences · 2022Article
- Quantification of mutant-allele expression at isoform level in cancer from RNA-seq data.NAR genomics and bioinformatics · 2022Article
- Genomic reaction norms inform predictions of plastic and adaptive responses to climate change.The Journal of animal ecology · 2022Review
- Airpart: interpretable statistical models for analyzing allelic imbalance in single-cell datasets.Bioinformatics (Oxford, England) · 2022Article
- Article
- Evidence for and localization of proposed causative variants in cattle and pig genomes.Genetics, selection, evolution : GSE · 2021Review
- Expression quantitative trait loci in sheep liver and muscle contribute to variations in meat traits.Genetics, selection, evolution : GSE · 2021Article
- Unravelling the complex genetics of common kidney diseases: from variants to mechanisms.Nature reviews. Nephrology · 2020Review
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8 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe mutations changing the expression level of a gene, or expression quantitative trait loci (eQTL), can be identified by testing the association between genetic variants and gene expression in multiple individuals (eQTL mapping), or by comparing the expression of the alleles in a heterozygous individual (allele specific expression or ASE analysis). The aims of the study were to find and compare ASE and local eQTL in 4 bovine RNA-sequencing (RNA-Seq) datasets, validate them in an independent ASE study and investigate if they are associated with complex trait variation.
resultsWe present a novel method for distinguishing between ASE driven by polymorphisms in cis and parent of origin effects. We found that single nucleotide polymorphisms (SNPs) driving ASE are also often local eQTL and therefore presumably cis eQTL. These SNPs often, but not always, affect gene expression in multiple tissues and, when they do, the allele increasing expression is usually the same. However, there were systematic differences between ASE and local eQTL and between tissues and breeds. We also found that SNPs significantly associated with gene expression (p < 0.001) were likely to influence some complex traits (p < 0.001), which means that some mutations influence variation in complex traits by changing the expression level of genes.
conclusionWe conclude that ASE detects phenomenon that overlap with local eQTL, but there are also systematic differences between the SNPs discovered by the two methods. Some mutations influencing complex traits are actually eQTL and can be discovered using RNA-Seq including eQTL in the genes CAST, CAPN1, LCORL and LEPROTL1.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.