ArticleBMC bioinformatics2018
Gene co-expression networks from RNA sequencing of dairy cattle identifies genes and pathways affecting feed efficiency.
Article in BMC bioinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.
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Who cites it
28 citing papers in PubMed, 1 synthesis or guideline pooled it, 58 citations in OpenAlex.
- Weighted gene co-expression network analysis identifies modules and functionally enriched pathways in the lactation process.Scientific reports · 2021Pooled it
- Data-intensive immune network modelling for One Health.Briefings in bioinformatics · 2026Review
- Weighted gene co-expression network analysis reveals key genes and lncRNAs inFrontiers in immunology · 2026Article
- Gene expression analysis for feed efficiency trait in liver tissue of lactating Girolando cows.Genetics and molecular biology · 2026Article
- Identification of key factors causing ketosis in dairy cows with low feed intake.Animal biotechnology · 2025Article
- Identification of Metabolic Pathways and Hub Genes Associated with Ultrasound Subcutaneous Fat and Muscle Depth of the Longissimus Muscle in Cull Beef Cows Using Gene Co-Expression Analysis.Animals : an open access journal from MDPI · 2025Article
- Genome-wide association studies and functional annotation of pre-weaning calf mortality and reproductive traits in Nellore cattle from experimental selection lines.BMC genomics · 2024Article
- Article
- The mRNA-lncRNA landscape of multiple tissues uncovers key regulators and molecular pathways that underlie heterosis for feed intake and efficiency in laying chickens.Genetics, selection, evolution : GSE · 2023Article
- Identification of milk-related genes and regulatory networks in Bactrian camel either supplemented or under grazing.Tropical animal health and production · 2023Article
- Molecular Mechanism of m6A Methylation Modification GenesInternational journal of molecular sciences · 2023Article
- Improving gene regulatory network inference and assessment: The importance of using network structure.Frontiers in genetics · 2023Article
- Analysis of liver miRNA in Hu sheep with different residual feed intake.Frontiers in genetics · 2023Article
- Characterization of feed efficiency-related key signatures molecular in different cattle breeds.PloS one · 2023Article
- Feed efficiency in dairy sheep: An insight from the milk transcriptome.Frontiers in veterinary science · 2023Article
- Identifying key genes in milk fat metabolism by weighted gene co-expression network analysis.Scientific reports · 2022Article
- Nitrogen metabolism and mammary gland amino acid utilization in lactating dairy cows with different residual feed intake.Animal bioscience · 2021Article
- Novel functional sequences uncovered through a bovine multiassembly graph.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Detection and integrated analysis of lncRNA and mRNA relevant to plateau adaptation of Yak.Reproduction in domestic animals = Zuchthygiene · 2020Article
- Identification and Annotation of Potential Function of Regulatory Antisense Long Non-Coding RNAs Related to Feed Efficiency inInternational journal of molecular sciences · 2020Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSelection for feed efficiency is crucial for overall profitability and sustainability in dairy cattle production. Key regulator genes and genetic markers derived from co-expression networks underlying feed efficiency could be included in the genomic selection of the best cows. The present study identified co-expression networks associated with high and low feed efficiency and their regulator genes in Danish Holstein and Jersey cows. RNA-sequencing data from Holstein and Jersey cows with high and low residual feed intake (RFI) and treated with two diets (low and high concentrate) were used. Approximately 26 million and 25 million pair reads were mapped to bovine reference genome for Jersey and Holstein breed, respectively. Subsequently, the gene count expressions data were analysed using a Weighted Gene Co-expression Network Analysis (WGCNA) approach. Functional enrichment analysis from Ingenuity® Pathway Analysis (IPA®), ClueGO application and STRING of these modules was performed to identify relevant biological pathways and regulatory genes.
resultsWGCNA identified two groups of co-expressed genes (modules) significantly associated with RFI and one module significantly associated with diet. In Holstein cows, the salmon module with module trait relationship (MTR) = 0.7 and the top upstream regulators ATP7B were involved in cholesterol biosynthesis, steroid biosynthesis, lipid biosynthesis and fatty acid metabolism. The magenta module has been significantly associated (MTR = 0.51) with the treatment diet involved in the triglyceride homeostasis. In Jersey cows, the lightsteelblue1 (MTR = - 0.57) module controlled by IFNG and IL10RA was involved in the positive regulation of interferon-gamma production, lymphocyte differentiation, natural killer cell-mediated cytotoxicity and primary immunodeficiency.
conclusionThe present study provides new information on the biological functions in liver that are potentially involved in controlling feed efficiency. The hub genes and upstream regulators (ATP7b, IFNG and IL10RA) involved in these functions are potential candidate genes for the development of new biomarkers. However, the hub genes, upstream regulators and pathways involved in the co-expressed networks were different in both breeds. Hence, additional studies are required to investigate and confirm these findings prior to their use as candidate genes.
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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.