4.7 Article

Metabogenomic analysis to functionally annotate the regulatory role of long non-coding RNAs in the liver of cows with different nutrient partitioning phenotype

Journal

GENOMICS
Volume 114, Issue 1, Pages 202-214

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.ygeno.2021.12.004

Keywords

Long non-coding RNA; Metabogenomics; Nutrient partitioning; Bos taurus; Functional genome annotation; Functional annotation of animal genomes (FAANG)

Funding

  1. German Research Foundation (DFG) [KU 771/8-1, WE 1786/5-1]
  2. European Union [815668]
  3. European COST action FAANG-Europe [CA15112]

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By combining transcriptomic and metabolomic analyses, long non-coding RNAs (lncRNAs) were identified to have potential regulatory functions in livestock, especially in divergent nutrient partitioning. These lncRNAs may play important roles in fine-tuning gene expression involved in metabolic pathways associated with different nutrient partitioning phenotypes.
Long non-coding RNAs (lncRNAs) hold gene regulatory potential, but require substantial further functional annotation in livestock. Applying two metabogenomic approaches by combining transcriptomic and metabolomic analyses, we aimed to identify lncRNAs with potential regulatory function for divergent nutrient partitioning of lactating crossbred cows and to establish metabogenomic interaction networks comprising metabolites, genes and lncRNAs. Through correlation analysis of lncRNA expression with transcriptomic and metabolomic data, we unraveled lncRNAs that have a putative regulatory role in energy and lipid metabolism, the urea and tricarboxylic acid cycles, and gluconeogenesis. Especially FGF21, which correlated with a plentitude of differentially expressed genes, differentially abundant metabolites, as well as lncRNAs, suggested itself as a key metabolic regulator. Notably, lncRNAs in close physical proximity to coding-genes as well as lncRNAs with natural antisense transcripts appear to perform a fine-tuning function in gene expression involved in metabolic pathways associated with different nutrient partitioning phenotypes.

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