Application of Top-Down and bottom-up systems approaches in ruminant physiology and metabolism

Khuram Shahzad, Juan J. Loor

Research output: Contribution to journalReview article

Abstract

Systems biology is a computational field that has been used for several years across different scientific areas of biological research to uncover the complex interactions occurring in living organisms. Applications of systems concepts at the mammalian genome level are quite challenging, and new complimentary computational/experimental techniques are being introduced. Most recent work applying modern systems biology techniques has been conducted on bacteria, yeast, mouse, and human genomes. However, these concepts and tools are equally applicable to other species including ruminants (e.g., livestock). In systems biology, both bottom-up and top-down approaches are central to assemble information from all levels of biological pathways that must coordinate physiological processes. A bottom-up approach encompasses draft reconstruction, manual curation, network reconstruction through mathematical methods, and validation of these models through literature analysis (i.e., bibliomics). Whereas top-down approach encompasses metabolic network reconstructions using 'omics' data (e.g., transcriptomics, proteomics) generated through DNA microarrays, RNA-Seq or other modern high-throughput genomic techniques using appropriate statistical and bioinformatics methodologies. In this review we focus on top-down approach as a means to improve our knowledge of underlying metabolic processes in ruminants in the context of nutrition. We also explore the usefulness of tissue specific reconstructions (e.g., liver and adipose tissue) in cattle as a means to enhance productive efficiency.

Original languageEnglish (US)
Pages (from-to)379-394
Number of pages16
JournalCurrent Genomics
Volume13
Issue number5
DOIs
StatePublished - 2012

Keywords

  • Bioinformatics
  • Dairy cow
  • Microarray
  • Nutrigenomics

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

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