Title | Ruminant metabolic systems biology: reconstruction and integration of transcriptome dynamics underlying functional responses of tissues to nutrition and physiological state. |
Publication Type | Journal Article |
Year of Publication | 2012 |
Authors | Bionaz, M, Loor, JJ |
Journal | Gene Regul Syst Bio |
Volume | 6 |
Pagination | 109-25 |
Date Published | 2012 |
ISSN | 1177-6250 |
Abstract | High-throughput 'omics' data analysis via bioinformatics is one key component of the systems biology approach. The systems approach is particularly well-suited for the study of the interactions between nutrition and physiological state with tissue metabolism and functions during key life stages of organisms such as the transition from pregnancy to lactation in mammals, ie, the peripartal period. In modern dairy cows with an unprecedented genetic potential for milk synthesis, the nature of the physiologic and metabolic adaptations during the peripartal period is multifaceted and involves key tissues such as liver, adipose, and mammary. In order to understand such adaptation, we have reviewed several works performed in our and other labs. In addition, we have used a novel bioinformatics approach, Dynamic Impact Approach (DIA), in combination with partly previously published data to help interpret longitudinal biological adaptations of bovine liver, adipose, and mammary tissue to lactation using transcriptomics datasets. Use of DIA with transcriptomic data from those tissues during normal physiological adaptations and in animals fed different levels of energy prepartum allowed visualization and integration of most-impacted metabolic pathways around the time of parturition. The DIA is a suitable tool for applying the integrative systems biology approach. The ultimate goal is to visualize the complexity of the systems at study and uncover key molecular players involved in the tissue's adaptations to physiological state or nutrition. |
DOI | 10.4137/GRSB.S9852 |
Alternate Journal | Gene Regul Syst Bio |
PubMed ID | 22807626 |
PubMed Central ID | PMC3394460 |