Systems Biology, Bioinformatics and Livestock Science

Genomics to Systems Biology in Livestock Management: its Applications and Future Perspective

Author(s): Bheemshetty S. Patil*, Pallavi S. Kanthe, Prachi P. Parvatikar and Aravind V. Patil

Pp: 260-278 (19)

DOI: 10.2174/9789815165616123010017

* (Excluding Mailing and Handling)

Abstract

The recurrent and comprehensive study of biological systems as a single entity in response to stimuli is known as systems biology. The introduction of high-throughput technology for studying an animal's DNA, proteome, and metabolome was a blow to reductionism in livestock science. It is based on ideas formalized in models derived from global functional genomics investigations of the genome, transcriptome, proteome, metabolome, and other complex biological systems. The mapping of entire sets of genes, transcripts, proteins, and metabolites from a variety of organisms has driven the creation of novel '-omic' technologies for gathering and analyzing vast amounts of data. This widely defined systems approach is being used to address a wide range of issues and organizational scales, along with several elements of livestock research. It is well established that the tools that relate genetic variations to their cellular activities, pathways, and other biological roles will become even more essential in the future. For each animal genomics research issue, a vision, current state of the art, research needed to progress the field, expected outputs, and partnerships are required. Modern computational tools capable of finding functional implications and biologically meaningful networks complement the ever-increasing ability to generate massive molecular, microbial, and metabolite data sets. The intricate inter-tissue responses to physiological status and nutrition can now be seen at the same time. The knowledge acquired from the application of functional analysis of systems biology data sets to livestock management in order to improve productivity, quality, and yield. 


Keywords: Genomics, Host-pathogen interactions, HoxD genes, Livestock, Systems biology.

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