Please use this identifier to cite or link to this item: http://223.31.159.10:8080/jspui/handle/123456789/1153
Title: Identification and downstream analyses of domains amplified in plant genomes: The case of StAR-related lipid transfer (START) domains in rice
Authors: Mahtha, Sanjeet Kumar
Purama, Ravi Kiran
Kumari, Renu
Yadav, Gitanjali
Keywords: Proteome analysis
Hidden Markov Models
Phylogenetics
START domains
Transcription factors
Oryza
Issue Date: 2021
Publisher: Springer Nature Publishing AG
Citation: Methods in Molecular Biology, 2238: 325-338
Abstract: Plant genomes can withstand small- and large-scale duplications, at a far greater success than any other kingdom in the tree of life, resulting in the existence and evolution of gene families, often with over a hundred members! The gene families, in turn, go through subfunctionalization or neofunctionalization, to form protein domains performing unique or grouped functions in context of the original activity. Due to the large number of such cases in the plant kingdom, it has become a routine task for plant biologists to investigate their specific gene family of interest. In this chapter, we provide a simple and standard pipeline for this effort, taking the example of steroidogenic acute regulatory protein (StAR) related lipid transfer (START) domains in rice, as reference. We describe the extraction, processing, and downstream analysis of Oryza sativa var. japonica proteome towards identification and comparative exploration of START domains. This was done by training profile Hidden Markov Models (HMM) of 35 reported START domains in Arabidopsis, which were then used to search potential homologs in rice. Downstream investigations included domain structure analysis, visualization of exon–intron patterns, chromosomal localization of START genes, and phylogenetic studies, followed by identification of cis-regulatory elements and gene regulatory network construction. Additionally, we have also highlighted various alternative tools and techniques that can be used to perform similar analyses, along with salient features.
Description: Accepted date: 21 January 2021
URI: https://link.springer.com/protocol/10.1007%2F978-1-0716-1068-8_22
http://223.31.159.10:8080/jspui/handle/123456789/1153
ISBN: 978-1-0716-1067-1
Appears in Collections:Institutional Publications

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