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http://223.31.159.10:8080/jspui/handle/123456789/563
Title: | IGMAP: An interactive mapping and clustering platform for plants |
Authors: | Priya, Piyush Bandhiwal, Nitesh Misra, Gopal Mondal, Subhashish Yadav, Gitanjali |
Keywords: | IGMAP |
Issue Date: | 2015 |
Publisher: | Cell Press |
Citation: | Mol. Plant, 8(5): 818-821 |
Abstract: | Next-generation sequencing (NGS) technologies have resulted in a massive surge of high-throughput genomic data, particularly for the plant kingdom, boosting the development of methods for gene family discovery and identification of clustering patterns at genomic scales. Plants are well known for the occurrence of both genic and chromosomal duplications that have resulted in the widespread existence of gene families in this kingdom, apart from being associated with subsequent evolutionary divergence via sub-functionalization or neo- functionalization (Flagel and Wendel, 2009). These divergent mechanisms eventually lead to the formation of gene clusters, which in turn, have been shown to confer selective advantages to the genome including co-inheritance and co- regulation (Fischbach et al., 2008). Although gene clusters have been conventionally understood to be the genetic building blocks of prokaryotic genomes, comparative genomic studies have revealed the presence of functionally related genes that are clustered in lower nematodes, fungi, and several higher eukaryotes (Zorio et al., 1994; Blumenthal, 1998; Lee and Sonnhammer, 2003; Hurst et al., 2004; Thomas, 2006). However, very few data are available on the modularity or clustered linkage of genes in plants, despite the widespread occurrence of duplication events in the kingdom. In this regard, recent reports of biosynthetic modules and clustered organization of genes spotted in several major classes of plant-derived secondary metabolites arising through neo-functionalization and relocation of duplicated or existing genes, have offered an exciting niche (Osbourn, 2010). The presently available approaches for the identification and analysis of plant gene clusters include map-based cloning, forward and reverse genetics, and genome mining. As the wealth of plant genome sequence data continues to increase exponentially, newer methods are going to be required to carry out genome mining in a rational and useful manner. |
Description: | Accepted date: January 18, 2015 |
URI: | http://172.16.0.77:8080/jspui/handle/123456789/563 |
ISSN: | 1674-2052 |
Appears in Collections: | Institutional Publications |
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