Literature DB >> 15865973

The role of geographic analysis in locating, understanding, and using plant genetic diversity.

Andy Jarvis1, Sam Yeaman, Luigi Guarino, Joe Tohme.   

Abstract

The genetic structure of an organism is shaped by various factors, many of which vary significantly over space. In this chapter, we provide insight on how studying geographic patterns may contribute to an improved understanding of variability in genetic structure. We first review the theoretical background on how differences in genetic structure may be generated through processes that are inherently variable over space. We then present novices with some basics on how geographic information systems (GIS) may be adopted to study this variation, including advice on software, data, and the type of research questions that might be addressed. The chapter finishes with a brief review of how spatial analysis has contributed to the conservation and use of plant genetic resources, through an understanding of spatial patterns in species distribution and genetic structure. We conclude that spatial variation is a factor often overlooked in genetic studies and one that merits greater consideration. With the advent of functional genomics and improved quantification of adaptive traits, spatial analysis may be key in understanding variation in genetic structure through careful analysis of genotype-environment interactions.

Mesh:

Year:  2005        PMID: 15865973     DOI: 10.1016/S0076-6879(05)95017-9

Source DB:  PubMed          Journal:  Methods Enzymol        ISSN: 0076-6879            Impact factor:   1.600


  2 in total

1.  A gap analysis methodology for collecting crop genepools: a case study with phaseolus beans.

Authors:  Julián Ramírez-Villegas; Colin Khoury; Andy Jarvis; Daniel Gabriel Debouck; Luigi Guarino
Journal:  PLoS One       Date:  2010-10-20       Impact factor: 3.240

2.  Spatial analysis to support geographic targeting of genotypes to environments.

Authors:  Glenn Hyman; Dave Hodson; Peter Jones
Journal:  Front Physiol       Date:  2013-03-18       Impact factor: 4.566

  2 in total

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