Comparative Genomics of Cotton and Arabidopsis

  • Junkang Rong
  • Andrew H. Paterson
Part of the Plant Genetics and Genomics: Crops and Models book series (PGG, volume 3)


Upland cotton (G. hirsutum), a tetraploid species, evolved from a reunion of two diploid species (most probably G. herbaceum and G. raimondii with A and D genomes respectively) about 1-2 million year ago. Cytogenetic and molecular evidence indicated that A and D diploid cottons diverged from a common ancestor about 7-10 million years ago. High-density genetic linkage maps reveal the homoeologous relationship between A and D chromosomes, and permit the reconstruction of the gene order of their hypothetical common ancestor. Comparative studies with the inferred gene order of the hypothetical cotton ancestor and Arabidopsis pre-duplication ancestor indicate that cotton and Arabidopsis share a useful level of correspondence of gene order. This syntenic relationship is very helpful in identification and isolation of important cotton genes using Arabidopsis sequence information. As an example, the correspondence between some mapped fiber QTLs and some cloned fiber related cDNA/genes is shown. Cotton fibers and Arabidopsis trichomes both develop from epidermal cells and are single celled ‘organs’. With the aid of the considerable knowledge of Arabidopsis trichome development, some cotton homologs of Arabidopsis trichome genes have been cloned and shown to be related to fiber development. An eventual sequence for the cotton genome(s) will further advance the ability of cotton researchers to utilize translational genomics approaches to benefit from Arabidopsis functional information, also clarifying the consequences of additional ancient duplication in cotton, and perhaps hinting at the identities of genes that contribute to the unique features of cotton.


Cotton Fiber Fiber Development Cotton Genome Matching Locus Tetraploid Cotton 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Plant Genome Mapping LaboratoryThe University of Georgia

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