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Cotton QTLdb: a cotton QTL database for QTL analysis, visualization, and comparison between Gossypium hirsutum and G. hirsutum × G. barbadense populations

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Abstract

Key message

A specialized database currently containing more than 2200 QTL is established, which allows graphic presentation, visualization and submission of QTL.

Abstract

In cotton quantitative trait loci (QTL), studies are focused on intraspecific Gossypium hirsutum and interspecific G. hirsutum × G. barbadense populations. These two populations are commercially important for the textile industry and are evaluated for fiber quality, yield, seed quality, resistance, physiological, and morphological trait QTL. With meta-analysis data based on the vast amount of QTL studies in cotton it will be beneficial to organize the data into a functional database for the cotton community. Here we provide a tool for cotton researchers to visualize previously identified QTL and submit their own QTL to the Cotton QTLdb database. The database provides the user with the option of selecting various QTL trait types from either the G. hirsutum or G. hirsutum × G. barbadense populations. Based on the user’s QTL trait selection, graphical representations of chromosomes of the population selected are displayed in publication ready images. The database also provides users with trait information on QTL, LOD scores, and explained phenotypic variances for all QTL selected. The CottonQTLdb database provides cotton geneticist and breeders with statistical data on cotton QTL previously identified and provides a visualization tool to view QTL positions on chromosomes. Currently the database (Release 1) contains 2274 QTLs, and succeeding QTL studies will be updated regularly by the curators and members of the cotton community that contribute their data to keep the database current. The database is accessible from http://www.cottonqtldb.org.

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Acknowledgments

This study was funded in part by New Mexico Agricultural Experiment Station.

Conflict of interest

The authors declare that they have no conflict of interests.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Informed consent was obtained from all individual participants included in the study.

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Authors and Affiliations

  1. Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, USA

    Joseph I Said & Jinfa Zhang

  2. Department of Computer Science, The University of Texas at El Paso, El Paso, USA

    Joseph A Knapka

  3. Department of Computer Science, New Mexico State University, Las Cruces, NM, USA

    Mingzhou Song

Authors
  1. Joseph I Said
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  2. Joseph A Knapka
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  3. Mingzhou Song
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  4. Jinfa Zhang
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Corresponding authors

Correspondence to Mingzhou Song or Jinfa Zhang.

Additional information

Communicated by S. Hohmann.

J. I. Said and J. A. Knapka were co-first authors.

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Said, J.I., Knapka, J.A., Song, M. et al. Cotton QTLdb: a cotton QTL database for QTL analysis, visualization, and comparison between Gossypium hirsutum and G. hirsutum × G. barbadense populations. Mol Genet Genomics 290, 1615–1625 (2015). https://doi.org/10.1007/s00438-015-1021-y

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  • DOI: https://doi.org/10.1007/s00438-015-1021-y

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