Researchers Map Fiber Quality Traits of Upland Cotton Using Three-parent Composite Population

Cotton is one of the most economically important crops worldwide because it is the basic raw material in the textile industry and it also used in oil and livestock feed production. Through conventional breeding, scientists have improved various traits of the crop, especially in increasing its yield and improving its quality. However, the unfavorable correlations between the lint yield and fiber quality limit conventional breeding programs in improving upland cotton. Thus, combining molecular tools and conventional breeding methods is necessary to develop cotton cultivars with better quality. Furthermore, the use of three or more cultivars/lines in making composite cross populations can increase the marker density of genetic maps for breeding.

To construct a relatively high density map and determine complex traits associated with fiber quality traits, Ke Zhang and colleagues from Southwest University in China used three upland cotton cultivars to make a segregating population. The resulting genetic map contained 978 microsatellites and 69 linkage groups, covering about 94.1 percent of the whole tetraploid cotton genome. They have detected 63 quantitative trait loci (QTL) or portions of the DNA with linked genes that confer a quantitative trait. Of these 63 QTL, 11 were associated with fiber elongation, 16 for fiber length, 9 for fiber micronaire reading, 10 for fiber strength, and 17 for fiber length uniformity. This genetic map and QTL can be used for breeding programs of upland cotton to further improve fiber quality.

Read more details about this study published by Molecular Breeding journal at http://www.springerlink.com/content/r2r34x26p15j47v4/.

This article is part of the Crop Biotech Update, a weekly summary of world developments in agri-biotech for developing countries, produced by the Global Knowledge Center on Crop Biotechnology, International Service for the Aquisition of Agri-Biotech Applications SEAsiaCenter (ISAAA)

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