Identification of cotton fiber quality quantitative trait loci using intraspecific crosses derived from two near-isogenic lines differing in fiber bundle strength
Cotton fiber properties are very important to the yarn quality. Modern high-speed textile operations around the world require long, strong and fine cotton fibers. The objective of this research was to identify stable fiber quantitative trait loci (QTLs) that could be used in cotton breeding through marker-assisted selection (MAS). Two cotton lines, MD90ne and MD52ne, are near-isogenic with significant differences in fiber properties, especially strength. Fiber samples from 734 progeny plants of two F2 populations (A and B) derived from crosses between MD90ne and MD52ne were collected at Stoneville, MS, USA in 2012. Fiber quality attributes were measured using a High Volume Instrument 1000. A simple sequence repeat (SSR) genetic linkage map with 165 loci covering 632.53 cM was constructed using population A, consisting of 356 F2 individuals and used for identifying QTLs related to fiber bundle strength (FBS), short fiber index (SFI) and upper-half mean fiber length (UHML). One QTL for FBS originating from the stronger fiber parent MD52ne was identified on chromosome (Chr.) 3. Three QTLs each for SFI and UHML were identified on Chrs. 3, 4 and 14 and Chrs. 3, 11 and 24, respectively. Population B, consisting of 378 F2 progeny, was used to confirm these QTLs by analyzing 57 SSR markers mapped on Chrs. 3, 14 and 24. Three QTLs—qFBS-c3, qSFI-c14 and qUHML-c24—were confirmed and appeared stable. These three QTLs could potentially be used in breeding to improve cotton fiber quality through a MAS strategy.
KeywordsCotton Fiber quality Fiber strength Microsatellite markers QTL
This project was supported by USDA-ARS CRIS project 6435-21000-017-00D and Cotton Incorporated project 10-747. We greatly thank Dr. William Meredith, who developed the cotton lines MD90ne and MD52ne and made them available for us to use in the present research. Our appreciation also goes to Mrs. Sheron Simpson and Dr. Brian Scheffler at Genomic and Bioinformatic Research Unit at Stoneville, MS for their excellent support in SSR marker analysis. Mention of trade names or commercial products in this article is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U. S. Department of Agriculture, which is an equal opportunity provider and employer.
- Felker GS (2001) Fiber quality and new spinning technologies. In: Dugger P, Richter DC (eds) Beltwide cotton conferences. National Cotton Council of America, Anaheim, pp 5–7Google Scholar
- Hinchliffe DJ, Meredith WR, Yeater KM, Kim HJ, Woodward AW, Chen ZJ, Triplett BA (2010) Near-isogenic cotton germplasm lines that differ in fiber-bundle strength have temporal differences in fiber gene expression patterns as revealed by comparative high-throughput profiling. Theor Appl Genet 120:1347–1366PubMedCrossRefGoogle Scholar
- Lacape JM, Llewellyn D, Jacobs J, Arioli T, Becker D, Calhoun S, Al-Ghazi Y, Liu S, Palai O, Georges S, Giband M, de Assuncao H, Barroso PA, Claverie M, Gawryziak G, Jean J, Vialle M, Viot C (2010) Meta-analysis of cotton fiber quality QTLs across diverse environments in a Gossypium hirsutum × G. barbadense RIL population. BMC Plant Biol 10:132PubMedCentralPubMedCrossRefGoogle Scholar
- McCouch SR, Cho YG, Yano PE, Blinstrub M, Morishima H, Kinoshita T (1997) Report on QTL nomenclature. Rice Genet Newsl 14:11–13Google Scholar
- Meredith MR (1984) Quantitative genetics. In: Koh JW, Lewis CF (eds) Cotton. Crop Science Society of America, Madison, pp 132–147Google Scholar
- Rong J, Feltus FA, Waghmare VN, Pierce GJ, Chee PW, Draye X, Saranga Y, Wright RJ, Wilkins TA, May OL, Smith CW, Gannaway JR, Wendel JF, Paterson AH (2007) Meta-analysis of polyploid cotton QTL shows unequal contributions of subgenomes to a complex network of genes and gene clusters implicated in lint fiber development. Genetics 176:2577–2588PubMedCentralPubMedCrossRefGoogle Scholar
- Ulloa M, Meredith WR (2000) Genetic linkage map and QTL analysis of agronomic and fiber quality traits in an intraspecific population. J Cotton Sci 4:161–170Google Scholar
- Van Ooijen JW (2006) JoinMap 4.0: software for the calculation of genetic linkage maps in experimental populations. Kyazma B.V., WageningenGoogle Scholar
- Van Ooijen JW (2009) MapQTL 6, software for the mapping of quantitative trait loci in experimental populations of diploid species. Kyazma BV, WageningenGoogle Scholar
- Yu JZ, Kohel RJ, Fang DD, Cho J, Van Deynze A, Ulloa M, Hoffman SM, Pepper AE, Stelly DM, Jenkins JN, Saha S, Kumpatla SP, Shah MR, Hugie WV, Percy RG (2012) A high-density simple sequence repeat and single nucleotide polymorphism genetic map of the tetraploid cotton genome. G3 (Bethesda) 2:43–58Google Scholar
- Yu J, Zhang K, Li S, Yu S, Zhai H, Wu M, Li X, Fan S, Song M, Yang D, Li Y, Zhang J (2013) Mapping quantitative trait loci for lint yield and fiber quality across environments in a Gossypium hirsutum × Gossypium barbadense backcross inbred line population. Theor Appl Genet 126:275–287PubMedCrossRefGoogle Scholar