Molecular dissection of interspecific variation between Gossypium hirsutum and Gossypium barbadense (cotton) by a backcross-self approach: I. Fiber elongation

Chee, Peng W.; Draye, Xavier; Jiang, Chunxiao; Decanini, Laura; Delmonte, Terrye A.; Bredhauer, Robert; Smith, C. Wayne; Paterson, Andrew H.

doi:10.1007/s00122-005-2063-z

Cited by 91 publications

(67 citation statements)

References 17 publications

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“…These include seven QTLs for fiber length located in the same chromosomal regions as reported earlier [10,26,34,41,42], two QTLs for fiber uniformity ratio located in the same chromosomal regions [43,46], two QTLs for fiber micronaire [10,43,44], three QTLs for fiber elongation [30,36,42,43,46,47], and 4 QTLs for fiber strength [26,34,36,43,44,46,47]. For example, the chromosome regions where QTLs were detected for fiber length in our research matched those in an interspecific map developed from an F 2 population [10]; the QTLs may be common QTLs for fiber quality traits.…”

Section: Qtls For Cotton Fiber Quality Traitsmentioning

confidence: 64%

Construction of a linkage map and QTL mapping for fiber quality traits in upland cotton (Gossypium hirsutum L.)

Liang

Hua

et al. 2013

Chin. Sci. Bull.

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With the development in spinning technology, the improvement of cotton fiber quality is becoming more and more important. The main objective of this research was to construct a high-density genetic linkage map to facilitate marker assisted selection for fiber quality traits in upland cotton (Gossypium hirsutum L.). A genetic linkage map comprising 421 loci and covering 3814.3 cM, accounting for approximately 73.35% of the cotton genome, was constructed using an F 2 population derived from cross GX1135 (P 1 )×GX100-2 (P 2 ). Forty-four of 49 linkage groups were assigned to the 26 chromosomes. Fiber quality traits were investigated in F 2 population sampled from individuals, and in F 2:3 , and F 2:4 generations sampled by lines from two sites and one respectively, and each followed a randomized complete block design with two replications. Thirty-nine quantitative trait loci were detected for five fiber quality traits with data from single environments (separate analysis each): 12 for fiber length, five for fiber uniformity, nine for fiber strength, seven for fiber elongation, and six for fiber micronaire, whereas 15 QTLs were found in combined analysis (data from means of different environments in F 2:3 generation). Among these QTLs, qFL-chr5-2 and qFL-chr14-2 for fiber length were detected simultaneously in three generations (four environments) and verified further by combined analysis, and these QTLs should be useful for marker assisted selection to improve fiber quality in upland cotton.upland cotton (Gossypium hirsutum L.), fiber quality traits, genetic linkage map, marker assisted selection, QTLs Citation:Liang Q Z, Hu C, Hua H, et al. Construction of a linkage map and QTL mapping for fiber quality traits in upland cotton (Gossypium hirsutum L.). Chin Sci Bull, 2013, 58: 32333243,

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Section: Qtls For Cotton Fiber Quality Traitsmentioning

confidence: 64%

Construction of a linkage map and QTL mapping for fiber quality traits in upland cotton (Gossypium hirsutum L.)

Liang

Hua

et al. 2013

Chin. Sci. Bull.

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“…05 by Paterson (EL05.1) and Chr. 22 by Chee (EL22.3) (Chee et al 2005a). This is an example of homeologous loci for a fiber related trait detected in different experiments.…”

Section: Resultsmentioning

confidence: 91%

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

Feltus²,

et al. 2007

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QTL mapping experiments yield heterogeneous results due to the use of different genotypes, environments, and sampling variation. Compilation of QTL mapping results yields a more complete picture of the genetic control of a trait and reveals patterns in organization of trait variation. A total of 432 QTL mapped in one diploid and 10 tetraploid interspecific cotton populations were aligned using a reference map and depicted in a CMap resource. Early demonstrations that genes from the non-fiberproducing diploid ancestor contribute to tetraploid lint fiber genetics gain further support from multiple populations and environments and advanced-generation studies detecting QTL of small phenotypic effect. Both tetraploid subgenomes contribute QTL at largely non-homeologous locations, suggesting divergent selection acting on many corresponding genes before and/or after polyploid formation. QTL correspondence across studies was only modest, suggesting that additional QTL for the target traits remain to be discovered. Crosses between closely-related genotypes differing by single-gene mutants yield profoundly different QTL landscapes, suggesting that fiber variation involves a complex network of interacting genes. Members of the lint fiber development network appear clustered, with cluster members showing heterogeneous phenotypic effects. Meta-analysis linked to synteny-based and expression-based information provides clues about specific genes and families involved in QTL networks. MOST naturally occurring genetic variation in populations reflects polymorphic alleles that individually have relatively small effects but collectively result in continuous variation among members of the population. Through genetic mapping, the number and location of loci associated with complex trait variation, i.e., quantitative trait loci or QTL, can be estimated and used to infer the genetic basis of traits that differ between varieties and/or species (Paterson et al. 1988). DNA markers linked to QTL can also be used as diagnostic tools in the selection of desirable genotypes (markerassisted selection) and as a starting point for cloning of QTL. For these reasons, vast numbers of QTL representing a myriad of traits have been mapped in agronomically important crops, and also in botanical models and animals. A handful of genes underlying QTL have been cloned (e.g., Frary et al. 2000) based largely on fine mapping (Paterson et al. 1990).A recurring complication in the use of QTL data is that different parental combinations and/or experiments conducted in different environments often result in identification of partly or wholly nonoverlapping sets of QTL. The majority of such differences in the QTL landscape are presumed to be due to environment sensitivity of genes. The use of stringent statistical thresholds to infer QTL while controlling experiment-wise error rates (Lander and Botstein 1989;Churchill and Doerge 1994) implies that only a small fraction of these nonoverlapping QTL can be attributed to falsepositive results. Small QTL wit...

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“…It is difficult to determine allelic relations between the QTLs among different populations due to lack of common markers. Some QTLs detected in the present research were positioned on the same chromosome or subgenome as compared with previous reports, which includes 5 QTLs for fiber strength on D7, D9, D6 and D8 (2 QTLs) (Paterson et al 2003;Lacape et al 2005); 7 QTLs for fiber length on A5, A12, D9, D6 (2 QTLs), D11 and D5 (Lacape et al 2005;Chee et al 2005b); 4 QTLs for fiber fineness on A5, D9, D6 and D8 (Paterson et al 2003;Lacape et al 2005;Draye et al 2005); 1 QTL for fiber uniformity on D2 (Paterson et al 2003;Lacape et al 2005;Chee et al 2005b); 1 QTL for FE on A11 (Paterson et al 2003;Chee et al 2005a). They may be common QTL for fiber quality in tetraploid cotton.…”

Section: Discussionmentioning

confidence: 96%

Genetic mapping of quantitative trait loci for fiber quality and yield trait by RIL approach in Upland cotton

et al. 2006

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The improvement of cotton fiber quality has become more important because of changes in spinning technology. Stable quantitative trait loci (QTLs) for fiber quality will enable molecular marker-assisted selection to improve fiber quality of future cotton cultivars. A simple sequence repeat (SSR) genetic linkage map consisting of 156 loci covering 1,024.4 cM was constructed using a series of recombinant inbred lines (RIL) developed from an F 2 population of an Upland cotton (Gossypium hirsutum L.) cross 7235 · TM-1. Phenotypic data were collected at Nanjing and Guanyun County in 2002 and 2003 for 5 fiber quality and 6 yield traits. We found 25 major QTLs (LOD ‡3.0) and 28 putative QTLs (2.0 < LOD < 3.0) for fiber quality and yield components in two or four environments independently. Among the 25 QTLs with LOD ‡ 3, we found 4 QTLs with large effects on fiber quality and 7 QTLs with large effects on yield components. The most important chromosome D8 in the present study was densely populated with markers and QTLs, in which 36 SSR loci within a chromosomal region of 72.7 cM and 9 QTLs for 8 traits were detected.

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Molecular dissection of interspecific variation between Gossypium hirsutum and Gossypium barbadense (cotton) by a backcross-self approach: I. Fiber elongation

Cited by 91 publications

References 17 publications

Construction of a linkage map and QTL mapping for fiber quality traits in upland cotton (Gossypium hirsutum L.)

Construction of a linkage map and QTL mapping for fiber quality traits in upland cotton (Gossypium hirsutum L.)

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

Genetic mapping of quantitative trait loci for fiber quality and yield trait by RIL approach in Upland cotton

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