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

Junkang Rong, F. Alex Feltus, Vijay N. Waghmare, Gary J. Pierce, Peng W. Chee, Xavier Draye, Yehoshua Saranga, Robert J. Wright, Thea A. Wilkins, O. Lloyd May, C. Wayne Smith, John R. Gannaway, Jonathan F. Wendel, Andrew H. Paterson*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

216 Scopus citations

Abstract

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-fiber-producing 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.

Original languageEnglish
Pages (from-to)2577-2588
Number of pages12
JournalGenetics
Volume176
Issue number4
DOIs
StatePublished - Aug 2007

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