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Yield-enhancing quantitative trait loci (QTLs) from wild species

Paper ID Volume ID Publish Year Pages File Format Full-Text
14814 1253 2008 15 PDF Available
Title
Yield-enhancing quantitative trait loci (QTLs) from wild species
Abstract

Wild species of crop plants are increasingly being used to improve various agronomic traits including yield in cultivars. Dense molecular maps have enabled mapping of quantitative trait loci (QTLs) for complex traits such as yield. QTLs for increased yield have been identified from wild relatives of several crop plants. Advanced backcross QTL analysis has been used to identify naturally occurring favorable QTL alleles for yield and minimize the effect of unwanted alleles from wild species. Yield QTLs from wild species are distributed on almost all chromosomes but more often in some regions. Many QTLs for yield and related traits derived from different wild accessions or species map to identical chromosomal regions. QTLs for highly correlated yield associated traits are also often co-located implying linkage or pleiotropic effects. Many QTLs have been detected in more than one environment and in more than one genetic background. The overall direction of effect of some QTLs however, may vary with genetic context. Thus, there is evidence of stable and consistent major effect yield-enhancing QTLs derived from wild species in several crops. Such QTLs are good targets for use in marker assisted selection though their context-dependency is a major constraint. Literature on yield QTLs mapped from wild species is summarized with special reference to rice and tomato.

Keywords
Oryza; Solanum; Wild species; Rice; Tomato; Yield QTL; Molecular markers; Yield related traits
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Yield-enhancing quantitative trait loci (QTLs) from wild species
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Publisher
Database: Elsevier - ScienceDirect
Journal: Biotechnology Advances - Volume 26, Issue 1, January–February 2008, Pages 106–120
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us