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Identification of quantitative trait loci for yield and yield components in an advanced backcross population derived from the Oryza sativa variety IR64 and the wild relative O. rufipogon
Authors:E.?M.?Septiningsih,J.?Prasetiyono,E.?Lubis,T.?H.?Tai,T.?Tjubaryat,S.?Moeljopawiro,S.?R.?McCouch  author-information"  >  author-information__contact u-icon-before"  >  mailto:SRM@cornell.edu"   title="  SRM@cornell.edu"   itemprop="  email"   data-track="  click"   data-track-action="  Email author"   data-track-label="  "  >Email author
Affiliation:(1) Department of Plant Breeding, Cornell University, 240 Emerson Hall, Ithaca, NY 14853–1901, USA;(2) Research Institute for Food Crop Biotechnology, 16111 Bogor, Indonesia;(3) Muara Experiment Station, 16114 Bogor, Indonesia;(4) USDA-ARS CPGRU and Department of Agronomy and Range Science, University of California, One Shields Avenue, Davis, CA 95616 , USA;(5) Sukamandi Research Institute for Rice, Jl. Raya 9, Cikampek, Sukamandi, West Java, Indonesia
Abstract:A BC2F2 population developed from an interspecific cross between Oryza sativa (cv IR64) and O. rufipogon (IRGC 105491) was used in an advanced backcross QTL analysis to identify and introduce agronomically useful genes from this wild relative into the cultivated gene pool. The objectives of this study were: (1) to identify putative yield and yield component QTLs that can be useful to improve the elite cultivar IR64; (2) to compare the QTLs within this study with previously reported QTLs in rice as the basis for identifying QTLs that are stable across different environments and genetic backgrounds; and (3) to compare the identified QTLs with previously reported QTLs from maize to examine the degree of QTL conservation across the grass family. Two hundred eighty-five families were evaluated in two field environments in Indonesia, with two replications each, for 12 agronomic traits. A total of 165 markers consisting of 131 SSRs and 34 RFLPs were used to construct the genetic linkage map. By employing interval mapping and composite interval mapping, 42 QTLs were identified. Despite its inferior performance, 33% of the QTL alleles originating from O. rufipogon had a beneficial effect for yield and yield components in the IR64 background. Twenty-two QTLs (53.4%) were located in similar regions as previously reported rice QTLs, suggesting the existence of stable QTLs across genetic backgrounds and environments. Twenty QTLs (47.6%) were exclusively detected in this study, uncovering potentially novel alleles from the wild, some of which might improve the performance of the tropical indica variety IR64. Additionally, several QTLs for plant height, grain weight, and flowering time detected in this study corresponded to homeologous regions in maize containing previously detected maize QTLs for these traits.
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