Mapping quantitative trait loci for yield, yield components and morphological traits in an advanced backcross population between Oryza rufipogon and the Oryza sativa cultivar Jefferson

Abstract

An advanced backcross population between an accession of Oryza rufipogon (IRGC 105491) and the U.S. cultivar Jefferson (Oryza sativa ssp. japonica) was developed to identify quantitative trait loci (QTLs) for yield, yield components and morphological traits. The genetic linkage map generated for this population consisted of 153 SSR and RFLP markers with an average interval size of 10.3 cM. Thirteen traits were examined, nine of which were measured in multiple environments. Seventy-six QTLs above an experiment-wise significance threshold of P<0.01 (corresponding to an interval mapping LOD>3.6 or a composite interval mapping LOD>3.9) were identified. For the traits measured in multiple environments, 47% of the QTLs were detected in at least two environments. The O. rufipogon allele was favorable for 53% of the yield and yield component QTLs, including loci for yield, grains per panicle, panicle length, and grain weight. Morphological traits related to the domestication process and/or weedy characteristics, including plant height, shattering, tiller type and awns, were found clustered on chromosomes 1 and 4. Comparisons to previous studies involving wild x cultivated crosses revealed O. rufipogon alleles with stable effects in multiple genetic backgrounds and environments, several of which have not been detected in studies between Oryza sativa cultivars, indicating potentially novel alleles from O. rufipogon. Some O. rufipogon-derived QTLs, however, were in similar regions as previously reported QTLs from Oryza sativa cultivars, providing evidence for conservation of these QTLs across the Oryza genus. In addition, several QTLs for grain weight, plant height, and flowering time were localized to putative homeologous regions in maize where QTLs for these traits have been previously reported, supporting the hypothesis of functional conservation of QTLs across the grasses.

Weedy rice in sustainable rice production. A review

“…However, only seedcovering-imposed dormancy has been reported in weedy rice (Gu et al 2003(Gu et al , 2005. About 10 epistatically interacting dormancy-related QTLs have been identified in weedy rice co-localized with genes for shattering, pericarp color, and flowering time (Cai and Morishima 2000;Thomson et al 2003;Lee et al 2005;Gu et al 2003Gu et al , 2004Gu et al , 2005Gu et al , 2011Wen et al 2008;Ye et al 2010). Weedy rice seeds generally have increased seed longevity and remain viable for years compared to cultivated rice.…”

Análise de associação quanto à produtividade e seus caracteres componentes em linhagens e cultivares de arroz de terras altas

“…No cromossomo 2, o marcador Q6YUX0, também associado ao caráter NGP, foi ancorado pelo marcador RM240, previamente associado ao PCG por Zhuang et al (2002), por meio do QTL qTGWT-2-2 e, por Thomson et al (2003), pelo QTL gw2.1. No cromossomo 4, o marcador RM252 havia sido previamente relacionado ao PCG, em uma população segregante do cruzamento interespecífico O. sativa x O. glumaepatula (Brondani et al, 2002).…”

Developmental Change of Vegetative Plant Architecture of Annual-Form-Wild Rice (&lt;i&gt;Oryza rufipogon&lt;/i&gt; Griff.) Elevates Competitive Ability during the Late Development under a Dense Condition

“…For instance, when a QTL associated with a yield component such as grain weight is closely linked to another QTL associated with yield and they showed same i-allele, it is intuitively thought that QTL associated with the yield component will be the cause and the detection of QTL associated with yield will be the effect (or by-product) [53,55]. Such thinking implicitly supposes positive regression relationship between a yield component and yield.…”

“…The consistency of i-allele between two QTLs which shared an identical NML has been regarded as one of evidences for enhancing the possibility that the two QTLs might be identical and show a cause-and-effect relationship in some cases [22,43,[53][54][55]. For instance, when a QTL associated with a yield component such as grain weight is closely linked to another QTL associated with yield and they showed same i-allele, it is intuitively thought that QTL associated with the yield component will be the cause and the detection of QTL associated with yield will be the effect (or by-product) [53,55].…”