Genetic loci responding to two cycles of divergent selection for grain yield under drought stress in a rice breeding population

Venuprasad, R.; Bool, M. E.; Dalid, Cheryl; Bernier, Jérôme; Kumar, Arvind; Atlin, G. N.

doi:10.1007/s10681-009-9898-3

Cited by 62 publications

(53 citation statements)

References 15 publications

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“…The small populations after selection are too small to be utilized for QTL mapping using a conventional marker-trait association model. Nevertheless, efforts have recently been made to map QTL in single selected populations by detecting segregation distortion loci using simple Chisquare tests (Li et al, 2005;Venuprasad et al, 2009;Zhang et al, 2011Zhang et al, , 2014. Obviously, the simple Chi-square tests are not the optimal methods because they cannot take advantage of the unique feature of large number of small advanced breeding progenies to perform a joint analysis in most plant and animal breeding programs.…”

Section: Discussionmentioning

confidence: 99%

Mapping quantitative trait loci in selected breeding populations: A segregation distortion approach

Cui

Zhang

et al. 2015

Heredity

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Quantitative trait locus (QTL) mapping is often conducted in line-crossing experiments where a sample of individuals is randomly selected from a pool of all potential progeny. QTLs detected from such an experiment are important for us to understand the genetic mechanisms governing a complex trait, but may not be directly relevant to plant breeding if they are not detected from the breeding population where selection is targeting for. QTLs segregating in one population may not necessarily segregate in another population. To facilitate marker-assisted selection, QTLs must be detected from the very population which the selection is targeting. However, selected breeding populations often have depleted genetic variation with small population sizes, resulting in low power in detecting useful QTLs. On the other hand, if selection is effective, loci controlling the selected trait will deviate from the expected Mendelian segregation ratio. In this study, we proposed to detect QTLs in selected breeding populations via the detection of marker segregation distortion in either a single population or multiple populations using the same selection scheme. Simulation studies showed that QTL can be detected in strong selected populations with selected population sizes as small as 25 plants. We applied the new method to detect QTLs in two breeding populations of rice selected for high grain yield. Seven QTLs were identified, four of which have been validated in advanced generations in a follow-up study. Cloned genes in the vicinity of the four QTLs were also reported in the literatures. This mapping-by-selection approach provides a new avenue for breeders to improve breeding progress. The new method can be applied to breeding programs not only in rice but also in other agricultural species including crops, trees and animals. Heredity (2015) 115, 538-546; doi:10.1038/hdy.2015.56; published online 1 July 2015 INTRODUCTIONOver a century of breeding efforts has produced numerous varieties of domestic plants and animals to provide ample food resources for human. The great successes in plant and animal breeding have largely been achieved by exploiting within-species genetic variation for traits of interest through phenotypic selection. Although appropriate phenotypic selection is effective to exploit useful genetic variation of complex traits in breeding populations, the rich sources of naturally occurring genetic variation in plants and animals are largely hidden at the phenotypic levels and remain uncharacterized at the genomic and molecular levels. As a result, they are very much under-utilized in the past breeding programs. Meanwhile, the past decades have witnessed tremendous progress in genetic dissections of complex traits in plants and animals using DNA markers and genomic technologies (Francia et al., 2005;Collard and Mackill, 2008;Miah et al., 2013). During this period of time, thousands of quantitative trait locus (QTL) affecting a wide range of complex traits have been identified in different plant and animal species. These ...

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Section: Discussionmentioning

confidence: 99%

Mapping quantitative trait loci in selected breeding populations: A segregation distortion approach

Cui

Zhang

et al. 2015

Heredity

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“…Hence, for quantitative traits such as drought tolerance, quantitative trait loci (QTL) mapping followed by marker-assisted breeding (MAB) is considered as an alternate strategy to overcome this limitation 11 . Though several QTLs for yield under drought stress have been mapped in rice [12][13][14][15][16] , only few have been successfully deployed in MAB till date 17 . Identifying consistent QTLs for yield under stress with large effect and fine-mapping them will speed up MAB for drought tolerance in rice 12,18 .…”

Section: Rice (Oryza Sativamentioning

confidence: 99%

Fine mapping of consistent quantitative trait loci for yield under drought stress using rice (Oryza sativa) recombinant inbred lines adapted to rainfed environment

Muthukumar¹,

Vivek²,

Poornima³

et al. 2015

Current Science

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Drought stress is a serious constraint, especially in rainfed rice production, and breeding for drought tolerance by selection based on yield under stress, though effective, is slow. Mapping quantitative trait loci (QTLs) for yield and its components under drought stress predominant in rainfed target populations of environment (TPE) will help overcome this limitation. In the present study, a subset of 143 F 8 and F 9 recombinant inbred (RI) lines derived from IR62266-42-6-2 (IR62266), a high-yielding indica ecotype and Norungan, a landrace from TPE, was used to map QTLs for yield and its components under drought predominant in TPE. A large effect yield QTL observed under drought stress in TPE was consistent across two years with a phenotypic variation of 31.3% and 37.9% and additive effect of 629.2 and 424.9 kg/ha. Further, this region was fine-mapped to 94.0 kb with positive effect on grain yield under stress.

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“…The SMF is a result of the alternate recurrences of waterlogging and water deficit. Such condition can affect root development and its physiological functions (Bañoc, Yamauchi, Kamoshita, Wade, & Pardales, 2000b;Niones et al, 2012;Suralta et al, 2010;Suralta & Yamauchi, 2008), soil nutrient availability (Iijima, Morita, Zegada-Lizarazu, & Izumi, 2007;Kondo, Singh, Agbisit, & Murty, 2005;Suralta et al, 2010;Tran et al, 2014) as well as shoot growth, causing severe yield losses particularly when the drought period coincides with the reproductive stage (O' Toole, 1982;Venuprasad et al, 2009;Verulkar et al, 2010). For the adaptation of rice plants to such rainfed lowlands, several roots traits have been shown to be desirable such as deep roots, strong roots that can penetrate hardpan (Cairns, Impa, O'Toole, Jagadish, & Price, 2011;Clark, Ferraris, Price, & Whalley, 2008;Wade et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Functional roles of root plasticity and its contribution to water uptake and dry matter production of CSSLs with the genetic background of KDML105 under soil moisture fluctuation

Owusu-Nketia

Siangliw

et al. 2018

Plant Production Science

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Soil moisture fluctuation (SMF) stress due to erratic rainfall in rainfed lowland (RFL) rice ecosystems negatively affect production. Under such condition, root plasticity is one of the key traits that play important roles for plant adaptation. This study aimed to evaluate root plasticity expression and its functional roles in water uptake, dry matter production and yield under SMF using three chromosome segment substitution lines (CSSLs) with major genetic background of KDML105 and a common substituted segment in chromosome 8. The CSSLs showed greater shoot dry matter production than KDML105 under SMF, which was attributed to the maintenance of stomatal conductance resulting in higher grain yield. The root system development based on total root length of the CSSLs were significantly higher than that of KDML105 due to the promoted production of nodal and lateral roots. These results implied that the common substituted segments in chromosome 8 of the 3 CSSLs may be responsible for the expression of their root plasticity under SMF and contributed to the increase in water uptake and consequently dry matter production and yield. These CSSLs could be used as a good source of genetic material for drought resistance breeding programs targeting rainfed lowland condition with fluctuating soil moisture environments and for further genetic studies to elucidate mechanisms underlying root plasticity. ARTICLE HISTORY

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Genetic loci responding to two cycles of divergent selection for grain yield under drought stress in a rice breeding population

Cited by 62 publications

References 15 publications

Mapping quantitative trait loci in selected breeding populations: A segregation distortion approach

Mapping quantitative trait loci in selected breeding populations: A segregation distortion approach

Fine mapping of consistent quantitative trait loci for yield under drought stress using rice (Oryza sativa) recombinant inbred lines adapted to rainfed environment

Functional roles of root plasticity and its contribution to water uptake and dry matter production of CSSLs with the genetic background of KDML105 under soil moisture fluctuation

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