Inheritance and QTL Mapping of Antibiosis to Green Leafhopper in Rice

Wang, Chunming; Yasui, Hirofumi; Yoshimura, Atsushi; Zhai, Huqu; Wan, Jianmin

doi:10.2135/cropsci2004.1039a

Cited by 10 publications

(7 citation statements)

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“…Gene pyramiding is difficult using conventional phenotyping methods, due to the epistatic effects of genes [25]. However, an advantage of pyramiding the two QTLs governing seed yield was observed in our study, and the identification of markers linked with each QTL allows for the identification of plants carrying one or both QTLs.…”

Section: Discussionmentioning

confidence: 67%

An approach for jatropha improvement using pleiotropic QTLs regulating plant growth and seed yield

Sun

Liu

et al. 2012

Biotechnol Biofuels

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BackgroundHigher seed yield is one of the objectives of jatropha breeding. However, genetic analysis of the yield traits has not been done in jatropha. Quantitative trait loci (QTL) mapping was conducted to identify genetic factors controlling growth and seed yield in jatropha, a promising biofuel crop.ResultsA linkage map was constructed consisting of 105 SSR (simple sequence repeat) markers converged into 11 linkage groups. With this map, we identified a total of 28 QTLs for 11 growth and seed traits using a population of 296 backcrossing jatropha trees. Two QTLs qTSW-5 and qTSW-7 controlling seed yield were mapped on LGs 5 and 7 respectively, where two QTL clusters controlling yield related traits were detected harboring five and four QTLs respectively. These two QTL clusters were critical with pleiotropic roles in regulating plant growth and seed yield. Positive additive effects of the two QTLs indicated higher values for the traits conferred by the alleles from J. curcas, while negative additive effects of the five QTLs on LG6, controlling plant height, branch number (in the 4th and 10th months post seed germination), female flower number and fruit number respectively, indicated higher values conferred by the alleles from J. integerrima. Therefore favored alleles from both the parents could be expected to be integrated into elite jatropha plant by further backcrossing and marker assisted selection. Efficient ways to improve the seed yield by applying the two QTL clusters are discussed.ConclusionThis study is the first report on genetic analysis of growth and seed traits with molecular markers in jatropha. An approach for jatropha improvement is discussed using pleiotropic QTLs, which will be likely to lead to initiation of molecular breeding in jatropha by integrating more markers in the QTL regions.

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Section: Discussionmentioning

confidence: 67%

An approach for jatropha improvement using pleiotropic QTLs regulating plant growth and seed yield

Sun

Liu

et al. 2012

Biotechnol Biofuels

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“…Various germplasms were successfully utilized for development of chromosome segment substitution lines for studies on pest and disease resistance and other agronomic triats in rice [21-23]. Here we generated backcross populations for map construction and QTL mapping, which required less time to be developed and being 'immortal' for future QTL mapping due to jatropha's perennial life cycle.…”

Section: Discussionmentioning

confidence: 99%

Mapping QTLs for oil traits and eQTLs for oleosin genes in jatropha

Liu

Wang

et al. 2011

BMC Plant Biol

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BackgroundThe major fatty acids in seed oil of jatropha, a biofuel crop, are palmitic acid (C16:0), stearic acid (C18:0), oleic acid (C18:1) and linoleic acid (C18:2). High oleic acid and total oil content are desirable for jatropha breeding. Until now, little was known about the genetic bases of these oil traits in jatropha. In this study, quantitative trait locus (QTL) and expression QTL analyses were applied to identify genetic factors that are relevant to seed oil traits in jatropha.ResultsComposite interval mapping identified 18 QTL underlying the oil traits. A highly significant QTL qC18:1-1 was detected at one end of linkage group (LG) 1 with logarithm of the odd (LOD) 18.4 and percentage of variance explained (PVE) 36.0%. Interestingly, the QTL qC18:1-1 overlapped with qC18:2-1, controlling oleic acid and linoleic acid compositions. Among the significant QTL controlling total oil content, qOilC-4 was mapped on LG4 a relatively high significant level with LOD 5.0 and PVE 11.1%. Meanwhile, oleosins are the major composition in oil body affecting oil traits; we therefore developed SNP markers in three oleosin genes OleI, OleII and OleIII, which were mapped onto the linkage map. OleI and OleIII were mapped on LG5, closing to QTLs controlling oleic acid and stearic acid. We further determined the expressions of OleI, OleII and OleIII in mature seeds from the QTL mapping population, and detected expression QTLs (eQTLs) of the three genes on LGs 5, 6 and 8 respectively. The eQTL of OleIII, qOleIII-5, was detected on LG5 with PVE 11.7% and overlapped with QTLs controlling stearic acid and oleic acid, implying a cis- or trans-element for the OleIII affecting fatty acid compositions.ConclusionWe identified 18 QTLs underlying the oil traits and 3 eQTLs of the oleosin acid genes. The QTLs and eQTLs, especially qC18:1-1, qOilC-4 and qOleIII-5 with contribution rates (R2) higher than 10%, controlling oleic acid, total oil content and oleosin gene expression respectively, will provide indispensable data for initiating molecular breeding to improve seed oil traits in jatropha, the key crop for biodiesel production.

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“…QTLs affecting the biology of several hemipterans have been described in tomato (Maliepaard et al, 1995), wheat (Castro et al, 2005) and rice (Alam and Cohen, 1998;Wang et al, 2004;Duan et al, 2007). These QTLs affect the behaviour, the biotic potential, or both of their targets.…”

Section: Discussionmentioning

confidence: 99%

Mapping and validation of QTLs for resistance to aphids and whiteflies in melon

et al. 2010

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Aphis gossypii and Bemisia tabaci are severe hemipteran pests of melon crops and breeding for resistance to both insects is required to reduce pesticide use. Resistance was evaluated for its effect on behaviour and biotic potential of both hemipterans in a population of recombinant inbred lines (RILs) derived from the cross Védrantais x PI 161375. Insect variability was considered using two A. gossypii clones and two B. tabaci populations. Two additive QTLs affected the whiteflies. Four additive QTLs and two couples of epistatic QTLs affected the aphids. Amongst them, a major QTL affects both behaviour and biotic potential of A. gossypii and therefore a same R gene induces both antixenosis and antibiosis. This major QTL colocalizes with the Vat gene belonging to the NBS-LRR gene family. No loci affected both aphids and whiteflies contrary to what was observed for the Mi1.2 gene, a NBS-LRR gene in tomato. Original populations with different allelic compositions at QTLs affecting A. gossypii were built by one inter-crossing of RILs used for the mapping process. The genetic background was shown homogeneous between these populations what allowed validating QTLs and investigating the effect of allelic combinations at QTLs. Effects of QTLs were stronger than expected and some QTLs had a wider spectrum than expected. This strategy of validation appeared rapid and low cost.

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Inheritance and QTL Mapping of Antibiosis to Green Leafhopper in Rice

Cited by 10 publications

References 1 publication

An approach for jatropha improvement using pleiotropic QTLs regulating plant growth and seed yield

An approach for jatropha improvement using pleiotropic QTLs regulating plant growth and seed yield

Mapping QTLs for oil traits and eQTLs for oleosin genes in jatropha

Mapping and validation of QTLs for resistance to aphids and whiteflies in melon

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