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Association mapping for important agronomic traits in core collection of rice (Oryza sativa L.) with SSR markers.

Zhang P, Liu X, Tong H, Lu Y, Li J - PLoS ONE (2014)

Bottom Line: An association mapping for 12 agronomic traits was carried out using a core collection of rice consisting of 150 landraces (Panel 1) with 274 simple sequence repeat (SSR) markers, and the mapping results were further verified using a Chinese national rice micro-core collection (Panel 2) and a collection from a global molecular breeding program (Panel 3).Our results showed that (1) 76 significant (P<0.05) trait-marker associations were detected using mixed linear model (MLM) within Panel 1 in two years, among which 32% were identical with previously mapped QTLs, and 11 significant associations had >10% explained ratio of genetic variation; (2) A total of seven aforementioned trait-marker associations were verified within Panel 2 and 3 when using a general linear model (GLM) and 55 SSR markers of the 76 significant trait-marker associations.However, no significant trait-marker association was found to be identical within three panels when using the MLM model; (3) several desirable alleles of the loci which showed significant trait-marker associations were identified.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, China; State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China.

ABSTRACT
Mining elite genes within rice landraces is of importance for the improvement of cultivated rice. An association mapping for 12 agronomic traits was carried out using a core collection of rice consisting of 150 landraces (Panel 1) with 274 simple sequence repeat (SSR) markers, and the mapping results were further verified using a Chinese national rice micro-core collection (Panel 2) and a collection from a global molecular breeding program (Panel 3). Our results showed that (1) 76 significant (P<0.05) trait-marker associations were detected using mixed linear model (MLM) within Panel 1 in two years, among which 32% were identical with previously mapped QTLs, and 11 significant associations had >10% explained ratio of genetic variation; (2) A total of seven aforementioned trait-marker associations were verified within Panel 2 and 3 when using a general linear model (GLM) and 55 SSR markers of the 76 significant trait-marker associations. However, no significant trait-marker association was found to be identical within three panels when using the MLM model; (3) several desirable alleles of the loci which showed significant trait-marker associations were identified. The research provided important information for further mining these elite genes within rice landraces and using them for rice breeding.

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Plots of observed versus expected P-values using MLM (Q+K) model for 12 agronomic traits in 2009.Blue symbol represents expected P-values, and red symbol represents observed P-values.
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pone-0111508-g003: Plots of observed versus expected P-values using MLM (Q+K) model for 12 agronomic traits in 2009.Blue symbol represents expected P-values, and red symbol represents observed P-values.

Mentions: Observed versus expected P values for each trait-marker association were plotted to assess the control of type I errors. Uniform distributions between the observed and expected P values for all traits were observed, and were demonstrated by similar distributions in two years (Figures 2 and 3). As the deviations from the expectation demonstrated that the statistical analysis may cause spurious associations [28], our result indicated that the false positives were well controlled in the MLM method in this study.


Association mapping for important agronomic traits in core collection of rice (Oryza sativa L.) with SSR markers.

Zhang P, Liu X, Tong H, Lu Y, Li J - PLoS ONE (2014)

Plots of observed versus expected P-values using MLM (Q+K) model for 12 agronomic traits in 2009.Blue symbol represents expected P-values, and red symbol represents observed P-values.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4216065&req=5

pone-0111508-g003: Plots of observed versus expected P-values using MLM (Q+K) model for 12 agronomic traits in 2009.Blue symbol represents expected P-values, and red symbol represents observed P-values.
Mentions: Observed versus expected P values for each trait-marker association were plotted to assess the control of type I errors. Uniform distributions between the observed and expected P values for all traits were observed, and were demonstrated by similar distributions in two years (Figures 2 and 3). As the deviations from the expectation demonstrated that the statistical analysis may cause spurious associations [28], our result indicated that the false positives were well controlled in the MLM method in this study.

Bottom Line: An association mapping for 12 agronomic traits was carried out using a core collection of rice consisting of 150 landraces (Panel 1) with 274 simple sequence repeat (SSR) markers, and the mapping results were further verified using a Chinese national rice micro-core collection (Panel 2) and a collection from a global molecular breeding program (Panel 3).Our results showed that (1) 76 significant (P<0.05) trait-marker associations were detected using mixed linear model (MLM) within Panel 1 in two years, among which 32% were identical with previously mapped QTLs, and 11 significant associations had >10% explained ratio of genetic variation; (2) A total of seven aforementioned trait-marker associations were verified within Panel 2 and 3 when using a general linear model (GLM) and 55 SSR markers of the 76 significant trait-marker associations.However, no significant trait-marker association was found to be identical within three panels when using the MLM model; (3) several desirable alleles of the loci which showed significant trait-marker associations were identified.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, China; State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China.

ABSTRACT
Mining elite genes within rice landraces is of importance for the improvement of cultivated rice. An association mapping for 12 agronomic traits was carried out using a core collection of rice consisting of 150 landraces (Panel 1) with 274 simple sequence repeat (SSR) markers, and the mapping results were further verified using a Chinese national rice micro-core collection (Panel 2) and a collection from a global molecular breeding program (Panel 3). Our results showed that (1) 76 significant (P<0.05) trait-marker associations were detected using mixed linear model (MLM) within Panel 1 in two years, among which 32% were identical with previously mapped QTLs, and 11 significant associations had >10% explained ratio of genetic variation; (2) A total of seven aforementioned trait-marker associations were verified within Panel 2 and 3 when using a general linear model (GLM) and 55 SSR markers of the 76 significant trait-marker associations. However, no significant trait-marker association was found to be identical within three panels when using the MLM model; (3) several desirable alleles of the loci which showed significant trait-marker associations were identified. The research provided important information for further mining these elite genes within rice landraces and using them for rice breeding.

Show MeSH