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Genetic analysis of cold tolerance at the germination and booting stages in rice by association mapping.

Pan Y, Zhang H, Zhang D, Li J, Xiong H, Yu J, Li J, Rashid MA, Li G, Ma X, Cao G, Han L, Li Z - PLoS ONE (2015)

Bottom Line: In general, the negative effects were much stronger than the positive effects in both subspecies.Markers for QTL with positive effects in one subspecies were shown to be effective for selection of cold tolerance in that subspecies, but not in the other subspecies.QTL with strong negative effects on cold tolerance should be avoided during MAS breeding so as to not cancel the effect of favorable QTL at other loci.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Crop Heterosis and Utilization, Ministry of Education, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China; Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi, 530005, China.

ABSTRACT
Low temperature affects the rice plants at all stages of growth. It can cause severe seedling injury and male sterility resulting in severe yield losses. Using a mini core collection of 174 Chinese rice accessions and 273 SSR markers we investigated cold tolerance at the germination and booting stages, as well as the underlying genetic bases, by association mapping. Two distinct populations, corresponding to subspecies indica and japonica showed evident differences in cold tolerance and its genetic basis. Both subspecies were sensitive to cold stress at both growth stages. However, japonica was more tolerant than indica at all stages as measured by seedling survival and seed setting. There was a low correlation in cold tolerance between the germination and booting stages. Fifty one quantitative trait loci (QTLs) for cold tolerance were dispersed across all 12 chromosomes; 22 detected at the germination stage and 33 at the booting stage. Eight QTLs were identified by at least two of four measures. About 46% of the QTLs represented new loci. The only QTL shared between indica and japonica for the same measure was qLTSSvR6-2 for SSvR. This implied a complicated mechanism of old tolerance between the two subspecies. According to the relative genotypic effect (RGE) of each genotype for each QTL, we detected 18 positive genotypes and 21 negative genotypes in indica, and 19 positive genotypes and 24 negative genotypes in japonica. In general, the negative effects were much stronger than the positive effects in both subspecies. Markers for QTL with positive effects in one subspecies were shown to be effective for selection of cold tolerance in that subspecies, but not in the other subspecies. QTL with strong negative effects on cold tolerance should be avoided during MAS breeding so as to not cancel the effect of favorable QTL at other loci.

No MeSH data available.


Related in: MedlinePlus

Average LnP(D) and ΔK over 10 repeats of STRUCTURE simulation.
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pone.0120590.g001: Average LnP(D) and ΔK over 10 repeats of STRUCTURE simulation.

Mentions: When we ran the STRUCTURE simulation using 60 SSRs, the LnP(D) value increased with K from 1 to 10, but showed an evident knee and there was a sharp peak of Evanno’s ΔK at K = 2 (Fig. 1). These results indicated that there were two distinctly divergent populations, corresponding to subspecies indica and japonica. To survey the influence of population structure on LD, we analyzed LD in the whole population and in each of the subgroups (i.e. indica and japonica) identified by structure analysis (Fig. 2, S3 Table). At the whole population level, the r2 within the whole genome was 0.0624±0.0865. For SSR markers with physical distances less than 50 kb, the r2 was 0.1443±0.2149; for those between 50 kb and 150 kb, r2 was 0.1332±0.1829; for those between 150 kb and 500 kb, r2 was 0.0926±0.1353; for those between 500 kb and 1000 kb, r2 was 0.0624±0.0765; and for those more than 1,000 kb, r2 was 0.0605±0.0818. Thus LD for markers with physical distances shorter than 50 kb was not obviously different from those between 50 kb and 150 kb, but decreased dramatically for those further than 150 kb. Compared to the whole population, LDs within indica and japonica were obviously lower (S3 Table and Fig. 2). For SSR markers with physical distances shorter than 50 kb, mean r2 were 0.1388±0.2135 and 0.1810±0.3203 for indica and japonica, respectively; for markers between 50 kb and 150 kb, 0.0761±0.0796 and 0.0760±0.0368; for markers between 150 kb and 500 kb, 0.0331±0.0573 and 0.0392±0.0616; for markers between 500 kb and 1000 kb, 0.0155±0.0148 and 0.0336±0.0505; and for markers more than 1000 kb, 0.0134±0.0165 and 0.0201±0.0261. These results indicated that LDs between close markers (such as physical distances less than 50 kb) in both indica and japonica did not decrease relative to the whole population, however, the LDs between distant markers especially those more than 150 kb decreased dramatically (S3 Table). Given the above results, we carried out the association analysis within indica and japonica independently in order to avoid false positive associations; and given that few non-linked markers showed strong LD, we used the GLM model that controls population structure but not kinship for the association analysis within indica and japonica.


Genetic analysis of cold tolerance at the germination and booting stages in rice by association mapping.

Pan Y, Zhang H, Zhang D, Li J, Xiong H, Yu J, Li J, Rashid MA, Li G, Ma X, Cao G, Han L, Li Z - PLoS ONE (2015)

Average LnP(D) and ΔK over 10 repeats of STRUCTURE simulation.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4366098&req=5

pone.0120590.g001: Average LnP(D) and ΔK over 10 repeats of STRUCTURE simulation.
Mentions: When we ran the STRUCTURE simulation using 60 SSRs, the LnP(D) value increased with K from 1 to 10, but showed an evident knee and there was a sharp peak of Evanno’s ΔK at K = 2 (Fig. 1). These results indicated that there were two distinctly divergent populations, corresponding to subspecies indica and japonica. To survey the influence of population structure on LD, we analyzed LD in the whole population and in each of the subgroups (i.e. indica and japonica) identified by structure analysis (Fig. 2, S3 Table). At the whole population level, the r2 within the whole genome was 0.0624±0.0865. For SSR markers with physical distances less than 50 kb, the r2 was 0.1443±0.2149; for those between 50 kb and 150 kb, r2 was 0.1332±0.1829; for those between 150 kb and 500 kb, r2 was 0.0926±0.1353; for those between 500 kb and 1000 kb, r2 was 0.0624±0.0765; and for those more than 1,000 kb, r2 was 0.0605±0.0818. Thus LD for markers with physical distances shorter than 50 kb was not obviously different from those between 50 kb and 150 kb, but decreased dramatically for those further than 150 kb. Compared to the whole population, LDs within indica and japonica were obviously lower (S3 Table and Fig. 2). For SSR markers with physical distances shorter than 50 kb, mean r2 were 0.1388±0.2135 and 0.1810±0.3203 for indica and japonica, respectively; for markers between 50 kb and 150 kb, 0.0761±0.0796 and 0.0760±0.0368; for markers between 150 kb and 500 kb, 0.0331±0.0573 and 0.0392±0.0616; for markers between 500 kb and 1000 kb, 0.0155±0.0148 and 0.0336±0.0505; and for markers more than 1000 kb, 0.0134±0.0165 and 0.0201±0.0261. These results indicated that LDs between close markers (such as physical distances less than 50 kb) in both indica and japonica did not decrease relative to the whole population, however, the LDs between distant markers especially those more than 150 kb decreased dramatically (S3 Table). Given the above results, we carried out the association analysis within indica and japonica independently in order to avoid false positive associations; and given that few non-linked markers showed strong LD, we used the GLM model that controls population structure but not kinship for the association analysis within indica and japonica.

Bottom Line: In general, the negative effects were much stronger than the positive effects in both subspecies.Markers for QTL with positive effects in one subspecies were shown to be effective for selection of cold tolerance in that subspecies, but not in the other subspecies.QTL with strong negative effects on cold tolerance should be avoided during MAS breeding so as to not cancel the effect of favorable QTL at other loci.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Crop Heterosis and Utilization, Ministry of Education, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China; Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi, 530005, China.

ABSTRACT
Low temperature affects the rice plants at all stages of growth. It can cause severe seedling injury and male sterility resulting in severe yield losses. Using a mini core collection of 174 Chinese rice accessions and 273 SSR markers we investigated cold tolerance at the germination and booting stages, as well as the underlying genetic bases, by association mapping. Two distinct populations, corresponding to subspecies indica and japonica showed evident differences in cold tolerance and its genetic basis. Both subspecies were sensitive to cold stress at both growth stages. However, japonica was more tolerant than indica at all stages as measured by seedling survival and seed setting. There was a low correlation in cold tolerance between the germination and booting stages. Fifty one quantitative trait loci (QTLs) for cold tolerance were dispersed across all 12 chromosomes; 22 detected at the germination stage and 33 at the booting stage. Eight QTLs were identified by at least two of four measures. About 46% of the QTLs represented new loci. The only QTL shared between indica and japonica for the same measure was qLTSSvR6-2 for SSvR. This implied a complicated mechanism of old tolerance between the two subspecies. According to the relative genotypic effect (RGE) of each genotype for each QTL, we detected 18 positive genotypes and 21 negative genotypes in indica, and 19 positive genotypes and 24 negative genotypes in japonica. In general, the negative effects were much stronger than the positive effects in both subspecies. Markers for QTL with positive effects in one subspecies were shown to be effective for selection of cold tolerance in that subspecies, but not in the other subspecies. QTL with strong negative effects on cold tolerance should be avoided during MAS breeding so as to not cancel the effect of favorable QTL at other loci.

No MeSH data available.


Related in: MedlinePlus