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Whole genome sequencing of elite rice cultivars as a comprehensive information resource for marker assisted selection.

Duitama J, Silva A, Sanabria Y, Cruz DF, Quintero C, Ballen C, Lorieux M, Scheffler B, Farmer A, Torres E, Oard J, Tohme J - PLoS ONE (2015)

Bottom Line: We identified repetitive elements and recurrent copy number variation covering about 200 Mbp of the rice genome.Genotyping of over 18 million polymorphic locations within O. sativa allowed us to reconstruct the individual haplotype patterns shaping the genomic background of elite varieties used by farmers throughout the Americas.We expect that both the analysis methods and the genomic information described here would be of great use for the rice research community and for other groups carrying on similar sequencing efforts in other crops.

View Article: PubMed Central - PubMed

Affiliation: Agrobiodiversity research area, International Center for Tropical Agriculture, Cali, Colombia.

ABSTRACT
Current advances in sequencing technologies and bioinformatics revealed the genomic background of rice, a staple food for the poor people, and provided the basis to develop large genomic variation databases for thousands of cultivars. Proper analysis of this massive resource is expected to give novel insights into the structure, function, and evolution of the rice genome, and to aid the development of rice varieties through marker assisted selection or genomic selection. In this work we present sequencing and bioinformatics analyses of 104 rice varieties belonging to the major subspecies of Oryza sativa. We identified repetitive elements and recurrent copy number variation covering about 200 Mbp of the rice genome. Genotyping of over 18 million polymorphic locations within O. sativa allowed us to reconstruct the individual haplotype patterns shaping the genomic background of elite varieties used by farmers throughout the Americas. Based on a reconstruction of the alleles for the gene GBSSI, we could identify novel genetic markers for selection of varieties with high amylose content. We expect that both the analysis methods and the genomic information described here would be of great use for the rice research community and for other groups carrying on similar sequencing efforts in other crops.

No MeSH data available.


Genome-wide diversity patterns for sequenced cultivars of indica and japonica.a) Neighbor joining dendogram for the full dataset of accessions analyzed in this study. b) Moving from within to outside, the circles have the following information: 1). Density of repeat elements (0% to 100%). 2) Diversity within japonica (0–10). 3) Diversity within indica (0–10). 4) Pairwise Fst between indica and japonica (0–1). For each population, diversity is estimated in 100kbp windows as the average number of pairwise differences per kilobasepair (See methods for details). Green colors indicate values close to the maximum on each category (or larger for the case of diversity values). Red colors indicate values close to zero. Yellow colors indicate intermediate values. Genomic locations of genes related to selective sweeps are shown in red lines.
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pone.0124617.g001: Genome-wide diversity patterns for sequenced cultivars of indica and japonica.a) Neighbor joining dendogram for the full dataset of accessions analyzed in this study. b) Moving from within to outside, the circles have the following information: 1). Density of repeat elements (0% to 100%). 2) Diversity within japonica (0–10). 3) Diversity within indica (0–10). 4) Pairwise Fst between indica and japonica (0–1). For each population, diversity is estimated in 100kbp windows as the average number of pairwise differences per kilobasepair (See methods for details). Green colors indicate values close to the maximum on each category (or larger for the case of diversity values). Red colors indicate values close to zero. Yellow colors indicate intermediate values. Genomic locations of genes related to selective sweeps are shown in red lines.

Mentions: For further validation of our genotype calls, we built neighbor-joining dendograms using the genetic distances estimated from the high quality SNPs (filter 3 in Table 1) identified in the whole dataset and within each subpopulation (Fig 1a, S3 Fig and S1–S4 Files). The dendograms were consistent with those shown in previous studies [4, 7]. Nonetheless, we obtained a clearer separation between indica and O. nivara accessions when compared with [7] presumably due to greater number of indica accessions included in our analysis. Population structure analysis of the high quality SNPs within O. sativa accessions consistently separated the indica, aus, aromatic, temperate japonica and tropical japonica populations as values of the number of allowed populations increased from 2 to 5 (S4 Fig). Pairwise Fst values predicted by structure [33] ranged from 0.1 for tropical vs. temperate japonica to 0.37 for indica vs temperate japonica. These pairwise Fsts were smaller than previously reported [4] probably because the elite lines in our study contributed large haplotypes of outgroup introgressions that reduced the overall segregation between indica and japonica. We calculated for each population and for each filtering strategy the number of private SNPs (polymorphic in only one population) (S5 Fig) and we found that the groups indica and O. rufipogon showed the largest number of private SNPs and that aromatic and temperate japonica showed the smallest numbers of private SNPs. We finally calculated the linkage disequilibrium (LD) decay for O. sativa, indica and japonica and we found that, consistent with previous studies [3, 14], the LD-decay was faster for indica compared to japonica and to O. sativa (S6 Fig).


Whole genome sequencing of elite rice cultivars as a comprehensive information resource for marker assisted selection.

Duitama J, Silva A, Sanabria Y, Cruz DF, Quintero C, Ballen C, Lorieux M, Scheffler B, Farmer A, Torres E, Oard J, Tohme J - PLoS ONE (2015)

Genome-wide diversity patterns for sequenced cultivars of indica and japonica.a) Neighbor joining dendogram for the full dataset of accessions analyzed in this study. b) Moving from within to outside, the circles have the following information: 1). Density of repeat elements (0% to 100%). 2) Diversity within japonica (0–10). 3) Diversity within indica (0–10). 4) Pairwise Fst between indica and japonica (0–1). For each population, diversity is estimated in 100kbp windows as the average number of pairwise differences per kilobasepair (See methods for details). Green colors indicate values close to the maximum on each category (or larger for the case of diversity values). Red colors indicate values close to zero. Yellow colors indicate intermediate values. Genomic locations of genes related to selective sweeps are shown in red lines.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4414565&req=5

pone.0124617.g001: Genome-wide diversity patterns for sequenced cultivars of indica and japonica.a) Neighbor joining dendogram for the full dataset of accessions analyzed in this study. b) Moving from within to outside, the circles have the following information: 1). Density of repeat elements (0% to 100%). 2) Diversity within japonica (0–10). 3) Diversity within indica (0–10). 4) Pairwise Fst between indica and japonica (0–1). For each population, diversity is estimated in 100kbp windows as the average number of pairwise differences per kilobasepair (See methods for details). Green colors indicate values close to the maximum on each category (or larger for the case of diversity values). Red colors indicate values close to zero. Yellow colors indicate intermediate values. Genomic locations of genes related to selective sweeps are shown in red lines.
Mentions: For further validation of our genotype calls, we built neighbor-joining dendograms using the genetic distances estimated from the high quality SNPs (filter 3 in Table 1) identified in the whole dataset and within each subpopulation (Fig 1a, S3 Fig and S1–S4 Files). The dendograms were consistent with those shown in previous studies [4, 7]. Nonetheless, we obtained a clearer separation between indica and O. nivara accessions when compared with [7] presumably due to greater number of indica accessions included in our analysis. Population structure analysis of the high quality SNPs within O. sativa accessions consistently separated the indica, aus, aromatic, temperate japonica and tropical japonica populations as values of the number of allowed populations increased from 2 to 5 (S4 Fig). Pairwise Fst values predicted by structure [33] ranged from 0.1 for tropical vs. temperate japonica to 0.37 for indica vs temperate japonica. These pairwise Fsts were smaller than previously reported [4] probably because the elite lines in our study contributed large haplotypes of outgroup introgressions that reduced the overall segregation between indica and japonica. We calculated for each population and for each filtering strategy the number of private SNPs (polymorphic in only one population) (S5 Fig) and we found that the groups indica and O. rufipogon showed the largest number of private SNPs and that aromatic and temperate japonica showed the smallest numbers of private SNPs. We finally calculated the linkage disequilibrium (LD) decay for O. sativa, indica and japonica and we found that, consistent with previous studies [3, 14], the LD-decay was faster for indica compared to japonica and to O. sativa (S6 Fig).

Bottom Line: We identified repetitive elements and recurrent copy number variation covering about 200 Mbp of the rice genome.Genotyping of over 18 million polymorphic locations within O. sativa allowed us to reconstruct the individual haplotype patterns shaping the genomic background of elite varieties used by farmers throughout the Americas.We expect that both the analysis methods and the genomic information described here would be of great use for the rice research community and for other groups carrying on similar sequencing efforts in other crops.

View Article: PubMed Central - PubMed

Affiliation: Agrobiodiversity research area, International Center for Tropical Agriculture, Cali, Colombia.

ABSTRACT
Current advances in sequencing technologies and bioinformatics revealed the genomic background of rice, a staple food for the poor people, and provided the basis to develop large genomic variation databases for thousands of cultivars. Proper analysis of this massive resource is expected to give novel insights into the structure, function, and evolution of the rice genome, and to aid the development of rice varieties through marker assisted selection or genomic selection. In this work we present sequencing and bioinformatics analyses of 104 rice varieties belonging to the major subspecies of Oryza sativa. We identified repetitive elements and recurrent copy number variation covering about 200 Mbp of the rice genome. Genotyping of over 18 million polymorphic locations within O. sativa allowed us to reconstruct the individual haplotype patterns shaping the genomic background of elite varieties used by farmers throughout the Americas. Based on a reconstruction of the alleles for the gene GBSSI, we could identify novel genetic markers for selection of varieties with high amylose content. We expect that both the analysis methods and the genomic information described here would be of great use for the rice research community and for other groups carrying on similar sequencing efforts in other crops.

No MeSH data available.