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Single feature polymorphism discovery in rice.

Kumar R, Qiu J, Joshi T, Valliyodan B, Xu D, Nguyen HT - PLoS ONE (2007)

Bottom Line: The efficacy of such method was tested in rice, and the results presented in the paper indicate high sensitivity in predicting SFP.The sensitivity of polymorphism detection was further demonstrated by the fact that no biasness was observed in detecting SFP with either single or multiple nucleotide polymorphisms.The high density SFP data that can be generated quite effectively by the current method has promise for high resolution genetic mapping studies, as physical location of features are well-defined on rice genome.

View Article: PubMed Central - PubMed

Affiliation: Division of Plant Sciences, University of Missouri-Columbia, Columbia, Missouri, United States of America. kumarr@missouri.edu

ABSTRACT
The discovery of nucleotide diversity captured as single feature polymorphism (SFP) by using the expression array is a high-throughput and effective method in detecting genome-wide polymorphism. The efficacy of such method was tested in rice, and the results presented in the paper indicate high sensitivity in predicting SFP. The sensitivity of polymorphism detection was further demonstrated by the fact that no biasness was observed in detecting SFP with either single or multiple nucleotide polymorphisms. The high density SFP data that can be generated quite effectively by the current method has promise for high resolution genetic mapping studies, as physical location of features are well-defined on rice genome.

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Polymorphic features predicted by in-silico analyses and gene-chip experiments. NIP = Nipponbare; CP = Cypress; RT = RT0034 and PM = perfect match.
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pone-0000284-g004: Polymorphic features predicted by in-silico analyses and gene-chip experiments. NIP = Nipponbare; CP = Cypress; RT = RT0034 and PM = perfect match.

Mentions: All the computationally predicted SFPs (supplementary Table S3), irrespective of number associated with polymorphism direction (+/−), were considered as an example of approximate number of SFPs that can be predicted when the methods presented in the paper is used to derive SFP call between japonica and indica sub-species. Since SFPs in CP&RT pair was validated by sequence information, we compared the numbers of gene-chip predicted SFPs to those predicted by in-silico analyses. From gene-chip method at 9% estimated FDR, 4% of the total perfect match (PM) features present on the array (see methods) were polymorphic in CP&RT compared to 10.8% predicted by in-silico analyses in Nipponbare & 93-11 (Figure 4). However by lowering the stringency of estimated FDR to 10% the number of predicted SFPs in CP&RT dataset nearly doubled to 61055 that account 9.6% of the total PM features (Table 1b, Figure 4). Although validation of SFPs predicted at 10% estimated FDR increased the sensitivity of SFP detection considerably but simultaneously the observed FDR determined after sequencing also doubled to 20% compared to the estimated value by permutation (Table 3b). Considering the above results if we exclude ∼20% of the total SFP predicted at 10% estimated FDR in CP&RT dataset still ∼8% of total features present on the array are polymorphic compared to 10.8% predicted by in-silico analyses in Nipponbare & 93-11. The discrepancy in number of polymorphic features between the CP&RT and Nipponbare&93-11 datasets may be because of expected inherent diversity in their genome.


Single feature polymorphism discovery in rice.

Kumar R, Qiu J, Joshi T, Valliyodan B, Xu D, Nguyen HT - PLoS ONE (2007)

Polymorphic features predicted by in-silico analyses and gene-chip experiments. NIP = Nipponbare; CP = Cypress; RT = RT0034 and PM = perfect match.
© Copyright Policy
Related In: Results  -  Collection

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pone-0000284-g004: Polymorphic features predicted by in-silico analyses and gene-chip experiments. NIP = Nipponbare; CP = Cypress; RT = RT0034 and PM = perfect match.
Mentions: All the computationally predicted SFPs (supplementary Table S3), irrespective of number associated with polymorphism direction (+/−), were considered as an example of approximate number of SFPs that can be predicted when the methods presented in the paper is used to derive SFP call between japonica and indica sub-species. Since SFPs in CP&RT pair was validated by sequence information, we compared the numbers of gene-chip predicted SFPs to those predicted by in-silico analyses. From gene-chip method at 9% estimated FDR, 4% of the total perfect match (PM) features present on the array (see methods) were polymorphic in CP&RT compared to 10.8% predicted by in-silico analyses in Nipponbare & 93-11 (Figure 4). However by lowering the stringency of estimated FDR to 10% the number of predicted SFPs in CP&RT dataset nearly doubled to 61055 that account 9.6% of the total PM features (Table 1b, Figure 4). Although validation of SFPs predicted at 10% estimated FDR increased the sensitivity of SFP detection considerably but simultaneously the observed FDR determined after sequencing also doubled to 20% compared to the estimated value by permutation (Table 3b). Considering the above results if we exclude ∼20% of the total SFP predicted at 10% estimated FDR in CP&RT dataset still ∼8% of total features present on the array are polymorphic compared to 10.8% predicted by in-silico analyses in Nipponbare & 93-11. The discrepancy in number of polymorphic features between the CP&RT and Nipponbare&93-11 datasets may be because of expected inherent diversity in their genome.

Bottom Line: The efficacy of such method was tested in rice, and the results presented in the paper indicate high sensitivity in predicting SFP.The sensitivity of polymorphism detection was further demonstrated by the fact that no biasness was observed in detecting SFP with either single or multiple nucleotide polymorphisms.The high density SFP data that can be generated quite effectively by the current method has promise for high resolution genetic mapping studies, as physical location of features are well-defined on rice genome.

View Article: PubMed Central - PubMed

Affiliation: Division of Plant Sciences, University of Missouri-Columbia, Columbia, Missouri, United States of America. kumarr@missouri.edu

ABSTRACT
The discovery of nucleotide diversity captured as single feature polymorphism (SFP) by using the expression array is a high-throughput and effective method in detecting genome-wide polymorphism. The efficacy of such method was tested in rice, and the results presented in the paper indicate high sensitivity in predicting SFP. The sensitivity of polymorphism detection was further demonstrated by the fact that no biasness was observed in detecting SFP with either single or multiple nucleotide polymorphisms. The high density SFP data that can be generated quite effectively by the current method has promise for high resolution genetic mapping studies, as physical location of features are well-defined on rice genome.

Show MeSH