Limits...
A new method to reconstruct recombination events at a genomic scale.

Melé M, Javed A, Pybus M, Calafell F, Parida L, Bertranpetit J, Genographic Consortium Membe - PLoS Comput. Biol. (2010)

Bottom Line: Newer recombinations overwrite traces of past ones and our results indicate more recent recombinations are detected by IRiS with greater sensitivity.Principal component analysis and multidimensional scaling based on recotypes reproduced the relationships between the eleven HapMap Phase III populations that can be expected from known human population history, thus further validating IRiS.We believe that our new method will contribute to the study of the distribution of recombination events across the genomes and, for the first time, it will allow the use of recombination as genetic marker to study human genetic variation.

View Article: PubMed Central - PubMed

Affiliation: IBE, Institute of Evolutionary Biology (UPF-CSIC), CEXS-UPF-PRBB, Barcelona, Catalonia, Spain.

ABSTRACT
Recombination is one of the main forces shaping genome diversity, but the information it generates is often overlooked. A recombination event creates a junction between two parental sequences that may be transmitted to the subsequent generations. Just like mutations, these junctions carry evidence of the shared past of the sequences. We present the IRiS algorithm, which detects past recombination events from extant sequences and specifies the place of each recombination and which are the recombinants sequences. We have validated and calibrated IRiS for the human genome using coalescent simulations replicating standard human demographic history and a variable recombination rate model, and we have fine-tuned IRiS parameters to simultaneously optimize for false discovery rate, sensitivity, and accuracy in placing the recombination events in the sequence. Newer recombinations overwrite traces of past ones and our results indicate more recent recombinations are detected by IRiS with greater sensitivity. IRiS analysis of the MS32 region, previously studied using sperm typing, showed good concordance with estimated recombination rates. We also applied IRiS to haplotypes for 18 X-chromosome regions in HapMap Phase 3 populations. Recombination events detected for each individual were recoded as binary allelic states and combined into recotypes. Principal component analysis and multidimensional scaling based on recotypes reproduced the relationships between the eleven HapMap Phase III populations that can be expected from known human population history, thus further validating IRiS. We believe that our new method will contribute to the study of the distribution of recombination events across the genomes and, for the first time, it will allow the use of recombination as genetic marker to study human genetic variation.

Show MeSH

Related in: MedlinePlus

Distribution of the number of detections using the optimal method.Each line represents the distribution of detections for particular recombination events. The dataset corresponds to one COSI simulation. Only those recombinations reaching the threshold will be considered as true events. The pick of each distribution will locate the breakpoint position for each particular recombination event along the sequence. The optimal method (grains 20, 10 and 5 forward and reverse and a threshold of 42) creates narrower maximal intervals in the detection distributions than when only using grain 10.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC2991245&req=5

pcbi-1001010-g003: Distribution of the number of detections using the optimal method.Each line represents the distribution of detections for particular recombination events. The dataset corresponds to one COSI simulation. Only those recombinations reaching the threshold will be considered as true events. The pick of each distribution will locate the breakpoint position for each particular recombination event along the sequence. The optimal method (grains 20, 10 and 5 forward and reverse and a threshold of 42) creates narrower maximal intervals in the detection distributions than when only using grain 10.

Mentions: Finally, using the same approach, we can potentially aggregate detections of multiple runs performed with different grain sizes and also we can run the algorithm in both forward and reverse directions. This aggregation improved significantly the performance of the method (see next section) by increasing the sensitivity and reducing the false discovery rate. Moreover, it allowed a much more precise inference of the breakpoint position since maximum intervals become much narrower (Figure 3).


A new method to reconstruct recombination events at a genomic scale.

Melé M, Javed A, Pybus M, Calafell F, Parida L, Bertranpetit J, Genographic Consortium Membe - PLoS Comput. Biol. (2010)

Distribution of the number of detections using the optimal method.Each line represents the distribution of detections for particular recombination events. The dataset corresponds to one COSI simulation. Only those recombinations reaching the threshold will be considered as true events. The pick of each distribution will locate the breakpoint position for each particular recombination event along the sequence. The optimal method (grains 20, 10 and 5 forward and reverse and a threshold of 42) creates narrower maximal intervals in the detection distributions than when only using grain 10.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2991245&req=5

pcbi-1001010-g003: Distribution of the number of detections using the optimal method.Each line represents the distribution of detections for particular recombination events. The dataset corresponds to one COSI simulation. Only those recombinations reaching the threshold will be considered as true events. The pick of each distribution will locate the breakpoint position for each particular recombination event along the sequence. The optimal method (grains 20, 10 and 5 forward and reverse and a threshold of 42) creates narrower maximal intervals in the detection distributions than when only using grain 10.
Mentions: Finally, using the same approach, we can potentially aggregate detections of multiple runs performed with different grain sizes and also we can run the algorithm in both forward and reverse directions. This aggregation improved significantly the performance of the method (see next section) by increasing the sensitivity and reducing the false discovery rate. Moreover, it allowed a much more precise inference of the breakpoint position since maximum intervals become much narrower (Figure 3).

Bottom Line: Newer recombinations overwrite traces of past ones and our results indicate more recent recombinations are detected by IRiS with greater sensitivity.Principal component analysis and multidimensional scaling based on recotypes reproduced the relationships between the eleven HapMap Phase III populations that can be expected from known human population history, thus further validating IRiS.We believe that our new method will contribute to the study of the distribution of recombination events across the genomes and, for the first time, it will allow the use of recombination as genetic marker to study human genetic variation.

View Article: PubMed Central - PubMed

Affiliation: IBE, Institute of Evolutionary Biology (UPF-CSIC), CEXS-UPF-PRBB, Barcelona, Catalonia, Spain.

ABSTRACT
Recombination is one of the main forces shaping genome diversity, but the information it generates is often overlooked. A recombination event creates a junction between two parental sequences that may be transmitted to the subsequent generations. Just like mutations, these junctions carry evidence of the shared past of the sequences. We present the IRiS algorithm, which detects past recombination events from extant sequences and specifies the place of each recombination and which are the recombinants sequences. We have validated and calibrated IRiS for the human genome using coalescent simulations replicating standard human demographic history and a variable recombination rate model, and we have fine-tuned IRiS parameters to simultaneously optimize for false discovery rate, sensitivity, and accuracy in placing the recombination events in the sequence. Newer recombinations overwrite traces of past ones and our results indicate more recent recombinations are detected by IRiS with greater sensitivity. IRiS analysis of the MS32 region, previously studied using sperm typing, showed good concordance with estimated recombination rates. We also applied IRiS to haplotypes for 18 X-chromosome regions in HapMap Phase 3 populations. Recombination events detected for each individual were recoded as binary allelic states and combined into recotypes. Principal component analysis and multidimensional scaling based on recotypes reproduced the relationships between the eleven HapMap Phase III populations that can be expected from known human population history, thus further validating IRiS. We believe that our new method will contribute to the study of the distribution of recombination events across the genomes and, for the first time, it will allow the use of recombination as genetic marker to study human genetic variation.

Show MeSH
Related in: MedlinePlus