Dataset Information

Recombination spot identification Based on gapped k-mers.

ABSTRACT: Recombination is crucial for biological evolution, which provides many new combinations of genetic diversity. Accurate identification of recombination spots is useful for DNA function study. To improve the prediction accuracy, researchers have proposed several computational methods for recombination spot identification. The k-mer feature is one of the most useful features for modeling the properties and function of DNA sequences. However, it suffers from the inherent limitation. If the value of word length k is large, the occurrences of k-mers are closed to a binary variable, with a few k-mers present once and most k-mers are absent. This usually causes the sparse problem and reduces the classification accuracy. To solve this problem, we add gaps into k-mer and introduce a new feature called gapped k-mer (GKM) for identification of recombination spots. By using this feature, we present a new predictor called SVM-GKM, which combines the gapped k-mers and Support Vector Machine (SVM) for recombination spot identification. Experimental results on a widely used benchmark dataset show that SVM-GKM outperforms other highly related predictors. Therefore, SVM-GKM would be a powerful predictor for computational genomics.

SUBMITTER: Wang R

PROVIDER: S-EPMC4814916 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

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Recombination spot identification Based on gapped k-mers.

Wang Rong R Xu Yong Y Liu Bin B

Scientific reports 20160331

Recombination is crucial for biological evolution, which provides many new combinations of genetic diversity. Accurate identification of recombination spots is useful for DNA function study. To improve the prediction accuracy, researchers have proposed several computational methods for recombination spot identification. The k-mer feature is one of the most useful features for modeling the properties and function of DNA sequences. However, it suffers from the inherent limitation. If the value of ...[more]

PMID: 27030570

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Project description:BackgroundPlMERS-CoV is a coronavirus known to cause severe disease in humans, taxonomically classified under the subgenus Merbecovirus. Recent findings showed that the close relatives of MERS-CoV infecting vespertillionid bats (family Vespertillionidae), named NeoCoV and PDF-2180, use their hosts' ACE2 as their entry receptor, unlike the DPP4 receptor usage of MERS-CoV. Previous research suggests that this difference in receptor usage between these related viruses is a result of recombination. However, the precise location of the recombination breakpoints and the details of the recombination event leading to the change of receptor usage remain unclear.MethodsWe used maximum likelihood-based phylogenetics and genetic similarity comparisons to characterise the evolutionary history of all complete Merbecovirus genome sequences. Recombination events were detected by multiple computational methods implemented in the recombination detection program. To verify the influence of recombination, we inferred the phylogenetic relation of the merbecovirus genomes excluding recombinant segments and that of the viruses' receptor binding domains and examined the level of congruency between the phylogenies. Finally, the geographic distribution of the genomes was inspected to identify the possible location where the recombination event occurred.ResultsSimilarity plot analysis and the recombination-partitioned phylogenetic inference showed that MERS-CoV is highly similar to NeoCoV (and PDF-2180) across its whole genome except for the spike-encoding region. This is confirmed to be due to recombination by confidently detecting a recombination event between the proximal ancestor of MERS-CoV and a currently unsampled merbecovirus clade. Notably, the upstream recombination breakpoint was detected in the N-terminal domain and the downstream breakpoint at the S2 subunit of spike, indicating that the acquired recombined fragment includes the receptor-binding domain. A tanglegram comparison further confirmed that the receptor binding domain-encoding region of MERS-CoV was acquired via recombination. Geographic mapping analysis on sampling sites suggests the possibility that the recombination event occurred in Africa.ConclusionTogether, our results suggest that recombination can lead to receptor switching of merbecoviruses during circulation in bats. These results are useful for future epidemiological assessments and surveillance to understand the spillover risk of bat coronaviruses to the human population.

Dataset Information

Recombination spot identification Based on gapped k-mers.

Publications

Recombination spot identification Based on gapped k-mers.

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