Evidence map›Paper›PMID 18405366›Full record

ArticleBMC bioinformatics2008

Local conservation scores without a priori assumptions on neutral substitution rates.

Janis Dingel, Pavol Hanus, Niccolò Leonardi, Joachim Hagenauer, Jürgen Zech, Jakob C Mueller

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Article in BMC bioinformatics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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6 authors.

Janis DingelInstitute for Communications Engineering, Technische Universität München, Munich, Germany. janis.dingel@tum.de
Pavol Hanus
Niccolò Leonardi
Joachim Hagenauer
Jürgen Zech
Jakob C Mueller

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundComparative genomics aims to detect signals of evolutionary conservation as an indicator of functional constraint. Surprisingly, results of the ENCODE project revealed that about half of the experimentally verified functional elements found in non-coding DNA were classified as unconstrained by computational predictions. Following this observation, it has been hypothesized that this may be partly explained by biased estimates on neutral evolutionary rates used by existing sequence conservation metrics. All methods we are aware of rely on a comparison with the neutral rate and conservation is estimated by measuring the deviation of a particular genomic region from this rate. Consequently, it is a reasonable assumption that inaccurate neutral rate estimates may lead to biased conservation and constraint estimates.

resultsWe propose a conservation signal that is produced by local Maximum Likelihood estimation of evolutionary parameters using an optimized sliding window and present a Kullback-Leibler projection that allows multiple different estimated parameters to be transformed into a conservation measure. This conservation measure does not rely on assumptions about neutral evolutionary substitution rates and little a priori assumptions on the properties of the conserved regions are imposed. We show the accuracy of our approach (KuLCons) on synthetic data and compare it to the scores generated by state-of-the-art methods (phastCons, GERP, SCONE) in an ENCODE region. We find that KuLCons is most often in agreement with the conservation/constraint signatures detected by GERP and SCONE while qualitatively very different patterns from phastCons are observed. Opposed to standard methods KuLCons can be extended to more complex evolutionary models, e.g. taking insertion and deletion events into account and corresponding results show that scores obtained under this model can diverge significantly from scores using the simpler model.

conclusionOur results suggest that discriminating among the different degrees of conservation is possible without making assumptions about neutral rates. We find, however, that it cannot be expected to discover considerably different constraint regions than GERP and SCONE. Consequently, we conclude that the reported discrepancies between experimentally verified functional and computationally identified constraint elements are likely not to be explained by biased neutral rate estimates.

Indexed as

AlgorithmsEvolution, MolecularModels, GeneticSequence Homology, Nucleic AcidComputer SimulationConserved SequenceDNAGenetic VariationLikelihood FunctionsModels, StatisticalSequence Analysis, DNADNA

Identifiers

PMID18405366
PMCPMC2375903

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