Identifying a High Fraction of the Human Genome to be under Selective Constraint Using GERP++

By Eugene Davydov, David L. Goode, Marina Sirota, Gregory M. Cooper, Arend Sidow, Serafim Batzoglou. 2010

1,712 citations recorded by the source corpus.

Computational efforts to identify functional elements within genomes leverage comparative sequence information by looking for regions that exhibit evidence of selective constraint. One way of detecting constrained elements is to follow a bottom-up approach by computing constraint scores for individual positions of a multiple alignment and then defining constrained elements as segments of contiguous, highly scoring nucleotide positions. Here we present GERP++, a new tool that uses maximum likelihood evolutionary rate estimation for position-specific scoring and, in contrast to previous bottom-up methods, a novel dynamic programming approach to subsequently define constrained elements. GERP++ evaluates a richer set of candidate element breakpoints and ranks them based on statistical significance, eliminating the need for biased heuristic extension techniques. Using GERP++ we identify over 1.3 million constrained elements spanning over 7% of the human genome. We predict a higher fraction than earlier estimates largely due to the annotation of longer constrained elements, which improves one to one correspondence between predicted elements with known functional sequences. GERP++ is an efficient and effective tool to provide both nucleotide- and element-level constraint scores within deep multiple sequence alignments.

Subfields: Molecular Biology

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Citations in the corpus

Genic Intolerance to Functional Variation and the Interpretation of Personal Genomes (2013, neutral): “…missense mutations, yet another future direction could be to incorporate variant-level information in the form of conservation scores (e.g. GERP ++ ) [1] or in silico protein-damaging characterizing tools (e.g. PolyPhen-2 [2] or SIFT [4]), as we briefly explored in this paper with the RVIS-PP2.”
Comparison and integration of deleteriousness prediction methods for nonsynonymous SNVs in whole exome sequencing studies. (2015, background): “2) (25) and CONDEL (26)] and 3 conservation scores [GERP++ (27), SiPhy (28) (http://www.”
dbNSFP v3.0: A One-Stop Database of Functional Predictions and Annotations for Human Non-synonymous and Splice Site SNVs (2016, background): “It added two functional prediction scores, MutationAssessor [Reva et al., 2011] and FATHMM [Shihab et al., 2013]; two conservation scores, GERP++ [Davydov et al., 2010] and SiPhy C© 2015 WILEY PERIODICALS, INC. [Garber et al., 2009; Lindblad-Toh et al., 2011]; and allele frequencies from the 1000…”
dbNSFP v2.0: A Database of Human Non-synonymous SNVs and Their Functional Predictions and Annotations (2013, methodology): “FATHMM and GERP++ show skewed unimodal distributions, while MutationAssessor, PhyloP and SiPhy show complex multimodal distributions.”
PERCH: a unified framework for disease gene prioritization (2017, neutral): “…PolyPhen2 [Adzhubei et al., 2010], SIFT [Kumar et al., 2009], FATHMM [Shihab et al., 2013], LRT [Chun and Fay, 2009], Mutation Taster [Schwarz et al., 2010], Mutation Assessor [Reva et al., 2011], PhyloP [Pollard et al., 2010], GERP++ [Davydov et al., 2010], and SiPhy [Garber et al., 2009].”