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Table 3 Evaluation of pathogenicity of novel variants using in-silico prediction tools

From: Urea cycle disorders in India: clinical course, biochemical and genetic investigations, and prenatal testing

Gene

Mutation

Protein change

Mutation taster

LRT

SIFT

PROVEAN

DANN

ExAC

dbSNP

ASS1

c.190G > A

p.Val64Ile

Disease causing

Neutral

Tolerated

Neutral

0.9791

0.00003303

556,297,791

c.269G > A

p.Gly90Asp

Disease causing

Unknown

Damaging

Damaging

0.9985

Not Present

1,422,867,920

c.271A > C

p.Thr91Pro

Disease causing

Unknown

Damaging

Damaging

0.9963

0.00003324

769,018,733

c.570C > A

p.Tyr190Ter

Disease causing

Unknown

NA

NA

0.9957

Not Present

Not Present

c.1139delA

p.Gln380Argfs*20

Disease causing

NA

NA

NA

NA

Not Present

1,213,378,896

ASL

c.89_94delinsGTCGTA

p.Tyr30_Asp31delinsCysArg

Disease causing

NA

NA

NA

NA

Not present

Not present

c.326C > G

p.Thr109Arg

Disease causing

Deleterious

Damaging

Damaging

0.9938

Not present

Not Present

c.593C > T

p.Pro198Leu

Disease causing

Deleterious

Damaging

Damaging

0.9992

Not Present

1,282,829,485

c.649C > T

p.Arg217Ter

Disease causing

Neutral

NA

NA

0.9972

0.000008443

369,879,957

c.733T > C

p.Trp245Arg

Disease causing

Deleterious

Damaging

Damaging

0.9941

Not present

Not Present

c.749T > A

p.Met250Lys

Disease causing

Deleterious

Damaging

Damaging

0.9791

Not present

754,634,171

c.913G > A

p.Gly305Arg

Disease causing

Deleterious

Damaging

Damaging

0.9993

Not present

Not Present

c.967A > G

p.Lys323Glu

Disease causing

Deleterious

Damaging

Damaging

0.9987

Not present

Not Present

OTC

c.773_790del

p.Asn258_263Del

Disease causing

NA

NA

NA

NA

Not present

Not Present

c.805G > A

p.Gly269Arg

Disease causing

Deleterious

Damaging

Damaging

0.9992

Not Present

Not Present

ARG1

c.2T > C

p.Met1Thr

Disease causing

Deleterious

Damaging

Neutral

0.9809

Not Present

Not Present

c.132_146del

p.Gln44_Lys48del

Disease causing

NA

NA

NA

NA

Not Present

Not Present

c.295G > A

p.Gly99Arg

Disease causing

Deleterious

Damaging

Damaging

0.9993

0.00001658

753,829,097

c.551delC

p.Pro184Leufs*7

Disease causing

NA

NA

NA

NA

Not Present

Not Present

c.802 + 2 T > G

Splice site

Disease causing

NA

NA

NA

0.9948

Not Present

Not Present

c.877delG

p.Val293Ter

Disease causing

NA

NA

NA

NA

Not Present

Not Present

CPS1

c.254 + 4A > G

Splice site

Disease causing

NA

NA

NA

0.9747

Not Present

Not Present

NAGS

c.787G > T

p.Glu263Ter

Disease causing

Deleterious

NA

NA

0.9963

Not Present

Not Present

c.991C > T

p.Gln331Ter

Disease causing

Deleterious

NA

NA

0.9973

Not Present

1,445,639,047

  1. Mutation Taster: An in silico prediction tool for the pathogenicity of a variant based on evolutionary conservation, splice-site, mRNA, protein and regulatory features. The potential is predicted by a naive Bayes classifier
  2. LRT: Likelihood ratio test (LRT) predicts deleterious variants through identification of highly conserved amino acid regions using a comparative genomics data set of 32 vertebrate species. Range 0 to 1
  3. SIFT: SIFT (sorts intolerant from tolerant) is an in silico prediction tool for nonsynonymous variants based on sequence homology derived from closely related sequences collected through PSI-BLAST. Range 0 to 1 with values less than 0.05 usually considered intolerant. 40% of the values in this database are below 0.01
  4. PROVEAN: Protein Variation Effect Analyzer is an in silico tool that predicts how nonsynonymous, MNP, or in-frame indel variant will affect a protein’s biological function. The prediction is based on alignment-based scores derived from pairwise sequence alignments between the query sequence and each of the related sequences at the protein level. Range − 14 to + 14
  5. DANN: DANN is a pathogenicity scoring methodology developed by Daniel Quang, Yifei Chen and Xiaohui Xie at the University of California, Irvine. It is based on deep neural networks. The value range is 0 to 1, with 1 given to the variants predicted to be the most damaging