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Harnessing omics big data in nine vertebrate species by genome-wide prioritization of sequence variants with the highest predicted deleterious effect on protein function
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Rozman, Vita
(
Author
),
ID
Kunej, Tanja
(
Author
)
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https://www.liebertpub.com/doi/10.1089/omi.2018.0046
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Abstract
Harnessing the genomics big data requires innovation in how we extract and interpret biologically relevant variants. Currently, there is no established catalog of prioritized missense variants associated with deleterious protein function phenotypes. We report in this study, to the best of our knowledge, the first genome-wide prioritization of sequence variants with the most deleterious effect on protein function (potentially deleterious variants [pDelVars]) in nine vertebrate species: human, cattle, horse, sheep, pig, dog, rat, mouse, and zebrafish.The analysis was conducted using the Ensembl/BioMart tool. Genes comprising pDelVars in the highest number of examined species were identified using a Python script. Multiple genomic alignments of the selected genes were built to identify interspecies orthologous potentially deleterious variants, which we defined as the ‘‘ortho-pDelVars.’’ Genome-wide prioritization revealed that in humans, 0.12% of the known variants are predicted to be deleterious. In seven out of nine examined vertebrate species, the genes encoding the multiple PDZ domain crumbs cell polarity complex component (MPDZ) and the transforming acidic coiled-coil containing protein 2 (TACC2) comprise pDelVars. Five interspecies ortho-pDelVars were identified in three genes.These findings offer new ways to harness genomics big data by facilitating the identification of functional polymorphisms in humans and animal models and thus provide a future basis for optimization of protocols for whole genome prioritization of pDelVars and screening of orthologous sequence variants. The approach presented here can inform various postgenomic applications such as personalized medicine and multiomics study of health interventions (iatromics).
Language:
English
Keywords:
big data
,
potentially deleterious variants (pDelVars)
,
orthologous potentially deleterious variants (ortho-pDelVars)
,
PolyPhen (polymorphism phenotyping)
,
SIFT (sorts intolerant from tolerant)
,
single-nucleotide polymorphism (SNP)
Work type:
Article
Typology:
1.01 - Original Scientific Article
Organization:
BF - Biotechnical Faculty
Publication status:
Published
Publication version:
Author Accepted Manuscript
Year:
2018
Number of pages:
Str. 410-421
Numbering:
Vol. 22, no. 6
PID:
20.500.12556/RUL-133071
UDC:
575
ISSN on article:
1536-2310
DOI:
10.1089/omi.2018.0046
COBISS.SI-ID:
4072584
Publication date in RUL:
10.11.2021
Views:
1038
Downloads:
290
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Record is a part of a journal
Title:
Omics. a ǂjournal of integrative biology
Shortened title:
Omics
Publisher:
Mary Ann Liebert
ISSN:
1536-2310
COBISS.SI-ID:
512299289
Secondary language
Language:
Slovenian
Keywords:
genetika
,
genomika
,
bioinformatika
,
baze podatkov
,
proteini
,
vretenčarji
Projects
Funder:
ARRS - Slovenian Research Agency
Project number:
P4-0220
Name:
Primerjalna genomika in genomska biodiverziteta
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