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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

Finding protein-coding genes through human polymorphisms.

Edward Wijaya¹, Martin C Frith, Paul Horton

¹Graduate School of Frontier Sciences, University of Tokyo, Kashiwa, Japan. e-wijaya@cb.k.u-tokyo.ac.jp

|January 26, 2013

Summary

This summary is machine-generated.

Human genome variations can create novel protein-coding genes not found in reference catalogs. This study identifies 5,737 new potential genes, impacting human biology and medicine research.

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Area of Science:

Genomics
Bioinformatics
Human Biology

Background:

Human gene catalogs are essential for biology and medicine.
Current catalogs rely on reference genome sequences, overlooking individual genetic variations (polymorphisms).
The impact of polymorphisms on gene identification itself remains understudied.

Purpose of the Study:

To investigate how genetic polymorphisms affect the computational identification of protein-coding genes.
To discover novel protein-coding genes arising from genomic variations.

Main Methods:

Computationally predicted protein-coding genes by identifying long open reading frames (ORFs) in mRNA sequences aligned to a reference genome.
Systematically evaluated the impact of known polymorphisms on ORF prediction.
Utilized homology searches to validate the protein-coding potential of newly identified ORFs.

Main Results:

Genetic polymorphisms can disrupt existing open reading frames (ORFs) and create new ones.
Identified 5,737 putative protein-coding genes absent from the reference genome.
These novel genes, supported by protein homology, were found in previously unannotated genomic regions in other catalogs.

Conclusions:

Individual genome polymorphisms can lead to the discovery of novel protein-coding genes.
This finding challenges the completeness of current human gene catalogs.
Highlights the importance of considering genetic variation in comprehensive gene identification.