Dataset Information

The transcript-centric mutations in human genomes.

ABSTRACT: Since the human genome is mostly transcribed, genetic variations must exhibit sequence signatures reflecting the relationship between transcription processes and chromosomal structures as we have observed in unicellular organisms. In this study, a set of 646 ubiquitous expression-invariable genes (EIGs) which are present in germline cells were defined and examined based on RNA-sequencing data from multiple high-throughput transcriptomic data. We demonstrated a relationship between gene expression level and transcript-centric mutations in the human genome based on single nucleotide polymorphism (SNP) data. A significant positive correlation was shown between gene expression and mutation, where highly-expressed genes accumulate more mutations than lowly-expressed genes. Furthermore, we found four major types of transcript-centric mutations: C?T, A?G, C?G, and G?T in human genomes and identified a negative gradient of the sequence variations aligning from the 5' end to the 3' end of the transcription units (TUs). The periodical occurrence of these genetic variations across TUs is associated with nucleosome phasing. We propose that transcript-centric mutations are one of the major driving forces for gene and genome evolution along with creation of new genes, gene/genome duplication, and horizontal gene transfer.

SUBMITTER: Cui P

PROVIDER: S-EPMC5054492 | biostudies-literature | 2012 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The transcript-centric mutations in human genomes.

Cui Peng P Lin Qiang Q Ding Feng F Hu Songnian S Yu Jun J

Genomics, proteomics & bioinformatics 20120201 1

Since the human genome is mostly transcribed, genetic variations must exhibit sequence signatures reflecting the relationship between transcription processes and chromosomal structures as we have observed in unicellular organisms. In this study, a set of 646 ubiquitous expression-invariable genes (EIGs) which are present in germline cells were defined and examined based on RNA-sequencing data from multiple high-throughput transcriptomic data. We demonstrated a relationship between gene expressio ...[more]

PMID: 22449397

Similar Datasets

Project description:BackgroundThe body of disease mutations with known phenotypic relevance continues to increase and is expected to do so even faster with the advent of new experimental techniques such as whole-genome sequencing coupled with disease association studies. However, genomic association studies are limited by the molecular complexity of the phenotype being studied and the population size needed to have adequate statistical power. One way to circumvent this problem, which is critical for the study of rare diseases, is to study the molecular patterns emerging from functional studies of existing disease mutations. Current gene-centric analyses to study mutations in coding regions are limited by their inability to account for the functional modularity of the protein. Previous studies of the functional patterns of known human disease mutations have shown a significant tendency to cluster at protein domain positions, namely position-based domain hotspots of disease mutations. However, the limited number of known disease mutations remains the main factor hindering the advancement of mutation studies at a functional level. In this paper, we address this problem by incorporating mutations known to be disruptive of phenotypes in other species. Focusing on two evolutionarily distant organisms, human and yeast, we describe the first inter-species analysis of mutations of phenotypic relevance at the protein domain level.ResultsThe results of this analysis reveal that phenotypic mutations from yeast cluster at specific positions on protein domains, a characteristic previously revealed to be displayed by human disease mutations. We found over one hundred domain hotspots in yeast with approximately 50% in the exact same domain position as known human disease mutations.ConclusionsWe describe an analysis using protein domains as a framework for transferring functional information by studying domain hotspots in human and yeast and relating phenotypic changes in yeast to diseases in human. This first-of-a-kind study of phenotypically relevant yeast mutations in relation to human disease mutations demonstrates the utility of a multi-species analysis for advancing the understanding of the relationship between genetic mutations and phenotypic changes at the organismal level.

Dataset Information

The transcript-centric mutations in human genomes.

Publications

The transcript-centric mutations in human genomes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets