Novel Transcriptional Activity and Extensive Allelic Imbalance in the Human MHC Region
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA428235 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR6435180_1.fastq.gz | Fastqsanger.gz | |||
| SRR6435180_2.fastq.gz | Fastqsanger.gz | |||
| SRR6435181_1.fastq.gz | Fastqsanger.gz | |||
| SRR6435181_2.fastq.gz | Fastqsanger.gz | |||
| SRR6435182_1.fastq.gz | Fastqsanger.gz |
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Project description:The MHC region encodes HLA genes and is the most complex region in the human genome. The extensive polymorphic nature of the HLA hinders accurate localization and functional assessment of disease risk loci within this region. Using targeted capture sequencing and constructing individualized genomes for transcriptome alignment, we identified 908 novel transcripts within the human MHC region. These include 593 novel isoforms of known genes, 137 antisense strand RNAs, 119 novel long intergenic noncoding RNAs, and 5 transcripts of 3 novel putative protein-coding human endogenous retrovirus genes. We revealed allele-dependent expression imbalance involving 88% of all heterozygous transcribed single nucleotide polymorphisms throughout the MHC transcriptome. Among these variants, we show that the genetic variant associated with Behc ̧et’s disease in the HLA-B/MICA region, which tags HLA-B*51, is within novel long intergenic noncoding RNA transcripts that are exclusively expressed from the haplotype with the protective but not the disease risk allele. Further, we showed that the transcriptome within the MHC region can be defined by 14 distinct coexpression clusters, with evidence of coregulation by unique transcription factors in at least 9 of these clusters. Our data suggest a very complex regulatory map of the human MHC, and can help uncover functional consequences of disease risk loci in this region.
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Project description:The MHC region encodes HLA genes and is the most complex region in the human genome. The extensively polymorphic nature of the HLA hinders accurate localization and functional assessment of disease risk loci within this region. Using targeted capture sequencing and constructing individualized genomes for transcriptome alignment, we identified 908 novel transcripts within the human MHC region. These include 593 novel isoforms of known genes, 137 antisense strand RNAs, 119 novel long intergenic noncoding RNAs, and 5 transcripts of 3 novel putative protein-coding human endogenous retrovirus genes. We revealed allele-dependent expression imbalance involving 88% of all heterozygous transcribed single nucleotide polymorphisms throughout the MHC transcriptome. Among these variants, the genetic variant associated with Behçet's disease in the HLA-B/MICA region, which tags HLA-B*51, is within novel long intergenic noncoding RNA transcripts that are exclusively expressed from the haplotype with the protective but not the disease risk allele. Further, the transcriptome within the MHC region can be defined by 14 distinct coexpression clusters, with evidence of coregulation by unique transcription factors in at least 9 of these clusters. Our data suggest a very complex regulatory map of the human MHC, and can help uncover functional consequences of disease risk loci in this region.
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Project description:The diploid fungal pathogen Candida albicans is a highly heterozygous organism, with numerous non-synonymous substitutions often seen within two alleles. RNA-sequencing of the wild-type strain SC5314 has revealed 233 genes with significant levels of allelic expression imbalance. Overall percentage protein identity comparisons were significantly lower in these differentially expressed alleles. This suggests that two different, perhaps functionally divergent, proteins are being expressed at significantly different quantities by the two alleles of a single gene. Previously, gene expression levels have been correlated with structural factors such as GC content, ORF length and codon usage. Here, these factors were first correlated with overall gene expression data to decipher the relationship they have with gene expression in Candida albicans. These relationships were then used to assess the contribution of these factors to allelic expression imbalance. GC content and codon usage did not differ significantly in differentially expressed alleles whereas ORF length was found to be significantly lower in the allele with lowest expression. This surprising result goes against the overall trend observed between length and gene expression. Differences in GC content and ORF length between alleles correlated strongly with percentage protein identity, suggesting an indirect link between these factors and allelic expression imbalance.
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