Dataset Information

Profiling of conserved non-coding elements upstream of SHOX and functional characterisation of the SHOX cis-regulatory landscape.

ABSTRACT: Genetic defects such as copy number variations (CNVs) in non-coding regions containing conserved non-coding elements (CNEs) outside the transcription unit of their target gene, can underlie genetic disease. An example of this is the short stature homeobox (SHOX) gene, regulated by seven CNEs located downstream and upstream of SHOX, with proven enhancer capacity in chicken limbs. CNVs of the downstream CNEs have been reported in many idiopathic short stature (ISS) cases, however, only recently have a few CNVs of the upstream enhancers been identified. Here, we set out to provide insight into: (i) the cis-regulatory role of these upstream CNEs in human cells, (ii) the prevalence of upstream CNVs in ISS, and (iii) the chromatin architecture of the SHOX cis-regulatory landscape in chicken and human cells. Firstly, luciferase assays in human U2OS cells, and 4C-seq both in chicken limb buds and human U2OS cells, demonstrated cis-regulatory enhancer capacities of the upstream CNEs. Secondly, CNVs of these upstream CNEs were found in three of 501 ISS patients. Finally, our 4C-seq interaction map of the SHOX region reveals a cis-regulatory domain spanning more than 1 Mb and harbouring putative new cis-regulatory elements.

SUBMITTER: Verdin H

PROVIDER: S-EPMC4668379 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Profiling of conserved non-coding elements upstream of SHOX and functional characterisation of the SHOX cis-regulatory landscape.

Verdin Hannah H Fernández-Miñán Ana A Benito-Sanz Sara S Janssens Sandra S Callewaert Bert B De Waele Kathleen K De Schepper Jean J François Inge I Menten Björn B Heath Karen E KE Gómez-Skarmeta José Luis JL De Baere Elfride E

Scientific reports 20151203

Genetic defects such as copy number variations (CNVs) in non-coding regions containing conserved non-coding elements (CNEs) outside the transcription unit of their target gene, can underlie genetic disease. An example of this is the short stature homeobox (SHOX) gene, regulated by seven CNEs located downstream and upstream of SHOX, with proven enhancer capacity in chicken limbs. CNVs of the downstream CNEs have been reported in many idiopathic short stature (ISS) cases, however, only recently ha ...[more]

PMID: 26631348

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Project description:PurposePrior studies have demonstrated the significance of specific cis-regulatory variants in retinal disease; however, determining the functional impact of regulatory variants remains a major challenge. In this study, we utilized a machine learning approach, trained on epigenomic data from the adult human retina, to systematically quantify the predicted impact of cis-regulatory variants.MethodsWe used human retinal DNA accessibility data (ATAC-seq) to determine a set of 18.9k high-confidence, putative cis-regulatory elements. Eighty percent of these elements were used to train a machine learning model utilizing a gapped k-mer support vector machine-based approach. In silico saturation mutagenesis and variant scoring was applied to predict the functional impact of all potential single nucleotide variants within cis-regulatory elements. Impact scores were tested in a 20% hold-out dataset and compared to allele population frequency, phylogenetic conservation, transcription factor (TF) binding motifs, and existing massively parallel reporter assay data.ResultsWe generated a model that distinguishes between human retinal regulatory elements and negative test sequences with 95% accuracy. Among a hold-out test set of 3.7k human retinal CREs, all possible single nucleotide variants were scored. Variants with negative impact scores correlated with higher phylogenetic conservation of the reference allele, disruption of predicted TF binding motifs, and massively parallel reporter expression.ConclusionsWe demonstrated the utility of human retinal epigenomic data to train a machine learning model for the purpose of predicting the impact of non-coding regulatory sequence variants. Our model accurately scored sequences and predicted putative transcription factor binding motifs. This approach has the potential to expedite the characterization of pathogenic non-coding sequence variants in the context of unexplained retinal disease.Translational relevanceThis workflow and resulting dataset serve as a promising genomic tool to facilitate the clinical prioritization of functionally disruptive non-coding mutations in the retina.

Dataset Information

Profiling of conserved non-coding elements upstream of SHOX and functional characterisation of the SHOX cis-regulatory landscape.

Publications

Profiling of conserved non-coding elements upstream of SHOX and functional characterisation of the SHOX cis-regulatory landscape.

Similar Datasets

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