Remus: A Web Application for Prioritization of Regulatory Regions and Variants in Monogenic Diseases

BackgroundAnalysis of variants in distant regulatory elements could improve the current 25–50% yield of genetic testing for monogenic diseases. However, the vast size of the regulome, great number of variants, and the difficulty in predicting their phenotypic impact make searching for pathogenic variants in the regulatory genome challenging. New tools for the identification of regulatory variants based on their relevance to the phenotype are needed.MethodsWe used tissue-specific regulatory loci mapped by ENCODE and FANTOM, together with miRNA–gene interactions from miRTarBase and miRWalk, to develop Remus, a web application for the identification of tissue-specific regulatory regions. Remus searches for regulatory features linked to the known disease-associated genes and filters them using activity status in the target tissues relevant for the studied disorder. For user convenience, Remus provides a web interface and facilitates in-browser filtering of variant files suitable for sensitive patient data.ResultsTo evaluate our approach, we used a set of 146 regulatory mutations reported causative for 68 distinct monogenic disorders and a manually curated a list of tissues affected by these disorders. In 89.7% of cases, Remus identified the regulator containing the pathogenic mutation. The tissue-specific search limited the number of considered variants by 82.5% as compared to a tissue-agnostic search.ConclusionRemus facilitates the identification of regulatory regions potentially associated with a monogenic disease and can supplement classical analysis of coding variations with the aim of improving the diagnostic yield in whole-genome sequencing experiments.

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Prevalence of hereditary tubulointerstitial kidney diseases in the German Chronic Kidney Disease study

10.1101/2021.09.29.21264100 ◽

2021 ◽

Author(s):

Bernt Popp ◽

Arif B. Ekici ◽

Karl X. Knaup ◽

Karen Schneider ◽

Steffen Uebe ◽

...

Keyword(s):

Chronic Kidney Disease ◽

Kidney Disease ◽

Kidney Diseases ◽

Diagnostic Yield ◽

Genetic Disorder ◽

Clinical Criteria ◽

Pathogenic Variants ◽

Increased Risk ◽

Monogenic Diseases ◽

Disease Study

ABSTRACTExome sequencing (ES) studies in chronic kidney disease (CKD) cohorts could identify pathogenic variants in ∼10% of patients. This implies underdiagnosis of hereditary CKD. Tubulointerstitial kidney diseases, showing no typical clinical/histologic finding but tubulointerstitial fibrosis, are particularly difficult to diagnose.We used a custom designed targeted panel (29 genes) and MUC1-SNaPshot to sequence 271 DNA samples, selected by clinical criteria from 5,217 individuals in the German Chronic Kidney Disease (GCKD) cohort.We identified 33 pathogenic small variants. Of these 27 (81.8%) were in COL4-genes, the largest group being 15 COL4A5-variants with nine unrelated individuals carrying c.1871G>A, p.(Gly624Asp). We found three cysteine variants in UMOD, a novel missense, and a novel splice variant in HNF1B and the homoplastic MTTF variant m.616T>C. Copy-number analysis identified a heterozygous COL4A5-deletion, and a HNF1B-duplication/-deletion, respectively. Overall, pathogenic variants were present in 12.5% (34/271) and variants of unknown significance in 9.6% (26/271) of selected individuals. Bioinformatic predictions paired with gold standard diagnostics for MUC1 (SNaPshot) could not identify the typical cytosine duplication (“c.428dupC”) in any individual, implying that ADTKD-MUC1 is rare.Our study shows that >10% of individuals with certain clinical features carry disease variants in genes associated with tubulointerstitial kidney diseases. COL4-genes constitute the largest fraction, implying they are overlooked using clinical Alport-syndrome criteria. We also identified variants easily missed by some ES pipelines. Finally, our results indicate that the filtering criteria applied enrich for an underlying genetic disorder.SIGNIFICANCE STATEMENTCKD affects >10% of the global population and recent studies imply that a considerable portion can be attributed to monogenic diseases, which are likely underappreciated in the clinical routine. Tubulointerstitial kidney diseases are a particularly difficult group of hereditary kidney diseases to diagnose both clinically and genetically. To investigate the prevalence of these disorders in a large CKD cohort we established a set of clinical criteria and designed a custom panel sequencing pipeline. Based on the diagnostic yield of 12.5%, we recommend an algorithm to clinically select and genetically evaluate patients with increased risk for a hereditary tubulointerstitial kidney disease.

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Identification of distal regulatory regions in the human αIIb gene locus necessary for consistent, high-level megakaryocyte expression

Blood ◽

10.1182/blood-2002-05-1307 ◽

2002 ◽

Vol 100 (10) ◽

pp. 3588-3596 ◽

Cited By ~ 16

Author(s):

Michael A. Thornton ◽

Chunyan Zhang ◽

Maria A. Kowalska ◽

Mortimer Poncz

Keyword(s):

Gene Locus ◽

Tissue Specificity ◽

Mrna Level ◽

Regulatory Elements ◽

Proximal Promoter ◽

Regulatory Regions ◽

Platelet Surface ◽

Tissue Specific ◽

Intergenic Regions ◽

High Level

The αIIb/β3-integrin receptor is present at high levels only in megakaryocytes and platelets. Its presence on platelets is critical for hemostasis. The tissue-specific nature of this receptor's expression is secondary to the restricted expression of αIIb, and studies of the αIIb proximal promoter have served as a model of a megakaryocyte-specific promoter. We have examined the αIIb gene locus for distal regulatory elements. Sequence comparison between the human (h) and murine (m) αIIb loci revealed high levels of conservation at intergenic regions both 5′ and 3′ to the αIIb gene. Additionally, deoxyribonuclease (DNase) I sensitivity mapping defined tissue-specific hypersensitive (HS) sites that coincide, in part, with these conserved regions. Transgenic mice containing various lengths of the hαIIb gene locus, which included or excluded the various conserved/HS regions, demonstrated that the proximal promoter was sufficient for tissue specificity, but that a region 2.5 to 7.1 kb upstream of the hαIIb gene was necessary for consistent expression. Another region 2.2 to 7.4 kb downstream of the gene enhanced expression 1000-fold and led to levels of hαIIb mRNA that were about 30% of the native mαIIb mRNA level. These constructs also resulted in detectable hαIIb/mβ3 on the platelet surface. This work not only confirms the importance of the proximal promoter of the αIIb gene for tissue specificity, but also characterizes the distal organization of the αIIb gene locus and provides an initial localization of 2 important regulatory regions needed for the expression of the αIIb gene at high levels during megakaryopoiesis.

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WebSeq: A Genomic Data Analytics Platform for Monogenic Disease Discovery

10.1101/2021.11.16.460500 ◽

2021 ◽

Author(s):

Milind Agarwal ◽

Kshitiz Ghimire ◽

Joy D. Cogan ◽

Janet Markle ◽

Keyword(s):

Web Application ◽

Genomic Data ◽

Gene Panel ◽

Monogenic Disease ◽

Mendelian Disease ◽

Web Interface ◽

Non Profit ◽

Gene Enrichment ◽

Monogenic Diseases ◽

Family Based

Whole exome sequencing (WES) is commonly used to study monogenic diseases. The application of this sequencing technology has gained in popularity amongst clinicians and researchers as WES pricing has declined. The accumulation of WES data creates a need for a robust, flexible, scalable and easy-to-use analytics platform to allow researchers to gain biological insight from this genomic data. We present WebSeq, a self-contained server and web interface to facilitate intuitive analysis of WES data. WebSeq provides access to sophisticated tools and pipelines through a user-friendly and modern web interface. WebSeq has modules that support i) FASTQ to VCF conversion, ii) VCF to ANNOVAR CSV conversion, iii) family-based analyses for Mendelian disease gene discovery, iv) cohort-wide gene enrichment analyses, (v) an automated IGV browser, and (vi) a 'virtual gene panel' analysis module. WebSeq Pro, our expanded pipeline, also supports SNP genotype analyses such as ancestry inference and kinship testing. WebSeq Lite, our minimal pipeline, supports family-based analyses, cohort-wide gene enrichment analyses, and a virtual gene panel along with the IGV browser module. We anticipate that the rigorous use of our web application will allow researchers to expedite discoveries from human genomic data. WebSeq Lite, WebSeq, and WebSeq Pro are fully containerized using Docker, run on all major operating systems, and are freely available for personal, academic, and non-profit use at http://bitly.ws/g6cn .

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One in seven pathogenic variants can be challenging to detect by NGS: an analysis of 450,000 patients with implications for clinical sensitivity and genetic test implementation

Genetics in Medicine ◽

10.1038/s41436-021-01187-w ◽

2021 ◽

Author(s):

Stephen E. Lincoln ◽

Tina Hambuch ◽

Justin M. Zook ◽

Sara L. Bristow ◽

Kathryn Hatchell ◽

...

Keyword(s):

Diagnostic Yield ◽

Copy Number Variants ◽

Low Complexity ◽

Clinical Genetic ◽

Clinical Sensitivity ◽

Pathogenic Variants ◽

Wide Range ◽

Large Indels ◽

Next Generation Sequencing Ngs ◽

The Impact

Abstract Purpose To evaluate the impact of technically challenging variants on the implementation, validation, and diagnostic yield of commonly used clinical genetic tests. Such variants include large indels, small copy-number variants (CNVs), complex alterations, and variants in low-complexity or segmentally duplicated regions. Methods An interlaboratory pilot study used synthetic specimens to assess detection of challenging variant types by various next-generation sequencing (NGS)–based workflows. One well-performing workflow was further validated and used in clinician-ordered testing of more than 450,000 patients. Results In the interlaboratory study, only 2 of 13 challenging variants were detected by all 10 workflows, and just 3 workflows detected all 13. Limitations were also observed among 11 less-challenging indels. In clinical testing, 21.6% of patients carried one or more pathogenic variants, of which 13.8% (17,561) were classified as technically challenging. These variants were of diverse types, affecting 556 of 1,217 genes across hereditary cancer, cardiovascular, neurological, pediatric, reproductive carrier screening, and other indicated tests. Conclusion The analytic and clinical sensitivity of NGS workflows can vary considerably, particularly for prevalent, technically challenging variants. This can have important implications for the design and validation of tests (by laboratories) and the selection of tests (by clinicians) for a wide range of clinical indications.

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Exploring functionally annotated transcriptional consensus regulatory elements with CONREL

Database ◽

10.1093/database/baaa071 ◽

2020 ◽

Vol 2020 ◽

Author(s):

Davide Dalfovo ◽

Samuel Valentini ◽

Alessandro Romanel

Keyword(s):

Cell Lines ◽

Web Application ◽

Regulatory Networks ◽

Regulatory Elements ◽

Levels Of Abstraction ◽

Binding Motifs ◽

Extensive Collection ◽

Transcription Factor Binding Motifs ◽

Gene Regulatory ◽

Genomic Regions

Abstract Understanding the interaction between human genome regulatory elements and transcription factors is fundamental to elucidate the structure of gene regulatory networks. Here we present CONREL, a web application that allows for the exploration of functionally annotated transcriptional ‘consensus’ regulatory elements at different levels of abstraction. CONREL provides an extensive collection of consensus promoters, enhancers and active enhancers for 198 cell-lines across 38 tissue types, which are also combined to provide global consensuses. In addition, 1000 Genomes Project genotype data and the ‘total binding affinity’ of thousands of transcription factor binding motifs at genomic regulatory elements is fully combined and exploited to characterize and annotate functional properties of our collection. Comparison with other available resources highlights the strengths and advantages of CONREL. CONREL can be used to explore genomic loci, specific genes or genomic regions of interest across different cell lines and tissue types. The resource is freely available at https://bcglab.cibio.unitn.it/conrel.

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Tissue‐specific regulatory elements in mammalian promoters

Molecular Systems Biology ◽

10.1038/msb4100114 ◽

2007 ◽

Vol 3 (1) ◽

pp. 73 ◽

Cited By ~ 34

Author(s):

Andrew D Smith ◽

Pavel Sumazin ◽

Michael Q Zhang

Keyword(s):

Regulatory Elements ◽

Tissue Specific

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A Common Motif within the Negative Regulatory Regions of Multiple Factors Inhibits Their Transcriptional Synergy

Molecular and Cellular Biology ◽

10.1128/mcb.20.16.6040-6050.2000 ◽

2000 ◽

Vol 20 (16) ◽

pp. 6040-6050 ◽

Cited By ~ 154

Author(s):

Jorge A. Iñiguez-Lluhí ◽

David Pearce

Keyword(s):

Binding Sites ◽

Regulatory Elements ◽

General Mechanism ◽

Proper Function ◽

Protein Motif ◽

Regulatory Regions ◽

Response Elements ◽

Common Motif ◽

Single Response ◽

Dna Regulatory Elements

ABSTRACT DNA regulatory elements frequently harbor multiple recognition sites for several transcriptional activators. The response mounted from such compound response elements is often more pronounced than the simple sum of effects observed at single binding sites. The determinants of such transcriptional synergy and its control, however, are poorly understood. Through a genetic approach, we have uncovered a novel protein motif that limits the transcriptional synergy of multiple DNA-binding regulators. Disruption of these conserved synergy control motifs (SC motifs) selectively increases activity at compound, but not single, response elements. Although isolated SC motifs do not regulate transcription when tethered to DNA, their transfer to an activator lacking them is sufficient to impose limits on synergy. Mechanistic analysis of the two SC motifs found in the glucocorticoid receptor N-terminal region reveals that they function irrespective of the arrangement of the receptor binding sites or their distance from the transcription start site. Proper function, however, requires the receptor's ligand-binding domain and an engaged dimer interface. Notably, the motifs are not functional in yeast and do not alter the effect of p160 coactivators, suggesting that they require other nonconserved components to operate. Many activators across multiple classes harbor seemingly unrelated negative regulatory regions. The presence of SC motifs within them, however, suggests a common function and identifies SC motifs as critical elements of a general mechanism to modulate higher-order interactions among transcriptional regulators.

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