Annotation und Interpretation von Varianten und Polymorphismen im humanen Genom

Das Gesamtvolumen genomischer Sequenzierungsdaten nimmt, dank der Entwicklung der DNA-Hochdurchsatz-Sequenziertechniken, in den letzten Jahren in unglaublichem Tempo zu. Dies erweitert unser Wissen des humanen Genoms über dessen Aufbau, die Struktur und die räumliche Organisation. Die Erkenntnis um den komplexen Aufbau wird in naher Zukunft in die Interpretation von Variationen auch im klinischen Kontext einfließen müssen, birgt sie doch zahlreiche potentielle Möglichkeiten in der Diagnostik. Whole Genome Sequencing hat schon jetzt den Sprung aus den Forschungslaboren in die angewandte Diagnostik von Krankenhäusern geschafft und erlaubt damit die Einführung der Präzisionsmedizin für alle Patienten. Für eine optimale klinische Interpretation genomischer Varianten ist es wichtig, konsistente und passende Referenzen zu verwenden. Hierzu zählt neben der Auswahl des Referenzgenoms auch die verwendete Datenbank zur Annotierung von funktionalen Einheiten auf der DNA. Diese Arbeit geht auf zwei wichtige Schritte auf dem Weg zum Einsatz des WGS im klinischen Alltag ein. Der erste Schritt beinhaltet, möglichst schnell die gefundenen Varianten zu genomischen Eigenschaften und Featu- res (in Relation zu einer Referenz) zuzuordnen. Dies ist aufgrund der großen Datenmengen ein zunehmendes Problem geworden. Mit Jannovar wird hier eine Softwarebibliothek vorgestellt, welche hervorragend an diese Ansprüche angepasst ist. Die Bibliothek ist schnell, flexibel und kann leicht in Annotationspipelines und eigene Programme integriert werden. Die so annotierten und charakterisierten Veränderungen des Genotyps bilden eine Basis für die weitere Interpretation und Beurteilung durch andere Programme. Die Repräsentation der Genomreferenz entwickelt sich hin zu einem Graphengenom, um die populationsspezifische Variabilität zumindest ansatzweise abzubilden. Diese kann einen enormen Einfluss auf die Interpretation von Varianten haben. Im zweiten Schritt geht es darum, diese populationsspezifische Komplexität zu erläutern. Mit ASDPex wird ein heuristischer Algorithmus vorgestellt, welcher für WGS-Daten eines Individuums das Auftreten von alternativen Haplotypsequenzen vorhersagt. Dafür verwendet es die Verteilung der Allelfrequenzen der individuellen Varianten und gleicht sie mit einer Art Fingerabdruck aus haplotypspezifischen Varianten ab. Das Wissen um die alternativen Sequenzen kann die Verlässlichkeit der klinischen Interpretation weiter verbessern. Zukünftig wird es darum gehen, noch mehr Daten in die Varianteninterpretation zu integrieren, um noch mehr falsch positive/falsch negative Assoziationen zu verhindern und irrelevante Varianten herauszufiltern

Combining callers improves the detection of copy number variants from whole-genome sequencing

Copy Number Variants (CNVs) are deletions, duplications or insertions larger than 50 base pairs. They account for a large percentage of the normal genome variation and play major roles in human pathology. While array-based approaches have long been used to detect them in clinical practice, whole-genome sequencing (WGS) bears the promise to allow concomitant exploration of CNVs and smaller variants. However, accurately calling CNVs from WGS remains a difficult computational task, for which a consensus is still lacking. In this paper, we explore practical calling options to reach the best compromise between sensitivity and sensibility. We show that callers based on different signal (paired-end reads, split reads, coverage depth) yield complementary results. We suggest approaches combining four selected callers (Manta, Delly, ERDS, CNVnator) and a regenotyping tool (SV2), and show that this is applicable in everyday practice in terms of computation time and further interpretation. We demonstrate the superiority of these approaches over array-based Comparative Genomic Hybridization (aCGH), specifically regarding the lack of resolution in breakpoint definition and the detection of potentially relevant CNVs. Finally, we confirm our results on the NA12878 benchmark genome, as well as one clinically validated sample. In conclusion, we suggest that WGS constitutes a timely and economically valid alternative to the combination of aCGH and whole-exome sequencing

An integrative systems approach identifies novel candidates in Marfan syndrome-related pathophysiology.

Marfan syndrome (MFS) is an autosomal dominant genetic disorder caused by mutations in the FBN1 gene. Although many peripheral tissues are affected, aortic complications, such as dilation, dissection and rupture, are the leading causes of MFS-related mortality. Aberrant TGF-beta signalling plays a major role in the pathophysiology of MFS. However, the contributing mechanisms are still poorly understood. Here, we aimed at identifying novel aorta-specific pathways involved in the pathophysiology of MFS. For this purpose, we employed the Fbn1 under-expressing mgR/mgR mouse model of MFS. We performed RNA-sequencing of aortic tissues of 9-week-old mgR/mgR mice compared with wild-type (WT) mice. With a false discovery rat

Influence of Interferon-Alpha Combined with Chemo (Radio) Therapy on Immunological Parameters in Pancreatic Adenocarcinoma

Prognosis of patients with carcinoma of the exocrine pancreas is particularly poor. A combination of chemotherapy with immunotherapy could be an option for treatment of pancreatic cancer. The aim of this study was to perform an immunomonitoring of 17 patients with pancreatic cancer from the CapRI-2 study, and tumor-bearing mice treated with combination of chemo (radio) therapies with interferon-2. Low doses of interferon-2 led to a decrease in total leukocyte and an increase in monocyte counts. Furthermore, we observed a positive effect of interferon-2 therapy on the dendritic cells and NK (natural killer) cell activation immediately after the first injection. In addition, we recorded an increased amount of interferon- and IL-10 in the serum following the interferon-2 therapy. These data clearly demonstrate that pancreatic carcinoma patients also show an immunomodulatory response to interferon-2 therapy. Analysis of immunosuppressive cells in the Panc02 orthotopic mouse model of pancreatic cancer revealed an accumulation of the myeloid-derived suppressor cells in spleens and tumors of the mice treated with interferon-2 and 5-fluorouracil. The direct effect of the drugs on myeloid-derived suppressor cells was also registered in vitro. These data expose the importance of immunosuppressive mechanisms induced by combined chemo-immunotherapy

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition

Composite transcriptome assembly of RNA-seq data in a sheep model for delayed bone healing

<p>Abstract</p> <p>Background</p> <p>The sheep is an important model organism for many types of medically relevant research, but molecular genetic experiments in the sheep have been limited by the lack of knowledge about ovine gene sequences.</p> <p>Results</p> <p>Prior to our study, mRNA sequences for only 1,556 partial or complete ovine genes were publicly available. Therefore, we developed a composite <it>de novo </it>transcriptome assembly method for next-generation sequence data to combine known ovine mRNA and EST sequences, mRNA sequences from mouse and cow, and sequences assembled <it>de novo </it>from short read RNA-Seq data into a composite reference transcriptome, and identified transcripts from over 12 thousand previously undescribed ovine genes. Gene expression analysis based on these data revealed substantially different expression profiles in standard versus delayed bone healing in an ovine tibial osteotomy model. Hundreds of transcripts were differentially expressed between standard and delayed healing and between the time points of the standard and delayed healing groups. We used the sheep sequences to design quantitative RT-PCR assays with which we validated the differential expression of 26 genes that had been identified by RNA-seq analysis. A number of clusters of characteristic expression profiles could be identified, some of which showed striking differences between the standard and delayed healing groups. Gene Ontology (GO) analysis showed that the differentially expressed genes were enriched in terms including <it>extracellular matrix</it>, <it>cartilage development</it>, <it>contractile fiber</it>, and <it>chemokine activity</it>.</p> <p>Conclusions</p> <p>Our results provide a first atlas of gene expression profiles and differentially expressed genes in standard and delayed bone healing in a large-animal model and provide a number of clues as to the shifts in gene expression that underlie delayed bone healing. In the course of our study, we identified transcripts of 13,987 ovine genes, including 12,431 genes for which no sequence information was previously available. This information will provide a basis for future molecular research involving the sheep as a model organism.</p

MicroRNAs Differentially Expressed in Postnatal Aortic Development Downregulate Elastin via 3′ UTR and Coding-Sequence Binding Sites

Elastin production is characteristically turned off during the maturation of elastin-rich organs such as the aorta. MicroRNAs (miRNAs) are small regulatory RNAs that down-regulate target mRNAs by binding to miRNA regulatory elements (MREs) typically located in the 3′ UTR. Here we show a striking up-regulation of miR-29 and miR-15 family miRNAs during murine aortic development with commensurate down-regulation of targets including elastin and other extracellular matrix (ECM) genes. There were a total of 14 MREs for miR-29 in the coding sequences (CDS) and 3′ UTR of elastin, which was highly significant, and up to 22 miR-29 MREs were found in the CDS of multiple ECM genes including several collagens. This overrepresentation was conserved throughout mammalian evolution. Luciferase reporter assays showed synergistic effects of miR-29 and miR-15 family miRNAs on 3′ UTR and coding-sequence elastin constructs. Our results demonstrate that multiple miR-29 and miR-15 family MREs are characteristic for some ECM genes and suggest that miR-29 and miR-15 family miRNAs are involved in the down-regulation of elastin in the adult aorta

Alternate-locus aware variant calling in whole genome sequencing

BACKGROUND: The last two human genome assemblies have extended the previous linear golden-path paradigm of the human genome to a graph-like model to better represent regions with a high degree of structural variability. The new model offers opportunities to improve the technical validity of variant calling in whole-genome sequencing (WGS). METHODS: We developed an algorithm that analyzes the patterns of variant calls in the 178 structurally variable regions of the GRCh38 genome assembly, and infers whether a given sample is most likely to contain sequences from the primary assembly, an alternate locus, or their heterozygous combination at each of these 178 regions. We investigate 121 in-house WGS datasets that have been aligned to the GRCh37 and GRCh38 assemblies. RESULTS: We show that stretches of sequences that are largely but not entirely identical between the primary assembly and an alternate locus can result in multiple variant calls against regions of the primary assembly. In WGS analysis, this results in characteristic and recognizable patterns of variant calls at positions that we term alignable scaffold-discrepant positions (ASDPs). In 121 in-house genomes, on average 51.8±3.8 of the 178 regions were found to correspond best to an alternate locus rather than the primary assembly sequence, and filtering these genomes with our algorithm led to the identification of 7863 variant calls per genome that colocalized with ASDPs. Additionally, we found that 437 of 791 genome-wide association study hits located within one of the regions corresponded to ASDPs. CONCLUSIONS: Our algorithm uses the information contained in the 178 structurally variable regions of the GRCh38 genome assembly to avoid spurious variant calls in cases where samples contain an alternate locus rather than the corresponding segment of the primary assembly. These results suggest the great potential of fully incorporating the resources of graph-like genome assemblies into variant calling, but also underscore the importance of developing computational resources that will allow a full reconstruction of the genotype in personal genomes. Our algorithm is freely available at https://github.com/charite/asdpex. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13073-016-0383-z) contains supplementary material, which is available to authorized users

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file 32: Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.Peer reviewedPublisher PD