Edwin Cuppen

Bio: Edwin Cuppen is an academic researcher from Utrecht University. The author has contributed to research in topics: Gene & Cancer. The author has an hindex of 83, co-authored 330 publications receiving 28862 citations. Previous affiliations of Edwin Cuppen include Radboud University Nijmegen & American Academy of Arts and Sciences.

Sambamba: fast processing of NGS alignment formats

Abstract: Sambamba is a high-performance robust tool and library for working with SAM, BAM and CRAM sequence alignment files; the most common file formats for aligned next generation sequencing data. Sambamba is a faster alternative to samtools that exploits multi-core processing and dramatically reduces processing time. Sambamba is being adopted at sequencing centers, not only because of its speed, but also because of additional functionality, including coverage analysis and powerful filtering capability. AVAILABILITY AND IMPLEMENTATION: Sambamba is free and open source software, available under a GPLv2 license. Sambamba can be downloaded and installed from http://www.open-bio.org/wiki/Sambamba. Sambamba v0.5.0 was released with doi:10.5281/zenodo.13200. CONTACT: j.c.p.prins@umcutrecht.nl.

SARS-CoV-2 productively infects human gut enterocytes.

Abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can cause coronavirus disease 2019 (COVID-19), an influenza-like disease that is primarily thought to infect the lungs with transmission through the respiratory route. However, clinical evidence suggests that the intestine may present another viral target organ. Indeed, the SARS-CoV-2 receptor angiotensin-converting enzyme 2 (ACE2) is highly expressed on differentiated enterocytes. In human small intestinal organoids (hSIOs), enterocytes were readily infected by SARS-CoV and SARS-CoV-2, as demonstrated by confocal and electron microscopy. Enterocytes produced infectious viral particles, whereas messenger RNA expression analysis of hSIOs revealed induction of a generic viral response program. Therefore, the intestinal epithelium supports SARS-CoV-2 replication, and hSIOs serve as an experimental model for coronavirus infection and biology.

A framework for variation discovery and genotyping using next-generation DNA sequencing data

Abstract: Recent advances in sequencing technology make it possible to comprehensively catalogue genetic variation in population samples, creating a foundation for understanding human disease, ancestry and evolution. The amounts of raw data produced are prodigious and many computational steps are required to translate this output into high-quality variant calls. We present a unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs. Our process includes (1) initial read mapping; (2) local realignment around indels; (3) base quality score recalibration; (4) SNP discovery and genotyping to find all potential variants; and (5) machine learning to separate true segregating variation from machine artifacts common to next-generation sequencing technologies. We discuss the application of these tools, instantiated in the Genome Analysis Toolkit (GATK), to deep whole-genome, whole-exome capture, and multi-sample low-pass (~4×) 1000 Genomes Project datasets.

DNA methylation patterns and epigenetic memory

Abstract: The character of a cell is defined by its constituent proteins, which are the result of specific patterns of gene expression. Crucial determinants of gene expression patterns are DNA-binding transcription factors that choose genes for transcriptional activation or repression by recognizing the sequence of DNA bases in their promoter regions. Interaction of these factors with their cognate sequences triggers a chain of events, often involving changes in the structure of chromatin, that leads to the assembly of an active transcription complex (e.g., Cosma et al. 1999). But the types of transcription factors present in a cell are not alone sufficient to define its spectrum of gene activity, as the transcriptional potential of a genome can become restricted in a stable manner during development. The constraints imposed by developmental history probably account for the very low efficiency of cloning animals from the nuclei of differentiated cells (Rideout et al. 2001; Wakayama and Yanagimachi 2001). A “transcription factors only” model would predict that the gene expression pattern of a differentiated nucleus would be completely reversible upon exposure to a new spectrum of factors. Although many aspects of expression can be reprogrammed in this way (Gurdon 1999), some marks of differentiation are evidently so stable that immersion in an alien cytoplasm cannot erase the memory. The genomic sequence of a differentiated cell is thought to be identical in most cases to that of the zygote from which it is descended (mammalian B and T cells being an obvious exception). This means that the marks of developmental history are unlikely to be caused by widespread somatic mutation. Processes less irrevocable than mutation fall under the umbrella term “epigenetic” mechanisms. A current definition of epigenetics is: “The study of mitotically and/or meiotically heritable changes in gene function that cannot be explained by changes in DNA sequence” (Russo et al. 1996). There are two epigenetic systems that affect animal development and fulfill the criterion of heritability: DNA methylation and the Polycomb-trithorax group (Pc-G/trx) protein complexes. (Histone modification has some attributes of an epigenetic process, but the issue of heritability has yet to be resolved.) This review concerns DNA methylation, focusing on the generation, inheritance, and biological significance of genomic methylation patterns in the development of mammals. Data will be discussed favoring the notion that DNA methylation may only affect genes that are already silenced by other mechanisms in the embryo. Embryonic transcription, on the other hand, may cause the exclusion of the DNA methylation machinery. The heritability of methylation states and the secondary nature of the decision to invite or exclude methylation support the idea that DNA methylation is adapted for a specific cellular memory function in development. Indeed, the possibility will be discussed that DNA methylation and Pc-G/trx may represent alternative systems of epigenetic memory that have been interchanged over evolutionary time. Animal DNA methylation has been the subject of several recent reviews (Bird and Wolffe 1999; Bestor 2000; Hsieh 2000; Costello and Plass 2001; Jones and Takai 2001). For recent reviews of plant and fungal DNA methylation, see Finnegan et al. (2000), Martienssen and Colot (2001), and Matzke et al. (2001).

MicroRNA signatures in human cancers

Abstract: MicroRNA (miRNA ) alterations are involved in the initiation and progression of human cancer. The causes of the widespread differential expression of miRNA genes in malignant compared with normal cells can be explained by the location of these genes in cancer-associated genomic regions, by epigenetic mechanisms and by alterations in the miRNA processing machinery. MiRNA-expression profiling of human tumours has identified signatures associated with diagnosis, staging, progression, prognosis and response to treatment. In addition, profiling has been exploited to identify miRNA genes that might represent downstream targets of activated oncogenic pathways, or that target protein- coding genes involved in cancer.

MicroRNA signatures in human cancers

Abstract: MicroRNA (miRNA) alterations are involved in the initiation and progression of human cancer. The causes of the widespread differential expression of miRNA genes in malignant compared with normal cells can be explained by the location of these genes in cancer-associated genomic regions, by epigenetic mechanisms and by alterations in the miRNA processing machinery. MiRNA-expression profiling of human tumours has identified signatures associated with diagnosis, staging, progression, prognosis and response to treatment. In addition, profiling has been exploited to identify miRNA genes that might represent downstream targets of activated oncogenic pathways, or that target protein- coding genes involved in cancer.