Auto Tag: Leiden Genome Technology Center

September 22, 2019  |  

Next generation sequencing technology: Advances and applications.

Impressive progress has been made in the field of Next Generation Sequencing (NGS). Through advancements in the fields of molecular biology and technical engineering, parallelization of the sequencing reaction has profoundly increased the total number of produced sequence reads per run. Current sequencing platforms allow for a previously unprecedented view into complex mixtures of RNA and DNA samples. NGS is currently evolving into a molecular microscope finding its way into virtually every fields of biomedical research. In this chapter we review the technical background of the different commercially available NGS platforms with respect to template generation and the sequencing reaction and take a small step towards what the upcoming NGS technologies will bring. We close with an overview of different implementations of NGS into biomedical research. This article is part of a Special Issue entitled: From Genome to Function. Copyright © 2014 Elsevier B.V. All rights reserved.

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September 22, 2019  |  

Identification of differentially expressed splice variants by the proteogenomic pipeline Splicify.

Proteogenomics, i.e. comprehensive integration of genomics and proteomics data, is a powerful approach identifying novel protein biomarkers. This is especially the case for proteins that differ structurally between disease and control conditions. As tumor development is associated with aberrant splicing, we focus on this rich source of cancer specific biomarkers. To this end, we developed a proteogenomic pipeline, Splicify, which is able to detect differentially expressed protein isoforms. Splicify is based on integrating RNA massive parallel sequencing data and tandem mass spectrometry proteomics data to identify protein isoforms resulting from differential splicing between two conditions. Proof of concept was obtained by applying Splicify to RNA sequencing and mass spectrometry data obtained from colorectal cancer cell line SW480, before and after siRNA-mediated down-modulation of the splicing factors SF3B1 and SRSF1. These analyses revealed 2172 and 149 differentially expressed isoforms, respectively, with peptide confirmation upon knock-down of SF3B1 and SRSF1 compared to their controls. Splice variants identified included RAC1, OSBPL3, MKI67 and SYK. One additional sample was analyzed by PacBio Iso-Seq full-length transcript sequencing after SF3B1 down-modulation. This analysis verified the alternative splicing identified by Splicify and in addition identified novel splicing events that were not represented in the human reference genome annotation. Therefore, Splicify offers a validated proteogenomic data analysis pipeline for identification of disease specific protein biomarkers resulting from mRNA alternative splicing. Splicify is publicly available on GitHub (https://github.com/NKI-TGO/SPLICIFY) and suitable to address basic research questions using pre-clinical model systems as well as translational research questions using patient-derived samples, e.g. allowing to identify clinically relevant biomarkers. Copyright © 2017, The American Society for Biochemistry and Molecular Biology.

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September 22, 2019  |  

Human and rhesus macaque KIR haplotypes defined by their transcriptomes.

The killer-cell Ig-like receptors (KIRs) play a central role in the immune recognition in infection, pregnancy, and transplantation through their interactions with MHC class I molecules. KIR genes display abundant copy number variation as well as high levels of polymorphism. As a result, it is challenging to characterize this structurally dynamic region. KIR haplotypes have been analyzed in different species using conventional characterization methods, such as Sanger sequencing and Roche/454 pyrosequencing. However, these methods are time-consuming and often failed to define complete haplotypes, or do not reach allele-level resolution. In addition, most analyses were performed on genomic DNA, and thus were lacking substantial information about transcription and its corresponding modifications. In this paper, we present a single-molecule real-time sequencing approach, using Pacific Biosciences Sequel platform to characterize the KIR transcriptomes in human and rhesus macaque (Macaca mulatta) families. This high-resolution approach allowed the identification of novel Mamu-KIR alleles, the extension of reported allele sequences, and the determination of human and macaque KIR haplotypes. In addition, multiple recombinant KIR genes were discovered, all located on contracted haplotypes, which were likely the result of chromosomal rearrangements. The relatively high number of contracted haplotypes discovered might be indicative of selection on small KIR repertoires and/or novel fusion gene products. This next-generation method provides an improved high-resolution characterization of the KIR cluster in humans and macaques, which eventually may aid in a better understanding and interpretation of KIR allele-associated diseases, as well as the immune response in transplantation and reproduction. Copyright © 2018 by The American Association of Immunologists, Inc.

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