Christian Iseli

Exome sequencing identifies recurrent somatic MAP2K1 and MAP2K2 mutations in melanoma

We performed exome sequencing to detect somatic mutations in protein-coding regions in seven melanoma cell lines and donor-matched germline cells. All melanoma samples had high numbers of somatic mutations, which showed the hallmark of UV-induced DNA repair. Such a hallmark was absent in tumor sample–specific mutations in two metastases derived from the same individual. Two melanomas with non-canonical BRAF mutations harbored gain-of-function MAP2K1 and MAP2K2 (MEK1 and MEK2, respectively) mutations, resulting in constitutive ERK phosphorylation and higher resistance to MEK inhibitors. Screening a larger cohort of individuals with melanoma revealed the presence of recurring somatic MAP2K1 and MAP2K2 mutations, which occurred at an overall frequency of 8%. Furthermore, missense and nonsense somatic mutations were frequently found in three candidate melanoma genes, FAT4, LRP1B and DSC1.

Comprehensive sampling of gene expression in human cell lines with massively parallel signature sequencing

Whereas information is rapidly accumulating about the structure and position of genes encoded in the human genome, less is known about the complexity and relative abundance of their expression in individual human cells and tissues. Here, we describe the characteristics of the transcriptomes of two cultured cell lines, HB4a (normal breast epithelium) and HCT-116 (colon adenocarcinoma), using massively parallel signature sequencing (MPSS). We generated in excess of 107 short signature sequences per cell line, thus providing a comprehensive snapshot of gene expression, within the technical limitations of the method. The number of genes expressed at one copy per cell or more in either of the lines was estimated to be between 10,000 and 15,000. The vast majority of the transcripts found in these cells can be mapped to known genes and their polyadenylation variants. Among the genes that could be identified from their signature sequences, ≈8,500 were expressed by both cell lines, whereas 6,000 showed cellular specificity. Taking into account sequence tags that map uniquely to the genome but not to known transcripts, overall the data are consistent with an upper limit of 17,000 for the total number of genes expressed at more than one copy per cell in one or both of the two cell lines examined.

A C++ compiler for FPGA custom execution units synthesis

If reconfigurable processors are to become widely used, we will need tools to help conventional programmer use them. In particular, a single high-level language should be used to program the whole application; both the part which will become the hardware configuration and the part which remains software. Spyder is a reconfigurable processor with configurable execution units. The C++ language has been chosen as the source language to program this processor. In this paper we present a compiler capable of synthesizing the hardware configuration of FPGA execution units from C++ source code. The same source code can be compiled by a standard C++ compiler for simulation purposes. First estimates show that this approach leads to very short synthesize time as compared to VHDL synthesizer for a similar quality of the generated hardware.

Establishment of the epithelial-specific transcriptome of normal and malignant human breast cells based on MPSS and array expression data

IntroductionDiverse microarray and sequencing technologies have been widely used to characterise the molecular changes in malignant epithelial cells in breast cancers. Such gene expression studies to identify markers and targets in tumour cells are, however, compromised by the cellular heterogeneity of solid breast tumours and by the lack of appropriate counterparts representing normal breast epithelial cells.MethodsMalignant neoplastic epithelial cells from primary breast cancers and luminal and myoepithelial cells isolated from normal human breast tissue were isolated by immunomagnetic separation methods. Pools of RNA from highly enriched preparations of these cell types were subjected to expression profiling using massively parallel signature sequencing (MPSS) and four different genome wide microarray platforms. Functional related transcripts of the differential tumour epithelial transcriptome were used for gene set enrichment analysis to identify enrichment of luminal and myoepithelial type genes. Clinical pathological validation of a small number of genes was performed on tissue microarrays.ResultsMPSS identified 6,553 differentially expressed genes between the pool of normal luminal cells and that of primary tumours substantially enriched for epithelial cells, of which 98% were represented and 60% were confirmed by microarray profiling. Significant expression level changes between these two samples detected only by microarray technology were shown by 4,149 transcripts, resulting in a combined differential tumour epithelial transcriptome of 8,051 genes. Microarray gene signatures identified a comprehensive list of 907 and 955 transcripts whose expression differed between luminal epithelial cells and myoepithelial cells, respectively. Functional annotation and gene set enrichment analysis highlighted a group of genes related to skeletal development that were associated with the myoepithelial/basal cells and upregulated in the tumour sample. One of the most highly overexpressed genes in this category, that encoding periostin, was analysed immunohistochemically on breast cancer tissue microarrays and its expression in neoplastic cells correlated with poor outcome in a cohort of poor prognosis estrogen receptor-positive tumours.ConclusionUsing highly enriched cell populations in combination with multiplatform gene expression profiling studies, a comprehensive analysis of molecular changes between the normal and malignant breast tissue was established. This study provides a basis for the identification of novel and potentially important targets for diagnosis, prognosis and therapy in breast cancer.

The generation and utilization of a cancer-oriented representation of the human transcriptome by using expressed sequence tags

Whereas genome sequencing defines the genetic potential of an organism, transcript sequencing defines the utilization of this potential and links the genome with most areas of biology. To exploit the information within the human genome in the fight against cancer, we have deposited some two million expressed sequence tags (ESTs) from human tumors and their corresponding normal tissues in the public databases. The data currently define ≈23,500 genes, of which only ≈1,250 are still represented only by ESTs. Examination of the EST coverage of known cancer-related (CR) genes reveals that <1% do not have corresponding ESTs, indicating that the representation of genes associated with commonly studied tumors is high. The careful recording of the origin of all ESTs we have produced has enabled detailed definition of where the genes they represent are expressed in the human body. More than 100,000 ESTs are available for seven tissues, indicating a surprising variability of gene usage that has led to the discovery of a significant number of genes with restricted expression, and that may thus be therapeutically useful. The ESTs also reveal novel nonsynonymous germline variants (although the one-pass nature of the data necessitates careful validation) and many alternatively spliced transcripts. Although widely exploited by the scientific community, vindicating our totally open source policy, the EST data generated still provide extensive information that remains to be systematically explored, and that may further facilitate progress toward both the understanding and treatment of human cancers.

Transcriptome-guided characterization of genomic rearrangements in a breast cancer cell line

We have identified new genomic alterations in the breast cancer cell line HCC1954, using high-throughput transcriptome sequencing. With 120 Mb of cDNA sequences, we were able to identify genomic rearrangement events leading to fusions or truncations of genes including MRE11 and NSD1, genes already implicated in oncogenesis, and 7 rearrangements involving other additional genes. This approach demonstrates that high-throughput transcriptome sequencing is an effective strategy for the characterization of genomic rearrangements in cancers.

Probabilistic base calling of Solexa sequencing data

BackgroundSolexa/Illumina short-read ultra-high throughput DNA sequencing technology produces millions of short tags (up to 36 bases) by parallel sequencing-by-synthesis of DNA colonies. The processing and statistical analysis of such high-throughput data poses new challenges; currently a fair proportion of the tags are routinely discarded due to an inability to match them to a reference sequence, thereby reducing the effective throughput of the technology.ResultsWe propose a novel base calling algorithm using model-based clustering and probability theory to identify ambiguous bases and code them with IUPAC symbols. We also select optimal sub-tags using a score based on information content to remove uncertain bases towards the ends of the reads.ConclusionWe show that the method improves genome coverage and number of usable tags as compared with Solexas data processing pipeline by an average of 15%. An R package is provided which allows fast and accurate base calling of Solexas fluorescence intensity files and the production of informative diagnostic plots.

Identification of cancer/testis-antigen genes by massively parallel signature sequencing

Massively parallel signature sequencing (MPSS) generates millions of short sequence tags corresponding to transcripts from a single RNA preparation. Most MPSS tags can be unambiguously assigned to genes, thereby generating a comprehensive expression profile of the tissue of origin. From the comparison of MPSS data from 32 normal human tissues, we identified 1,056 genes that are predominantly expressed in the testis. Further evaluation by using MPSS tags from cancer cell lines and EST data from a wide variety of tumors identified 202 of these genes as candidates for encoding cancer/testis (CT) antigens. Of these genes, the expression in normal tissues was assessed by RT-PCR in a subset of 166 intron-containing genes, and those with confirmed testis-predominant expression were further evaluated for their expression in 21 cancer cell lines. Thus, 20 CT or CT-like genes were identified, with several exhibiting expression in five or more of the cancer cell lines examined. One of these genes is a member of a CT gene family that we designated as CT45. The CT45 family comprises six highly similar (>98% cDNA identity) genes that are clustered in tandem within a 125-kb region on Xq26.3. CT45 was found to be frequently expressed in both cancer cell lines and lung cancer specimens. Thus, MPSS analysis has resulted in a significant extension of our knowledge of CT antigens, leading to the discovery of a distinctive X-linked CT-antigen gene family.

Rapid evolution of cancer/testis genes on the X chromosome

BackgroundCancer/testis (CT) genes are normally expressed only in germ cells, but can be activated in the cancer state. This unusual property, together with the finding that many CT proteins elicit an antigenic response in cancer patients, has established a role for this class of genes as targets in immunotherapy regimes. Many families of CT genes have been identified in the human genome, but their biological function for the most part remains unclear. While it has been shown that some CT genes are under diversifying selection, this question has not been addressed before for the class as a whole.ResultsTo shed more light on this interesting group of genes, we exploited the generation of a draft chimpanzee (Pan troglodytes) genomic sequence to examine CT genes in an organism that is closely related to human, and generated a high-quality, manually curated set of human:chimpanzee CT gene alignments. We find that the chimpanzee genome contains homologues to most of the human CT families, and that the genes are located on the same chromosome and at a similar copy number to those in human. Comparison of putative human:chimpanzee orthologues indicates that CT genes located on chromosome X are diverging faster and are undergoing stronger diversifying selection than those on the autosomes or than a set of control genes on either chromosome X or autosomes.ConclusionGiven their high level of diversifying selection, we suggest that CT genes are primarily responsible for the observed rapid evolution of protein-coding genes on the X chromosome.

ZFN-site searches genomes for zinc finger nuclease target sites and off-target sites.

BackgroundZinc Finger Nucleases (ZFNs) are man-made restriction enzymes useful for manipulating genomes by cleaving target DNA sequences. ZFNs allow therapeutic gene correction or creation of genetically modified model organisms. ZFN specificity is not absolute; therefore, it is essential to select ZFN target sites without similar genomic off-target sites. It is important to assay for off-target cleavage events at sites similar to the target sequence.ResultsZFN-Site is a web interface that searches multiple genomes for ZFN off-target sites. Queries can be based on the target sequence or can be expanded using degenerate specificity to account for known ZFN binding preferences. ZFN off-target sites are outputted with links to genome browsers, facilitating off-target cleavage site screening. We verified ZFN-Site using previously published ZFN half-sites and located their target sites and their previously described off-target sites. While we have tailored this tool to ZFNs, ZFN-Site can also be used to find potential off-target sites for other nucleases, such as TALE nucleases.ConclusionsZFN-Site facilitates genome searches for possible ZFN cleavage sites based on user-defined stringency limits. ZFN-Site is an improvement over other methods because the FetchGWI search engine uses an indexed search of genome sequences for all ZFN target sites and possible off-target sites matching the half-sites and stringency limits. Therefore, ZFN-Site does not miss potential off-target sites.