Advancing transcriptome platforms

During the last decade of years, remarkable technological innovations have emerged that allow the direct or indirect determination of the transcriptome at unprecedented scale and speed. Studies using these methods have already altered our view of the extent and complexity of transcript profiling, which has advanced from one-gene-at-a-time to a holistic view of the genome. Here, we outline the major technical advances in transcriptome characterization, including the most popular used hybridization-based platform, the well accepted tag-based sequencing platform, and the recently developed RNA-Seq (RNA sequencing) based platform. Importantly, these next-generation technologies revolutionize assessing the entire transcriptome via the recent RNA-Seq technology

FISH mapping and molecular organization of the major repetitive sequences of tomato

This paper presents a bird's-eye view of the major repeats and chromatin types of tomato. Using fluorescence in-situ hybridization (FISH) with Cot-1, Cot-10 and Cot-100 DNA as probes we mapped repetitive sequences of different complexity on pachytene complements. Cot-100 was found to cover all heterochromatin regions, and could be used to identify repeat-rich clones in BAC filter hybridization. Next we established the chromosomal locations of the tandem and dispersed repeats with respect to euchromatin, nucleolar organizer regions (NORs), heterochromatin, and centromeres. The tomato genomic repeats TGRII and TGRIII appeared to be major components of the pericentromeres, whereas the newly discovered TGRIV repeat was found mainly in the structural centromeres. The highly methylated NOR of chromosome 2 is rich in [GACA](4), a microsatellite that also forms part of the pericentromeres, together with [GA](8), [GATA](4) and Ty1-copia. Based on the morphology of pachytene chromosomes and the distribution of repeats studied so far, we now propose six different chromatin classes for tomato: (1) euchromatin, (2) chromomeres, (3) distal heterochromatin and interstitial heterochromatic knobs, (4) pericentromere heterochromatin, (5) functional centromere heterochromatin and (6) nucleolar organizer regio

Single cell transcriptome analysis using next generation sequencing.

The heterogeneity of tissues, especially in cancer research, is a central issue in transcriptome analysis. In recent years, research has primarily focused on the development of methods for single cell analysis. Single cell analysis aims at gaining (novel) insights into biological processes of healthy and diseased cells. Some of the challenges in transcriptome analysis concern low abundance of sample starting material, necessary sample amplification steps and subsequent analysis. In this study, two fundamentally different approaches to amplification were compared using next-generation sequencing analysis: I. exponential amplification using polymerase-chain-reaction (PCR) and II. linear amplification. For both approaches, protocols for single cell extraction, cell lysis, cDNA synthesis, cDNA amplification and preparation of next-generation sequencing libraries were developed. We could successfully show that transcriptome analysis of low numbers of cells is feasible with both exponential and linear amplification. Using exponential amplification, the highest amplification rates up to 106 were possible. The reproducibility of results is a strength of the linear amplification method. The analysis of next generation sequencing data in single cell samples showed detectable expression in at least 16.000 genes. The variance between samples results in a need to work with a greater amount of biological replicates. In summary it can be said that single cell transcriptome analysis with next generation sequencing is possible but improvements leading to a higher yield of transcriptome reads is required. In the near future by comparing single cancer cells with healthy ones for example, a basis for improved prognosis and diagnosis can be realised

Capturing the ‘ome’ : the expanding molecular toolbox for RNA and DNA library construction

All sequencing experiments and most functional genomics screens rely on the generation of libraries to comprehensively capture pools of targeted sequences. In the past decade especially, driven by the progress in the field of massively parallel sequencing, numerous studies have comprehensively assessed the impact of particular manipulations on library complexity and quality, and characterized the activities and specificities of several key enzymes used in library construction. Fortunately, careful protocol design and reagent choice can substantially mitigate many of these biases, and enable reliable representation of sequences in libraries. This review aims to guide the reader through the vast expanse of literature on the subject to promote informed library generation, independent of the application

Isolation of Unknown Genes from Human Bone Marrow by Differental Screening and Single-Pass cDNA Sequences Determination

A cDNA sequencing project was initiated to characterize gene expression in human bone marrow and develop strategies to isolate novel genes. Forty-eight random cDNAs from total human bone marrow were subjected to single-pass DNA sequence analysis to determine a limited complexity of mRNAs expressed in the bone marrow. Overall, 8 cDNAs (17%) showed no similarity to known sequences. Information from DNA sequence analysis was used to develop a differential prescreen to subtract unwanted cDNAs and to enrich for unknown cDNAs. Forty-eight cDNAs that were negative with a complex probe were subject to single-pass DNA sequence determination. Of these prescreened cDNAs, the number of unknown sequences increased to 23 (48%). Unknown cDNAs were also characterized by RNA expression analysis using 25 different human leukemic cell lines. Of 13 unknown cDNAs tested, 10 were expressed in all cell types tested and 3 revealed a hematopoietic lineage-restricted expression pattern. Interestingly, while a total of only 96 bone marrow cDNAs were sequenced, 31 of these cDNAs represent sequences from unknown genes and 12 showed significant similarities to sequences in the data bases. One cDNA revealed a significant similarity to a serine/threonine-protein kinase at the amino acid level (56% identity for 123 amino acids) and may represent a previously unknown kinase. Differential screening techniques coupled with single-pass cDNA sequence analysis may prove to be a powerful and simple technique to examine developmental gene expression

Review of precision cancer medicine: Evolution of the treatment paradigm.

In recent years, biotechnological breakthroughs have led to identification of complex and unique biologic features associated with carcinogenesis. Tumor and cell-free DNA profiling, immune markers, and proteomic and RNA analyses are used to identify these characteristics for optimization of anticancer therapy in individual patients. Consequently, clinical trials have evolved, shifting from tumor type-centered to gene-directed, histology-agnostic, with innovative adaptive design tailored to biomarker profiling with the goal to improve treatment outcomes. A plethora of precision medicine trials have been conducted. The majority of these trials demonstrated that matched therapy is associated with superior outcomes compared to non-matched therapy across tumor types and in specific cancers. To improve the implementation of precision medicine, this approach should be used early in the course of the disease, and patients should have complete tumor profiling and access to effective matched therapy. To overcome the complexity of tumor biology, clinical trials with combinations of gene-targeted therapy with immune-targeted approaches (e.g., checkpoint blockade, personalized vaccines and/or chimeric antigen receptor T-cells), hormonal therapy, chemotherapy and/or novel agents should be considered. These studies should target dynamic changes in tumor biologic abnormalities, eliminating minimal residual disease, and eradicating significant subclones that confer resistance to treatment. Mining and expansion of real-world data, facilitated by the use of advanced computer data processing capabilities, may contribute to validation of information to predict new applications for medicines. In this review, we summarize the clinical trials and discuss challenges and opportunities to accelerate the implementation of precision oncology

Clinical application of high throughput molecular screening techniques for pharmacogenomics.

Genetic analysis is one of the fastest-growing areas of clinical diagnostics. Fortunately, as our knowledge of clinically relevant genetic variants rapidly expands, so does our ability to detect these variants in patient samples. Increasing demand for genetic information may necessitate the use of high throughput diagnostic methods as part of clinically validated testing. Here we provide a general overview of our current and near-future abilities to perform large-scale genetic testing in the clinical laboratory. First we review in detail molecular methods used for high throughput mutation detection, including techniques able to monitor thousands of genetic variants for a single patient or to genotype a single genetic variant for thousands of patients simultaneously. These methods are analyzed in the context of pharmacogenomic testing in the clinical laboratories, with a focus on tests that are currently validated as well as those that hold strong promise for widespread clinical application in the near future. We further discuss the unique economic and clinical challenges posed by pharmacogenomic markers. Our ability to detect genetic variants frequently outstrips our ability to accurately interpret them in a clinical context, carrying implications both for test development and introduction into patient management algorithms. These complexities must be taken into account prior to the introduction of any pharmacogenomic biomarker into routine clinical testing

A new approach to understanding T cell development: the isolation and characterization of immature CD4-, CD8-, CD3- T cell cDNAs by subtraction cloning

During T cell development in the mammalian thymus, immature T cells are observed that lack the cell surface markers CD4, CD8, and CD3. A subtracted cDNA library was constructed to isolate cDNAs that are specific for these immature T cells. Tissue-specific expression of 97 individual cDNAs were examined using different cell types by Northern blot analysis, and six cDNAs were analyzed by reverse transcriptase (RT) polymerase chain reaction (PCR) detection of RNA. Approximately 50% of the clones could not be detected on Northern blots, and 40% of the clones were expressed by at least one other cell-type including monocytes, mature T cells, and B cells. Eight cDNA clones appear to be specific for the CD4-, CD8-, CD3- T cell line, used to construct the library, as determined by Northern blot analysis. In addition, 330 cDNA clones were subjected to partial automated DNA sequence determination. Database searches, with both nucleotide and protein translations, revealed cDNAs that exhibit interesting similarities to human cell-cycle gene 1, platelet-derived growth factor receptor, c-fms oncogene (CSF-1) receptor, and members of the immunoglobulin gene superfamily. This approach of employing subtraction coupled with large scale partial cDNA sequence determination can be useful to identify genes that may be involved in early T cell growth, cellular recognition or differentiation