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Illumina next generation sequencing data and expression microarrays data from retinoblastoma and medulloblastoma tissues.

ABSTRACT: Retinoblastoma (Rb) is a pediatric intraocular malignancy and probably the most robust clinical model on which genetic predisposition to develop cancer has been demonstrated. Since deletions in chromosome 13 have been described in this tumor, we performed next generation sequencing to test whether recurrent losses could be detected in low coverage data. We used Illumina platform for 13 tumor tissue samples: two pools of 4 retinoblastoma cases each and one pool of 5 medulloblastoma cases (raw data can be found at http://www.ebi.ac.uk/ena/data/view/PRJEB6630). We first created an in silico reference profile generated from a human sequenced genome (GRCh37p5). From this data we calculated an integrity score to get an overview of gains and losses in all chromosomes; we next analyzed each chromosome in windows of 40 kb length, calculating for each window the log2 ratio between reads from tumor pool and in silico reference. Finally we generated panoramic maps with all the windows whether lost or gained along each chromosome associated to its cytogenetic bands to facilitate interpretation. Expression microarrays was done for the same samples and a list of over and under expressed genes is presented here. For this detection a significance analysis was done and a log2 fold change was chosen as significant (raw data can be found at http://www.ncbi.nlm.nih.gov/geo/accession number GSE11488). The complete research article can be found at Cancer Genetics journal (Garcia-Chequer et al., in press) [1]. In summary here we provide an overview with visual graphics of gains and losses chromosome by chromosome in retinoblastoma and medulloblastoma, also the integrity score analysis and a list of genes with relevant expression associated. This material can be useful to researchers that may want to explore gains and losses in other malignant tumors with this approach or compare their data with retinoblastoma.

SUBMITTER: Garcia-Chequer AJ

PROVIDER: S-EPMC4753385 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

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Illumina next generation sequencing data and expression microarrays data from retinoblastoma and medulloblastoma tissues.

García-Chequer A J AJ Méndez-Tenorio A A Olguín-López G G Sánchez-Vallejo C C Isa P P Arias C F CF Torres J J Hernández-Angeles A A Ramírez-Ortiz M A MA Lara C C Cabrera-Muñoz Ma de L Mde L Sadowinski-Pine S S Bravo-Ortiz J C JC Ramón-García G G Diegopérez-Ramírez J J Ramírez-Reyes G G Casarrubias-Islas R R Ramírez J J Orjuela M M Ponce-Castañeda M V MV

Data in brief 20160127

Retinoblastoma (Rb) is a pediatric intraocular malignancy and probably the most robust clinical model on which genetic predisposition to develop cancer has been demonstrated. Since deletions in chromosome 13 have been described in this tumor, we performed next generation sequencing to test whether recurrent losses could be detected in low coverage data. We used Illumina platform for 13 tumor tissue samples: two pools of 4 retinoblastoma cases each and one pool of 5 medulloblastoma cases (raw dat ...[more]

PMID: 26937470

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Project description:BACKGROUND:When compared to Sanger sequencing technology, next-generation sequencing (NGS) technologies are hindered by shorter sequence read length, higher base-call error rate, non-uniform coverage, and platform-specific sequencing artifacts. These characteristics lower the quality of their downstream analyses, e.g. de novo and reference-based assembly, by introducing sequencing artifacts and errors that may contribute to incorrect interpretation of data. Although many tools have been developed for quality control and pre-processing of NGS data, none of them provide flexible and comprehensive trimming options in conjunction with parallel processing to expedite pre-processing of large NGS datasets. METHODS:We developed ngsShoRT (next-generation sequencing Short Reads Trimmer), a flexible and comprehensive open-source software package written in Perl that provides a set of algorithms commonly used for pre-processing NGS short read sequences. We compared the features and performance of ngsShoRT with existing tools: CutAdapt, NGS QC Toolkit and Trimmomatic. We also compared the effects of using pre-processed short read sequences generated by different algorithms on de novo and reference-based assembly for three different genomes: Caenorhabditis elegans, Saccharomyces cerevisiae S288c, and Escherichia coli O157 H7. RESULTS:Several combinations of ngsShoRT algorithms were tested on publicly available Illumina GA II, HiSeq 2000, and MiSeq eukaryotic and bacteria genomic short read sequences with the focus on removing sequencing artifacts and low-quality reads and/or bases. Our results show that across three organisms and three sequencing platforms, trimming improved the mean quality scores of trimmed sequences. Using trimmed sequences for de novo and reference-based assembly improved assembly quality as well as assembler performance. In general, ngsShoRT outperformed comparable trimming tools in terms of trimming speed and improvement of de novo and reference-based assembly as measured by assembly contiguity and correctness. CONCLUSIONS:Trimming of short read sequences can improve the quality of de novo and reference-based assembly and assembler performance. The parallel processing capability of ngsShoRT reduces trimming time and improves the memory efficiency when dealing with large datasets. We recommend combining sequencing artifacts removal, and quality score based read filtering and base trimming as the most consistent method for improving sequence quality and downstream assemblies. ngsShoRT source code, user guide and tutorial are available at http://research.bioinformatics.udel.edu/genomics/ngsShoRT/. ngsShoRT can be incorporated as a pre-processing step in genome and transcriptome assembly projects.

Project description:BackgroundReproducibility of results can have a significant impact on the acceptance of new technologies in gene expression analysis. With the recent introduction of the so-called next-generation sequencing (NGS) technology and established microarrays, one is able to choose between two completely different platforms for gene expression measurements. This study introduces a novel methodology for gene-ranking stability analysis that is applied to the evaluation of gene-ranking reproducibility on NGS and microarray data.ResultsThe same data used in a well-known MicroArray Quality Control (MAQC) study was also used in this study to compare ranked lists of genes from MAQC samples A and B, obtained from Affymetrix HG-U133 Plus 2.0 and Roche 454 Genome Sequencer FLX platforms. An initial evaluation, where the percentage of overlapping genes was observed, demonstrates higher reproducibility on microarray data in 10 out of 11 gene-ranking methods. A gene set enrichment analysis shows similar enrichment of top gene sets when NGS is compared with microarrays on a pathway level. Our novel approach demonstrates high accuracy of decision trees when used for knowledge extraction from multiple bootstrapped gene set enrichment analysis runs. A comparison of the two approaches in sample preparation for high-throughput sequencing shows that alternating decision trees represent the optimal knowledge representation method in comparison with classical decision trees.ConclusionsUsual reproducibility measurements are mostly based on statistical techniques that offer very limited biological insights into the studied gene expression data sets. This paper introduces the meta-learning-based gene set enrichment analysis that can be used to complement the analysis of gene-ranking stability estimation techniques such as percentage of overlapping genes or classic gene set enrichment analysis. It is useful and practical when reproducibility of gene ranking results or different gene selection techniques is observed. The proposed method reveals very accurate descriptive models that capture the co-enrichment of gene sets which are differently enriched in the compared data sets.

Project description:BackgroundMassively parallel sequencing technology is revolutionizing approaches to genomic and genetic research. Since its advent, the scale and efficiency of Next-Generation Sequencing (NGS) has rapidly improved. In spite of this success, sequencing genomes or genomic regions with extremely biased base composition is still a great challenge to the currently available NGS platforms. The genomes of some important pathogenic organisms like Plasmodium falciparum (high AT content) and Mycobacterium tuberculosis (high GC content) display extremes of base composition. The standard library preparation procedures that employ PCR amplification have been shown to cause uneven read coverage particularly across AT and GC rich regions, leading to problems in genome assembly and variation analyses. Alternative library-preparation approaches that omit PCR amplification require large quantities of starting material and hence are not suitable for small amounts of DNA/RNA such as those from clinical isolates. We have developed and optimized library-preparation procedures suitable for low quantity starting material and tolerant to extremely high AT content sequences.ResultsWe have used our optimized conditions in parallel with standard methods to prepare Illumina sequencing libraries from a non-clinical and a clinical isolate (containing ~53% host contamination). By analyzing and comparing the quality of sequence data generated, we show that our optimized conditions that involve a PCR additive (TMAC), produces amplified libraries with improved coverage of extremely AT-rich regions and reduced bias toward GC neutral templates.ConclusionWe have developed a robust and optimized Next-Generation Sequencing library amplification method suitable for extremely AT-rich genomes. The new amplification conditions significantly reduce bias and retain the complexity of either extremes of base composition. This development will greatly benefit sequencing clinical samples that often require amplification due to low mass of DNA starting material.

Project description:BACKGROUND: This study describes how the complete mitogenome of a terrestrial snail, Cylindrus obtusus (Draparnaud, 1805) was sequenced without PCRs from a collection specimen that had been in 70% ethanol for 8 years. The mitogenome was obtained with Illumina GAIIx shot gun sequencing. Although the used specimen was collected relatively recently and kept in a DNA-friendly preservative (not formalin as frequently used with old museum specimens), we believe that the exclusion of PCRs as facilitated by NGS (Next Generation Sequencing) removes a great obstacle in DNA sequencing of collection specimens. A brief comparison is made between our Illumina GAIIx approach and a similar study that made use of the Roche 454-FLX platform. RESULTS: The mtDNA sequence of C. obtusus is 14,610 bases in length (about 0.5 kb larger than other stylommatophoran mitogenomes reported hitherto) and contains the 37 genes (13 protein coding genes, two rRNAs and 22 tRNAs) typical for metazoans. Except for a swap between the position of tRNA-Pro and tRNA-Ala, the gene arrangement of C. obtusus is identical to that reported for Cepaea nemoralis. The 'aberrant' rearrangement of tRNA-Thr and COIII compared to that of other Sigmurethra (and the majority of gastropods), is not unique for C. nemoralis (subfamily Helicinae), but is also shown to occur in C. obtusus (subfamily Ariantinae) and might be a synapomorphy for the family Helicidae. CONCLUSIONS: Natural history collections potentially harbor a wealth of information for the field of evolutionary genetics, but it can be difficult to amplify DNA from such specimens (due to DNA degradation for instance). Because NGS techniques do not rely on primer-directed amplification (PCR) and allow DNA to be fragmented (DNA gets sheared during library preparation), NGS could be a valuable tool for retrieving DNA sequence data from such specimens. A comparison between Illumina GAIIx and the Roche 454 platform suggests that the former might be more suited for de novo sequencing of mitogenomes.

Dataset Information

Illumina next generation sequencing data and expression microarrays data from retinoblastoma and medulloblastoma tissues.

Publications

Illumina next generation sequencing data and expression microarrays data from retinoblastoma and medulloblastoma tissues.

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