Detection of mutations in the dystrophin gene via automated DHPLC screening and direct sequencing

BACKGROUND: Currently molecular diagnostic laboratories focus only on the identification of large deletion and duplication mutations (spanning one exon or more) for Duchenne Muscular Dystrophy (DMD) yielding 65% of causative mutations. These mutations are detected by an existing set of multiplexed polymerase chain reaction (PCR) primer pairs. Due to the large size of the dystrophin gene (79 exons), finding point mutations (substitutions, deletions or insertions of one or several nucleotides) has been prohibitively expensive and laborious. The aim of this project was to develop an effective and convenient method of finding all, or most, mutations in the dystrophin gene with only a moderate increase in cost. RESULTS: Using denaturing high performance liquid chromatography (DHPLC) screening and direct sequencing, 86 PCR amplicons of genomic DNA from the dystrophin gene were screened for mutations in eight patients diagnosed with DMD who had tested negative for large DNA rearragements. Mutations likely to be disease-causative were found in six of the eight patients. All 86 amplicons from the two patients in whom no likely disease-causative mutations were found were completely sequenced and only polymorphisms were found. CONCLUSIONS: We have shown that it is now feasible for clinical laboratories to begin testing for both point mutations and large deletions/duplications in the dystrophin gene. The detection rate will rise from 65% to greater than 92% with only a moderate increase in cost

New methods for next generation sequencing based microRNA expression profiling

<p>Abstract</p> <p>Background</p> <p>MicroRNAs are small non-coding RNA transcripts that regulate post-transcriptional gene expression. The millions of short sequence reads generated by next generation sequencing technologies make this technique explicitly suitable for profiling of known and novel microRNAs. A modification to the small-RNA expression kit (SREK, Ambion) library preparation method for the SOLiD sequencing platform is described to generate microRNA sequencing libraries that are compatible with the Illumina Genome Analyzer.</p> <p>Results</p> <p>High quality sequencing libraries can successfully be prepared from as little as 100 ng small RNA enriched RNA. An easy to use perl-based analysis pipeline called E-miR was developed to handle the sequencing data in several automated steps including data format conversion, 3' adapter removal, genome alignment and annotation to non-coding RNA transcripts. The sample preparation and E-miR pipeline were used to identify 37 cardiac enriched microRNAs in stage 16 chicken embryos. Isomir expression profiles between the heart and embryo were highly correlated for all miRNAs suggesting that tissue or cell specific miRNA modifications do not occur.</p> <p>Conclusions</p> <p>In conclusion, our alternative sample preparation method can successfully be applied to generate high quality miRNA sequencing libraries for the Illumina genome analyzer.</p

Developing a set of ancestry-sensitive DNA markers reflecting continental origins of humans

Background: The identification and use of Ancestry-Sensitive Markers (ASMs), i.e. genetic polymorphisms facilitating the genetic reconstruction of geographical origins of individuals, is far from straightforward. Results: Here we describe the ascertainment and application of five different sets of 47 single nucleotide polymorphisms (SNPs) allowing the inference of major human groups of different continental origin. For this, we first used 74 cell lines, representing human males from six different geographical areas and screened them with the Affymetrix Mapping 10K assay. In addition to using summary statistics estimating the genetic diversity among multiple groups of individuals defined by geography or language, we also used the program STRUCTURE to detect genetically distinct subgroups. Subsequently, we used a pairwise FSTranking procedure among all pairs of genetic subgroups in order to identify a single best performing set of ASMs. Our initial results were independently confirmed by genotyping this set of ASMs in 22 individuals from Somalia, Afghanistan and Sudan and in 919 samples from the CEPH Human Genome Diversity Panel (HGDP-CEPH). Conclusion: By means of our pairwise population FSTranking approach we identified a set of 47 SNPs that could serve as a panel of ASMs at a continental level

Standard Mutation Nomenclature in Molecular Diagnostics

To translate basic research findings into clinical practice, it is essential that information about mutations and variations in the human genome are communicated easily and unequivocally. Unfortunately, there has been much confusion regarding the description of genetic sequence variants. This is largely because research articles that first report novel sequence variants do not often use standard nomenclature, and the final genomic sequence is compiled over many separate entries. In this article, we discuss issues crucial to clear communication, using examples of genes that are commonly assayed in clinical laboratories. Although molecular diagnostics is a dynamic field, this should not inhibit the need for and movement toward consensus nomenclature for accurate reporting among laboratories. Our aim is to alert laboratory scientists and other health care professionals to the important issues and provide a foundation for further discussions that will ultimately lead to solutions

GeneHopper: a web-based search engine to link gene-expression platforms through GenBank accession numbers

Global gene-expression analysis is carried out using different technologies that are either array- or sequence-tag-based. To compare experiments that are performed on these different platforms, array probes and sequence tags need to be linked. An additional challenge is cross-referencing between species, to compare human profiles with those obtained in a mouse model, for example. We have developed the web-based search engine GeneHopper to link different expression resources based on UniGene clusters and HomoloGene orthologs databases of the National Center for Biotechnology Information (NCBI)

Properties and units in the clinical laboratory sciences part XXIV. Properties and units in clinical molecular genetics (IUPAC Technical Report)

This document describes the application of the syntax, semantic rules, and format of the Nomenclature for Properties and Units (NPU) terminology for coded dedicated kinds-of-property in the subject field of clinical molecular genetics. A vocabulary for NPU definitions in this field, based on international terminology and nomenclature, is introduced and examples of actual NPU definitions for different types of investigations are given and explained

CORE_TF: a user-friendly interface to identify evolutionary conserved transcription factor binding sites in sets of co-regulated genes

<p>Abstract</p> <p>Background</p> <p>The identification of transcription factor binding sites is difficult since they are only a small number of nucleotides in size, resulting in large numbers of false positives and false negatives in current approaches. Computational methods to reduce false positives are to look for over-representation of transcription factor binding sites in a set of similarly regulated promoters or to look for conservation in orthologous promoter alignments.</p> <p>Results</p> <p>We have developed a novel tool, "CORE_TF" (Conserved and Over-REpresented Transcription Factor binding sites) that identifies common transcription factor binding sites in promoters of co-regulated genes. To improve upon existing binding site predictions, the tool searches for position weight matrices from the TRANSFAC^{<it>R </it>}database that are over-represented in an experimental set compared to a random set of promoters and identifies cross-species conservation of the predicted transcription factor binding sites. The algorithm has been evaluated with expression and chromatin-immunoprecipitation on microarray data. We also implement and demonstrate the importance of matching the random set of promoters to the experimental promoters by GC content, which is a unique feature of our tool.</p> <p>Conclusion</p> <p>The program CORE_TF is accessible in a user friendly web interface at <url>http://www.LGTC.nl/CORE_TF</url>. It provides a table of over-represented transcription factor binding sites in the users input genes' promoters and a graphical view of evolutionary conserved transcription factor binding sites. In our test data sets it successfully predicts target transcription factors and their binding sites.</p

Literature-aided meta-analysis of microarray data: a compendium study on muscle development and disease

Background: Comparative analysis of expression microarray studies is difficult due to the large influence of technical factors on experimental outcome. Still, the identified differentially expressed genes may hint at the same biological processes. However, manually curated assignment of genes to biological processes, such as pursued by the Gene Ontology (GO) consortium, is incomplete and limited. We hypothesised that automatic association of genes with biological processes through thesaurus-controlled mining of Medline abstracts would be more effective. Therefore, we developed a novel algorithm (LAMA: Literature-Aided Meta-Analysis) to quantify the similarity between transcriptomics studies. We evaluated our algorithm on a large compendium of 102 microarray studies published in the field of muscle development and disease, and compared it to similarity measures based on gene overlap and over-representation of biological processes assigned by GO. Results: While the overlap in both genes and overrepresented GO-terms was poor, LAMA retrieved many more biologically meaningful links between studies, with substantially lower influence of technical factors. LAMA correctly grouped muscular dystrophy, regeneration and myositis studies, and linked patient and corresponding mouse model studies. LAMA also retrieves the connecting biological concepts. Among other new discoveries, we associated cullin proteins, a class of ubiquitinylation proteins, with genes down-regulated during muscle regeneration, whereas ubiquitinylation was previously reported to be activated during the inverse process: muscle atrophy. Conclusion: Our literature-based association analysis is capable of finding hidden common biological denominators in microarray studies, and circumvents the need for raw data analysis or curated gene annotation databases

Large scale single nucleotide polymorphism discovery in unsequenced genomes using second generation high throughput sequencing technology: applied to turkey

<p>Abstract</p> <p>Background</p> <p>The development of second generation sequencing methods has enabled large scale DNA variation studies at moderate cost. For the high throughput discovery of single nucleotide polymorphisms (SNPs) in species lacking a sequenced reference genome, we set-up an analysis pipeline based on a short read de novo sequence assembler and a program designed to identify variation within short reads. To illustrate the potential of this technique, we present the results obtained with a randomly sheared, enzymatically generated, 2-3 kbp genome fraction of six pooled <it>Meleagris gallopavo </it>(turkey) individuals.</p> <p>Results</p> <p>A total of 100 million 36 bp reads were generated, representing approximately 5-6% (~62 Mbp) of the turkey genome, with an estimated sequence depth of 58. Reads consisting of bases called with less than 1% error probability were selected and assembled into contigs. Subsequently, high throughput discovery of nucleotide variation was performed using sequences with more than 90% reliability by using the assembled contigs that were 50 bp or longer as the reference sequence. We identified more than 7,500 SNPs with a high probability of representing true nucleotide variation in turkeys. Increasing the reference genome by adding publicly available turkey BAC-end sequences increased the number of SNPs to over 11,000. A comparison with the sequenced chicken genome indicated that the assembled turkey contigs were distributed uniformly across the turkey genome. Genotyping of a representative sample of 340 SNPs resulted in a SNP conversion rate of 95%. The correlation of the minor allele count (MAC) and observed minor allele frequency (MAF) for the validated SNPs was 0.69.</p> <p>Conclusion</p> <p>We provide an efficient and cost-effective approach for the identification of thousands of high quality SNPs in species currently lacking a sequenced genome and applied this to turkey. The methodology addresses a random fraction of the genome, resulting in an even distribution of SNPs across the targeted genome.</p