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)

Decay of Sexual Trait Genes in an Asexual Parasitoid Wasp.

Trait loss is a widespread phenomenon with pervasive consequences for a species’ evolutionary potential. The genetic changes underlying trait loss have only been clarified in a small number of cases. None of these studies can identify whether the loss of the trait under study was a result of neutral mutation accumulation or negative selection. This distinction is relatively clear-cut in the loss of sexual traits in asexual organisms. Male-specific sexual traits are not expressed and can only decay through neutral mutations, whereas female-specific traits are expressed and subject to negative selection. We present the genome of an asexual parasitoid wasp and compare it to that of a sexual lineage of the same species. We identify a short-list of 16 genes for which the asexual lineage carries deleterious SNP or indel variants, whereas the sexual lineag e does not. Using tissue-specific expression data from other insects, we show that fifteen of these are expressed in male-specific reproductive tissues. Only one deleterious variant was found that is expressed in the female-specific spermathecae, a trait that is heavily degraded and thought to be under negative selection in L. clavipes . Although the phenotypic decay of male-specific sexual traits in asexuals is generally slow compared with the decay of female-specific sexual traits, we show that male-specific traits do indeed accumulate deleterious mutations as expected by theory. Our results provide an excellent starting point for detailed s tudy of the genomics of neutral and selected trait decay

Literature-aided interpretation of gene expression data with the weighted global test

Most methods for the interpretation of gene expression profiling experiments rely on the categorization of genes, as provided by the Gene Ontology (GO) and pathway databases. Due to the manual curation process, such databases are never up-to-date and tend to be limited in focus and coverage. Automated literature mining tools provide an attractive, alternative approach. We review how they can be employed for the interpretation of gene expression profiling experiments. We illustrate that their comprehensive scope aids the interpretation of data from domains poorly covered by GO or alternative databases, and allows for the linking of gene expression with diseases, drugs, tissues and other types of concepts. A framework for proper statistical evaluation of the associations between gene expression values and literature concepts was lacking and is now implemented in a weighted extension of global test. The weights are the literature association scores and reflect the importance of a gene for the concept of interest. In a direct comparison with classical GO-based gene sets, we show that use of literature-based associations results in the identification of much more specific GO categories. We demonstrate the possibilities for linking of gene expression data to patient survival in breast cancer and the action and metabolism of drugs. Coupling with online literature mining tools ensures transparency and allows further study of the identified associations. Literature mining tools are therefore powerful additions to the toolbox for the interpretation of high-throughput genomics data.UB – Publicatie

Can subtle changes in gene expression be consistently detected with different microarray platforms?

Background: The comparability of gene expression data generated with different microarray platforms is still a matter of concern. Here we address the performance and the overlap in the detection of differentially expressed genes for five different microarray platforms in a challenging biological context where differences in gene expression are few and subtle. Results: Gene expression profiles in the hippocampus of five wild-type and five transgenic δC-doublecortin-like kinase mice were evaluated with five microarray platforms: Applied Biosystems, Affymetrix, Agilent, Illumina, LGTC home-spotted arrays. Using a fixed false discovery rate of 10% we detected surprising differences between the number of differentially expressed genes per platform. Four genes were selected by ABI, 130 by Affymetrix, 3,051 by Agilent, 54 by Illumina, and 13 by LGTC. Two genes were found significantly differentially expressed by all platforms and the four genes identified by the ABI platform were found by at least three other platforms. Quantitative RT-PCR analysis confirmed 20 out of 28 of the genes detected by two or more platforms and 8 out of 15 of the genes detected by Agilent only. We observed improved correlations between platforms when ranking the genes based on the significance level than with a fixed statistical cut-off. We demonstrate significant overlap in the affected gene sets identified by the different platforms, although biological processes were represented by only partially overlapping sets of genes. Aberrances in GABA-ergic signalling in the transgenic mice were consistently found by all platforms. Conclusion: The different microarray platforms give partially complementary views on biological processes affected. Our data indicate that when analyzing samples with only subtle differences in gene expression the use of two different platforms might be more attractive than increasing the number of replicates. Commercial two-color platforms seem to have higher power for finding differentially expressed genes between groups with small differences in expression

HNPCC: Six new pathogenic mutations

BACKGROUND: Hereditary non-polyposis colorectal cancer (HNPCC) is an autosomal dominant disease with a high risk for colorectal and endometrial cancer caused by germline mutations in DNA mismatch-repair genes (MMR). HNPCC accounts for approximately 2 to 5% of all colorectal cancers. Here we present 6 novel mutations in the DNA mismatch-repair genes MLH1, MSH2 and MSH6. METHODS: Patients with clinical diagnosis of HNPCC were counselled. Tumor specimen were analysed for microsatellite instability and immunohistochemistry for MLH1, MSH2 and MSH6 protein was performed. If one of these proteins was not detectable in the tumor mutation analysis of the corresponding gene was carried out. RESULTS: We identified 6 frameshift mutations (2 in MLH1, 3 in MSH2, 1 in MSH6) resulting in a premature stop: two mutations in MLH1 (c.2198_2199insAACA [p.N733fsX745], c.2076_2077delTG [p.G693fsX702]), three mutations in MSH2 (c.810_811delGT [p.C271fsX282], c.763_766delAGTGinsTT [p.F255fsX282], c.873_876delGACT [p.L292fsX298]) and one mutation in MSH6 (c.1421_1422dupTG [p.C475fsX480]). All six tumors tested for microsatellite instability showed high levels of microsatellite instability (MSI-H). CONCLUSIONS: HNPCC in families with MSH6 germline mutations may show an age of onset that is comparable to this of patients with MLH1 and MSH2 mutations

LAMA2 gene mutation update: Toward a more comprehensive picture of the laminin-α2 variome and its related phenotypes

Congenital muscular dystrophy type 1A (MDC1A) is one of the main subtypes of early-onset muscle disease, caused by disease-associated variants in the laminin-α2 (LAMA2) gene. MDC1A usually presents as a severe neonatal hypotonia and failure to thrive. Muscle weakness compromises normal motor development, leading to the inability to sit unsupported or to walk independently. The phenotype associated with LAMA2 defects has been expanded to include milder and atypical cases, being now collectively known as LAMA2-related muscular dystrophies (LAMA2-MD). Through an international multicenter collaborative effort, 61 new LAMA2 disease-associated variants were identified in 86 patients, representing the largest number of patients and new disease-causing variants in a single report. The collaborative variant collection was supported by the LOVD-powered LAMA2 gene variant database (https://www.LOVD.nl/LAMA2), updated as part of this work. As of December 2017, the database contains 486 unique LAMA2 variants (309 disease-associated), obtained from direct submissions and literature reports. Database content was systematically reviewed and further insights concerning LAMA2-MD are presented. We focus on the impact of missense changes, especially the c.2461A > C (p.Thr821Pro) variant and its association with late-onset LAMA2-MD. Finally, we report diagnostically challenging cases, highlighting the relevance of modern genetic analysis in the characterization of clinically heterogeneous muscle diseases.info:eu-repo/semantics/publishedVersio

Novel variants in GNAI3 associated with auriculocondylar syndrome strengthen a common dominant negative effect

Auriculocondylar syndrome is a rare craniofacial disorder comprising core features of micrognathia, condyle dysplasia and question mark ear. Causative variants have been identified in PLCB4, GNAI3 and EDN1, which are predicted to function within the EDN1-EDNRA pathway during early pharyngeal arch patterning. To date, two GNAI3 variants in three families have been reported. Here we report three novel GNAI3 variants, one segregating with affected members in a family previously linked to 1p21.1-q23.3 and two de novo variants in simplex cases. Two variants occur in known functional motifs, the G1 and G4 boxes, and the third variant is one amino acid outside of the G1 box. Structural modeling shows that all five altered GNAI3 residues identified to date cluster in a region involved in GDP/GTP binding. We hypothesize that all GNAI3 variants lead to dominant negative effects.CRANIRAREUniversite Paris Descartes-Sorbonne Paris Cite Pole de Recherche et d'Enseignement SuperieurAgence Nationale de la Recherche (project EvoDevoMut)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)National Health and Medical Research Council of AustraliaUniv São Paulo, Inst Biociencias, Dept Genet & Biol Evolut, Ctr Pesquisas Genoma Humano & Celulas Tronco, BR-05508090 São Paulo, BrazilUniv Paris 05, Sorbonne Paris Cite, INSERM, U1163, Paris, FranceUniv São Paulo, HRCA, Dept Clin Genet, Bauru, BrazilUniv Melbourne, Royal Childrens Hosp, Murdoch Childrens Res Inst, Victorian Clin Genet Serv, Melbourne, Vic, AustraliaUniv Melbourne, Dept Paediat, Melbourne, Vic, AustraliaRoyal Childrens Hosp, Dept Plast & Maxillofacial Surg, Melbourne, Vic, AustraliaHosp Sick Children, Dept Otolaryngol Head & Neck Surg, Toronto, ON M5G 1X8, CanadaUniv São Paulo, Inst Biosci, BR-05508090 São Paulo, BrazilLeiden Univ, Med Ctr, Leiden Genome Technol Ctr, Leiden, NetherlandsUniversidade Federal de São Paulo, Inst Ciencia & Tecnol, Sao Jose Dos Campos, BrazilHop Necker Enfants Malad, AP HP, Dept Genet, Paris, FranceUniversidade Federal de São Paulo, Inst Ciencia & Tecnol, Sao Jose Dos Campos, BrazilUniversite Paris Descartes-Sorbonne Paris Cite Pole de Recherche et d'Enseignement Superieur: SPC/JFG/2013-031National Health and Medical Research Council of Australia: 607431Web of Scienc

Brain tumour diagnostics using a DNA methylation-based classifier as a diagnostic support tool

Aims: Methylation profiling (MP) is increasingly incorporated in the diagnostic process of central nervous system (CNS) tumours at our centres in The Netherlands and Scandinavia. We aimed to identify the benefits and challenges of MP as a support tool for CNS tumour diagnostics. Methods: About 502 CNS tumour samples were analysed using (850 k) MP. Profiles were matched with the DKFZ/Heidelberg CNS Tumour Classifier. For each case, the final pathological diagnosis was compared to the diagnosis before MP. Results: In 54.4% (273/502) of all analysed cases, the suggested methylation class (calibrated score ≥0.9) corresponded with the initial pathological diagnosis. The diagnosis of 24.5% of these cases (67/273) was more refined after incorporation of the MP result. In 9.8% of cases (49/502), the MP result led to a new diagnosis, resulting in an altered WHO grade in 71.4% of these cases (35/49). In 1% of cases (5/502), the suggested class based on MP was initially disregarded/interpreted as misleading, but in retrospect, the MP result predicted the right diagnosis for three of these cases. In six cases, the suggested class was interpreted as ‘discrepant but noncontributory’. The remaining 33.7% of cases (169/502) had a calibrated score <0.9, including 7.8% (39/502) for which no class indication was given at all (calibrated score <0.3). Conclusions: MP is a powerful tool to confirm and fine-tune the pathological diagnosis of CNS tumours, and to avoid misdiagnoses. However, it is crucial to interpret the results in the context of clinical, radiological, histopathological and other molecular information

Locus Reference Genomic sequences: an improved basis for describing human DNA variants

As our knowledge of the complexity of gene architecture grows, and we increase our understanding of the subtleties of gene expression, the process of accurately describing disease-causing gene variants has become increasingly problematic. In part, this is due to current reference DNA sequence formats that do not fully meet present needs. Here we present the Locus Reference Genomic (LRG) sequence format, which has been designed for the specific purpose of gene variant reporting. The format builds on the successful National Center for Biotechnology Information (NCBI) RefSeqGene project and provides a single-file record containing a uniquely stable reference DNA sequence along with all relevant transcript and protein sequences essential to the description of gene variants. In principle, LRGs can be created for any organism, not just human. In addition, we recognize the need to respect legacy numbering systems for exons and amino acids and the LRG format takes account of these. We hope that widespread adoption of LRGs - which will be created and maintained by the NCBI and the European Bioinformatics Institute (EBI) - along with consistent use of the Human Genome Variation Society (HGVS)-approved variant nomenclature will reduce errors in the reporting of variants in the literature and improve communication about variants affecting human health. Further information can be found on the LRG web site: http://www.lrg-sequence.org

High-Throughput Detection of Induced Mutations and Natural Variation Using KeyPoint™ Technology

Reverse genetics approaches rely on the detection of sequence alterations in target genes to identify allelic variants among mutant or natural populations. Current (pre-) screening methods such as TILLING and EcoTILLING are based on the detection of single base mismatches in heteroduplexes using endonucleases such as CEL 1. However, there are drawbacks in the use of endonucleases due to their relatively poor cleavage efficiency and exonuclease activity. Moreover, pre-screening methods do not reveal information about the nature of sequence changes and their possible impact on gene function. We present KeyPoint™ technology, a high-throughput mutation/polymorphism discovery technique based on massive parallel sequencing of target genes amplified from mutant or natural populations. KeyPoint combines multi-dimensional pooling of large numbers of individual DNA samples and the use of sample identification tags (“sample barcoding”) with next-generation sequencing technology. We show the power of KeyPoint by identifying two mutants in the tomato eIF4E gene based on screening more than 3000 M2 families in a single GS FLX sequencing run, and discovery of six haplotypes of tomato eIF4E gene by re-sequencing three amplicons in a subset of 92 tomato lines from the EU-SOL core collection. We propose KeyPoint technology as a broadly applicable amplicon sequencing approach to screen mutant populations or germplasm collections for identification of (novel) allelic variation in a high-throughput fashion