Discover hidden splicing variations by mapping personal transcriptomes to personal genomes.

RNA-seq has become a popular technology for studying genetic variation of pre-mRNA alternative splicing. Commonly used RNA-seq aligners rely on the consensus splice site dinucleotide motifs to map reads across splice junctions. Consequently, genomic variants that create novel splice site dinucleotides may produce splice junction RNA-seq reads that cannot be mapped to the reference genome. We developed and evaluated an approach to identify 'hidden' splicing variations in personal transcriptomes, by mapping personal RNA-seq data to personal genomes. Computational analysis and experimental validation indicate that this approach identifies personal specific splice junctions at a low false positive rate. Applying this approach to an RNA-seq data set of 75 individuals, we identified 506 personal specific splice junctions, among which 437 were novel splice junctions not documented in current human transcript annotations. 94 splice junctions had splice site SNPs associated with GWAS signals of human traits and diseases. These involve genes whose splicing variations have been implicated in diseases (such as OAS1), as well as novel associations between alternative splicing and diseases (such as ICA1). Collectively, our work demonstrates that the personal genome approach to RNA-seq read alignment enables the discovery of a large but previously unknown catalog of splicing variations in human populations

Genomic convergence and network analysis approach to identify candidate genes in Alzheimer's disease

BACKGROUND: Alzheimer’s disease (AD) is one of the leading genetically complex and heterogeneous disorder that is influenced by both genetic and environmental factors. The underlying risk factors remain largely unclear for this heterogeneous disorder. In recent years, high throughput methodologies, such as genome-wide linkage analysis (GWL), genome-wide association (GWA) studies, and genome-wide expression profiling (GWE), have led to the identification of several candidate genes associated with AD. However, due to lack of consistency within their findings, an integrative approach is warranted. Here, we have designed a rank based gene prioritization approach involving convergent analysis of multi-dimensional data and protein-protein interaction (PPI) network modelling. RESULTS: Our approach employs integration of three different AD datasets- GWL,GWA and GWE to identify overlapping candidate genes ranked using a novel cumulative rank score (S(R)) based method followed by prioritization using clusters derived from PPI network. S(R) for each gene is calculated by addition of rank assigned to individual gene based on either p value or score in three datasets. This analysis yielded 108 plausible AD genes. Network modelling by creating PPI using proteins encoded by these genes and their direct interactors resulted in a layered network of 640 proteins. Clustering of these proteins further helped us in identifying 6 significant clusters with 7 proteins (EGFR, ACTB, CDC2, IRAK1, APOE, ABCA1 and AMPH) forming the central hub nodes. Functional annotation of 108 genes revealed their role in several biological activities such as neurogenesis, regulation of MAP kinase activity, response to calcium ion, endocytosis paralleling the AD specific attributes. Finally, 3 potential biochemical biomarkers were found from the overlap of 108 AD proteins with proteins from CSF and plasma proteome. EGFR and ACTB were found to be the two most significant AD risk genes. CONCLUSIONS: With the assumption that common genetic signals obtained from different methodological platforms might serve as robust AD risk markers than candidates identified using single dimension approach, here we demonstrated an integrated genomic convergence approach for disease candidate gene prioritization from heterogeneous data sources linked to AD. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2164-15-199) contains supplementary material, which is available to authorized users

HID-1 controls formation of large dense core vesicles by influencing cargo sorting and trans-Golgi network acidification

Large dense core vesicles (LDCVs) mediate the regulated release of neuropeptides and peptide hormones. They form at the trans-Golgi network (TGN), where their soluble content aggregates to form a dense core, but the mechanisms controlling biogenesis are still not completely understood. Recent studies have implicated the peripheral membrane protein HID-1 in neuropeptide sorting and insulin secretion. Using CRISPR/Cas9, we generated HID-1 KO rat neuroendocrine cells, and we show that the absence of HID-1 results in specific defects in peptide hormone and monoamine storage and regulated secretion. Loss of HID-1 causes a reduction in the number of LDCVs and affects their morphology and biochemical properties, due to impaired cargo sorting and dense core formation. HID-1 KO cells also exhibit defects in TGN acidification together with mislocalization of the Golgi-enriched vacuolar H+-ATPase subunit isoform a2. We propose that HID-1 influences early steps in LDCV formation by controlling dense core formation at the TGN.</jats:p

Expression-Based Genome-Wide Association Study Links Vitamin D-Binding Protein With Autoantigenicity in Type 1 Diabetes.

Type 1 diabetes (T1D) is caused by autoreactive T cells that recognize pancreatic islet antigens and destroy insulin-producing β-cells. This attack results from a breakdown in tolerance for self-antigens, which is controlled by ectopic antigen expression in the thymus and pancreatic lymph nodes (PLNs). The autoantigens known to be involved include a set of islet proteins, such as insulin, GAD65, IA-2, and ZnT8. In an attempt to identify additional antigenic proteins, we performed an expression-based genome-wide association study using microarray data from 118 arrays of the thymus and PLNs of T1D mice. We ranked all 16,089 protein-coding genes by the likelihood of finding repeated differential expression and the degree of tissue specificity for pancreatic islets. The top autoantigen candidate was vitamin D-binding protein (VDBP). T-cell proliferation assays showed stronger T-cell reactivity to VDBP compared with control stimulations. Higher levels and frequencies of serum anti-VDBP autoantibodies (VDBP-Abs) were identified in patients with T1D (n = 331) than in healthy control subjects (n = 77). Serum vitamin D levels were negatively correlated with VDBP-Ab levels in patients in whom T1D developed during the winter. Immunohistochemical localization revealed that VDBP was specifically expressed in α-cells of pancreatic islets. We propose that VDBP could be an autoantigen in T1D

Review of the potential health impact of B-casomorphins and related peptides : report of the DATEX working group on B-casomorphins

v2009o

Islet cell cytoplasmic antibody reactivity in midgestational human fetal pancreas

The reactivity of islet cell cytoplasmic antibodies (ICA)-positive and ICA-negative sera of recent onset type 1 diabetic patients was studied in human fetal pancreata of 12-18 weeks' gestation and compared with the reactivity of these sera in adult human control pancreata. The aims of the study were: (1) to observe the presence of ICA staining in human fetal islet cells; (2) to compare endpoint titres (in Juvenile Diabetes Foundation units) of ICA-positive patient sera in fetal pancreata and adult human control pancreata. Ten ICA-positive sera and eight ICA-negative sera from newly diagnosed diabetic patients and four sera from healthy controls were tested on three human adult and eight human fetal pancreata. As in the adult control pancreata. ICA-positive sera reacted to insulin-, glucagon-, and somatostatin-positive cells of fetal pancreata of all gestational ages. This was observed both in single cells and in cells in islet-like cell clusters. Dilution of a reference serum gave similar results in both adult and fetal pancreata. In contrast, the ICA-positive patient sera yielded a striking heterogeneity in fetal as well as in adult pancreata. However, end-point titres between adult and fetal pancreata did not differ significantly (P>0.05). In conclusion, ICA-positive sera from recent onset diabetic patients show that the expression of molecules to which ICA react is present in all islet cells and starts before week 12 of gestation

Flanking p10 contribution and sequence bias in matrix based epitope prediction: revisiting the assumption of independent binding pockets

<p>Abstract</p> <p>Background</p> <p>Eluted natural peptides from major histocompatibility molecules show patterns of conserved residues. Crystallographic structures show that the bound peptide in class II major histocompatibility complex adopts a near uniform polyproline II-like conformation. This way allele-specific favoured residues are able to anchor into pockets in the binding groove leaving other peptide side chains exposed for recognition by T cells. The anchor residues form a motif. This sequence pattern can be used to screen large sequences for potential epitopes. Quantitative matrices extend the motif idea to include the contribution of non-anchor peptide residues. This report examines two new matrices that extend the binding register to incorporate the polymorphic p10 pocket of human leukocyte antigen DR1. Their performance is quantified against experimental binding measurements and against the canonical nine-residue register matrix.</p> <p>Results</p> <p>One new matrix shows significant improvement over the base matrix; the other does not. The new matrices differ in the sequence of the peptide library.</p> <p>Conclusion</p> <p>One of the extended quantitative matrices showed significant improvement in prediction over the original nine residue matrix and over the other extended matrix. Proline in the sequence of the peptide library of the better performing matrix presumably stabilizes the peptide conformation through neighbour interactions. Such interactions may influence epitope prediction in this test of quantitative matrices. This calls into question the assumption of the independent contribution of individual binding pockets.</p

UNC-108/RAB-2 and its effector RIC-19 are involved in dense core vesicle maturation in Caenorhabditis elegans

Uncoordinated movement in Rab2 mutants is caused by impaired retention of cargo on dense core vesicles, not by defective synaptic vesicle release. (Also see the companion article by Edwards et al. in this issue.