LINE-1 Mediated Insertion into Poc1a (Protein of Centriole 1 A) Causes Growth Insufficiency and Male Infertility in Mice.

Skeletal dysplasias are a common, genetically heterogeneous cause of short stature that can result from disruptions in many cellular processes. We report the identification of the lesion responsible for skeletal dysplasia and male infertility in the spontaneous, recessive mouse mutant chagun. We determined that Poc1a, encoding protein of the centriole 1a, is disrupted by the insertion of a processed Cenpw cDNA, which is flanked by target site duplications, suggestive of a LINE-1 retrotransposon-mediated event. Mutant fibroblasts have impaired cilia formation and multipolar spindles. Male infertility is caused by defective spermatogenesis early in meiosis and progressive germ cell loss. Spermatogonial stem cell transplantation studies revealed that Poc1a is essential for normal function of both Sertoli cells and germ cells. The proliferative zone of the growth plate is small and disorganized because chondrocytes fail to re-align after cell division and undergo increased apoptosis. Poc1a and several other genes associated with centrosome function can affect the skeleton and lead to skeletal dysplasias and primordial dwarfisms. This mouse mutant reveals how centrosome dysfunction contributes to defects in skeletal growth and male infertility.

CD1d-unrestricted NKT cells are endowed with a hybrid function far superior than that of iNKT cells.

Invariant natural killer T (iNKT) cells to date represent the best example of cells known to have a hybrid function, representing both innate and adaptive immunity. Shared phenotypic similarities with NK cells together with a rapid response to a cytokine stimulus and a productive TCR engagement are the features that underline the hybrid nature of iNKT cells. Using these criteria, we provide molecular and functional evidence demonstrating that CD1d-independent (CD1d(ind)) NKT cells, a population of CD1d-unrestricted NKT cells, are endowed with a hybrid function far superior to that of iNKT cells: (i) an extensive shared program with NK cells, (ii) a closer Euclidian distance with NK cells, and (iii) the ability to respond to innate stimuli (Poly:IC) with cytotoxic potential in the same manner as NK cells identify a hybrid feature in CD1d(ind)NKT cells that truly fulfills the dual function of an NK and a T cell. Our finding that CD1d(ind)NKT cells are programmed to act like NK cells in response to innate signals while being capable of adaptive responses is unprecedented, and thus might reemphasize CD1d-unrestricted NKT cells as a subset of lymphocytes that could affect biological processes of antimicrobial and tumor immunity in a unique way.

Novel bioinformatics method for identification of genome-wide non-canonical spliced regions using RNA-Seq data.

SETTING: During endoplasmic reticulum (ER) stress, the endoribonuclease (RNase) Ire1α initiates removal of a 26 nt region from the mRNA encoding the transcription factor Xbp1 via an unconventional mechanism (atypically within the cytosol). This causes an open reading frame-shift that leads to altered transcriptional regulation of numerous downstream genes in response to ER stress as part of the unfolded protein response (UPR). Strikingly, other examples of targeted, unconventional splicing of short mRNA regions have yet to be reported. OBJECTIVE: Our goal was to develop an approach to identify non-canonical, possibly very short, splicing regions using RNA-Seq data and apply it to ER stress-induced Ire1α heterozygous and knockout mouse embryonic fibroblast (MEF) cell lines to identify additional Ire1α targets. RESULTS: We developed a bioinformatics approach called the Read-Split-Walk (RSW) pipeline, and evaluated it using two Ire1α heterozygous and two Ire1α-null samples. The 26 nt non-canonical splice site in Xbp1 was detected as the top hit by our RSW pipeline in heterozygous samples but not in the negative control Ire1α knockout samples. We compared the Xbp1 results from our approach with results using the alignment program BWA, Bowtie2, STAR, Exonerate and the Unix "grep" command. We then applied our RSW pipeline to RNA-Seq data from the SKBR3 human breast cancer cell line. RSW reported a large number of non-canonical spliced regions for 108 genes in chromosome 17, which were identified by an independent study. CONCLUSIONS: We conclude that our RSW pipeline is a practical approach for identifying non-canonical splice junction sites on a genome-wide level. We demonstrate that our pipeline can detect novel splice sites in RNA-Seq data generated under similar conditions for multiple species, in our case mouse and human.

A bioinformatics approach reveals novel interactions of the OVOL transcription factors in the regulation of epithelial - mesenchymal cell reprogramming and cancer progression.

BACKGROUND: Mesenchymal to Epithelial Transition (MET) plasticity is critical to cancer progression, and we recently showed that the OVOL transcription factors (TFs) are critical regulators of MET. Results of that work also posed the hypothesis that the OVOLs impact MET in a range of cancers. We now test this hypothesis by developing a model, OVOL Induced MET (OI-MET), and sub-model (OI-MET-TF), to characterize differential gene expression in MET common to prostate cancer (PC) and breast cancer (BC). RESULTS: In the OI-MET model, we identified 739 genes differentially expressed in both the PC and BC models. For this gene set, we found significant enrichment of annotation for BC, PC, cancer, and MET, as well as regulation of gene expression by AP1, STAT1, STAT3, and NFKB1. Focusing on the target genes for these four TFs plus the OVOLs, we produced the OI-MET-TF sub-model, which shows even greater enrichment for these annotations, plus significant evidence of cooperation among these five TFs. Based on known gene/drug interactions, we prioritized targets in the OI-MET-TF network for follow-on analysis, emphasizing the clinical relevance of this work. Reflecting these results back to the OI-MET model, we found that binding motifs for the TF pair AP1/MYC are more frequent than expected and that the AP1/MYC pair is significantly enriched in binding in cancer models, relative to non-cancer models, in these promoters. This effect is seen in both MET models (solid tumors) and in non-MET models (leukemia). These results are consistent with our hypothesis that the OVOLs impact cancer susceptibility by regulating MET, and extend the hypothesis to include mechanisms not specific to MET. CONCLUSIONS: We find significant evidence of the OVOL, AP1, STAT1, STAT3, and NFKB1 TFs having important roles in MET, and more broadly in cancer. We prioritize known gene/drug targets for follow-up in the clinic, and we show that the AP1/MYC TF pair is a strong candidate for intervention.

Convergence of genetic influences in comorbidity.

BACKGROUND: Predisposition to complex diseases is explained in part by genetic variation, and complex diseases are frequently comorbid, consistent with pleiotropic genetic variation influencing comorbidity. Genome Wide Association (GWA) studies typically assess association between SNPs and a single-disease phenotype. Fisher meta-analysis combines evidence of association from single-disease GWA studies, assuming that each study is an independent test of the same hypothesis. The Rank Product (RP) method overcomes limitations posed by Fisher assumptions, though RP was not designed for GWA data. METHODS: We modified RP to accommodate GWA data, and we call it modRP. Using p-values output from GWA studies, we aggregate evidence for association between SNPs and related phenotypes. To assess significance, RP randomly samples the observed ranks to develop the null distribution of the RP statistic, and then places the observed RPs into the null distribution. ModRP eliminates the effect of linkage disequilibrium and controls for differences in power at tested SNPs, to meet RP assumptions in application to GWA data. RESULTS: After validating modRP based on both positive and negative control studies, we searched for pleiotropic influences on comorbid substance use disorders in a novel study, and found two SNPs to be significantly associated with comorbid cocaine, opium, and nicotine dependence. Placing these SNPs into biological context, we developed a protein network modeling the interaction of cocaine, nicotine, and opium with these variants. CONCLUSIONS: ModRP is a novel approach to identifying pleiotropic genetic influences on comorbid complex diseases. It can be used to assess association for related phenotypes where raw data is unavailable or inappropriate for analysis using other approaches. The method is conceptually simple and produces statistically significant, biologically relevant results.

Decade-long bacterial community dynamics in cystic fibrosis airways.

The structure and dynamics of bacterial communities in the airways of persons with cystic fibrosis (CF) remain largely unknown. We characterized the bacterial communities in 126 sputum samples representing serial collections spanning 8-9 y from six age-matched male CF patients. Sputum DNA was analyzed by bar-coded pyrosequencing of the V3-V5 hypervariable region of the 16S rRNA gene, defining 662 operational taxonomic units (OTUs) from >633,000 sequences. Bacterial community diversity decreased significantly over time in patients with typically progressive lung disease but remained relatively stable in patients with a mild lung disease phenotype. Antibiotic use, rather than patient age or lung function, was the primary driver of decreasing diversity. Interpatient variability in community structure exceeded intrapatient variability in serial samples. Antibiotic treatment was associated with pronounced shifts in community structure, but communities showed both short- and long-term resilience after antibiotic perturbation. There was a positive correlation between OTU occurrence and relative abundance, with a small number of persistent OTUs accounting for the greatest abundance. Significant changes in community structure, diversity, or total bacterial density at the time of pulmonary exacerbation were not observed. Despite decreasing community diversity in patients with progressive disease, total bacterial density remained relatively stable over time. These findings show the critical relationship between airway bacterial community structure, disease stage, and clinical state at the time of sample collection. These features are the key parameters with which to assess the complex ecology of the CF airway.

The NIH National Center for Integrative Biomedical Informatics (NCIBI).

The National Center for Integrative and Biomedical Informatics (NCIBI) is one of the eight NCBCs. NCIBI supports information access and data analysis for biomedical researchers, enabling them to build computational and knowledge models of biological systems to address the Driving Biological Problems (DBPs). The NCIBI DBPs have included prostate cancer progression, organ-specific complications of type 1 and 2 diabetes, bipolar disorder, and metabolic analysis of obesity syndrome. Collaborating with these and other partners, NCIBI has developed a series of software tools for exploratory analysis, concept visualization, and literature searches, as well as core database and web services resources. Many of our training and outreach initiatives have been in collaboration with the Research Centers at Minority Institutions (RCMI), integrating NCIBI and RCMI faculty and students, culminating each year in an annual workshop. Our future directions include focusing on the TranSMART data sharing and analysis initiative.

Candidate exome capture identifies mutation of SDCCAG8 as the cause of a retinal-renal ciliopathy.

Nephronophthisis-related ciliopathies (NPHP-RC) are recessive disorders that feature dysplasia or degeneration occurring preferentially in the kidney, retina and cerebellum. Here we combined homozygosity mapping with candidate gene analysis by performing 'ciliopathy candidate exome capture' followed by massively parallel sequencing. We identified 12 different truncating mutations of SDCCAG8 (serologically defined colon cancer antigen 8, also known as CCCAP) in 10 families affected by NPHP-RC. We show that SDCCAG8 is localized at both centrioles and interacts directly with OFD1 (oral-facial-digital syndrome 1), which is associated with NPHP-RC. Depletion of sdccag8 causes kidney cysts and a body axis defect in zebrafish and induces cell polarity defects in three-dimensional renal cell cultures. This work identifies loss of SDCCAG8 function as a cause of a retinal-renal ciliopathy and validates exome capture analysis for broadly heterogeneous single-gene disorders.

Modeling complex genetic and environmental influences on comorbid bipolar disorder with tobacco use disorder.

BACKGROUND: Comorbidity of psychiatric and substance use disorders represents a significant complication in the clinical course of both disorders. Bipolar Disorder (BD) is a psychiatric disorder characterized by severe mood swings, ranging from mania to depression, and up to a 70% rate of comorbid Tobacco Use Disorder (TUD). We found epidemiological evidence consistent with a common underlying etiology for BD and TUD, as well as evidence of both genetic and environmental influences on BD and TUD. Therefore, we hypothesized a common underlying genetic etiology, interacting with nicotine exposure, influencing susceptibility to both BD and TUD. METHODS: Using meta-analysis, we compared TUD rates for BD patients and the general population. We identified candidate genes showing statistically significant, replicated, evidence of association with both BD and TUD. We assessed commonality among these candidate genes and hypothesized broader, multi-gene network influences on the comorbidity. Using Fisher Exact tests we tested our hypothesized genetic networks for association with the comorbidity, then compared the inferences drawn with those derived from the commonality assessment. Finally, we prioritized candidate SNPs for validation. RESULTS: We estimate risk for TUD among BD patients at 2.4 times that of the general population. We found three candidate genes associated with both BD and TUD (COMT, SLC6A3, and SLC6A4) and commonality analysis suggests that these genes interact in predisposing psychiatric and substance use disorders. We identified a 69 gene network that influences neurotransmitter signaling and shows significant over-representation of genes associated with BD and TUD, as well as genes differentially expressed with exposure to tobacco smoke. Twenty four of these genes are known drug targets. CONCLUSIONS: This work highlights novel bioinformatics resources and demonstrates the effectiveness of using an integrated bioinformatics approach to improve our understanding of complex disease etiology. We illustrate the development and testing of hypotheses for a comorbidity predisposed by both genetic and environmental influences. Consistent with our hypothesis, the selected network models multiple interacting genetic influences on comorbid BD with TUD, as well as the environmental influence of nicotine. This network nominates candidate genes for validation and drug testing, and we offer a panel of SNPs prioritized for follow-up.