A bayesian approach to estimation and testing in time-course microarray experiments

The objective of the present paper is to develop a truly functional Bayesian method specifically designed for time series microarray data. The method allows one to identify differentially expressed genes in a time-course microarray experiment, to rank them and to estimate their expression profiles. Each gene expression profile is modeled as an expansion over some orthonormal basis, where the coefficients and the number of basis functions are estimated from the data. The proposed procedure deals successfully with various technical difficulties that arise in typical microarray experiments such as a small number of observations, non-uniform sampling intervals and missing or replicated data. The procedure allows one to account for various types of errors and offers a good compromise between nonparametric techniques and techniques based on normality assumptions. In addition, all evaluations are performed using analytic expressions, so the entire procedure requires very small computational effort. The procedure is studied using both simulated and real data, and is compared with competitive recent approaches. Finally, the procedure is applied to a case study of a human breast cancer cell line stimulated with estrogen. We succeeded in finding new significant genes that were not marked in an earlier work on the same dataset

A community-based resource for automatic exome variant-calling and annotation in Mendelian disorders

BACKGROUND: Mendelian disorders are mostly caused by single mutations in the DNA sequence of a gene, leading to a phenotype with pathologic consequences. Whole Exome Sequencing of patients can be a cost-effective alternative to standard genetic screenings to find causative mutations of genetic diseases, especially when the number of cases is limited. Analyzing exome sequencing data requires specific expertise, high computational resources and a reference variant database to identify pathogenic variants. RESULTS: We developed a database of variations collected from patients with Mendelian disorders, which is automatically populated thanks to an associated exome-sequencing pipeline. The pipeline is able to automatically identify, annotate and store insertions, deletions and mutations in the database. The resource is freely available online http://exome.tigem.it. The exome sequencing pipeline automates the analysis workflow (quality control and read trimming, mapping on reference genome, post-alignment processing, variation calling and annotation) using state-of-the-art software tools. The exome-sequencing pipeline has been designed to run on a computing cluster in order to analyse several samples simultaneously. The detected variants are annotated by the pipeline not only with the standard variant annotations (e.g. allele frequency in the general population, the predicted effect on gene product activity, etc.) but, more importantly, with allele frequencies across samples progressively collected in the database itself, stratified by Mendelian disorder. CONCLUSIONS: We aim at providing a resource for the genetic disease community to automatically analyse whole exome-sequencing samples with a standard and uniform analysis pipeline, thus collecting variant allele frequencies by disorder. This resource may become a valuable tool to help dissecting the genotype underlying the disease phenotype through an improved selection of putative patient-specific causative or phenotype-associated variations

Time-course analysis of genome-wide gene expression data from hormone-responsive human breast cancer cells

<p>Abstract</p> <p>Background</p> <p>Microarray experiments enable simultaneous measurement of the expression levels of virtually all transcripts present in cells, thereby providing a ‘molecular picture’ of the cell state. On the other hand, the genomic responses to a pharmacological or hormonal stimulus are dynamic molecular processes, where time influences gene activity and expression. The potential use of the statistical analysis of microarray data in time series has not been fully exploited so far, due to the fact that only few methods are available which take into proper account temporal relationships between samples.</p> <p>Results</p> <p>We compared here four different methods to analyze data derived from a time course mRNA expression profiling experiment which consisted in the study of the effects of estrogen on hormone-responsive human breast cancer cells. Gene expression was monitored with the innovative Illumina BeadArray platform, which includes an average of 30-40 replicates for each probe sequence randomly distributed on the chip surface. We present and discuss the results obtained by applying to these datasets different statistical methods for serial gene expression analysis. The influence of the normalization algorithm applied on data and of different parameter or threshold choices for the selection of differentially expressed transcripts has also been evaluated. In most cases, the selection was found fairly robust with respect to changes in parameters and type of normalization. We then identified which genes showed an expression profile significantly affected by the hormonal treatment over time. The final list of differentially expressed genes underwent cluster analysis of functional type, to identify groups of genes with similar regulation dynamics.</p> <p>Conclusions</p> <p>Several methods for processing time series gene expression data are presented, including evaluation of benefits and drawbacks of the different methods applied. The resulting protocol for data analysis was applied to characterization of the gene expression changes induced by estrogen in human breast cancer ZR-75.1 cells over an entire cell cycle.</p

Allelic Expression Imbalance in the Human Retinal Transcriptome and Potential Impact on Inherited Retinal Diseases

Inherited retinal diseases (IRDs) are often associated with variable clinical expressivity (VE) and incomplete penetrance (IP). Underlying mechanisms may include environmental, epigenetic, and genetic factors. Cis-acting expression quantitative trait loci (cis-eQTLs) can be implicated in the regulation of genes by favoring or hampering the expression of one allele over the other. Thus, the presence of such loci elicits allelic expression imbalance (AEI) that can be traced by massive parallel sequencing techniques. In this study, we performed an AEI analysis on RNA-sequencing (RNA-seq) data, from 52 healthy retina donors, that identified 194 imbalanced single nucleotide polymorphisms(SNPs) in 67 IRD genes. Focusing on SNPs displaying AEI at a frequency higher than 10%, we found evidence of AEI in several IRD genes regularly associated with IP and VE (BEST1, RP1, PROM1, and PRPH2). Based on these SNPs commonly undergoing AEI, we performed pyrosequencing in an independent sample set of 17 healthy retina donors in order to confirm our findings. Indeed, we were able to validate CDHR1, BEST1, and PROM1 to be subjected to cis-acting regulation. With this work, we aim to shed light on differentially expressed alleles in the human retina transcriptome that, in the context of autosomal dominant IRD cases, could help to explain IP or VE.Peer reviewe

Epigenetic alteration of microRNAs in DNMT3B-mutated patients of ICF syndrome

Immunodeficiency, Centromeric region instability, Facial anomalies (ICF; OMIM #242860) syndrome, due to mutations in the DNMT3B gene, is characterized by inheritance of aberrant patterns of DNA methylation and heterochromatin defects. Patients show variable agammaglobulinemia and a reduced number of T cells, making them prone to infections and death before adulthood. Other variable symptoms include facial dysmorphism, growth and mental retardation. Despite the recent advances in identifying the dysregulated genes, the molecular mechanisms, which underlie the altered gene expression causing ICF phenotype complexity, are not well understood. Held the recently-shown tight correlation between epigenetics and microRNAs (miRNAs), we searched for miRNAs regulated by DNMT3B activity, comparing cell lines from ICF patients with those from healthy individuals. We observe that eighty-nine miRNAs, some of which involved in immune function, development and neurogenesis, are dysregulated in ICF (LCLs) compared to wild-type cells. Significant DNA hypomethylation of miRNA CpG islands was not observed in cases of miRNA up-regulation in ICF cells, suggesting a more subtle effect of DNMT3B deficiency on their regulation; however, a modification of histone marks, especially H3K27 and H3K4 trimethylation, and H4 acetylation, was observed concomitantly with changes in microRNA expression. Functional correlation between miRNA and mRNA expression of their targets allow us to suppose a regulation either at mRNA level or at protein level. These results provide a better understanding of how DNA methylation and histone code interact to regulate the class of microRNA genes and enable us to predict molecular events possibly contributing to ICF condition

Triple Vectors Expand AAV Transfer Capacity in the Retina.

Retinal gene transfer with adeno-associated viral (AAV) vectors holds great promise for the treatment of inherited retinal degenerations (IRDs). One limit of AAV is its transfer capacity of about 5 kb, which can be expanded to about 9 kb, using dual AAV vectors. This strategy would still not suffice for treatment of IRDs such as Usher syndrome type 1D or Alström syndrome type I (ALMS) due to mutations in CDH23 or ALMS1, respectively. To overcome this limitation, we generated triple AAV vectors, with a maximal transfer capacity of about 14 kb. Transcriptomic analysis following triple AAV transduction showed the expected full-length products along a number of aberrant transcripts. However, only the full-length transcripts are efficiently translated in vivo. We additionally showed that approximately 4% of mouse photoreceptors are transduced by triple AAV vectors and showed correct localization of recombinant ALMS1. The low-photoreceptor transduction levels might justify the modest and transient improvement we observe in the retina of a mouse model of ALMS. However, the levels of transduction mediated by triple AAV vectors in pig retina reached 40% of those observed with single vectors, and this bodes well for further improving the efficiency of triple AAV vectors in the retina. Mol Ther 2018 Feb 7 26(2):524-541

YAP contributes to DNA methylation remodeling upon mouse embryonic stem cell differentiation

The Yes-associated protein YAP, one of the major effectors of the Hippo pathway together with its related protein TAZ, mediates a range of cellular processes from proliferation and death to morphogenesis. YAP and TAZ regulate a large number of target genes, acting as co-activators of DNA-binding transcription factors or as negative regulators of transcription by interacting with the nucleosome remodeling and histone deacetylase complexes. YAP is expressed in self-renewing embryonic stem cells (ESCs), although it is still debated whether it plays any crucial roles in the control of either stemness or differentiation. Here we show that the transient downregulation of YAP in mouse ESCs perturbs cellular homeostasis, leading to the inability to differentiate properly. Bisulfite genomic sequencing revealed that this transient knockdown caused a genome-wide alteration of the DNA methylation remodeling that takes place during the early steps of differentiation, suggesting that the phenotype we observed might be due to the dysregulation of some of the mechanisms involved in regulation of ESC exit from pluripotency. By gene expression analysis we identified two molecules which could have a role in the altered genome-wide methylation profile: the long non-coding RNA Ephemeron, whose rapid upregulation is crucial for ESCs transition into epiblast, and the methyltransferase-like protein Dnmt3l, which, during the embryo development, cooperates with Dnmt3a and Dnmt3b to contribute to the de novo DNA methylation that governs early steps of ESC differentiation. These data suggest a new role for YAP in the governance of the epigenetic dynamics of exit from pluripotency

BATS: a Bayesian user-friendly software for Analyzing Time Series microarray experiments

BATS is a user-friendly software for Bayesian Analysis of Time Series microarray experiments based on the novel, truly functional and fully Bayesian approach proposed in Angelini et at. (2006). The software is specifically designed for time series data. It allows an user to automatically identify and rank differentially expressed genes and to estimate their expression profiles. BATS successfully manages various technical difficulties which arise in microarray time-course experiments, such as a small number of observations, non-uniform sampling intervals, and presence of missing or multiple data. BATS can carry out analysis with both simulated and real experimental data. It also handles data from different platforms. 1 Availability: BATS is written in Matlab and executable in Windows (Macintosh and Linux version are currently under development). It is freely available upon request from the authors.

Myopalladin promotes muscle growth through modulation of the serum response factor pathway

Myopalladin (MYPN) is a striated muscle-specific, immunoglobulin-containing protein located in the Z-line and I-band of the sarcomere as well as the nucleus. Heterozygous MYPN gene mutations are associated with hypertrophic, dilated, and restrictive cardiomyopathy, and homozygous loss-of-function truncating mutations have recently been identified in patients with cap myopathy, nemaline myopathy, and congenital myopathy with hanging big toe

Massive-Scale RNA-Seq Analysis of Non Ribosomal Transcriptome in Human Trisomy 21

Hybridization- and tag-based technologies have been successfully used in Down syndrome to identify genes involved in various aspects of the pathogenesis. However, these technologies suffer from several limits and drawbacks and, to date, information about rare, even though relevant, RNA species such as long and small non-coding RNAs, is completely missing. Indeed, none of published works has still described the whole transcriptional landscape of Down syndrome. Although the recent advances in high-throughput RNA sequencing have revealed the complexity of transcriptomes, most of them rely on polyA enrichment protocols, able to detect only a small fraction of total RNA content. On the opposite end, massive-scale RNA sequencing on rRNA-depleted samples allows the survey of the complete set of coding and non-coding RNA species, now emerging as novel contributors to pathogenic mechanisms. Hence, in this work we analysed for the first time the complete transcriptome of human trisomic endothelial progenitor cells to an unprecedented level of resolution and sensitivity by RNA-sequencing. Our analysis allowed us to detect differential expression of even low expressed genes crucial for the pathogenesis, to disclose novel regions of active transcription outside yet annotated loci, and to investigate a plethora of non-polyadenilated long as well as short non coding RNAs. Novel splice isoforms for a large subset of crucial genes, and novel extended untranslated regions for known genes—possibly novel miRNA targets or regulatory sites for gene transcription—were also identified in this study. Coupling the rRNA depletion of samples, followed by high-throughput RNA-sequencing, to the easy availability of these cells renders this approach very feasible for transcriptome studies, offering the possibility of investigating in-depth blood-related pathological features of Down syndrome, as well as other genetic disorders