Lorena Pantano

A myriad of miRNA variants in control and Huntington’s disease brain regions detected by massively parallel sequencing

Huntington disease (HD) is a neurodegenerative disorder that predominantly affects neurons of the forebrain. We have applied the Illumina massively parallel sequencing to deeply analyze the small RNA populations of two different forebrain areas, the frontal cortex (FC) and the striatum (ST) of healthy individuals and individuals with HD. More than 80% of the small-RNAs were annotated as microRNAs (miRNAs) in all samples. Deep sequencing revealed length and sequence heterogeneity (IsomiRs) for the vast majority of miRNAs. Around 80–90% of the miRNAs presented modifications in the 3′-terminus mainly in the form of trimming and/or as nucleotide addition variants, while the 5′-terminus of the miRNAs was specially protected from changes. Expression profiling showed strong miRNA and isomiR expression deregulation in HD, most being common to both FC and ST. The analysis of the upstream regulatory regions in co-regulated miRNAs suggests a role for RE1-Silencing Transcription Factor (REST) and P53 in miRNAs downregulation in HD. The putative targets of deregulated miRNAs and seed-region IsomiRs strongly suggest that their altered expression contributes to the aberrant gene expression in HD. Our results show that miRNA variability is a ubiquitous phenomenon in the adult human brain, which may influence gene expression in physiological and pathological conditions.

Genome assembly comparison identifies structural variants in the human genome

Numerous types of DNA variation exist, ranging from SNPs to larger structural alterations such as copy number variants (CNVs) and inversions. Alignment of DNA sequence from different sources has been used to identify SNPs and intermediate-sized variants (ISVs). However, only a small proportion of total heterogeneity is characterized, and little is known of the characteristics of most smaller-sized (<50 kb) variants. Here we show that genome assembly comparison is a robust approach for identification of all classes of genetic variation. Through comparison of two human assemblies (Celeras R27c compilation and the Build 35 reference sequence), we identified megabases of sequence (in the form of 13,534 putative non-SNP events) that were absent, inverted or polymorphic in one assembly. Database comparison and laboratory experimentation further demonstrated overlap or validation for 240 variable regions and confirmed >1.5 million SNPs. Some differences were simple insertions and deletions, but in regions containing CNVs, segmental duplication and repetitive DNA, they were more complex. Our results uncover substantial undescribed variation in humans, highlighting the need for comprehensive annotation strategies to fully interpret genome scanning and personalized sequencing projects.

A pathogenic mechanism in Huntington's disease involves small CAG-repeated RNAs with neurotoxic activity.

Huntingtons disease (HD) is an autosomal dominantly inherited disorder caused by the expansion of CAG repeats in the Huntingtin (HTT) gene. The abnormally extended polyglutamine in the HTT protein encoded by the CAG repeats has toxic effects. Here, we provide evidence to support that the mutant HTT CAG repeats interfere with cell viability at the RNA level. In human neuronal cells, expanded HTT exon-1 mRNA with CAG repeat lengths above the threshold for complete penetrance (40 or greater) induced cell death and increased levels of small CAG-repeated RNAs (sCAGs), of ≈21 nucleotides in a Dicer-dependent manner. The severity of the toxic effect of HTT mRNA and sCAG generation correlated with CAG expansion length. Small RNAs obtained from cells expressing mutant HTT and from HD human brains significantly decreased neuronal viability, in an Ago2-dependent mechanism. In both cases, the use of anti-miRs specific for sCAGs efficiently blocked the toxic effect, supporting a key role of sCAGs in HTT-mediated toxicity. Luciferase-reporter assays showed that expanded HTT silences the expression of CTG-containing genes that are down-regulated in HD. These results suggest a possible link between HD and sCAG expression with an aberrant activation of the siRNA/miRNA gene silencing machinery, which may trigger a detrimental response. The identification of the specific cellular processes affected by sCAGs may provide insights into the pathogenic mechanisms underlying HD, offering opportunities to develop new therapeutic approaches.

SeqBuster, a bioinformatic tool for the processing and analysis of small RNAs datasets, reveals ubiquitous miRNA modifications in human embryonic cells

High-throughput sequencing technologies enable direct approaches to catalog and analyze snapshots of the total small RNA content of living cells. Characterization of high-throughput sequencing data requires bioinformatic tools offering a wide perspective of the small RNA transcriptome. Here we present SeqBuster, a highly versatile and reliable web-based toolkit to process and analyze large-scale small RNA datasets. The high flexibility of this tool is illustrated by the multiple choices offered in the pre-analysis for mapping purposes and in the different analysis modules for data manipulation. To overcome the storage capacity limitations of the web-based tool, SeqBuster offers a stand-alone version that permits the annotation against any custom database. SeqBuster integrates multiple analyses modules in a unique platform and constitutes the first bioinformatic tool offering a deep characterization of miRNA variants (isomiRs). The application of SeqBuster to small-RNA datasets of human embryonic stem cells revealed that most miRNAs present different types of isomiRs, some of them being associated to stem cell differentiation. The exhaustive description of the isomiRs provided by SeqBuster could help to identify miRNA-variants that are relevant in physiological and pathological processes. SeqBuster is available at http://estivill_lab.crg.es/seqbuster.

Fibroblast‐Derived Induced Pluripotent Stem Cells Show No Common Retroviral Vector Insertions

Several laboratories have reported the reprogramming of mouse and human fibroblasts into pluripotent cells, using retroviruses carrying the Oct4, Sox2, Klf4, and c‐Myc transcription factor genes. In these experiments the frequency of reprogramming was lower than 0.1% of the infected cells, raising the possibility that additional events are required to induce reprogramming, such as activation of genes triggered by retroviral insertions. We have therefore determined by ligation‐mediated polymerase chain reaction (LM‐PCR) the retroviral insertion sites in six induced pluripotent stem (iPS) cell clones derived from mouse fibroblasts. Seventy‐nine insertion sites were assigned to a single mouse genome location. Thirty‐five of these mapped to gene transcription units, whereas 29 insertions landed within 10 kilobases of transcription start sites. No common insertion site was detected among the iPS clones studied. Moreover, bioinformatics analyses revealed no enrichment of a specific gene function, network, or pathway among genes targeted by retroviral insertions. We conclude that Oct4, Sox2, Klf4, and c‐Myc are sufficient to promote fibroblast‐to‐iPS cell reprogramming and propose that the observed low reprogramming frequencies may have alternative explanations. STEM CELLS 2009;27:300–306

A highly expressed miR-101 isomiR is a functional silencing small RNA

BackgroundMicroRNAs (miRNAs) are short non-coding regulatory RNAs that control gene expression usually producing translational repression and gene silencing. High-throughput sequencing technologies have revealed heterogeneity at length and sequence level for the majority of mature miRNAs (IsomiRs). Most isomiRs can be explained by variability in either Dicer1 or Drosha cleavage during miRNA biogenesis at 5’ or 3’ of the miRNA (trimming variants). Although isomiRs have been described in different tissues and organisms, their functional validation as modulators of gene expression remains elusive. Here we have characterized the expression and function of a highly abundant miR-101 5’-trimming variant (5’-isomiR-101).ResultsThe analysis of small RNA sequencing data in several human tissues and cell lines indicates that 5’-isomiR-101 is ubiquitously detected and a highly abundant, especially in the brain. 5’-isomiR-101 was found in Ago-2 immunocomplexes and complementary approaches showed that 5’-isomiR-101 interacted with different members of the silencing (RISC) complex. In addition, 5’-isomiR-101 decreased the expression of five validated miR-101 targets, suggesting that it is a functional variant. Both the binding to RISC members and the degree of silencing were less efficient for 5’-isomiR-101 compared with miR-101. For some targets, both miR-101 and 5’-isomiR-101 significantly decreased protein expression with no changes in the respective mRNA levels. Although a high number of overlapping predicted targets suggest similar targeted biological pathways, a correlation analysis of the expression profiles of miR-101 variants and predicted mRNA targets in human brains at different ages, suggest specific functions for miR-101- and 5’-isomiR-101.ConclusionsThese results suggest that isomiRs are functional variants and further indicate that for a given miRNA, the different isomiRs may contribute to the overall effect as quantitative and qualitative fine-tuners of gene expression.

Microarray and deep sequencing cross-platform analysis of the mirRNome and isomiR variation in response to epidermal growth factor

BackgroundEpidermal Growth Factor (EGF) plays an important function in the regulation of cell growth, proliferation, and differentiation by binding to its receptor (EGFR) and providing cancer cells with increased survival responsiveness. Signal transduction carried out by EGF has been extensively studied at both transcriptional and post-transcriptional levels. Little is known about the involvement of microRNAs (miRNAs) in the EGF signaling pathway. miRNAs have emerged as major players in the complex networks of gene regulation, and cancer miRNA expression studies have evidenced a direct involvement of miRNAs in cancer progression.ResultsIn this study, we have used an integrative high content analysis approach to identify the specific miRNAs implicated in EGF signaling in HeLa cells as potential mediators of cancer mediated functions. We have used microarray and deep-sequencing technologies in order to obtain a global view of the EGF miRNA transcriptome with a robust experimental cross-validation. By applying a procedure based on Rankprod tests, we have delimited a solid set of EGF-regulated miRNAs. After validating regulated miRNAs by reverse transcription quantitative PCR, we have derived protein networks and biological functions from the predicted targets of the regulated miRNAs to gain insight into the potential role of miRNAs in EGF-treated cells. In addition, we have analyzed sequence heterogeneity due to editing relative to the reference sequence (isomiRs) among regulated miRNAs.ConclusionsWe propose that the use of global genomic miRNA cross-validation derived from high throughput technologies can be used to generate more reliable datasets inferring more robust networks of co-regulated predicted miRNA target genes.

Identification of Copy Number Variants Defining Genomic Differences among Major Human Groups

Background Understanding the genetic contribution to phenotype variation of human groups is necessary to elucidate differences in disease predisposition and response to pharmaceutical treatments in different human populations. Methodology/Principal Findings We have investigated the genome-wide profile of structural variation on pooled samples from the three populations studied in the HapMap project by comparative genome hybridization (CGH) in different array platforms. We have identified and experimentally validated 33 genomic loci that show significant copy number differences from one population to the other. Interestingly, we found an enrichment of genes related to environment adaptation (immune response, lipid metabolism and extracellular space) within these regions and the study of expression data revealed that more than half of the copy number variants (CNVs) translate into gene-expression differences among populations, suggesting that they could have functional consequences. In addition, the identification of single nucleotide polymorphisms (SNPs) that are in linkage disequilibrium with the copy number alleles allowed us to detect evidences of population differentiation and recent selection at the nucleotide variation level. Conclusions Overall, our results provide a comprehensive view of relevant copy number changes that might play a role in phenotypic differences among major human populations, and generate a list of interesting candidates for future studies.

A non-biased framework for the annotation and classification of the non-miRNA small RNA transcriptome

MOTIVATION Recent progress in high-throughput sequencing technologies has largely contributed to reveal a highly complex landscape of small non-coding RNAs (sRNAs), including novel non-canonical sRNAs derived from long non-coding RNA, repeated elements, transcription start sites and splicing site regions among others. The published frameworks for sRNA data analysis are focused on miRNA detection and prediction, ignoring further information in the dataset. As a consequence, tools for the identification and classification of the sRNAs not belonging to miRNA family are currently lacking. RESULTS Here, we present, SeqCluster, an extension of the currently available SeqBuster tool to identify and analyze at different levels the sRNAs not annotated or predicted as miRNAs. This new module deals with sequences mapping onto multiple locations and permits a highly versatile and user-friendly interaction with the data in order to easily classify sRNA sequences with a putative functional importance. We were able to detect all known classes of sRNAs described to date using SeqCluster with different sRNA datasets.

ProSeeK: A web server for MLPA probe design

BackgroundThe technological evolution of platforms for detecting genome-wide copy number imbalances has allowed the discovery of an unexpected amount of human sequence that is variable in copy number among individuals. This type of human variation can make an important contribution to human diversity and disease susceptibility. Multiplex Ligation-dependent Probe Amplification (MLPA) is a targeted method to assess copy number differences for up to 40 genomic loci in one single experiment. Although specific MLPA assays can be ordered from MRC-Holland (the proprietary company of the MLPA technology), custom designs are also developed in many laboratories worldwide. After our own experience, an important drawback of custom MLPA assays is the time spent during the design of the specific oligonucleotides that are used as probes. Due to the large number of probes included in a single assay, a number of restrictions need to be met in order to maximize specificity and to increase success likelihood.ResultsWe have developed a web tool for facilitating and optimising custom probe design for MLPA experiments. The algorithm only requires the target sequence in FASTA format and a set of parameters, that are provided by the user according to each specific MLPA assay, to identify the best probes inside the given region.ConclusionTo our knowledge, this is the first available tool for optimizing custom probe design of MLPA assays. The ease-of-use and speed of the algorithm dramatically reduces the turn around time of probe design. ProSeeK will become a useful tool for all laboratories that are currently using MLPA in their research projects for CNV studies.