3,919 research outputs found
Genome-Wide Survey of MicroRNA - Transcription Factor Feed-Forward Regulatory Circuits in Human
In this work, we describe a computational framework for the genome-wide
identification and characterization of mixed
transcriptional/post-transcriptional regulatory circuits in humans. We
concentrated in particular on feed-forward loops (FFL), in which a master
transcription factor regulates a microRNA, and together with it, a set of joint
target protein coding genes. The circuits were assembled with a two step
procedure. We first constructed separately the transcriptional and
post-transcriptional components of the human regulatory network by looking for
conserved over-represented motifs in human and mouse promoters, and 3'-UTRs.
Then, we combined the two subnetworks looking for mixed feed-forward regulatory
interactions, finding a total of 638 putative (merged) FFLs. In order to
investigate their biological relevance, we filtered these circuits using three
selection criteria: (I) GeneOntology enrichment among the joint targets of the
FFL, (II) independent computational evidence for the regulatory interactions of
the FFL, extracted from external databases, and (III) relevance of the FFL in
cancer. Most of the selected FFLs seem to be involved in various aspects of
organism development and differentiation. We finally discuss a few of the most
interesting cases in detail.Comment: 51 pages, 5 figures, 4 tables. Supporting information included.
Accepted for publication in Molecular BioSystem
Assessing the Gene Content of the Megagenome: Sugar Pine (Pinus lambertiana).
Sugar pine (Pinus lambertiana Douglas) is within the subgenus Strobus with an estimated genome size of 31 Gbp. Transcriptomic resources are of particular interest in conifers due to the challenges presented in their megagenomes for gene identification. In this study, we present the first comprehensive survey of the P. lambertiana transcriptome through deep sequencing of a variety of tissue types to generate more than 2.5 billion short reads. Third generation, long reads generated through PacBio Iso-Seq have been included for the first time in conifers to combat the challenges associated with de novo transcriptome assembly. A technology comparison is provided here to contribute to the otherwise scarce comparisons of second and third generation transcriptome sequencing approaches in plant species. In addition, the transcriptome reference was essential for gene model identification and quality assessment in the parallel project responsible for sequencing and assembly of the entire genome. In this study, the transcriptomic data were also used to address questions surrounding lineage-specific Dicer-like proteins in conifers. These proteins play a role in the control of transposable element proliferation and the related genome expansion in conifers
One Decade of Development and Evolution of MicroRNA Target Prediction Algorithms
Nearly two decades have passed since the publication of the first study reporting the discovery of microRNAs (miRNAs). The key role of miRNAs in post-transcriptional gene regulation led to the performance of an increasing number of studies focusing on origins, mechanisms of action and functionality of miRNAs. In order to associate each miRNA to a specific functionality it is essential to unveil the rules that govern miRNA action. Despite the fact that there has been significant improvement exposing structural characteristics of the miRNA-mRNA interaction, the entire physical mechanism is not yet fully understood. In this respect, the development of computational algorithms for miRNA target prediction becomes increasingly important. This manuscript summarizes the research done on miRNA target prediction. It describes the experimental data currently available and used in the field and presents three lines of computational approaches for target prediction. Finally, the authors put forward a number of considerations regarding current challenges and future direction
Pairwise gene GO-based measures for biclustering of high-dimensional expression data
Background: Biclustering algorithms search for groups of genes that share the same
behavior under a subset of samples in gene expression data. Nowadays, the biological
knowledge available in public repositories can be used to drive these algorithms to
find biclusters composed of groups of genes functionally coherent. On the other hand,
a distance among genes can be defined according to their information stored in Gene
Ontology (GO). Gene pairwise GO semantic similarity measures report a value for each
pair of genes which establishes their functional similarity. A scatter search-based
algorithm that optimizes a merit function that integrates GO information is studied in
this paper. This merit function uses a term that addresses the information through a GO
measure.
Results: The effect of two possible different gene pairwise GO measures on the
performance of the algorithm is analyzed. Firstly, three well known yeast datasets with
approximately one thousand of genes are studied. Secondly, a group of human
datasets related to clinical data of cancer is also explored by the algorithm. Most of
these data are high-dimensional datasets composed of a huge number of genes. The
resultant biclusters reveal groups of genes linked by a same functionality when the
search procedure is driven by one of the proposed GO measures. Furthermore, a
qualitative biological study of a group of biclusters show their relevance from a cancer
disease perspective.
Conclusions: It can be concluded that the integration of biological information
improves the performance of the biclustering process. The two different GO measures
studied show an improvement in the results obtained for the yeast dataset. However, if
datasets are composed of a huge number of genes, only one of them really improves
the algorithm performance. This second case constitutes a clear option to explore
interesting datasets from a clinical point of view.Ministerio de Economía y Competitividad TIN2014-55894-C2-
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Functional Effects of let-7g Expression in Colon Cancer Metastasis.
MicroRNA regulation is crucial for gene expression and cell functions. It has been linked to tumorigenesis, development and metastasis in colorectal cancer (CRC). Recently, the let-7 family has been identified as a tumor suppressor in different types of cancers. However, the function of the let-7 family in CRC metastasis has not been fully investigated. Here, we focused on analyzing the role of let-7g in CRC. The Cancer Genome Atlas (TCGA) genomic datasets of CRC and detailed data from a Taiwanese CRC cohort were applied to study the expression pattern of let-7g. In addition, in vitro as well as in vivo studies have been performed to uncover the effects of let-7g on CRC. We found that the expression of let-7g was significantly lower in CRC specimens. Our results further supported the inhibitory effects of let-7g on CRC cell migration, invasion and extracellular calcium influx through store-operated calcium channels. We report a critical role for let-7g in the pathogenesis of CRC and suggest let-7g as a potential therapeutic target for CRC treatment
Non-coding RNA regulatory networks
It is well established that the vast majority of human RNA transcripts do not encode for proteins and that non-coding RNAs regulate cell physiology and shape cellular functions. A subset of them is involved in gene regulation at different levels, from epigenetic gene silencing to post-transcriptional regulation of mRNA stability. Notably, the aberrant expression of many non-coding RNAs has been associated with aggressive pathologies. Rapid advances in network biology indicates that the robustness of cellular processes is the result of specific properties of biological networks such as scale-free degree distribution and hierarchical modularity, suggesting that regulatory network analyses could provide new insights on gene regulation and dysfunction mechanisms. In this study we present an overview of public repositories where non-coding RNA-regulatory interactions are collected and annotated, we discuss unresolved questions for data integration and we recall existing resources to build and analyse networks
Identification of the miRNAome of early mesoderm progenitor cells and cardiomyocytes derived from human pluripotent stem cells
MicroRNAs are small non-coding RNAs involved in post-transcriptional regulation of gene expression related to many cellular functions. We performed a small-RNAseq analysis of cardiac differentiation from pluripotent stem cells. Our analyses identified some new aspects about microRNA expression in this differentiation process. First, we described a dynamic expression profile of microRNAs where some of them are clustered according to their expression level. Second, we described the extensive network of isomiRs and ADAR modifications. Third, we identified the microRNAs families and clusters involved in the establishment of cardiac lineage and define the mirRNAome based on these groups. Finally, we were able to determine a more accurate miRNAome associated with cardiomyocytes by comparing the expressed microRNAs with other mature cells. MicroRNAs exert their effect in a complex and interconnected way, making necessary a global analysis to better understand their role. Our data expands the knowledge of microRNAs and their implications in cardiomyogenesis.Fil: Garate, Ximena. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: la Greca, Alejandro Damián. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Neiman, Gabriel. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Bluguermann, Carolina. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Santín Velazque, Natalia Lucía. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Moro, Lucía Natalia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Luzzani, Carlos Daniel. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Scassa, Maria Elida. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Sevlever, Gustavo. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Romorini, Leonardo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Miriuka, Santiago Gabriel. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin
Analysis of non-coding DNA from whole exome sequencing data
Next Generation Sequencing technologies have completely changed the way to study molecular bases underlying Rare Genetic Diseases (RGDs). Currently, sequencing of the exonic portion of the human genome – the exome (1%) – performed through Whole Exome Sequencing (WES) experiments represents the most used approach to discover molecular mechanisms underlying RGDs. To date, several tools have been developed to analyse and interpret data generated from WES. However, due to both technical and experimental limitations, its diagnostic rate is ~20-30%.
In this context, we evaluated whether WES data contain information on non-coding sequences, focusing on microRNAs (miRNAs). Comparative analysis of capture design and experimental coverage allowed to disclose that in WES data reside information related to miRNA sequences that are efficiently captured by most exome enrichment kits. We therefore analysed WES of a cohort of 259 individuals, including patients affected by several genetic diseases and their unaffected relatives, searching for variants in miRNAs and performing functional annotation. Sanger sequence validation confirms the reliable call of variants mapping in miRNA sequences.
To date, no dedicated tool is available to properly retrieve and analyse miRNAs from WES and WGS data. We therefore developed a tool, “AnnomiR”, that allows to systematically analyse miRNA variants and miRNAs, providing functional annotation retrieved from several databases. This tool can be integrated in a standard workflow of analysis for WES and WGS data.
WES data contain a great amount of information that is generally discarded by commonly used workflow of analysis and that should be considered, as it could help in the comprehension of molecular mechanisms underlying RGDs. In this context, systematic study of miRNAs could help elucidating their role as disease-causative and phenotypic modifiers in a wide spectrum of human diseases, allowing to achieve a better characterisation of variability of the human genome related to these non-coding sequences
A combination of transcriptional and microRNA regulation improves the stability of the relative concentrations of target genes
It is well known that, under suitable conditions, microRNAs are able to fine
tune the relative concentration of their targets to any desired value. We show
that this function is particularly effective when one of the targets is a
Transcription Factor (TF) which regulates the other targets. This combination
defines a new class of feed-forward loops (FFLs) in which the microRNA plays
the role of master regulator. Using both deterministic and stochastic equations
we show that these FFLs are indeed able not only to fine-tune the TF/target
ratio to any desired value as a function of the miRNA concentration but also,
thanks to the peculiar topology of the circuit, to ensures the stability of
this ratio against stochastic fluctuations. These two effects are due to the
interplay between the direct transcriptional regulation and the indirect
TF/Target interaction due to competition of TF and target for miRNA binding
(the so called "sponge effect"). We then perform a genome wide search of these
FFLs in the human regulatory network and show that they are characterizedby a
very peculiar enrichment pattern. In particular they are strongly enriched in
all the situations in which the TF and its target have to be precisely kept at
the same concentration notwithstanding the environmental noise. As an example
we discuss the FFL involving E2F1 as Transcription Factor, RB1 as target and
miR-17 family as master regulator. These FFLs ensure a tight control of the
E2F/RB ratio which in turns ensures the stability of the transition from the
G0/G1 to the S phase in quiescent cells.Comment: 23 pages, 10 figure
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