Expressão de microRNAs envolvidos com o crescimento muscular do pacu (Piaractus mesopotamicus): análises in vivo e in vitro

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Reduced circulating miR-196b levels is associated with preeclampsia

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Genome-wide association study of reproductive traits in Nellore heifers using Bayesian inference

An important goal of Zebu breeding programs is to improve reproductive performance. A major problem faced with the genetic improvement of reproductive traits is that recording the time for an animal to reach sexual maturity is costly. Another issue is that accurate estimates of breeding values are obtained only a long time after the young bulls have gone through selection. An alternative to overcome these problems is to use traits that are indicators of the reproductive efficiency of the herd and are easier to measure, such as age at first calving. Another problem is that heifers that have conceived once may fail to conceive in the next breeding season, which increases production costs. Thus, increasing heifer's rebreeding rates should improve the economic efficiency of the herd. Response to selection for these traits tends to be slow, since they have a low heritability and phenotypic information is provided only later in the life of the animal. Genome-wide association studies (GWAS) are useful to investigate the genetic mechanisms that underlie these traits by identifying the genes and metabolic pathways involved. Data from 1853 females belonging to the Agricultural Jacarezinho LTDA were used. Genotyping was performed using the BovineHD BeadChip (777 962 single nucleotide polymorphisms (SNPs)) according to the protocol of Illumina - Infinium Assay II ® Multi-Sample HiScan with the unit SQ ™ System. After quality control, 305 348 SNPs were used for GWAS. Forty-two and 19 SNPs had a Bayes factor greater than 150 for heifer rebreeding and age at first calving, respectively. All significant SNPs for age at first calving were significant for heifer rebreeding. These 42 SNPs were next or within 35 genes that were distributed over 18 chromosomes and comprised 27 protein-encoding genes, six pseudogenes and two miscellaneous noncoding RNAs. The use of Bayes factor to determine the significance of SNPs allowed us to identify two sets of 42 and 19 significant SNPs for heifer rebreeding and age at first calving, respectively, which explain 11.35 % and 6.42 % of their phenotypic variance, respectively. These SNPs provide relevant information to help elucidate which genes affect these traits.

Identification of sense and antisense transcripts regulated by drought in sugarcane

Sugarcane is an important sugar and energy crop that can be used efficiently for biofuels production. The development of sugarcane cultivars tolerant to drought could allow for the expansion of plantations to sub-prime regions. Knowledge on the mechanisms underlying drought responses and its relationship with carbon partition would greatly help to define routes to increase yield. In this work we studied sugarcane responses to drought using a custom designed oligonucleotide array with 21,901 different probes. The oligoarrays were designed to contain probes that detect transcription in both sense and antisense orientation. We validated the results obtained using quantitative real-time PCR (qPCR). A total of 987 genes were differentially expressed in at least one sample of sugarcane plants submitted to drought for 24, 72 and 120 h. Among them, 928 were sense transcripts and 59 were antisense transcripts. Genes related to Carbohydrate Metabolism, RNA Metabolism and Signal Transduction were selected for gene expression validation by qPCR that indicated a validation percentage of 90 %. From the probes presented on the array, 75 % of the sense probes and 11.9 % of the antisense probes have signal above background and can be classified as expressed sequences. Our custom sugarcane oligonucleotide array provides sensitivity and good coverage of sugarcane transcripts for the identification of a representative proportion of natural antisense transcripts (NATs) and sense-antisense transcript pairs (SATs). The antisense transcriptome showed, in most cases, co-expression with respective sense transcripts.

The humankind genome: from genetic diversity to the origin of human diseases

Genome-wide association studies have failed to establish common variant risk for the majority of common human diseases. The underlying reasons for this failure are explained by recent studies of resequencing and comparison of over 1200 human genomes and 10 000 exomes, together with the delineation of DNA methylation patterns (epigenome) and full characterization of coding and noncoding RNAs (transcriptome) being transcribed. These studies have provided the most comprehensive catalogues of functional elements and genetic variants that are now available for global integrative analysis and experimental validation in prospective cohort studies. With these datasets, researchers will have unparalleled opportunities for the alignment, mining, and testing of hypotheses for the roles of specific genetic variants, including copy number variations, single nucleotide polymorphisms, and indels as the cause of specific phenotypes and diseases. Through the use of next-generation sequencing technologies for genotyping and standardized ontological annotation to systematically analyze the effects of genomic variation on humans and model organism phenotypes, we will be able to find candidate genes and new clues for disease’s etiology and treatment. This article describes essential concepts in genetics and genomic technologies as well as the emerging computational framework to comprehensively search websites and platforms available for the analysis and interpretation of genomic data.

RNA interference in mammalian cell systems

In the last decade, few areas of biology have been transformed as thoroughly as RNA molecular biology. Without any doubt, one of the most significant advances has been the discovery of small (20-30 nucleotide) noncoding RNAs that regulate genes and genomes. The effects of small RNAs on gene expression and control are generally inhibitory, and the corresponding regulatory mechanisms are therefore collectively subsumed under the heading of RNA silencing and/or RNA interference. Two primary categories of these small RNAs - short interfering RNAs (siRNAs) and microRNAs (miRNAs) - act in both somatic and germline lineages of eukaryotic species to regulate endogenous genes and to defend the genome from invasive nucleic acids. Recent advances have revealed unexpected diversity in their biogenesis pathways and the regulatory mechanisms that they access. Our understanding of siRNA and miRNA-based regulation has direct implications for fundamental biology as well as disease aetiology and treatment as it is discussed in this review on 'new techniques in molecular biology'.

MicroRNA-381 Represses ID1 and is Deregulated in Lung Adenocarcinoma

MicroRNAs are small, noncoding RNAs that suppress gene expression by binding to the 3' untranslated region (UTR) and thereby repress translation or decrease messenger RNA stability. Inhibitor of differentiation 1 (ID1) is a putative stem-cell gene involved in invasion and angiogenesis. We previously showed that ID1 is regulated by Src kinases, overexpressed in human lung adenocarcinoma, and targeted by Src-dependent microRNAs. The current study focused on the association between miR-381 and ID1 in lung adenocarcinoma.

MicroRNAs: a new class of regulatory genes affecting metabolism

MicroRNAs (miRNAs) are short noncoding RNAs that regulate gene expression by binding to target mRNAs, which leads to reduced protein synthesis and sometimes decreased steady-state mRNA levels. Although hundreds of miRNAs have been identified, much less is known about their biological function. Several studies have provided evidence that miRNAs affect pathways that are fundamental for metabolic control in higher organisms such as adipocyte and skeletal muscle differentiation. Furthermore, some miRNAs have been implicated in lipid, amino acid, and glucose homeostasis. These studies open the possibility that miRNAs may contribute to common metabolic diseases and point to novel therapeutic opportunities based on targeting of miRNAs.

Mechanistic aspects of NMD in human cells

Eukaryotic mRNAs with premature translation termination codons (PTCs) are recognized and degraded through a process termed nonsense-mediated mRNA decay (NMD). To get more insight into the recruitment of the central NMD factor UPF1 to target mRNAs, we mapped transcriptome-wide UPF1-binding sites by individual-nucleotide-resolution UV cross-linking and immunoprecipitation (iCLIP) in human cells and found that UPF1 preferentially associated with 3′ UTRs in translationally active cells but underwent significant redistribution toward coding regions (CDS) upon translation inhibition. This indicates that UPF1 binds RNA before translation and gets displaced from the CDS by translating ribosomes. Corroborated by RNA immunoprecipitation and by UPF1 cross-linking to long noncoding RNAs, our evidence for translation-independent UPF1-RNA interaction suggests that the triggering of NMD occurs after UPF1 binding to mRNA, presumably through activation of RNA-bound UPF1 by aberrant translation termination. Unlike in yeast, in mammalian cells NMD has been reported to be restricted to cap-binding complex (CBC)–bound mRNAs during the pioneer round of translation. However, we compared decay kinetics of two NMD reporter genes in mRNA fractions bound to either CBC or the eukaryotic initiation factor 4E (eIF4E) in human cells and show that NMD destabilizes eIF4E-bound transcripts as efficiently as those associated with CBC. These results corroborate an emerging unified model for NMD substrate recognition, according to which NMD can ensue at every aberrant translation termination event.

Silencing microRNA-134 produces neuroprotective and prolonged seizure-suppressive effects

Temporal lobe epilepsy is a common, chronic neurological disorder characterized by recurrent spontaneous seizures. MicroRNAs (miRNAs) are small, noncoding RNAs that regulate post-transcriptional expression of protein-coding mRNAs, which may have key roles in the pathogenesis of neurological disorders. In experimental models of prolonged, injurious seizures (status epilepticus) and in human epilepsy, we found upregulation of miR-134, a brain-specific, activity-regulated miRNA that has been implicated in the control of dendritic spine morphology. Silencing of miR-134 expression in vivo using antagomirs reduced hippocampal CA3 pyramidal neuron dendrite spine density by 21% and rendered mice refractory to seizures and hippocampal injury caused by status epilepticus. Depletion of miR-134 after status epilepticus in mice reduced the later occurrence of spontaneous seizures by over 90% and mitigated the attendant pathological features of temporal lobe epilepsy. Thus, silencing miR-134 exerts prolonged seizure-suppressant and neuroprotective actions; determining whether these are anticonvulsant effects or are truly antiepileptogenic effects requires additional experimentation.

Systematic expression profiling of the mouse transcriptome using RIKEN cDNA mircoarrays

The number of known mRNA transcripts in the mouse has been greatly expanded by the RIKEN Mouse Gene Encyclopedia project. Validation of their reproducible expression in a tissue is an important contribution to the study of functional genomics. In this report, we determine the expression profile of 57,931 clones on 20 mouse tissues using cDNA microarrays. Of these 57,931 clones, 22,928 clones correspond to the FANTOM2 clone set. The set represents 20,234 transcriptional units (TUs) out of 33,409 TUs in the FANTOM2 set. We identified 7206 separate clones that satisfied stringent criteria for tissue-specific expression. Gene Ontology terms were assigned for these 7206 clones, and the proportion of 'molecular function' ontology for each tissue-specific clone was examined. These data will provide insights into the function of each tissue. Tissue-specific gene expression profiles obtained using our cDNA microarrays were also compared with the data extracted from the GNF Expression Atlas based on Affymetrix microarrays. One major outcome of the RIKEN transcriptome analysis is the identification of numerous nonprotein-coding mRNAs. The expression profile was also used to obtain evidence of expression for putative noncoding RNAs. In addition, 1926 clones (70%) of 2768 clones that were categorized as unknown EST, and 1969 (58%) clones of 3388 clones that were categorized as unclassifiable were also shown to be reproducibly expressed.

Construction of representative transcript and protein sets of human, mouse, and rat as a platform for their transcriptome and proteome analysis

The number of mammalian transcripts identified by full-length cDNA projects and genome sequencing projects is increasing remarkably. Clustering them into a strictly nonredundant and comprehensive set provides a platform for functional analysis of the transcriptome and proteome, but the quality of the clustering and predictive usefulness have previously required manual curation to identify truncated transcripts and inappropriate clustering of closely related sequences. A Representative Transcript and Protein Sets (RTPS) pipeline was previously designed to identify the nonredundant and comprehensive set of mouse transcripts based on clustering of a large mouse full-length cDNA set (FANTOM2). Here we propose an alternative method that is more robust, requires less manual curation, and is applicable to other organisms in addition to mouse. RTPSs of human, mouse, and rat have been produced by this method and used for validation. Their comprehensiveness and quality are discussed by comparison with other clustering approaches. The RTPSs are available at ftp://fantom2.gsc.riken.go.jp/RTPS/. (C). 2004 Elsevier Inc. All rights reserved.

RNA regulation: a new genetics?

Do non-coding RNAs that are derived from the introns and exons of protein-coding and non-protein-coding genes represent a fundamental advance in the genetic operating system of higher organisms? Recent evidence from comparative genomics and molecular genetics indicates that this might be the case. If so, there will be profound consequences for our understanding of the genetics of these organisms, and in particular how the trajectories of differentiation and development and the differences among individuals and species are genomically programmed. But how might this hypothesis be tested?

Antisense transcription in the mammalian transcriptome

Antisense transcription (transcription from the opposite strand to a protein-coding or sense strand) has been ascribed roles in gene regulation involving degradation of the corresponding sense transcripts (RNA interference), as well as gene silencing at the chromatin level. Global transcriptome analysis provides evidence that a large proportion of the genome can produce transcripts from both strands, and that antisense transcripts commonly link neighboring genes in complex loci into chains of linked transcriptional units. Expression profiling reveals frequent concordant regulation of sense/antisense pairs. We present experimental evidence that perturbation of an antisense RNA can alter the expression of sense messenger RNAs, suggesting that antisense transcription contributes to control of transcriptional outputs in mammals.

Inherent size constraints on prokaryote gene networks due to "accelerating" growth

Networks exhibiting accelerating growth have total link numbers growing faster than linearly with network size and either reach a limit or exhibit graduated transitions from nonstationary-to-stationary statistics and from random to scale-free to regular statistics as the network size grows. However, if for any reason the network cannot tolerate such gross structural changes then accelerating networks are constrained to have sizes below some critical value. This is of interest as the regulatory gene networks of single-celled prokaryotes are characterized by an accelerating quadratic growth and are size constrained to be less than about 10,000 genes encoded in DNA sequence of less than about 10 megabases. This paper presents a probabilistic accelerating network model for prokaryotic gene regulation which closely matches observed statistics by employing two classes of network nodes (regulatory and non-regulatory) and directed links whose inbound heads are exponentially distributed over all nodes and whose outbound tails are preferentially attached to regulatory nodes and described by a scale-free distribution. This model explains the observed quadratic growth in regulator number with gene number and predicts an upper prokaryote size limit closely approximating the observed value. (c) 2005 Elsevier GmbH. All rights reserved.