Tuning the engine: an introduction to resources on post-transcriptional regulation of gene expression

EARLY FLOWERING is a dominant gain-of-function allele of FANTASTIC FOUR 1/2c that promotes early flowering in tomato

Flowering time, an important factor in plant adaptability and genetic improvement, is regulated by various genes in tomato (Solanum lycopersicum). In this study, we characterized a tomato mutant, EARLY FLOWERING (EF), that developed flowers much earlier than its parental control. EF is a dominant gain-of-function allele with a T-DNA inserted 139 bp downstream of the stop codon of FANTASTIC FOUR 1/2c (FAF1/2c). The transcript of SlFAF1/2c was at elevated levels in the EF mutant. Overexpressing SlFAF1/2c in tomato plants phenocopied the early flowering trait of the EF mutant. Knocking out SlFAF1/2c in the EF mutant reverted the early flowering phenotype of the mutant to the normal flowering time of the wild-type tomato plants. SlFAF1/2c promoted the floral transition by shortening the vegetative phase rather than by reducing the number of leaves produced before the emergence of the first inflorescence. The COP9 signalosome subunit 5B (CSN5B) was shown to interact with FAF1/2c, and knocking out CSN5B led to an early flowering phenotype in tomato. Interestingly, FAF1/2c was found to reduce the accumulation of the CSN5B protein by reducing its protein stability. These findings imply that FAF1/2c regulates flowering time in tomato by reducing the accumulation and stability of CSN5B, which influences the expression of SINGLE FLOWER TRUSS (SFT), JOINTLESS (J) and UNIFLORA (UF). Thus, a new allele of SlFAF1/2c was discovered and found to regulate flowering time in tomato.

MicroSalmon: A Comprehensive, Searchable Resource of Predicted MicroRNA Targets and 3'UTR Cis-Regulatory Elements in the Full-Length Sequenced Atlantic Salmon Transcriptome

Complete 3′UTRs unambiguously assigned to specific mRNA isoforms from the Atlantic salmon full-length (FL) transcriptome were collected into a 3′UTRome. miRNA response elements (MREs) and other cis-regulatory motifs were subsequently predicted and assigned to 3′UTRs of all FL-transcripts. The MicroSalmon GitHub repository provides all results. RNAHybrid and sRNAtoolbox tools predicted the MREs. UTRscan and the Teiresias algorithm predicted other 3′UTR cis-acting motifs, both known vertebrate motifs and putative novel motifs. MicroSalmon provides search programs to retrieve all FL-transcripts targeted by a miRNA (median number 1487), all miRNAs targeting an FL-transcript (median number 27), and other cis-acting motifs. As thousands of FL-transcripts may be targets of each miRNA, additional experimental strategies are necessary to reduce the likely true and relevant targets to a number that may be functionally validated. Low-complexity motifs known to affect mRNA decay in vertebrates were over-represented. Many of these were enriched in the terminal end, while purine- or pyrimidine-rich motifs with unknown functions were enriched immediately downstream of the stop codon. Furthermore, several novel complex motifs were over-represented, indicating conservation and putative function. In conclusion, MicroSalmon is an extensive and useful, searchable resource for study of Atlantic salmon transcript regulation by miRNAs and cis-acting 3′UTR motifs.

Tissue expression and variation analysis of three bovine adipokine genes revealed their effect on growth traits in native Chinese cattle

Adipokines play a crucial role in the regulation of energy homeostasis; however, little is known about genetic alterations in this family that may contribute to economic traits in cattle. Therefore, this study conducts transcript profiles, variations and association studies of three major adipokines, leptin (LEP), tumour necrosis factor (TNF) and angiopoietin-like protein 8 (ANGPTL8), to evaluate their effects on native Chinese cattle. Using quantitative real-time PCR, the study revealed that the bovine LEP was expressed primarily in the back and visceral fat, while TNF was predominantly expressed in spleen and ANGPTL8 was mainly expressed in back fat and liver. Five single nucleotide polymorphisms (SNPs) including two missense SNPs (SNP1: g.12254T>C and SNP2: g.14177C>T) in LEP, a synonymous SNP (SNP3: g.2130A>G) in TNF and two SNPs (SNP4: g.629G>A and SNP5: g.884T>C) in the 5'UTR of ANGPTL8 were identified and genotyped in 537 individuals from six Chinese cattle breeds. Bioinformatics analysis revealed that SNP1 might disrupt the efficient binding of LEP to its receptor, SNP3 might affect translation efficiency of TNF, and SNP4 and SNP5 were likely to affect stability, splicing and nuclear export of ANGPTL8 mRNA. Consistently, association studies indicated that three SNPs (SNP1, SNP3 and SNP5) were significantly associated with body weight, heart girth, average daily gain, hip width and body length in 100 Nanyang cattle (p < 0.05). Overall, our results support the view that LEP, TNF and ANGPTL8 could be used as biomarkers to improve the growth performance in Chinese cattle selection programmes.

A Regulatory T-Cell Gene Signature Is a Specific and Sensitive Biomarker to Identify Children With New-Onset Type 1 Diabetes

Type 1 diabetes (T1D) is caused by immune-mediated destruction of insulin-producing β-cells. Insufficient control of autoreactive T cells by regulatory T cells (Tregs) is believed to contribute to disease pathogenesis, but changes in Treg function are difficult to quantify because of the lack of Treg-exclusive markers in humans and the complexity of functional experiments. We established a new way to track Tregs by using a gene signature that discriminates between Tregs and conventional T cells regardless of their activation states. The resulting 31-gene panel was validated with the NanoString nCounter platform and then measured in sorted CD4(+)CD25(hi)CD127(lo) Tregs from children with T1D and age-matched control subjects. By using biomarker discovery analysis, we found that expression of a combination of six genes, including TNFRSF1B (CD120b) and FOXP3, was significantly different between Tregs from subjects with new-onset T1D and control subjects, resulting in a sensitive (mean ± SD 0.86 ± 0.14) and specific (0.78 ± 0.18) biomarker algorithm. Thus, although the proportion of Tregs in peripheral blood is similar between children with T1D and control subjects, significant changes in gene expression can be detected early in disease process. These findings provide new insight into the mechanisms underlying the failure to control autoimmunity in T1D and might lead to a biomarker test to monitor Tregs throughout disease progression.

Sequence analysis of three canine adipokine genes revealed an association between TNF polymorphisms and obesity in Labrador dogs

Obesity is an emerging health problem in purebred dogs. Due to their crucial role in energy homeostasis control, genes encoding adipokines are considered candidate genes, and their variants may be associated with predisposition to obesity. Searching for polymorphism was carried out in three adipokine genes (TNF, RETN and IL6). The study was performed on 260 dogs, including lean (n = 109), overweight (n = 88) and obese (n = 63) dogs. The largest cohort was represented by Labrador Retrievers (n = 136). Altogether, 24 novel polymorphisms were identified: 12 in TNF (including one missense SNP), eight in RETN (including one missense SNP) and four in IL6. Distributions of five common SNPs (two in TNF, two in RETN and one in IL6) were further analyzed with regard to body condition score. Two SNPs in the non-coding parts of TNF (c.-40A>C and c.233+14G>A) were associated with obesity in Labrador dogs. The obtained results showed that the studied adipokine genes are highly polymorphic and two polymorphisms in the TNF gene may be considered as markers predisposing Labrador dogs to obesity.

Evolution of the unspliced transcriptome

BACKGROUND

Despite their abundance, unspliced EST data have received little attention as a source of information on non-coding RNAs. Very little is know, therefore, about the genomic distribution of unspliced non-coding transcripts and their relationship with the much better studied regularly spliced products. In particular, their evolution has remained virtually unstudied.

RESULTS

We systematically study the evidence on unspliced transcripts available in EST annotation tracks for human and mouse, comprising 104,980 and 66,109 unspliced EST clusters, respectively. Roughly one third of these are located totally inside introns of known genes (TINs) and another third overlaps exonic regions (PINs). Eleven percent are "intergenic", far away from any annotated gene. Direct evidence for the independent transcription of many PINs and TINs is obtained from CAGE tag and chromatin data. We predict more than 2000 3'UTR-associated RNA candidates for each human and mouse. Fifteen to twenty percent of the unspliced EST cluster are conserved between human and mouse. With the exception of TINs, the sequences of unspliced EST clusters evolve significantly slower than genomic background. Furthermore, like spliced lincRNAs, they show highly tissue-specific expression patterns.

CONCLUSIONS

Unspliced long non-coding RNAs are an important, rapidly evolving, component of mammalian transcriptomes. Their analysis is complicated by their preferential association with complex transcribed loci that usually also harbor a plethora of spliced transcripts. Unspliced EST data, although typically disregarded in transcriptome analysis, can be used to gain insights into this rarely investigated transcriptome component. The frequently postulated connection between lack of splicing and nuclear retention and the surprising overlap of chromatin-associated transcripts suggests that this class of transcripts might be involved in chromatin organization and possibly other mechanisms of epigenetic control.

SeAMotE: a method for high-throughput motif discovery in nucleic acid sequences

Background

The large amount of data produced by high-throughput sequencing poses new computational challenges. In the last decade, several tools have been developed for the identification of transcription and splicing factor binding sites.

Results

Here, we introduce the SeAMotE (Sequence Analysis of Motifs Enrichment) algorithm for discovery of regulatory regions in nucleic acid sequences. SeAMotE provides (i) a robust analysis of high-throughput sequence sets, (ii) a motif search based on pattern occurrences and (iii) an easy-to-use web-server interface. We applied our method to recently published data including 351 chromatin immunoprecipitation (ChIP) and 13 crosslinking immunoprecipitation (CLIP) experiments and compared our results with those of other well-established motif discovery tools. SeAMotE shows an average accuracy of 80% in finding discriminative motifs and outperforms other methods available in literature.

Conclusions

SeAMotE is a fast, accurate and flexible algorithm for the identification of sequence patterns involved in protein-DNA and protein-RNA recognition. The server can be freely accessed at http://s.tartaglialab.com/new_submission/seamote.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-925) contains supplementary material, which is available to authorized users.

AURA 2: Empowering discovery of post-transcriptional networks

Post-transcriptional regulation (PTR) of gene expression is now recognized as a major determinant of cell phenotypes. The recent availability of methods to map protein-RNA interactions in entire transcriptomes such as RIP, CLIP and their variants, together with global polysomal and ribosome profiling techniques, are driving the exponential accumulation of vast amounts of data on mRNA contacts in cells, and of corresponding predictions of PTR events. However, this exceptional quantity of information cannot be exploited at its best to reconstruct potential PTR networks, as it still lies scattered throughout several databases and in isolated reports of single interactions. To address this issue, we developed the second and vastly enhanced version of the Atlas of UTR Regulatory Activity (AURA 2), a meta-database centered on mapping interaction of trans-factors with human and mouse UTRs. AURA 2 includes experimentally demonstrated binding sites for RBPs, ncRNAs, thousands of cis-elements, variations, RNA epigenetics data and more. Its user-friendly interface offers various data-mining features including co-regulation search, network generation and regulatory enrichment testing. Gene expression profiles for many tissues and cell lines can be also combined with these analyses to display only the interactions possible in the system under study. AURA 2 aims at becoming a valuable toolbox for PTR studies and at tracing the road for how PTR network-building tools should be designed. AURA 2 is available at http://aura.science.unitn.it.

microRNAs and RNA-binding proteins: a complex network of interactions and reciprocal regulations in cancer

In the last decade, an ever-growing number of connections between microRNAs (miRNAs) and RNA-binding proteins (RBPs) have uncovered a new level of complexity of gene expression regulation in cancer. In this review, we examine several aspects of the functional interactions between miRNAs and RBPs in cancer models. We will provide examples of reciprocal regulation: miRNAs regulating the expression of RBPs, or the converse, where an RNA-binding protein specifically regulates the expression of a specific miRNA, or when an RBP can exert a widespread effect on miRNAs via the modulation of a key protein for miRNA production or function. Moreover, we will focus on the ever-growing number of functional interactions that have been discovered in the last few years: RBPs that were shown to cooperate with microRNAs in the downregulation of shared target mRNAs or, on the contrary, that inhibit microRNA action, thus resulting in a protection of the specific target mRNAs. We surely need to obtain a deeper comprehension of such intricate networks to have a chance of understanding and, thus, fighting cancer.