Methods to study splicing from high-throughput RNA Sequencing data

The development of novel high-throughput sequencing (HTS) methods for RNA (RNA-Seq) has provided a very powerful mean to study splicing under multiple conditions at unprecedented depth. However, the complexity of the information to be analyzed has turned this into a challenging task. In the last few years, a plethora of tools have been developed, allowing researchers to process RNA-Seq data to study the expression of isoforms and splicing events, and their relative changes under different conditions. We provide an overview of the methods available to study splicing from short RNA-Seq data. We group the methods according to the different questions they address: 1) Assignment of the sequencing reads to their likely gene of origin. This is addressed by methods that map reads to the genome and/or to the available gene annotations. 2) Recovering the sequence of splicing events and isoforms. This is addressed by transcript reconstruction and de novo assembly methods. 3) Quantification of events and isoforms. Either after reconstructing transcripts or using an annotation, many methods estimate the expression level or the relative usage of isoforms and/or events. 4) Providing an isoform or event view of differential splicing or expression. These include methods that compare relative event/isoform abundance or isoform expression across two or more conditions. 5) Visualizing splicing regulation. Various tools facilitate the visualization of the RNA-Seq data in the context of alternative splicing. In this review, we do not describe the specific mathematical models behind each method. Our aim is rather to provide an overview that could serve as an entry point for users who need to decide on a suitable tool for a specific analysis. We also attempt to propose a classification of the tools according to the operations they do, to facilitate the comparison and choice of methods.Comment: 31 pages, 1 figure, 9 tables. Small corrections adde

New Zealand Blackcurrant Extract Improves Cycling Performance and Fat Oxidation in Cyclists

PURPOSE: Blackcurrant intake increases peripheral blood flow in humans, potentially by anthocyanin-induced vasodilation which may affect substrate delivery and exercise performance. We examined the effects of New Zealand blackcurrant (NZBC) extract on substrate oxidation, cycling time-trial performance and plasma lactate responses following the time-trial in trained cyclists. METHODS: Using a randomized, double-blind, crossover design, fourteen healthy men (age: 38 ± 13 years, height: 178 ± 4 cm, body mass: 77 ± 9 kg, V?O2max: 53 ± 6 ml·kg-1·min-1, mean ± SD) ingested NZBC extract (300 mg?day-1 CurraNZ™ containing 105 mg anthocyanin) or placebo (PL, 300 mg microcrystalline cellulose M102) for 7-days (washout 14-days). On day 7, participants performed 30 min of cycling (3x10 min at 45, 55 and 65% V?O2max), followed by a 16.1 km time-trial with lactate sampling during a 20-minute passive recovery. RESULTS: NZBC extract increased fat oxidation at 65% V?O2max by 27% (P < 0.05) and improved 16.1 km time-trial performance by 2.4% (NZBC: 1678 ± 108 s, PL: 1722 ± 131 s, P < 0.05). Plasma lactate was higher with NZBC extract immediately following the time-trial (NZBC: 7.06 ± 1.73 mmol?L-1, PL: 5.92 ± 1.58 mmol?L-1 P < 0.01). CONCLUSIONS: Seven days intake of New Zealand blackcurrant extract improves 16.1 km cycling time-trial performance and increases fat oxidation during moderate intensity cycling

As Far as the Eye Can See: Relationship between Psychopathic Traits and Pupil Response to Affective Stimuli

Psychopathic individuals show a range of affective processing deficits, typically associated with the interpersonal/affective component of psychopathy. However, previous research has been inconsistent as to whether psychopathy, within both offender and community populations, is associated with deficient autonomic responses to the simple presentation of affective stimuli. Changes in pupil diameter occur in response to emotionally arousing stimuli and can be used as an objective indicator of physiological reactivity to emotion. This study used pupillometry to explore whether psychopathic traits within a community sample were associated with hypo-responsivity to the affective content of stimuli. Pupil activity was recorded for 102 adult (52 female) community participants in response to affective (both negative and positive affect) and affectively neutral stimuli, that included images of scenes, static facial expressions, dynamic facial expressions and sound-clips. Psychopathic traits were measured using the Triarchic Psychopathy Measure. Pupil diameter was larger in response to negative stimuli, but comparable pupil size was demonstrated across pleasant and neutral stimuli. A linear relationship between subjective arousal and pupil diameter was found in response to sound-clips, but was not evident in response to scenes. Contrary to predictions, psychopathy was unrelated to emotional modulation of pupil diameter across all stimuli. The findings were the same when participant gender was considered. This suggests that psychopathy within a community sample is not associated with autonomic hypo-responsivity to affective stimuli, and this effect is discussed in relation to later defensive/appetitive mobilisation deficits

An EMT-Driven Alternative Splicing Program Occurs in Human Breast Cancer and Modulates Cellular Phenotype

Epithelial-mesenchymal transition (EMT), a mechanism important for embryonic development, plays a critical role during malignant transformation. While much is known about transcriptional regulation of EMT, alternative splicing of several genes has also been correlated with EMT progression, but the extent of splicing changes and their contributions to the morphological conversion accompanying EMT have not been investigated comprehensively. Using an established cell culture model and RNA–Seq analyses, we determined an alternative splicing signature for EMT. Genes encoding key drivers of EMT–dependent changes in cell phenotype, such as actin cytoskeleton remodeling, regulation of cell–cell junction formation, and regulation of cell migration, were enriched among EMT–associated alternatively splicing events. Our analysis suggested that most EMT–associated alternative splicing events are regulated by one or more members of the RBFOX, MBNL, CELF, hnRNP, or ESRP classes of splicing factors. The EMT alternative splicing signature was confirmed in human breast cancer cell lines, which could be classified into basal and luminal subtypes based exclusively on their EMT–associated splicing pattern. Expression of EMT–associated alternative mRNA transcripts was also observed in primary breast cancer samples, indicating that EMT–dependent splicing changes occur commonly in human tumors. The functional significance of EMT–associated alternative splicing was tested by expression of the epithelial-specific splicing factor ESRP1 or by depletion of RBFOX2 in mesenchymal cells, both of which elicited significant changes in cell morphology and motility towards an epithelial phenotype, suggesting that splicing regulation alone can drive critical aspects of EMT–associated phenotypic changes. The molecular description obtained here may aid in the development of new diagnostic and prognostic markers for analysis of breast cancer progression.National Institutes of Health (U.S.) (R01-HG002439)National Science Foundation (U.S.) (equipment grant)National Institutes of Health (U.S.) (Integrative Cancer Biology Program Grant U54-CA112967)David H. Koch Institute for Integrative Cancer Research at MIT (Ludwig Center for Metastasis Research)David H. Koch Institute for Integrative Cancer Research at MITMassachusetts Institute of Technology (Croucher Scholarship)Massachusetts Institute of Technology (Ludwig Fund postdoctoral fellowship)National Institutes of Health (U.S.) (NIH CA100324)National Institutes of Health (U.S.) (AECC9526-5267

Characterization of the mouse Dazap1 gene encoding an RNA-binding protein that interacts with infertility factors DAZ and DAZL

BACKGROUND: DAZAP1 (DAZ Associated Protein 1) was originally identified by a yeast two-hybrid system through its interaction with a putative male infertility factor, DAZ (Deleted in Azoospermia). In vitro, DAZAP1 interacts with both the Y chromosome-encoded DAZ and an autosome-encoded DAZ-like protein, DAZL. DAZAP1 contains two RNA-binding domains (RBDs) and a proline-rich C-terminal portion, and is expressed most abundantly in the testis. To understand the biological function of DAZAP1 and the significance of its interaction with DAZ and DAZL, we isolated and characterized the mouse Dazap1 gene, and studied its expression and the subcellular localization of its protein product. RESULTS: The human and mouse genes have similar genomic structures and map to syntenic chromosomal regions. The mouse and human DAZAP1 proteins share 98% identity and their sequences are highly similar to the Xenopus orthologue Prrp, especially in the RBDs. Dazap1 is expressed throughout testis development. Western blot detects a single 45 kD DAZAP1 protein that is most abundant in the testis. Although a majority of DAZAP1 is present in the cytoplasmic fraction, they are not associated with polyribosomes. CONCLUSIONS: DAZAP1 is evolutionarily highly conserved. Its predominant expression in testes suggests a role in spermatogenesis. Its subcellular localization indicates that it is not directly involved in mRNA translation

Evaluation of clustering algorithms for gene expression data

BACKGROUND: Cluster analysis is an integral part of high dimensional data analysis. In the context of large scale gene expression data, a filtered set of genes are grouped together according to their expression profiles using one of numerous clustering algorithms that exist in the statistics and machine learning literature. A closely related problem is that of selecting a clustering algorithm that is "optimal" in some sense from a rather impressive list of clustering algorithms that currently exist. RESULTS: In this paper, we propose two validation measures each with two parts: one measuring the statistical consistency (stability) of the clusters produced and the other representing their biological functional congruence. Smaller values of these indices indicate better performance for a clustering algorithm. We illustrate this approach using two case studies with publicly available gene expression data sets: one involving a SAGE data of breast cancer patients and the other involving a time course cDNA microarray data on yeast. Six well known clustering algorithms UPGMA, K-Means, Diana, Fanny, Model-Based and SOM were evaluated. CONCLUSION: No single clustering algorithm may be best suited for clustering genes into functional groups via expression profiles for all data sets. The validation measures introduced in this paper can aid in the selection of an optimal algorithm, for a given data set, from a collection of available clustering algorithms

Sex differences in energy balance, body composition, and metabolic and endocrine markers during prolonged arduous military training

Energy deficits are common in military training and can result in endocrine and metabolic disturbances. This study provides first investigation of sex differences in energy balance, body composition, and endocrine and metabolic markers in response to prolonged and arduous military training. Men experienced greater energy deficits than women due to higher energy expenditure, which was not compensated for by increased energy intake. These energy deficits were not associated with decreases in fat or lean mass or metabolic or endocrine function

Binary classification of dyslipidemia from the waist-to-hip ratio and body mass index: a comparison of linear, logistic, and CART models

BACKGROUND: We sought to improve upon previously published statistical modeling strategies for binary classification of dyslipidemia for general population screening purposes based on the waist-to-hip circumference ratio and body mass index anthropometric measurements. METHODS: Study subjects were participants in WHO-MONICA population-based surveys conducted in two Swiss regions. Outcome variables were based on the total serum cholesterol to high density lipoprotein cholesterol ratio. The other potential predictor variables were gender, age, current cigarette smoking, and hypertension. The models investigated were: (i) linear regression; (ii) logistic classification; (iii) regression trees; (iv) classification trees (iii and iv are collectively known as "CART"). Binary classification performance of the region-specific models was externally validated by classifying the subjects from the other region. RESULTS: Waist-to-hip circumference ratio and body mass index remained modest predictors of dyslipidemia. Correct classification rates for all models were 60–80%, with marked gender differences. Gender-specific models provided only small gains in classification. The external validations provided assurance about the stability of the models. CONCLUSIONS: There were no striking differences between either the algebraic (i, ii) vs. non-algebraic (iii, iv), or the regression (i, iii) vs. classification (ii, iv) modeling approaches. Anticipated advantages of the CART vs. simple additive linear and logistic models were less than expected in this particular application with a relatively small set of predictor variables. CART models may be more useful when considering main effects and interactions between larger sets of predictor variables

Does green tea affect postprandial glucose, insulin and satiety in healthy subjects: a randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Results of epidemiological studies have suggested that consumption of green tea could lower the risk of type 2 diabetes. Intervention studies show that green tea may decrease blood glucose levels, and also increase satiety. This study was conducted to examine the postprandial effects of green tea on glucose levels, glycemic index, insulin levels and satiety in healthy individuals after the consumption of a meal including green tea.</p> <p>Methods</p> <p>The study was conducted on 14 healthy volunteers, with a crossover design. Participants were randomized to either 300 ml of green tea or water. This was consumed together with a breakfast consisting of white bread and sliced turkey. Blood samples were drawn at 0, 15, 30, 45, 60, 90, and 120 minutes. Participants completed several different satiety score scales at the same times.</p> <p>Results</p> <p>Plasma glucose levels were higher 120 min after ingestion of the meal with green tea than after the ingestion of the meal with water. No significant differences were found in serum insulin levels, or the area under the curve for glucose or insulin. Subjects reported significantly higher satiety, having a less strong desire to eat their favorite food and finding it less pleasant to eat another mouthful of the same food after drinking green tea compared to water.</p> <p>Conclusions</p> <p>Green tea showed no glucose or insulin-lowering effect. However, increased satiety and fullness were reported by the participants after the consumption of green tea.</p> <p>Trial registration number</p> <p>NCT01086189</p