Analysis of alternative cleavage and polyadenylation in mature and differentiating neurons using RNA-seq data

Background: Most eukaryotic protein-coding genes exhibit alternative cleavage and polyadenylation (APA), resulting in mRNA isoforms with different 3′ untranslated regions (3′ UTRs). Studies have shown that brain cells tend to express long 3′ UTR isoforms using distal cleavage and polyadenylation sites (PASs). Methods: Using our recently developed, comprehensive PAS database PolyA_DB, we developed an efficient method to examine APA, named Significance Analysis of Alternative Polyadenylation using RNA-seq (SAAP-RS). We applied this method to study APA in brain cells and neurogenesis. Results: We found that neurons globally express longer 3′ UTRs than other cell types in brain, and microglia and endothelial cells express substantially shorter 3′ UTRs. We show that the 3′ UTR diversity across brain cells can be corroborated with single cell sequencing data. Further analysis of APA regulation of 3′ UTRs during differentiation of embryonic stem cells into neurons indicates that a large fraction of the APA events regulated in neurogenesis are similarly modulated in myogenesis, but to a much greater extent. Conclusion: Together, our data delineate APA profiles in different brain cells and indicate that APA regulation in neurogenesis is largely an augmented process taking place in other types of cell differentiation.     

Overdispersed fungus germination data: statistical analysis using R

ABSTRACT

Proportion data from dose-response experiments are often overdispersed, characterised by a larger variance than assumed by the standard binomial model. Here, we present different models proposed in the literature that incorporate overdispersion. We also discuss how to select the best model to describe the data and present, using R software, specific code used to fit and interpret binomial, quasi-binomial, beta-binomial, and binomial-normal models, as well as to assess goodness-of-fit. We illustrate applications of these generalized linear models and generalized linear mixed models with a case study from a biological control experiment, where different isolates of Isaria fumosorosea (Hypocreales: Cordycipitaceae) were used to assess which ones presented higher resistance to UV-B radiation. We show how to test for differences between isolates and also how to statistically group isolates presenting a similar behaviour.     

A comparison of statistical methods for detecting differentially expressed genes from RNA-seq data

RNA-Seq technologies are quickly revolutionizing genomic studies, and statistical methods for RNA-seq data are under continuous development. Timely review and comparison of the most recently proposed statistical methods will provide a useful guide for choosing among them for data analysis. Particular interest surrounds the ability to detect differential expression (DE) in genes. Here we compare four recently proposed statistical methods, edgeR, DESeq, baySeq, and a method with a two-stage Poisson model (TSPM), through a variety of simulations that were based on different distribution models or real data. We compared the ability of these methods to detect DE genes in terms of the significance ranking of genes and false discovery rate control. All methods compared are implemented in freely available software. We also discuss the availability and functions of the currently available versions of these software.     

Multiple functional linear model for association analysis of RNA-seq with imaging

Emerging integrative analysis of genomic and anatomical imaging data which has not been well developed, provides invaluable information for the holistic discovery of the genomic structure of disease and has the potential to open a new avenue for discovering novel disease susceptibility genes which cannot be identified if they are analyzed separately. A key issue to the success of imaging and genomic data analysis is how to reduce their dimensions. Most previous methods for imaging information extraction and RNA-seq data reduction do not explore imaging spatial information and often ignore gene expression variation at the genomic positional level. To overcome these limitations, we extend functional principle component analysis from one dimension to two dimensions (2DFPCA) for representing imaging data and develop a multiple functional linear model (MFLM) in which functional principal scores of images are taken as multiple quantitative traits and RNA-seq profile across a gene is taken as a function predictor for assessing the association of gene expression with images. The developed method has been applied to image and RNA-seq data of ovarian cancer and kidney renal clear cell carcinoma (KIRC) studies. We identified 24 and 84 genes whose expressions were associated with imaging variations in ovarian cancer and KIRC studies, respectively. Our results showed that many significantly associated genes with images were not differentially expressed, but revealed their morphological and metabolic functions. The results also demonstrated that the peaks of the estimated regression coefficient function in the MFLM often allowed the discovery of splicing sites and multiple isoforms of gene expressions.     

Predominant contribution of cis‐regulatory divergence in the evolution of mouse alternative splicing

Divergence of alternative splicing represents one of the major driving forces to shape phenotypic diversity during evolution. However, the extent to which these divergences could be explained by the evolving cis‐regulatory versus trans‐acting factors remains unresolved. To globally investigate the relative contributions of the two factors for the first time in mammals, we measured splicing difference between C57BL/6J and SPRET/EiJ mouse strains and allele‐specific splicing pattern in their F1 hybrid. Out of 11,818 alternative splicing events expressed in the cultured fibroblast cells, we identified 796 with significant difference between the parental strains. After integrating allele‐specific data from F1 hybrid, we demonstrated that these events could be predominately attributed to cis‐regulatory variants, including those residing at and beyond canonical splicing sites. Contrary to previous observations in Drosophila, such predominant contribution was consistently observed across different types of alternative splicing. Further analysis of liver tissues from the same mouse strains and reanalysis of published datasets on other strains showed similar trends, implying in general the predominant contribution of cis‐regulatory changes in the evolution of mouse alternative splicing.     

Identification of regulatory cis-acting elements for alternative splicing of presenilin 2 exon 5 under hypoxic stress conditions

An alternatively spliced form of the presenilin 2 (PS2) gene lacking exon 5 (PS2V) was found in human brains with sporadic Alzheimer's disease. PS2V was induced by hypoxic stress in human neuroblastoma SK-N-SH cells, indicating that hypoxic stress affects the splicing machineries for PS2 exon 5. Here, we identified the critical cis-acting element (sec 2) on the PS2 pre-mRNA responsible for the aberrant splicing of PS2 exon 5 under hypoxic stress conditions. The element was composed of 23 nucleotides in exon 5 and RNA structural analyses showed a stem-loop structure in this sequence. Treatment with an antisense oligonucleotide directed toward the cis-acting element caused an increase in exon 5 inclusion. These results indicate that the sec 2 identified in this study is a novel regulatory element for exon 5 splicing under stress conditions and that trans-acting factors could specifically bind to the element to skip exon 5 of PS2.     

Biometrical modeling of twin and family data using standard mixed model software

Summary .   Biometrical genetic modeling of twin or other family data can be used to decompose the variance of an observed response or 'phenotype' into genetic and environmental components. Convenient parameterizations requiring few random effects are proposed, which allow such models to be estimated using widely available software for linear mixed models (continuous phenotypes) or generalized linear mixed models (categorical phenotypes). We illustrate the proposed approach by modeling family data on the continuous phenotype birth weight and twin data on the dichotomous phenotype depression. The example data sets and commands for Stata and R/S-PLUS are available at the Biometrics website.     

Comparison of statistical models to analyse the genetic effect on within-litter variance in pigs

Genetics affects not only the weight of piglets at birth but also the variability of birth weight within litter. Previous studies on this topic assigned the sample standard deviation of piglet birth weights within litter as an observation to the sow. However, the contribution of the difference in mean birth weight per sex on the within-litter variance has been neglected so far. This work deals with the genetic effect on within-litter variance when different statistical models with different distributional assumptions are used and considers the sex effect and appropriate weights per trait. Traits were formed from the pooled sample variance of male and female birth weights within litter. A linear model approach was fitted to the logarithmized within-litter variance and the sample standard deviation. A generalized linear model with gamma-distributed residuals and log-link function was applied to the untransformed sample variance. Models were compared by analysing data from 9439 litters from Landrace and Large White of a commercial breeding programme. The estimates of heritability for different traits ranged from 7% to 11%. Although the generalized linear mixed model is preferred from a mathematical view, the rank correlations between breeding values of the linear mixed models and the generalized linear mixed model were relatively high, i.e. 94% to 98%. By residual diagnostics, a linear mixed model using the weighted and pooled within-litter standard deviation was identified as most suitable.     

Novel alternative splicing of GABA receptor RDL exon 9 from Laodelphax striatellus modulates agonist potency

The resistance to dieldrin gene (RDL) encodes the primary subunit of the insect ionotropic γ-aminobutyric acid (GABA) receptor (GABAR), which is the target of phenylpyrazole and isoxazoline insecticides. The splice variants in exons 3 and 6 of RDL, which have been widely explored in many insects, modulate the agonist potency of the homomeric RDL GABAR and potentially play an important role in the development of insects. In the present study, four splice variants of exon 9 were identified in RDL of the small brown planthopper, Laodelphax striatellus (LsRDL), resulting in LsRDL-9a, LsRDL-9a’, LsRDL-9b, and LsRDL-9c. LsRDL-9a has one more amino acid (E, glutamic acid) compared with LsRDL-9a’, and LsRDL-9b lacked two amino acids and had seven different amino acids compared with LsRDL-9c. Two-electrode voltage-clamp recording on LsRDLs expressed in Xenopus oocytes showed that alternative splicing of exon 9 has significant impact on LsRDL sensitivity to the agonists GABA and β-alanine, whereas no significant difference was observed in the potencies of the non-competitive antagonists (NCAs) ethiprole and fluralaner on the splice variants. Our results suggest that alternative splicing of RDL exon 9 broadens functional capabilities of the GABAR in L. striatellus by influencing the action of GABA.     

Identification of an intronic splicing regulatory element involved in auto‐regulation of alternative splicing of SCL33 pre‐mRNA

In Arabidopsis, pre‐mRNAs of serine/arginine‐rich (SR) proteins undergo extensive alternative splicing (AS). However, little is known about the cis‐elements and trans‐acting proteins involved in regulating AS. Using a splicing reporter (GFP–intron–GFP), consisting of the GFP coding sequence interrupted by an alternatively spliced intron of SCL33, we investigated whether cis‐elements within this intron are sufficient for AS, and which SR proteins are necessary for regulated AS. Expression of the splicing reporter in protoplasts faithfully produced all splice variants from the intron, suggesting that cis‐elements required for AS reside within the intron. To determine which SR proteins are responsible for AS, the splicing pattern of the GFP–intron–GFP reporter was investigated in protoplasts of three single and three double mutants of SR genes. These analyses revealed that SCL33 and a closely related paralog, SCL30a, are functionally redundant in generating specific splice variants from this intron. Furthermore, SCL33 protein bound to a conserved sequence in this intron, indicating auto‐regulation of AS. Mutations in four GAAG repeats within the conserved region impaired generation of the same splice variants that are affected in the scl33 scl30a double mutant. In conclusion, we have identified the first intronic cis‐element involved in AS of a plant SR gene, and elucidated a mechanism for auto‐regulation of AS of this intron.