Tissue-specific mouse mRNA isoform networks

Characterization and Comparative Analysis of Whole-Transcriptome Sequencing in High- and Low-Fecundity Chongming White Goat Ovaries during the Estrus Phase

Reproductive performance is one of the most important economic traits in the goat industry. Increasing the number of goats is an effective measure to improve production efficiency and reduce production costs. Ovaries are important reproductive organs in female mammals that directly affect the estrous cycle and reproductive abilities. Understanding the complex transcription network of non-coding RNAs (lncRNAs, circRNAs, and miRNAs) and messenger RNA (mRNA) could lead to significant insights into the ovarian regulation of the reproductive processes of animals. However, the whole-transcriptome analysis of the non-coding RNAs and mRNA of the ovaries in Chongming white goats between high-fecundity (HP) and low-fecundity (LP) groups is limited. In this study, a whole-transcriptome sequencing approach was used to identify lncRNA, circRNA, miRNA, and mRNA expression in the ovaries of Chongming white goats during the estrus phase using RNA-Seq technology. More than 20,000 messenger RNAs (mRNAs), 10,000 long non-coding RNAs (lncRNAs), 3500 circular RNAs (circRNAs), and 1000 micro RNAs (miRNAs) were identified. A total of 1024 differential transcripts (724 mRNAs, 112 lncRNAs, 178 circRNAs, and 10 miRNAs) existing between the HP and the LP groups were revealed through a bioinformatics analysis. They were enriched in the prolactin signaling pathway, the Jak-STAT signaling pathway, and the GnRH signaling pathway, as well as various metabolic pathways. Differentially expressed mRNAs (such as LYPD6, VEGFA, NOS3, TNXB, and EPHA2) and miRNAs (such as miR-10a-5p) play key roles in the regulation of goat ovaries during the estrus phase. The enrichment of pathways related to reproduction, such as the Hippo, Hedgehog, PI3K-AKT, and MAPK signaling pathways, suggests that they might be involved in the prolificacy of goat ovaries. Overall, we identified several gene modules associated with goat fecundity and provided a basis for a molecular mechanism in the ovaries of Chongming white goats.

Tissue Specificity Based Isoform Function Prediction

Alternative splicing enables a gene spliced into different isoforms and hence protein variants. Identifying individual functions of these isoforms help deciphering the functional diversity of proteins. Although much efforts have been made for automatic gene function prediction, few efforts have been moved toward computational isoform function prediction, mainly due to the unavailable (or scanty) functional annotations of isoforms. Existing efforts directly combine multiple RNA-seq datasets without account of the important tissue specificity of alternative splicing. To bridge this gap, we introduce a novel approach called TS-Isofun to predict the functions of isoforms by integrating multiple functional association networks with respect to tissue specificity. TS-Isofun first constructs tissue-specific isoform functional association networks using multiple RNA-seq datasets from tissue-wise. Next, TS-Isofun assigns weights to these networks and models the tissue specificity by selectively integrating them with adaptive weights. It then introduces a joint matrix factorization-based data fusion model to leverage the integrated network, gene-level data and functional annotations of genes to infer the functions of isoforms. To achieve coherent weight assignment and isoform function prediction, TS-Isofun jointly optimizes the weights of individual networks and the isoform function prediction in a unified objective function. Experimental results show that TS-Isofun significantly outperforms state-of-the-art methods and the account of tissue specificity contributes to more accurate isoform function prediction.

FINER: enhancing the prediction of tissue-specific functions of isoforms by refining isoform interaction networks

Annotating the functions of gene products is a mainstay in biology. A variety of databases have been established to record functional knowledge at the gene level. However, functional annotations at the isoform resolution are in great demand in many biological applications. Although critical information in biological processes such as protein-protein interactions (PPIs) is often used to study gene functions, it does not directly help differentiate the functions of isoforms, as the 'proteins' in the existing PPIs generally refer to 'genes'. On the other hand, the prediction of isoform functions and prediction of isoform-isoform interactions, though inherently intertwined, have so far been treated as independent computational problems in the literature. Here, we present FINER, a unified framework to jointly predict isoform functions and refine PPIs from the gene level to the isoform level, enabling both tasks to benefit from each other. Extensive computational experiments on human tissue-specific data demonstrate that FINER is able to gain at least 5.16% in AUC and 15.1% in AUPRC for functional prediction across multiple tissues by refining noisy PPIs, resulting in significant improvement over the state-of-the-art methods. Some in-depth analyses reveal consistency between FINER's predictions and the tissue specificity as well as subcellular localization of isoforms.

IsoDA: Isoform-Disease Association Prediction by Multiomics Data Fusion

A gene can be spliced into different isoforms by alternative splicing, which contributes to the functional diversity of protein species. Computational prediction of gene-disease associations (GDAs) has been studied for decades. However, the process of identifying the isoform-disease associations (IDAs) at a large scale is rarely explored, which can decipher the pathology at a more granular level. The main bottleneck is the lack of IDAs in current databases and the multilevel omics data fusion. To bridge this gap, we propose a computational approach called Isoform-Disease Association prediction by multiomics data fusion (IsoDA) to predict IDAs. Based on the relationship between a gene and its spliced isoforms, IsoDA first introduces a dispatch and aggregation term to dispatch gene-disease associations to individual isoforms, and reversely aggregate these dispatched associations to their hosting genes. At the same time, it fuses the genome, transcriptome, and proteome data by joint matrix factorization to improve the prediction of IDAs. Experimental results show that IsoDA significantly outperforms the related state-of-the-art methods at both the gene level and isoform level. A case study further shows that IsoDA credibly identifies three isoforms spliced from apolipoprotein E, which have individual associations with Alzheimer's disease, and two isoforms spliced from vascular endothelial growth factor A, which have different associations with coronary heart disease. The codes of IsoDA are available at http://mlda.swu.edu.cn/codes.php?name=IsoDA.

Overview of PAX gene family: analysis of human tissue-specific variant expression and involvement in human disease

Paired-box (PAX) genes encode a family of highly conserved transcription factors found in vertebrates and invertebrates. PAX proteins are defined by the presence of a paired domain that is evolutionarily conserved across phylogenies. Inclusion of a homeodomain and/or an octapeptide linker subdivides PAX proteins into four groups. Often termed "master regulators", PAX proteins orchestrate tissue and organ development throughout cell differentiation and lineage determination, and are essential for tissue structure and function through maintenance of cell identity. Mutations in PAX genes are associated with myriad human diseases (e.g., microphthalmia, anophthalmia, coloboma, hypothyroidism, acute lymphoblastic leukemia). Transcriptional regulation by PAX proteins is, in part, modulated by expression of alternatively spliced transcripts. Herein, we provide a genomics update on the nine human PAX family members and PAX homologs in 16 additional species. We also present a comprehensive summary of human tissue-specific PAX transcript variant expression and describe potential functional significance of PAX isoforms. While the functional roles of PAX proteins in developmental diseases and cancer are well characterized, much remains to be understood regarding the functional roles of PAX isoforms in human health. We anticipate the analysis of tissue-specific PAX transcript variant expression presented herein can serve as a starting point for such research endeavors.

Roles of developmentally regulated KIF2A alternative isoforms in cortical neuron migration and differentiation

KIF2A is a kinesin motor protein with essential roles in neural progenitor division and axonal pruning during brain development. However, how different KIF2A alternative isoforms function during development of the cerebral cortex is not known. Here, we focus on three Kif2a isoforms expressed in the developing cortex. We show that Kif2a is essential for dendritic arborization in mice and that the functions of all three isoforms are sufficient for this process. Interestingly, only two of the isoforms can sustain radial migration of cortical neurons; a third isoform, lacking a key N-terminal region, is ineffective. By proximity-based interactome mapping for individual isoforms, we identify previously known KIF2A interactors, proteins localized to the mitotic spindle poles and, unexpectedly, also translation factors, ribonucleoproteins and proteins that are targeted to organelles, prominently to the mitochondria. In addition, we show that a KIF2A mutation, which causes brain malformations in humans, has extensive changes to its proximity-based interactome, with depletion of mitochondrial proteins identified in the wild-type KIF2A interactome. Our data raises new insights about the importance of alternative splice variants during brain development.

Computational Methods for Predicting Functions at the mRNA Isoform Level

Multiple mRNA isoforms of the same gene are produced via alternative splicing, a biological mechanism that regulates protein diversity while maintaining genome size. Alternatively spliced mRNA isoforms of the same gene may sometimes have very similar sequence, but they can have significantly diverse effects on cellular function and regulation. The products of alternative splicing have important and diverse functional roles, such as response to environmental stress, regulation of gene expression, human heritable, and plant diseases. The mRNA isoforms of the same gene can have dramatically different functions. Despite the functional importance of mRNA isoforms, very little has been done to annotate their functions. The recent years have however seen the development of several computational methods aimed at predicting mRNA isoform level biological functions. These methods use a wide array of proteo-genomic data to develop machine learning-based mRNA isoform function prediction tools. In this review, we discuss the computational methods developed for predicting the biological function at the individual mRNA isoform level.

A rapid and simple quantitative method for specific detection of smaller coterminal RNA by PCR (DeSCo-PCR): application to the detection of viral subgenomic RNAs

RNAs that are 5'-truncated versions of a longer RNA but share the same 3' terminus can be generated by alternative promoters in transcription of cellular mRNAs or by replicating RNA viruses. These truncated RNAs cannot be distinguished from the longer RNA by a simple two-primer RT-PCR because primers that anneal to the cDNA from the smaller RNA also anneal to-and amplify-the longer RNA-derived cDNA. Thus, laborious methods, such as northern blot hybridization, are used to distinguish shorter from longer RNAs. For rapid, low-cost, and specific detection of these truncated RNAs, we report detection of smaller coterminal RNA by PCR (DeSCo-PCR). DeSCo-PCR uses a nonextendable blocking primer (BP), which outcompetes a forward primer (FP) for annealing to longer RNA-derived cDNA, while FP outcompetes BP for annealing to shorter RNA-derived cDNA. In the presence of BP, FP, and the reverse primer, only cDNA from the shorter RNA is amplified in a single-tube reaction containing both RNAs. Many positive strand RNA viruses generate 5'-truncated forms of the genomic RNA (gRNA) called subgenomic RNAs (sgRNA), which play key roles in viral gene expression and pathogenicity. We demonstrate that DeSCo-PCR is easily optimized to selectively detect relative quantities of sgRNAs of red clover necrotic mosaic virus from plants and Zika virus from human cells, each infected with viral strains that generate different amounts of sgRNA. This technique should be readily adaptable to other sgRNA-producing viruses, and for quantitative detection of any truncated or alternatively spliced RNA.