Deciphering the Plant Splicing Code: Experimental and Computational Approaches for Predicting Alternative Splicing and Splicing Regulatory Elements

Extensive alternative splicing (AS) of precursor mRNAs (pre-mRNAs) in multicellular eukaryotes increases the protein-coding capacity of a genome and allows novel ways to regulate gene expression. In flowering plants, up to 48% of intron-containing genes exhibit AS. However, the full extent of AS in plants is not yet known, as only a few high-throughput RNA-Seq studies have been performed. As the cost of obtaining RNA-Seq reads continues to fall, it is anticipated that huge amounts of plant sequence data will accumulate and help in obtaining a more complete picture of AS in plants. Although it is not an onerous task to obtain hundreds of millions of reads using high-throughput sequencing technologies, computational tools to accurately predict and visualize AS are still being developed and refined. This review will discuss the tools to predict and visualize transcriptome-wide AS in plants using short-reads and highlight their limitations. Comparative studies of AS events between plants and animals have revealed that there are major differences in the most prevalent types of AS events, suggesting that plants and animals differ in the way they recognize exons and introns. Extensive studies have been performed in animals to identify cis-elements involved in regulating AS, especially in exon skipping. However, few such studies have been carried out in plants. Here, we review the current state of research on splicing regulatory elements (SREs) and briefly discuss emerging experimental and computational tools to identify cis-elements involved in regulation of AS in plants. The availability of curated alternative splice forms in plants makes it possible to use computational tools to predict SREs involved in AS regulation, which can then be verified experimentally. Such studies will permit identification of plant-specific features involved in AS regulation and contribute to deciphering the splicing code in plants

Systematic discovery of structural elements governing stability of mammalian messenger RNAs.

Decoding post-transcriptional regulatory programs in RNA is a critical step towards the larger goal of developing predictive dynamical models of cellular behaviour. Despite recent efforts, the vast landscape of RNA regulatory elements remains largely uncharacterized. A long-standing obstacle is the contribution of local RNA secondary structure to the definition of interaction partners in a variety of regulatory contexts, including--but not limited to--transcript stability, alternative splicing and localization. There are many documented instances where the presence of a structural regulatory element dictates alternative splicing patterns (for example, human cardiac troponin T) or affects other aspects of RNA biology. Thus, a full characterization of post-transcriptional regulatory programs requires capturing information provided by both local secondary structures and the underlying sequence. Here we present a computational framework based on context-free grammars and mutual information that systematically explores the immense space of small structural elements and reveals motifs that are significantly informative of genome-wide measurements of RNA behaviour. By applying this framework to genome-wide human mRNA stability data, we reveal eight highly significant elements with substantial structural information, for the strongest of which we show a major role in global mRNA regulation. Through biochemistry, mass spectrometry and in vivo binding studies, we identified human HNRPA2B1 (heterogeneous nuclear ribonucleoprotein A2/B1, also known as HNRNPA2B1) as the key regulator that binds this element and stabilizes a large number of its target genes. We created a global post-transcriptional regulatory map based on the identity of the discovered linear and structural cis-regulatory elements, their regulatory interactions and their target pathways. This approach could also be used to reveal the structural elements that modulate other aspects of RNA behaviour

Integration of CLIP experiments of RNAbinding proteins: a novel approach to predict context-dependent splicing factors from transcriptomic data

Background: Splicing is a genetic process that has important implications in several diseases including cancer. Deciphering the complex rules of splicing regulation is crucial to understand and treat splicing-related diseases. Splicing factors and other RNA-binding proteins (RBPs) play a key role in the regulation of splicing. The specific binding sites of an RBP can be measured using CLIP experiments. However, to unveil which RBPs regulate a condition, it is necessary to have a priori hypotheses, as a single CLIP experiment targets a single protein. Results: In this work, we present a novel methodology to predict context-specific splicing factors from transcriptomic data. For this, we systematically collect, integrate and analyze more than 900 CLIP experiments stored in four CLIP databases: POSTAR2, CLIPdb, DoRiNA and StarBase. The analysis of these experiments shows the strong coherence between the binding sites of RBPs of similar families. Augmenting this information with expression changes, we are able to correctly predict the splicing factors that regulate splicing in two gold-standard experiments in which specific splicing factors are knocked-down. Conclusions: The methodology presented in this study allows the prediction of active splicing factors in either cancer or any other condition by only using the information of transcript expression. This approach opens a wide range of possible studies to understand the splicing regulation of different conditions. A tutorial with the source code and databases is available at https://gitlab.com/fcarazo.m/sfprediction

Clinical impact of splicing in neurodevelopmental disorders.

Clinical exome sequencing is frequently used to identify gene-disrupting variants in individuals with neurodevelopmental disorders. While splice-disrupting variants are known to contribute to these disorders, clinical interpretation of cryptic splice variants outside of the canonical splice site has been challenging. Here, we discuss papers that improve such detection

DNA Sequencing Resolves Misdiagnosed and Rare Genetic Disorders

This chapter focuses on the mandatory requirement of DNA sequencing approaches for genetic diagnosis and recurrence prevention of inherited diseases. Sequencing the DNA and coded transcripts has intensely promoted our understanding of functional genomics and the fundamental importance of non-coding genomic sequences in causing heritable diseases, when mutated. Though Sanger sequencing, the first employed approach in identifying genetic mutations has been replaced nowadays in many laboratories with the highly robust massive parallel sequencing techniques, “Sanger” remains vital in countries with limited resources and also of essential importance in validating the results of large scale sequencing technologies. Next generation sequencing (NGS) enabled the parallel sequencing of the whole exome (WES) and whole genome (WGS) regions of human genome and has revolutionized the field of genetic and genomic research in human. WES and WGS have facilitated the identification of the role of previously unrecognized genes in causing neurologic phenotypes, brain structural malformation, and resolved the causal genes in puzzling and misdiagnosed genetic phenotypes. Role of fusion genes and non-coding RNA in causing neurogenetic recessive diseases has been uncovered by the application of NGS platforms, published examples are presented in this chapter. Extensive phenotypic variability that retained patients either as misdiagnosed or undiagnosed cases for years has been correctly diagnosed through NGS research applications

What is Life?

In searching for life in extraterrestrial space, it is essential to act based on an unequivocal definition of life. In the twentieth century, life was defined as cells that self-replicate, metabolize, and are open for mutations, without which genetic information would remain unchangeable, and evolution would be impossible. Current definitions of life derive from statistical mechanics, physics, and chemistry of the twentieth century in which life is considered to function machine like, ignoring a central role of communication. Recent observations show that context-dependent meaningful communication and network formation (and control) are central to all life forms. Evolutionary relevant new nucleotide sequences now appear to have originated from social agents such as viruses, their parasitic relatives, and related RNA networks, not from errors. By applying the known features of natural languages and communication, a new twenty-first century definition of life can be reached in which communicative interactions are central to all processes of life. A new definition of life must integrate the current empirical knowledge about interactions between cells, viruses, and RNA networks to provide a better explanatory power than the twentieth century narrative

Exploration of alternative splicing events in ten different grapevine cultivars

Background: The complex dynamics of gene regulation in plants are still far from being fully understood. Among many factors involved, alternative splicing (AS) in particular is one of the least well documented. For many years, AS has been considered of less relevant in plants, especially when compared to animals, however, since the introduction of next generation sequencing techniques the number of plant genes believed to be alternatively spliced has increased exponentially. Results: Here, we performed a comprehensive high-throughput transcript sequencing of ten different grapevine cultivars, which resulted in the first high coverage atlas of the grape berry transcriptome. We also developed findAS, a software tool for the analysis of alternatively spliced junctions. We demonstrate that at least 44 % of multi-exonic genes undergo AS and a large number of low abundance splice variants is present within the 131.622 splice junctions we have annotated from Pinot noir. Conclusions: Our analysis shows that similar to 70 % of AS events have relatively low expression levels, furthermore alternative splice sites seem to be enriched near the constitutive ones in some extent showing the noise of the splicing mechanisms. However, AS seems to be extensively conserved among the 10 cultivars

The Expanding Landscape of Alternative Splicing Variation in Human Populations.

Alternative splicing is a tightly regulated biological process by which the number of gene products for any given gene can be greatly expanded. Genomic variants in splicing regulatory sequences can disrupt splicing and cause disease. Recent developments in sequencing technologies and computational biology have allowed researchers to investigate alternative splicing at an unprecedented scale and resolution. Population-scale transcriptome studies have revealed many naturally occurring genetic variants that modulate alternative splicing and consequently influence phenotypic variability and disease susceptibility in human populations. Innovations in experimental and computational tools such as massively parallel reporter assays and deep learning have enabled the rapid screening of genomic variants for their causal impacts on splicing. In this review, we describe technological advances that have greatly increased the speed and scale at which discoveries are made about the genetic variation of alternative splicing. We summarize major findings from population transcriptomic studies of alternative splicing and discuss the implications of these findings for human genetics and medicine