Technologies for the Global Discovery and Analysis of Alternative Splicing

SANS (USH1G) regulates pre-mRNA splicing by mediating the intra-nuclear transfer of tri-snRNP complexes

Splicing is catalyzed by the spliceosome, a compositionally dynamic complex assembled stepwise on pre-mRNA. We reveal links between splicing machinery components and the intrinsically disordered ciliopathy protein SANS. Pathogenic mutations in SANS/USH1G lead to Usher syndrome—the most common cause of deaf-blindness. Previously, SANS was shown to function only in the cytosol and primary cilia. Here, we have uncovered molecular links between SANS and pre-mRNA splicing catalyzed by the spliceosome in the nucleus. We show that SANS is found in Cajal bodies and nuclear speckles, where it interacts with components of spliceosomal sub-complexes such as SF3B1 and the large splicing cofactor SON but also with PRPFs and snRNAs related to the tri-snRNP complex. SANS is required for the transfer of tri-snRNPs between Cajal bodies and nuclear speckles for spliceosome assembly and may also participate in snRNP recycling back to Cajal bodies. SANS depletion alters the kinetics of spliceosome assembly, leading to accumulation of complex A. SANS deficiency and USH1G pathogenic mutations affects splicing of genes related to cell proliferation and human Usher syndrome. Thus, we provide the first evidence that splicing dysregulation may participate in the pathophysiology of Usher syndrome.

Nucleic Acid Platform Technologies

Every microarray experiment is based on a common format. First, a large number of nucleotide "spots" are arrayed onto a substrate, typically a glass slide, a silicon chip, or microbeads. Second, a complex population of nucleic acids (isolated from cells, selected from in vitro-synthesized libraries, or obtained from another source) is labeled, typically with fluorescent dyes. Third, the labeled nucleic acids are allowed to hybridize to their complementary spot(s) on the microarray. Fourth, the hybridized microarray is washed, allowing the amount of hybridized label to then be quantified. Analysis of the raw data generates a readout of the levels of each species of RNA in the original complex population. This introduction includes several examples of microarray applications and provides a discussion of the basic steps of most microarray experiments.

Transcriptome analyses reveal genes of alternative splicing associated with muscle development in chickens

Alternative splicing (AS) of pre-mRNA is a central mode of genetic regulation in higher eukaryotes. High-throughput experimental verification of alternative splice forms, functional characterization, and regulation of alternative splicing are key directions for research. However, little information is available on the transcriptome-wide changes during different ages in different chicken breeds. In this study, the sequencing reads of chicken muscle tissues collected from White feather broiler (day 42) and Luning Chicken (day 70, 120, 150) were mapped to the chicken genome. Results showed that a total of 16,958 genes were annotated, with 2230 differentially expressed genes (DEGs) when comparing White feather broiler and Luning Chicken, and an average of 700 DEGs when comparing different ages in Luning Chicken. Functional classification by Gene Ontology (GO) and pathways analysis for selecting the genes showed most DEGs were related to muscle development and immune response. Of the 16,958 genes, a total of 6249 genes (36.85%) underwent AS events, and over 40% were specifically expressed in each library. Additionally, 6 DEGs (SRPK3, ENSGALG00000022884, CCL4, GATM, SESN1, PTTG1IP) involved in muscle development and immunity response were found to be alternatively spliced among all the four muscle tissues. In conclusion, we present a complete dataset involving the spatial and temporal transcriptome of chicken muscle tissue using RNA -seq. These data will facilitate the understanding of the effects of breed and age on the development of muscle and uncover that AS events of candidate genes may have important functional roles in regulation of muscle development in chicken.

Functional Networks of Highest-Connected Splice Isoforms: From The Chromosome 17 Human Proteome Project

Alternative splicing allows a single gene to produce multiple transcript-level splice isoforms from which the translated proteins may show differences in their expression and function. Identifying the major functional or canonical isoform is important for understanding gene and protein functions. Identification and characterization of splice isoforms is a stated goal of the HUPO Human Proteome Project and of neXtProt. Multiple efforts have catalogued splice isoforms as "dominant", "principal", or "major" isoforms based on expression or evolutionary traits. In contrast, we recently proposed highest connected isoforms (HCIs) as a new class of canonical isoforms that have the strongest interactions in a functional network and revealed their significantly higher (differential) transcript-level expression compared to nonhighest connected isoforms (NCIs) regardless of tissues/cell lines in the mouse. HCIs and their expression behavior in the human remain unexplored. Here we identified HCIs for 6157 multi-isoform genes using a human isoform network that we constructed by integrating a large compendium of heterogeneous genomic data. We present examples for pairs of transcript isoforms of ABCC3, RBM34, ERBB2, and ANXA7. We found that functional networks of isoforms of the same gene can show large differences. Interestingly, differential expression between HCIs and NCIs was also observed in the human on an independent set of 940 RNA-seq samples across multiple tissues, including heart, kidney, and liver. Using proteomic data from normal human retina and placenta, we showed that HCIs are a promising indicator of expressed protein isoforms exemplified by NUDFB6 and M6PR. Furthermore, we found that a significant percentage (20%, p = 0.0003) of human and mouse HCIs are homologues, suggesting their conservation between species. Our identified HCIs expand the repertoire of canonical isoforms and are expected to facilitate studying main protein products, understanding gene regulation, and possibly evolution. The network is available through our web server as a rich resource for investigating isoform functional relationships (http://guanlab.ccmb.med.umich.edu/hisonet). All MS/MS data were available at ProteomeXchange Web site (http://www.proteomexchange.org) through their identifiers (retina: PXD001242, placenta: PXD000754).

Assessing long-distance RNA sequence connectivity via RNA-templated DNA-DNA ligation

Many RNAs, including pre-mRNAs and long non-coding RNAs, can be thousands of nucleotides long and undergo complex post-transcriptional processing. Multiple sites of alternative splicing within a single gene exponentially increase the number of possible spliced isoforms, with most human genes currently estimated to express at least ten. To understand the mechanisms underlying these complex isoform expression patterns, methods are needed that faithfully maintain long-range exon connectivity information in individual RNA molecules. In this study, we describe SeqZip, a methodology that uses RNA-templated DNA–DNA ligation to retain and compress connectivity between distant sequences within single RNA molecules. Using this assay, we test proposed coordination between distant sites of alternative exon utilization in mouse Fn1, and we characterize the extraordinary exon diversity of Drosophila melanogaster Dscam1.

DOI:http://dx.doi.org/10.7554/eLife.03700.001

A flow chart can show how an outcome can be achieved from a particular start point by breaking down an activity into a list of possible steps. Often, a flow chart contains several alternative steps, not all of which are taken every time the flow chart is used. The same can be said of genes, which are biological instructions that often contain many options within their DNA sequences.

Proteins—which perform many roles in cells—are built following the instructions contained in genes. First, the DNA sequence of the gene is copied. This produces a molecule of ribonucleic acid (RNA), which is able to move around the cell to find the machinery that can use the genetic information to make a protein. Genes and their RNA copies contain instructions with more steps—called exons—than are necessary to make a working protein, so extra exons are removed (‘spliced’) from the RNA copies. Different combinations of exons can be removed, so splicing can make different versions of the RNA called isoforms. These allow a single gene to build many different proteins. In fruit flies, for example, the different exons of the gene Dscam1 can be spliced into one of 38,016 unique RNA isoforms.

Current technology only allows researchers to deduce the sequence of RNA molecules by combining sequences recorded from short fragments of the molecule. However, before splicing, RNA molecules tend to be much longer than this, so this restricts our understanding of the RNA isoforms found in cells. Here, Roy et al. devised and tested a new method called SeqZip to solve this problem.

SeqZip uses short fragments of DNA called ligamers that can only stick to the sections of RNA that will remain after the molecule has been spliced. After splicing, the ligamers can be stuck together to make a DNA replica of the spliced RNA. The end product is at least 49 times shorter than the original RNA, so it is easier to sequence. In addition, the combinations of the ligamers in the DNA replica show which exons of a specific gene are kept and which ones are spliced out.

To test the method, Roy et al. studied a mouse gene that has six RNA isoforms. SeqZip reduced the length of the RNA by five times and made it possible to measure how frequently the different isoforms naturally arise. Roy et al. also used SeqZip to work out which isoforms of the Dscam1 gene are used at different stages in the life of fruit fly larvae. SeqZip can provide insights into how complex organisms like flies, mice, and humans have evolved with relatively few—a little over 20,000—genes in their genomes.

DOI:http://dx.doi.org/10.7554/eLife.03700.002

Revisiting the identification of canonical splice isoforms through integration of functional genomics and proteomics evidence

Canonical isoforms in different databases have been defined as the most prevalent, most conserved, most expressed, longest, or the one with the clearest description of domains or posttranslational modifications. In this article, we revisit these definitions of canonical isoforms based on functional genomics and proteomics evidence, focusing on mouse data. We report a novel functional relationship network-based approach for identifying the highest connected isoforms (HCIs). We show that 46% of these HCIs are not the longest transcripts. In addition, this approach revealed many genes that have more than one highly connected isoforms. Averaged across 175 RNA-seq datasets covering diverse tissues and conditions, 65% of the HCIs show higher expression levels than nonhighest connected isoforms at the transcript level. At the protein level, these HCIs highly overlap with the expressed splice variants, based on proteomic data from eight different normal tissues. These results suggest that a more confident definition of canonical isoforms can be made through integration of multiple lines of evidence, including HCIs defined by biological processes and pathways, expression prevalence at the transcript level, and relative or absolute abundance at the protein level. This integrative proteogenomics approach can successfully identify principal isoforms that are responsible for the canonical functions of genes.

Splicing in the human brain

It has become increasingly clear over the past decade that RNA has important functions in human cells beyond its role as an intermediate translator of DNA to protein. It is now known that RNA plays highly specific roles in pathways involved in regulatory, structural, and catalytic functions. The complexity of RNA production and regulation has become evident with the advent of high-throughput methods to study the transcriptome. Deep sequencing has revealed an enormous diversity of RNA types and transcript isoforms in human cells. The transcriptome of the human brain is particularly interesting as it contains more expressed genes than other tissues and also displays an extreme diversity of transcript isoforms, indicating that highly complex regulatory pathways are present in the brain. Several of these regulatory proteins are now identified, including RNA-binding proteins that are neuron specific. RNA-binding proteins also play important roles in regulating the splicing process and the temporal and spatial isoform production. While significant progress has been made in understanding the human transcriptome, many questions still remain regarding the basic mechanisms of splicing and subcellular localization of RNA. A long-standing question is to what extent the splicing of pre-mRNA is cotranscriptional and posttranscriptional, respectively. Recent data, including studies of the human brain, indicate that splicing is primarily cotranscriptional in human cells. This chapter describes the current understanding of splicing and splicing regulation in the human brain and discusses the recent global sequence-based analyses of transcription and splicing.

The landscape of alternative splicing in buccal mucosa squamous cell carcinoma

OBJECTIVES

Alternative splicing (AS) is a key regulatory mechanism in the process of protein synthesis generating transcriptome and proteome diversity. In this study, we attempted to identify alternative splicing in a pair of BMSCC cancer and adjacent normal tissue using RNAseq datasets and also assessed the potential of these datasets to provide quantitative measurements for alternative splicing levels.

MATERIALS AND METHODS

We performed high-throughput sequencing of buccal mucosal cancer and healthy tissue cDNA library which resulted in a transcriptome map of BMSCC cancer. RNAseq analysis was performed to assess alternative splicing complexity in cancer tissue and to search splice junction sequences that represent candidate 'new' splicing events. The splice junctions were predicted by SpliceMap software and putative assembled transcripts validated using the RT-PCR. We also analyzed the coding potential of alternative spliced candidate by HMMER.

RESULTS

We detected a total of 11 novel splice junctions derived mostly from alternate 5' splice site; including two of them which contained new translation initiation sites (TISs). We have identified novel IgG pseudogene and a fusion transcript of MEMO1 and RPS9, which were further confirmed by PCR from genomic DNA. We also found novel putative long non-coding RNA (lncRNA), which is antisense to SPINK5 gene. The coding potential of these AS variants revealed that alternative splicing caused premature termination, insertion/deletion of amino acid (s) or formation of novel N-terminus.

CONCLUSIONS

Differential splicing of these novel AS variants between cancer and adjacent normal tissue suggests their involvement in BMSCC cancer development and progression.

An exon-centric perspective

During the past ten years, remarkable progress has been made in our understanding of the complexity and regulation of alternative splicing. The generation of large datasets of quantitative alternative splicing profiling information has revealed that transcripts from at least 95% of multi-exon human genes undergo alternative splicing, and that thousands of exons in mammalian transcriptomes are subject to striking regulatory patterns. Together with advanced computational methods, these datasets have enabled the inference of a predictive code for tissue-dependent alternative splicing. This code has further provided new insight into splicing regulatory mechanisms. Collectively, these approaches are revealing the existence of discrete networks of exons that are coordinately regulated in diverse biologically normal and disease contexts. A major challenge ahead is to systematically determine the functions of exons comprising these exon networks as well as the factors and mechanisms responsible for their regulation. This perspective provides an account of progress in these areas and also discusses future avenues of exon-centric exploration.

Monitoring endoplasmic reticulum stress responsive mRNAs by RNA sequencing

Gene expression profile upon endoplasmic reticulum (ER) stress was analyzed by deep shotgun sequencing of mRNAs (DSSR) using RNAs from polysomes or cytoplasm of the HT29 cell. Two time points, 4h after tunicamycin treatment when IRE1α signaling pathway is active and 16h after the treatment when it is inactive, were used. There was a transient decrease in the proportion of shorter mRNA species (<1000bp) in polysome, while it increased transiently in the cytoplasm. Despite such an overall change and decrease in total amount of polysomes, the majority of the 6966 genes analyzed had less than 2 fold change in their expressions. We searched for the genes whose expression was elevated by 2 folds or more in both polysome and cytoplasm and confirmed the results with RT-PCR. There were 7 genes elevated only at 4h (Group I), 20 genes only at 16h (Group II) and 7 genes both at 4 and 16h (Group III). There were 3 genes involved in ribosomal RNA biogenesis in Group I and 2 genes involved mTOR control in Group III. This was consistent with the concept that the ribosome is the essential site for managing ER stress. DSSR is a useful tool for the search of candidates of ER stress responsive genes.

Alternative splicing of apoptosis-related genes in imatinib-treated K562 cells identified by exon array analysis

Imatinib is the therapeutic standard for newly diagnosed patients with chronic myeloid leukemia (CML). In these patients, imatinib has been shown to induce an apoptotic response specifically in cells expressing the oncogenic fusion protein BCR-ABL. Previous studies in our lab revealed that imatinib-induced apoptosis in K562 cells involves a shift in production of Bcl-x splice isoforms towards the pro-apoptotic Bcl-x_S splice variant. Here, we report the findings from our subsequent study to identify other apoptosis-related genes that are differentially spliced in response to imatinib treatment. Gene expression profiling of imatinib-treated K562 cells was performed by the Affymetrix GeneChip^® Human Exon 1.0 ST array, and differences in exon-level expression and alternative splicing were analyzed using the easyExon software. Detailed analysis by reverse transcription-PCR (RT-PCR) and sequencing of key genes confirmed the experimental results of the exon array. Our results suggest that imatinib treatment of K562 cells causes a transcriptional shift towards alternative splicing in a large number of apoptotic genes. The present study provides insight into the molecular character of apoptotic leukemia cells and may help to improve the mechanism of imatinib therapy in patients with CML.

Networking in a global world: establishing functional connections between neural splicing regulators and their target transcripts

Recent genome-wide analyses have indicated that almost all primary transcripts from multi-exon human genes undergo alternative pre-mRNA splicing (AS). Given the prevalence of AS and its importance in expanding proteomic complexity, a major challenge that lies ahead is to determine the functional specificity of isoforms in a cellular context. A significant fraction of alternatively spliced transcripts are regulated in a tissue- or cell-type-specific manner, suggesting that these mRNA variants likely function in the generation of cellular diversity. Complementary to these observations, several tissue-specific splicing factors have been identified, and a number of methodological advances have enabled the identification of large repertoires of target transcripts regulated by these proteins. An emerging theme is that tissue-specific splicing factors regulate coherent sets of splice variants in genes known to function in related biological pathways. This review focuses on the recent progress in our understanding of neural-specific splicing factors and their regulatory networks and outlines existing and emerging strategies for uncovering important biological roles for the isoforms that comprise these networks.

Decoding muscle alternative splicing

Muscle was one of the first tissues in which alternative splicing was widely observed. Cloning and sequencing of muscle-derived cDNAs in the early 1980's revealed that many of the abundant contractile proteins arise by alternative splicing of genes that are more widely expressed. Consequently alternative splicing events in contractile protein genes have long been used as models to dissect the mechanisms of alternative splicing. Transcriptomic and computational analyses have complemented traditional molecular analyses of alternative splicing in muscle and other tissues, illuminating the general underlying principles of coregulated splicing programs. This has culminated in the first attempt to computationally predict tissue-specific changes in splicing. Investigations of myotonic dystrophy (DM), in which CUG expansion RNA leads to misregulated splicing in muscle, have enhanced our understanding of developmentally regulated splicing and led to the development of promising therapeutic strategies based on targeting the toxic RNA repeats.

Enrichment map: a network-based method for gene-set enrichment visualization and interpretation

Background

Gene-set enrichment analysis is a useful technique to help functionally characterize large gene lists, such as the results of gene expression experiments. This technique finds functionally coherent gene-sets, such as pathways, that are statistically over-represented in a given gene list. Ideally, the number of resulting sets is smaller than the number of genes in the list, thus simplifying interpretation. However, the increasing number and redundancy of gene-sets used by many current enrichment analysis software works against this ideal.

Principal Findings

To overcome gene-set redundancy and help in the interpretation of large gene lists, we developed “Enrichment Map”, a network-based visualization method for gene-set enrichment results. Gene-sets are organized in a network, where each set is a node and edges represent gene overlap between sets. Automated network layout groups related gene-sets into network clusters, enabling the user to quickly identify the major enriched functional themes and more easily interpret the enrichment results.

Conclusions

Enrichment Map is a significant advance in the interpretation of enrichment analysis. Any research project that generates a list of genes can take advantage of this visualization framework. Enrichment Map is implemented as a freely available and user friendly plug-in for the Cytoscape network visualization software (http://baderlab.org/Software/EnrichmentMap/).

Development of a novel splice array platform and its application in the identification of alternative splice variants in lung cancer

Background

Microarrays strategies, which allow for the characterization of thousands of alternative splice forms in a single test, can be applied to identify differential alternative splicing events. In this study, a novel splice array approach was developed, including the design of a high-density oligonucleotide array, a labeling procedure, and an algorithm to identify splice events.

Results

The array consisted of exon probes and thermodynamically balanced junction probes. Suboptimal probes were tagged and considered in the final analysis. An unbiased labeling protocol was developed using random primers. The algorithm used to distinguish changes in expression from changes in splicing was calibrated using internal non-spliced control sequences. The performance of this splice array was validated with artificial constructs for CDC6, VEGF, and PCBP4 isoforms. The platform was then applied to the analysis of differential splice forms in lung cancer samples compared to matched normal lung tissue. Overexpression of splice isoforms was identified for genes encoding CEACAM1, FHL-1, MLPH, and SUSD2. None of these splicing isoforms had been previously associated with lung cancer.

Conclusions

This methodology enables the detection of alternative splicing events in complex biological samples, providing a powerful tool to identify novel diagnostic and prognostic biomarkers for cancer and other pathologies.

Alternative splicing: global insights

Following the original reports of pre-mRNA splicing in 1977, it was quickly realized that splicing together of different combinations of splice sites--alternative splicing--allows individual genes to generate more than one mRNA isoform. The full extent of alternative splicing only began to be revealed once large-scale genome and transcriptome sequencing projects began, rapidly revealing that alternative splicing is the rule rather than the exception. Recent technical innovations have facilitated the investigation of alternative splicing at a global scale. Splice-sensitive microarray platforms and deep sequencing allow quantitative profiling of very large numbers of alternative splicing events, whereas global analysis of the targets of RNA binding proteins reveals the regulatory networks involved in post-transcriptional gene control. Combined with sophisticated computational analysis, these new approaches are beginning to reveal the so-called 'RNA code' that underlies tissue and developmentally regulated alternative splicing, and that can be disrupted by disease-causing mutations.

Spliceosomes walk the line: splicing errors and their impact on cellular function

The splicing of nuclear pre-mRNAs is a fundamental process required for the expression of most metazoan genes. The majority of the approximately 25,000 genes encoded by the human genome has been shown to produce more than one kind of transcripts through alternative splicing. Alternative splicing of pre-mRNAs can lead to the production of multiple protein isoforms from a single gene, significantly enriching the proteomic diversity of higher eukaryotic organisms. Because regulation of this process determines the timing and location that a particular protein isoform is produced, changes of alternative splicing patterns have the potential to modulate many cellular activities. Consequently, pre-mRNA splicing must occur with a high degree of specificity and fidelity to ensure the appropriate expression of functional mRNAs. Here we review recent progress made in understanding the extent of alternative splicing within the human genome with particular emphasis on splicing fidelity.

Alternative splicing in lung cancer

Alterations in alternative splicing affect essential biologic processes and are the basis for a number of pathologic conditions, including cancer. In this review we will summarize the evidence supporting the relevance of alternative splicing in lung cancer. An example that illustrates this relevance is the altered balance between Bcl-xL and Bcl-xS, two splice variants of the apoptosis regulator Bcl-x. Splice modifications in cancer-related genes can be associated with modifications either in cis-acting splicing regulatory sequences or in trans-acting splicing factors. In fact, lung tumors show abnormal expression of splicing regulators such as ASF/SF2 or some members of the heterogeneous nuclear ribonucleoprotein family. The potential significance of alternative splicing as a target for lung cancer diagnosis or treatment will also be discussed.

Genome-wide identification of alternative splice forms down-regulated by nonsense-mediated mRNA decay in Drosophila

Alternative mRNA splicing adds a layer of regulation to the expression of thousands of genes in Drosophila melanogaster. Not all alternative splicing results in functional protein; it can also yield mRNA isoforms with premature stop codons that are degraded by the nonsense-mediated mRNA decay (NMD) pathway. This coupling of alternative splicing and NMD provides a mechanism for gene regulation that is highly conserved in mammals. NMD is also active in Drosophila, but its effect on the repertoire of alternative splice forms has been unknown, as has the mechanism by which it recognizes targets. Here, we have employed a custom splicing-sensitive microarray to globally measure the effect of alternative mRNA processing and NMD on Drosophila gene expression. We have developed a new algorithm to infer the expression change of each mRNA isoform of a gene based on the microarray measurements. This method is of general utility for interpreting splicing-sensitive microarrays and high-throughput sequence data. Using this approach, we have identified a high-confidence set of 45 genes where NMD has a differential effect on distinct alternative isoforms, including numerous RNA–binding and ribosomal proteins. Coupled alternative splicing and NMD decrease expression of these genes, which may in turn have a downstream effect on expression of other genes. The NMD–affected genes are enriched for roles in translation and mitosis, perhaps underlying the previously observed role of NMD factors in cell cycle progression. Our results have general implications for understanding the NMD mechanism in fly. Most notably, we found that the NMD–target mRNAs had significantly longer 3′ untranslated regions (UTRs) than the nontarget isoforms of the same genes, supporting a role for 3′ UTR length in the recognition of NMD targets in fly.

A gene can be processed into multiple mRNAs through alternative splicing. Alternative splicing increases the number of proteins encoded by the genome, but not all alternative mRNAs produce protein. Instead, some are degraded by nonsense-mediated mRNA decay (NMD), a surveillance system that was originally identified as a means of clearing the cell of mRNAs with nonsense, or stop codon, mutations. Alternative splicing that introduces early stop codons will lead to NMD, offering a way for the cell to down-regulate gene expression after a gene has been transcribed. In this paper, we have developed a new analysis method to study the combined effect of alternative splicing and degradation in the fruit fly Drosophila melanogaster using microarrays. We have found a stringently defined set of 45 genes that can be spliced either into an mRNA that encodes a protein or into an mRNA that is degraded by NMD, down-regulating the overall gene expression. The affected genes include a number that are central to the cell's regulatory processes, including translation, RNA splicing, and cell cycle progression. Our results also help shed light on how NMD determines whether a stop codon is premature, and thus whether to target an mRNA for degradation.

Genomic landscape of developing male germ cells

Spermatogenesis is a highly orchestrated developmental process by which spermatogonia develop into mature spermatozoa. This process involves many testis- or male germ cell-specific gene products whose expressions are strictly regulated. In the past decade the advent of high-throughput gene expression analytical techniques has made functional genomic studies of this process, particularly in model animals such as mice and rats, feasible and practical. These studies have just begun to reveal the complexity of the genomic landscape of the developing male germ cells. Over 50% of the mouse and rat genome are expressed during testicular development. Among transcripts present in germ cells, 40% - 60% are uncharacterized. A number of genes, and consequently their associated biological pathways, are differentially expressed at different stages of spermatogenesis. Developing male germ cells present a rich repertoire of genetic processes. Tissue-specific as well as spermatogenesis stage-specific alternative splicing of genes exemplifies the complexity of genome expression. In addition to this layer of control, discoveries of abundant presence of antisense transcripts, expressed psuedogenes, non-coding RNAs (ncRNA) including long ncRNAs, microRNAs (miRNAs) and Piwi-interacting RNAs (piRNAs), and retrogenes all point to the presence of multiple layers of expression and functional regulation in male germ cells. It is anticipated that application of systems biology approaches will further our understanding of the regulatory mechanism of spermatogenesis.

Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing

We carried out the first analysis of alternative splicing complexity in human tissues using mRNA-Seq data. New splice junctions were detected in approximately 20% of multiexon genes, many of which are tissue specific. By combining mRNA-Seq and EST-cDNA sequence data, we estimate that transcripts from approximately 95% of multiexon genes undergo alternative splicing and that there are approximately 100,000 intermediate- to high-abundance alternative splicing events in major human tissues. From a comparison with quantitative alternative splicing microarray profiling data, we also show that mRNA-Seq data provide reliable measurements for exon inclusion levels.

A global view of gene activity and alternative splicing by deep sequencing of the human transcriptome

The functional complexity of the human transcriptome is not yet fully elucidated. We report a high-throughput sequence of the human transcriptome from a human embryonic kidney and a B cell line. We used shotgun sequencing of transcripts to generate randomly distributed reads. Of these, 50% mapped to unique genomic locations, of which 80% corresponded to known exons. We found that 66% of the polyadenylated transcriptome mapped to known genes and 34% to nonannotated genomic regions. On the basis of known transcripts, RNA-Seq can detect 25% more genes than can microarrays. A global survey of messenger RNA splicing events identified 94,241 splice junctions (4096 of which were previously unidentified) and showed that exon skipping is the most prevalent form of alternative splicing.