The emerging era of genomic data integration for analyzing splice isoform function

MI-PVT: A Tool for Visualizing the Chromosome-Centric Human Proteome

We have developed the web-based Michigan Proteome Visualization Tool (MI-PVT) to visualize and compare protein expression and isoform-level function across human chromosomes and tissues (http://guanlab.ccmb.med.umich.edu/mipvt). As proof of principle, we have populated the tool with Human Proteome Map (HPM) data. We were able to observe many biologically interesting features. From the vantage point of our chromosome 17 team, for example, we found more than 300 proteins from chromosome 17 expressed in each of the 30 tissues and cell types studied, with the highest number of expressed proteins being 685 in testis. Comparisons of expression levels across tissues showed low numbers of proteins expressed in esophagus, but esophagus had 12 cytoskeletal proteins coded on chromosome 17 with very high expression (>1000 spectral counts). This customized MI-PVT should be helpful for biologists to browse and study specific proteins and protein data sets across tissues and chromosomes. Users can upload any data of interest in MI-PVT for visualization. Our aim is to integrate extensive mass-spectrometric proteomic data into the tool to facilitate finding chromosome-centric protein expression and correlation across tissues.

Computational Inferences of the Functions of Alternative/Noncanonical Splice Isoforms Specific to HER2+/ER-/PR- Breast Cancers, a Chromosome 17 C-HPP Study

This study was conducted as a part of the Chromosome-Centric Human Proteome Project (C-HPP) of the Human Proteome Organization. The main objective is to identify and evaluate functionality of a set of specific noncanonical isoforms expressed in HER2-neu positive, estrogen receptor negative (ER-), and progesterone receptor negative (PR-) breast cancers (HER2+/ER-/PR- BC), an aggressive subtype of breast cancers that cause significant morbidity and mortality. We identified 11 alternative splice isoforms that were differentially expressed in HER2+/ER-/PR- BC compared to normal mammary, triple negative breast cancer and triple positive breast cancer tissues (HER2+/ER+/PR+). We used a stringent criterion that differentially expressed noncanonical isoforms (adjusted p value < 0.05) and have to be expressed in all replicates of HER2+/ER-/PR- BC samples, and the trend in differential expression (up or down) is the same in all comparisons. Of the 11 protein isoforms, six were overexpressed in HER2+/ER-/PR- BC. We explored possible functional roles of these six proteins using several complementary computational tools. Biological processes including cell cycle events and glycolysis were linked to four of these proteins. For example, glycolysis was the top ranking functional process for DMXL2 isoform 3, with a fold change of 27 compared to just two for the canonical protein. No previous reports link DMXL2 with any metabolic processes; the canonical protein is known to participate in signaling pathways. Our results clearly indicate distinct functions for the six overexpressed alternative splice isoforms, and these functions could be specific to HER2+/ER-/PR- tumor progression. Further detailed analysis is warranted as these proteins could be explored as potential biomarkers and therapeutic targets for HER2+/ER-/PR- BC patients.

Tracks through the genome to physiological events

New Findings

What is the topic of this review?

We discuss tools available to access genome‐wide data sets that harbour cell‐specific, brain region‐specific and tissue‐specific information on exon usage for several species, including humans. In this Review, we demonstrate how to access this information in genome databases and its enormous value to physiology.

What advances does it highlight?

The sheer scale of protein diversity that is possible from complex genes, including those that encode voltage‐gated ion channels, is vast. But this choice is critical for a complete understanding of protein function in the most physiologically relevant context.

Many proteins of great interest to physiologists and neuroscientists are structurally complex and located in specialized subcellular domains, such as neuronal synapses and transverse tubules of muscle. Genes that encode these critical signalling molecules (receptors, ion channels, transporters, enzymes, cell adhesion molecules, cell–cell interaction proteins and cytoskeletal proteins) are similarly complex. Typically, these genes are large; human Dystrophin (DMD) encodes a cytoskeletal protein of muscle and it is the largest naturally occurring gene at a staggering 2.3 Mb. Large genes contain many non‐coding introns and coding exons; human Titin (TTN), which encodes a protein essential for the assembly and functioning of vertebrate striated muscles, has over 350 exons and consequently has an enormous capacity to generate different forms of Titin mRNAs that have unique exon combinations. Functional and pharmacological differences among protein isoforms originating from the same gene may be subtle but nonetheless of critical physiological significance. Standard functional, immunological and pharmacological approaches, so useful for characterizing proteins encoded by different genes, typically fail to discriminate among splice isoforms of individual genes. Tools are now available to access genome‐wide data sets that harbour cell‐specific, brain region‐specific and tissue‐specific information on exon usage for several species, including humans. In this Review, we demonstrate how to access this information in genome databases and its enormous value to physiology.

BreakSeek: a breakpoint-based algorithm for full spectral range INDEL detection

Although recent developed algorithms have integrated multiple signals to improve sensitivity for insertion and deletion (INDEL) detection, they are far from being perfect and still have great limitations in detecting a full size range of INDELs. Here we present BreakSeek, a novel breakpoint-based algorithm, which can unbiasedly and efficiently detect both homozygous and heterozygous INDELs, ranging from several base pairs to over thousands of base pairs, with accurate breakpoint and heterozygosity rate estimations. Comprehensive evaluations on both simulated and real datasets revealed that BreakSeek outperformed other existing methods on both sensitivity and specificity in detecting both small and large INDELs, and uncovered a significant amount of novel INDELs that were missed before. In addition, by incorporating sophisticated statistic models, we for the first time investigated and demonstrated the importance of handling false and conflicting signals for multi-signal integrated methods.

Proteomic Validation of Transcript Isoforms, Including Those Assembled from RNA-Seq Data

Human proteome analysis now requires an understanding of protein isoforms. We recently published the PG Nexus pipeline, which facilitates high confidence validation of exons and splice junctions by integrating genomics and proteomics data. Here we comprehensively explore how RNA-seq transcriptomics data, and proteomic analysis of the same sample, can identify protein isoforms. RNA-seq data from human mesenchymal (hMSC) stem cells were analyzed with our new TranscriptCoder tool to generate a database of protein isoform sequences. MS/MS data from matching hMSC samples were then matched against the TranscriptCoder-derived database, along with Ensembl and the neXtProt database. Querying the TranscriptCoder-derived or Ensembl database could unambiguously identify ∼450 protein isoforms, with isoform-specific proteotypic peptides, including candidate hMSC-specific isoforms for the genes DPYSL2 and FXR1. Where isoform-specific peptides did not exist, groups of nonisoform-specific proteotypic peptides could specifically identify many isoforms. In both the above cases, isoforms will be detectable with targeted MS/MS assays. Unfortunately, our analysis also revealed that some isoforms will be difficult to identify unambiguously as they do not have peptides that are sufficiently distinguishing. We covisualize mRNA isoforms and peptides in a genome browser to illustrate the above situations. Mass spectrometry data is available via ProteomeXchange (PXD001449).

Do housekeeping genes exist?

The searching of human housekeeping (HK) genes has been a long quest since the emergence of transcriptomics, and is instrumental for us to understand the structure of genome and the fundamentals of biological processes. The resolved genes are frequently used in evolution studies and as normalization standards in quantitative gene-expression analysis. Within the past 20 years, more than a dozen HK-gene studies have been conducted, yet none of them sampled human tissues completely. We believe an integration of these results will help remove false positive genes owing to the inadequate sampling. Surprisingly, we only find one common gene across 15 examined HK-gene datasets comprising 187 different tissue and cell types. Our subsequent analyses suggest that it might not be appropriate to rigidly define HK genes as expressed in all tissue types that have diverse developmental, physiological, and pathological states. It might be beneficial to use more robustly identified HK functions for filtering criteria, in which the representing genes can be a subset of genome. These genes are not necessarily the same, and perhaps need not to be the same, everywhere in our body.

Isoform-level brain expression profiling of the spermidine/spermine N1-Acetyltransferase1 (SAT1) gene in major depression and suicide

Low brain expression of the spermidine/spermine N-1 acetyltransferase (SAT1) gene, the rate-limiting enzyme involved in catabolism of polyamines that mediate the polyamine stress response (PSR), has been reported in depressed suicides. However, it is unknown whether this effect is associated with depression or with suicide and whether all or only specific isoforms expressed by SAT1, such as the primary 171 amino acid protein-encoding transcript (SSAT), or an alternative splice variant (SSATX) that is involved in SAT1 regulated unproductive splicing and transcription (RUST), are involved. We applied next generation sequencing (RNA-seq) to assess gene-level, isoform-level, and exon-level SAT1 expression differences between healthy controls (HC, N = 29), DSM-IV major depressive disorder suicides (MDD-S, N = 21) and MDD non-suicides (MDD, N = 9) in the dorsal lateral prefrontal cortex (Brodmann Area 9, BA9) of medication-free individuals postmortem. Using small RNA-seq, we also examined miRNA species putatively involved in SAT1 post-transcriptional regulation. A DSM-IV diagnosis was made by structured interview. Toxicology and history ruled out recent psychotropic medication. At the gene-level, we found low SAT1 expression in both MDD-S (vs. HC, p = 0.002) and MDD (vs. HC, p = 0.002). At the isoform-level, reductions in MDD-S (vs. HC) were most pronounced in four transcripts including SSAT and SSATX, while reductions in MDD (vs. HC) were pronounced in three transcripts, one of which was reduced in MDD relative to MDD-S (all p < 0.1 FDR corrected). We did not observe evidence for differential exon-usage (i.e. splicing) nor differences in miRNA expression. Results replicate the finding of low SAT1 brain expression in depressed suicides in an independent sample and implicate low SAT1 brain expression in MDD independent of suicide. Low expressions of both SSAT and SATX isoforms suggest that shared transcriptional mechanisms involved in RUST may account for low SAT1 brain expression in depressed suicides. Future studies are required to understand the functions and regulation of SAT1 isoforms, and how they relate to the pathogenesis of MDD and suicide.

MIsoMine: a genome-scale high-resolution data portal of expression, function and networks at the splice isoform level in the mouse

Products of multiexon genes, especially in higher organisms, are a mixture of isoforms with different or even opposing functions, and therefore need to be treated separately. However, most studies and available resources such as Gene Ontology provide only gene-level function annotations, and therefore lose the differential information at the isoform level. Here we report MIsoMine, a high-resolution portal to multiple levels of functional information of alternatively spliced isoforms in the mouse. This data portal provides tissue-specific expression patterns and co-expression networks, along with such previously published functional genomic data as protein domains, predicted isoform-level functions and functional relationships. The core utility of MIsoMine is allowing users to explore a preprocessed, quality-controlled set of RNA-seq data encompassing diverse tissues and cell lineages. Tissue-specific co-expression networks were established, allowing a 2D ranking of isoforms and tissues by co-expression patterns. The results of the multiple isoforms of the same gene are presented in parallel to facilitate direct comparison, with cross-talking to prioritized functions at the isoform level. MIsoMine provides the first isoform-level resolution effort at genome-scale. We envision that this data portal will be a valuable resource for exploring functional genomic data, and will complement the existing functionalities of the mouse genome informatics database and the gene expression database for the laboratory mouse.

Database URL: http://guanlab.ccmb.med.umich.edu/misomine/

Actionable clinical decisions based on comprehensive genomic evaluation in asymptomatic adults

Whole-exome sequencing (WES) arises as a new approach in diagnosing individuals affected by multigenic and complex phenotypes. Herein, we aim to examine whether WES is useful in screening asymptomatic individuals for actionable interventions, which has not yet been established. Twenty-five healthy adults underwent WES, bioinformatics, and manual curation of their exomes. Six participants (24%) harbored significant, management-changing variants in cancer predisposition genes, American College of Medical Genetics, and genomics reportable cardiac diseases and pharmacogenomic biomarkers that have led to clinical recommendations and interventions. Furthermore, more than 80% of the participants (21) carried 1–3 genetic variants with an associated clinical guideline for an altered drug dosing or administration based on the FDA’s table of pharmacogenomics. These results support WES potential not only to answer specific diagnostic questions presented by the relevant personal and/or family history but also to uncover clinically important genetic findings unrelated to the primary indication for sequencing.

Human genes with a greater number of transcript variants tend to show biological features of housekeeping and essential genes

Human genes with a greater number of transcript variants are more likely to play functionally important roles such as cellular maintenance and survival.

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.

GeneFriends: a human RNA-seq-based gene and transcript co-expression database

Co-expression networks have proven effective at assigning putative functions to genes based on the functional annotation of their co-expressed partners, in candidate gene prioritization studies and in improving our understanding of regulatory networks. The growing number of genome resequencing efforts and genome-wide association studies often identify loci containing novel genes and there is a need to infer their functions and interaction partners. To facilitate this we have expanded GeneFriends, an online database that allows users to identify co-expressed genes with one or more user-defined genes. This expansion entails an RNA-seq-based co-expression map that includes genes and transcripts that are not present in the microarray-based co-expression maps, including over 10 000 non-coding RNAs. The results users obtain from GeneFriends include a co-expression network as well as a summary of the functional enrichment among the co-expressed genes. Novel insights can be gathered from this database for different splice variants and ncRNAs, such as microRNAs and lincRNAs. Furthermore, our updated tool allows candidate transcripts to be linked to diseases and processes using a guilt-by-association approach. GeneFriends is freely available from http://www.GeneFriends.org and can be used to quickly identify and rank candidate targets relevant to the process or disease under study.

Alternative applications for distinct RNA sequencing strategies

Recent advances in RNA library preparation methods, platform accessibility and cost efficiency have allowed high-throughput RNA sequencing (RNAseq) to replace conventional hybridization microarray platforms as the method of choice for mRNA profiling and transcriptome analyses. RNAseq is a powerful technique to profile both long and short RNA expression, and the depth of information gained from distinct RNAseq methods is striking and facilitates discovery. In addition to expression analysis, distinct RNAseq approaches also allow investigators the ability to assess transcriptional elongation, DNA variance and exogenous RNA content. Here we review the current state of the art in transcriptome sequencing and address epigenetic regulation, quantification of transcription activation, RNAseq output and a diverse set of applications for RNAseq data. We detail how RNAseq can be used to identify allele-specific expression, single-nucleotide polymorphisms and somatic mutations and discuss the benefits and limitations of using RNAseq to monitor DNA characteristics. Moreover, we highlight the power of combining RNA- and DNAseq methods for genomic analysis. In summary, RNAseq provides the opportunity to gain greater insight into transcriptional regulation and output than simply miRNA and mRNA profiling.