Biology subjects

McIntyre, L.

Publications and source records attributed to McIntyre, L..

At least 19 recordsLinked to original sources

bioRxiv2026

Sex and Alternative Splicing in Disease: a meta-analytic approach to identify interactions

How cell type, sex and disease interact and affect gene expression and splicing is an important, but complicated question. Visualizing and testing specific hypotheses around these complex interactions is an important first step to identifying molecular components underpinning complex disease. Using a meta-analytical framework, we develop an analytical path for identifying testable molecular hypotheses of complex interactions between splicing, sex, disease and cell type. We focus on type 1 diabetes (T1D) but the approach is generalizable to any complex disease with defined candidate loci. Previous studies report T1D-associated splicing in candidate genes, differences in disease effects across immune cell types, sex effects on splicing and cell-type-specific splicing. However, identifying and interpreting complex interactions between sex, splicing and disease are challenging. Here we demonstrate how a gene expression study of T1D, designed to evaluate these interactions can be analyzed in a straightforward manner. We find that sex-dependent T1D-associated splicing is markedly more prevalent in CD4 T cells than in CD8 T cells, affecting 72% of T1D candidate genes in CD4 cells compared to 30% in CD8 cells. We pinpoint exons whose rate of inclusion is affected by the interaction of sex and disease. We use long-read RNAseq to identify novel intron retention events and splice sites which are quantified with short-reads leading to a richer description of the regulatory impact of T1D on alternative splicing. We identify a set of candidate isoforms for follow-up molecular studies in BACH2, a transcription factor known to be relevant in disease prevalence.

genomics↗

bioRxiv2026

A framework for identifying transcript orthologs: the evolution of sex bias in alternative transcript structure in Drosophila

BackgroundRecent advances in long read technologies provide an unprecedented opportunity to study transcript evolution. However, comparative evolutionary studies, even in Drosophila, are limited by inconsistent and incomplete annotation, and the lack of annotated transcript homology. ResultsIn this study of five species spanning 28 million years (D. melanogaster, D. simulans, D. yakuba, D. santomea and D. serrata), we infer transcript homology using reciprocal liftover, and orthology using network analyses, with data validation from long read RNA-seq of male and female head tissue. We build the first genus level annotation, with 15,996 genes and 56,370 transcripts. Expressed transcripts are conserved, 73% of transcript orthologs are detected in all species. Even the improved annotation underestimates the number of genes with alternative transcripts, with 75% of genes expressing multiple structurally diverse transcripts. In a replicated quantitative evaluation of [~]10,000 genes, both male and female-biased transcripts are expressed in 410 (D. melanogaster), 608 (D. simulans), and 493 (D. serrata) genes and in 118 orthologous genes in the D. melanogaster - D. simulans species pair, indicating greater potential for resolution of sexual conflict by alternative transcription than previously appreciated. We identified 605 transcript orthologs conserved for sex bias in the D. melanogaster-D. simulans species pair and of these, 22 male and 19 female-biased transcripts were conserved in sex bias with the outgroup D. serrata, including transcripts of genes involved in brain development, Sxl target Glutamine synthetase 2 and ciboulot. ConclusionsConserved alternative transcripts suggest that transcriptional diversity is a pervasive driver of the evolution of functional diversity.

genomics↗

bioRxiv2025

The promise of long-read RNA-seq: reducing bias in analyses of allele imbalance

Inaccurate allele and gene expression counts due to map bias and genome ambiguity lead to high false positive and false negative rates in studies of allelic imbalance. We demonstrate that long read RNA-seq and straightforward quality control measures can be used to reduce bias in allele counts in case studies from four species: Drosophila melanogaster, a diploid insect; Solanum tuberosum, an autopolyploid plant; Pongo abelii, a highly heterozygous diploid primate, and Homo sapiens. We recommend 1) mapping to a personalized genome to increase the number of allele assignments 2) tracking multimapping reads and tuning mapping parameters to ensure accurate allele and gene expression counts and 3) evaluating apparent extreme allele bias to identify errors in genome assembly and annotation. We show that these steps can be executed in a straightforward manner and recommend tools for each step.

genetics↗

bioRxiv2025

Lipid Nanoparticle Delivery of Mesenchymal Stromal Cell-Derived microRNA 187-3p as a First-in-Class Therapy for Myocardial Dysfunction in Sepsis

BackgroundSepsis-induced myocardial dysfunction is a common and critical complication of sepsis. Extracellular vesicles (EVs) from clonally expanded immortalized mesenchymal stromal cells (ciMSCs) contain microRNAs that may be exploited as therapy. MethodsIn mouse models of septic cardiomyopathy induced by caecum ligation and puncture, cardiac function was determined by invasive and echocardiographic assessment. Primary cardiomyocytes derived from foetal murine and human adult ventricular tissue, as well as murine hearts were used for mechanistic studies. Studies using post-mortem human hearts or patient plasma, and clinical and echocardiographic measurements were used to establish translational relevance. ResultsIn preclinical models of sepsis, intravenous administration of either MSCs or ciMSC-EVs, given after the induction of sepsis, prevented a decrease in myocardial ejection fraction, ventricular inflammation, and mortality compared to placebo or platelet-derived control EVs. EV-microRNA sequencing identified enrichment for microRNA-187a-3p (miR-187) in ciMSC-EVs. miR-187 is anti-inflammatory; with interleukin-6 (IL-6) as its major target. Intravenous delivery of lipid nanoparticle (LNP) encapsulated miR-187 improved cardiac function, reduced inflammation, and enhanced survival of septic mice. In cardiomyocytes and in murine hearts, LNP-miR-187 reduces inflammation and expression of myocardial transcription factors linked to fetal gene reactivation in failing septic hearts. In human septic hearts, low circulating miR-187 levels correlate with reduced cardiac function and high sequential organ failure assessment (SOFA) scores. ConclusionThese findings support the development of first-in-class, cell-free, miRNA-based therapy as a novel approach to treat sepsis-induced cardiomyopathy to address a critical gap in sepsis care. One Sentence SummarymiR-based therapy for sepsis The Clinical PerspectiveA. What is NEW? Sepsis accounts for 1 in 5 deaths worldwide. Here, we demonstrate that sepsis-induced myocardial dysfunction represents a discrete, targetable sepsis-trait -- a distinct biological abnormality characterized by cardiomyocyte inflammation and fetal gene reactivation. This component contributes to the propagation of organ dysfunction and overall mortality and may respond to focused epigenetic-based interventions. B. What are the Clinical implications? Currently, there are no effective treatments to reduce, limit, or reverse the immune dysfunction component of sepsis that contributes to multiorgan failure, such as sepsis-induced cardiomyopathy. We identify miR-187 as a clinically relevant post-transcriptional regulator of cardiac inflammation and cardiomyocyte gene expression. Intravenous delivery of miR-187 encapsulated in a lipid nanoparticle (LNP) represents a fundamentally distinct, effective and pathogen-agnostic approach to correcting sepsis-induced cardiac dysfunction through modulation of cardiomyocyte inflammatory and metabolic pathways.

molecular biology↗

bioRxiv2024

SQANTI-reads: a tool for the quality assessment of long read data in multi-sample lrRNA-seq experiments.

SQANTI-reads leverages SQANTI3, a tool for the analysis of the quality of transcript models, to develop a read-level quality control framework for replicated long-read RNA-seq experiments. The number and distribution of reads, as well as the number and distribution of unique junction chains (transcript splicing patterns), in SQANTI3 structural categories are informative of raw data quality. Multi-sample visualizations of QC metrics are presented by experimental design factors to identify outliers. We introduce new metrics for 1) the identification of potentially under-annotated genes and putative novel transcripts and for 2) quantifying variation in junction donors and acceptors. We applied SQANTI-reads to two different datasets, a Drosophila developmental experiment and a multi-platform dataset from the LRGASP project and demonstrate that the tool effectively reveals the impact of read coverage on data quality, and readily identifies strong and weak splicing sites. SQANTI-reads is open source and available for download at GitHub.

bioinformatics↗

bioRxiv2023

Inter-species gene flow drives ongoing evolution of Streptococcus pyogenes and Streptococcus dysgalactiae subsp. equisimilis

Streptococcus dysgalactiae subsp. equisimilis (SDSE) is an emerging cause of human infection with invasive disease incidence and clinical manifestations comparable to the closely related species, Streptococcus pyogenes. Through systematic genomic analyses of 501 disseminated SDSE strains, we demonstrate extensive overlap between the genomes of SDSE and S. pyogenes. More than 75% of core genes are shared between the two species with one third demonstrating evidence of cross-species recombination. Twenty-five percent of mobile genetic element (MGE) clusters and 16 of 55 SDSE MGE insertion regions were found across species. Assessing potential cross-protection from leading S. pyogenes vaccine candidates on SDSE, 12/34 preclinical vaccine antigen genes were shown to be present in >99% of isolates of both species. Relevant to possible vaccine evasion, six vaccine candidate genes demonstrated evidence of inter-species recombination. These findings demonstrate previously unappreciated levels of genomic overlap between these closely related pathogens with implications for streptococcal pathobiology, disease surveillance and prevention.

microbiology↗

bioRxiv2023

DNA methylation responses to stress across different plant species

O_LIChanges in environments trigger plant DNA methylation responses, potentially modulating stress responses. Studies on stress-induced DNA methylation typically focus on single species, limiting our understanding of what are general and specific responses between species. C_LIO_LIUsing reduced-representation bisulfite sequencing epiGBS, we compared DNA methylation stress-responses across seven plant species. Because methylation can be targeted at transposable elements (TEs) and because environmental plasticity may be particularly relevant in asexual species, we hypothesize that genome size and reproduction mode explain differences in methylation responses between species. C_LIO_LIWe show that enrichment of environmentally-induced methylation responses in genes and TEs is a general feature across plant species. While previous studies have emphasized methylation responses in CHH-cytosines, we observed that cytosines in all sequence contexts (CG, CHG, CHH) are equally likely to respond to stress. Larger-genome species showed a higher proportion of stress-responding cytosines, and asexual species showed more cytosines with a strong methylation response to stress than sexually responding species. C_LIO_LIOur study highlights the role of TEs in methylome plasticity and identifies causes of variation in methylome plasticity. This provides guidance to extrapolating results from models to other plant species, and may contribute to better understanding of functionality of the response. C_LI

plant biology↗

bioRxiv2023

Sex-biased expression is associated with chromatin state in D. melanogaster and D. simulans

We propose a new model for the association of chromatin state and sex-bias in expression. We hypothesize enrichment of open chromatin in the sex where we see expression bias (OS) and closed chromatin in the opposite sex (CO). In this study of D. melanogaster and D. simulans head tissue, sex-bias in expression is associated with H3K4me3 (open mark) in males for male-biased genes and in females for female-biased genes in both species. Sex-bias in expression is also largely conserved in direction and magnitude between the two species on the X and autosomes. In male-biased orthologs, the sex-bias ratio is more divergent between species if both species have H3K27me2me3 marks in females compared to when either or neither species has H3K27me2me3 in females. H3K27me2me3 marks in females are associated with male-bias in expression on the autosomes in both species, but on the X only in D. melanogaster. In female-biased orthologs the relationship between the species for the sex-bias ratio is similar regardless of the H3K27me2me3 marks in males. Female-biased orthologs are more similar in the ratio of sex-bias than male-biased orthologs and there is an excess of male-bias in expression in orthologs that gain/lose sex-bias. There is an excess of male-bias in sex-limited expression in both species suggesting excess male-bias is due to rapid evolution between the species. The X chromosome has an enrichment in male-limited H3K4me3 in both species and an enrichment of sex-bias in expression compared to the autosomes.

evolutionary biology↗

bioRxiv2022

Shifts in isoform usage underlie transcriptional differences in regulatory T cells in type 1 diabetes

Genome-wide association studies have identified numerous loci with allelic associations to Type 1 Diabetes (T1D) risk. Most disease-associated variants are enriched in regulatory sequences active in lymphoid cell types, suggesting that lymphocyte gene expression is altered in T1D. We assayed gene expression between T1D cases and healthy controls in two autoimmunity-relevant lymphocyte cell types, memory CD4+/CD25+ T-regulatory cells (Treg) and memory CD4+/CD25- T-cells, using a splicing event-based approach to characterize tissue-specific transcriptomes. Limited differences in isoform usage between T1D cases and controls were observed in memory CD4+/CD25- T-cells. In Tregs, 553 genes demonstrated differences in isoform usage between cases and controls, particularly RNA recognition and splicing factor genes. Many of these genes are regulated by the variable inclusion of exons that can trigger nonsense mediated decay. Our results suggest that dysregulation of gene expression, through shifts in alternative splicing in Tregs, contributes to T1D etiology.

genetics↗

bioRxiv2022

Ion Mobility for Unknown Metabolite Identification: Hope or Hype?

Ion mobility (IM) spectrometry provides semi-orthogonal data to mass spectrometry (MS), showing promise for identifying unknown metabolites in complex non-targeted metabolomics datasets. While current literature has showcased IM-MS for identifying unknowns under near ideal circumstances, less work has been conducted to evaluate the performance of this approach in metabolomics studies involving highly complex samples with difficult matrices. Here, we present a workflow incorporating de novo molecular formula annotation and MS/MS structure elucidation using SIRIUS 4 with experimental IM collision cross-section (CCS) measurements and machine learning CCS predictions to identify differential unknown metabolites in mutant strains of Caenorhabditis elegans. For many of those ion features this workflow enabled the successful filtering of candidate structures generated by in silico MS/MS predictions, though in some cases annotations were challenged by significant hurdles in instrumentation performance and data analysis. While for 37% of differential features we were able to successfully collect both MS/MS and CCS data, fewer than half of these features benefited from a reduction in the number of possible candidate structures using CCS filtering due to poor matching of the machine learning training sets, limited accuracy of experimental and predicted CCS values, and lack of candidate structures resulting from the MS/MS data. When using a CCS error cutoff of {+/-}3%, an average 28% of candidate structures could be successfully filtered. Herein, we identify and describe the bottlenecks and limitations associated with the identification of unknowns in non-targeted metabolomics using IM-MS to focus and provide insight on areas requiring further improvement.

biochemistry↗

bioRxiv2021

The evolution of splicing: transcriptome complexity and transcript distances implemented in TranD

Alternative splicing contributes to organismal complexity. Comparing transcripts between and within species is an important first step toward understanding questions about how evolution of transcript structure changes between species and contributes to sub-functionalization. These questions are confounded with issues of data quality and availability. The recent explosion of affordable long read sequencing of mRNA has considerably widened the ability to study transcriptional variation in non-model species. In this work, we develop a computational framework that uses nucleotide resolution distance metrics to compare transcript models for structural phenotypes: total transcript length, intron retention, donor/acceptor site variation, alternative exon cassettes, alternative 5/3 UTRs are each scored qualitatively and quantitatively in terms of number of nucleotides. For a single annotation file, all differences among transcripts within a gene are summarized and transcriptome-level complexity metrics: number of variable nucleotides, unique exons per gene, exons per transcript, and transcripts per gene are calculated. To compare two transcriptomes on the same co-ordinates, a weighted total distance between pairs of transcripts for the same gene is calculated. The weight function proposed has larger penalties for intron retention and exon skipping than alternative donor/acceptor sites. Minimum distances can be used to identify both transcript pairs and transcripts missing structural elements in either of the two annotations. This enables a broad range of functionality from comparing sister species to comparing different methods of building and summarizing transcriptomes. Importantly, the philosophy here is to output metrics, enabling others to explore the nucleotide-level distance metrics. Single transcriptome annotation summaries and pairwise comparisons are implemented in a new tool, TranD, distributed as a PyPi package and in the open-source web-based Galaxy (www.galaxyproject.org) platform.

genomics↗

bioRxiv2021

Ozone sensitivity of diverse maize genotypes is associated with differences in gene regulation, not gene content

The maize pangenome has demonstrate large amounts of presence/absence variation and it has been hypothesized that presence/absence variation contributes to stress response. To uncover whether the observed genetic variation in physiological response to elevated ozone (a secondary air pollutant that causes significant crop yield losses) concentration is due to variation in genic content, and/or variation in gene expression, we examine the impact of sustained elevated ozone concentration on the leaf tissue from 5 diverse maize inbred genotypes (B73, Mo17, Hp301, C123, NC338). Analysis of long reads from the transcriptomes of the 10 conditions found expressed genes in the leaf are part of the shared genome, with 94.5% of expressed genes from syntenic loci. Quantitative analysis of short reads from 120 plants (twelve from each condition) found limited transcriptional response to sustained ozone stress in the ozone resistant B73 genotype (151 genes), while more than 3,300 genes were significantly differentially expressed in the more sensitive NC338 genotype. The genes underpinning the divergence of B73 from the other 4 genotypes implicates ethylene signaling consistent with some findings in Arabidopsis. For the 82 of the 83 genes differentially expressed among all 5 genotypes and the 788 of 789 genes differentially expressed in 4 genotypes (excluding B73) in sensitivity to ozone is associated with oxidative stress tolerance being associated with a weaker response to a reactive oxygen species (ROS) signal and suggests that genetic variation in downstream processes is key to ozone tolerance.

genomics↗

bioRxiv2020

GAIT-GM: Galaxy tools for modeling metabolite changes as a function of gene expression

Galaxy is a user-friendly platform with a strong development community and a rich set of tools for omics data analysis. While multi-omics experiments are becoming popular, tools for multi-omics data analysis are poorly represented in this platform. Here we present GAIT-GM, a set of new Galaxy tools for integrative analysis of gene expression and metabolomics data. In the Annotation Tool, features are mapped to KEGG pathway using a text mining approach to increase the number of mapped metabolites. Several interconnected databases are used to maximally map gene IDs across species. In the Integration Tool, changes in metabolite levels are modelled as a function of gene expression in a flexible manner. Both unbiased exploration of relationships between genes and metabolites and biologically informed models based on pathway data are enabled. The GAIT-GM tools are freely available at https://github.com/SECIMTools/gait-gm.

bioinformatics↗

bioRxiv2020

Testcrosses are an efficient strategy for identifying cis regulatory variation: Bayesian analysis of allele specific expression (BASE)

Allelic imbalance (AI) occurs when alleles in a diploid individual are differentially expressed and indicates cis acting regulatory variation. What is the distribution of allelic effects in a natural population? Are all alleles the same? Are all alleles distinct? Tests of allelic effect are performed by crossing individuals and comparing expression between alleles directly in the F1. However, a crossing scheme that compares alleles pairwise is a prohibitive cost for more than a handful of alleles as the number of crosses is at least (n2-n)/2 where n is the number of alleles. We show here that a testcross design followed by a hypothesis test of AI between testcrosses can be used to infer differences between non-tester alleles, allowing n alleles to be compared with n crosses. Using a mouse dataset where both testcrosses and direct comparisons have been performed, we show that [~]75% of the predicted differences between non-tester alleles are validated in a background of [~]10% differences in AI. The testing for AI involves several complex bioinformatics steps. BASE is a complete bioinformatics pipeline that incorporates state-of-the-art error reduction techniques and a flexible Bayesian approach to estimating AI and formally comparing levels of AI between conditions. The modular structure of BASE has been packaged in Galaxy, made available in Nextflow and sbatch. (https://github.com/McIntyre-Lab/BASE_2020). In the mouse data, the direct test identifies more cis effects than the testcross. Cis-by-trans interactions with trans-acting factors on the X contributing to observed cis effects in autosomal genes in the direct cross remains a possible explanation for the discrepancy.

bioinformatics↗

bioRxiv2020

Prophage exotoxins enhance colonization fitness in epidemic scarlet fever-causing Streptococcus pyogenes

The re-emergence of scarlet fever poses a new global public health threat. The capacity of North-East Asian serotype M12 (emm12) Streptococcus pyogenes (group A Streptococcus, GAS) to cause scarlet fever has been linked epidemiologically to the presence of novel prophages, including prophage {Phi}HKU.vir encoding the secreted superantigens SSA and SpeC and the DNase Spd1. Here we report the comprehensive molecular characterization of {Phi}HKU.vir-encoded exotoxins. We demonstrate that streptolysin O (SLO)-induced glutathione efflux from host cellular stores is a previously unappreciated GAS virulence mechanism that promotes SSA release and activity, representing the first description of a thiol-activated bacterial superantigen. Spd1 is required for optimal growth in human blood, confers resistance to neutrophil killing, and degrades neutrophil extracellular traps (NETs). Investigating single, double and triple isogenic knockout mutants of the {Phi}HKU.vir-encoded exotoxins, we find that SpeC and Spd1 act synergistically to facilitate nasopharyngeal colonization in a mouse model. These results offer insight into the etiology and pathogenesis of scarlet fever-causing GAS mediated by phage {Phi}HKU.vir exotoxins.

microbiology↗

bioRxiv2020

A role for glutathione in buffering excess intracellular copper in Streptococcus pyogenes

Copper (Cu) is an essential metal for bacterial physiology but in excess it is bacteriotoxic. To limit Cu levels in the cytoplasm, most bacteria possess a transcriptionally-responsive system for Cu export. In the Gram-positive human pathogen Streptococcus pyogenes (Group A Streptococcus, GAS), this system is encoded by the copYAZ operon. In this study, we demonstrate that the site of GAS infection in vivo represents a Cu-rich environment but inactivation of the copA Cu efflux gene does not reduce virulence in a mouse model of invasive disease. In vitro, Cu treatment leads to multiple observable phenotypes, including defects in growth and viability, decreased fermentation, inhibition of glyceraldehyde 3-phosphate dehydrogenase (GapA) activity, and misregulation of metal homeostasis, likely as a consequence of mismetalation of non-cognate metal-binding sites. Surprisingly, the onset of these effects is delayed by [~]4 h even though expression of copZ is upregulated immediately upon exposure to Cu. We further show that the onset of all phenotypes coincides with depletion of intracellular glutathione (GSH). Supplementation with extracellular GSH replenishes the intracellular pool of this thiol and suppresses all the observable effects of Cu treatment. Our results indicate that GSH contributes to buffering of excess intracellular Cu when the transcriptionally-responsive Cu export system is overwhelmed. Thus, while the copYAZ operon is responsible for Cu homeostasis, GSH has a role in Cu tolerance that allows bacteria to maintain metabolism even in the presence of an excess of this metal ion. This study advances fundamental understanding of Cu handling in the bacterial cytoplasm. IMPORTANCEThe control of intracellular metal availability is fundamental to bacterial physiology. In the case of copper (Cu), it is established that rising intracellular Cu levels eventually fill the metal-sensing site of the endogenous Cu-sensing transcriptional regulator, which in turn induces transcription of a copper export pump. This response caps intracellular Cu availability below a well-defined threshold and prevents Cu toxicity. Glutathione, abundant in many bacteria, is known to bind Cu and is long assumed to contribute to bacterial Cu handling. However, there is some ambiguity since neither its biosynthesis nor uptake is Cu-regulated. Furthermore, there is little experimental support for this role of glutathione beyond measurement of the effect of Cu on growth of glutathione-deficient mutants. Our work with Group A Streptococcus provides new evidence that glutathione increases the threshold of intracellular Cu availability that can be tolerated by bacteria and thus advances fundamental understanding of bacterial Cu handling.

microbiology↗

bioRxiv2020

Phylogenomic resolution of sea spider diversification through integration of multiple data classes

Despite significant advances in invertebrate phylogenomics over the past decade, the higher-level phylogeny of Pycnogonida (sea spiders) remains elusive. Due to the inaccessibility of some small-bodied lineages, few phylogenetic studies have sampled all sea spider families. Previous efforts based on a handful of genes have yielded unstable tree topologies. Here, we inferred the relationships of 89 sea spider species using targeted capture of the mitochondrial genome, 56 conserved exons, 101 ultraconserved elements, and three nuclear ribosomal genes. We inferred molecular divergence times by integrating morphological data for fossil species to calibrate 15 nodes in the arthropod tree of life. This integration of data classes resolved the basal topology of sea spiders with high support. The enigmatic family Austrodecidae was resolved as the sister group to the remaining Pycnogonida and the small-bodied family Rhynchothoracidae as the sister group of the robust-bodied family Pycnogonidae. Molecular divergence time estimation recovered a basal divergence of crown group sea spiders in the Ordovician. Comparison of diversification dynamics with other marine invertebrate taxa that originated in the Paleozoic suggests that sea spiders and some crustacean groups exhibit resilience to mass extinction episodes, relative to mollusk and echinoderm lineages.

evolutionary biology↗

bioRxiv2019

tappAS: A comprehensive computational framework for the analysis of the functional impact of differential splicing

Traditionally, the functional analysis of gene expression data has used pathway and network enrichment algorithms. These methods are usually gene rather than transcript centric and hence fall short to unravel functional roles associated to posttranscriptional regulatory mechanisms such as Alternative Splicing (AS) and Alternative PolyAdenylation (APA), jointly referred here as Alternative Transcript Processing (AltTP). Moreover, short-read RNA-seq has serious limitations to resolve full-length transcripts, further complicating the study of isoform expression. Recent advances in long-read sequencing open exciting opportunities for studying isoform biology and function. However, there are no established bioinformatics methods for the functional analysis of isoform-resolved transcriptomics data to fully leverage these technological advances. Here we present a novel framework for Functional Iso-Transcriptomics analysis (FIT). This framework uses a rich isoform-level annotation database of functional domains, motifs and sites -both coding and non-coding- and introduces novel analysis methods to interrogate different aspects of the functional relevance of isoform complexity. The Functional Diversity Analysis (FDA) evaluates the variability at the inclusion/exclusion of functional domains across annotated transcripts of the same gene. Parameters can be set to evaluate if AltTP partially or fully disrupts functional elements. FDA is a measure of the potential of a multiple isoform transcriptome to have a functional impact. By combining these functional labels with expression data, the Differential Analysis Module evaluates the relative contribution of transcriptional (i.e. gene level) and post-transcriptional (i.e. transcript/protein levels) regulation on the biology of the system. Measures of isoform relevance such as Minor Isoform Filtering, Isoform Switching Events and Total Isoform Usage Change contribute to restricting analysis to biologically meaningful changes. Finally, novel methods for Differential Feature Inclusion, Co-Feature Inclusion, and the combination of UTR-lengthening with Alternative Polyadenylation analyses carefully dissects the contextual regulation of functional elements resulting from differential isoforms usage. These methods are implemented in the software tappAS, a user-friendly Java application that brings FIT to the hands of non-expert bioinformaticians supporting several model and non-model species. tappAS complements statistical analyses with powerful browsing tools and highly informative gene/transcript/CDS graphs.\n\nWe applied tappAS to the analysis of two mouse Neural Precursor Cells (NPCs) and Oligodendrocyte Precursor Cells (OPCs) whose transcriptome was defined by PacBio and quantified by Illumina. Using FDA we confirmed the high potential of AltTP regulation in our system, in which 90% of multi-isoform genes presented variation in functional features at the transcript or protein level. The Differential Analysis module revealed a high interplay between transcriptional and AltTP regulation in neural development, mainly controlled by differential expression, but where AltTP acts the main driver of important neural development biological mechanisms such as vesicle trafficking, signal transduction and RNA processing. The DFI analysis revealed that, globally, AltTP increased the availability of functional features in differentiated neural cells. DFI also showed that AltTP is a mechanism for altering gene function by changing cellular localization and binding properties of proteins, via the differential inclusion of NLS, transmembrane domains or DNA binding motifs, for example. Some of these findings were experimentally validated by others and us.\n\nIn summary, we propose a novel framework for the functional analysis of transcriptomes at isoform resolution. We anticipate the tappAS tool will be an important resource for the adoption of the Functional Iso-Transcriptomics analysis by functional genomics community.

bioinformatics↗