Comparative analysis of the transcriptome across distant species

Quantitative proteome dynamics across embryogenesis in a model chordate

The evolution of gene expression programs underlying the development of vertebrates remains poorly characterized. Here, we present a comprehensive proteome atlas of the model chordate Ciona, covering eight developmental stages and ∼7,000 translated genes, accompanied by a multi-omics analysis of co-evolution with the vertebrate Xenopus. Quantitative proteome comparisons argue against the widely held hourglass model, based solely on transcriptomic profiles, whereby peak conservation is observed during mid-developmental stages. Our analysis reveals maximal divergence at these stages, particularly gastrulation and neurulation. Together, our work provides a valuable resource for evaluating conservation and divergence of multi-omics profiles underlying the diversification of vertebrates.

Single-cell phylotranscriptomics of developmental and cell type evolution

Single-cell phylotranscriptomics is an emerging tool to reveal the molecular and cellular mechanisms of evolution. We summarize its utility in studying the hourglass pattern of ontogenetic evolution and for understanding the evolutionary history of cell types. The developmental hourglass model suggests that the mid-embryonic stage is the most conserved period of development across species, which is supported by morphological and molecular studies. Single-cell phylotranscriptomic analysis has revealed previously underappreciated heterogeneity in transcriptome ages among lineages and cell types throughout development, and has identified the lineages and tissues that drive the whole-organism hourglass pattern. Single-cell transcriptome age analyses also provide important insights into the origin of germ layers, the different selective forces on tissues during adaptation, and the evolutionary relationships between cell types.

Identification of overlay differentially expressed genes in both rats and goats with blast lung injury through comparative transcriptomics

PURPOSE

To identify the potential target genes of blast lung injury (BLI) for the diagnosis and treatment.

METHODS

This is an experimental study. The BLI models in rats and goats were established by conducting a fuel-air explosive power test in an unobstructed environment, which was subsequently validated through hematoxylin-eosin staining. Transcriptome sequencing was performed on lung tissues from both goats and rats. Differentially expressed genes were identified using the criteria of q ≤ 0.05 and |log2 fold change| ≥ 1. Following that, enrichment analyses were conducted for gene ontology and the Kyoto Encyclopedia of Genes and Genomes pathways. The potential target genes were further confirmed through quantitative real-time polymerase chain reaction and enzyme linked immunosorbent assay.

RESULTS

Observations through microscopy unveiled the presence of reddish edema fluid, erythrocytes, and instances of focal or patchy bleeding within the alveolar cavity. Transcriptome sequencing analysis identified a total of 83 differentially expressed genes in both rats and goats. Notably, 49 genes exhibited a consistent expression pattern, with 38 genes displaying up-regulation and 11 genes demonstrating down-regulation. Enrichment analysis highlighted the potential involvement of the interleukin-17 signaling pathway and vascular smooth muscle contraction pathway in the underlying mechanism of BLI. Furthermore, the experimental findings in both goats and rats demonstrated a strong association between BLI and several key genes, including anterior gradient 2, ankyrin repeat domain 65, bactericidal/permeability-increasing fold containing family A member 1, bactericidal/permeability-increasing fold containing family B member 1, and keratin 4, which exhibited up-regulation.

CONCLUSIONS

Anterior gradient 2, ankyrin repeat domain 65, bactericidal/permeability-increasing fold containing family A member 1, bactericidal/permeability-increasing fold containing family B member 1, and keratin 4 hold potential as target genes for the prognosis, diagnosis, and treatment of BLI.

How to utilize comparative transcriptomics to dissect morphological diversity in plants

Comparative transcriptomics has emerged as a powerful approach that allows us to unravel the genetic basis of organ morphogenesis and its diversification processes during evolution. However, the application of comparative transcriptomics in studying plant morphological diversity addresses challenges such as identifying homologous gene pairs, selecting appropriate developmental stages for comparison, and extracting biologically meaningful networks. Methods such as phylostratigraphy, clustering, and gene co-expression networks are explored to identify functionally equivalent genes, align developmental stages, and uncover gene regulatory relationships. In the current review, we highlight the importance of these approaches in overcoming the complexity of plant genomes, the impact of heterochrony on stage alignment, and the integration of gene networks with additional data for a comprehensive understanding of morphological evolution.

Exploration of the Noncoding Genome for Human-Specific Therapeutic Targets-Recent Insights at Molecular and Cellular Level

While it is well known that 98-99% of the human genome does not encode proteins, but are nevertheless transcriptionally active and give rise to a broad spectrum of noncoding RNAs [ncRNAs] with complex regulatory and structural functions, specific functions have so far been assigned to only a tiny fraction of all known transcripts. On the other hand, the striking observation of an overwhelmingly growing fraction of ncRNAs, in contrast to an only modest increase in the number of protein-coding genes, during evolution from simple organisms to humans, strongly suggests critical but so far essentially unexplored roles of the noncoding genome for human health and disease pathogenesis. Research into the vast realm of the noncoding genome during the past decades thus lead to a profoundly enhanced appreciation of the multi-level complexity of the human genome. Here, we address a few of the many huge remaining knowledge gaps and consider some newly emerging questions and concepts of research. We attempt to provide an up-to-date assessment of recent insights obtained by molecular and cell biological methods, and by the application of systems biology approaches. Specifically, we discuss current data regarding two topics of high current interest: (1) By which mechanisms could evolutionary recent ncRNAs with critical regulatory functions in a broad spectrum of cell types (neural, immune, cardiovascular) constitute novel therapeutic targets in human diseases? (2) Since noncoding genome evolution is causally linked to brain evolution, and given the profound interactions between brain and immune system, could human-specific brain-expressed ncRNAs play a direct or indirect (immune-mediated) role in human diseases? Synergistic with remarkable recent progress regarding delivery, efficacy, and safety of nucleic acid-based therapies, the ongoing large-scale exploration of the noncoding genome for human-specific therapeutic targets is encouraging to proceed with the development and clinical evaluation of novel therapeutic pathways suggested by these research fields.

Cloning and functional characterization of porcine AACS revealing the regulative roles for fat deposition in pigs

Fat deposition is a quantitative trait controlled by multiple genes in pigs. Using transcriptome sequencing, we previously reported that AACS is differentially expressed in the subcutaneous fat tissue of Dingyuan pigs with divergent backfat thickness. Therefore, with the aim of further characterizing this gene and its protein, we cloned the entire 3286-bp mRNA sequence of the porcine AACS, and the encoded AACS protein is a hydrophilic protein without a signal peptide or transmembrane sequence. Our findings suggested that among various tissues and pig breeds, AACS was highly expressed in subcutaneous fat. We have identified three completely linked SNP loci in the AACS gene: A-1759C, C-1683T, and A-1664G. The double luciferase activity test in the 5' flanking region indicated that the flanking region of AACS contained several active regulatory elements. The three linked SNPs that were identified in one of the critical active elements, and might serve as important molecular markers regulating backfat thickness. Finally, we observed that AACS overexpression inhibited the proliferation and differentiation of subcutaneous preadipocytes. Collectively, our results suggest that AACS inhibits subcutaneous fat deposition in pigs. This study provides a new molecular marker for understanding the mechanism of porcine fat deposition.

Molecular logic of synaptic diversity between Drosophila tonic and phasic motoneurons

Although neuronal subtypes display unique synaptic organization and function, the underlying transcriptional differences that establish these features are poorly understood. To identify molecular pathways that contribute to synaptic diversity, single-neuron Patch-seq RNA profiling was performed on Drosophila tonic and phasic glutamatergic motoneurons. Tonic motoneurons form weaker facilitating synapses onto single muscles, while phasic motoneurons form stronger depressing synapses onto multiple muscles. Super-resolution microscopy and in vivo imaging demonstrated that synaptic active zones in phasic motoneurons are more compact and display enhanced Ca2+ influx compared with their tonic counterparts. Genetic analysis identified unique synaptic properties that mapped onto gene expression differences for several cellular pathways, including distinct signaling ligands, post-translational modifications, and intracellular Ca2+ buffers. These findings provide insights into how unique transcriptomes drive functional and morphological differences between neuronal subtypes.

Elegant Nematodes Improve Our Understanding of Human Neuronal Diseases, the Role of Pollutants and Strategies of Resilience

The prevalence of neurodegenerative disorders such as Alzheimer's and Parkinson's disease are rising globally. The role of environmental pollution in neurodegeneration is largely unknown. Thus, this perspective advocates exposome research in C. elegans models of human diseases. The models express amyloid proteins such as Aβ, recapitulate the degeneration of specifically vulnerable neurons and allow for correlated neurobehavioral phenotyping throughout the entire life span of the nematode. Neurobehavioral traits like locomotion gaits, rigidity, or cognitive decline are quantifiable and carefully mimic key aspects of the human diseases. Underlying molecular pathways of neurodegeneration are elucidated in pollutant-exposed C. elegans Alzheimer's or Parkinson's models by transcriptomics (RNA-seq), mass spectrometry-based proteomics and omics addressing other biochemical traits. Validation of the identified disease pathways can be achieved by genome-wide association studies in matching human cohorts. A consistent One Health approach includes isolation of nematodes from contaminated sites and their comparative investigation by imaging, neurobehavioral profiling and single worm proteomics. C. elegans models of neurodegenerative diseases are likewise well-suited for high throughput methods that provide a promising strategy to identify resilience pathways of neurosafety and keep up with the number of pollutants, nonchemical exposome factors, and their interactions.

Going circular: history, present, and future of circRNAs in cancer

To date, thousands of highly abundant and conserved single-stranded RNA molecules shaped into ring structures (circRNAs) have been identified. CircRNAs are multifunctional molecules that have been shown to regulate gene expression transcriptionally and post-transcriptionally and exhibit distinct tissue- and development-specific expression patterns associated with a variety of normal and disease conditions, including cancer pathogenesis. Over the past years, due to their intrinsic stability and resistance to ribonucleases, particular attention has been drawn to their use as reliable diagnostic and prognostic biomarkers in cancer diagnosis, treatment, and prevention. However, there are some critical caveats to their utility in the clinic. Their circular shape limits their annotation and a complete functional elucidation is lacking. This makes their detection and biomedical application still challenging. Herein, we review the current knowledge of circRNA biogenesis and function, and of their involvement in tumorigenesis and potential utility in cancer-targeted therapy.

Cross-species transcriptomics reveals bifurcation point during the arterial-to-hemogenic transition

Hemogenic endothelium (HE) with hematopoietic stem cell (HSC)-forming potential emerge from specialized arterial endothelial cells (AECs) undergoing the endothelial-to-hematopoietic transition (EHT) in the aorta-gonad-mesonephros (AGM) region. Characterization of this AECs subpopulation and whether this phenomenon is conserved across species remains unclear. Here we introduce HomologySeeker, a cross-species method that leverages refined mouse information to explore under-studied human EHT. Utilizing single-cell transcriptomic ensembles of EHT, HomologySeeker reveals a parallel developmental relationship between these two species, with minimal pre-HSC signals observed in human cells. The pre-HE stage contains a conserved bifurcation point between the two species, where cells progress towards HE or late AECs. By harnessing human spatial transcriptomics, we identify ligand modules that contribute to the bifurcation choice and validate CXCL12 in promoting hemogenic choice using a human in vitro differentiation system. Our findings advance human arterial-to-hemogenic transition understanding and offer valuable insights for manipulating HSC generation using in vitro models.

A deep-learning-based RNA-seq germline variant caller

Summary

RNA sequencing (RNA-seq) can be applied to diverse tasks including quantifying gene expression, discovering quantitative trait loci and identifying gene fusion events. Although RNA-seq can detect germline variants, the complexities of variable transcript abundance, target capture and amplification introduce challenging sources of error. Here, we extend DeepVariant, a deep-learning-based variant caller, to learn and account for the unique challenges presented by RNA-seq data. Our DeepVariant RNA-seq model produces highly accurate variant calls from RNA-sequencing data, and outperforms existing approaches such as Platypus and GATK. We examine factors that influence accuracy, how our model addresses RNA editing events and how additional thresholding can be used to facilitate our models' use in a production pipeline.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

dTtc1, a conserved tetratricopeptide repeat protein, is required for maturation of Drosophila egg chambers via its role in stabilizing electron transport chain components

We recently identified the Drosophila ortholog of TTC1 (dTtc1) as an interacting partner of Egalitarian, an RNA adaptor of the Dynein motor. In order to better understand the function of this relatively uncharacterized protein, we depleted dTtc1 in the Drosophila female germline. Depletion of dTtc1 resulted in defective oogenesis and no mature eggs were produced. A closer examination revealed that mRNA cargoes normally transported by Dynein were relatively unaffected. However, mitochondria in dTtc1 depleted egg chambers displayed an extremely swollen phenotype. Ultrastructural analysis revealed a lack of cristae. These phenotypes were not observed upon disruption of Dynein. Thus, this function of dTtc1 is likely to be Dynein independent. Consistent with a role for dTtc1 in mitochondrial biology, a published proteomics screen revealed that dTtc1 interacts with numerous components of electron transport chain (ETC) complexes. Our results indicate that the expression level of several of these ETC components was significantly reduced upon depletion of dTtc1. Importantly, this phenotype was completely rescued upon expression of wild-type GFP-dTtc1 in the depleted background. Lastly, we demonstrate that the mitochondrial phenotype caused by a lack of dTtc1 is not restricted to the germline but is also observed in somatic tissues. Our model suggests that dTtc1, likely in combination with cytoplasmic chaperones, is required for stabilizing ETC components.

Alternative splicing outcomes across an RNA-binding protein concentration gradient

Alternative splicing (AS) is a dynamic RNA processing step that produces multiple RNA isoforms from a single pre-mRNA transcript and contributes to the complexity of the cellular transcriptome and proteome. This process is regulated through a network of cis-regulatory sequence elements and trans-acting factors, most-notably RNA binding proteins (RBPs). The muscleblind-like (MBNL) and RNA binding fox-1 homolog (RBFOX) are two well characterized families of RBPs that regulate fetal to adult AS transitions critical for proper muscle, heart, and central nervous system development. To better understand how the concentration of these RBPs influences AS transcriptome wide, we engineered a MBNL1 and RBFOX1 inducible HEK-293 cell line. Modest induction of exogenous RBFOX1 in this cell line modulated MBNL1-dependent AS outcomes in 3 skipped exon events, despite significant levels of endogenous RBFOX1 and RBFOX2. Due to background RBFOX levels, we conducted a focused analysis of dose-dependent MBNL1 skipped exon AS outcomes and generated transcriptome wide dose-response curves. Analysis of this data demonstrates that MBNL1-regulated exclusion events may require higher concentrations of MBNL1 protein to properly regulate AS outcomes compared to inclusion events and that multiple arrangements of YGCY motifs can produce similar splicing outcomes. These results suggest that rather than a simple relationship between the organization of RBP binding sites and a specific splicing outcome, that complex interaction networks govern both AS inclusion and exclusion events across a RBP gradient.

Analysis of the P. lividus sea urchin genome highlights contrasting trends of genomic and regulatory evolution in deuterostomes

Sea urchins are emblematic models in developmental biology and display several characteristics that set them apart from other deuterostomes. To uncover the genomic cues that may underlie these specificities, we generated a chromosome-scale genome assembly for the sea urchin Paracentrotus lividus and an extensive gene expression and epigenetic profiles of its embryonic development. We found that, unlike vertebrates, sea urchins retained ancestral chromosomal linkages but underwent very fast intrachromosomal gene order mixing. We identified a burst of gene duplication in the echinoid lineage and showed that some of these expanded genes have been recruited in novel structures (water vascular system, Aristotle's lantern, and skeletogenic micromere lineage). Finally, we identified gene-regulatory modules conserved between sea urchins and chordates. Our results suggest that gene-regulatory networks controlling development can be conserved despite extensive gene order rearrangement.

Transcriptomic congruence analysis for evaluating model organisms

Model organisms are instrumental substitutes for human studies to expedite basic, translational, and clinical research. Despite their indispensable role in mechanistic investigation and drug development, molecular congruence of animal models to humans has long been questioned and debated. Little effort has been made for an objective quantification and mechanistic exploration of a model organism's resemblance to humans in terms of molecular response under disease or drug treatment. We hereby propose a framework, namely Congruence Analysis for Model Organisms (CAMO), for transcriptomic response analysis by developing threshold-free differential expression analysis, quantitative concordance/discordance scores incorporating data variabilities, pathway-centric downstream investigation, knowledge retrieval by text mining, and topological gene module detection for hypothesis generation. Instead of a genome-wide vague and dichotomous answer of "poorly" or "greatly" mimicking humans, CAMO assists researchers to numerically quantify congruence, to dissect true cross-species differences from unwanted biological or cohort variabilities, and to visually identify molecular mechanisms and pathway subnetworks that are best or least mimicked by model organisms, which altogether provides foundations for hypothesis generation and subsequent translational decisions.

Molecular Logic of Synaptic Diversity Between Drosophila Tonic and Phasic Motoneurons

Although neuronal subtypes display unique synaptic organization and function, the underlying transcriptional differences that establish these features is poorly understood. To identify molecular pathways that contribute to synaptic diversity, single neuron PatchSeq RNA profiling was performed on Drosophila tonic and phasic glutamatergic motoneurons. Tonic motoneurons form weaker facilitating synapses onto single muscles, while phasic motoneurons form stronger depressing synapses onto multiple muscles. Super-resolution microscopy and in vivo imaging demonstrated synaptic active zones in phasic motoneurons are more compact and display enhanced Ca 2+ influx compared to their tonic counterparts. Genetic analysis identified unique synaptic properties that mapped onto gene expression differences for several cellular pathways, including distinct signaling ligands, post-translational modifications and intracellular Ca 2+ buffers. These findings provide insights into how unique transcriptomes drive functional and morphological differences between neuronal subtypes.

Genome-guided comparative in planta transcriptome analyses for identifying cross-species common virulence factors in bacterial phytopathogens

Plant bacterial disease is a complex outcome achieved through a combination of virulence factors that are activated during infection. However, the common virulence factors across diverse plant pathogens are largely uncharacterized. Here, we established a pan-genome shared across the following plant pathogens: Burkholderia glumae, Ralstonia solanacearum, and Xanthomonas oryzae pv. oryzae. By overlaying in planta transcriptomes onto the pan-genome, we investigated the expression profiles of common genes during infection. We found over 70% of identical patterns for genes commonly expressed by the pathogens in different plant hosts or infection sites. Co-expression patterns revealed the activation of a signal transduction cascade to recognize and respond to external changes within hosts. Using mutagenesis, we uncovered a relationship between bacterial virulence and functions highly conserved and shared in the studied genomes of the bacterial phytopathogens, including flagellar biosynthesis protein, C4-dicarboxylate ABC transporter, 2-methylisocitrate lyase, and protocatechuate 3,4-dioxygenase (PCD). In particular, the disruption of PCD gene led to attenuated virulence in all pathogens and significantly affected phytotoxin production in B. glumae. This PCD gene was ubiquitously distributed in most plant pathogens with high homology. In conclusion, our results provide cross-species in planta models for identifying common virulence factors, which can be useful for the protection of crops against diverse pathogens.

Genetic Characterization of Some Saudi Arabia's Accessions from Commiphora gileadensis Using Physio-Biochemical Parameters, Molecular Markers, DNA Barcoding Analysis and Relative Gene Expression

Commiphora gileadensis L. is a medicinal plant, known as balsam, with pharmaceutical potential for its phytochemical activities and chemical constituents. Genetic diversity is a genetic tool used in medicinal plant evolution and conservation. Three accessions from C. gileadensis were collected from three localities in Saudi Arabia (Jeddah, Jizan and Riyadh). Genetic characterization was carried out using physio-biochemical parameters, molecular markers (inter-simple sequence repeat (ISSR) and start codon targeted (SCoT)), DNA barcoding (18 S rRNA and ITS rDNA regions), relative gene expressions (phenylalanine ammonia-lyase 1 (PAL1), defensin (PR-12)) and pathogenesis-related protein (AFPRT). The results of this study showed that C. gileadensis accession C3, collected from Riyadh, had the highest content from the physio-biochemical parameters perspective, with values of 92.54 mg/g and 77.13 mg/g for total phenolic content (TPC) and total flavonoid content (TFC), respectively. Furthermore, the highest content of antioxidant enzyme activity was present in accession C3 with values of 16.87, 60.87, 35.76 and 27.98 U mg-1 for superoxide dismutase (SOD), peroxidase (POD), catalase (CAT) (mol/min/mg FW) and ascorbate peroxidase (APX) (U mg-1 protein), respectively. The highest total number of bands and number of unique bands were 138 and 59, respectively, for the SCoT marker. The SCoT marker was the most efficient for the genetic diversity of C. gileadensis by producing the highest polymorphism (75.63%). DNA barcoding using 18 S and ITS showed the nearby Commiphora genus and clustered C. gileadensis accessions from Jeddah and Jizan in one clade and the C. gileadensis accession from Ryiadh in a separate cluster. Moreover, relative gene expression of the PAL1, defensin (PR-12) and AFPRT (PR1) genes was upregulated in the C. gileadensis accession from Ryiadh. In conclusion, ecological and environmental conditions in each locality affect the genomic expression and genetic diversity, which can help the evolution of important medicinal plants and improve breeding and conservation systems.

Dynamic Transcriptional Landscape of Grass Carp (Ctenopharyngodon idella) Reveals Key Transcriptional Features Involved in Fish Development

A high-quality baseline transcriptome is a valuable resource for developmental research as well as a useful reference for other studies. We gathered 41 samples representing 11 tissues/organs from 22 important developmental time points within 197 days of fertilization of grass carp eggs in order to systematically examine the role of lncRNAs and alternative splicing in fish development. We created a high-quality grass carp baseline transcriptome with a completeness of up to 93.98 percent by combining strand-specific RNA sequencing and single-molecule real-time RNA sequencing technologies, and we obtained temporal expression profiles of 33,055 genes and 77,582 transcripts during development and tissue differentiation. A family of short interspersed elements was preferentially expressed at the early stage of zygotic activation in grass carp, and its possible regulatory components were discovered through analysis. Additionally, after thoroughly analyzing alternative splicing events, we discovered that retained intron (RI) alternative splicing events change significantly in both zygotic activation and tissue differentiation. During zygotic activation, we also revealed the precise regulatory characteristics of the underlying functional RI events.

HLH-1 Modulates Muscle Proteostasis During Caenorhabditis elegans Larval Development

Muscle proteostasis is shaped by the myogenic transcription factor MyoD which regulates the expression of chaperones during muscle differentiation. Whether MyoD can also modulate chaperone expression in terminally differentiated muscle cells remains open. Here we utilized a temperature-sensitive (ts) conditional knockdown nonsense mutation in MyoD ortholog in C. elegans, HLH-1, to ask whether MyoD plays a role in maintaining muscle proteostasis post myogenesis. We showed that hlh-1 is expressed during larval development and that hlh-1 knockdown at the first, second, or third larval stages resulted in severe defects in motility and muscle organization. Motility defects and myofilament organization were rescued when the clearance of hlh-1(ts) mRNA was inhibited, and hlh-1 mRNA levels were restored. Moreover, hlh-1 knockdown modulated the expression of chaperones with putative HLH-1 binding sites in their promoters, supporting HLH-1 role in muscle maintenance during larval development. Finally, mild disruption of hlh-1 expression during development resulted in earlier dysregulation of muscle maintenance and function during adulthood. We propose that the differentiation transcription factor, HLH-1, contributes to muscle maintenance and regulates cell-specific chaperone expression post differentiation. HLH-1 may thus impact muscle proteostasis and potentially the onset and manifestation of sarcopenia.

Coexpression reveals conserved gene programs that co-vary with cell type across kingdoms

What makes a mouse a mouse, and not a hamster? Differences in gene regulation between the two organisms play a critical role. Comparative analysis of gene coexpression networks provides a general framework for investigating the evolution of gene regulation across species. Here, we compare coexpression networks from 37 species and quantify the conservation of gene activity 1) as a function of evolutionary time, 2) across orthology prediction algorithms, and 3) with reference to cell- and tissue-specificity. We find that ancient genes are expressed in multiple cell types and have well conserved coexpression patterns, however they are expressed at different levels across cell types. Thus, differential regulation of ancient gene programs contributes to transcriptional cell identity. We propose that this differential regulation may play a role in cell diversification in both the animal and plant kingdoms.

Dysregulation and therapeutic targeting of RNA splicing in cancer

High-throughput sequencing and functional characterization of the cancer transcriptome have uncovered cancer-specific dysregulation of RNA splicing across a variety of cancers. Alterations in the cancer genome and dysregulation of RNA splicing factors lead to missplicing, splicing alteration-dependent gene expression and, in some cases, generation of novel splicing-derived proteins. Here, we review recent advances in our understanding of aberrant splicing in cancer pathogenesis and present strategies to harness cancer-specific aberrant splicing for therapeutic intent.

Mechanisms of non-coding RNA-modulated alternative splicing in cancer

Alternative splicing (AS) is a common and pivotal process for eukaryotic gene expression regulation, which enables a precursor RNA to produce multiple transcript variants with diverse cellular functions. Aberrant AS represents a hallmark of cancer, engaged in all stages of tumorigenesis from initiation to metastasis. Accumulating pieces of evidence have revealed the involvement of non-coding RNAs (ncRNAs) in regulating AS in human cancers. In this review, we overview the underlying mechanisms of non-coding RNAs, including microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) modulated AS at diverse levels in human cancers, and summarize their regulatory functions in tumorigenesis.

Universal gene co-expression network reveals receptor-like protein genes involved in broad-spectrum resistance in pepper (Capsicum annuum L.)

Receptor-like proteins (RLPs) on plant cells have been implicated in immune responses and developmental processes. Although hundreds of RLP genes have been identified in plants, only a few RLPs have been functionally characterized in a limited number of plant species. Here, we identified RLPs in the pepper (Capsicum annuum) genome and performed comparative transcriptomics coupled with the analysis of conserved gene co-expression networks (GCNs) to reveal the role of core RLP regulators in pepper-pathogen interactions. A total of 102 RNA-seq datasets of pepper plants infected with four pathogens were used to construct CaRLP-targeted GCNs (CaRLP-GCNs). Resistance-responsive CaRLP-GCNs were merged to construct a universal GCN. Fourteen hub CaRLPs, tightly connected with defense-related gene clusters, were identified in eight modules. Based on the CaRLP-GCNs, we evaluated whether hub CaRLPs in the universal GCN are involved in the biotic stress response. Of the nine hub CaRLPs tested by virus-induced gene silencing, three genes (CaRLP264, CaRLP277, and CaRLP351) showed defense suppression with less hypersensitive response-like cell death in race-specific and non-host resistance response to viruses and bacteria, respectively, and consistently enhanced susceptibility to Ralstonia solanacearum and/or Phytophthora capsici. These data suggest that key CaRLPs are involved in the defense response to multiple biotic stresses and can be used to engineer a plant with broad-spectrum resistance. Together, our data show that generating a universal GCN using comprehensive transcriptome datasets can provide important clues to uncover genes involved in various biological processes.

Phylotranscriptomic patterns of network stochasticity and pathway dynamics during embryogenesis

MOTIVATION

The hourglass model is a popular evo-devo model depicting that the developmental constraints in the middle of a developmental process are higher, and hence the phenotypes are evolutionarily more conserved, than those that occur in early and late ontogeny stages. Although this model has been supported by studies analyzing developmental gene expression data, the evolutionary explanation and molecular mechanism behind this phenomenon are not fully understood yet. To approach this problem, Raff proposed a hypothesis and claimed that higher interconnectivity among elements in an organism during organogenesis resulted in the larger constraints at the mid-developmental stage. By employing stochastic network analysis and gene-set pathway analysis, we aim to demonstrate such changes of interconnectivity claimed in Raff's hypothesis.

RESULTS

We first compared the changes of network randomness among developmental processes in different species by measuring the stochasticity within the biological network in each developmental stage. By tracking the network entropy along each developmental process, we found that the network stochasticity follows an anti-hourglass trajectory, and such a pattern supports Raff's hypothesis in dynamic changes of interconnections among biological modules during development. To understand which biological functions change during the transition of network stochasticity, we sketched out the pathway dynamics along the developmental stages and found that species may activate similar groups of biological processes across different stages. Moreover, higher interspecies correlations are found at the mid-developmental stages.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

RNA metabolism and links to inflammatory regulation and disease

Inflammation is vital to protect the host against foreign organism invasion and cellular damage. It requires tight and concise gene expression for regulation of pro- and anti-inflammatory gene expression in immune cells. Dysregulated immune responses caused by gene mutations and errors in post-transcriptional regulation can lead to chronic inflammatory diseases and cancer. The mechanisms underlying post-transcriptional gene expression regulation include mRNA splicing, mRNA export, mRNA localisation, mRNA stability, RNA/protein interaction, and post-translational events such as protein stability and modification. The majority of studies to date have focused on transcriptional control pathways. However, post-transcriptional regulation of mRNA in eukaryotes is equally important and related information is lacking. In this review, we will focus on the mechanisms involved in the pre-mRNA splicing events, mRNA surveillance, RNA degradation pathways, disorders or symptoms caused by mutations or errors in post-transcriptional regulation during innate immunity especially toll-like receptor mediated pathways.

Cross-Kingdom Comparative Transcriptomics Reveals Conserved Genetic Modules in Response to Cadmium Stress

It is known that organisms have developed various mechanisms to cope with cadmium (Cd) stress, while we still lack a system-level understanding of the functional isomorphy among them. In the present study, a cross-kingdom comparison was conducted among Escherichia coli, Saccharomyces cerevisiae, and Chlamydomonas reinhardtii, through toxicological tests, comparative transcriptomics, as well as conventional functional genomics. An equivalent level of Cd stress was determined via inhibition tests. Through transcriptome comparison, the three organisms exhibited differential gene expression under the same Cd stress relative to the corresponding no-treatment control. Results from functional enrichment analysis of differentially expressed genes (DEGs) showed that four metabolic pathways responsible for combating Cd stress were commonly regulated in the three organisms, including antioxidant reactions, sulfur metabolism, cell wall remodeling, and metal transport. In vivo expression patterns of 43 DEGs from the four pathways were further examined using quantitative PCR and resulted in a relatively comparable dynamic of gene expression patterns with transcriptome sequencing (RNA-seq). Cross-kingdom comparison of typical Cd stress-responding proteins resulted in the detection of 12 groups of homologous proteins in the three species. A class of potential metal transporters were subjected to cross-transformation to test their functional complementation. An ABC transporter gene in E. coli, possibly homologous to the yeast ycf1, was heterologously expressed in S. cerevisiae, resulting in enhanced Cd tolerance. Overall, our findings indicated that conserved genetic modules against Cd toxicity were commonly regulated among distantly related microbial species, which will be helpful for utilizing them in modifying microbial traits for bioremediation.

IMPORTANCE Research is establishing a systems biology view of biological response to Cd stress. It is meaningful to explore whether there is regulatory isomorphy among distantly related organisms. A transcriptomic comparison was done among model microbes, leading to the identification of a conserved cellular model pinpointing the generic strategies utilized by microbes for combating Cd stress. A novel E. coli transporter gene substantially increased yeast’s Cd tolerance. Knowledge on systems understanding of the cellular response to metals provides the basis for developing bioengineering remediation technology.

Virus infection modulates male sexual behaviour in Caenorhabditis elegans

Mating dynamics follow from natural selection on mate choice and individuals maximizing their reproductive success. Mate discrimination reveals itself by a plethora of behaviours and morphological characteristics, each of which can be affected by pathogens. A key question is how pathogens affect mate choice and outcrossing behaviour. Here we investigated the effect of Orsay virus on the mating dynamics of the androdiecious (male and hermaphrodite) nematode Caenorhabditis elegans. We tested genetically distinct strains and found that viral susceptibility differed between sexes in a genotype-dependent manner with males of reference strain N2 being more resistant than hermaphrodites. Males displayed a constitutively higher expression of intracellular pathogen response (IPR) genes, whereas the antiviral RNAi response did not have increased activity in males. Subsequent monitoring of sex ratios over 10 generations revealed that viral presence can change mating dynamics in isogenic populations. Sexual attraction assays showed that males preferred mating with uninfected rather than infected hermaphrodites. Together our results illustrate for the first time that viral infection can significantly affect male mating choice and suggest altered mating dynamics as a novel cause benefitting outcrossing under pathogenic stress conditions in C. elegans.

Alternative splicing level related to intron size and organism complexity

Background

Alternative splicing is the process of selecting different combinations of splice sites to produce variably spliced mRNAs. However, the relationships between alternative splicing prevalence and level (ASP/L) and variations of intron size and organism complexity (OC) remain vague. Here, we developed a robust protocol to analyze the relationships between ASP/L and variations of intron size and OC. Approximately 8 Tb raw RNA-Seq data from 37 eumetazoan species were divided into three sets of species based on variations in intron size and OC.

Results

We found a strong positive correlation between ASP/L and OC, but no correlation between ASP/L and intron size across species. Surprisingly, ASP/L displayed a positive correlation with mean intron size of genes within individual genomes. Moreover, our results revealed that four ASP/L-related pathways contributed to the differences in ASP/L that were associated with OC. In particular, the spliceosome pathway displayed distinct genomic features, such as the highest gene expression level, conservation level, and fraction of disordered regions. Interestingly, lower or no obvious correlations were observed among these genomic features.

Conclusions

The positive correlation between ASP/L and OC ubiquitously exists in eukaryotes, and this correlation is not affected by the mean intron size of these species. ASP/L-related splicing factors may play an important role in the evolution of OC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08172-2.

Identification of essential genes in Caenorhabditis elegans through whole genome sequencing of legacy mutant collections

It has been estimated that 15%–30% of the ∼20,000 genes in C. elegans are essential, yet many of these genes remain to be identified or characterized. With the goal of identifying unknown essential genes, we performed whole-genome sequencing on complementation pairs from legacy collections of maternal-effect lethal and sterile mutants. This approach uncovered maternal genes required for embryonic development and genes with apparent sperm-specific functions. In total, 58 putative essential genes were identified on chromosomes III–V, of which 52 genes are represented by novel alleles in this collection. Of these 52 genes, 19 (40 alleles) were selected for further functional characterization. The terminal phenotypes of embryos were examined, revealing defects in cell division, morphogenesis, and osmotic integrity of the eggshell. Mating assays with wild-type males revealed previously unknown male-expressed genes required for fertilization and embryonic development. The result of this study is a catalog of mutant alleles in essential genes that will serve as a resource to guide further study toward a more complete understanding of this important model organism. As many genes and developmental pathways in C. elegans are conserved and essential genes are often linked to human disease, uncovering the function of these genes may also provide insight to further our understanding of human biology.

Similarities of developmental gene expression changes in the brain between human and experimental animals: rhesus monkey, mouse, Zebrafish, and Drosophila

AIM

Experimental animals, such as non-human primates (NHPs), mice, Zebrafish, and Drosophila, are frequently employed as models to gain insights into human physiology and pathology. In developmental neuroscience and related research fields, information about the similarities of developmental gene expression patterns between animal models and humans is vital to choose what animal models to employ. Here, we aimed to statistically compare the similarities of developmental changes of gene expression patterns in the brains of humans with those of animal models frequently used in the neuroscience field.

METHODS

The developmental gene expression datasets that we analyzed consist of the fold-changes and P values of gene expression in the brains of animals of various ages compared with those of the youngest postnatal animals available in the dataset. By employing the running Fisher algorithm in a bioinformatics platform, BaseSpace, we assessed similarities between the developmental changes of gene expression patterns in the human (Homo sapiens) hippocampus with those in the dentate gyrus (DG) of the rhesus monkey (Macaca mulatta), the DG of the mouse (Mus musculus), the whole brain of Zebrafish (Danio rerio), and the whole brain of Drosophila (D. melanogaster).

RESULTS

Among all possible comparisons of different ages and animals in developmental changes in gene expression patterns within the datasets, those between rhesus monkeys and mice were highly similar to those of humans with significant overlap P-value as assessed by the running Fisher algorithm. There was the highest degree of gene expression similarity between 40-59-year-old humans and 6-12-year-old rhesus monkeys (overlap P-value = 2.1 × 10^- 72). The gene expression similarity between 20-39-year-old humans and 29-day-old mice was also significant (overlap P = 1.1 × 10^- 44). Moreover, there was a similarity in developmental changes of gene expression patterns between 1-2-year-old Zebrafish and 40-59-year-old humans (Overlap P-value = 1.4 × 10^- 6). The overlap P-value of developmental gene expression patterns between Drosophila and humans failed to reach significance (30 days Drosophila and 6-11-year-old humans; overlap P-value = 0.0614).

CONCLUSIONS

These results indicate that the developmental gene expression changes in the brains of the rhesus monkey, mouse, and Zebrafish recapitulate, to a certain degree, those in humans. Our findings support the idea that these animal models are a valid tool for investigating the development of the brain in neurophysiological and neuropsychiatric studies.

Differential transcript usage analysis of bulk and single-cell RNA-seq data with DTUrtle

Motivation

Each year, the number of published bulk and single-cell RNA-seq datasets is growing exponentially. Studies analyzing such data are commonly looking at gene-level differences, while the collected RNA-seq data inherently represents reads of transcript isoform sequences. Utilizing transcriptomic quantifiers, RNA-seq reads can be attributed to specific isoforms, allowing for analysis of transcript-level differences. A differential transcript usage (DTU) analysis is testing for proportional differences in a gene’s transcript composition, and has been of rising interest for many research questions, such as analysis of differential splicing or cell-type identification.

Results

We present the R package DTUrtle, the first DTU analysis workflow for both bulk and single-cell RNA-seq datasets, and the first package to conduct a ‘classical’ DTU analysis in a single-cell context. DTUrtle extends established statistical frameworks, offers various result aggregation and visualization options and a novel detection probability score for tagged-end data. It has been successfully applied to bulk and single-cell RNA-seq data of human and mouse, confirming and extending key results. In addition, we present novel potential DTU applications like the identification of cell-type specific transcript isoforms as biomarkers.

Availability and implementation

The R package DTUrtle is available at https://github.com/TobiTekath/DTUrtle with extensive vignettes and documentation at https://tobitekath.github.io/DTUrtle/.

Supplementary information

Supplementary data are available at Bioinformatics online.

The Need for a Human Pangenome Reference Sequence

The reference human genome sequence is inarguably the most important and widely used resource in the fields of human genetics and genomics. It has transformed the conduct of biomedical sciences and brought invaluable benefits to the understanding and improvement of human health. However, the commonly used reference sequence has profound limitations, because across much of its span, it represents the sequence of just one human haplotype. This single, monoploid reference structure presents a critical barrier to representing the broad genomic diversity in the human population. In this review, we discuss the modernization of the reference human genome sequence to a more complete reference of human genomic diversity, known as a human pangenome.

Transcriptome-wide Cas13 guide RNA design for model organisms and viral RNA pathogens

The recent characterization of RNA-targeting CRISPR nucleases has enabled diverse transcriptome engineering and screening applications that depend crucially on prediction and selection of optimized CRISPR guide RNAs (gRNAs). Previously, we developed a computational model to predict RfxCas13d gRNA activity for all human protein-coding genes. Here, we extend this framework to six model organisms (human, mouse, zebrafish, fly, nematode, and flowering plants) for protein-coding genes and noncoding RNAs (ncRNAs) and also to four RNA virus families (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2], HIV-1, H1N1 influenza, and Middle East respiratory syndrome [MERS]). We include experimental validation of predictions by testing knockdown of multiple ncRNAs (MALAT1, HOTAIRM1, Gas5, and Pvt1) in human and mouse cells. We developed a freely available web-based platform (cas13design) with pre-scored gRNAs for transcriptome-wide targeting in several organisms and an interactive design tool to predict optimal gRNAs for custom RNA targets entered by the user. This resource will facilitate CRISPR-Cas13 RNA targeting in model organisms, emerging viral threats to human health.

Comparative Analyses of Gene Co-expression Networks: Implementations and Applications in the Study of Evolution

Similarities and differences in the associations of biological entities among species can provide us with a better understanding of evolutionary relationships. Often the evolution of new phenotypes results from changes to interactions in pre-existing biological networks and comparing networks across species can identify evidence of conservation or adaptation. Gene co-expression networks (GCNs), constructed from high-throughput gene expression data, can be used to understand evolution and the rise of new phenotypes. The increasing abundance of gene expression data makes GCNs a valuable tool for the study of evolution in non-model organisms. In this paper, we cover motivations for why comparing these networks across species can be valuable for the study of evolution. We also review techniques for comparing GCNs in the context of evolution, including local and global methods of graph alignment. While some protein-protein interaction (PPI) bioinformatic methods can be used to compare co-expression networks, they often disregard highly relevant properties, including the existence of continuous and negative values for edge weights. Also, the lack of comparative datasets in non-model organisms has hindered the study of evolution using PPI networks. We also discuss limitations and challenges associated with cross-species comparison using GCNs, and provide suggestions for utilizing co-expression network alignments as an indispensable tool for evolutionary studies going forward.

Alternative splicing of mRNA in colorectal cancer: new strategies for tumor diagnosis and treatment

Alternative splicing (AS) is an important event that contributes to posttranscriptional gene regulation. This process leads to several mature transcript variants with diverse physiological functions. Indeed, disruption of various aspects of this multistep process, such as cis- or trans- factor alteration, promotes the progression of colorectal cancer. Therefore, targeting some specific processes of AS may be an effective therapeutic strategy for treating cancer. Here, we provide an overview of the AS events related to colorectal cancer based on research done in the past 5 years. We focus on the mechanisms and functions of variant products of AS that are relevant to malignant hallmarks, with an emphasis on variants with clinical significance. In addition, novel strategies for exploiting the therapeutic value of AS events are discussed.

The clinical importance of tandem exon duplication-derived substitutions

Most coding genes in the human genome are annotated with multiple alternative transcripts. However, clear evidence for the functional relevance of the protein isoforms produced by these alternative transcripts is often hard to find. Alternative isoforms generated from tandem exon duplication-derived substitutions are an exception. These splice events are rare, but have important functional consequences. Here, we have catalogued the 236 tandem exon duplication-derived substitutions annotated in the GENCODE human reference set. We find that more than 90% of the events have a last common ancestor in teleost fish, so are at least 425 million years old, and twenty-one can be traced back to the Bilateria clade. Alternative isoforms generated from tandem exon duplication-derived substitutions also have significantly more clinical impact than other alternative isoforms. Tandem exon duplication-derived substitutions have >25 times as many pathogenic and likely pathogenic mutations as other alternative events. Tandem exon duplication-derived substitutions appear to have vital functional roles in the cell and may have played a prominent part in metazoan evolution.

Single worm transcriptomics identifies a developmental core network of oscillating genes with deep conservation across nematodes

High-resolution spatial and temporal maps of gene expression have facilitated a comprehensive understanding of animal development and evolution. In nematodes, the small body size represented a major challenge for such studies, but recent advancements have helped overcome this limitation. Here, we have implemented single worm transcriptomics (SWT) in the nematode model organism Pristionchus pacificus to provide a high-resolution map of the developmental transcriptome. We selected 38 time points from hatching of the J2 larvae to young adults to perform transcriptome analysis over 60 h of postembryonic development. A mean sequencing depth of 4.5 million read pairs allowed the detection of more than 23,135 (80%) of all genes. Nearly 3000 (10%) genes showed oscillatory expression with discrete expression levels, phases, and amplitudes. Gene age analysis revealed an overrepresentation of ancient gene classes among oscillating genes, and around one-third of them have 1:1 orthologs in C. elegans. One important gene family overrepresented among oscillating genes is collagens. Several of these collagen genes are regulated by the developmental switch gene eud-1, indicating a potential function in the regulation of mouth-form plasticity, a key developmental process in this facultative predatory nematode. Together, our analysis provides (1) an updated protocol for SWT in nematodes that is applicable to many microscopic species, (2) a 1- to 2-h high-resolution catalog of P. pacificus gene expression throughout postembryonic development, and (3) a comparative analysis of oscillatory gene expression between the two model organisms P. pacificus and C. elegans and associated evolutionary dynamics.

Comparative Transcriptomics Reveals Distinct Patterns of Gene Expression Conservation through Vertebrate Embryogenesis

Despite life's diversity, studies of variation often remind us of our shared evolutionary past. Abundant genome sequencing and analyses of gene regulatory networks illustrate that genes and entire pathways are conserved, reused, and elaborated in the evolution of diversity. Predating these discoveries, 19th-century embryologists observed that though morphology at birth varies tremendously, certain stages of vertebrate embryogenesis appear remarkably similar across vertebrates. In the mid to late 20th century, anatomical variability of early and late-stage embryos and conservation of mid-stages embryos (the "phylotypic" stage) was named the hourglass model of diversification. This model has found mixed support in recent analyses comparing gene expression across species possibly owing to differences in species, embryonic stages, and gene sets compared. We compare 186 microarray and RNA-seq data sets covering embryogenesis in six vertebrate species. We use an unbiased clustering approach to group stages of embryogenesis by transcriptomic similarity and ask whether gene expression similarity of clustered embryonic stages deviates from a null expectation. We characterize expression conservation patterns of each gene at each evolutionary node after correcting for phylogenetic nonindependence. We find significant enrichment of genes exhibiting early conservation, hourglass, late conservation patterns in both microarray and RNA-seq data sets. Enrichment of genes showing patterned conservation through embryogenesis indicates diversification of embryogenesis may be temporally constrained. However, the circumstances under which each pattern emerges remain unknown and require both broad evolutionary sampling and systematic examination of embryogenesis across species.

Bipartite tight spectral clustering (BiTSC) algorithm for identifying conserved gene co-clusters in two species

MOTIVATION

Gene clustering is a widely used technique that has enabled computational prediction of unknown gene functions within a species. However, it remains a challenge to refine gene function prediction by leveraging evolutionarily conserved genes in another species. This challenge calls for a new computational algorithm to identify gene co-clusters in two species, so that genes in each co-cluster exhibit similar expression levels in each species and strong conservation between the species.

RESULTS

Here, we develop the bipartite tight spectral clustering (BiTSC) algorithm, which identifies gene co-clusters in two species based on gene orthology information and gene expression data. BiTSC novelly implements a formulation that encodes gene orthology as a bipartite network and gene expression data as node covariates. This formulation allows BiTSC to adopt and combine the advantages of multiple unsupervised learning techniques: kernel enhancement, bipartite spectral clustering, consensus clustering, tight clustering and hierarchical clustering. As a result, BiTSC is a flexible and robust algorithm capable of identifying informative gene co-clusters without forcing all genes into co-clusters. Another advantage of BiTSC is that it does not rely on any distributional assumptions. Beyond cross-species gene co-clustering, BiTSC also has wide applications as a general algorithm for identifying tight node co-clusters in any bipartite network with node covariates. We demonstrate the accuracy and robustness of BiTSC through comprehensive simulation studies. In a real data example, we use BiTSC to identify conserved gene co-clusters of Drosophila melanogaster and Caenorhabditis elegans, and we perform a series of downstream analysis to both validate BiTSC and verify the biological significance of the identified co-clusters.

AVAILABILITY AND IMPLEMENTATION

The Python package BiTSC is open-access and available at https://github.com/edensunyidan/BiTSC.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Tissue-specific dynamic codon redefinition in Drosophila

Translational stop codon readthrough occurs in organisms ranging from viruses to mammals and is especially prevalent in decoding Drosophila and viral mRNAs. Recoding of UGA, UAG, or UAA to specify an amino acid allows a proportion of the protein encoded by a single gene to be C-terminally extended. The extended product from Drosophila kelch mRNA is 160 kDa, whereas unextended Kelch protein, a subunit of a Cullin3-RING ubiquitin ligase, is 76 kDa. Previously we reported tissue-specific regulation of readthrough of the first kelch stop codon. Here, we characterize major efficiency differences in a variety of cell types. Immunoblotting revealed low levels of readthrough in malpighian tubules, ovary, and testis but abundant readthrough product in lysates of larval and adult central nervous system (CNS) tissue. Reporters of readthrough demonstrated greater than 30% readthrough in adult brains, and imaging in larval and adult brains showed that readthrough occurred in neurons but not glia. The extent of readthrough stimulatory sequences flanking the readthrough stop codon was assessed in transgenic Drosophila and in human tissue culture cells where inefficient readthrough occurs. A 99-nucleotide sequence with potential to form an mRNA stem-loop 3' of the readthrough stop codon stimulated readthrough efficiency. However, even with just six nucleotides of kelch mRNA sequence 3' of the stop codon, readthrough efficiency only dropped to 6% in adult neurons. Finally, we show that high-efficiency readthrough in the Drosophila CNS is common; for many neuronal proteins, C-terminal extended forms of individual proteins are likely relatively abundant.

Juxtapose: a gene-embedding approach for comparing co-expression networks

BACKGROUND

Gene co-expression networks (GCNs) are not easily comparable due to their complex structure. In this paper, we propose a tool, Juxtapose, together with similarity measures that can be utilized for comparative transcriptomics between a set of organisms. While we focus on its application to comparing co-expression networks across species in evolutionary studies, Juxtapose is also generalizable to co-expression network comparisons across tissues or conditions within the same species.

METHODS

A word embedding strategy commonly used in natural language processing was utilized in order to generate gene embeddings based on walks made throughout the GCNs. Juxtapose was evaluated based on its ability to embed the nodes of synthetic structures in the networks consistently while also generating biologically informative results. Evaluation of the techniques proposed in this research utilized RNA-seq datasets from GTEx, a multi-species experiment of prefrontal cortex samples from the Gene Expression Omnibus, as well as synthesized datasets. Biological evaluation was performed using gene set enrichment analysis and known gene relationships in literature.

RESULTS

We show that Juxtapose is capable of globally aligning synthesized networks as well as identifying areas that are conserved in real gene co-expression networks without reliance on external biological information. Furthermore, output from a matching algorithm that uses cosine distance between GCN embeddings is shown to be an informative measure of similarity that reflects the amount of topological similarity between networks.

CONCLUSIONS

Juxtapose can be used to align GCNs without relying on known biological similarities and enables post-hoc analyses using biological parameters, such as orthology of genes, or conserved or variable pathways.

AVAILABILITY

A development version of the software used in this paper is available at https://github.com/klovens/juxtapose.

To mock or not: a comprehensive comparison of mock IP and DNA input for ChIP-seq

Chromatin immunoprecipitation (IP) followed by sequencing (ChIP-seq) is the gold standard to detect transcription-factor (TF) binding sites in the genome. Its success depends on appropriate controls removing systematic biases. The predominantly used controls, i.e. DNA input, correct for uneven sonication, but not for nonspecific interactions of the IP antibody. Another type of controls, 'mock' IP, corrects for both of the issues, but is not widely used because it is considered susceptible to technical noise. The tradeoff between the two control types has not been investigated systematically. Therefore, we generated comparable DNA input and mock IP experiments. Because mock IPs contain only nonspecific interactions, the sites predicted from them using DNA input indicate the spurious-site abundance. This abundance is highly correlated with the 'genomic activity' (e.g. chromatin openness). In particular, compared to cell lines, complex samples such as whole organisms have more spurious sites-probably because they contain multiple cell types, resulting in more expressed genes and more open chromatin. Consequently, DNA input and mock IP controls performed similarly for cell lines, whereas for complex samples, mock IP substantially reduced the number of spurious sites. However, DNA input is still informative; thus, we developed a simple framework integrating both controls, improving binding site detection.

A Trans-Omics Comparison Reveals Common Gene Expression Strategies in Four Model Organisms and Exposes Similarities and Differences between Them

The ultimate goal of gene expression regulation is on the protein level. However, because the amounts of mRNAs and proteins are controlled by their synthesis and degradation rates, the cellular amount of a given protein can be attained by following different strategies. By studying omics data for six expression variables (mRNA and protein amounts, plus their synthesis and decay rates), we previously demonstrated the existence of common expression strategies (CESs) for functionally related genes in the yeast Saccharomyces cerevisiae. Here we extend that study to two other eukaryotes: the yeast Schizosaccharomyces pombe and cultured human HeLa cells. We also use genomic data from the model prokaryote Escherichia coli as an external reference. We show that six-variable profiles (6VPs) can be constructed for every gene and that these 6VPs are similar for genes with similar functions in all the studied organisms. The differences in 6VPs between organisms can be used to establish their phylogenetic relationships. The analysis of the correlations among the six variables supports the hypothesis that most gene expression control occurs in actively growing organisms at the transcription rate level, and that translation plays a minor role. We propose that living organisms use CESs for the genes acting on the same physiological pathways, especially for those belonging to stable macromolecular complexes, but CESs have been modeled by evolution to adapt to the specific life circumstances of each organism.

The Role of the U5 snRNP in Genetic Disorders and Cancer

Pre-mRNA splicing is performed by the spliceosome, a dynamic macromolecular complex consisting of five small uridine-rich ribonucleoprotein complexes (the U1, U2, U4, U5, and U6 snRNPs) and numerous auxiliary splicing factors. A plethora of human disorders are caused by genetic variants affecting the function and/or expression of splicing factors, including the core snRNP proteins. Variants in the genes encoding proteins of the U5 snRNP cause two distinct and tissue-specific human disease phenotypes – variants in PRPF6, PRPF8, and SNRP200 are associated with retinitis pigmentosa (RP), while variants in EFTUD2 and TXNL4A cause the craniofacial disorders mandibulofacial dysostosis Guion-Almeida type (MFDGA) and Burn-McKeown syndrome (BMKS), respectively. Furthermore, recurrent somatic mutations or changes in the expression levels of a number of U5 snRNP proteins (PRPF6, PRPF8, EFTUD2, DDX23, and SNRNP40) have been associated with human cancers. How and why variants in ubiquitously expressed spliceosome proteins required for pre-mRNA splicing in all human cells result in tissue-restricted disease phenotypes is not clear. Additionally, why variants in different, yet interacting, proteins making up the same core spliceosome snRNP result in completely distinct disease outcomes – RP, craniofacial defects or cancer – is unclear. In this review, we define the roles of different U5 snRNP proteins in RP, craniofacial disorders and cancer, including how disease-associated genetic variants affect pre-mRNA splicing and the proposed disease mechanisms. We then propose potential hypotheses for how U5 snRNP variants cause tissue specificity resulting in the restricted and distinct human disorders.

Sex-Specific Selection Drives the Evolution of Alternative Splicing in Birds

Males and females of the same species share the majority of their genomes, yet they are frequently exposed to conflicting selection pressures. Gene regulation is widely assumed to resolve these conflicting sex-specific selection pressures, and although there has been considerable focus on elucidating the role of gene expression level in sex-specific adaptation, other regulatory mechanisms have been overlooked. Alternative splicing enables different transcripts to be generated from the same gene, meaning that exons which have sex-specific beneficial effects can in theory be retained in the gene product, whereas exons with detrimental effects can be skipped. However, at present, little is known about how sex-specific selection acts on broad patterns of alternative splicing. Here, we investigate alternative splicing across males and females of multiple bird species. We identify hundreds of genes that have sex-specific patterns of splicing and establish that sex differences in splicing are correlated with phenotypic sex differences. Additionally, we find that alternatively spliced genes have evolved rapidly as a result of sex-specific selection and suggest that sex differences in splicing offer another route to sex-specific adaptation when gene expression level changes are limited by functional constraints. Overall, our results shed light on how a diverse transcriptional framework can give rise to the evolution of phenotypic sexual dimorphism.

MeDAS: a Metazoan Developmental Alternative Splicing database

Alternative splicing is widespread throughout eukaryotic genomes and greatly increases transcriptomic diversity. Many alternative isoforms have functional roles in developmental processes and are precisely temporally regulated. To facilitate the study of alternative splicing in a developmental context, we created MeDAS, a Metazoan Developmental Alternative Splicing database. MeDAS is an added-value resource that re-analyses publicly archived RNA-seq libraries to provide quantitative data on alternative splicing events as they vary across the time course of development. It has broad temporal and taxonomic scope and is intended to assist the user in identifying trends in alternative splicing throughout development. To create MeDAS, we re-analysed a curated set of 2232 Illumina polyA+ RNA-seq libraries that chart detailed time courses of embryonic and post-natal development across 18 species with a taxonomic range spanning the major metazoan lineages from Caenorhabditis elegans to human. MeDAS is freely available at https://das.chenlulab.com both as raw data tables and as an interactive browser allowing searches by species, tissue, or genomic feature (gene, transcript or exon ID and sequence). Results will provide details on alternative splicing events identified for the queried feature and can be visualised at the gene-, transcript- and exon-level as time courses of expression and inclusion levels, respectively.

Comparative transcriptomic analysis of rat versus mouse cerebral cortex after traumatic brain injury

The heterogeneity of traumatic brain injury (TBI)-induced secondary injury has greatly hampered the development of effective treatments for TBI patients. Targeting common processes across species may be an innovative strategy to combat debilitating TBI. In the present study, a cross-species transcriptome comparison was performed for the first time to determine the fundamental processes of secondary brain injury in Sprague-Dawley rat and C57/BL6 mouse models of TBI, caused by acute controlled cortical impact. The RNA sequencing data from the mouse model of TBI were downloaded from the Gene Expression Omnibus (ID: GSE79441) at the National Center for Biotechnology Information. For the rat data, peri-injury cerebral cortex samples were collected for transcriptomic analysis 24 hours after TBI. Differentially expressed gene-based functional analysis revealed that common features between the two species were mainly involved in the regulation and activation of the innate immune response, including complement cascades as well as Toll-like and nucleotide oligomerization domain-like receptor pathways. These findings were further corroborated by gene set enrichment analysis. Moreover, transcription factor analysis revealed that the families of signal transducers and activators of transcription (STAT), basic leucine zipper (BZIP), Rel homology domain (RHD), and interferon regulatory factor (IRF) transcription factors play vital regulatory roles in the pathophysiological processes of TBI, and are also largely associated with inflammation. These findings suggest that targeting the common innate immune response might be a promising therapeutic approach for TBI. The animal experimental procedures were approved by the Beijing Neurosurgical Institute Animal Care and Use Committee (approval No. 201802001) on June 6, 2018.

A primer for generating and using transcriptome data and gene sets

Transcriptomic approaches have provided a growing set of powerful tools with which to study genome-wide patterns of gene expression. Rapidly evolving technologies enable analysis of transcript abundance data from particular tissues and even single cells. This Primer discusses methods that can be used to collect and profile RNAs from specific tissues or cells, process and analyze high-throughput RNA-sequencing data, and define sets of genes that accurately represent a category, such as tissue-enriched or tissue-specific gene expression.

Summary: This Primer gives an overview of the considerations required when planning and conducting transcriptome profiling experiments, from sample isolation to data analysis and display, and discusses best practice in defining gene sets for use in addressing biological questions.