Gene-level differential analysis at transcript-level resolution

mRNA Transcript Variants Expressed in Mammalian Cells

Gene expression or gene regulation studies often assume one gene expresses one mRNA. However, contrary to the conventional idea, a single gene in mammalian cells can express multiple transcript variants translated into several different proteins. The transcript variants are generated through transcription from alternative start sites and alternative post-transcriptional processing of the precursor mRNA (pre-mRNA). In addition, gene mutations and RNA editing further enhance the diversity of the transcript variants. The transcript variants can encode proteins with various domains, expanding the functional repertoire of a single gene. Some transcript variants may not encode proteins but function as non-coding RNAs and regulate gene expression. The expression level of the transcript variants may vary between cell types or within the same cells under different biological conditions. Transcript variants are characteristic of cell differentiation in a particular tissue, and the variants may play a key role in normal development and aging. Studies also reported that some transcript variants may have roles in disease pathogenesis. The biological significances urge studying the complexity of gene expression at the transcript level. This article updates the molecular basis of transcript variants in mammalian cells, including the formation mechanisms and potential roles in host biology. Gaining insight into the transcript variants will not only identify novel mechanisms of gene regulation but also unravel the role of the variants in health and disease.

A landscape of X-inactivation during human T cell development

Females exhibit a more robust immune response to both self-antigens and non-self-antigens than males, resulting in a higher prevalence of autoimmune diseases but more effective responses against infection. Increased expression of X-linked immune genes in female T cells is thought to underlie this enhanced response. Here we isolate thymocytes from pediatric thymi of healthy males (46, XY), females (46, XX), a female with completely skewed X-chromosome inactivation (46, XX, cXCI) and a female with Turner syndrome (45, X0). Using whole exome sequencing, RNA sequencing and DNA methylation data, we present a sex-aware expression profile of T cell development and generate a high-resolution map of escape from X-chromosome inactivation (XCI). Unexpectedly, XCI is transcriptionally and epigenetically stable throughout T cell development, and is independent of expression of XIST, the lncRNA responsible for XCI initiation during early embryonic development. In thymocytes, several genes known to escape XCI are expressed from only one X-chromosome. Additionally, we further reveal that a second X-chromosome is dispensable for T cell development. Our study thus provides a high-resolution map of XCI during human development and suggests a re-evaluation of XCI in sex differences in T cell function.

Determining the effects of paternal obesity on sperm chromatin at histone H3 lysine 4 tri-methylation in relation to the placental transcriptome and cellular composition

Paternal obesity has been implicated in adult-onset metabolic disease in offspring. However, the molecular mechanisms driving these paternal effects and the developmental processes involved remain poorly understood. One underexplored possibility is the role of paternally induced effects on placenta development and function. To address this, we investigated paternal high-fat diet-induced obesity in relation to sperm histone H3 lysine 4 tri-methylation signatures, the placenta transcriptome, and cellular composition. C57BL6/J male mice were fed either a control or high-fat diet for 10 weeks beginning at 6 weeks of age. Males were timed-mated with control-fed C57BL6/J females to generate pregnancies, followed by collection of sperm, and placentas at embryonic day (E)14.5. Chromatin immunoprecipitation targeting histone H3 lysine 4 tri-methylation (H3K4me3) followed by sequencing (ChIP-seq) was performed on sperm to define obesity-associated changes in enrichment. Paternal obesity corresponded with altered sperm H3K4me3 at promoters of genes involved in metabolism and development. Notably, altered sperm H3K4me3 was also localized at placental enhancers. Bulk RNA-sequencing on placentas revealed paternal obesity-associated sex-specific changes in expression of genes involved in hypoxic processes such as angiogenesis, nutrient transport, and imprinted genes, with a subset of de-regulated genes showing changes in H3K4me3 in sperm at corresponding promoters. Paternal obesity was also linked to impaired placenta development; specifically, a deconvolution analysis revealed altered trophoblast cell lineage specification. These findings implicate paternal obesity effects on placenta development and function as one potential developmental route to offspring metabolic disease.

Gene count estimation with pytximport enables reproducible analysis of bulk RNA sequencing data in Python

SUMMARY

Transcript quantification tools efficiently map bulk RNA sequencing (RNA-seq) reads to reference transcriptomes. However, their output consists of transcript count estimates that are subject to multiple biases and cannot be readily used with existing differential gene expression analysis tools in Python.Here we present pytximport, a Python implementation of the tximport R package that supports a variety of input formats, different modes of bias correction, inferential replicates, gene-level summarization of transcript counts, transcript-level exports, transcript-to-gene mapping generation, and optional filtering of transcripts by biotype. pytximport is part of the scverse ecosystem of open-source Python software packages for omics analyses and includes both a Python as well as a command-line interface.With pytximport, we propose a bulk RNA-seq analysis workflow based on Bioconda and scverse ecosystem packages, ensuring reproducible analyses through Snakemake rules. We apply this pipeline to a publicly available RNA-seq dataset, demonstrating how pytximport enables the creation of Python-centric workflows capable of providing insights into transcriptomic alterations.

AVAILABILITY AND IMPLEMENTATION

pytximport is licensed under the GNU General Public License version 3. The source code is available at https://github.com/complextissue/pytximport and via Zenodo with DOI: 10.5281/zenodo.13907917. A related Snakemake workflow is available through GitHub at https://github.com/complextissue/snakemake-bulk-rna-seq-workflow and Zenodo with DOI: 10.5281/zenodo.12713811. Documentation and a vignette for new users are available at: https://pytximport.readthedocs.io.

Molecular impact of nicotine and smoking exposure on the developing and adult mouse brain

Maternal smoking during pregnancy (MSDP) is associated with significant cognitive and behavioral effects on offspring. While neurodevelopmental outcomes have been studied for prenatal exposure to nicotine, the main psychoactive component of cigarette smoke, its contribution to MSDP effects has never been explored. Comparing the effects of these substances on molecular signaling in the prenatal and adult brain may provide insights into nicotinic and broader tobacco consequences that are developmental-stage specific or age-independent. Pregnant mice were administered nicotine or exposed to chronic cigarette smoke, and RNA-sequencing was performed on frontal cortices of postnatal day 0 pups born to these mice, as well as on frontal cortices and blood of the adult dams. We identified 1,010 and 4,165 differentially expressed genes (DEGs) in nicotine and smoking-exposed pup brains, respectively (FDR<0.05, Ns = 19 nicotine-exposed vs 23 vehicle-exposed; 46 smoking-exposed vs 49 controls). Prenatal nicotine exposure (PNE) alone was related to dopaminergic synapses and long-term synaptic depression, whereas MSDP was associated with the SNARE complex and vesicle transport. Both substances affected SMN-Sm protein complexes and postsynaptic endosomes. Analyses at the transcript, exon, and exon-exon junction levels supported gene level results and revealed additional smoking-affected processes. No DEGs at FDR<0.05 were found in adult mouse brain for any substance (12 nicotine-administered vs 11 vehicle-administered; 12 smoking-exposed vs 12 controls), nor in adult blood (12 smoking-exposed vs 12 controls), and only 3% and 6.41% of the DEGs in smoking-exposed pup brain replicated in smoking-exposed blood and human prenatal brain, respectively. Together, these results demonstrate variable but overlapping molecular effects of PNE and MSDP on the developing brain, and attenuated effects of both smoking and nicotine on adult versus fetal brain.

Placental and fetal enrichment of microplastics from disposable paper cups: implications for metabolic and reproductive health during pregnancy

The disposable paper cups (DPCs) release millions of microplastics (MPs) when used for hot beverages. However, the tissue-specific deposition and toxic effects of MPs and associated toxins remain largely unexplored, especially at daily consumption levels. We administered MPs and associated toxins extracted from leading brand DPCs to pregnant mice, revealing dose-responsive harmful effects on fetal development and maternal physiology. MPs were detected in all 13 examined tissues, with preferred depositions in the fetus, placenta, kidney, spleen, lung, and heart, contributing to impaired phenotypes. Brain tissues had the smallest MPs (90.35 % < 10 µm). A dose-responsive shift in the cecal microbiome from Firmicutes to Bacteroidetes was observed, coupled with enhanced biosynthesis of microbial fatty acids. A moderate consumption of 3.3 cups daily was sufficient to alter the cecal microbiome, global metabolic functions, and immune health, as reflected by tissue-specific transcriptomic analyses in maternal blood, placenta, and mammary glands, leading to neurodegenerative and miscarriage risks. Gene-based benchmark dose framework analysis suggested a safe exposure limit of 2 to 4 cups/day in pregnant mice. Our results highlight tissue-specific accumulation and metabolic and reproductive toxicities in mice at DPC consumption levels presumed non-hazardous, with potential health implications for pregnant women and fetuses.

Importance of Transcript Variants in Transcriptome Analyses

RNA sequencing (RNA-Seq) has become a widely adopted technique for studying gene expression. However, conventional RNA-Seq analyses rely on gene expression (GE) values that aggregate all the transcripts produced under a single gene identifier, overlooking the complexity of transcript variants arising from different transcription start sites or alternative splicing. Transcript variants may encode proteins with diverse functional domains, or noncoding RNAs. This study explored the implications of neglecting transcript variants in RNA-Seq analyses. Among the 1334 transcription factor (TF) genes expressed in mouse embryonic stem (ES) or trophoblast stem (TS) cells, 652 were differentially expressed in TS cells based on GE values (365 upregulated and 287 downregulated, ≥absolute 2-fold changes, false discovery rate (FDR) p-value ≤ 0.05). The 365 upregulated genes expressed 883 transcript variants. Further transcript expression (TE) based analyses identified only 174 (<20%) of the 883 transcripts to be upregulated. The remaining 709 transcripts were either downregulated or showed no significant changes. Meanwhile, the 287 downregulated genes expressed 856 transcript variants and only 153 (<20%) of the 856 transcripts were downregulated. The other 703 transcripts were either upregulated or showed no significant change. Additionally, the 682 insignificant TF genes (GE values < absolute 2-fold changes and/or FDR p-values > 0.05) between ES and TS cells expressed 2215 transcript variants. These included 477 (>21%) differentially expressed transcripts (276 upregulated and 201 downregulated, ≥absolute 2-fold changes, FDR p-value ≤ 0.05). Hence, GE based RNA-Seq analyses do not represent accurate expression levels due to divergent transcripts expression from the same gene. Our findings show that by including transcript variants in RNA-Seq analyses, we can generate a precise understanding of a gene's functional and regulatory landscape; ignoring the variants may result in an erroneous interpretation.

Reduced protein-coding transcript diversity in severe dengue emphasises the role of alternative splicing

Dengue fever, a neglected tropical arboviral disease, has emerged as a global health concern in the past decade. Necessitating a nuanced comprehension of the intricate dynamics of host-virus interactions influencing disease severity, we analysed transcriptomic patterns using bulk RNA-seq from 112 age- and gender-matched NS1 antigen-confirmed hospital-admitted dengue patients with varying severity. Severe cases exhibited reduced platelet count, increased lymphocytosis, and neutropenia, indicating a dysregulated immune response. Using bulk RNA-seq, our analysis revealed a minimal overlap between the differentially expressed gene and transcript isoform, with a distinct expression pattern across the disease severity. Severe patients showed enrichment in retained intron and nonsense-mediated decay transcript biotypes, suggesting altered splicing efficiency. Furthermore, an up-regulated programmed cell death, a haemolytic response, and an impaired interferon and antiviral response at the transcript level were observed. We also identified the potential involvement of the RBM39 gene among others in the innate immune response during dengue viral pathogenesis, warranting further investigation. These findings provide valuable insights into potential therapeutic targets, underscoring the importance of exploring transcriptomic landscapes between different disease sub-phenotypes in infectious diseases.

Transcriptomic signatures across a critical sedimentation threshold in a major reef-building coral

Sedimentation is a major cause of global near-shore coral reef decline. Although the negative impacts of sedimentation on coral reef community composition have been well-documented, the effects of sedimentation on coral metabolism in situ have received comparatively little attention. Using transcriptomics, we identified gene expression patterns changing across a previously defined sedimentation threshold that was deemed critical due to changes in coral cover and community composition. We identified genes, pathways, and molecular processes associated with this transition that may allow corals, such as Porites lobata, to tolerate chronic, severe sedimentation and persist in turbid environments. Alternative energy generation pathways may help P. lobata maintain a persistent stress response to survive when the availability of light and oxygen is diminished. We found evidence for the expression of genes linked to increased environmental sensing and cellular communication that likely allow P. lobata to efficiently respond to sedimentation stress and associated pathogen challenges. Cell damage increases under stress; consequently, we found apoptosis pathways over-represented under severe sedimentation, a likely consequence of damaged cell removal to maintain colony integrity. The results presented here provide a framework for the response of P. lobata to sedimentation stress under field conditions. Testing this framework and its related hypotheses using multi-omics approaches can deepen our understanding of the metabolic plasticity and acclimation potential of corals to sedimentation and their resilience in turbid reef systems.

A Novel Approach to Comparative RNA-Seq Does Not Support a Conserved Set of Orthologs Underlying Animal Regeneration

Molecular studies of animal regeneration typically focus on conserved genes and signaling pathways that underlie morphogenesis. To date, a holistic analysis of gene expression across animals has not been attempted, as it presents a suite of problems related to differences in experimental design and gene homology. By combining orthology analyses with a novel statistical method for testing gene enrichment across large data sets, we are able to test whether tissue regeneration across animals shares transcriptional regulation. We applied this method to a meta-analysis of six publicly available RNA-Seq data sets from diverse examples of animal regeneration. We recovered 160 conserved orthologous gene clusters, which are enriched in structural genes as opposed to those regulating morphogenesis. A breakdown of gene presence/absence provides limited support for the conservation of pathways typically implicated in regeneration, such as Wnt signaling and cell pluripotency pathways. Such pathways are only conserved if we permit large amounts of paralog switching through evolution. Overall, our analysis does not support the hypothesis that a shared set of ancestral genes underlie regeneration mechanisms in animals. After applying the same method to heat shock studies and getting similar results, we raise broader questions about the ability of comparative RNA-Seq to reveal conserved gene pathways across deep evolutionary relationships.

Machine learning unveils an immune-related DNA methylation profile in germline DNA from breast cancer patients

BACKGROUND

There is an unmet need for precise biomarkers for early non-invasive breast cancer detection. Here, we aimed to identify blood-based DNA methylation biomarkers that are associated with breast cancer.

METHODS

DNA methylation profiling was performed for 524 Asian Chinese individuals, comprising 256 breast cancer patients and 268 age-matched healthy controls, using the Infinium MethylationEPIC array. Feature selection was applied to 649,688 CpG sites in the training set. Predictive models were built by training three machine learning models, with performance evaluated on an independent test set. Enrichment analysis to identify transcription factors binding to regions associated with the selected CpG sites and pathway analysis for genes located nearby were conducted.

RESULTS

A methylation profile comprising 51 CpGs was identified that effectively distinguishes breast cancer patients from healthy controls achieving an AUC of 0.823 on an independent test set. Notably, it outperformed all four previously reported breast cancer-associated methylation profiles. Enrichment analysis revealed enrichment of genomic loci associated with the binding of immune modulating AP-1 transcription factors, while pathway analysis of nearby genes showed an overrepresentation of immune-related pathways.

CONCLUSION

This study has identified a breast cancer-associated methylation profile that is immune-related to potential for early cancer detection.

Clustering of multi-tissue transcriptomes in gilts with normal cyclicity or delayed puberty reveals genes related to pubertal development†

In gilts, puberty is marked by standing estrus in the presence of a boar. Delayed puberty (DP; failure to display pubertal estrus) is a major reason for gilt removal. To investigate the physiological determinants underlying DP in gilts, transcriptomic data from tissues relevant to estrus and puberty, such as mediobasal hypothalamus, anterior pituitary gland, ovarian cortex, olfactory bulb, amygdala, and hippocampus, were obtained from age-matched DP (n = 8) and cyclic control gilts at follicular phase (n = 8) and luteal phase (n = 8) of the estrous cycle. A gene expression module analysis via three-way gene × individual × tissue clustering using tensor decomposition identified pituitary and ovary gene modules contributing to regulation of pubertal development. Analysis of gene expression in the hypothalamic-pituitary-ovary axis identified reduced expression of hypothalamic genes critical for stimulating gonadotropin secretion (KISS1 and TAC3) and reduced expression of LHB in the anterior pituitary of DP gilts compared with their cyclic counterparts. Consequently, luteinizing hormone-induced genes in the ovary important for folliculogenesis (OXTR, RUNX2, and PTX3) were less expressed in DP gilts. Other intrafollicular genes (AHR, PTGS2, PTGFR, and IGFBP7) and genes in the steroidogenesis pathways (STAR and CYP11A1) necessary to complete the ovulatory cascade were also less expressed in DP gilts. This is the first clustering of multi-tissue expression data from DP and cyclic gilts to identify genes differentially expressed in gilts of similar ages but at different levels of sexual development. A critical lack of gonadotropin support and reduced ovarian responsiveness underlie DP in gilts.

Sox9 regulates alternative splicing and pancreatic beta cell function

Despite significant research, mechanisms underlying the failure of islet beta cells that result in type 2 diabetes (T2D) are still under investigation. Here, we report that Sox9, a transcriptional regulator of pancreas development, also functions in mature beta cells. Our results show that Sox9-depleted rodent beta cells have defective insulin secretion, and aging animals develop glucose intolerance, mimicking the progressive degeneration observed in T2D. Using genome editing in human stem cells, we show that beta cells lacking SOX9 have stunted first-phase insulin secretion. In human and rodent cells, loss of Sox9 disrupts alternative splicing and triggers accumulation of non-functional isoforms of genes with key roles in beta cell function. Sox9 depletion reduces expression of protein-coding splice variants of the serine-rich splicing factor arginine SRSF5, a major splicing enhancer that regulates alternative splicing. Our data highlight the role of SOX9 as a regulator of alternative splicing in mature beta cell function.

Suppressed transcript diversity and immune response in COVID-19 ICU patients: a longitudinal study

Understanding the dynamic changes in gene expression during Acute Respiratory Distress Syndrome (ARDS) progression in post-acute infection patients is crucial for unraveling the underlying mechanisms. Study investigates the longitudinal changes in gene/transcript expression patterns in hospital-admitted severe COVID-19 patients with ARDS post-acute SARS-CoV-2 infection. Blood samples were collected at three time points and patients were stratified into severe and mild ARDS, based on their oxygenation saturation (SpO2/FiO2) kinetics over 7 d. Decline in transcript diversity was observed over time, particularly in patients with higher severity, indicating dysregulated transcriptional landscape. Comparing gene/transcript-level analyses highlighted a rather limited overlap. With disease progression, a transition towards an inflammatory state was evident. Strong association was found between antibody response and disease severity, characterized by decreased antibody response and activated B cell population in severe cases. Bayesian network analysis identified various factors associated with disease progression and severity, viz. humoral response, TLR signaling, inflammatory response, interferon response, and effector T cell abundance. The findings highlight dynamic gene/transcript expression changes during ARDS progression, impact on tissue oxygenation and elucidate disease pathogenesis.

A comprehensive characterisation of phaeochromocytoma and paraganglioma tumours through histone protein profiling, DNA methylation and transcriptomic analysis genome wide

BACKGROUND

Phaeochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumours. Pathogenic variants have been identified in more than 15 susceptibility genes; associated tumours are grouped into three Clusters, reinforced by their transcriptional profiles. Cluster 1A PPGLs have pathogenic variants affecting enzymes of the tricarboxylic acid cycle, including succinate dehydrogenase. Within inherited PPGLs, these are the most common. PPGL tumours are known to undergo epigenetic reprograming, and here, we report on global histone post-translational modifications and DNA methylation levels, alongside clinical phenotypes.

RESULTS

Out of the 25 histone post-translational modifications examined, Cluster 1A PPGLs were distinguished from other tumours by a decrease in hyper-acetylated peptides and an increase in H3K4me2. DNA methylation was compared between tumours from individuals who developed metastatic disease versus those that did not. The majority of differentially methylated sites identified tended to be completely methylated or unmethylated in non-metastatic tumours, with low inter-sample variance. Metastatic tumours by contrast consistently had an intermediate DNA methylation state, including the ephrin receptor EPHA4 and its ligand EFNA3. Gene expression analyses performed to identify genes involved in metastatic tumour behaviour pin-pointed a number of genes previously described as mis-regulated in Cluster 1A tumours, as well as highlighting the tumour suppressor RGS22 and the pituitary tumour-transforming gene PTTG1.

CONCLUSIONS

Combined transcriptomic and DNA methylation analyses revealed aberrant pathways, including ones that could be implicated in metastatic phenotypes and, for the first time, we report a decrease in hyper-acetylated histone marks in Cluster 1 PPGLs.

Systemic and intrinsic functions of ATRX in glial cell fate and CNS myelination in male mice

Myelin, an extension of the oligodendrocyte plasma membrane, wraps around axons to facilitate nerve conduction. Myelination is compromised in ATR-X intellectual disability syndrome patients, but the causes are unknown. We show that loss of ATRX leads to myelination deficits in male mice that are partially rectified upon systemic thyroxine administration. Targeted ATRX inactivation in either neurons or oligodendrocyte progenitor cells (OPCs) reveals OPC-intrinsic effects on myelination. OPCs lacking ATRX fail to differentiate along the oligodendrocyte lineage and acquire a more plastic state that favors astrocytic differentiation in vitro and in vivo. ATRX chromatin occupancy in OPCs greatly overlaps with that of the chromatin remodelers CHD7 and CHD8 as well as H3K27Ac, a mark of active enhancers. Overall, our data indicate that ATRX regulates the onset of myelination systemically via thyroxine, and by promoting OPC differentiation and suppressing astrogliogenesis. These functions of ATRX identified in mice could explain white matter pathogenesis observed in ATR-X syndrome patients.

Expression and splicing mediate distinct biological signals

BACKGROUND

Through alternative splicing, most human genes produce multiple isoforms in a cell-, tissue-, and disease-specific manner. Numerous studies show that alternative splicing is essential for development, diseases, and their treatments. Despite these important examples, the extent and biological relevance of splicing are currently unknown.

RESULTS

To solve this problem, we developed pairedGSEA and used it to profile transcriptional changes in 100 representative RNA-seq datasets. Our systematic analysis demonstrates that changes in splicing, on average, contribute to 48.1% of the biological signal in expression analyses. Gene-set enrichment analysis furthermore indicates that expression and splicing both convey shared and distinct biological signals.

CONCLUSIONS

These findings establish alternative splicing as a major regulator of the human condition and suggest that most contemporary RNA-seq studies likely miss out on critical biological insights. We anticipate our results will contribute to the transition from a gene-centric to an isoform-centric research paradigm.

PLEX.I: a tool to discover features in multiplex networks that reflect clinical variation

Molecular profiling technologies, such as RNA sequencing, offer new opportunities to better discover and understand the molecular networks involved in complex biological processes. Clinically important variations of diseases, or responses to treatment, are often reflected, or even caused, by the dysregulation of molecular interaction networks specific to particular network regions. In this work, we propose the R package PLEX.I, that allows quantifying and testing variation in the direct neighborhood of a given node between networks corresponding to different conditions or states. We illustrate PLEX.I in two applications in which we discover variation that is associated with different responses to tamoxifen treatment and to sex-specific responses to bacterial stimuli. In the first case, PLEX.I analysis identifies two known pathways i) that have already been implicated in the same context as the tamoxifen mechanism of action, and ii) that would have not have been identified using classical differential gene expression analysis.

Cross-species analysis of differential transcript usage in humans and chickens with fatty liver disease

Background and Aim

Fatty liver disease is a common condition, characterized by excess fat accumulation in the liver. It can contribute to more severe liver-related health issues, making it a critical concern in avian and human medicine. Apart from modifying the gene expression of liver cells, the disease also alters the expression of specific transcript isoforms, which might serve as new biological markers for both species. This study aimed to identify cross-species genes displaying differential expressions in their transcript isoforms in humans and chickens with fatty liver disease.

Materials and Methods

We performed differential gene expression and differential transcript usage (DTU) analyses on messenger RNA datasets from the livers of both chickens and humans with fatty liver disease. Using appropriate cross-species gene identification methods, we reviewed the acquired candidate genes and their transcript isoforms to determine their potential role in fatty liver disease's pathogenesis.

Results

We identified seven genes - ALG5, BRD7, DIABLO, RSU1, SFXN5, STIMATE, TJP3, and VDAC2 - and their corresponding transcript isoforms as potential candidates (false discovery rate ≤0.05). Our findings showed that these genes most likely contribute to fatty disease development and progression.

Conclusion

This study successfully identified novel human-chicken DTU genes in fatty liver disease. Further research is encouraged to verify the functions and regulations of these transcript isoforms as potential diagnostic markers for fatty liver disease in humans and chickens.

Exportin 1 inhibition prevents neuroendocrine transformation through SOX2 down-regulation in lung and prostate cancers

In lung and prostate adenocarcinomas, neuroendocrine (NE) transformation to an aggressive derivative resembling small cell lung cancer (SCLC) is associated with poor prognosis. We previously described dependency of SCLC on the nuclear transporter exportin 1. Here, we explored the role of exportin 1 in NE transformation. We observed up-regulated exportin 1 in lung and prostate pretransformation adenocarcinomas. Exportin 1 was up-regulated after genetic inactivation of TP53 and RB1 in lung and prostate adenocarcinoma cell lines, accompanied by increased sensitivity to the exportin 1 inhibitor selinexor in vitro. Exportin 1 inhibition prevented NE transformation in different TP53/RB1-inactivated prostate adenocarcinoma xenograft models that acquire NE features upon treatment with the aromatase inhibitor enzalutamide and extended response to the EGFR inhibitor osimertinib in a lung cancer transformation patient-derived xenograft (PDX) model exhibiting combined adenocarcinoma/SCLC histology. Ectopic SOX2 expression restored the enzalutamide-promoted NE phenotype on adenocarcinoma-to-NE transformation xenograft models despite selinexor treatment. Selinexor sensitized NE-transformed lung and prostate small cell carcinoma PDXs to standard cytotoxics. Together, these data nominate exportin 1 inhibition as a potential therapeutic target to constrain lineage plasticity and prevent or treat NE transformation in lung and prostate adenocarcinoma.

RNA covariation at helix-level resolution for the identification of evolutionarily conserved RNA structure

Many biologically important RNAs fold into specific 3D structures conserved through evolution. Knowing when an RNA sequence includes a conserved RNA structure that could lead to new biology is not trivial and depends on clues left behind by conservation in the form of covariation and variation. For that purpose, the R-scape statistical test was created to identify from alignments of RNA sequences, the base pairs that significantly covary above phylogenetic expectation. R-scape treats base pairs as independent units. However, RNA base pairs do not occur in isolation. The Watson-Crick (WC) base pairs stack together forming helices that constitute the scaffold that facilitates the formation of the non-WC base pairs, and ultimately the complete 3D structure. The helix-forming WC base pairs carry most of the covariation signal in an RNA structure. Here, I introduce a new measure of statistically significant covariation at helix-level by aggregation of the covariation significance and covariation power calculated at base-pair-level resolution. Performance benchmarks show that helix-level aggregated covariation increases sensitivity in the detection of evolutionarily conserved RNA structure without sacrificing specificity. This additional helix-level sensitivity reveals an artifact that results from using covariation to build an alignment for a hypothetical structure and then testing the alignment for whether its covariation significantly supports the structure. Helix-level reanalysis of the evolutionary evidence for a selection of long non-coding RNAs (lncRNAs) reinforces the evidence against these lncRNAs having a conserved secondary structure.

Transcriptomics for Clinical and Experimental Biology Research: Hang on a Seq

Sequencing the human genome empowers translational medicine, facilitating transcriptome-wide molecular diagnosis, pathway biology, and drug repositioning. Initially, microarrays are used to study the bulk transcriptome; but now short-read RNA sequencing (RNA-seq) predominates. Positioned as a superior technology, that makes the discovery of novel transcripts routine, most RNA-seq analyses are in fact modeled on the known transcriptome. Limitations of the RNA-seq methodology have emerged, while the design of, and the analysis strategies applied to, arrays have matured. An equitable comparison between these technologies is provided, highlighting advantages that modern arrays hold over RNA-seq. Array protocols more accurately quantify constitutively expressed protein coding genes across tissue replicates, and are more reliable for studying lower expressed genes. Arrays reveal long noncoding RNAs (lncRNA) are neither sparsely nor lower expressed than protein coding genes. Heterogeneous coverage of constitutively expressed genes observed with RNA-seq, undermines the validity and reproducibility of pathway analyses. The factors driving these observations, many of which are relevant to long-read or single-cell sequencing are discussed. As proposed herein, a reappreciation of bulk transcriptomic methods is required, including wider use of the modern high-density array data-to urgently revise existing anatomical RNA reference atlases and assist with more accurate study of lncRNAs.

RNA covariation at helix-level resolution for the identification of evolutionarily conserved RNA structure

Many biologically important RNAs fold into specific 3D structures conserved through evolution. Knowing when an RNA sequence includes a conserved RNA structure that could lead to new biology is not trivial and depends on clues left behind by conservation in the form of covariation and variation. For that purpose, the R-scape statistical test was created to identify from alignments of RNA sequences, the base pairs that significantly covary above phylogenetic expectation. R-scape treats base pairs as independent units. However, RNA base pairs do not occur in isolation. The Watson-Crick (WC) base pairs stack together forming helices that constitute the scaffold that facilitates the formation of the non-WC base pairs, and ultimately the complete 3D structure. The helix-forming WC base pairs carry most of the covariation signal in an RNA structure. Here, I introduce a new measure of statistically significant covariation at helix-level by aggregation of the covariation significance and covariation power calculated at base-pair-level resolution. Performance benchmarks show that helix-level aggregated covariation increases sensitivity in the detection of evolutionarily conserved RNA structure without sacrificing specificity. This additional helix-level sensitivity reveals an artifact that results from using covariation to build an alignment for a hypothetical structure and then testing the alignment for whether its covariation significantly supports the structure. Helix-level reanalysis of the evolutionary evidence for a selection of long non-coding RNAs (lncRNAs) reinforces the evidence against these lncRNAs having a conserved secondary structure.

Availability

Helix aggregated E-values are integrated in the R-scape software package (version 2.0.0.p and higher). The R-scape web server eddylab.org/R-scape includes a link to download the source code.

Contact

elenarivas@fas.harvard.edu.

Supplementary information

Supplementary data and code are provided with this manuscript at rivaslab.org .

Systematic Review and Meta-analysis of Peripheral Blood DNA Methylation Studies in Inflammatory Bowel Disease

BACKGROUND AND AIMS

Over the past decade, the DNA methylome has been increasingly studied in peripheral blood of inflammatory bowel disease [IBD] patients. However, a comprehensive summary and meta-analysis of peripheral blood leukocyte [PBL] DNA methylation studies has thus far not been conducted. Here, we systematically reviewed all available literature up to February 2022 and summarized the observations by means of meta-analysis.

METHODS

We conducted a systematic search and critical appraisal of IBD-associated DNA methylation studies in PBL using the biomarker-based cross-sectional studies [BIOCROSS] tool. Subsequently, we performed meta-analyses on the summary statistics obtained from epigenome-wide association studies [EWAS] that included patients with Crohn's disease [CD], ulcerative colitis [UC] and/or healthy controls [HC].

RESULTS

Altogether, we included 15 studies for systematic review. Critical appraisal revealed large methodological and outcome heterogeneity between studies. Summary statistics were obtained from four studies based on a cumulative 552 samples [177 CD, 132 UC and 243 HC]. Consistent differential methylation was identified for 256 differentially methylated probes [DMPs; Bonferroni-adjusted p ≤ 0.05] when comparing CD with HC and 103 when comparing UC with HC. Comparing IBD [CD + UC] with HC resulted in 224 DMPs. Importantly, several of the previously identified DMPs, such as VMP1/TMEM49/MIR21 and RPS6KA2, were consistently differentially methylated across all studies.

CONCLUSION

Methodological homogenization of IBD epigenetic studies is needed to allow for easier aggregation and independent validation. Nonetheless, we were able to confirm previous observations. Our results can serve as the basis for future IBD epigenetic biomarker research in PBL.

Interaction between Microbes and Host in Sow Vaginas in Early Pregnancy

Extensive research has explored the causes of embryo losses during early pregnancy by analyzing interaction mechanisms in sows' uterus, ignoring the importance of the lower reproductive tract in pregnancy development regulation. Despite recent progress in understanding the diversity of vaginal microbes under different physiological states, the dynamic of sows' vaginal microbiotas during pregnancy and the interaction between vaginal microbes and the host are poorly understood. Here, we performed a comprehensive analysis of sows' vaginal microbial communities in early pregnancy coupled with overall patterns of vaginal mucosal epithelium gene expression. The vaginal microbiota was analyzed by 16s rRNA or metagenome sequencing, and the vaginal mucosal epithelium transcriptome was analyzed by RNA sequencing, followed by integration of the data layers. We found that the sows' vaginal microbiotas in early pregnancy develop dynamically, and there is a homeostasis balance of Firmicutes and Proteobacteria. Subsequently, we identified two pregnancy-specific communities, which play diverse roles. The microbes in the vagina stimulate the epithelial cells, while vaginal epithelium changes its structure and functions in response to stimulation. These changes produce specific inflammation responses to promote pregnancy development. Our findings demonstrate the interaction between microbes and host in the sow vagina in early pregnancy to promote pregnancy development, meanwhile providing a reference data set for the study of targeted therapies of microbial homeostasis dysregulation in the female reproductive tract. IMPORTANCE This work sheds light on the dynamics of the sow vaginal microbiotas in early pregnancy and its roles in pregnancy development. Furthermore, this study provides insight into the functional mechanisms of reproductive tract microbes by outlining vaginal microbe-host interactions, which might identify new research and intervention targets for improving pregnancy development by modulating lower reproductive tract microbiota.

Identifying novel regulators of placental development using time-series transcriptome data

The placenta serves as a connection between the mother and the fetus during pregnancy, providing the fetus with oxygen, nutrients, and growth hormones. However, the regulatory mechanisms and dynamic gene interaction networks underlying early placental development are understudied. Here, we generated RNA-sequencing data from mouse fetal placenta at embryonic days 7.5, 8.5, and 9.5 to identify genes with timepoint-specific expression, then inferred gene interaction networks to analyze highly connected network modules. We determined that timepoint-specific gene network modules were associated with distinct developmental processes, and with similar expression profiles to specific human placental cell populations. From each module, we identified hub genes and their direct neighboring genes, which were predicted to govern placental functions. We confirmed that four novel candidate regulators identified through our analyses regulate cell migration in the HTR-8/SVneo cell line. Overall, we predicted several novel regulators of placental development expressed in specific placental cell types using network analysis of bulk RNA-sequencing data. Our findings and analysis approaches will be valuable for future studies investigating the transcriptional landscape of early development.

CIS controls the functional polarization of GM-CSF-derived macrophages

The cytokine granulocyte-macrophage-colony stimulating factor (GM-CSF) possesses the capacity to differentiate monocytes into macrophages (MØs) with opposing functions, namely, proinflammatory M1-like MØs and immunosuppressive M2-like MØs. Despite the importance of these opposing biological outcomes, the intrinsic mechanism that regulates the functional polarization of MØs under GM-CSF signaling remains elusive. Here, we showed that GM-CSF-induced MØ polarization resulted in the expression of cytokine-inducible SH2-containing protein (CIS) and that CIS deficiency skewed the differentiation of monocytes toward immunosuppressive M2-like MØs. CIS deficiency resulted in hyperactivation of the JAK-STAT5 signaling pathway, consequently promoting downregulation of the transcription factor Interferon Regulatory Factor 8 (IRF8). Loss- and gain-of-function approaches highlighted IRF8 as a critical regulator of the M1-like polarization program. In vivo, CIS deficiency induced the differentiation of M2-like macrophages, which promoted strong Th2 immune responses characterized by the development of severe experimental asthma. Collectively, our results reveal a CIS-modulated mechanism that clarifies the opposing actions of GM-CSF in MØ differentiation and uncovers the role of GM-CSF in controlling allergic inflammation.

Multi-Organ Transcriptome Response of Lumpfish (Cyclopterus lumpus) to Aeromonas salmonicida Subspecies salmonicida Systemic Infection

Lumpfish is utilized as a cleaner fish to biocontrol sealice infestations in Atlantic salmon farms. Aeromonas salmonicida, a Gram-negative facultative intracellular pathogen, is the causative agent of furunculosis in several fish species, including lumpfish. In this study, lumpfish were intraperitoneally injected with different doses of A. salmonicida to calculate the LD50. Samples of blood, head-kidney, spleen, and liver were collected at different time points to determine the infection kinetics. We determined that A. salmonicida LD50 is 102 CFU per dose. We found that the lumpfish head-kidney is the primary target organ of A. salmonicida. Triplicate biological samples were collected from head-kidney, spleen, and liver pre-infection and at 3- and 10-days post-infection for RNA-sequencing. The reference genome-guided transcriptome assembly resulted in 6246 differentially expressed genes. The de novo assembly resulted in 403,204 transcripts, which added 1307 novel genes not identified by the reference genome-guided transcriptome. Differential gene expression and gene ontology enrichment analyses suggested that A. salmonicida induces lethal infection in lumpfish by uncontrolled and detrimental blood coagulation, complement activation, inflammation, DNA damage, suppression of the adaptive immune system, and prevention of cytoskeleton formation.

A mechanism for red coloration in vertebrates

Red coloration is a salient feature of the natural world. Many vertebrates produce red color by converting dietary yellow carotenoids into red ketocarotenoids via an unknown mechanism. Here, we show that two enzymes, cytochrome P450 2J19 (CYP2J19) and 3-hydroxybutyrate dehydrogenase 1-like (BDH1L), are sufficient to catalyze this conversion. In birds, both enzymes are expressed at the sites of ketocarotenoid biosynthesis (feather follicles and red cone photoreceptors), and genetic evidence implicates these enzymes in yellow/red color variation in feathers. In fish, the homologs of CYP2J19 and BDH1L are required for ketocarotenoid production, and we show that these enzymes are sufficient to produce ketocarotenoids in cell culture and when ectopically expressed in fish skin. Finally, we demonstrate that the red-cone-enriched tetratricopeptide repeat protein 39B (TTC39B) enhances ketocarotenoid production when co-expressed with CYP2J19 and BDH1L. The discovery of this mechanism of ketocarotenoid biosynthesis has major implications for understanding the evolution of color diversity in vertebrates.

Identification and annotation of milk associated genes from milk somatic cells using expression and RNA-seq data

It is of interest to identify and annotate milk associated genes using expression profiling and RNA-Seq data from milk somatic cells. RNA-Seq data was pre-processed and mapping was done to identify differentially expressed genes (DEG). The functional insights about the up and down regulated genes were gleaned using the protein-protein interaction Network in the STRING database followed by CytoHubba analysis in Cytoscope. Gene ontology, annotation and pathway enrichment was completed using ShinyGO, David tool and QTL analysis. These analysis shows that 21 genes are linked with the secretion of milk.

Temporally restricted activation of IFNβ signaling underlies response to immune checkpoint therapy in mice

The biological determinants of the response to immune checkpoint blockade (ICB) in cancer remain incompletely understood. Little is known about dynamic biological events that underpin therapeutic efficacy due to the inability to frequently sample tumours in patients. Here, we map the transcriptional profiles of 144 responding and non-responding tumours within two mouse models at four time points during ICB. We find that responding tumours display on/fast-off kinetics of type-I-interferon (IFN) signaling. Phenocopying of this kinetics using time-dependent sequential dosing of recombinant IFNs and neutralizing antibodies markedly improves ICB efficacy, but only when IFNβ is targeted, not IFNα. We identify Ly6C⁺/CD11b⁺ inflammatory monocytes as the primary source of IFNβ and find that active type-I-IFN signaling in tumour-infiltrating inflammatory monocytes is associated with T cell expansion in patients treated with ICB. Together, our results suggest that on/fast-off modulation of IFNβ signaling is critical to the therapeutic response to ICB, which can be exploited to drive clinical outcomes towards response.

Immune checkpoint blockade (ICB) is partially successful as a cancer therapy. Here using mouse models, the authors transcriptionally monitor responding and non-responding tumours showing that responding tumours were associated with transient IFN-β signalling which could promote the anti-tumour response.

Differential Expression of Genes between a Tolerant and a Susceptible Maize Line in Response to a Sugarcane Mosaic Virus Infection

To uncover novel genes associated with the Sugarcane mosaic virus (SCMV) response, we used RNA-Seq data to analyze differentially expressed genes (DEGs) and transcript expression pattern clusters between a tolerant/resistant (CI-RL1) and a susceptible (B73) line, in addition to the F1 progeny (CI-RL1xB73). A Gene Ontology (GO) enrichment of DEGs led us to propose three genes possibly associated with the CI-RL1 response: a heat shock 90-2 protein and two ABC transporters. Through a clustering analysis of the transcript expression patterns (CTEPs), we identified two genes putatively involved in viral systemic spread: the maize homologs to the PIEZO channel (ZmPiezo) and to the Potyvirus VPg Interacting Protein 1 (ZmPVIP1). We also observed the complex behavior of the maize eukaryotic factors ZmeIF4E and Zm-elfa (involved in translation), homologs to eIF4E and eEF1α in A. thaliana. Together, the DEG and CTEPs results lead us to suggest that the tolerant/resistant CI-RL1 response to the SCMV encompasses the action of diverse genes and, for the first time, that maize translation factors are associated with viral interaction.

A single-cell transcriptional gradient in human cutaneous memory T cells restricts Th17/Tc17 identity

The homeostatic mechanisms that fail to restrain chronic tissue inflammation in diseases, such as psoriasis vulgaris, remain incompletely understood. We profiled transcriptomes and epitopes of single psoriatic and normal skin-resident T cells, revealing a gradated transcriptional program of coordinately regulated inflammation-suppressive genes. This program, which is sharply suppressed in lesional skin, strikingly restricts Th17/Tc17 cytokine and other inflammatory mediators on the single-cell level. CRISPR-based deactivation of two core components of this inflammation-suppressive program, ZFP36L2 and ZFP36, replicates the interleukin-17A (IL-17A), granulocyte macrophage-colony-stimulating factor (GM-CSF), and interferon gamma (IFNγ) elevation in psoriatic memory T cells deficient in these transcripts, functionally validating their influence. Combinatoric expression analysis indicates the suppression of specific inflammatory mediators by individual program members. Finally, we find that therapeutic IL-23 blockade reduces Th17/Tc17 cell frequency in lesional skin but fails to normalize this inflammatory-suppressive program, suggesting how treated lesions may be primed for recurrence after withdrawal of treatment.

BaRTv2: a highly resolved barley reference transcriptome for accurate transcript-specific RNA-seq quantification

Accurate characterisation of splice junctions (SJs) as well as transcription start and end sites in reference transcriptomes allows precise quantification of transcripts from RNA-seq data, and enables detailed investigations of transcriptional and post-transcriptional regulation. Using novel computational methods and a combination of PacBio Iso-seq and Illumina short-read sequences from 20 diverse tissues and conditions, we generated a comprehensive and highly resolved barley reference transcript dataset from the European 2-row spring barley cultivar Barke (BaRTv2.18). Stringent and thorough filtering was carried out to maintain the quality and accuracy of the SJs and transcript start and end sites. BaRTv2.18 shows increased transcript diversity and completeness compared with an earlier version, BaRTv1.0. The accuracy of transcript level quantification, SJs and transcript start and end sites have been validated extensively using parallel technologies and analysis, including high-resolution reverse transcriptase-polymerase chain reaction and 5'-RACE. BaRTv2.18 contains 39 434 genes and 148 260 transcripts, representing the most comprehensive and resolved reference transcriptome in barley to date. It provides an important and high-quality resource for advanced transcriptomic analyses, including both transcriptional and post-transcriptional regulation, with exceptional resolution and precision.

ZFP36L2 suppresses mTORc1 through a P53-dependent pathway to prevent peripartum cardiomyopathy in mice

Pregnancy is associated with substantial physiological changes of the heart, and disruptions in these processes can lead to peripartum cardiomyopathy (PPCM). The molecular processes that cause physiological and pathological changes in the heart during pregnancy are not well characterized. Here, we show that mTORc1 was activated in pregnancy to facilitate cardiac enlargement that was reversed after delivery in mice. mTORc1 activation in pregnancy was negatively regulated by the mRNA-destabilizing protein ZFP36L2 through its degradation of Mdm2 mRNA and P53 stabilization, leading to increased SESN2 and REDD1 expression. This pathway impeded uncontrolled cardiomyocyte hypertrophy during pregnancy, and mice with cardiac-specific Zfp36l2 deletion developed rapid cardiac dysfunction after delivery, while prenatal treatment of these mice with rapamycin improved postpartum cardiac function. Collectively, these data provide what we believe to be a novel pathway for the regulation of mTORc1 through mRNA stabilization of a P53 ubiquitin ligase. This pathway was critical for normal cardiac growth during pregnancy, and its reduction led to PPCM-like adverse remodeling in mice.

Sperm histone H3 lysine 4 tri-methylation serves as a metabolic sensor of paternal obesity and is associated with the inheritance of metabolic dysfunction

OBJECTIVE

Parental environmental exposures can strongly influence descendant risks for adult disease. How paternal obesity changes the sperm chromatin leading to the acquisition of metabolic disease in offspring remains controversial and ill-defined. The objective of this study was to assess (1) whether obesity induced by a high-fat diet alters sperm histone methylation; (2) whether paternal obesity can induce metabolic disturbances across generations; (3) whether there could be cumulative damage to the sperm epigenome leading to enhanced metabolic dysfunction in descendants; and (4) whether obesity-sensitive regions associate with embryonic epigenetic and transcriptomic profiles. Using a genetic mouse model of epigenetic inheritance, we investigated the role of histone H3 lysine 4 methylation (H3K4me3) in the paternal transmission of metabolic dysfunction. This transgenic mouse overexpresses the histone demethylase enzyme KDM1A in the developing germline and has an altered sperm epigenome at the level of histone H3K4 methylation. We hypothesized that challenging transgenic sires with a high-fat diet would further erode the sperm epigenome and lead to enhanced metabolic disturbances in the next generations.

METHODS

To assess whether paternal obesity can have inter- or transgenerational impacts, and if so to identify potential mechanisms of this non-genetic inheritance, we used wild-type C57BL/6NCrl and transgenic males with a pre-existing altered sperm epigenome. To induce obesity, sires were fed either a control or high-fat diet (10% or 60% kcal fat, respectively) for 10-12 weeks, then bred to wild-type C57BL/6NCrl females fed a regular diet. F1 and F2 descendants were characterized for metabolic phenotypes by examining the effects of paternal obesity by sex, on body weight, fat mass distribution, the liver transcriptome, intraperitoneal glucose, and insulin tolerance tests. To determine whether obesity altered the F0 sperm chromatin, native chromatin immunoprecipitation-sequencing targeting H3K4me3 was performed. To gain insight into mechanisms of paternal transmission, we compared our sperm H3K4me3 profiles with embryonic and placental chromatin states, histone modification, and gene expression profiles.

RESULTS

Obesity-induced alterations in H3K4me3 occurred in genes implicated in metabolic, inflammatory, and developmental processes. These processes were associated with offspring metabolic dysfunction and corresponded to genes enriched for H3K4me3 in embryos and overlapped embryonic and placenta gene expression profiles. Transgenerational susceptibility to metabolic disease was only observed when obese F0 had a pre-existing modified sperm epigenome. This coincided with increased H3K4me3 alterations in sperm and more severe phenotypes affecting their offspring.

CONCLUSIONS

Our data suggest sperm H3K4me3 might serve as a metabolic sensor that connects paternal diet with offspring phenotypes via the placenta. This non-DNA-based knowledge of inheritance has the potential to improve our understanding of how environment shapes heritability and may lead to novel routes for the prevention of disease. This study highlights the need to further study the connection between the sperm epigenome, placental development, and children's health.

SUMMARY SENTENCE

Paternal obesity impacts sperm H3K4me3 and is associated with placenta, embryonic and metabolic outcomes in descendants.

SRTdb: an omnibus for human tissue and cancer-specific RNA transcripts

The production of functional mature RNA transcripts from genes undergoes various pre-transcriptional regulation and post-transcriptional modifications. Accumulating studies demonstrated that gene transcription carries out in tissue and cancer type-dependent ways. However, RNA transcript-level specificity analysis in large-scale transcriptomics data across different normal tissue and cancer types is lacking. We applied reference-based de novo transcript assembly and quantification of 27,741 samples across 33 cancer types, 29 tissue types, and 25 cancer cell line types. We totally identified 231,836 specific RNA transcripts (SRTs) across various tissue and cancer types, most of which are found independent of specific genes. Almost half of tumor SRTs are also tissue-specific but in different tissues. Furthermore, we found that 10 ~ 20% of tumor SRTs in most tumor types were testis-specific. The SRT database (SRTdb) was constructed based on these resources. Taking liver cancer as an example, we showed how SRTdb resource is utilized to optimize the identification of RNA transcripts for more precision diagnosis of particular cancers. Our results provide a useful resource for exploring transcript specificity across various cancer and tissue types, and boost the precision medicine for tumor patients.

Placental Transcription Profiling in 6-23 Weeks' Gestation Reveals Differential Transcript Usage in Early Development

The human placenta is a rapidly developing transient organ that is key to pregnancy success. Early development of the conceptus occurs in a low oxygen environment before oxygenated maternal blood begins to flow into the placenta at ~10-12 weeks' gestation. This process is likely to substantially affect overall placental gene expression. Transcript variability underlying gene expression has yet to be profiled. In this study, accurate transcript expression profiles were identified for 84 human placental chorionic villus tissue samples collected across 6-23 weeks' gestation. Differential gene expression (DGE), differential transcript expression (DTE) and differential transcript usage (DTU) between 6-10 weeks' and 11-23 weeks' gestation groups were assessed. In total, 229 genes had significant DTE yet no significant DGE. Integration of DGE and DTE analyses found that differential expression patterns of individual transcripts were commonly masked upon aggregation to the gene-level. Of the 611 genes that exhibited DTU, 534 had no significant DGE or DTE. The four most significant DTU genes ADAM10, VMP1, GPR126, and ASAH1, were associated with hypoxia-responsive pathways. Transcript usage is a likely regulatory mechanism in early placentation. Identification of functional roles will facilitate new insight in understanding the origins of pregnancy complications.

acorde unravels functionally interpretable networks of isoform co-usage from single cell data

Alternative splicing (AS) is a highly-regulated post-transcriptional mechanism known to modulate isoform expression within genes and contribute to cell-type identity. However, the extent to which alternative isoforms establish co-expression networks that may be relevant in cellular function has not been explored yet. Here, we present acorde, a pipeline that successfully leverages bulk long reads and single-cell data to confidently detect alternative isoform co-expression relationships. To achieve this, we develop and validate percentile correlations, an innovative approach that overcomes data sparsity and yields accurate co-expression estimates from single-cell data. Next, acorde uses correlations to cluster co-expressed isoforms into a network, unraveling cell type-specific alternative isoform usage patterns. By selecting same-gene isoforms between these clusters, we subsequently detect and characterize genes with co-differential isoform usage (coDIU) across cell types. Finally, we predict functional elements from long read-defined isoforms and provide insight into biological processes, motifs, and domains potentially controlled by the coordination of post-transcriptional regulation. The code for acorde is available at https://github.com/ConesaLab/acorde .

Accurate expression quantification from nanopore direct RNA sequencing with NanoCount

Accurately quantifying gene and isoform expression changes is essential to understanding cell functions, differentiation and disease. Sequencing full-length native RNAs using long-read direct RNA sequencing (DRS) has the potential to overcome many limitations of short and long-read sequencing methods that require RNA fragmentation, cDNA synthesis or PCR. However, there are a lack of tools specifically designed for DRS and its ability to identify differential expression in complex organisms is poorly characterised. We developed NanoCount for fast, accurate transcript isoform quantification in DRS and demonstrate it outperforms similar methods. Using synthetic controls and human SH-SY5Y cell differentiation into neuron-like cells, we show that DRS accurately quantifies RNA expression and identifies differential expression of genes and isoforms. Differential expression of 231 genes, 333 isoforms, plus 27 isoform switches were detected between undifferentiated and differentiated SH-SY5Y cells and samples clustered by differentiation state at the gene and isoform level. Genes upregulated in neuron-like cells were associated with neurogenesis. NanoCount quantification of thousands of novel isoforms discovered with DRS likewise enabled identification of their differential expression. Our results demonstrate enhanced DRS isoform quantification with NanoCount and establish the ability of DRS to identify biologically relevant differential expression of genes and isoforms.

Transcriptomic Landscape of Herbivore Oviposition in Arabidopsis: A Systematic Review

Herbivore oviposition produces all sorts of responses in plants, involving wide and complex genetic rearrangements. Many transcriptomic studies have been performed to understand this interaction, producing a bulk of transcriptomic data. However, the use of many transcriptomic techniques across the years, the lack of comparable transcriptomic context at the time of publication, and the use of outdated databases are limitations to understand this biological process. The current analysis intends to retrieve oviposition studies and process them with up-to-date techniques and updated databases. To reduce heterogeneities, the same processing techniques were applied, and Arabidopsis was selected to avoid divergencies on plant taxa stress response strategies. By doing so, we intended to understand the major mechanisms and regulatory processes linked to oviposition response. Differentially expressed gene (DEG) identification and co-expression network-based analyses were the main tools to achieve this goal. Two microarray studies and three RNA-seq analyses passed the screening criteria. The collected data pertained to the lepidopteran Pieris brassicae and the mite Tetranychus urticae, and covered a timeline from 3 to 144 h. Among the 18, 221 DEGs found, 15, 406 were exclusive of P. brassicae (72 h) and 801 were exclusive for the rest of the experiments. Excluding P. brassicae (72 h), shared genes on the rest of the experiments were twice the unique genes, indicating common response mechanisms were predominant. Enrichment analyses indicated that shared processes were circumscribed to earlier time points, and after 24 h, the divergences escalated. The response was characterized by patterns of time-dependent waves of unique processes. P. brassicae oviposition induced a rich response that shared functions across time points, while T. urticae eggs triggered less but more diverse time-dependent functions. The main processes altered were associated with hormonal cascades [e.g., salicilic acid (SA) and jasmonic acid (JA)], defense [reactive oxygen species (ROS) and glucosinolates], cell wall rearrangements, abiotic stress responses, and energy metabolism. Key gene drivers of the identified processes were also identified and presented. The current results enrich and clarify the information regarding the molecular behavior of the plant in response to oviposition by herbivores. This information is valuable for multiple stress response engineering tools, among other applications.

Long read sequencing reveals novel isoforms and insights into splicing regulation during cell state changes

BACKGROUND

Alternative splicing is a key mechanism underlying cellular differentiation and a driver of complexity in mammalian neuronal tissues. However, understanding of which isoforms are differentially used or expressed and how this affects cellular differentiation remains unclear. Long read sequencing allows full-length transcript recovery and quantification, enabling transcript-level analysis of alternative splicing processes and how these change with cell state. Here, we utilise Oxford Nanopore Technologies sequencing to produce a custom annotation of a well-studied human neuroblastoma cell line SH-SY5Y, and to characterise isoform expression and usage across differentiation.

RESULTS

We identify many previously unannotated features, including a novel transcript of the voltage-gated calcium channel subunit gene, CACNA2D2. We show differential expression and usage of transcripts during differentiation identifying candidates for future research into state change regulation.

CONCLUSIONS

Our work highlights the potential of long read sequencing to uncover previously unknown transcript diversity and mechanisms influencing alternative splicing.

Gene expression in the amygdala and hippocampus of cyclic and acyclic gilts

Age at first estrus is the earliest phenotypic indicator of future reproductive success of gilts. Prebreeding anestrus is a major reason for reproductive failure leading to culling of replacement gilts. The two types of prebreeding anestrus are delay in attaining puberty (prepubertal anestrus, PPA) and silent ovulation (behavioral anestrus, BA). Neural tissues such as amygdala and hippocampus play a major role in regulating sexual behavior, social interactions, and receptivity to males. Differences in gene expression in the amygdala and hippocampus of gilts were analyzed in three comparisons: 1) PPA cases and cyclic controls at follicular phase of estrous cycle, 2) BA cases and cyclic controls at luteal phase of estrous cycle, and 3) gilts at different stages of the ovarian cycle (cyclic gilts at follicular phase and luteal phase of estrous cycle) to gain functional understanding of how these rarely studied tissues may differ between pubertal phenotypes and different stages of the estrous cycle of gilts. Differentially expressed genes (DEG) between PPA and BA cases and their respective cyclic controls were involved in neurological and behavioral disorders as well as nervous system functions that could directly or indirectly involved in development of behaviors related to estrus. The comparison between cyclic follicular and luteal phase control gilts identified the greatest number of DEG in the hippocampus and amygdala. These DEG were involved in adult neurogenesis and neural synapse (e.g., GABAergic, dopamine, cholinergic), suggesting that these tissues undergo structural changes and synaptic plasticity in gilts. This is the first report to demonstrate that the stage of estrous cycle is associated with dynamic changes in gene expression within porcine hippocampus and amygdala and indicates a role of gonadal steroids in regulating their biology.

Hippocampal neurons' cytosolic and membrane-bound ribosomal transcript profiles are differentially regulated by learning and subsequent sleep

Sleep loss disrupts consolidation of hippocampus-dependent memory. To understand the cellular basis for this effect, we quantified RNAs associated with translating ribosomes in cytosol and on cellular membranes of different hippocampal neuron populations. Our analysis suggests that while sleep loss (but not learning) alters numerous ribosomal transcripts in cytosol, learning has dramatic effects on transcript profiles for less–well-characterized membrane-bound ribosomes. We demonstrate that postlearning sleep deprivation occludes already minimal learning-driven changes on cytosolic ribosomes. It simultaneously alters transcripts associated with metabolic and biosynthetic processes in membrane-bound ribosomes in excitatory hippocampal neurons and highly active, putative “engram” neurons, respectively. Together, these findings provide insights into the cellular mechanisms altered by learning and their disruption by subsequent sleep loss.

The hippocampus is essential for consolidating transient experiences into long-lasting memories. Memory consolidation is facilitated by postlearning sleep, although the underlying cellular mechanisms are largely unknown. We took an unbiased approach to this question by using a mouse model of hippocampally mediated, sleep-dependent memory consolidation (contextual fear memory). Because synaptic plasticity is associated with changes to both neuronal cell membranes (e.g., receptors) and cytosol (e.g., cytoskeletal elements), we characterized how these cell compartments are affected by learning and subsequent sleep or sleep deprivation (SD). Translating ribosome affinity purification was used to profile ribosome-associated RNAs in different subcellular compartments (cytosol and membrane) and in different cell populations (whole hippocampus, Camk2a+ neurons, or highly active neurons with phosphorylated ribosomal subunit S6 [pS6+]). We examined how transcript profiles change as a function of sleep versus SD and prior learning (contextual fear conditioning; CFC). While sleep loss altered many cytosolic ribosomal transcripts, CFC altered almost none, and CFC-driven changes were occluded by subsequent SD. In striking contrast, SD altered few transcripts on membrane-bound (MB) ribosomes, while learning altered many more (including long non-coding RNAs [lncRNAs]). The cellular pathways most affected by CFC were involved in structural remodeling. Comparisons of post-CFC MB transcript profiles between sleeping and SD mice implicated changes in cellular metabolism in Camk2a+ neurons and protein synthesis in highly active pS6+ (putative “engram”) neurons as biological processes disrupted by SD. These findings provide insights into how learning affects hippocampal neurons and suggest that the effects of SD on memory consolidation are cell type and subcellular compartment specific.

3D RNA-seq: a powerful and flexible tool for rapid and accurate differential expression and alternative splicing analysis of RNA-seq data for biologists

RNA-sequencing (RNA-seq) analysis of gene expression and alternative splicing should be routine and robust but is often a bottleneck for biologists because of different and complex analysis programs and reliance on specialized bioinformatics skills. We have developed the '3D RNA-seq' App, an R shiny App and web-based pipeline for the comprehensive analysis of RNA-seq data from any organism. It represents an easy-to-use, flexible and powerful tool for analysis of both gene and transcript-level gene expression to identify differential gene/transcript expression, differential alternative splicing and differential transcript usage (3D) as well as isoform switching from RNA-seq data. 3D RNA-seq integrates state-of-the-art differential expression analysis tools and adopts best practice for RNA-seq analysis. The program is designed to be run by biologists with minimal bioinformatics experience (or by bioinformaticians) allowing lab scientists to analyse their RNA-seq data. It achieves this by operating through a user-friendly graphical interface which automates the data flow through the programs in the pipeline. The comprehensive analysis performed by 3D RNA-seq is extremely rapid and accurate, can handle complex experimental designs, allows user setting of statistical parameters, visualizes the results through graphics and tables, and generates publication quality figures such as heat-maps, expression profiles and GO enrichment plots. The utility of 3D RNA-seq is illustrated by analysis of data from a time-series of cold-treated Arabidopsis plants and from dexamethasone-treated male and female mouse cortex and hypothalamus data identifying dexamethasone-induced sex- and brain region-specific differential gene expression and alternative splicing.

3D RNA-seq: a powerful and flexible tool for rapid and accurate differential expression and alternative splicing analysis of RNA-seq data for biologists

RNA-sequencing (RNA-seq) analysis of gene expression and alternative splicing should be routine and robust but is often a bottleneck for biologists because of different and complex analysis programs and reliance on specialized bioinformatics skills. We have developed the '3D RNA-seq' App, an R shiny App and web-based pipeline for the comprehensive analysis of RNA-seq data from any organism. It represents an easy-to-use, flexible and powerful tool for analysis of both gene and transcript-level gene expression to identify differential gene/transcript expression, differential alternative splicing and differential transcript usage (3D) as well as isoform switching from RNA-seq data. 3D RNA-seq integrates state-of-the-art differential expression analysis tools and adopts best practice for RNA-seq analysis. The program is designed to be run by biologists with minimal bioinformatics experience (or by bioinformaticians) allowing lab scientists to analyse their RNA-seq data. It achieves this by operating through a user-friendly graphical interface which automates the data flow through the programs in the pipeline. The comprehensive analysis performed by 3D RNA-seq is extremely rapid and accurate, can handle complex experimental designs, allows user setting of statistical parameters, visualizes the results through graphics and tables, and generates publication quality figures such as heat-maps, expression profiles and GO enrichment plots. The utility of 3D RNA-seq is illustrated by analysis of data from a time-series of cold-treated Arabidopsis plants and from dexamethasone-treated male and female mouse cortex and hypothalamus data identifying dexamethasone-induced sex- and brain region-specific differential gene expression and alternative splicing.

Comprehensive molecular characterization of lung tumors implicates AKT and MYC signaling in adenocarcinoma to squamous cell transdifferentiation

BACKGROUND

Lineage plasticity, the ability to transdifferentiate among distinct phenotypic identities, facilitates therapeutic resistance in cancer. In lung adenocarcinomas (LUADs), this phenomenon includes small cell and squamous cell (LUSC) histologic transformation in the context of acquired resistance to targeted inhibition of driver mutations. LUAD-to-LUSC transdifferentiation, occurring in up to 9% of EGFR-mutant patients relapsed on osimertinib, is associated with notably poor prognosis. We hypothesized that multi-parameter profiling of the components of mixed histology (LUAD/LUSC) tumors could provide insight into factors licensing lineage plasticity between these histologies.

METHODS

We performed genomic, epigenomics, transcriptomics and protein analyses of microdissected LUAD and LUSC components from mixed histology tumors, pre-/post-transformation tumors and reference non-transformed LUAD and LUSC samples. We validated our findings through genetic manipulation of preclinical models in vitro and in vivo and performed patient-derived xenograft (PDX) treatments to validate potential therapeutic targets in a LUAD PDX model acquiring LUSC features after osimertinib treatment.

RESULTS

Our data suggest that LUSC transdifferentiation is primarily driven by transcriptional reprogramming rather than mutational events. We observed consistent relative upregulation of PI3K/AKT, MYC and PRC2 pathway genes. Concurrent activation of PI3K/AKT and MYC induced squamous features in EGFR-mutant LUAD preclinical models. Pharmacologic inhibition of EZH1/2 in combination with osimertinib prevented relapse with squamous-features in an EGFR-mutant patient-derived xenograft model, and inhibition of EZH1/2 or PI3K/AKT signaling re-sensitized resistant squamous-like tumors to osimertinib.

CONCLUSIONS

Our findings provide the first comprehensive molecular characterization of LUSC transdifferentiation, suggesting putative drivers and potential therapeutic targets to constrain or prevent lineage plasticity.

Reorganization of the 3D genome pinpoints non-coding drivers of primary prostate tumors

Prostate cancer is a heterogeneous disease whose progression is linked to genome instability. However, the impact of this instability on the non-coding genome and its three-dimensional organization to aid progression is unclear. Using primary benign and tumor tissue, we find a high concordance in higher order three-dimensional genome organization. This concordance argues for constraints to the topology of prostate tumor genomes. Nonetheless, we identified changes in focal chromatin interactions, typical of loops bridging non-coding cis-regulatory elements, and showed how structural variants can induce these changes to guide cis-regulatory element hijacking. Such events resulted in opposing differential expression of genes found at antipodes of rearrangements. Collectively, these results argue that changes to focal chromatin interactions, as opposed to higher order genome organization, allow for aberrant gene regulation and are repeatedly mediated by structural variants in primary prostate cancer.

Human Saliva as a Diagnostic Specimen for Early Detection of Inflammatory Biomarkers by Real-Time RT-PCR

Nowadays human saliva is more frequently studied as a non-invasive, stress-free, and preferable diagnostic material than blood. Supporting evidences acknowledge saliva as a mirror that reflects the body's physical state. Numerous studies have also demonstrated the presence and use of RNA derived from saliva in the early diagnosis of disease by real-time reverse transcriptase polymerase chain reaction (RT-PCR). Assessing the host inflammatory response in patients and its resolution at an early stage can serve as a prognostic and predictive method in determining therapeutic response or disease progression. In this context, the potential of saliva as a specimen to diagnose early inflammatory biomarkers using RT-PCR seems fascinating and useful. Here, we review inflammatory biomarkers within the saliva, focusing on early detection of these biomarkers using RT-PCR and the factors influencing the quality of saliva specimen.