Comparison of the transcriptional landscapes between human and mouse tissues

Assessing and mitigating batch effects in large-scale omics studies

Batch effects in omics data are notoriously common technical variations unrelated to study objectives, and may result in misleading outcomes if uncorrected, or hinder biomedical discovery if over-corrected. Assessing and mitigating batch effects is crucial for ensuring the reliability and reproducibility of omics data and minimizing the impact of technical variations on biological interpretation. In this review, we highlight the profound negative impact of batch effects and the urgent need to address this challenging problem in large-scale omics studies. We summarize potential sources of batch effects, current progress in evaluating and correcting them, and consortium efforts aiming to tackle them.

Maternal immune activation exerts long-term effects on activity and sleep in male offspring mice

Exposure to infectious or non-infectious immune activation during early development is a serious risk factor for long-term behavioural dysfunctions. Mouse models of maternal immune activation (MIA) have increasingly been used to address neuronal and behavioural dysfunctions in response to prenatal infections. One commonly employed MIA model involves administering poly(I:C) (polyriboinosinic-polyribocytdilic acid), a synthetic analogue of double-stranded RNA, during gestation, which robustly induces an acute viral-like inflammatory response. Using electroencephalography (EEG) and infrared (IR) activity recordings, we explored alterations in sleep/wake, circadian and locomotor activity patterns on the adult male offspring of poly(I:C)-treated mothers. Our findings demonstrate that these offspring displayed reduced home cage activity during the (subjective) night under both light/dark or constant darkness conditions. In line with this finding, these mice exhibited an increase in non-rapid eye movement (NREM) sleep duration as well as an increase in sleep spindles density. Following sleep deprivation, poly(I:C)-exposed offspring extended NREM sleep duration and prolonged NREM sleep bouts during the dark phase as compared with non-exposed mice. Additionally, these mice exhibited a significant alteration in NREM sleep EEG spectral power under heightened sleep pressure. Together, our study highlights the lasting effects of infection and/or immune activation during pregnancy on circadian activity and sleep/wake patterns in the offspring.

Comparative proteomics analysis of the mouse mini-gut organoid: insights into markers of gluten challenge from celiac disease intestinal biopsies

Introduction

Organoid models enable three-dimensional representation of cellular systems, providing flexible and accessible research tools, and can highlight key biomolecules. Such models of the intestinal epithelium can provide significant knowledge for the study of celiac disease and provide an additional context for the nature of markers observed from patient biopsy data.

Methods

Using LC-MS/MS, the proteomes of the crypt and enterocyte-like states of a mouse mini-gut organoid model were measured. The data were further compared with published biopsy data by comparing the changes induced by gluten challenge after a gluten-free diet.

Results and discussion

These analyses identified 4,850 protein groups and revealed how 400 putative biomarkers of dietary challenge were differentially expressed in the organoid model. In addition to the extensive changes within the differentiated cells, the data reiterated the disruption of the crypt-villus axis after gluten challenge. The mass spectrometry data are available via ProteomeXchange with the identifier PXD025690.

Gapped-kmer sequence modeling robustly identifies regulatory vocabularies and distal enhancers conserved between evolutionarily distant mammals

Gene regulatory elements drive complex biological phenomena and their mutations are associated with common human diseases. The impacts of human regulatory variants are often tested using model organisms such as mice. However, mapping human enhancers to conserved elements in mice remains a challenge, due to both rapid enhancer evolution and limitations of current computational methods. We analyze distal enhancers across 45 matched human/mouse cell/tissue pairs from a comprehensive dataset of DNase-seq experiments, and show that while cell-specific regulatory vocabulary is conserved, enhancers evolve more rapidly than promoters and CTCF binding sites. Enhancer conservation rates vary across cell types, in part explainable by tissue specific transposable element activity. We present an improved genome alignment algorithm using gapped-kmer features, called gkm-align, and make genome wide predictions for 1,401,803 orthologous regulatory elements. We show that gkm-align discovers 23,660 novel human/mouse conserved enhancers missed by previous algorithms, with strong evidence of conserved functional activity.

Generation of functional neurons from adult human mucosal olfactory ensheathing glia by direct lineage conversion

A recent approach to promote central nervous system (CNS) regeneration after injury or disease is direct conversion of somatic cells to neurons. This is achieved by transduction of viral vectors that express neurogenic transcription factors. In this work we propose adult human mucosal olfactory ensheathing glia (hmOEG) as a candidate for direct reprogramming to neurons due to its accessibility and to its well-characterized neuroregenerative capacity. After induction of hmOEG with the single neurogenic transcription factor NEUROD1, the cells under study exhibited morphological and immunolabeling neuronal features, fired action potentials and expressed glutamatergic and GABAergic markers. In addition, after engraftment of transduced hmOEG cells in the mouse hippocampus, these cells showed specific neuronal labeling. Thereby, if we add to the neuroregenerative capacity of hmOEG cultures the conversion to neurons of a fraction of their population through reprogramming techniques, the engraftment of hmOEG and hmOEG-induced neurons could be a procedure to enhance neural repair after central nervous system injury.

Lethal phenotypes in Mendelian disorders

PURPOSE

Existing resources that characterize the essentiality status of genes are based on either proliferation assessment in human cell lines, viability evaluation in mouse knockouts, or constraint metrics derived from human population sequencing studies. Several repositories document phenotypic annotations for rare disorders; however, there is a lack of comprehensive reporting on lethal phenotypes.

METHODS

We queried Online Mendelian Inheritance in Man for terms related to lethality and classified all Mendelian genes according to the earliest age of death recorded for the associated disorders, from prenatal death to no reports of premature death. We characterized the genes across these lethality categories, examined the evidence on viability from mouse models and explored how this information could be used for novel gene discovery.

RESULTS

We developed the Lethal Phenotypes Portal to showcase this curated catalog of human essential genes. Differences in the mode of inheritance, physiological systems affected, and disease class were found for genes in different lethality categories, as well as discrepancies between the lethal phenotypes observed in mouse and human.

CONCLUSION

We anticipate that this resource will aid clinicians in the diagnosis of early lethal conditions and assist researchers in investigating the properties that make these genes essential for human development.

Genomic, molecular, and cellular divergence of the human brain

While many core biological processes are conserved across species, the human brain has evolved with unique capacities. Current understanding of the neurobiological mechanisms that endow human traits as well as associated vulnerabilities remains limited. However, emerging data have illuminated species divergence in DNA elements and genome organization, in molecular, morphological, and functional features of conserved neural cell types, as well as temporal differences in brain development. Here, we summarize recent data on unique features of the human brain and their complex implications for the study and treatment of brain diseases. We also consider key outstanding questions in the field and discuss the technologies and foundational knowledge that will be required to accelerate understanding of human neurobiology.

SCTC: inference of developmental potential from single-cell transcriptional complexity

Inferring the developmental potential of single cells from scRNA-Seq data and reconstructing the pseudo-temporal path of cell development are fundamental but challenging tasks in single-cell analysis. Although single-cell transcriptional diversity (SCTD) measured by the number of expressed genes per cell has been widely used as a hallmark of developmental potential, it may lead to incorrect estimation of differentiation states in some cases where gene expression does not decrease monotonously during the development process. In this study, we propose a novel metric called single-cell transcriptional complexity (SCTC), which draws on insights from the economic complexity theory and takes into account the sophisticated structure information of scRNA-Seq count matrix. We show that SCTC characterizes developmental potential more accurately than SCTD, especially in the early stages of development where cells typically have lower diversity but higher complexity than those in the later stages. Based on the SCTC, we provide an unsupervised method for accurate, robust, and transferable inference of single-cell pseudotime. Our findings suggest that the complexity emerging from the interplay between cells and genes determines the developmental potential, providing new insights into the understanding of biological development from the perspective of complexity theory.

Exploration of tissue fixation methods suitable for digital pathological studies of the testis

BACKGROUND

The way of testicular tissue fixation directly affects the correlation and structural integrity between connective tissue and seminiferous tubules, which is essential for the study of male reproductive development. This study aimed to find the optimal fixative and fixation time to produce high-quality testicular histopathological sections, and provided a suitable foundation for in-depth study of male reproductive development with digital pathology technology.

METHODS

Testes were removed from both sides of 25 male C57BL/6 mice. Samples were fixed in three different fixatives, 10% neutral buffered formalin (10% NBF), modified Davidson's fluid (mDF), and Bouin's Fluid (BF), for 8, 12, and 24 h, respectively. Hematoxylin and eosin (H&E) staining, periodic acid Schiff-hematoxylin (PAS-h) staining, and immunohistochemistry (IHC) were used to evaluate the testicle morphology, staging of mouse seminiferous tubules, and protein preservation. Aperio ScanScope CS2 panoramic scanning was used to perform quantitative analyses.

RESULTS

H&E staining showed 10% NBF resulted in an approximately 15-17% reduction in the thickness of seminiferous epithelium. BF and mDF provided excellent results when staining acrosomes with PAS-h. IHC staining of synaptonemal complexes 3 (Sycp3) was superior in mDF compared to BF-fixed samples. Fixation in mDF and BF improved testis tissue morphology compared to 10% NBF.

CONCLUSIONS

Quantitative analysis showed that BF exhibited a very low IHC staining efficiency and revealed that mouse testes fixed for 12 h with mDF, exhibited morphological details, excellent efficiency of PAS-h staining for seminiferous tubule staging, and IHC results. In addition, the morphological damage of testis was prolonged with the duration of fixation time.

Next-Generation Modeling of Cancer Using Organoids

In the last decade, organoid technology has become a cornerstone in cancer research. Organoids are long-term primary cell cultures, usually of epithelial origin, grown in a three-dimensional (3D) protein matrix and a fully defined medium. Organoids can be derived from many organs and cancer types and sites, encompassing both murine and human tissues. Importantly, they can be established from various stages during tumor evolution and recapitulate with high accuracy patient genomics and phenotypes in vitro, offering a platform for personalized medicine. Additionally, organoids are remarkably amendable for experimental manipulation. Taken together, these features make organoids a powerful tool with applications in basic cancer research and personalized medicine. Here, we will discuss the origins of organoid culture, applications in cancer research, and how cancer organoids can synergize with other models of cancer to drive basic discoveries as well as to translate these toward clinical solutions.

Mapping putative enhancers in mouse oocytes and early embryos reveals TCF3/12 as key folliculogenesis regulators

Dynamic epigenomic reprogramming occurs during mammalian oocyte maturation and early development. However, the underlying transcription circuitry remains poorly characterized. By mapping cis-regulatory elements using H3K27ac, we identified putative enhancers in mouse oocytes and early embryos distinct from those in adult tissues, enabling global transitions of regulatory landscapes around fertilization and implantation. Gene deserts harbour prevalent putative enhancers in fully grown oocytes linked to oocyte-specific genes and repeat activation. Embryo-specific enhancers are primed before zygotic genome activation and are restricted by oocyte-inherited H3K27me3. Putative enhancers in oocytes often manifest H3K4me3, bidirectional transcription, Pol II binding and can drive transcription in STARR-seq and a reporter assay. Finally, motif analysis of these elements identified crucial regulators of oogenesis, TCF3 and TCF12, the deficiency of which impairs activation of key oocyte genes and folliculogenesis. These data reveal distinctive regulatory landscapes and their interacting transcription factors that underpin the development of mammalian oocytes and early embryos.

Exploring the prospects, advancements, and challenges of in vitro modeling of the heart-brain axis

Research on bidirectional communication between the heart and brain has often relied on studies involving nonhuman animals. Dependance on animal models offer limited applicability to humans and a lack of high-throughput screening. Recently, the field of 3D cell biology, specifically organoid technology, has rapidly emerged as a valuable tool for studying interactions across organ systems, i.e., gut-brain axis. The initial success of organoid models indicates the usefulness of 3D cultures for elucidating the intricate interactivity of the autonomic nervous system and overall health. This perspective aims to explore the potential of advancing in vitro modeling of the heart-brain axis by discussing the benefits, applications, and adaptability of organoid technologies. We closely examine the current state of brain organoids in conjunction with the advancements of cardiac organoids. Moreover, we explore the use of combined organoid systems to investigate pathophysiology and provide a platform for treatment discovery. Finally, we address the challenges that accompany the use of 3D models for studying the heart-brain axis with an emphasis on generating tailored engineering strategies for further refinement of dynamic organ system modeling in vitro.

An integrated toolkit for human microglia functional genomics

BACKGROUND

Microglia, the brain's resident immune cells, play vital roles in brain development, and disorders like Alzheimer's disease (AD). Human iPSC-derived microglia (iMG) provide a promising model to study these processes. However, existing iMG generation protocols face challenges, such as prolonged differentiation time, lack of detailed characterization, and limited gene function investigation via CRISPR-Cas9.

METHODS

Our integrated toolkit for in-vitro microglia functional genomics optimizes iPSC differentiation into iMG through a streamlined two-step, 20-day process, producing iMG with a normal karyotype. We confirmed the iMG's authenticity and quality through single-cell RNA sequencing, chromatin accessibility profiles (ATAC-Seq), proteomics and functional tests. The toolkit also incorporates a drug-dependent CRISPR-ON/OFF system for temporally controlled gene expression. Further, we facilitate the use of multi-omic data by providing online searchable platform that compares new iMG profiles to human primary microglia: https://sherlab.shinyapps.io/IPSC-derived-Microglia/ .

RESULTS

Our method generates iMG that closely align with human primary microglia in terms of transcriptomic, proteomic, and chromatin accessibility profiles. Functionally, these iMG exhibit Ca2 + transients, cytokine driven migration, immune responses to inflammatory signals, and active phagocytosis of CNS related substrates including synaptosomes, amyloid beta and myelin. Significantly, the toolkit facilitates repeated iMG harvesting, essential for large-scale experiments like CRISPR-Cas9 screens. The standalone ATAC-Seq profiles of our iMG closely resemble primary microglia, positioning them as ideal tools to study AD-associated single nucleotide variants (SNV) especially in the genome regulatory regions.

CONCLUSIONS

Our advanced two-step protocol rapidly and efficiently produces authentic iMG. With features like the CRISPR-ON/OFF system and a comprehensive multi-omic data platform, our toolkit equips researchers for robust microglial functional genomic studies. By facilitating detailed SNV investigation and offering a sustainable cell harvest mechanism, the toolkit heralds significant progress in neurodegenerative disease drug research and therapeutic advancement.

MALAT1: A Long Non-Coding RNA with Multiple Functions and Its Role in Processes Associated with Fat Deposition

Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) belongs to the lncRNA molecules, which are involved in transcriptional and epigenetic regulation and the control of gene expression, including the mechanism of chromatin remodeling. MALAT1 was first discovered during carcinogenesis in lung adenocarcinoma, hence its name. In humans, 66 of its isoforms have been identified, and in pigs, only 2 are predicted, for which information is available in Ensembl databases (Ensembl Release 111). MALAT1 is expressed in numerous tissues, including adipose, adrenal gland, heart, kidney, liver, ovary, pancreas, sigmoid colon, small intestine, spleen, and testis. MALAT1, as an lncRNA, shows a wide range of functions. It is involved in the regulation of the cell cycle, where it has pro-proliferative effects and high cellular levels during the G1/S and mitotic (M) phases. Moreover, it is involved in invasion, metastasis, and angiogenesis, and it has a crucial function in alternative splicing during carcinogenesis. In addition, MALAT1 plays a significant role in the processes of fat deposition and adipogenesis. The human adipose tissue stem cells, during differentiation into adipocytes, secrete MALAT1 as one the most abundant lncRNAs in the exosomes. MALAT1 expression in fat tissue is positively correlated with adipogenic FABP4 and LPL. This lncRNA is involved in the regulation of PPARγ at the transcription stage, fatty acid metabolism, and insulin signaling. The wide range of MALAT1 functions makes it an interesting target in studies searching for drugs to prevent obesity development in humans. In turn, in farm animals, it can be a source of selection markers to control the fat tissue content.

Modeling of new markers for the diagnosis and prognosis of pancreatic cancer based on the transition from inflammation to cancer

Background

Pancreatic adenocarcinoma (PAAD) is a lethal disease with a poor prognosis. Genes involved in acute pancreatitis (AP) or chronic pancreatitis (CP) might be important for PAAD development. This study sought to identify potential PAAD diagnosis markers and to establish a PAAD prognosis prediction model based on AP- and CP-related genes.

Methods

The significantly differentially expressed genes in both AP or CP and PAAD were obtained by a bioinformatics analysis. A risk-score model for predicting survival was constructed based on The Cancer Genome Atlas (TCGA) data and validated using an International Cancer Genome Consortium (ICGC) cohort. Protein expression and the effects of the genes in the risk models were validated by immunohistochemistry, or Cell Counting Kit-8 (CCK-8) and transwell assays. The study sample data included six AP tissue samples and five normal pancreatic tissue samples, six CP tissue samples and six normal pancreatic tissue samples from the Gene Expression Omnibus (GEO) expression profiling microarrays GSE109227 and GSE41418 data sets, respectively, and fragments per kilobase per million mapped fragments (FPKM) data from four normal controls and 150 PAAD cases from TCGA database, and 182 cancer patient samples with complete survival prognostic data from the ICGC database.

Results

In total, 508 significantly differentially expressed genes were found in both AP or CP and PAAD. Trefoil factor 2 (TFF2), tubulointerstitial nephritis antigen (TINAG), trefoil factor 1 (TFF1), aquaporin 5 (AQP5), SAM pointed domain containing ETS transcription factor (SPDEF), anterior gradient protein 2 (AGR2), apolipoprotein B messenger RNA editing enzyme catalytic subunit 1 (APOBEC1), kallikrein-related peptidase 6 (KLK6), dopa decarboxylase (DDC), mucin 13 (MUC13), claudin 18 (CLDN18), annexin A10 (ANXA10), and tetraspanin 1 (TSPAN1) were found to be present in PAAD and had the largest fold change. A risk-score model, comprising 19 genes, was constructed for prognostic prediction. A high-risk score indicated a poor prognosis. TINAG, DDC, SPDEF, and APOBEC1 proteins were increased in PAAD, while TINAG and DDC were correlated with the pathologic grade. Decreased TINAG, APOBEC1, transmembrane protein 94 (TMEM94), and kelch like family member 36 (KLHL36) expression inhibited PAAD cell proliferation, while decreased SPDEF, TMEM94, and KLHL36 expression significantly inhibited PAAD cell migration.

Conclusions

The AP and CP co-related genes were significantly correlated with PAAD. TINAG, DDC, SPDEF, and APOBEC1 could serve as new PAAD predictors. The risk model developed in this study could be used to predict the prognosis of PAAD patients.

BORIS/CTCFL epigenetically reprograms clustered CTCF binding sites into alternative transcriptional start sites

BACKGROUND

Pervasive usage of alternative promoters leads to the deregulation of gene expression in carcinogenesis and may drive the emergence of new genes in spermatogenesis. However, little is known regarding the mechanisms underpinning the activation of alternative promoters.

RESULTS

Here we describe how alternative cancer-testis-specific transcription is activated. We show that intergenic and intronic CTCF binding sites, which are transcriptionally inert in normal somatic cells, could be epigenetically reprogrammed into active de novo promoters in germ and cancer cells. BORIS/CTCFL, the testis-specific paralog of the ubiquitously expressed CTCF, triggers the epigenetic reprogramming of CTCF sites into units of active transcription. BORIS binding initiates the recruitment of the chromatin remodeling factor, SRCAP, followed by the replacement of H2A histone with H2A.Z, resulting in a more relaxed chromatin state in the nucleosomes flanking the CTCF binding sites. The relaxation of chromatin around CTCF binding sites facilitates the recruitment of multiple additional transcription factors, thereby activating transcription from a given binding site. We demonstrate that the epigenetically reprogrammed CTCF binding sites can drive the expression of cancer-testis genes, long noncoding RNAs, retro-pseudogenes, and dormant transposable elements.

CONCLUSIONS

Thus, BORIS functions as a transcription factor that epigenetically reprograms clustered CTCF binding sites into transcriptional start sites, promoting transcription from alternative promoters in both germ cells and cancer cells.

Direct comparison of canine and human immune responses using transcriptomic and functional analyses

The canine spontaneous cancer model is increasingly utilized to evaluate new combined cancer immunotherapy approaches. While the major leukocyte subsets and phenotypes are closely related in dogs and humans, the functionality of T cells and antigen presenting cells in the two species has not been previously compared in detail. Such information would be important in interpreting immune response data and evaluating the potential toxicities of new cancer immunotherapies in dogs. To address this question, we used in vitro assays to compare the transcriptomic, cytokine, and proliferative responses of activated canine and human T cells, and also compared responses in activated macrophages. Transcriptomic analysis following T cell activation revealed shared expression of 515 significantly upregulated genes and 360 significantly downregulated immune genes. Pathway analysis identified 33 immune pathways shared between canine and human activated T cells, along with 34 immune pathways that were unique to each species. Activated human T cells exhibited a marked Th1 bias, whereas canine T cells were transcriptionally less active overall. Despite similar proliferative responses to activation, canine T cells produced significantly less IFN-γ than human T cells. Moreover, canine macrophages were significantly more responsive to activation by IFN-γ than human macrophages, as reflected by co-stimulatory molecule expression and TNF-α production. Thus, these studies revealed overall broad similarity in responses to immune activation between dogs and humans, but also uncovered important key quantitative and qualitative differences, particularly with respect to T cell responses, that should be considered in designing and evaluating cancer immunotherapy studies in dogs.

Transcription readthrough is prevalent in healthy human tissues and associated with inherent genomic features

Transcription termination is a crucial step in the production of conforming mRNAs and functional proteins. Under cellular stress conditions, the transcription machinery fails to identify the termination site and continues transcribing beyond gene boundaries, a phenomenon designated as transcription readthrough. However, the prevalence and impact of this phenomenon in healthy human tissues remain unexplored. Here, we assessed transcription readthrough in almost 3000 transcriptome profiles representing 23 human tissues and found that 34% of the expressed protein-coding genes produced readthrough transcripts. The production of readthrough transcripts was restricted in genomic regions with high transcriptional activity and was associated with inefficient splicing and increased chromatin accessibility in terminal regions. In addition, we showed that these transcripts contained several binding sites for the same miRNA, unravelling a potential role as miRNA sponges. Overall, this work provides evidence that transcription readthrough is pervasive and non-stochastic, not only in abnormal conditions but also in healthy tissues. This suggests a potential role for such transcripts in modulating normal cellular functions.

Lethal phenotypes in Mendelian disorders

Essential genes are those whose function is required for cell proliferation and/or organism survival. A gene's intolerance to loss-of-function can be allocated within a spectrum, as opposed to being considered a binary feature, since this function might be essential at different stages of development, genetic backgrounds or other contexts. Existing resources that collect and characterise the essentiality status of genes are based on either proliferation assessment in human cell lines, embryonic and postnatal viability evaluation in different model organisms, and gene metrics such as intolerance to variation scores derived from human population sequencing studies. There are also several repositories available that document phenotypic annotations for rare disorders in humans such as the Online Mendelian Inheritance in Man (OMIM) and the Human Phenotype Ontology (HPO) knowledgebases. This raises the prospect of being able to use clinical data, including lethality as the most severe phenotypic manifestation, to further our characterisation of gene essentiality. Here we queried OMIM for terms related to lethality and classified all Mendelian genes into categories, according to the earliest age of death recorded for the associated disorders, from prenatal death to no reports of premature death. To showcase this curated catalogue of human essential genes, we developed the Lethal Phenotypes Portal (https://lethalphenotypes.research.its.qmul.ac.uk), where we also explore the relationships between these lethality categories, constraint metrics and viability in cell lines and mouse. Further analysis of the genes in these categories reveals differences in the mode of inheritance of the associated disorders, physiological systems affected and disease class. We highlight how the phenotypic similarity between genes in the same lethality category combined with gene family/group information can be used for novel disease gene discovery. Finally, we explore the overlaps and discrepancies between the lethal phenotypes observed in mouse and human and discuss potential explanations that include differences in transcriptional regulation, functional compensation and molecular disease mechanisms. We anticipate that this resource will aid clinicians in the diagnosis of early lethal conditions and assist researchers in investigating the properties that make these genes essential for human development.

Stem cell therapy for heart failure in the clinics: new perspectives in the era of precision medicine and artificial intelligence

Stem/progenitor cells have been widely evaluated as a promising therapeutic option for heart failure (HF). Numerous clinical trials with stem/progenitor cell-based therapy (SCT) for HF have demonstrated encouraging results, but not without limitations or discrepancies. Recent technological advancements in multiomics, bioinformatics, precision medicine, artificial intelligence (AI), and machine learning (ML) provide new approaches and insights for stem cell research and therapeutic development. Integration of these new technologies into stem/progenitor cell therapy for HF may help address: 1) the technical challenges to obtain reliable and high-quality therapeutic precursor cells, 2) the discrepancies between preclinical and clinical studies, and 3) the personalized selection of optimal therapeutic cell types/populations for individual patients in the context of precision medicine. This review summarizes the current status of SCT for HF in clinics and provides new perspectives on the development of computation-aided SCT in the era of precision medicine and AI/ML.

mRNA initiation and termination are spatially coordinated

The expression of a precise mRNA transcriptome is crucial for establishing cell identity and function, with dozens of alternative isoforms produced for a single gene sequence. The regulation of mRNA isoform usage occurs by the coordination of co-transcriptional mRNA processing mechanisms across a gene. Decisions involved in mRNA initiation and termination underlie the largest extent of mRNA isoform diversity, but little is known about any relationships between decisions at both ends of mRNA molecules. Here, we systematically profile the joint usage of mRNA transcription start sites (TSSs) and polyadenylation sites (PASs) across tissues and species. Using both short and long read RNA-seq data, we observe that mRNAs preferentially using upstream TSSs also tend to use upstream PASs, and congruently, the usage of downstream sites is similarly paired. This observation suggests that mRNA 5' end choice may directly influence mRNA 3' ends. Our results suggest a novel "Positional Initiation-Termination Axis" (PITA), in which the usage of alternative terminal sites are coupled based on the order in which they appear in the genome. PITA isoforms are more likely to encode alternative protein domains and use conserved sites. PITA is strongly associated with the length of genomic features, such that PITA is enriched in longer genes with more area devoted to regions that regulate alternative 5' or 3' ends. Strikingly, we found that PITA genes are more likely than non-PITA genes to have multiple, overlapping chromatin structural domains related to pairing of ordinally coupled start and end sites. In turn, PITA coupling is also associated with fast RNA Polymerase II (RNAPII) trafficking across these long gene regions. Our findings indicate that a combination of spatial and kinetic mechanisms couple transcription initiation and mRNA 3' end decisions based on ordinal position to define the expression mRNA isoforms.

A gene-based score for the risk stratification of stage IA lung adenocarcinoma

OBJECTIVE

We aim to molecularly stratify stage IA lung adenocarcinoma (LUAD) for precision medicine.

METHODS

Twelve multi-institution datasets (837 cases of IA) were used to classify the high- and low-risk types (based on survival status within 5 years), and the biological differences were compared. Then, a gene-based classifying score (IA score) was trained, tested and validated by several machine learning methods. Furthermore, we estimated the significance of the IA score in the prognostic assessment, chemotherapy prediction and risk stratification of stage IA LUAD. We also developed an R package for the clinical application. The SEER database (15708 IA samples) and TCGA Pan-Cancer (1881 stage I samples) database were used to verify clinical significance.

RESULTS

Compared with the low-risk group, the high-risk group of stage IA LUAD has obvious enrichment of the malignant pathway and more driver mutations and copy number variations. The effect of the IA score on the classification of high- and low-risk stage IA LUAD was much better than that of classical clinicopathological factors (training set: AUC = 0.9, validation set: AUC = 0.7). The IA score can significantly predict the prognosis of stage IA LUAD and has a prognostic effect for stage I pancancer. The IA score can effectively predict chemotherapy sensitivity and occult metastasis or invasion in stage IA LUAD. The R package IAExpSuv has a good risk probability prediction effect for both groups and single stages of IA LUAD.

CONCLUSIONS

The IA score can effectively stratify the risk of stage IA LUAD, offering good assistance in precision medicine.

APPLICATION OF QUANTILE DISCRETIZATION AND BAYESIAN NETWORK ANALYSIS TO PUBLICLY AVAILABLE CYSTIC FIBROSIS DATA SETS

The availability of multiple publicly-available datasets studying the same phenomenon has the promise of accelerating scientific discovery. Meta-analysis can address issues of reproducibility and often increase power. The promise of meta-analysis is especially germane to rarer diseases like cystic fibrosis (CF), which affects roughly 100,000 people worldwide. A recent search of the National Institute of Health's Gene Expression Omnibus revealed 1.3 million data sets related to cancer compared to about 2,000 related to CF. These studies are highly diverse, involving different tissues, animal models, treatments, and clinical covariates. In our search for gene expression studies of primary human airway epithelial cells, we identified three studies with compatible methodologies and sufficient metadata: GSE139078, Sala Study, and PRJEB9292. Even so, experimental designs were not identical, and we identified significant batch effects that would have complicated functional analysis. Here we present quantile discretization and Bayesian network construction using the Hill climb method as a powerful tool to overcome experimental differences and reveal biologically relevant responses to the CF genotype itself, exposure to virus, bacteria, and drugs used to treat CF. Functional patterns revealed by cluster Profiler included interferon signaling, interferon gamma signaling, interleukins 4 and 13 signaling, interleukin 6 signaling, interleukin 21 signaling, and inactivation of CSF3/G-CSF signaling pathways showing significant alterations. These pathways were consistently associated with higher gene expression in CF epithelial cells compared to non-CF cells, suggesting that targeting these pathways could improve clinical outcomes. The success of quantile discretization and Bayesian network analysis in the context of CF suggests that these approaches might be applicable to other contexts where exactly comparable data sets are hard to find.

Human and mouse neutrophils share core transcriptional programs in both homeostatic and inflamed contexts

Neutrophils are frequently studied in mouse models, but the extent to which findings translate to humans remains poorly defined. In an integrative analysis of 11 mouse and 13 human datasets, we find a strong correlation of neutrophil gene expression across species. In inflammation, neutrophils display substantial transcriptional diversity but share a core inflammation program. This program includes genes encoding IL-1 family members, CD14, IL-4R, CD69, and PD-L1. Chromatin accessibility of core inflammation genes increases in blood compared to bone marrow and further in tissue. Transcription factor enrichment analysis implicates members of the NF-κB family and AP-1 complex as important drivers, and HoxB8 neutrophils with JunB knockout show a reduced expression of core inflammation genes in resting and activated cells. In independent single-cell validation data, neutrophil activation by type I or type II interferon, G-CSF, and E. coli leads to upregulation in core inflammation genes. In COVID-19 patients, higher expression of core inflammation genes in neutrophils is associated with more severe disease. In vitro treatment with GM-CSF, LPS, and type II interferon induces surface protein upregulation of core inflammation members. Together, we demonstrate transcriptional conservation in neutrophils in homeostasis and identify a core inflammation program shared across heterogeneous inflammatory conditions.

The mRNA-lncRNA landscape of multiple tissues uncovers key regulators and molecular pathways that underlie heterosis for feed intake and efficiency in laying chickens

BACKGROUND

Heterosis is routinely exploited to improve animal performance. However, heterosis and its underlying molecular mechanism for feed intake and efficiency have been rarely explored in chickens. Feed efficiency continues to be an important breeding goal trait since feed accounts for 60 to 70% of the total production costs in poultry. Here, we profiled the mRNA-lncRNA landscape of 96 samples of the hypothalamus, liver and duodenum mucosa from White Leghorn (WL), Beijing-You chicken (YY), and their reciprocal crosses (WY and YW) to elucidate the regulatory mechanisms of heterosis.

RESULTS

We observed negative heterosis for both feed intake and residual feed intake (RFI) in YW during the laying period from 43 to 46 weeks of age. Analysis of the global expression pattern showed that non-additivity was a major component of the inheritance of gene expression in the three tissues for YW but not for WY. The YW-specific non-additively expressed genes (YWG) and lncRNA (YWL) dominated the total number of non-additively expressed genes and lncRNA in the hypothalamus and duodenum mucosa. Enrichment analysis of YWG showed that mitochondria components and oxidation phosphorylation (OXPHOS) pathways were shared among the three tissues. The OXPHOS pathway was enriched by target genes for YWL with non-additive inheritance of expression in the liver and duodenum mucosa. Weighted gene co-expression network analysis revealed divergent co-expression modules associated with feed intake and RFI in the three tissues from WL, YW, and YY. Among the negatively related modules, the OXPHOS pathway was enriched by hub genes in the three tissues, which supports the critical role of oxidative phosphorylation. Furthermore, protein quantification of ATP5I was highly consistent with ATP5I expression in the liver, which suggests that, in crossbred YW, non-additive gene expression is down-regulated and decreases ATP production through oxidative phosphorylation, resulting in negative heterosis for feed intake and efficiency.

CONCLUSIONS

Our results demonstrate that non-additively expressed genes and lncRNA involved in oxidative phosphorylation in the hypothalamus, liver, and duodenum mucosa are key regulators of the negative heterosis for feed intake and RFI in layer chickens. These findings should facilitate the rational choice of suitable parents for producing crossbred chickens.

Deep learning applications in single-cell genomics and transcriptomics data analysis

Traditional bulk sequencing methods are limited to measuring the average signal in a group of cells, potentially masking heterogeneity, and rare populations. The single-cell resolution, however, enhances our understanding of complex biological systems and diseases, such as cancer, the immune system, and chronic diseases. However, the single-cell technologies generate massive amounts of data that are often high-dimensional, sparse, and complex, thus making analysis with traditional computational approaches difficult and unfeasible. To tackle these challenges, many are turning to deep learning (DL) methods as potential alternatives to the conventional machine learning (ML) algorithms for single-cell studies. DL is a branch of ML capable of extracting high-level features from raw inputs in multiple stages. Compared to traditional ML, DL models have provided significant improvements across many domains and applications. In this work, we examine DL applications in genomics, transcriptomics, spatial transcriptomics, and multi-omics integration, and address whether DL techniques will prove to be advantageous or if the single-cell omics domain poses unique challenges. Through a systematic literature review, we have found that DL has not yet revolutionized the most pressing challenges of the single-cell omics field. However, using DL models for single-cell omics has shown promising results (in many cases outperforming the previous state-of-the-art models) in data preprocessing and downstream analysis. Although developments of DL algorithms for single-cell omics have generally been gradual, recent advances reveal that DL can offer valuable resources in fast-tracking and advancing research in single-cell.

A systematic safety pipeline for selection of T-cell receptors to enter clinical use

Cancer immunotherapy using T cell receptor-engineered T cells (TCR-Ts) represents a promising treatment option. However, technologies for pre-clinical safety assessment are incomplete or inaccessible to most laboratories. Here, TCR-T off-target reactivity was assessed in five steps: (1) Mapping target amino acids necessary for TCR-T recognition, followed by (2) a computational search for, and (3) reactivity screening against, candidate cross-reactive peptides in the human proteome. Natural processing and presentation of recognized peptides was evaluated using (4) short mRNAs, and (5) full-length proteins. TCR-Ts were screened for recognition of unintended HLA alleles, and as proxy for off-target reactivity in vivo, a syngeneic, HLA-A*02:01-transgenic mouse model was used. Validation demonstrated importance of studying recognition of full-length candidate off-targets, and that the clinically applied 1G4 TCR has a hitherto unknown reactivity to unintended HLA alleles, relevant for patient selection. This widely applicable strategy should facilitate evaluation of candidate therapeutic TCRs and inform clinical decision-making.

Novel pharmacological approaches in abdominal aortic aneurysm

Abdominal aortic aneurysm (AAA) is a severe vascular disease and a major public health issue with an unmet medical need for therapy. This disease is featured by a progressive dilation of the abdominal aorta, boosted by atherosclerosis, ageing, and smoking as major risk factors. Aneurysm growth increases the risk of aortic rupture, a life-threatening emergency with high mortality rates. Despite the increasing progress in our knowledge about the etiopathology of AAA, an effective pharmacological treatment against this disorder remains elusive and surgical repair is still the unique available therapeutic approach for high-risk patients. Meanwhile, there is no medical alternative for patients with small aneurysms but close surveillance. Clinical trials assessing the efficacy of antihypertensive agents, statins, doxycycline, or anti-platelet drugs, among others, failed to demonstrate a clear benefit limiting AAA growth, while data from ongoing clinical trials addressing the benefit of metformin on aneurysm progression are eagerly awaited. Recent preclinical studies have postulated new therapeutic targets and pharmacological strategies paving the way for the implementation of future clinical studies exploring these novel therapeutic strategies. This review summarises some of the most relevant clinical and preclinical studies in search of new therapeutic approaches for AAA.

Modeling brain and neural crest neoplasms with human pluripotent stem cells

Pluripotent stem cells offer unique avenues to study human-specific aspects of disease and are a highly versatile tool in cancer research. Oncogenic processes and developmental programs often share overlapping transcriptomic and epigenetic signatures, which can be reactivated in induced pluripotent stem cells. With the emergence of brain organoids, the ability to recapitulate brain development and structure has vastly improved, making in vitro models more realistic and hence more suitable for biomedical modeling. This review highlights recent research and current challenges in human pluripotent stem cell modeling of brain and neural crest neoplasms, and concludes with a call for more rigorous quality control and for the development of models for rare tumor subtypes.

Single-cell landscape analysis reveals systematic senescence in mammalian Down syndrome

BACKGROUND

Down syndrome (DS), which is characterized by various malfunctions, is the most common chromosomal disorder. As the DS population continues to grow and most of those with DS live beyond puberty, early-onset health problems have become apparent. However, the cellular landscape and molecular alterations have not been thoroughly studied.

METHODS

This study utilized single-cell resolution techniques to examine DS in humans and mice, spanning seven distinct organs. A total of 71 934 mouse and 98 207 human cells were analyzed to uncover the molecular alterations occurring in different cell types and organs related to DS, specifically starting from the fetal stage. Additionally, SA-β-Gal staining, western blot, and histological study were employed to verify the alterations.

RESULTS

In this study, we firstly established the transcriptomic profile of the mammalian DS, deciphering the cellular map and molecular mechanism. Our analysis indicated that DS cells across various types and organs experienced senescence stresses from as early as the fetal stage. This was marked by elevated SA-β-Gal activity, overexpression of cell cycle inhibitors, augmented inflammatory responses, and a loss of cellular identity. Furthermore, we found evidence of mitochondrial disturbance, an increase in ribosomal protein transcription, and heightened apoptosis in fetal DS cells. This investigation also unearthed a regulatory network driven by an HSA21 gene, which leads to genome-wide expression changes.

CONCLUSION

The findings from this study offer significant insights into the molecular alterations that occur in DS, shedding light on the pathological processes underlying this disorder. These results can potentially guide future research and treatment development for DS.

A Multi-Tissue Gene Expression Atlas of Water Buffalo (Bubalus bubalis) Reveals Transcriptome Conservation between Buffalo and Cattle

We generated 73 transcriptomic data of water buffalo, which were integrated with publicly available data in this species, yielding a large dataset of 355 samples representing 20 major tissue categories. We established a multi-tissue gene expression atlas of water buffalo. Furthermore, by comparing them with 4866 cattle transcriptomic data from the cattle genotype-tissue expression atlas (CattleGTEx), we found that the transcriptomes of the two species exhibited conservation in their overall gene expression patterns, tissue-specific gene expression and house-keeping gene expression. We further identified conserved and divergent expression genes between the two species, with the largest number of differentially expressed genes found in the skin, which may be related to structural and functional differences in the skin of the two species. This work provides a source of functional annotation of the buffalo genome and lays the foundations for future genetic and evolutionary studies in water buffalo.

Novel technologies for applying immune checkpoint blockers

Cancer cells develop several ways to subdue the immune system among others via upregulation of inhibitory immune checkpoint (ICP) proteins. These ICPs paralyze immune effector cells and thereby enable unfettered tumor growth. Monoclonal antibodies (mAbs) that block ICPs can prevent immune exhaustion. Due to their outstanding effects, mAbs revolutionized the field of cancer immunotherapy. However, current ICP therapy regimens suffer from issues related to systemic administration of mAbs, including the onset of immune related adverse events, poor pharmacokinetics, limited tumor accessibility and immunogenicity. These drawbacks and new insights on spatiality prompted the exploration of novel administration routes for mAbs for instance peritumoral delivery. Moreover, novel ICP drug classes that are adept to novel delivery technologies were developed to circumvent the drawbacks of mAbs. We therefore review the state-of-the-art and novel delivery strategies of ICP drugs.

Implementation of blood-brain barrier on microfluidic chip: recent advance and future prospects

The complex structure of the blood-brain barrier (BBB) hinders its modeling and the treatment of brain diseases. The microfluidic technology promotes the development of BBB-on-a-chip platforms, which can be used to reproduce the complex brain microenvironment and physiological reactions. Compared with traditional transwell technology, microfluidic BBB-on-a-chip shows great technical advantages in terms of flexible control of fluid shear stress in the chip and fabrication efficiency of the chip system, which can be enhanced by the development of lithography and three-dimensional (3D) printing. It is convenient to accurately monitor the dynamic changes of biochemical parameters of individual cells in the model by integrating an automatic super-resolution imaging sensing platform. In addition, biomaterials, especially hydrogels and conductive polymers, solve the limitations of microfluidic BBB-on-a-chip by compounding onto microfluidic chip to provide a 3D space and special performance on the microfluidic chip. The microfluidic BBB-on-a-chip promotes the development of basic research, including cell migration, mechanism exploration of neurodegenerative diseases, drug barrier permeability, SARS-CoV-2 pathology. This study summarizes the recent advances, challenges and future prospects of microfluidic BBB-on-a-chip, which can help to promote the development of personalized medicine and drug discovery.

Selective Transcription Factor Blockade Reduces Human Retinal Endothelial Cell Expression of Intercellular Adhesion Molecule-1 and Leukocyte Binding

The interaction between leukocytes and cytokine-activated retinal endothelium is an initiating step in non-infectious uveitis involving the posterior eye, mediated by cell adhesion molecules. However, because cell adhesion molecules are required for immune surveillance, therapeutic interventions would ideally be employed indirectly. Using 28 primary human retinal endothelial cell isolates, this study sought to identify transcription factor targets for reducing levels of the key retinal endothelial cell adhesion molecule, intercellular adhesion molecule (ICAM)-1, and limiting leukocyte binding to the retinal endothelium. Five candidate transcription factors-C2CD4B, EGR3, FOSB, IRF1, and JUNB-were identified by differential expression analysis of a transcriptome generated from IL-1β- or TNF-α-stimulated human retinal endothelial cells, interpreted in the context of the published literature. Further filtering involved molecular studies: of the five candidates, C2CD4B and IRF1 consistently demonstrated extended induction in IL-1β- or TNF-α-activated retinal endothelial cells and demonstrated a significant decrease in both ICAM-1 transcript and ICAM-1 membrane-bound protein expression by cytokine-activated retinal endothelial cells following treatment with small interfering RNA. RNA interference of C2CD4B or IRF1 significantly reduced leukocyte binding in a majority of human retinal endothelial cell isolates stimulated by IL-1β or TNF-α. Our observations suggest that the transcription factors C2CD4B and IRF1 may be potential drug targets for limiting leukocyte-retinal endothelial cell interactions in non-infectious uveitis involving the posterior eye.

Considerations in the Preclinical Assessment of the Safety of Antisense Oligonucleotides

The nucleic acid therapeutics field has made tremendous progress in the past decades. Continuous advances in chemistry and design have led to many successful clinical applications, eliciting even more interest from researchers including both academic groups and drug development companies. Many preclinical studies in the field focus on improving the delivery of antisense oligonucleotide drugs (ONDs) and/or assessing their efficacy in target tissues, often neglecting the evaluation of toxicity, at least in early phases of development. A series of consensus recommendations regarding regulatory considerations and expectations have been generated by the Oligonucleotide Safety Working Group and the Japanese Research Working Group for the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use S6 and Related Issues (WGS6) in several white papers. However, safety aspects should also be kept in sight in earlier phases while screening and designing OND to avoid subsequent failure in the development phase. Experts and members of the network "DARTER," a COST Action funded by the Cooperation in Science and Technology of the EU, have utilized their collective experience working with OND, as well as their insights into OND-mediated toxicities, to generate a series of consensus recommendations to assess OND toxicity in early stages of preclinical research. In the past few years, several publications have described predictive assays, which can be used to assess OND-mediated toxicity in vitro or ex vivo to filter out potential toxic candidates before moving to in vivo phases of preclinical development, that is, animal toxicity studies. These assays also have the potential to provide translational insight since they allow a safety evaluation in human in vitro systems. Yet, small preliminary in vivo studies should also be considered to complement this early assessment. In this study, we summarize the state of the art and provide guidelines and recommendations on the different tests available for these early stage preclinical assessments.

The evolution of ovary-biased gene expression in Hawaiian Drosophila

With detailed data on gene expression accessible from an increasingly broad array of species, we can test the extent to which our developmental genetic knowledge from model organisms predicts expression patterns and variation across species. But to know when differences in gene expression across species are significant, we first need to know how much evolutionary variation in gene expression we expect to observe. Here we provide an answer by analyzing RNAseq data across twelve species of Hawaiian Drosophilidae flies, focusing on gene expression differences between the ovary and other tissues. We show that over evolutionary time, there exists a cohort of ovary specific genes that is stable and that largely corresponds to described expression patterns from laboratory model Drosophila species. Our results also provide a demonstration of the prediction that, as phylogenetic distance increases, variation between species overwhelms variation between tissue types. Using ancestral state reconstruction of expression, we describe the distribution of evolutionary changes in tissue-biased expression, and use this to identify gains and losses of ovary-biased expression across these twelve species. We then use this distribution to calculate the evolutionary correlation in expression changes between genes, and demonstrate that genes with known interactions in D. melanogaster are significantly more correlated in their evolution than genes with no or unknown interactions. Finally, we use this correlation matrix to infer new networks of genes that share evolutionary trajectories, and we present these results as a dataset of new testable hypotheses about genetic roles and interactions in the function and evolution of the Drosophila ovary.

Chikungunya patient transcriptional signatures faithfully recapitulated in a C57BL/6J mouse model

Introduction

An adult wild-type C57BL/6J mouse model of chikungunya virus (CHIKV) infection and disease has been extensively used to study the alphaviral arthritic immunopathology and to evaluate new interventions. How well mouse models recapitulate the gene expression profiles seen in humans remains controversial.

Methods

Herein we perform a comparative transcriptomics analysis using RNA-Seq datasets from the C57BL/6J CHIKV mouse model with datasets obtained from adults and children acutely infected with CHIKV.

Results

Despite sampling quite different tissues, peripheral blood from humans and feet from mice, gene expression profiles were quite similar, with an overlap of up to ≈50% for up-regulated single copy orthologue differentially expressed genes. Furthermore, high levels of significant concordance between mouse and human were seen for immune pathways and signatures, which were dominated by interferons, T cells and monocyte/macrophages. Importantly, predicted responses to a series of anti-inflammatory drug and biologic treatments also showed cogent similarities between species.

Discussion

Comparative transcriptomics and subsequent pathway analysis provides a detailed picture of how a given model recapitulates human gene expression. Using this method, we show that the C57BL/6J CHIKV mouse model provides a reliable and representative system in which to study CHIKV immunopathology and evaluate new treatments.

Robust and rigorous identification of tissue-specific genes by statistically extending tau score

OBJECTIVES

In this study, we aimed to identify tissue-specific genes for various human tissues/organs more robustly and rigorously by extending the tau score algorithm.

INTRODUCTION

Tissue-specific genes are a class of genes whose functions and expressions are preferred in one or several tissues restrictedly. Identification of tissue-specific genes is essential for discovering multi-cellular biological processes such as tissue-specific molecular regulations, tissue development, physiology, and the pathogenesis of tissue-associated diseases.

MATERIALS AND METHODS

Gene expression data derived from five large RNA sequencing (RNA-seq) projects, spanning 96 different human tissues, were retrieved from ArrayExpress and ExpressionAtlas. The first step is categorizing genes using significant filters and tau score as a specificity index. After calculating tau for each gene in all datasets separately, statistical distance from the maximum expression level was estimated using a new meaningful procedure. Specific expression of a gene in one or several tissues was calculated after the integration of tau and statistical distance estimation, which is called as extended tau approach. Obtained tissue-specific genes for 96 different human tissues were functionally annotated, and some comparisons were carried out to show the effectiveness of the extended tau method.

RESULTS AND DISCUSSION

Categorization of genes based on expression level and identification of tissue-specific genes for a large number of tissues/organs were executed. Genes were successfully assigned to multiple tissues by generating the extended tau approach as opposed to the original tau score, which can assign tissue specificity to single tissue only.

Synthesizing genome regulation data with vote-counting

The increasing availability of high-throughput datasets allows amalgamating research information across a large body of genome regulation studies. Given the recent success of meta-analyses on transcriptional regulators, epigenetic marks, and enhancer:gene associations, we expect that such surveys will continue to provide novel and reproducible insights. However, meta-analyses are severely hampered by the diversity of available data, concurring protocols, an eclectic amount of bioinformatics tools, and myriads of conceivable parameter combinations. Such factors can easily bar life scientists from synthesizing omics data and substantially curb their interpretability. Despite statistical challenges of the method, we would like to emphasize the advantages of joining data from different sources through vote-counting and showcase examples that achieve a simple but highly intuitive data integration.

Dynamic changes in spatiotemporal transcriptome reveal maternal immune dysregulation of autism spectrum disorder

Maternal immune activation (MIA) during pregnancy is known to be an environmental risk factor for neurodevelopment and autism spectrum disorder (ASD). However, it is unclear at which fetal brain developmental windows and regions MIA induces ASD-related neurodevelopmental transcriptional abnormalities. The non-chasm differentially expressed genes (DEGs) involved in MIA inducing ASD during fetal brain developmental windows were identified by performing the differential expression analysis and comparing the common DEGs among MIA at four different gestational development windows, ASD with multiple brain regions from human patients and mouse models, and human and mouse embryonic brain developmental trajectory. The gene set and functional enrichment analyses were performing to identify MIA dysregulated ASD-related the fetal neurodevelopmental windows and brain regions and function annotations. Additionally, the networks were constructed using Cytoscape for visualization. MIA at E12.5 and E14.5 increased the risk of distinct brain regions for ASD. MIA-driven transcriptional alterations of non-chasm DEGs, during the coincidence brain developmental windows between human and mice, involving ASD-relevant synaptic components, as well as immune- and metabolism-related functions and pathways. Furthermore, a great number of non-chasm brain development-, immune-, and metabolism-related DEGs were overlapped in at least two existing ASD-associated databases, suggesting that the others could be considered as the candidate targets to construct the model mice for explaining the pathological changes of ASD when environmental factors (MIA) and gene mutation effects co-occur. Overall, our search supported that transcriptome-based MIA dysregulated the brain development-, immune-, and metabolism-related non-chasm DEGs at specific embryonic brain developmental window and region, leading to abnormal embryonic neurodevelopment, to induce the increasing risk of ASD.

False-positive IRESes from Hoxa9 and other genes resulting from errors in mammalian 5' UTR annotations

Hyperconserved genomic sequences have great promise for understanding core biological processes. It has been recently proposed that scores of hyperconserved 5' untranslated regions (UTRs), also known as transcript leaders (hTLs), encode internal ribosome entry sites (IRESes) that drive cap-independent translation, in part, via interactions with ribosome expansion segments. However, the direct functional significance of such interactions has not yet been definitively demonstrated. We provide evidence that the putative IRESes previously reported in Hox gene hTLs are rarely included in transcript leaders. Instead, these regions function independently as transcriptional promoters. In addition, we find the proposed RNA structure of the putative Hoxa9 IRES is not conserved. Instead, sequences previously shown to be essential for putative IRES activity encode a hyperconserved transcription factor binding site (E-box) that contributes to its promoter activity and is bound by several transcription factors, including USF1 and USF2. Similar E-box sequences enhance the promoter activities of other putative Hoxa gene IRESes. Moreover, we provide evidence that the vast majority of hTLs with putative IRES activity overlap transcriptional promoters, enhancers, and 3' splice sites that are most likely responsible for their reported IRES activities. These results argue strongly against recently reported widespread IRES-like activities from hTLs and contradict proposed interactions between ribosomal expansion segment ES9S and putative IRESes. Furthermore, our work underscores the importance of accurate transcript annotations, controls in bicistronic reporter assays, and the power of synthesizing publicly available data from multiple sources.

Mouse models of COVID-19 recapitulate inflammatory pathways rather than gene expression

How well mouse models recapitulate the transcriptional profiles seen in humans remains debatable, with both conservation and diversity identified in various settings. Herein we use RNA-Seq data and bioinformatics approaches to analyze the transcriptional responses in SARS-CoV-2 infected lungs, comparing 4 human studies with the widely used K18-hACE2 mouse model, a model where hACE2 is expressed from the mouse ACE2 promoter, and a model that uses a mouse adapted virus and wild-type mice. Overlap of single copy orthologue differentially expressed genes (scoDEGs) between human and mouse studies was generally poor (≈15-35%). Rather than being associated with batch, sample treatment, viral load, lung damage or mouse model, the poor overlaps were primarily due to scoDEG expression differences between species. Importantly, analyses of immune signatures and inflammatory pathways illustrated highly significant concordances between species. As immunity and immunopathology are the focus of most studies, these mouse models can thus be viewed as representative and relevant models of COVID-19.

A Peptidomic Approach to Identify Novel Antigen Biomarkers for the Diagnosis of Tuberculosis

Background

Here, we conducted a peptidomic study in murine model to identify novel antigen biomarkers for the diagnosis of tuberculosis (TB) with improved performance.

Methods

Four recombinant proteins, including Mycobacterium tuberculosis protein 32 (MPT32), Mycobacterium tuberculosis protein 64 (MPT64), culture filtrate protein 10 (CFP10), and phosphate ABC transporter substrate-binding lipoprotein (PstS1) were expressed and intravenously injected into BALB/c mice. The serum were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The concentrations of candidate peptides in serum of suspected TB patients were determined using competitive enzyme-linked immunosorbent assay.

Results

A total of 65 peptides from 4 MTB precursor recombinant proteins were identified in mouse serum by LC-MS/MS, of which 5 peptides were selected as candidates for serological analysis. The concentrations of peptides MPT64-2, CFP10-2 and PstS1-2 in TB patients were significantly higher than those in non-TB patients. MPT64-2 exhibited the most promising sensitivity (81.4%), followed by PstS1-2 and CFP10-2. In addition, PstS1-2 had the highest specificity (93.3%), followed by CFP10-2 and MPT64-2. According to the area under the curve (AUC), MPT64-2 (AUC = 0.863), PstS1-2 (AUC = 0.812) and CFP10-2 (AUC = 0.809) exhibited better diagnostic validity.

Conclusion

We develop an effective approach to identify new antigen biomarkers via LC-MS/MS-based peptidomics. Multiple peptides exhibit promising efficacy in diagnosis of active TB patients.

Comparative transcriptome in large-scale human and cattle populations

BACKGROUND

Cross-species comparison of transcriptomes is important for elucidating evolutionary molecular mechanisms underpinning phenotypic variation between and within species, yet to date it has been essentially limited to model organisms with relatively small sample sizes.

RESULTS

Here, we systematically analyze and compare 10,830 and 4866 publicly available RNA-seq samples in humans and cattle, respectively, representing 20 common tissues. Focusing on 17,315 orthologous genes, we demonstrate that mean/median gene expression, inter-individual variation of expression, expression quantitative trait loci, and gene co-expression networks are generally conserved between humans and cattle. By examining large-scale genome-wide association studies for 46 human traits (average n = 327,973) and 45 cattle traits (average n = 24,635), we reveal that the heritability of complex traits in both species is significantly more enriched in transcriptionally conserved than diverged genes across tissues.

CONCLUSIONS

In summary, our study provides a comprehensive comparison of transcriptomes between humans and cattle, which might help decipher the genetic and evolutionary basis of complex traits in both species.

The effects of sequencing depth on the assembly of coding and noncoding transcripts in the human genome

Investigating the functions and activities of genes requires proper annotation of the transcribed units. However, transcript assembly efforts have produced a surprisingly large variation in the number of transcripts, and especially so for noncoding transcripts. This heterogeneity in assembled transcript sets might be partially explained by sequencing depth. Here, we used real and simulated short-read sequencing data as well as long-read data to systematically investigate the impact of sequencing depths on the accuracy of assembled transcripts. We assembled and analyzed transcripts from 671 human short-read data sets and four long-read data sets. At the first level, there is a positive correlation between the number of reads and the number of recovered transcripts. However, the effect of the sequencing depth varied based on cell or tissue type, the type of read and the nature and expression levels of the transcripts. The detection of coding transcripts saturated rapidly with both short and long-reads, however, there was no sign of early saturation for noncoding transcripts at any sequencing depth. Increasing long-read sequencing depth specifically benefited transcripts containing transposable elements. Finally, we show how single-cell RNA-seq can be guided by transcripts assembled from bulk long-read samples, and demonstrate that noncoding transcripts are expressed at similar levels to coding transcripts but are expressed in fewer cells. This study highlights the impact of sequencing depth on transcript assembly.

Altered differentiation of endometrial mesenchymal stromal fibroblasts is associated with endometriosis susceptibility

Cellular development is tightly regulated as mature cells with aberrant functions may initiate pathogenic processes. The endometrium is a highly regenerative tissue, shedding and regenerating each month. Endometrial stromal fibroblasts are regenerated each cycle from mesenchymal stem cells and play a pivotal role in endometriosis, a disease characterised by endometrial cells that grow outside the uterus. Why the cells of some women are more capable of developing into endometriosis lesions is not clear. Using isolated, purified and cultured endometrial cells of mesenchymal origin from 19 women with (n = 10) and without (n = 9) endometriosis we analysed the transcriptome of 33,758 individual cells and compared these to clinical characteristics and in vitro growth profiles. We show purified mesenchymal cell cultures include a mix of mesenchymal stem cells and two endometrial stromal fibroblast subtypes with distinct transcriptomic signatures indicative of varied progression through the differentiation processes. The fibroblast subgroup characterised by incomplete differentiation was predominantly (81%) derived from women with endometriosis and exhibited an altered in vitro growth profile. These results uncover an inherent difference in endometrial cells of women with endometriosis and highlight the relevance of cellular differentiation and its potential to contribute to disease susceptibility.

Comparing single cell transcriptome data to clinical characteristics and in vitro growth profiles uncovers a potential role for divergent mesenchymal-derived stromal fibroblast maturation in endometriosis susceptibility.

LGR5 is a conserved marker of hair follicle stem cells in multiple species and is present early and throughout follicle morphogenesis

Hair follicle stem cells are key for driving growth and homeostasis of the hair follicle niche, have remarkable regenerative capacity throughout hair cycling, and display fate plasticity during cutaneous wound healing. Due to the need for a transgenic reporter, essentially all observations related to LGR5-expressing hair follicle stem cells have been generated using transgenic mice, which have significant differences in anatomy and physiology from the human. Using a transgenic pig model, a widely accepted model for human skin and human skin repair, we demonstrate that LGR5 is a marker of hair follicle stem cells across species in homeostasis and development. We also report the strong similarities and important differences in expression patterns, gene expression profiles, and developmental processes between species. This information is important for understanding the fundamental differences and similarities across species, and ultimately improving human hair follicle regeneration, cutaneous wound healing, and skin cancer treatment.

Hypomorphic GINS3 variants alter DNA replication and cause Meier-Gorlin syndrome

The eukaryotic CDC45/MCM2-7/GINS (CMG) helicase unwinds the DNA double helix during DNA replication. The GINS subcomplex is required for helicase activity and is, therefore, essential for DNA replication and cell viability. Here, we report the identification of 7 individuals from 5 unrelated families presenting with a Meier-Gorlin syndrome–like (MGS-like) phenotype associated with hypomorphic variants of GINS3, a gene not previously associated with this syndrome. We found that MGS-associated GINS3 variants affecting aspartic acid 24 (D24) compromised cell proliferation and caused accumulation of cells in S phase. These variants shortened the protein half-life, altered key protein interactions at the replisome, and negatively influenced DNA replication fork progression. Yeast expressing MGS-associated variants of PSF3 (the yeast GINS3 ortholog) also displayed impaired growth, S phase progression defects, and decreased Psf3 protein stability. We further showed that mouse embryos homozygous for a D24 variant presented intrauterine growth retardation and did not survive to birth, and that fibroblasts derived from these embryos displayed accelerated cellular senescence. Taken together, our findings implicate GINS3 in the pathogenesis of MGS and support the notion that hypomorphic variants identified in this gene impaired cell and organismal growth by compromising DNA replication.