Sample size calculation while controlling false discovery rate for differential expression analysis with RNA-sequencing experiments

A meta-analysis approach for annotation and identification of lncRNAs controlling perirenal fat deposition in suckling lambs

Long non-coding RNAs (lncRNAs) are being studied in farm animals due to their association with traits of economic interest, such as fat deposition. Based on the analysis of perirenal fat transcriptomes, this research explored the relevance of these regulatory elements to fat deposition in suckling lambs. To that end, meta-analysis techniques have been implemented to efficiently characterize and detect differentially expressed transcripts from two different RNA-seq datasets, one including samples of two sheep breeds that differ in fat deposition features, Churra and Assaf (n = 14), and one generated from Assaf suckling lambs with different fat deposition levels (n = 8). The joint analysis of the 22 perirenal fat RNA-seq samples with the FEELnc software allowed the detection of 3953 novel lncRNAs. After the meta-analysis, 251 differentially expressed genes were identified, 21 of which were novel lncRNAs. Additionally, a co-expression analysis revealed that, in suckling lambs, lncRNAs may play a role in controlling angiogenesis and thermogenesis, processes highlighted in relation to high and low fat deposition levels, respectively. Overall, while providing information that could be applied for the improvement of suckling lamb carcass traits, this study offers insights into the biology of perirenal fat deposition regulation in mammals.

Inflammation and immune system pathways as biological signatures of adolescent depression-the IDEA-RiSCo study

The biological mechanisms underlying the onset of major depressive disorder (MDD) have predominantly been studied in adult populations from high-income countries, despite the onset of depression typically occurring in adolescence and the majority of the world's adolescents living in low- and middle-income countries (LMIC). Taking advantage of a unique adolescent sample in an LMIC (Brazil), this study aimed to identify biological pathways characterizing the presence and increased risk of depression in adolescence, and sex-specific differences in such biological signatures. We collected blood samples from a risk-stratified cohort of 150 Brazilian adolescents (aged 14-16 years old) comprising 50 adolescents with MDD, 50 adolescents at high risk of developing MDD but without current MDD, and 50 adolescents at low risk of developing MDD and without MDD (25 females and 25 males in each group). We conducted RNA-Seq and pathway analysis on whole blood. Inflammatory-related biological pathways, such as role of hypercytokinemia/hyperchemokinemia in the pathogenesis of influenza (z-score = 3.464, p < 0.001), interferon signaling (z-score = 2.464, p < 0.001), interferon alpha/beta signaling (z-score = 3.873, p < 0.001), and complement signaling (z-score = 2, p = 0.002) were upregulated in adolescents with MDD compared with adolescents without MDD independently from their level of risk. The up-regulation of such inflammation-related pathways was observed in females but not in males. Inflammatory-related pathways involved in the production of cytokines and in interferon and complement signaling were identified as key indicators of adolescent depression, and this effect was present only in females.

Unveiling candidate genes for metabolic resistance to malathion in Aedes albopictus through RNA sequencing-based transcriptome profiling

Aedes albopictus, also known as the Asian tiger mosquito, is indigenous to the tropical forests of Southeast Asia. Ae. albopictus is expanding across the globe at alarming rates, raising concern over the transmission of mosquito-borne diseases, such as dengue, West Nile fever, yellow fever, and chikungunya fever. Since Ae. albopictus was reported in Houston (Harris County, Texas) in 1985, this species has rapidly expanded to at least 32 states across the United States. Public health efforts aimed at controlling Ae. albopictus, including surveillance and adulticide spraying operations, occur regularly in Harris County. Despite rotation of insecticides to mitigate the development of resistance, multiple mosquito species including Culex quinquefasciatus and Aedes aegypti in Harris County show organophosphate and pyrethroid resistance. Aedes albopictus shows relatively low resistance levels as compared to Ae. aegypti, but kdr-mutation and the expression of detoxification genes have been reported in Ae. albopictus populations elsewhere. To identify potential candidate detoxification genes contributing to metabolic resistance, we used RNA sequencing of field-collected malathion-resistant and malathion-susceptible, and laboratory-maintained susceptible colonies of Ae. albopictus by comparing the relative expression of transcripts from three major detoxification superfamilies involved in malathion resistance due to metabolic detoxification. Between these groups, we identified 12 candidate malathion resistance genes and among these, most genes correlated with metabolic detoxification of malathion, including four P450 and one alpha esterase. Our results reveal the metabolic detoxification and potential cuticular-based resistance mechanisms associated with malathion resistance in Ae. albopictus in Harris County, Texas.

Role of Gut Microbe Composition in Psychosocial Symptom Response to Exercise Training in Breast Cancer Survivors (ROME) study: protocol for a randomised controlled trial

INTRODUCTION

Breast cancer survivors have an increased risk for chronic fatigue and altered gut microbiota composition, both with negative health and quality of life affects. Exercise modestly improves fatigue and is linked to gut microbial diversity and production of beneficial metabolites. Studies suggest that gut microbiota composition is a potential mechanism underlying fatigue response to exercise. Randomised controlled trials testing the effects of exercise on the gut microbiome are limited and there is a scarcity of findings specific to breast cancer survivors. The objective of this study is to determine if fitness-related modifications to gut microbiota occur and, if so, mediate the effects of aerobic exercise on fatigue response.

METHODS AND ANALYSIS

The research is a randomised controlled trial among breast cancer survivors aged 18-74 with fatigue. The primary aim is to determine the effects of aerobic exercise training compared with an attention control on gut microbiota composition. The secondary study aims are to test if exercise training (1) affects the gut microbiota composition directly and/or indirectly through inflammation (serum cytokines), autonomic nervous system (heart rate variability) or hypothalamic-pituitary-adrenal axis mediators (hair cortisol assays), and (2) effects on fatigue are direct and/or indirect through changes in the gut microbiota composition. All participants receive a standardised controlled diet. Assessments occur at baseline, 5 weeks, 10 weeks and 15 weeks (5 weeks post intervention completion). Faecal samples collect the gut microbiome and 16S gene sequencing will identify the microbiome. Fatigue is measured by a 13-item multidimensional fatigue scale.

ETHICS AND DISSEMINATION

The University of Alabama at Birmingham Institutional Review Board (IRB) approved this study on 15 May 2019, UAB IRB#30000320. A Data and Safety Monitoring Board convenes annually or more often if indicated. Findings will be disseminated in peer-reviewed journals and conference presentations.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov, NCT04088708.

A Transcriptomic Approach to Understand Patient Susceptibility to Pneumonia After Abdominal Surgery

OBJECTIVE

To describe immune pathways and gene networks altered following major abdominal surgery and to identify transcriptomic patterns associated with postoperative pneumonia.

BACKGROUND

Nosocomial infections are a major healthcare challenge, developing in over 20% of patients aged 45 or over undergoing major abdominal surgery, with postoperative pneumonia associated with an almost 5-fold increase in 30-day mortality.

METHODS

From a prospective consecutive cohort (n=150) undergoing major abdominal surgery, whole-blood RNA was collected preoperatively and at 3 time-points postoperatively (2-6, 24, and 48 h). Twelve patients diagnosed with postoperative pneumonia and 27 matched patients remaining infection-free were identified for analysis with RNA-sequencing.

RESULTS

Compared to preoperative sampling, 3639 genes were upregulated and 5043 downregulated at 2 to 6 hours. Pathway analysis demonstrated innate-immune activation with neutrophil degranulation and Toll-like-receptor signaling upregulation alongside adaptive-immune suppression. Cell-type deconvolution of preoperative RNA-sequencing revealed elevated S100A8/9-high neutrophils alongside reduced naïve CD4 T-cells in those later developing pneumonia. Preoperatively, a gene-signature characteristic of neutrophil degranulation was associated with postoperative pneumonia acquisition ( P =0.00092). A previously reported Sepsis Response Signature (SRSq) score, reflecting neutrophil dysfunction and a more dysregulated host response, at 48 hours postoperatively, differed between patients subsequently developing pneumonia and those remaining infection-free ( P =0.045). Analysis of the novel neutrophil gene-signature and SRSq scores in independent major abdominal surgery and polytrauma cohorts indicated good predictive performance in identifying patients suffering later infection.

CONCLUSIONS

Major abdominal surgery acutely upregulates innate-immune pathways while simultaneously suppressing adaptive-immune pathways. This is more prominent in patients developing postoperative pneumonia. Preoperative transcriptomic signatures characteristic of neutrophil degranulation and postoperative SRSq scores may be useful predictors of subsequent pneumonia risk.

Investigating the impact of feed-induced, subacute ruminal acidosis on rumen epimural transcriptome and metatranscriptome in young calves at 8- and 17-week of age

Introduction

With the goal to maximize intake of high-fermentable diet needed to meet energy needs during weaning period, calves are at risk for ruminal acidosis. Using the calves from previously established model of feed-induced, ruminal acidosis in young calves, we aimed to investigate the changes in rumen epimural transcriptome and its microbial metatranscriptome at weaning (8-week) and post-weaning (17-week) in canulated (first occurred at 3 weeks of age) Holstein bull calves with feed-induced subacute ruminal acidosis.

Methods

Eight bull calves were randomly assigned to acidosis-inducing diet (Treated, n = 4; pelleted, 42.7% starch, 15.1% neutral detergent fiber [NDF], and 57.8% nonfiber carbohydrates), while texturized starter was fed as a control (Control, n = 4; 35.3% starch, 25.3% NDF, and 48.1% nonfiber carbohydrates) starting at 1 week through 17 weeks. Calves fed acidosis-inducing diet showed significantly less (p < 0.01) body weight over the course of the experiment, in addition to lower ruminal pH (p < 0.01) compared to the control group. Rumen epithelial (RE) tissues were collected at both 8 weeks (via biopsy) and 17 weeks (via euthanasia) and followed for whole transcriptome RNA sequencing analysis. Differentially expressed genes (DEGs) analysis was done using cufflinks2 (fold-change ≥2 and p < 0.05) between treated and control groups at 8-week of age, and between 8- and 17-week for the treated group.

Results

At 8-week of age, DEGs between treatment groups showed an enrichment of genes related to the response to lipopolysaccharide (LPS) (p < 0.005). The impact of prolonged, feed-induced acidosis was reflected by the decreased expression (p < 0.005) in genes involved in cell proliferation related pathways in the RE at 17-week of age in the treated group. Unique sets of discriminant microbial taxa were identified between 8-and 17-week calves in the treated group and the treatment groups at 8-week, indicating that active microbial community changes in the RE are an integral part of the ruminal acidosis development and progression.

Peptide-based capture-and-release purification of extracellular vesicles and statistical algorithm enabled quality assessment

Circulating extracellular vesicles (EVs) have gained significant attention for discovering tumor biomarkers. However, isolating EVs with well-defined homogeneous populations from complex biological samples is challenging. Different isolation methods have been found to derive different EV populations carrying different molecular contents, which confounds current investigations and hinders subsequent clinical translation. Therefore, standardizing and building a rigorous assessment of isolated EV quality associated with downstream molecular analysis is essential. To address this need, we introduce a statistical algorithm (ExoQuality Index, EQI) by integrating multiple EV characterizations (size, particle concentration, zeta potential, total protein, and RNA), enabling direct EV quality assessment and comparisons between different isolation methods. We also introduced a novel capture-release isolation approach using a pH-responsive peptide conjugated with NanoPom magnetic beads (ExCy) for simple, fast, and homogeneous EV isolation from various biological fluids. Bioinformatic analysis of next-generation sequencing (NGS) data of EV total RNAs from pancreatic cancer patient plasma samples using our novel EV isolation approach and quality index strategy illuminates how this approach improves the identification of tumor associated molecular markers. Results showed higher human mRNA coverage compared to existing isolation approaches in terms of both pancreatic cancer pathways and EV cellular component pathways using gProfiler pathway analysis. This study provides a valuable resource for researchers, establishing a workflow to prepare and analyze EV samples carefully and contributing to the advancement of reliable and rigorous EV quality assessment and clinical translation.

Differential sensitivity to longitudinal and transverse stretch mediates transcriptional responses in mouse neonatal ventricular myocytes

To identify how cardiomyocyte mechanosensitive signaling pathways are regulated by anisotropic stretch, micropatterned mouse neonatal cardiomyocytes were stretched primarily longitudinally or transversely to the myofiber axis. Four hours of static, longitudinal stretch induced differential expression of 557 genes, compared with 30 induced by transverse stretch, measured using RNA-seq. A logic-based ordinary differential equation model of the cardiac myocyte mechanosignaling network, extended to include the transcriptional regulation and expression of 784 genes, correctly predicted measured expression changes due to anisotropic stretch with 69% accuracy. The model also predicted published transcriptional responses to mechanical load in vitro or in vivo with 63-91% accuracy. The observed differences between transverse and longitudinal stretch responses were not explained by differential activation of specific pathways but rather by an approximately twofold greater sensitivity to longitudinal stretch than transverse stretch. In vitro experiments confirmed model predictions that stretch-induced gene expression is more sensitive to angiotensin II and endothelin-1, via RhoA and MAP kinases, than to the three membrane ion channels upstream of calcium signaling in the network. Quantitative cardiomyocyte gene expression differs substantially with the axis of maximum principal stretch relative to the myofilament axis, but this difference is due primarily to differences in stretch sensitivity rather than to selective activation of mechanosignaling pathways.NEW & NOTEWORTHY Anisotropic stretch applied to micropatterned neonatal mouse ventricular myocytes induced markedly greater acute transcriptional responses when the major axis of stretch was parallel to the myofilament axis than when it was transverse. Analysis with a novel quantitative network model of mechanoregulated cardiomyocyte gene expression suggests that this difference is explained by higher cell sensitivity to longitudinal loading than transverse loading than by the activation of differential signaling pathways.

An integrated precision medicine approach in major depressive disorder: a study protocol to create a new algorithm for the prediction of treatment response

Major depressive disorder (MDD) is the most common psychiatric disease worldwide with a huge socio-economic impact. Pharmacotherapy represents the most common option among the first-line treatment choice; however, only about one third of patients respond to the first trial and about 30% are classified as treatment-resistant depression (TRD). TRD is associated with specific clinical features and genetic/gene expression signatures. To date, single sets of markers have shown limited power in response prediction. Here we describe the methodology of the PROMPT project that aims at the development of a precision medicine algorithm that would help early detection of non-responder patients, who might be more prone to later develop TRD. To address this, the project will be organized in 2 phases. Phase 1 will involve 300 patients with MDD already recruited, comprising 150 TRD and 150 responders, considered as extremes phenotypes of response. A deep clinical stratification will be performed for all patients; moreover, a genomic, transcriptomic and miRNomic profiling will be conducted. The data generated will be exploited to develop an innovative algorithm integrating clinical, omics and sex-related data, in order to predict treatment response and TRD development. In phase 2, a new naturalistic cohort of 300 MDD patients will be recruited to assess, under real-world conditions, the capability of the algorithm to correctly predict the treatment outcomes. Moreover, in this phase we will investigate shared decision making (SDM) in the context of pharmacogenetic testing and evaluate various needs and perspectives of different stakeholders toward the use of predictive tools for MDD treatment to foster active participation and patients' empowerment. This project represents a proof-of-concept study. The obtained results will provide information about the feasibility and usefulness of the proposed approach, with the perspective of designing future clinical trials in which algorithms could be tested as a predictive tool to drive decision making by clinicians, enabling a better prevention and management of MDD resistance.

Characterization of circulating microRNA profiles of postpartum dairy cows with persistent subclinical endometritis

Subclinical endometritis (SCE) is an unresolved inflammation of the endometrium of postpartum dairy cows, seriously affecting fertility. Current diagnosis, which relies on uterine cytology or even more invasive biopsy sampling, would benefit from the identification of blood-based diagnostic biomarkers. Due to the known role of microRNAs (miRNAs) in other diseases, this case-control study evaluated the cell-free circulating miRNA profiles of SCE cows, and the network of transcripts predicted to interact with those miRNAs, previously identified as differentially expressed genes (DEG) in the endometrium of the same cows. Healthy (H, n = 6) and persistent SCE (n = 11) cows characterized by endometrial cytology and biopsy were blood sampled at 21 and 44 d postpartum (DPP). Following extraction of cell-free plasma miRNAs and RNA-seq analysis, differential abundance analysis of miRNAs was performed with the DESeq2 R package (adjusted p-value of 0.05), and in silico prediction of miRNA-interacting genes on a sequence complementary basis was conducted using the miRWalk database. The principal component analysis showed a clear clustering between groups of uterine health phenotypes (H vs. SCE), although the clustering between groups was less pronounced at 44 DPP than at 21 DPP. No effect of the stage (21 vs. 44 DPP) was observed. A total of 799 known circulating miRNAs were identified, from which 34 demonstrated differential abundance between H and SCE cows (12 less abundant and 22 more abundant in SCE than in H cows). These 34 miRNAs are predicted to interact with 10,104 transcripts, among which 43, 81, and 147 were previously identified as differentially expressed in, respectively, endometrial luminal epithelial, glandular epithelial, and stromal cells of the same cows. This accounts for approximately half of the DEG identified between those H and SCE cows, including genes involved in endometrial cell proliferation, angiogenesis and immune response, whose dysregulation in SCE cows may impair pregnancy establishment. From 219 miRNAs with mean normalized read counts above 100, the presence and abundance of miR-425-3p and miR-2285z had the highest discriminatory level to differentiate SCE from H cows. In conclusion, despite apparent confinement to the endometrium, SCE is associated with a distinct circulating miRNA profile, which may represent a link between the systemic changes associated with disease and the endometrial immune response. The validation of a miRNA panel consisting of circulating cell-free miR-425-3p and miR-2285z may prove a relevant advancement for the noninvasive diagnosis of persistent SCE.

Comparison of Transcriptomic Changes in Survivors of Exertional Heat Illness with Malignant Hyperthermia Susceptible Patients

Exertional heat illness (EHI) is an occupational health hazard for athletes and military personnel-characterised by the inability to thermoregulate during exercise. The ability to thermoregulate can be studied using a standardised heat tolerance test (HTT) developed by The Institute of Naval Medicine. In this study, we investigated whole blood gene expression (at baseline, 2 h post-HTT and 24 h post-HTT) in male subjects with either a history of EHI or known susceptibility to malignant hyperthermia (MHS): a pharmacogenetic condition with similar clinical phenotype. Compared to healthy controls at baseline, 291 genes were differentially expressed in the EHI cohort, with functional enrichment in inflammatory response genes (up to a four-fold increase). In contrast, the MHS cohort featured 1019 differentially expressed genes with significant down-regulation of genes associated with oxidative phosphorylation (OXPHOS). A number of differentially expressed genes in the inflammation and OXPHOS pathways overlapped between the EHI and MHS subjects, indicating a common underlying pathophysiology. Transcriptome profiles between subjects who passed and failed the HTT (based on whether they achieved a plateau in core temperature or not, respectively) were not discernable at baseline, and HTT was shown to elevate inflammatory response gene expression across all clinical phenotypes.

Associations between the postpartum uterine and vaginal microbiota and the subsequent development of purulent vaginal discharge vary with dairy cow breed and parity

The objective of this study was to characterize the species composition and functional potential of the vaginal and uterine microbiota at 1 wk postpartum in dairy cows diagnosed with or without purulent vaginal discharge (PVD) at 3 wk postpartum. The hypothesis was that differences in the vaginal and uterine microbiota between cows diagnosed with (PVD+) or without (PVD-) PVD were dependent on parity and breed. Cytobrush samples of the vagina and uterus were collected at 1 wk postpartum from 36 Holstein-Friesian (7 primiparous and 29 multiparous) and 29 Jersey (10 primiparous and 19 multiparous) cows. Microbial DNA was isolated from each sample and processed for shotgun metagenomic sequencing. The odds of multiparous cows being diagnosed as PVD+ was less compared with primiparous cows (OR = 0.21). Neither the α-diversity nor β-diversity of the uterine and vaginal microbiota were associated with PVD but the β-diversity was different between breeds and between parities. In the vagina of primiparous cows, differences in the microbiota of PVD- and PVD+ cows were minor, but the microbiota of multiparous PVD+ cows had greater relative abundance of Fusobacterium necrophorum, Trueperella pyogenes, Porphyromonas levii, and greater functional potential for amino acid and protein synthesis, energy metabolism, and growth compared with PVD- cows. The uterus of primiparous PVD+ cows had lesser relative abundance of Bacteroides heparinolyticus compared with PVD- cows. In the uterine microbiota, differences included greater functional potential for cellulose biosynthesis and fucose catabolism in multiparous PVD+ cows compared with PVD- cows. In the uterine microbiota of primiparous PVD+ cows, the functional potential for gram-negative cell wall synthesis and for negative regulation of tumor necrosis factor signaling was lesser compared with multiparous PVD+ cows. In the vagina of Holstein-Friesian PVD+ cows, the relative abundance of Caviibacter abscessus was greater whereas in the vagina of Jersey PVD+ cows the relative abundance of Catenibacterium mitsuokai, Finegoldia magna, Klebsiella variicola, and Streptococcus anginosus was greater compared with PVD- cows. In the uterine microbiota of Holstein-Friesian cows, the functional potential for spermidine biosynthesis was reduced compared with PVD- cows. In summary, differences in the species composition and functional potential of the vaginal and uterine microbiota between PVD- and PVD+ cows were dependent on parity and breed. The findings suggest that alternative strategies may be required to treat PVD for different parities and breeds of dairy cow.

RNA-sequencing of peripheral whole blood of individuals at ultra-high-risk for psychosis - A longitudinal perspective

BACKGROUND

The peripheral blood is an attractive source of prognostic biomarkers for psychosis conversion. There is limited research on the transcriptomic changes associated with psychosis conversion in the peripheral whole blood.

STUDY DESIGN

We performed RNA-sequencing of peripheral whole blood from 65 ultra-high-risk (UHR) participants and 70 healthy control participants recruited in the Longitudinal Youth-at-Risk Study (LYRIKS) cohort. 13 UHR participants converted in the study duration. Samples were collected at 3 timepoints, at 12-months interval across a 2-year period. We examined whether the genes differential with psychosis conversion contain schizophrenia risk loci. We then examined the functional ontologies and GWAS associations of the differential genes. We also identified the overlap between differentially expressed genes across different comparisons.

STUDY RESULTS

Genes containing schizophrenia risk loci were not differentially expressed in the peripheral whole blood in psychosis conversion. The differentially expressed genes in psychosis conversion are enriched for ontologies associated with cellular replication. The differentially expressed genes in psychosis conversion are associated with non-neurological GWAS phenotypes reported to be perturbed in schizophrenia and psychosis but not schizophrenia and psychosis phenotypes themselves. We found minimal overlap between the genes differential with psychosis conversion and the genes that are differential between pre-conversion and non-conversion samples.

CONCLUSION

The associations between psychosis conversion and peripheral blood-based biomarkers are likely to be indirect. Further studies to elucidate the mechanism behind potential indirect associations are needed.

An approach for prioritizing candidate genes from RNA-seq using preclinical cocaine self-administration datasets as a test case

RNA-sequencing (RNA-seq) technology has led to a surge of neuroscience research using animal models to probe the complex molecular mechanisms underlying brain function and behavior, including substance use disorders. However, findings from rodent studies often fail to be translated into clinical treatments. Here, we developed a novel pipeline for narrowing candidate genes from preclinical studies by translational potential and demonstrated its utility in 2 RNA-seq studies of rodent self-administration. This pipeline uses evolutionary conservation and preferential expression of genes across brain tissues to prioritize candidate genes, increasing the translational utility of RNA-seq in model organisms. Initially, we demonstrate the utility of our prioritization pipeline using an uncorrected P-value. However, we found no differentially expressed genes in either dataset after correcting for multiple testing with false discovery rate (FDR < 0.05 or <0.1). This is likely due to low statistical power that is common across rodent behavioral studies, and, therefore, we additionally illustrate the use of our pipeline on a third dataset with differentially expressed genes corrected for multiple testing (FDR < 0.05). We also advocate for improved RNA-seq data collection, statistical testing, and metadata reporting that will bolster the field's ability to identify reliable candidate genes and improve the translational value of bioinformatics in rodent research.

Molecular fingerprints in the hippocampus of alcohol seeking during withdrawal

Alcohol use disorder (AUD) is characterized by pathological motivation to consume alcohol and cognitive inflexibility, leading to excessive alcohol seeking and use. Due to limited understanding of the molecular basis of the disease, there are few pharmacological interventions available to combat AUD. In this study, we aimed to investigate the molecular correlates of impaired extinction of alcohol seeking during alcohol withdrawal using a mouse model of AUD implemented in the automated IntelliCage social system. This model enabled us to distinguish between animals exhibiting AUD-prone and AUD-resistant phenotypes, based on the presence of ≥ 2 or < 2 criteria of AUD, respectively. We utilized new generation RNA sequencing to identify genes that were differentially expressed in the hippocampus and amygdala of mice meeting ≥ 2 or < 2 criteria, as these brain regions are implicated in alcohol motivation, seeking, consumption and the cognitive inflexibility characteristic of AUD. To complement the sequencing studies, we conducted ex vivo electrophysiology experiments. Our findings revealed significant dysregulation of the hippocampal genes associated with the actin cytoskeleton and synaptic function, including actin binding molecule cofilin, during alcohol withdrawal in mice meeting ≥ 2 criteria compared to those meeting < 2 criteria. Moreover, this dysregulation was accompanied by impaired synaptic transmission in the molecular layer of the hippocampal dentate gyrus (ML-DG). Additionally, we demonstrated that overexpression of cofilin in the polymorphic layer of the hippocampal dentate gyrus (PoDG) inhibited ML-DG synapses, increased motivation to seek alcohol, impaired extinction of alcohol seeking and increased correlation between AUD behaviors, resembling the phenotype observed in mice meeting ≥ 2 criteria. Overall, our study uncovers a novel mechanism linking increased hippocampal cofilin expression with the AUD phenotype.

Molecular fingerprints in the hippocampus of alcohol seeking during withdrawal

Alcohol use disorder (AUD) is characterized by excessive alcohol seeking and use. Here, we investigated the molecular correlates of impaired extinction of alcohol seeking using a multidimentional mouse model of AUD. We distinguished AUD-prone and AUD-resistant mice, based on the presence of ≥ 2 or < 2 criteria of AUD and utilized RNA sequencing to identify genes that were differentially expressed in the hippocampus and amygdala of mice meeting ≥ 2 or < 2 criteria, as these brain regions are implicated in alcohol motivation, seeking, consumption and the cognitive inflexibility characteristic of AUD. Our findings revealed dysregulation of the genes associated with the actin cytoskeleton, including actin binding molecule cofilin, and impaired synaptic transmission in the hippocampi of mice meeting ≥ 2 criteria. Overexpression of cofilin in the polymorphic layer of the dentate gyrus (PoDG) inhibited ML-DG synapses, increased motivation to seek alcohol and impaired extinction of alcohol seeking, resembling the phenotype observed in mice meeting ≥ 2 criteria. Overall, our study uncovers a novel mechanism linking increased hippocampal cofilin expression with the AUD phenotype.

Post-COVID symptoms are associated with endotypes reflecting poor inflammatory and hemostatic modulation

Introduction

Persistent symptoms after COVID-19 infection ("long COVID") negatively affects almost half of COVID-19 survivors. Despite its prevalence, its pathophysiology is poorly understood, with multiple host systems likely affected. Here, we followed patients from hospital to discharge and used a systems-biology approach to identify mechanisms of long COVID.

Methods

RNA-seq was performed on whole blood collected early in hospital and 4-12 weeks after discharge from 24 adult COVID-19 patients (10 reported post-COVID symptoms after discharge). Differential gene expression analysis, pathway enrichment, and machine learning methods were used to identify underlying mechanisms for post-COVID symptom development.

Results

Compared to patients with post-COVID symptoms, patients without post-COVID symptoms had larger temporal gene expression changes associated with downregulation of inflammatory and coagulation genes over time. Patients could also be separated into three patient endotypes with differing mechanistic trajectories, which was validated in another published patient cohort. The "Resolved" endotype (lowest rate of post-COVID symptoms) had robust inflammatory and hemostatic responses in hospital that resolved after discharge. Conversely, the inflammatory/hemostatic responses of "Suppressive" and "Unresolved" endotypes (higher rates of patients with post-COVID symptoms) were persistently dampened and activated, respectively. These endotypes were accurately defined by specific blood gene expression signatures (6-7 genes) for potential clinical stratification.

Discussion

This study allowed analysis of long COVID whole blood transcriptomics trajectories while accounting for the issue of patient heterogeneity. Two of the three identified and externally validated endotypes ("Unresolved" and "Suppressive") were associated with higher rates of post-COVID symptoms and either persistently activated or suppressed inflammation and coagulation processes. Gene biomarkers in blood could potentially be used clinically to stratify patients into different endotypes, paving the way for personalized long COVID treatment.

The power of effective study design in animal Experimentation: Exploring the statistical and ethical implications of asking multiple questions of a data set

One of the chief advantages of using highly standardised biological models including model organisms is that multiple variables can be precisely controlled so that the variable of interest is more easily studied. However, such an approach often obscures effects in sub-populations resulting from natural population heterogeneity. Efforts to expand our fundamental understanding of multiple sub-populations are in progress. However, such stratified or personalised approaches require fundamental modifications of our usual study designs that should be implemented in Brain, Behavior and Immunity (BBI) research going forward. Here we explore the statistical feasibility of asking multiple questions (including incorporating sex) within the same experimental cohort using statistical simulations of real data. We illustrate and discuss the large explosion in sample numbers necessary to detect effects with appropriate power for every additional question posed using the same data set. This exploration highlights the strong likelihood of type II errors (false negatives) for standard data and type I errors when dealing with complex genomic data, where studies are too under-powered to appropriately test these interactions. We show this power may differ for males and females in high throughput data sets such as RNA sequencing. We offer a rationale for the use of alternative experimental and statistical strategies based on interdisciplinary insights and discuss the real-world implications of increasing the complexities of our experimental designs, and the implications of not attempting to alter our experimental designs going forward.

Transcription dosage compensation does not occur in Down syndrome

Background

Trisomy 21, also known as Down syndrome, describes the genetic condition of having an extra copy of chromosome 21. The increase in DNA copy number has led to the "DNA dosage hypothesis", which claims that the level of gene transcription is proportional to the gene's DNA copy number. Yet many reports have suggested that a proportion of chromosome 21 genes are dosage compensated back towards typical expression levels (1.0x). In contrast, other reports suggest that dosage compensation is not a common mechanism of gene regulation in Trisomy 21, providing support to the DNA dosage hypothesis.

Results

In our work, we use both simulated and real data to dissect the elements of differential expression analysis that can lead to the appearance of dosage compensation even when compensation is demonstrably absent. Using lymphoblastoid cell lines derived from a family of an individual with Down syndrome, we demonstrate that dosage compensation is nearly absent at both nascent transcription (GRO-seq) and steady-state RNA (RNA-seq) levels.

Conclusions

Transcriptional dosage compensation does not occur in Down syndrome. Simulated data containing no dosage compensation can appear to have dosage compensation when analyzed via standard methods. Moreover, some chromosome 21 genes that appear to be dosage compensated are consistent with allele specific expression.

Association Between Serum MicroRNAs and Abdominal Aortic Aneurysm Diagnosis and Growth

OBJECTIVE

This study aimed to examine the association between serum microRNAs (miRNAs) and diagnosis and growth of abdominal aortic aneurysm (AAA), and to test their diagnostic and prognostic value.

METHODS

The expression levels of 800 miRNA tags were assessed in 108 patients with AAA, 12 age and sex matched healthy controls (HCs), and 12 patients with peripheral artery disease (PAD) using NanoString technology. Findings were assessed in an independent sample of 66 patients with AAA and 29 age and sex matched HCs by reverse transcriptase polymerase chain reaction. AAA growth was assessed by a median of three (interquartile range [IQR] 2, 3) repeat ultrasound scans over a median follow up of 1.1 (IQR 1.0, 2.0) years. The association between the miRNA and AAA diagnosis and growth was examined by regression and linear mixed effects analyses. The diagnostic and prognostic potential of the miRNAs were examined using area under the receiver operator characteristic curve (AUC), net re-classification index (NRI), and Cox hazard analyses.

RESULTS

In comparison with HCs, a model combining clinical risk factors, let-7b-5p and miR-548n had an AUC of 98.0% (95% confidence interval [CI] 95.6 - 100.0; p = .003) for diagnosing AAA, which was a significant improvement over clinical risk factors alone (NRI 1.74; 95% CI 1.61 - 1.87; p < .001). Compared with PAD, a model combining clinical risk factors and miR-548n had an AUC of 99.6% (95% CI 98.9 - 100.0, p = .037) for diagnosing AAA, which was a significant improvement over clinical risk factors alone (NRI 1.79, 95% CI 1.68 - 1.91; p < .001). In the longitudinal cohort, none of the miRNAs were able to predict the likelihood of reaching surgical threshold diameter better than clinical risk factors alone.

CONCLUSION

Serum let-7b-5p and miR548n significantly improved the ability to diagnose AAA. None of the miRNAs had independent prognosis value in predicting AAA growth.

Differences in Whole-Blood Transcriptional Profiles in Inflammatory Bowel Disease Patients Responding to Vedolizumab Compared with Non-Responders

Vedolizumab is efficacious in the treatment of Crohn's disease (CD) and ulcerative colitis (UC). However, a significant proportion of patients present with a non-response. To investigate whether differences in the clinical response to vedolizumab is reflected in changes in gene expression levels in whole blood, samples were collected at baseline before treatment, and at follow-up after 10-12 weeks. Whole genome transcriptional profiles were established by RNA sequencing. Before treatment, no differentially expressed genes were noted between responders (n = 9, UC 4, CD 5) and non-responders (n = 11, UC 3, CD 8). At follow-up, compared with baseline, responders displayed 201 differentially expressed genes, and 51 upregulated (e.g., translation initiation, mitochondrial translation, and peroxisomal membrane protein import) and 221 downregulated (e.g., Toll-like receptor activating cascades, and phagocytosis related) pathways. Twenty-two of the upregulated pathways in responders were instead downregulated in non-responders. The results correspond with a dampening of inflammatory activity in responders. Although considered a gut-specific drug, our study shows a considerable gene regulation in the blood of patients responding to vedolizumab. It also suggests that whole blood is not optimal for identifying predictive pre-treatment biomarkers based on individual genes. However, treatment outcomes may depend on several interacting genes, and our results indicate a possible potential of pathway analysis in predicting response to treatment, which merits further investigation.

Statistical power in network neuroscience

Network neuroscience has emerged as a leading method to study brain connectivity. The success of these investigations is dependent not only on approaches to accurately map connectivity but also on the ability to detect real effects in the data - that is, statistical power. We review the state of statistical power in the field and discuss sample size, effect size, measurement error, and network topology as key factors that influence the power of brain connectivity investigations. We use the term 'differential power' to describe how power can vary between nodes, edges, and graph metrics, leaving traces in both positive and negative connectome findings. We conclude with strategies for working with, rather than around, power in connectivity studies.

Detection of genes with differential expression dispersion unravels the role of autophagy in cancer progression

The majority of gene expression studies focus on the search for genes whose mean expression is different between two or more populations of samples in the so-called "differential expression analysis" approach. However, a difference in variance in gene expression may also be biologically and physiologically relevant. In the classical statistical model used to analyze RNA-sequencing (RNA-seq) data, the dispersion, which defines the variance, is only considered as a parameter to be estimated prior to identifying a difference in mean expression between conditions of interest. Here, we propose to evaluate four recently published methods, which detect differences in both the mean and dispersion in RNA-seq data. We thoroughly investigated the performance of these methods on simulated datasets and characterized parameter settings to reliably detect genes with a differential expression dispersion. We applied these methods to The Cancer Genome Atlas datasets. Interestingly, among the genes with an increased expression dispersion in tumors and without a change in mean expression, we identified some key cellular functions, most of which were related to catabolism and were overrepresented in most of the analyzed cancers. In particular, our results highlight autophagy, whose role in cancerogenesis is context-dependent, illustrating the potential of the differential dispersion approach to gain new insights into biological processes and to discover new biomarkers.

Influence of RNA-Seq library construction, sampling methods, and tissue harvesting time on gene expression estimation

RNA sequencing (RNA-Seq) is popular for measuring gene expression in non-model organisms, including wild populations. While RNA-Seq can detect gene expression variation among wild-caught individuals and yield important insights into biological function, sampling methods can also affect gene expression estimates. We examined the influence of multiple technical variables on estimated gene expression in a non-model fish, the westslope cutthroat trout (Oncorhynchus clarkii lewisi), using two RNA-Seq library types: 3' RNA-Seq (QuantSeq) and whole mRNA-Seq (NEB). We evaluated effects of dip netting versus electrofishing, and of harvesting tissue immediately versus 5 min after euthanasia on estimated gene expression in blood, gill, and muscle. We found no significant differences in gene expression between sampling methods or tissue collection times with either library type. When library types were compared using the same blood samples, 58% of genes detected by both NEB and QuantSeq showed significantly different expression between library types, and NEB detected 31% more genes than QuantSeq. Although the two library types recovered different numbers of genes and expression levels, results with NEB and QuantSeq were consistent in that neither library type showed differences in gene expression between sampling methods and tissue harvesting times. Our study suggests that researchers can safely rely on different fish sampling strategies in the field. In addition, while QuantSeq is more cost effective, NEB detects more expressed genes. Therefore, when it is crucial to detect as many genes as possible (especially low expressed genes), when alternative splicing is of interest, or when working with an organism lacking good genomic resources, whole mRNA-Seq is more powerful.

Statistical Power Analysis for Designing Bulk, Single-Cell, and Spatial Transcriptomics Experiments: Review, Tutorial, and Perspectives

Gene expression profiling technologies have been used in various applications such as cancer biology. The development of gene expression profiling has expanded the scope of target discovery in transcriptomic studies, and each technology produces data with distinct characteristics. In order to guarantee biologically meaningful findings using transcriptomic experiments, it is important to consider various experimental factors in a systematic way through statistical power analysis. In this paper, we review and discuss the power analysis for three types of gene expression profiling technologies from a practical standpoint, including bulk RNA-seq, single-cell RNA-seq, and high-throughput spatial transcriptomics. Specifically, we describe the existing power analysis tools for each research objective for each of the bulk RNA-seq and scRNA-seq experiments, along with recommendations. On the other hand, since there are no power analysis tools for high-throughput spatial transcriptomics at this point, we instead investigate the factors that can influence power analysis.

The complex role of transcription factor GAGA in germline death during Drosophila spermatogenesis: transcriptomic and bioinformatic analyses

The GAGA protein (also known as GAF) is a transcription factor encoded by the Trl gene in D. melanogaster. GAGA is involved in the regulation of transcription of many genes at all stages of fly development and life. Recently, we investigated the participation of GAGA in spermatogenesis and discovered that Trl mutants experience massive degradation of germline cells in the testes. Trl underexpression induces autophagic death of spermatocytes, thereby leading to reduced testis size. Here, we aimed to determine the role of the transcription factor GAGA in the regulation of ectopic germline cell death. We investigated how Trl underexpression affects gene expression in the testes. We identified 15,993 genes in three biological replicates of our RNA-seq analysis and compared transcript levels between hypomorphic Trl ^R85/Trl ³⁶² and Oregon testes. A total of 2,437 differentially expressed genes were found, including 1,686 upregulated and 751 downregulated genes. At the transcriptional level, we detected the development of cellular stress in the Trl-mutant testes: downregulation of the genes normally expressed in the testes (indicating slowed or abrogated spermatocyte differentiation) and increased expression of metabolic and proteolysis-related genes, including stress response long noncoding RNAs. Nonetheless, in the Flybase Gene Ontology lists of genes related to cell death, autophagy, or stress, there was no enrichment with GAGA-binding sites. Furthermore, we did not identify any specific GAGA-dependent cell death pathway that could regulate spermatocyte death. Thus, our data suggest that GAGA deficiency in male germline cells leads to an imbalance of metabolic processes, impaired mitochondrial function, and cell death due to cellular stress.

Multi-platform proteomic analysis of Alzheimer’s disease cerebrospinal fluid and plasma reveals network biomarkers associated with proteostasis and the matrisome

Robust and accessible biomarkers that can capture the heterogeneity of Alzheimer’s disease and its diverse pathological processes are urgently needed. Here, we undertook an investigation of Alzheimer’s disease cerebrospinal fluid (CSF) and plasma from the same subjects (n=18 control, n=18 AD) using three different proteomic platforms—SomaLogic SomaScan, Olink proximity extension assay, and tandem mass tag-based mass spectrometry—to assess which protein markers in these two biofluids may serve as reliable biomarkers of AD pathophysiology observed from unbiased brain proteomics studies. Median correlation of overlapping protein measurements across platforms in CSF (r~0.7) and plasma (r~0.6) was good, with more variability in plasma. The SomaScan technology provided the most measurements in plasma. Surprisingly, many proteins altered in AD CSF were found to be altered in the opposite direction in plasma, including important members of AD brain co-expression modules. An exception was SMOC1, a key member of the brain matrisome module associated with amyloid-β deposition in AD, which was found to be elevated in both CSF and plasma. Protein co-expression analysis on greater than 7000 protein measurements in CSF and 9500 protein measurements in plasma across all proteomic platforms revealed strong changes in modules related to autophagy, ubiquitination, and sugar metabolism in CSF, and endocytosis and the matrisome in plasma. Cross-platform and cross-biofluid proteomics represents a promising approach for AD biomarker development.

In vitro and in vivo-produced male dairy calves show molecular differences in the hepatic and muscular energy regulation

In cattle, the in vitro production (IVP) of embryos is becoming more relevant than embryos produced in vivo, i.e. after multiple ovulation and embryo transfer (MOET). However, the effects of IVP on the developmental programming of specific organs in the postnatal calves are yet unknown. Previously, we reported an epigenomic and transcriptomic profile of the hypothalamus–pituitary–testicular axis compatible with its earlier activation in IVP calves compared to MOET animals. Here, we studied the hepatic and muscular epigenome and transcriptome of those same male dairy calves (n = 4 per group). Tissue samples from liver and semitendinosus muscle were obtained at 3 months of age, and the extracted gDNA and RNA were sequenced through whole-genome bisulfite sequencing and RNA-sequencing, respectively. Next, bioinformatic analyses determined differentially methylated cytosines or differentially expressed genes [false discovery rate (FDR) < 0.05] for each Omic dataset; and nonparametrically combined genes (NPCG) for both integrated omics (P < 0.05). KEGG pathways enrichment analysis showed that NPCG upregulated in the liver and the muscle of the IVP calves were involved in oxidative phosphorylation and the tricarboxylic acid cycle. In contrast, ribosome and translation were upregulated in the liver but downregulated in the muscle of the IVP calves compared to the MOET calves (FDR < 0.05). A model considering the effect of the methylation levels and the group on the expression of all the genes involved in these pathways confirmed these findings. In conclusion, the multiomics data integration approach indicated an altered hepatic and muscular energy regulation in phenotypically normal IVP calves compared to MOET calves.

Transcriptomic signals of mitochondrial dysfunction and OXPHOS dynamics in fast-growth chicken

Introduction

Birds are equipped with unique evolutionary adaptations to counter oxidative stress. Studies suggest that lifespan is inversely correlated with oxidative damage in birds. Mitochondrial function and performance are critical for cellular homeostasis, but the age-related patterns of mitochondrial gene expression and oxidative phosphorylation (OXPHOS) in birds are not fully understood. The domestic chicken is an excellent model to understand aging in birds; modern chickens are selected for rapid growth and high fecundity and oxidative stress is a recurring feature in chicken. Comparing fast- and slow-growing chicken phenotypes provides us an opportunity to disentangle the nexus of oxidative homeostasis, growth rate, and age in birds.

Methods and Results

We compared pectoralis muscle gene expression patterns between a fast and a slow-growing chicken breed at 11 and 42 days old. Using RNAseq analyses, we found that mitochondrial dysfunction and reduced oxidative phosphorylation are major features of fast-growth breast muscle, compared to the slow-growing heritage breed. We found transcriptomic evidence of reduced OXPHOS performance in young fast-growth broilers, which declined further by 42 days.

Discussion

OXPHOS performance declines are a common feature of aging. Sirtuin signaling and NRF2 dependent oxidative stress responses support the progression of oxidative damage in fast-growth chicken. Our gene expression datasets showed that fast growth in early life places immense stress on oxidative performance, and rapid growth overwhelms the OXPHOS system. In summary, our study suggests constraints on oxidative capacity to sustain fast growth at high metabolic rates, such as those exhibited by modern broilers.

Effects of three graphene-based materials on the growth and photosynthesis of Brassica napus L

The environmental safety and threats of graphene-based materials (GBMs) to the agroecosystem have attracted increasing attention in recent years. However, the mechanisms underlying the effects of GBMs on plants remain unclear. Here, we investigated the phytotoxicity of reduced graphene oxide (RGO), graphene oxide (GO) and amine-functionalized graphene (G-NH2) on Brassica napus L. The results revealed that RGO impaired photosynthesis mainly by decreasing the chlorophyll content and Rubisco activity. A further gene-level analysis suggested that this effect of RGO might be due to its toxicity on sulfate transmembrane transporter and nitrogen metabolism, which ultimately led to nutrient imbalance. However, GO directly damaged the photosystem by disrupting the chloroplast structure, and a decrease in Rubisco activity indicated that GO also inhibits carbon fixation. Further gene-level analysis demonstrated that GO has toxicity on the chloroplast membrane, photosystem, photosynthethic electron transport and F-type ATPase. In addition, G-NH2 at 10-1000 mg L-1 showed no significant toxicity. These findings shed light on the potential mechanism for the toxicity of GBMs on plants for risk assessment.

Neurophysiological and transcriptomic predictors of chronic low back pain: Study protocol for a longitudinal inception cohort study

Chronic low back pain is one of the most common, costly, and debilitating pain conditions worldwide. Increased mechanistic understanding of the transition from acute to chronic low back and identification of predictive biomarkers could enhance the clinical assessment performed by healthcare providers and enable the development of targeted treatment to prevent and/or better manage chronic low back pain. This study protocol was designed to identify the neurological and transcriptomic biomarkers predictive of chronic low back pain at low back pain onset. This is a prospective descriptive longitudinal inception cohort study that will follow 340 individuals with acute low back pain and 40 healthy controls over 2 years. To analyze the neurophysiological and transcriptomic biomarkers of low back pain, the protocol includes psychological and pain-related survey data that will be collected beginning within 6 weeks of low back pain onset (baseline, 6, 12, 24, 52 weeks, and 2 years) and remotely at five additional time points (8, 10, 16, 20 weeks, and 18 months). Quantitative sensory testing and collection of blood samples for RNA sequencing will occur during the six in-person visits. The study results will describe variations in the neurophysiological and transcriptomic profiles of healthy pain-free controls and individuals with low back pain who either recover to pain-free status or develop chronic low back pain.

Progesterone differentially affects the transcriptomic profiles of cow endometrial cell types

Background

The endometrium is a heterogeneous tissue composed of luminal epithelial (LE), glandular epithelial (GE), and stromal cells (ST), experiencing progesterone regulated dynamic changes during the estrous cycle. In the cow, this regulation at the transcriptomic level was only evaluated in the whole tissue. This study describes specific gene expression in the three types of cells isolated from endometrial biopsies following laser capture microdissection and the transcriptome changes induced by progesterone in GE and ST cells.

Results

Endometrial LE, GE, and ST cells show specific transcriptomic profiles. Most of the differentially expressed genes (DEGs) in response to progesterone are cell type-specific (96%). Genes involved in cell cycle and nuclear division are under-expressed in the presence of progesterone in GE, highlighting the anti-proliferative action of progesterone in epithelial cells. Elevated progesterone concentrations are also associated with the under-expression of estrogen receptor 1 (ESR1) in GE and oxytocin receptor (OXTR) in GE and ST cells. In ST cells, transcription factors such as SOX17 and FOXA2, known to regulate uterine epithelial-stromal cross-talk conveying to endometrial receptivity, are over-expressed under progesterone influence.

Conclusions

The results from this study show that progesterone regulates endometrial function in a cell type-specific way, which is independent of the expression of its main receptor PGR. These novel insights into uterine physiology present the cell compartment as the physiological unit rather than the whole tissue.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08323-z.

Exploring the role of immune pathways in the risk and development of depression in adolescence: Research protocol of the IDEA-FLAME study

Extensive research suggests a role for the innate immune system in the pathogenesis of depression, but most of the studies are conducted in adult populations, in high-income countries and mainly focus on the study of inflammatory proteins alone, which provides only a limited understanding of the immune pathways involved in the development of depression. The IDEA-FLAME study aims to identify immune phenotypes underlying increased risk of developing depression in adolescence in a middle-income country. To this end, we will perform deep-immunophenotyping of peripheral blood mononuclear cells and RNA genome-wide gene expression analyses in a longitudinal cohort of Brazilian adolescents stratified for depression risk. The project will involve the 3-year follow-up of an already recruited cohort of 150 Brazilian adolescents selected for risk/presence of depression on the basis of a composite risk score we developed using sociodemographic characteristics (50 adolescents with low-risk and 50 with high-risk of developing depression, and 50 adolescents with a current major depressive disorder). We will 1) test whether the risk group classification at baseline is associated with differences in immune cell frequency, phenotype and functional status, 2) test whether baseline immune markers (cytokines and immune cell markers) are associated with severity of depression at 3-year follow-up, and 3) identify changes in gene expression of immune pathways over the 3-year follow-up in adolescents with increased risk and presence of depression. Because of the exploratory nature of the study, the findings would need to be replicated in a separate and larger sample. Ultimately, this research will contribute to elucidating key immune therapeutic targets and inform the development of interventions to prevent onset of depression among adolescents.

A novel role for vaping in mitochondrial gene dysregulation and inflammation fundamental to disease development

We constructed and analyzed the whole transcriptome in leukocytes of healthy adult vapers (with/without a history of smoking), ‘exclusive’ cigarette smokers, and controls (non-users of any tobacco products). Furthermore, we performed single-gene validation of expression data, and biochemical validation of vaping/smoking status by plasma cotinine measurement. Computational modeling, combining primary analysis (age- and sex-adjusted limmaVoom) and sensitivity analysis (cumulative e-liquid- and pack-year modeling), revealed that ‘current’ vaping, but not ‘past’ smoking, is significantly associated with gene dysregulation in vapers. Comparative analysis of the gene networks and canonical pathways dysregulated in vapers and smokers showed strikingly similar patterns in the two groups, although the extent of transcriptomic changes was more pronounced in smokers than vapers. Of significance is the preferential targeting of mitochondrial genes in both vapers and smokers, concurrent with impaired functional networks, which drive mitochondrial DNA-related disorders. Equally significant is the dysregulation of immune response genes in vapers and smokers, modulated by upstream cytokines, including members of the interleukin and interferon family, which play a crucial role in inflammation. Our findings accord with the growing evidence on the central role of mitochondria as signaling organelles involved in immunity and inflammatory response, which are fundamental to disease development.

scPower accelerates and optimizes the design of multi-sample single cell transcriptomic studies

Single cell RNA-seq has revolutionized transcriptomics by providing cell type resolution for differential gene expression and expression quantitative trait loci (eQTL) analyses. However, efficient power analysis methods for single cell data and inter-individual comparisons are lacking. Here, we present scPower; a statistical framework for the design and power analysis of multi-sample single cell transcriptomic experiments. We modelled the relationship between sample size, the number of cells per individual, sequencing depth, and the power of detecting differentially expressed genes within cell types. We systematically evaluated these optimal parameter combinations for several single cell profiling platforms, and generated broad recommendations. In general, shallow sequencing of high numbers of cells leads to higher overall power than deep sequencing of fewer cells. The model, including priors, is implemented as an R package and is accessible as a web tool. scPower is a highly customizable tool that experimentalists can use to quickly compare a multitude of experimental designs and optimize for a limited budget.

Comparative root transcriptome analysis of two soybean cultivars with different cadmium sensitivities reveals the underlying tolerance mechanisms

Soybean can provide rich protein and fat and has great economic value worldwide. Cadmium (Cd) is a toxic heavy metal to organisms. It can accumulate in plants and be transmitted to the human body via the food chain. Cd is a serious threat to soybean development, particularly root growth. Some soybean cultivars present tolerant symptoms under Cd stress; however, the potential mechanisms are not fully understood. Here, we optimized RNA-seq to identify the differentially expressed genes (DEGs) in Cd-sensitive (KUAI) and Cd-tolerant (KAIYU) soybean roots and compared the DEGs between KAIYU and KUAI. A total of 1506 and 1870 DEGs were identified in the roots of KUAI and KAIYU, respectively. Through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and gene function analyses, we found that genes related to antioxidants and sequestration were responsible for Cd tolerance in KAIYU. In addition, overexpression of Glyma11g02661, which encodes a heavy metal-transporting ATPase, significantly improved Cd tolerance in transgenic hairy roots. These results provide a preliminary understanding of the tolerance mechanisms in response to Cd stress in soybean root development and are of great importance in developing Cd-resistant soybean cultivars by using the identified DEGs through genetic modification.

Next-Generation Sequencing and Its Impacts on Entomological Research in Ecology and Evolution

The advent of NGS-based methods has been profoundly transforming entomological research. Through continual development and improvement of different methods and sequencing platforms, NGS has promoted mass elucidation of partial or whole genetic materials associated with beneficial insects, pests (of agriculture, forestry and animal, and human health), and species of conservation concern, helping to unravel ecological and evolutionary mechanisms and characterizing survival, trophic interactions, and dispersal. It is shifting the scale of biodiversity and environmental analyses from individuals and biodiversity indicator species to the large-scale study of communities and ecosystems using bulk samples of species or a mixed "soup" of environmental DNA. As the NGS-based methods have become more affordable, complexity demystified, and specificity and sensitivity proven, their use in entomological research has spread widely. This article presents several examples on how NGS-based methods have been used in entomology to provide incentives to apply them when appropriate and to open our minds to the expected advances in entomology that are yet to come.

Genetic response to nitrogen starvation in the aggressive Eucalyptus foliar pathogen Teratosphaeria destructans

Teratosphaeria destructans is one of the most aggressive foliar pathogens of Eucalyptus. The biological factors underpinning T. destructans infections, which include shoot and leaf blight on young trees, have never been interrogated. Thus, the means by which the pathogen modifies its host environment to overcome host defences remain unknown. By applying transcriptome sequencing, the aim of this study was to compare gene expression in a South African isolate of T. destructans grown on nitrogen-deficient and complete media. This made it possible to identify upregulated genes in a nitrogen-starved environment, often linked to the pathogenicity of the fungus. The results support the hypothesis that nitrogen starvation in T. destructans likely mirrors an in planta genetic response. This is because 45% of genes that were highly upregulated under nitrogen starvation have previously been reported to be associated with infection in other pathogen systems. These included several CAZymes, fungal effector proteins, peptidases, kinases, toxins, lipases and proteins associated with detoxification of toxic compounds. Twenty-five secondary metabolites were identified and expressed in both nitrogen-deficient and complete conditions. Additionally, the most highly expressed genes in both growth conditions had pathogenicity-related functions. This study highlights the large number of expressed genes associated with pathogenicity and overcoming plant defences. As such, the generated baseline knowledge regarding pathogenicity and aggressiveness in T. destructans is a valuable reference for future in planta work.

Analysis of Host Jejunum Transcriptome and Associated Microbial Community Structure Variation in Young Calves with Feed-Induced Acidosis

Diet-induced acidosis imposes a health risk to young calves. In this study, we aimed to investigate the host jejunum transcriptome changes, along with its microbial community variations, using our established model of feed-induced ruminal acidosis in young calves. Eight bull calves were randomly assigned to two diet treatments beginning at birth (a starch-rich diet, Aci; a control diet, Con). Whole-transcriptome RNA sequencing was performed on the jejunum tissues collected at 17 weeks of age. Ribosomal RNA reads were used for studying microbial community structure variations in the jejunum. A total of 853 differentially expressed genes were identified (402 upregulated and 451 downregulated) between the two groups. The cell cycle and the digestion and absorption of protein in jejunal tissue were affected by acidosis. Compared to the control, genera of Campylobacter, Burkholderia, Acidaminococcus, Corynebacterium, and Olsenella significantly increased in abundance in the Aci group, while Lachnoclostridium and Ruminococcus were significantly lower in the Aci group. Expression changes in the AXL gene were associated with the abundance variations of a high number of genera in jejunum. Our study provided a snapshot of the transcriptome changes in the jejunum and its associated meta-transcriptome changes in microbial communities in young calves with feed-induced acidosis.

Effects of Monochromatic Lighting During Incubation and Vaccination on the Splenic Transcriptome Profiles of Chicken

Lighting is a crucial environmental variable in poultry operations, but illumination during incubation is relatively understudied. The ability to stimulate development or immune performance using in ovo lighting is a promising approach for improving poultry health and welfare. This study investigated how monochromatic green light during incubation and vaccination method and timing affected chicken splenic gene expression patterns. We performed this study with 1,728 Hy-Line white layer eggs incubated under two light treatments during incubation: continuous dark and continuous green monochromatic light, over the entire incubation period. Half the eggs in each light treatment received in ovo vaccination, applied on embryonic day 18 (ED18). The remaining half were vaccinated by spraying on hatch day. After hatching, the light treatments followed the industry-standard lighting regimens. The study had six treatment groups with light-dark pairs for non-vaccinated, in ovo vaccinated, and post-hatch vaccinated. We assessed splenic gene expression at ED18 and at 7 days post-hatch (PH) in all the treatments. We isolated and sequenced 24 mRNA libraries on the Illumina platform, followed by bioinformatics and differential gene expression analyses. RNAseq analysis showed between 62 and 6,755 differentially expressed genes (DEGs) between comparisons, with the most prominent differences observed between ED and PH samples, followed by comparisons between vaccination methods. In contrast, light vs. dark treatments at ED showed limited effects on transcriptomic profiles. However, we observed a synergistic effect of lighting during incubation on post-hatch vaccination responses, with differentially expressed genes (DEGs) unique to the light treatment showing stimulation of cell proliferation with significance for immune activity (inferred from gene ontology terms). Gene ontology and pathway analysis indicated biological processes like cellular component organization or biogenesis, rhythmic process, developmental process, response to stimulus, and immune system processes were explained by the DEGs. While lighting is an important source of circadian stimulation, other controlled studies are required to clarify whether in ovo circadian entrainment plays a role in modulating immune responses.

Investigating the complex interplay between genotype and high-fat-diet feeding in the lactating mammary gland using the Tph1 and Ldlr knockout models

Obesity is a prevailing problem across the globe. Women who are obese have difficulty initiating and sustaining lactation. However, the impact of genetics and diet on breastfeeding outcomes is understudied. Here we explore the effect of diet and genotype on lactation. We utilized the low-density lipoprotein receptor (Ldlr-KO) transgenic mouse model as an obesity and hypercholesterolemia model. Additionally, we used the tryptophan hydroxylase 1 (Tph1-KO) mouse, recently identified as a potential anti-obesogenic model, to investigate if addition of Tph1-KO could ameliorate negative effects of obesity in Ldlr-KO mice. We created a novel transgenic mouse line by combining the Ldlr and Tph1 [double knockout (DKO)] mice to study the interaction between the two genotypes. Female mice were fed a low-fat diet (LFD; 10% fat) or high-fat diet (HFD; 60% fat) from 3 wk of age through early [lactation day 3 (L3)] or peak lactation [lactation day 11 (L11)]. After 4 wk of consuming either LFD or HFD, female mice were bred. On L2 and L10, dams were milked to investigate the effect of diet and genotype on milk composition. Dams were euthanized on L3 or L11. There was no impact of diet or genotype on milk protein or triglycerides (TGs) on L2; however, by L10, Ldlr-KO and DKO dams had increased TG levels in milk. RNA-sequencing of L11 mammary glands demonstrated Ldlr-KO dams fed HFD displayed enrichment of genes involved in immune system pathways. Interestingly, the DKO may alter vesicle budding and biogenesis during lactation. We also quantified macrophages by immunostaining for F4/80+ cells at L3 and L11. Diet played a significant role on L3 (P = 0.013), but genotype played a role at L11 (P < 0.0001) on numbers of F4/80+ cells. Thus the impact of diet and genotype on lactation differs depending on stage of lactation, illustrating complexities of understanding the intersection of these parameters.NEW & NOTEWORTHY We have created a novel mouse model that is focused on understanding the intersection of diet and genotype on mammary gland function during lactation.

Highly dampened blood transcriptome response in HIV patients after influenza infection

Respiratory viral (RV) infections represent a major threat for human health worldwide. Persons with HIV (PWH) have a compromised immune response and are thought to be at higher risk for severe RV disease. However, very little is known about the host immune response to RV infection in PWH. Here, we investigated gene expression changes in the peripheral blood of PWH co-infected with RV. Only very few differentially expressed genes could be detected between PWH with and without RV infection, suggesting that the immune response to RV in PWH is strongly dampened. Our data provides important insights into the host response to RV infections in HIV patients.

State of the Field in Multi-Omics Research: From Computational Needs to Data Mining and Sharing

Multi-omics, variously called integrated omics, pan-omics, and trans-omics, aims to combine two or more omics data sets to aid in data analysis, visualization and interpretation to determine the mechanism of a biological process. Multi-omics efforts have taken center stage in biomedical research leading to the development of new insights into biological events and processes. However, the mushrooming of a myriad of tools, datasets, and approaches tends to inundate the literature and overwhelm researchers new to the field. The aims of this review are to provide an overview of the current state of the field, inform on available reliable resources, discuss the application of statistics and machine/deep learning in multi-omics analyses, discuss findable, accessible, interoperable, reusable (FAIR) research, and point to best practices in benchmarking. Thus, we provide guidance to interested users of the domain by addressing challenges of the underlying biology, giving an overview of the available toolset, addressing common pitfalls, and acknowledging current methods' limitations. We conclude with practical advice and recommendations on software engineering and reproducibility practices to share a comprehensive awareness with new researchers in multi-omics for end-to-end workflow.

Metabolic flux and transcriptome analyses provide insights into the mechanism underlying zinc sulfate improved β-1,3-D-glucan production by Aureobasidium pullulans

The effects of zinc sulfate at various concentrations on β-1,3-D-glucan (β-glucan) and pullulan production were investigated in flasks, and 0.1 g/L zinc sulfate was found to be the optimum concentration favoring increased β-glucan production. When batch culture of Aureobasidium pullulans CCTCC M 2012259 with 0.1 g/L zinc sulfate was carried out, the maximum dry biomass decreased by 16.9% while β-glucan production significantly increased by 120.5%, compared to results obtained from the control without zinc sulfate addition. To reveal the mechanism underlying zinc sulfate improved β-glucan production, both metabolic flux analysis and RNA-seq analysis were performed. The results indicated that zinc sulfate decreased carbon flux towards biomass formation and ATP supply, down-regulated genes associated with membrane part and cellular components organization, leading to a decrease in dry cell weight. However, zinc sulfate increased metabolic flux towards β-glucan biosynthesis, up-regulated genes related to glycan biosynthesis and nucleotide metabolism, resulting in improved β-glucan production. This study provides insights into the changes in the metabolism of A. pullulans in response to zinc sulfate, and can serve as a valuable reference of genetic information for improving the production of polysaccharides through metabolic engineering.

Deep transfer learning for reducing health care disparities arising from biomedical data inequality

As artificial intelligence (AI) is increasingly applied to biomedical research and clinical decisions, developing unbiased AI models that work equally well for all ethnic groups is of crucial importance to health disparity prevention and reduction. However, the biomedical data inequality between different ethnic groups is set to generate new health care disparities through data-driven, algorithm-based biomedical research and clinical decisions. Using an extensive set of machine learning experiments on cancer omics data, we find that current prevalent schemes of multiethnic machine learning are prone to generating significant model performance disparities between ethnic groups. We show that these performance disparities are caused by data inequality and data distribution discrepancies between ethnic groups. We also find that transfer learning can improve machine learning model performance for data-disadvantaged ethnic groups, and thus provides an effective approach to reduce health care disparities arising from data inequality among ethnic groups.

Analysis of Inflammatory and Homeostatic Roles of Tissue-resident Macrophages in the Progression of Cholesteatoma by RNA-Seq

BACKGROUND

Tissue-resident macrophages (TRMØs) can act as innate-immune sentinels to protect body against microbe invaders and stimulating materials such as cholesterol crystals in cholesteatoma, as well as to preserve tissue integrity by cleaning unwanted cellular debris.

METHODS

TRMØs in the incised middle ear tissues were obtained from the patients with cholesteatoma as an experimental group and the patients without cholesteatoma as a control group. Differential gene expression profiling of TRMØs was conducted between two groups by analyzing GO processes, KEGG and GSEA pathways of inflammation, tissue repair and homeostasis.

RESULTS

The current study showed that 145 of 7060 genes were significantly up-regulated (logFC>2 and FDR <0.05) when compared with the patients without cholesteatoma. GO process, GSEA and Cytoscape analysis of the over-expressed genes illustrated the boosted inflammatory and anti-infection functions of TRMØs existed neutrophil function, leukocyte migration, and adaptive immune response involved receptors and signaling pathways. Whereas the homeostasis and repair functions of TRMØs were affected from up-regulated genes, such as over-expressed keratin-13 that helped form the outer keratinising squamous epithelial layer, and over-expressed MMPs that activated the extracellular matrix molecules to promote inflammation and disturb tissue remodeling. Additionally, 74 down-regulated genes (logFC<-2 and FDR <0.05) also affected the homeostasis and repair functions by affecting extracelluar matrix structure and contractile fibres in TRMØs.

CONCLUSIONS

The cellular and molecular levels in cholesteatoma is attributable to chronic infection and several disturbed cellular biological processes involving cell integrity and tissue remodeling.

Power analysis for RNA-Seq differential expression studies using generalized linear mixed effects models

Background

Power analysis becomes an inevitable step in experimental design of current biomedical research. Complex designs allowing diverse correlation structures are commonly used in RNA-Seq experiments. However, the field currently lacks statistical methods to calculate sample size and estimate power for RNA-Seq differential expression studies using such designs. To fill the gap, simulation based methods have a great advantage by providing numerical solutions, since theoretical distributions of test statistics are typically unavailable for such designs.

Results

In this paper, we propose a novel simulation based procedure for power estimation of differential expression with the employment of generalized linear mixed effects models for correlated expression data. We also propose a new procedure for power estimation of differential expression with the use of a bivariate negative binomial distribution for paired designs. We compare the performance of both the likelihood ratio test and Wald test under a variety of simulation scenarios with the proposed procedures. The simulated distribution was used to estimate the null distribution of test statistics in order to achieve the desired false positive control and was compared to the asymptotic Chi-square distribution. In addition, we applied the procedure for paired designs to the TCGA breast cancer data set.

Conclusions

In summary, we provide a framework for power estimation of RNA-Seq differential expression under complex experimental designs. Simulation results demonstrate that both the proposed procedures properly control the false positive rate at the nominal level.

Reconstruction and Analysis of Cattle Metabolic Networks in Normal and Acidosis Rumen Tissue

Simple Summary

Economics of feedlot beef production dictate that beef cattle must gain weight at their maximum potential rate; this involves getting them quickly onto a full feed of high fermentable diet which can induce the ruminal acidosis disease. The molecular host mechanisms that occur as a response to the acidosis, are mostly unknown. For answering this question, the rumen epithelial transcriptome in acidosis and control fattening steers were obtained. By RNA sequencing we found the different expression profiles of genes in normal and acidosis induced steers. Then we constructed two metabolic networks for normal and acidosis tissue based on gene expression profile. Our results suggest that rapid shifts to diets rich in fermentable carbohydrates cause an increased concentration of ruminal volatile fatty acids (VFA) and toxins and significant changes in transcriptome profiles and metabolites of rumen epithelial tissue, with negative effects on economic consequences of poor performance and animal health.

Abstract

The objective of this study was to develop a system-level understanding of acidosis biology. Therefore, the genes expression differences between the normal and acidosis rumen epithelial tissues were first examined using the RNA-seq data in order to understand the molecular mechanisms involved in the disease and then their corresponding metabolic networks constructed. A number of 1074 genes, 978 isoforms, 1049 transcription start sites (TSS), 998 coding DNA sequence (CDS) and 2 promoters were identified being differentially expressed in the rumen tissue between the normal and acidosis samples (p < 0.05). The functional analysis of 627 up-regulated genes revealed their involvement in ion transmembrane transport, filament organization, regulation of cell adhesion, regulation of the actin cytoskeleton, ATP binding, glucose transmembrane transporter activity, carbohydrate binding, growth factor binding and cAMP metabolic process. Additionally, 111 differentially expressed enzymes were identified between the rumen epithelial tissue of the normal and acidosis steers with 46 up-regulated and 65 down-regulated ones in the acidosis group. The pathways and reactions analyses associated with the up-regulated enzymes indicate that most of these enzymes are involved in the fatty acid metabolism, biosynthesis of amino acids, pyruvate and carbon metabolism while most of the down-regulated ones are involved in purine and pyrimidine, vitamin B6 and antibiotics metabolisms. The degree distribution of both metabolic networks follows a power-law one, hence displaying a scale-free property. The top 15 hub metabolites were determined in the acidosis metabolic network with most of them involved in the fatty acid oxidation, VFA biosynthesis, amino acid biogenesis and glutathione metabolism which plays an important role in the stress condition. The limitations of this study were low number of animals and using only epithelial tissue (ventral sac) for RNA-seq.