RNAflow: An Effective and Simple RNA-Seq Differential Gene Expression Pipeline Using Nextflow

Network-based integration of omics, physiological and environmental data in real-world Elbe estuarine Zander

Coastal and estuarine environments are under endogenic and exogenic pressures jeopardizing survival and diversity of inhabiting biota. Information of possible synergistic effects of multiple (a)biotic stressors and holobiont interaction are largely missing in estuaries like the Elbe but are of importance to estimate unforeseen effects on animals' physiology. Here, we seek to leverage host-transcriptional RNA-seq and gill mucus microbial 16S rRNA metabarcoding data coupled with physiological and abiotic measurements in a network analysis approach to decipher the impact of multiple stressors on the health of juvenile Sander lucioperca along one of the largest European estuaries. We find mesohaline areas characterized by gill tissue specific transcriptional responses matching osmosensing and tissue remodeling. Liver transcriptomes instead emphasized that zander from highly turbid areas were undergoing starvation which was supported by compromised body condition. Potential pathogenic bacteria, including Shewanella, Acinetobacter, Aeromonas and Chryseobacterium, dominated the gill microbiome along the freshwater transition and oxygen minimum zone. Their occurrence coincided with a strong adaptive and innate transcriptional immune response in host gill and enhanced energy demand in liver tissue supporting their potential pathogenicity. Taken together, we show physiological responses of a fish species and its microbiome to abiotic factors whose impact is expected to increase with consequences of climate change. We further present a method for the close-meshed detection of the main stressors and bacterial species with disease potential in a highly productive ecosystem.

Assessing the impact of transcriptomics data analysis pipelines on downstream functional enrichment results

Transcriptomics is widely used to assess the state of biological systems. There are many tools for the different steps, such as normalization, differential expression, and enrichment. While numerous studies have examined the impact of method choices on differential expression results, little attention has been paid to their effects on further downstream functional analysis, which typically provides the basis for interpretation and follow-up experiments. To address this, we introduce FLOP, a comprehensive nextflow-based workflow combining methods to perform end-to-end analyses of transcriptomics data. We illustrate FLOP on datasets ranging from end-stage heart failure patients to cancer cell lines. We discovered effects not noticeable at the gene-level, and observed that not filtering the data had the highest impact on the correlation between pipelines in the gene set space. Moreover, we performed three benchmarks to evaluate the 12 pipelines included in FLOP, and confirmed that filtering is essential in scenarios of expected moderate-to-low biological signal. Overall, our results underscore the impact of carefully evaluating the consequences of the choice of preprocessing methods on downstream enrichment analyses. We envision FLOP as a valuable tool to measure the robustness of functional analyses, ultimately leading to more reliable and conclusive biological findings.

The Association between the JAK-STAT Pathway and Hypertension among Kenyan Women Diagnosed with Breast Cancer

Background

Breast cancer is the most common malignant tumor in women worldwide, and disproportionately affects Sub-Saharan Africa compared to high income countries. The global disease burden is growing, with Sub-Saharan Africa reporting majority of the cases. In Kenya, breast cancer is the most commonly diagnosed cancer, with an annual incidence of 7,243 new cases in 2022, representing 25.5% of all reported cancers in women. Evidence suggests that women receiving breast cancer treatment are at a greater risk of developing hypertension than women without breast cancer. Hypertension prevalence has been on the rise in SSA, with poor detection, treatment and control. The JAK-STAT signaling is activated in hormone receptor-positive breast tumors, leading to inflammation, cell proliferation, and treatment resistance in cancer cells. We sought to understand the association between the expression of JAK-STAT Pathway genes and hypertension among Kenyan women diagnosed with breast cancer.

Methods

Breast tumor and non-tumor tissues were acquired from patients with a pathologic diagnosis of invasive breast carcinoma. RNA was extracted from fresh frozen tumor and adjacent normal tissue samples of 23 participants who had at least 50% tumor after pathological examination, as well as their corresponding adjacent normal samples. Differentially expressed JAK-STAT genes between tumor and normal breast tissues were assessed using the DESEq2 R package. Pearson correlation was used to assess the correlation between differentially expressed JAK-STAT genes and participants' blood pressure, heart rate, and body mass index (BMI).

Results

11,868 genes were differentially expressed between breast tumor and non-tumor tissues. Eight JAK-STAT genes were significantly dysregulated (Log2FC ≥ 1.0 and an Padj ≤ 0.05), with two genes (CISH and SCNN1A) being upregulated. Six genes (TGFBR2, STAT5A, STAT5B, TGFRB3, SMAD9, and SOCS2) were downregulated. We identified STAT5A and SOCS2 genes to be significantly correlated with elevated systolic pressure and heart rate, respectively.

Conclusions

Our study provides insights underlying the molecular mechanisms of hypertension among Kenyan women diagnosed with breast cancer. Understanding these mechanisms may help develop targeted treatments that may improve health outcomes of Kenyan women diagnosed with breast cancer. Longitudinal studies with larger cohorts will be needed to validate our results.

MultiRNAflow: integrated analysis of temporal RNA-seq data with multiple biological conditions

MOTIVATION

The dynamic transcriptional mechanisms that govern eukaryotic cell function can now be analyzed by RNA sequencing. However, the packages currently available for the analysis of raw sequencing data do not provide automatic analysis of complex experimental designs with multiple biological conditions and multiple analysis time-points.

RESULTS

The MultiRNAflow suite combines several packages in a unified framework allowing exploratory and supervised statistical analyses of temporal data for multiple biological conditions.

AVAILABILITY AND IMPLEMENTATION

The R package MultiRNAflow is freely available on Bioconductor (https://bioconductor.org/packages/MultiRNAflow/), and the latest version of the source code is available on a GitHub repository (https://github.com/loubator/MultiRNAflow).

Challenges and best practices in omics benchmarking

Technological advances enabling massively parallel measurement of biological features - such as microarrays, high-throughput sequencing and mass spectrometry - have ushered in the omics era, now in its third decade. The resulting complex landscape of analytical methods has naturally fostered the growth of an omics benchmarking industry. Benchmarking refers to the process of objectively comparing and evaluating the performance of different computational or analytical techniques when processing and analysing large-scale biological data sets, such as transcriptomics, proteomics and metabolomics. With thousands of omics benchmarking studies published over the past 25 years, the field has matured to the point where the foundations of benchmarking have been established and well described. However, generating meaningful benchmarking data and properly evaluating performance in this complex domain remains challenging. In this Review, we highlight some common oversights and pitfalls in omics benchmarking. We also establish a methodology to bring the issues that can be addressed into focus and to be transparent about those that cannot: this takes the form of a spreadsheet template of guidelines for comprehensive reporting, intended to accompany publications. In addition, a survey of recent developments in benchmarking is provided as well as specific guidance for commonly encountered difficulties.

Validation of RNA Extraction Methods and Suitable Reference Genes for Gene Expression Studies in Developing Fetal Human Inner Ear Tissue

A comprehensive gene expression investigation requires high-quality RNA extraction, in sufficient amounts for real-time quantitative polymerase chain reaction and next-generation sequencing. In this work, we compared different RNA extraction methods and evaluated different reference genes for gene expression studies in the fetal human inner ear. We compared the RNA extracted from formalin-fixed paraffin-embedded tissue with fresh tissue stored at -80 °C in RNAlater solution and validated the expression stability of 12 reference genes (from gestational week 11 to 19). The RNA from fresh tissue in RNAlater resulted in higher amounts and a better quality of RNA than that from the paraffin-embedded tissue. The reference gene evaluation exhibited four stably expressed reference genes (B2M, HPRT1, GAPDH and GUSB). The selected reference genes were then used to examine the effect on the expression outcome of target genes (OTOF and TECTA), which are known to be regulated during inner ear development. The selected reference genes displayed no differences in the expression profile of OTOF and TECTA, which was confirmed by immunostaining. The results underline the importance of the choice of the RNA extraction method and reference genes used in gene expression studies.

RNA-Seq-Pop: Exploiting the sequence in RNA sequencing-A Snakemake workflow reveals patterns of insecticide resistance in the malaria vector Anopheles gambiae

We provide a reproducible and scalable Snakemake workflow, called RNA-Seq-Pop, which provides end-to-end analysis of RNA sequencing data sets. The workflow allows the user to perform quality control, perform differential expression analyses and call genomic variants. Additional options include the calculation of allele frequencies of variants of interest, summaries of genetic variation and population structure, and genome-wide selection scans, together with clear visualizations. RNA-Seq-Pop is applicable to any organism, and we demonstrate the utility of the workflow by investigating pyrethroid resistance in selected strains of the major malaria mosquito, Anopheles gambiae. The workflow provides additional modules specifically for An. gambiae, including estimating recent ancestry and determining the karyotype of common chromosomal inversions. The Busia laboratory colony used for selections was collected in Busia, Uganda, in November 2018. We performed a comparative analysis of three groups: a parental G24 Busia strain; its deltamethrin-selected G28 offspring; and the susceptible reference strain Kisumu. Measures of genetic diversity reveal patterns consistent with that of laboratory colonization and selection, with the parental Busia strain exhibiting the highest nucleotide diversity, followed by the selected Busia offspring, and finally, Kisumu. Differential expression and variant analyses reveal that the selected Busia colony exhibits a number of distinct mechanisms of pyrethroid resistance, including the Vgsc-995S target-site mutation, upregulation of SAP genes, P450s and a cluster of carboxylesterases. During deltamethrin selections, the 2La chromosomal inversion rose in frequency (from 33% to 86%), supporting a previous link with pyrethroid resistance. RNA-Seq-Pop is hosted at: github.com/sanjaynagi/rna-seq-pop. We anticipate that the workflow will provide a useful tool to facilitate reproducible, transcriptomic studies in An. gambiae and other taxa.

transXpress: a Snakemake pipeline for streamlined de novo transcriptome assembly and annotation

BACKGROUND

RNA-seq followed by de novo transcriptome assembly has been a transformative technique in biological research of non-model organisms, but the computational processing of RNA-seq data entails many different software tools. The complexity of these de novo transcriptomics workflows therefore presents a major barrier for researchers to adopt best-practice methods and up-to-date versions of software.

RESULTS

Here we present a streamlined and universal de novo transcriptome assembly and annotation pipeline, transXpress, implemented in Snakemake. transXpress supports two popular assembly programs, Trinity and rnaSPAdes, and allows parallel execution on heterogeneous cluster computing hardware.

CONCLUSIONS

transXpress simplifies the use of best-practice methods and up-to-date software for de novo transcriptome assembly, and produces standardized output files that can be mined using SequenceServer to facilitate rapid discovery of new genes and proteins in non-model organisms.

Transcriptome analysis of Sf9 insect cells during production of recombinant Adeno-associated virus

The insect cell-baculovirus expression vector system (IC-BEVS) has emerged as an alternative time- and cost-efficient production platform for recombinant Adeno-associated virus (AAV) for gene therapy. However, a better understanding of the underlying biological mechanisms of IC-BEVS is fundamental to further optimize this expression system toward increased product titer and quality. Here, gene expression of Sf9 insect cells producing recombinant AAV through a dual baculovirus expression system, with low multiplicity of infection (MOI), was profiled by RNA-seq. An 8-fold increase in reads mapping to either baculovirus or AAV transgene sequences was observed between 24 and 48 h post-infection (hpi), confirming a take-over of the host cell transcriptome by the baculovirus. A total of 336 and 4784 genes were identified as differentially expressed at 24 hpi (vs non-infected cells) and at 48 hpi (vs. infected cells at 24 hpi), respectively, including dronc, birc5/iap5, and prp1. Functional annotation found biological processes such as cell cycle, cell growth, protein folding, and cellular amino acid metabolic processes enriched along infection. This work uncovers transcriptional changes in Sf9 in response to baculovirus infection, which provide new insights into cell and/or metabolic engineering targets that can be leveraged for rational bioprocess engineering of IC-BEVS for AAV production.

Developing a non-invasive diagnostic model for pediatric Crohn's disease using RNA-seq analysis

Introduction: Pediatric Crohn's disease is a chronic inflammatory condition that affects the digestive system in children and adolescents. It is characterized by symptoms such as abdominal pain, diarrhea, weight loss, and malnutrition, and can also cause complications like growth delays and delayed puberty. However, diagnosing pediatric Crohn's disease can be difficult, especially when it comes to non-invasive methods. Methods: In this study, we developed a diagnostic model using RNA-seq to analyze gene expression in ileal biopsy samples from children with Crohn's disease and non-pediatric Crohn's controls. Results: Our results showed that pediatric Crohn's disease is associated with altered expression of genes involved in immune response, inflammation, and tissue repair. We validated our findings using two independent datasets from the Gene Expression Omnibus (GEO) database, as well as through one prospective independent dataset, and found that our model had a high accuracy rate. Discussion: These findings suggest the possibility of non-invasive diagnosis for pediatric Crohn's disease and may inform the development of targeted therapies for this condition.

Transcriptome profiling of osteoclast subsets associated with arthritis: A pathogenic role of CCR2hi osteoclast progenitors

Introduction

The existence of different osteoclast progenitor (OCP) subsets has been confirmed by numerous studies. However, pathological inflammation-induced osteoclastogenesis remains incompletely understood. Detailed characterization of OCP subsets may elucidate the pathophysiology of increased osteoclast activity causing periarticular and systemic bone resorption in arthritis. In our study, we rely on previously defined OCP subsets categorized by the level of CCR2 expression as circulatory-like committed CCR2^hi OCPs, which are substantially expanded in arthritis, and marrow-resident CCR2^lo OCPs of immature phenotype and behavior.

Methods

In order to perform transcriptome characterization of those subsets in the context of collagen-induced arthritis (CIA), we sorted CCR2^hi and CCR2^lo periarticular bone marrow OCPs of control and arthritic mice, and performed next-generation RNA sequencing (n=4 for each group) to evaluate the differential gene expression profile using gene set enrichment analysis with further validation.

Results

A disparity between CCR2^hi and CCR2^lo subset transcriptomes (863 genes) was detected, with the enrichment of pathways for osteoclast differentiation, chemokine and NOD-like receptor signaling in the CCR2^hi OCP subset, and ribosome biogenesis in eukaryotes and ribosome pathways in the CCR2^lo OCP subset. The effect of intervention (CIA) within each subset was greater in CCR2^hi (92 genes) than in CCR2^lo (43 genes) OCPs. Genes associated with the osteoclastogenic pathway (Fcgr1, Socs3), and several genes involved in cell adhesion and migration (F11r, Cd38, Lrg1) identified the CCR2^hi subset and distinguish CIA from control group, as validated by qPCR (n=6 for control mice, n=9 for CIA mice). The latter gene set showed a significant positive correlation with arthritis clinical score and frequency of CCR2^hi OCPs. Protein-level validation by flow cytometry showed increased proportion of OCPs expressing F11r/CD321, CD38 and Lrg1 in CIA, indicating that they could be used as disease markers. Moreover, osteoclast pathway-identifying genes remained similarly expressed (Fcgr1) or even induced by several fold (Socs3) in preosteoclasts differentiated in vitro from CIA mice compared to pre-cultured levels, suggesting their importance for enhanced osteoclastogenesis of the CCR2^hi OCPs in arthritis.

Conclusion

Our approach detected differentially expressed genes that could identify distinct subset of OCPs associated with arthritis as well as indicate possible therapeutic targets aimed to modulate osteoclast activity.

BAFFR activates PI3K/AKT signaling in human naive but not in switched memory B cells through direct interactions with B cell antigen receptors

Binding of BAFF to BAFFR activates in mature B cells PI3K/AKT signaling regulating protein synthesis, metabolic fitness, and survival. In humans, naive and memory B cells express the same levels of BAFFR, but only memory B cells seem to survive without BAFF. Here, we show that BAFF activates PI3K/AKT only in naive B cells and changes the expression of genes regulating migration, proliferation, growth, and survival. BAFF-induced PI3K/AKT activation requires direct interactions between BAFFR and the B cell antigen receptor (BCR) components CD79A and CD79B and is enhanced by the AKT coactivator TCL1A. Compared to memory B cells, naive B cells express more surface BCRs, which interact better with BAFFR than IgG or IgA, thus allowing stronger responses to BAFF. As ablation of BAFFR in naive and memory B cells causes cell death independent of BAFF-induced signaling, BAFFR seems to act also as an intrinsic factor for B cell survival.

Long-term exposure to environmental diclofenac concentrations impairs growth and induces molecular changes in Lymnaea stagnalis freshwater snails

As pharmaceutical substances are highly used in human and veterinary medicine and subsequently released in the environment, they represent emerging contaminants in the aquatic compartment. Diclofenac (DCF) is one of the most commonly detected pharmaceuticals in water and little research has been focused on its long-term effects on freshwater invertebrates. In this study, we assessed the chronic impacts of DCF on the freshwater gastropod Lymnaea stagnalis using life history, behavioral and molecular approaches. These organisms were exposed from the embryo to the adult stage to three environmentally relevant DCF concentrations (0.1, 2 and 10 μg/L). The results indicated that DCF impaired shell growth and feeding behavior at the juvenile stage, yet no impacts on hatching, locomotion and response to light stress were noted. The molecular findings (metabolomics and transcriptomic) suggested that DCF may disturb the immune system, energy metabolism, osmoregulation and redox balance. In addition, prostaglandin synthesis could potentially be inhibited by DCF exposure. The molecular findings revealed signs of reproduction impairment but this trend was not confirmed by the physiological tests. Combined omics tools provided complementary information and enabled us to gain further insight into DCF effects in freshwater organisms.