A comparison of transcriptome analysis methods with reference genome

Transcriptomic signatures of prostate cancer progression: a comprehensive RNA-seq study

Transcriptomics has been entirely transformed by RNA-sequencing (RNA-seq) due to its high sensitivity, accuracy, and precision. This study analyzed RNA-seq data to identify potential biomarkers for prostate cancer (PCa), a serious health issue among aging men. Despite several existing studies, biomarkers that effectively detect PCa or its prognosis have yet to be entirely determined. The differentially expressed genes (DEGs) that are critical and clinically informative were identified in PCa patient samples that had been progression stage categorized into medium risk (MR) and high risk (HR). A total of 174 DEGs were found to be shared between MR and HR samples. Functional enrichment analysis revealed their involvement in crucial biological processes, such as p53 signaling, mitotic nuclear division, and inflammation. To further examine their interactions, a Protein-Protein Interaction (PPI) network was constructed, where key genes, such as KIF20A, TPX2, BUB1, BIRC5, BUB1B, and MKI67, were found in significant modules, hubs, and motifs. Several transcription factors, including STAT5B, MYC, and SOX5 controlled these genes. Heatmap analysis indicates that the expression of the six crucial genes (KIF20A, TPX2, BUB1, BIRC5, BUB1B, and MKI67) increases with progression from benign state to medium-risk and high-risk states. Additionally, a nomogram model was constructed to predict the prognostic value of these biomarkers. Among the studied genes, BIRC5, MKI67, and KIF20A are suggested as potential prognostic biomarkers, while NIFK and PPP1CC are suggested as new therapeutic targets. These findings indicate that these biomarkers show considerable promise in improving early detection and prognosis of PCa.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-025-04297-3.

Multi-Omics Profiling of Lipid Variation and Regulatory Mechanisms in Poultry Breast Muscles

This study aimed to elucidate the genetic basis of lipid composition in the breast muscles of poultry, including AA broilers, dwarf guinea fowl, quails, and pigeons, and the impact of artificial selection on lipid traits. By employing lipidomics and transcriptomic sequencing, the research analyzed the chest muscle tissues of these four poultry. A total of 1542 lipid molecules were identified, with 711 showing significant differences among species. These lipids primarily belonged to subclasses such as TG, PC, Phosphatidylethanolamine (PE), Ceramides (Cer), and Diglyceride (DG), with each species demonstrating distinct profiles in these subclasses. Additionally, 5790 orthologous genes were identified, with 763, 767, 24, and 8 genes in AA broilers, dwarf guinea fowl, quails, and pigeons, respectively, exhibiting positive selection (Ka/Ks > 1). Notably, 114 genes related to lipid metabolism displayed significant differential expression, particularly between AA broilers and dwarf guinea fowl. The findings revealed that the metabolic pathways of PC and LPC lipid molecules in the glycerophospholipid pathway, as well as TG lipid molecules in the glycerolipid pathway, exhibited marked interspecies differences, potentially contributing to variations in breast muscle lipid composition. These results provide a solid foundation for understanding the lipid composition and molecular regulatory mechanisms in diverse poultry, offering valuable insights for further research in poultry lipid metabolism and artificial breeding programs.

Oocyte transcriptomes and follicular fluid proteomics of ovine atretic follicles reveal the underlying mechanisms of oocyte degeneration

BACKGROUND

In mammals, female fertility is influenced by the result of follicular development (ovulation or atresia). Follicular atresia is a complex physiological process that results in the degeneration of oocytes from the ovary. However, the molecular mechanisms of oocyte degeneration and key protein markers of follicular atresia remain unclear. In this study, we investigated the complex transcriptional regulatory mechanisms and protein profiles in oocytes and follicular fluid in atretic follicle stages using single-cell RNA sequencing and tandem mass tag proteomics.

RESULTS

First, through paired analysis of different follicle development stages, we identified 175 atresia-specific genes and eight candidate oocyte-secreted factors, including PKG1, YTHDF2, and MYC. Meanwhile, we also characterized unique features of the oocyte transcriptional landscape in the atretic follicle stage that displayed cell death-related transcriptional changes and mechanisms, such as autophagy (TBK1 and IRS4), necroptosis (PKR), and apoptosis (MARCKS). Moreover, we identified atresia-specific genes, namely FTH1, TF, and ACSL4, which may participate in regulation of oocyte ferroptosis in atretic follicles through a series of mechanisms including ferritinophagy, ferritin transport, and lipid metabolism. Additionally, we uncovered 333 differentially expressed proteins that may coordinate follicular atresia and revealed key pathways, such as negative regulation of angiogenesis, metabolic pathways, and transcription and mRNA splicing, that lead to oocyte degeneration. Finally, by combining transcriptome and proteomics analyses, we identified two oocyte-secreted biomarkers, PGK1 and ANGPT2, that may be associated with follicular atresia.

CONCLUSIONS

In conclusion, our work offers a thorough characterization of oocyte transcription mechanism and follicular fluid protein changes in ovine atretic follicles, which offers a crucial reference for analyzing the mechanism of follicular atresia and establishing an oocyte quality assessment system in sheep.

Comparison of baseline global gene expression profiles of prostate cancer cell lines LNCaP and DU145

INTRODUCTION

DU145 and LNCaP are classic prostate cancer cell lines. Characterizing their baseline transcriptomics profiles (without any intervention) can offer insights into baseline genetic features and oncogenic pathways that should be considered while interpreting findings after various experimental interventions such as exogenous gene transfection or drug treatment.

METHODS

LNCaP and DU145 cell lines were cultured under normal conditions, followed by RNA extraction, cDNA conversion, library preparation, and RNA sequencing using the Illumina NovaSeq platform. The sequences were analyzed to identify differentially expressed genes (DEGs) and for gene ontology (GO) and pathway enrichment.

RESULTS

A total of 3916 and 2301 genes were found to be differentially upregulated and downregulated between LNCaP and DU145 cell lines, respectively. The GO and pathway analysis of up-regulated DEGs indicated significant enrichment of genes involved in extracellular matrix organization and cell-substrate adhesion, while down-regulated genes are involved in epithelial cell migration, cell death regulation, and cell proliferation.

CONCLUSION

The results showed significant differences in baseline gene expression and cellular pathways that may account for the varying metastatic potentials between LNCaP and DU145 cell lines, which should be considered when interpreting findings after experimental interventions.

Response of young rice panicles to salt stress: insights based on phenotype and transcriptome analysis

Saline-alkali soils limit rice growth and production. With an increasing global population, enhancing rice salt tolerance is crucial for improving yields in these areas. This study investigated the developmental characteristics of young panicles and pollen fertility in two rice varieties, 58M and 58L, under salt stress. Results showed that 58M had more substantial salt tolerance during panicle development. RNA sequencing of 18 samples from both varieties under high salt stress (0 h, 6 h, and 24 h) identified 469 common differentially expressed genes (DEGs) and 2,308 DEGs between the varieties. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment highlighted significant pathways such as phenylpropanoid biosynthesis, protein processing, and flavonoid biosynthesis. Six gene co-expression modules related to salt tolerance were identified, with six candidate genes (LOC_Os05g38530, LOC_Os04g07920, LOC_Os12g02105, LOC_Os01g06580, LOC_Os06g49250, and LOC_Os06g48300) potentially linked to salt tolerance. These findings provide insights into rice salt tolerance mechanisms and offer new genetic resources for breeding salt-tolerant rice.

Time series analysis combined with transcriptome sequencing to explore characteristic genes and potential molecular mechanisms associated with ultrasound-guided microwave ablation of glioma

OBJECTIVE

This study aimed to explore marker genes and their potential molecular mechanisms involved in US-guided MWA for glioma in mice.

METHOD

The differentially expressed genes (DEGs1 and DEGs2) and lncRNAs (DELs1 and DELs2) were obtained between Non (glioma tissues without MWA) and T0 groups (0h after MWA), as well as between Non and T24 groups (24h after MWA). The down-regulation cluster genes (CONDOWNDEGs) and upregulation cluster genes (CONUPDEGs) were identified by time series analysis. Candidate genes were obtained by overlapping CONDOWNDEGs with downregulation DEGs (DOWNDEGs)1 and DOWNDEGs2, as well as CONUPDEGs with up-regulation DEGs (UPDEGs)1 and UPDEGs2. The expressions of immune checkpoints and inflammatory factors, gene set enrichment analysis (GSEA), and protein subcellular localization were performed. The eXpression2Kinases (X2K), GeneMANIA, transcription factor (TF), and competing endogenous (ce) RNA regulatory networks were conducted. The expression of marker genes was validated by quantitative real-time polymerase chain reaction (qRT-PCR).

RESULTS

Five marker genes (IL32, VCAM1, IL34, NFKB1 and CXCL13) were identified, which were connected with immune-related functions. Two immune checkpoints (CD96 and TIGIT) and six inflammatory factors played key roles in US-guided MWA for glioma. ceRNA regulatory networks revealed that miR-625-5p, miR-625-3p, miR-31-5p and miR-671-5p were associated with target genes. qRT-PCR indicated both IL32, VCAM1, and NFKB1 were potential markers under US-guided MWA-related time series analysis.

CONCLUSION

The use of US-guided MWA might be a practical method for influencing the function of target genes, regulating time frames to decrease inflammation, and stimulating immune responses in glioma therapy.

Where the "ruber" Meets the Road: Using the Genome of the Red Diamond Rattlesnake to Unravel the Evolutionary Processes Driving Venom Evolution

Understanding the proximate and ultimate causes of phenotypic variation is fundamental in evolutionary research, as such variation provides the substrate for selection to act upon. Although trait variation can arise due to selection, the importance of neutral processes is sometimes understudied. We presented the first reference-quality genome of the Red Diamond Rattlesnake (Crotalus ruber) and used range-wide 'omic data to estimate the degree to which neutral and adaptive evolutionary processes shaped venom evolution. We characterized population structure and found substantial genetic differentiation across two populations, each with distinct demographic histories. We identified significant differentiation in venom expression across age classes with substantially reduced but discernible differentiation across populations. We then used conditional redundancy analysis to test whether venom expression variation was best predicted by neutral divergence patterns or geographically variable (a)biotic factors. Snake size was the most significant predictor of venom variation, with environment, prey availability, and neutral sequence variation also identified as significant factors, though to a lesser degree. By directly including neutrality in the model, our results confidently highlight the predominant, yet not singular, role of life history in shaping venom evolution.

Integrating Large Language Models in Bioinformatics Education for Medical Students: Opportunities and Challenges

Large language models (LLMs) offer transformative opportunities in bioinformatics education for medical students by creating interactive experiences. The integration of LLMs enhances educational outcomes through providing accessible code templates, clarifying the function of coding elements, and assisting in error troubleshooting. Here, we demonstrate the practical applications of LLMs with a case study on transcriptome sequencing data processing, a vital component of medical research. However, the reliability of the content that LLMs generate requires rigorous validation. Ensuring the accuracy and appropriateness of the LLM-generated information requires integrating innovative LLMs with traditional educational methods to prepare medical students effectively for future challenges in bioinformatics.

RNA-sequencing revisited data shed new light on wooden breast myopathy

Wooden Breast (WB) abnormality represents one of the major challenges that the poultry industry has faced in the last 10 years. Despite the enormous progress in understanding the mechanisms underlying WB, the precise initial causes remain to be clarified. In this scenario, the present research is intended to characterize the gene expression profiles of broiler Pectoralis major muscles affected by WB, comparing them to the unaffected counterpart, to provide new insights into the biological mechanisms underlying this defect and potentially identifying novel genes likely involved in its occurrence. To this purpose, data obtained in a previous study through the RNA-sequencing technology have been used to identify differentially expressed genes (DEGs) between 6 affected and 5 unaffected broilers' breast muscles, by using the newest reference genome assembly for Gallus gallus (GRCg7b). Also, to deeply investigate molecular and biological pathways involved in the WB progression, pathways analyses have been performed. The results achieved through the differential gene expression analysis mainly evidenced the downregulation of glycogen metabolic processes, gluconeogenesis, and tricarboxylic acid cycle in WB muscles, thus corroborating the evidence of a dysregulated energy metabolism characterizing breasts affected by this abnormality. Also, genes related to hypertrophic muscle growth have been identified as differentially expressed (e.g., WFIKKN1). Together with that, a downregulation of genes involved in mitochondrial biogenesis and functionality has been detected. Among them, PPARGC1A and PPARGC1B chicken genes are particularly noteworthy. These genes not only have essential roles in regulating mitochondrial biogenesis but also play pivotal roles in maintaining glucose and energy homeostasis. In view of that, their downregulation in WB-affected muscle may be considered as potentially related to both the mitochondrial dysfunction and altered glucose metabolism in WB muscles, and their key involvement in the molecular alterations characterizing this muscular abnormality might be hypothesized.

Diverse genetic alteration dysregulates neuropeptide and intracellular signalling in the suprachiasmatic nuclei

In mammals, intrinsic 24 h or circadian rhythms are primarily generated by the suprachiasmatic nuclei (SCN). Rhythmic daily changes in the transcriptome and proteome of SCN cells are controlled by interlocking transcription-translation feedback loops (TTFLs) of core clock genes and their proteins. SCN cells function as autonomous circadian oscillators, which synchronize through intercellular neuropeptide signalling. Physiological and behavioural rhythms can be severely disrupted by genetic modification of a diverse range of genes and proteins in the SCN. With the advent of next generation sequencing, there is unprecedented information on the molecular profile of the SCN and how it is affected by genetically targeted alteration. However, whether the expression of some genes is more readily affected by genetic alteration of the SCN is unclear. Here, using publicly available datasets from recent RNA-seq assessments of the SCN from genetically altered and control mice, we evaluated whether there are commonalities in transcriptome dysregulation. This was completed for four different phases across the 24 h cycle and was augmented by Gene Ontology Molecular Function (GO:MF) and promoter analysis. Common differentially expressed genes (DEGs) and/or enriched GO:MF terms included signalling molecules, their receptors, and core clock components. Finally, examination of the JASPAR database indicated that E-box and CRE elements in the promoter regions of several commonly dysregulated genes. From this analysis, we identify differential expression of genes coding for molecules involved in SCN intra- and intercellular signalling as a potential cause of abnormal circadian rhythms.

Unique feather color characteristics and transcriptome analysis of hair follicles in Liancheng White ducks

Avian feather color is a fascinating trait, and the genetic mechanism of duck plumage formation is still in the preliminary stage. In this study, feather color of Liancheng White ducks was analyzed by determination of melanin content and RNA-seq analysis. In this research, 9 ducks from Mallards (n = 3), Liancheng White (n = 3) and Pekin ducks (n = 3) were used by high performance liquid chromatography (HPLC) and Masson-Fontana staining to reveal the difference of feather melanin content. RNA-seq from 11 hair follicle tissues (1- and 8-wk-old) of Liancheng White ducks (n = 5) and Pekin ducks (n = 7) was used to analyze the candidate genes for the feather melanin synthesis, and Immunofluorescence experiment was used to show the protein expression in 6 black- and white-feathered ducks. Pectorale, skin, liver, fat, brain, heart, kidney, lung, spleen of an 8-wk-old black-feathered Mallard were collected for candidate gene expression. The results showed that the contents of feathers, beak, web melanin in Liancheng White ducks were higher than in Pekin ducks (p < 0.05). Melanin within hair follicles was located in the barb ridge and hair matrix of black feather duck, also we found that TYRP1, TYR, SOX10 genes were differentially expressed between Liancheng White and Pekin ducks (p < 0.05), and these genes were mainly expressed showed in duck skin tissues. This study revealed the unique feather color phenotype of Liancheng White duck shedding light on the transcriptome that underlies it.

Adjuvant Effects of a CC Chemokine for Enhancing the Efficacy of an Inactivated Streptococcus agalactiae Vaccine in Nile Tilapia (Oreochromis niloticus)

In this study, the ability of a CC chemokine (On-CC1) adjuvant to enhance the efficacy of a formalin-killed Streptococcus agalactiae vaccine (WC) in inducing immune responses against S. agalactiae in Nile tilapia was investigated through immune-related gene expression analysis, enzyme-linked immunosorbent assay (ELISA), transcriptome sequencing, and challenge tests. Significantly higher S. agalactiae-specific IgM levels were detected in fish in the WC+CC group than in the WC alone or control groups at 8 days postvaccination (dpv). The WC vaccine group exhibited increased specific IgM levels at 15 dpv, comparable to those of the WC+CC group, with sustained higher levels observed in the latter group at 29 dpv and after challenge with S. agalactiae for 14 days. Immune-related gene expression analysis revealed upregulation of all target genes in the control group compared to those in the vaccinated groups, with notable differences between the WC and WC+CC groups at various time intervals. Additionally, transcriptome analysis revealed differential gene expression profiles between the vaccinated (24 and 96 hpv) and control groups, with notable upregulation of immune-related genes in the vaccinated fish. Differential gene expression (DGE) analysis revealed significant upregulation of immunoglobulin and other immune-related genes in the control group compared to those in the vaccinated groups (24 and 96 hpv), with distinct patterns observed between the WC and WC+CC vaccine groups. Finally, challenge with a virulent strain of S. agalactiae resulted in significantly higher survival rates for fish in the WC and WC+CC groups compared to fish in the control group, with a notable increase in survival observed in fish in the WC+CC group.

Blood gene expression biomarkers of response to anti-TNF drugs in pediatric inflammatory bowel diseases before initiation of treatment

BACKGROUND/AIMS

Changes in gene expression profiles among individuals with inflammatory bowel diseases (IBDs) could potentially influence the responsiveness to anti-TNF treatment. The aim of this study was to identify genes that could serve as predictors of early response to anti-TNF therapies in pediatric IBD patients prior to the initiation of treatment.

METHODS

We conducted a prospective, longitudinal, and multicenter study, enrolling 24 pediatric IBD patients aged less than 18 years who were initiating treatment with either infliximab or adalimumab. RNA-seq from blood samples was analyzed using the DESeq2 library by comparing responders and non-responders to anti-TNF drugs.

RESULTS

Bioinformatic analyses unveiled 102 differentially expressed genes, with 99 genes exhibiting higher expression in responders compared to non-responders prior to the initiation of anti-TNF therapy. Functional enrichment analyses highlighted defense response to Gram-negative bacteria (FDR = 2.3 ×10-7) as the most significant biological processes, and hemoglobin binding (FDR = 0.002), as the most significant molecular function. Gene Set Enrichment Analysis (GSEA) revealed notable enrichment in transcriptional misregulation in cancer (FDR = 0.016). Notably, 13 genes (CEACAM8, CEACAM6, CILP2, COL17A1, OLFM4, INHBA, LCN2, LTF, MMP8, DEFA4, PRTN3, AZU1, and ELANE) were selected for validation, and a consistent trend of increased expression in responders prior to drug administration was observed for most of these genes, with findings for 4 of them being statistically significant (CEACAM8, LCN2, LTF2, and PRTN3).

CONCLUSIONS

We identified 102 differentially expressed genes involved in the response to anti-TNF drugs in children with IBDs and validated CEACAM8, LCN2, LTF2, and PRTN3. Genes participating in defense response to Gram-negative bacterium, serine-type endopeptidase activity, and transcriptional misregulation in cancer are good candidates for anticipating the response to anti-TNF drugs in children with IBDs.

Oleanolic acid inhibits the tumor progression by regulating Lactobacillus through the cytokine-cytokine receptor interaction pathway in 4T1-induced mice breast cancer model

The therapeutic mechanism of oleanolic acid (OA) in breast cancer has been widely reported, but little has been known about the combined effects of transcriptome and gut microbiome. In this study, the phenotypic effect of oleanolic acid on mice was tested at the end of the administration cycle, and RNA sequencing on murine tumor tissue and 16S-rRNA sequencing on intestinal contents were conducted to analyze gene expression profiles and microbial diversity between the control group and OA treated group using 4T1-induced mice breast cancer model. As a result, it has been confirmed that oleanolic acid would play a significant inhibitory effect on the development of breast tumors in mice. Based on the integrative analysis of the transcriptomic and metagenomic data, it was found that the abundance of Lactobacillus in the intestinal flora of mice significantly increased in the OA group. Moreover, the up-regulation of Il10 had a significant effect on inhibiting the tumor progression, which played a role through cytokine-cytokine receptor interaction pathway.

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.

Technological advancements in viral vector designing and optimization for therapeutic applications

Viral vector engineering is critical to the advancement of several sectors of biotechnology, gene therapy, and vaccine development. These vectors were produced from viruses, were employed to deliver therapeutic genes or to alter biological processes. The potential for viral vectors to improve the precision, safety, and efficiency of therapeutic interventions has boosted their demand. The dynamic interplay between technological advancements and computational tools in establishing the landscape of viral vector engineering and vector optimization for therapeutic reasons is discussed in this chapter. It also emphasizes the importance of in silico techniques in maximizing vector potential for therapeutics and many phases of viral vector engineering, from genomic analysis to computer modelling and advancements to improve precise gene delivery. High-throughput screening propels the expedited process of vector selection, and computational techniques to analyze complex omics data to further enhance vector capabilities have been discussed. As in silico models reveal insights into off-target effects and integration sites, vector safety (biodistribution and toxicity) remains a crucial part and bridges the gap between preclinical and clinical investigations. Despite the limitations, this chapter depicts a future in which technology and computing merge to catapult viral vector therapy into an era of boundless possibilities.

Critical Differential Expression Assessment for Individual Bulk RNA-Seq Projects

Finding the right balance of quality and quantity can be important, and it is essential that project quality does not drop below the level where important main conclusions are missed or misstated. We use knock-out and over-expression studies as a simplification to test recovery of a known causal gene in RNA-Seq cell line experiments. When single-end RNA-Seq reads are aligned with STAR and quantified with htseq-count, we found potential value in testing the use of the Generalized Linear Model (GLM) implementation of edgeR with robust dispersion estimation more frequently for either single-variate or multi-variate 2-group comparisons (with the possibility of defining criteria less stringent than |fold-change| > 1.5 and FDR < 0.05). When considering a limited number of patient sample comparisons with larger sample size, there might be some decreased variability between methods (except for DESeq1). However, at the same time, the ranking of the gene identified using immunohistochemistry (for ER/PR/HER2 in breast cancer samples from The Cancer Genome Atlas) showed as possible shift in performance compared to the cell line comparisons, potentially highlighting utility for standard statistical tests and/or limma-based analysis with larger sample sizes. If this continues to be true in additional studies and comparisons, then that could be consistent with the possibility that it may be important to allocate time for potential methods troubleshooting for genomics projects. Analysis of public data presented in this study does not consider all experimental designs, and presentation of downstream analysis is limited. So, any estimate from this simplification would be an underestimation of the true need for some methods testing for every project. Additionally, this set of independent cell line experiments has a limitation in being able to determine the frequency of missing a highly important gene if the problem is rare (such as 10% or lower). For example, if there was an assumption that only one method can be tested for "initial" analysis, then it is not completely clear to the extent that using edgeR-robust might perform better than DESeq2 in the cell line experiments. Importantly, we do not wish to cause undue concern, and we believe that it should often be possible to define a gene expression differential expression workflow that is suitable for some purposes for many samples. Nevertheless, at the same time, we provide a variety of measures that we believe emphasize the need to critically assess every individual project and maximize confidence in published results.

Transcriptome software results show significant variation among different commercial pipelines

BACKGROUND

We have been documenting the biological responses to low levels of radiation (natural background) and very low level radiation (below background), and thus these studies are testing mild external stimuli to which we would expect relatively mild biological responses. We recently published a transcriptome software comparison study based on RNA-Seqs from a below background radiation treatment of two model organisms, E. coli and C. elegans (Thawng and Smith, BMC Genomics 23:452, 2022). We reported DNAstar-D (Deseq2 in the DNAstar software pipeline) to be the more conservative, realistic tool for differential gene expression compared to other transcriptome software packages (CLC, Partek and DNAstar-E (using edgeR). Here we report two follow-up studies (one with a new model organism, Aedes aegypti and another software package (Azenta) on transcriptome responses from varying dose rates using three different sources of natural radiation.

RESULTS

When E. coli was exposed to varying levels of K40, we again found that the DNAstar-D pipeline yielded a more conservative number of DEGs and a lower fold-difference than the CLC pipeline and DNAstar-E run in parallel. After a 30 read minimum cutoff criterion was applied to the data, the number of significant DEGs ranged from 0 to 81 with DNAstar-D, while the number of significant DEGs ranged from 4 to 117 and 14 to 139 using DNAstar-E and the CLC pipelines, respectively. In terms of the extent of expression, the highest foldchange DEG was observed in DNAstar-E with 19.7-fold followed by 12.5-fold in CLC and 4.3-fold in DNAstar-D. In a recently completed study with Ae. Aegypti and using another software package (Azenta), we analyzed the RNA-Seq response to similar sources of low-level radiation and again found the DNAstar-D pipeline to give the more conservative number and fold-expression of DEGs compared to other softwares. The number of significant DEGs ranged 31-221 in Azenta and 31 to 237 in CLC, 19-252 in DNAstar-E and 0-67 in DNAStar-D. The highest fold-change of DEGs were found in CLC (1,350.9-fold), with DNAstar-E (5.9 -fold) and Azenta (5.5-fold) intermediate, and the lowest levels of expression (4-fold) found in DNAstar-D.

CONCLUSIONS

This study once again highlights the importance of choosing appropriate software for transcriptome analysis. Using three different biological models (bacteria, nematode and mosquito) in four different studies testing very low levels of radiation (Van Voorhies et al., Front Public Health 8:581796, 2020; Thawng and Smith, BMC Genomics 23:452, 2022; current study), the CLC software package resulted in what appears to be an exaggerated gene expression response in terms of numbers of DEGs and extent of expression. Setting a 30-read cutoff diminishes this exaggerated response in most of the software tested. We have further affirmed that DNAstar-Deseq2 gives a more conservative transcriptome expression pattern which appears more suitable for studies expecting subtle gene expression patterns.

Sex differences of microglia in the healthy brain from embryonic development to adulthood and across lifestyle influences

Microglia, the central nervous system innate immune cells, play a critical role in maintaining a homeostatic environment in the brain throughout life. These cells exhibit an impressive range of functions and characteristics that help to ensure proper functioning of the brain. Notably, microglia can present differences in their genetic and physical traits, which can be influenced by a range of factors, including age, environmental exposures, disease, and sex. Remarkably, microglia have been found to express receptors for sex hormones, suggesting that these hormones may play a role in modulating microglial behavior and potentially contribute to sex differences. Additionally, sex-chromosomal factors were shown to impact microglial genetics and functioning. In this review, we will examine how microglial responses in homeostasis are impacted by their interaction with sex hormones and sex chromosomes. Specifically, our investigation will focus on examining this interaction from embryonic development to adulthood, and the influence of lifestyle elements on various microglial features, including density and distribution, morphology, transcriptome, and proteome.

BamQuery: a proteogenomic tool to explore the immunopeptidome and prioritize actionable tumor antigens

MHC-I-associated peptides deriving from non-coding genomic regions and mutations can generate tumor-specific antigens, including neoantigens. Quantifying tumor-specific antigens' RNA expression in malignant and benign tissues is critical for discriminating actionable targets. We present BamQuery, a tool attributing an exhaustive RNA expression to MHC-I-associated peptides of any origin from bulk and single-cell RNA-sequencing data. We show that many cryptic and mutated tumor-specific antigens can derive from multiple discrete genomic regions, abundantly expressed in normal tissues. BamQuery can also be used to predict MHC-I-associated peptides immunogenicity and identify actionable tumor-specific antigens de novo.

Differentially expressed transcripts of Tetracapsuloides bryosalmonae (Cnidaria) between carrier and dead-end hosts involved in key biological processes: novel insights from a coupled approach of FACS and RNA sequencing

Tetracapsuloides bryosalmonae is a malacosporean endoparasite that infects a wide range of salmonids and causes proliferative kidney disease (PKD). Brown trout serves as a carrier host whereas rainbow trout represents a dead-end host. We thus asked if the parasite adapts to the different hosts by changing molecular mechanisms. We used fluorescent activated cell sorting (FACS) to isolate parasites from the kidney of brown trout and rainbow trout following experimental infection with T. bryosalmonae. The sorted parasite cells were then subjected to RNA sequencing. By this approach, we identified 1120 parasite transcripts that were expressed differentially in parasites derived from brown trout and rainbow trout. We found elevated levels of transcripts related to cytoskeleton organisation, cell polarity, peptidyl-serine phosphorylation in parasites sorted from brown trout. In contrast, transcripts related to translation, ribonucleoprotein complex biogenesis and subunit organisation, non-membrane bounded organelle assembly, regulation of protein catabolic process and protein refolding were upregulated in rainbow trout-derived parasites. These findings show distinct molecular adaptations of parasites, which may underlie their distinct outcomes in the two hosts. Moreover, the identification of these differentially expressed transcripts may enable the identification of novel drug targets that may be exploited as treatment against T. bryosalmonae. We here also describe for the first time how FACS based isolation of T. bryosalmonae cells from infected kidney of fish fosters research and allows to define differentially expressed parasite transcripts in carrier and dead-end fish hosts.

Hematopoiesis and Mast Cell Development

Hematopoietic stem cells (HSCs) are defined based on their capacity to replenish themselves (self-renewal) and give rise to all mature hematopoietic cell types (multi-lineage differentiation) over their lifetime. HSCs are mainly distributed in the bone marrow during adult life, harboring HSC populations and a hierarchy of different kinds of cells contributing to the "niche" that supports HSC regulation, myelopoiesis, and lymphopoiesis. In addition, HSC-like progenitors, innate immune cell precursors such as macrophages, mast cells, natural killer cells, innate lymphoid cells, and megakaryocytes and erythrocyte progenitor cells are connected by a series of complex ontogenic relationships. The first source of mast cells is the extraembryonic yolk sac, on embryonic day 7. Mast cell progenitors circulate and enter peripheral tissues where they complete their differentiation. Embryonic mast cell populations are gradually replaced by definitive stem cell-derived progenitor cells. Thereafter, mast cells originate from the bone marrow, developing from the hematopoietic stem cells via multipotent progenitors, common myeloid progenitors, and granulocyte/monocyte progenitors. In this review article, we summarize the knowledge on mast cell sources, particularly focusing on the complex and multifaceted mechanisms intervening between the hematopoietic process and the development of mast cells.

Towards Understanding the Key Signature Pathways Associated from Differentially Expressed Gene Analysis in an Indian Prostate Cancer Cohort

Prostate cancer (PCa) is one of the most prevalent cancers among men in India. Although studies on PCa have dealt with genetics, genomics, and the environmental influence in the causality of PCa, not many studies employing the Next Generation Sequencing (NGS) approaches of PCa have been carried out. In our previous study, we identified some causal genes and mutations specific to Indian PCa using Whole Exome Sequencing (WES). In the recent past, with the help of different cancer consortiums such as The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC), along with differentially expressed genes (DEGs), many cancer-associated novel non-coding RNAs have been identified as biomarkers. In this work, we attempt to identify differentially expressed genes (DEGs) including long non-coding RNAs (lncRNAs) associated with signature pathways from an Indian PCa cohort using the RNA-sequencing (RNA-seq) approach. From a cohort of 60, we screened six patients who underwent prostatectomy; we performed whole transcriptome shotgun sequencing (WTSS)/RNA-sequencing to decipher the DEGs. We further normalized the read counts using fragments per kilobase of transcript per million mapped reads (FPKM) and analyzed the DEGs using a cohort of downstream regulatory tools, viz., GeneMANIA, Stringdb, Cytoscape-Cytohubba, and cbioportal, to map the inherent signatures associated with PCa. By comparing the RNA-seq data obtained from the pairs of normal and PCa tissue samples using our benchmarked in-house cuffdiff pipeline, we observed some important genes specific to PCa, such as STEAP2, APP, PMEPA1, PABPC1, NFE2L2, and HN1L, and some other important genes known to be involved in different cancer pathways, such as COL6A1, DOK5, STX6, BCAS1, BACE1, BACE2, LMOD1, SNX9, CTNND1, etc. We also identified a few novel lncRNAs such as LINC01440, SOX2OT, ENSG00000232855, ENSG00000287903, and ENST00000647843.1 that need to be characterized further. In comparison with publicly available datasets, we have identified characteristic DEGs and novel lncRNAs implicated in signature PCa pathways in an Indian PCa cohort which perhaps have not been reported. This has set a precedent for us to validate candidates further experimentally, and we firmly believe this will pave a way toward the discovery of biomarkers and the development of novel therapies.

Breeding honey bees (Apis mellifera L.) for low and high Varroa destructor population growth: Gene expression of bees performing grooming behavior

Introduction

Social organisms, including honey bees (Apis mellifera L.), have defense mechanisms to control the multiplication and transmission of parasites and pathogens within their colonies. Self-grooming, a mechanism of behavioral immunity, seems to contribute to restrain the population growth of the ectoparasitic mite Varroa destructor in honey bee colonies. Because V. destructor is the most damaging parasite of honey bees, breeding them for resistance against the mite is a high priority of the beekeeping industry.

Methods

A bidirectional breeding program to select honey bee colonies with low and high V. destructor population growth (LVG and HVG, respectively) was conducted. Having high and low lines of bees allowed the study of genetic mechanisms underlying self-grooming behavior between the extreme genotypes. Worker bees were classified into two categories: 'light groomers' and 'intense groomers'. The brains of bees from the different categories (LVG-intense, LVG-light, HVG-intense, and HVG-light) were used for gene expression and viral quantification analyses. Differentially expressed genes (DEGs) associated with the LVG and HVG lines were identified.

Results

Four odorant-binding proteins and a gustatory receptor were identified as differentially expressed genes. A functional enrichment analysis showed 19 enriched pathways from a list of 219 down-regulated DEGs in HVG bees, including the Kyoto Encyclopedia of Genes and Genomes (KEGG) term of oxidative phosphorylation. Additionally, bees from the LVG line showed lower levels of Apis rhabdovirus 1 and 2, Varroa destructor virus -1 (VDV-1/DWV-B), and Deformed wing virus-A (DWV-A) compared to bees of the HVG line. The difference in expression of odorant-binding protein genes and a gustatory receptor between bee lines suggests a possible link between them and the perception of irritants to trigger rapid self-grooming instances that require the activation of energy metabolic pathways.

Discussion

These results provide new insights on the molecular mechanisms involved in honey bee grooming behavior. Differences in viral levels in the brains of LVG and HVG bees showed the importance of investigating the pathogenicity and potential impacts of neurotropic viruses on behavioral immunity. The results of this study advance the understanding of a trait used for selective breeding, self-grooming, and the potential of using genomic assisted selection to improve breeding programs.

A field-wide assessment of differential expression profiling by high-throughput sequencing reveals widespread bias

We assess inferential quality in the field of differential expression profiling by high-throughput sequencing (HT-seq) based on analysis of datasets submitted from 2008 to 2020 to the NCBI GEO data repository. We take advantage of the parallel differential expression testing over thousands of genes, whereby each experiment leads to a large set of p-values, the distribution of which can indicate the validity of assumptions behind the test. From a well-behaved p-value set π0, the fraction of genes that are not differentially expressed can be estimated. We found that only 25% of experiments resulted in theoretically expected p-value histogram shapes, although there is a marked improvement over time. Uniform p-value histogram shapes, indicative of <100 actual effects, were extremely few. Furthermore, although many HT-seq workflows assume that most genes are not differentially expressed, 37% of experiments have π0-s of less than 0.5, as if most genes changed their expression level. Most HT-seq experiments have very small sample sizes and are expected to be underpowered. Nevertheless, the estimated π0-s do not have the expected association with N, suggesting widespread problems of experiments with controlling false discovery rate (FDR). Both the fractions of different p-value histogram types and the π0 values are strongly associated with the differential expression analysis program used by the original authors. While we could double the proportion of theoretically expected p-value distributions by removing low-count features from the analysis, this treatment did not remove the association with the analysis program. Taken together, our results indicate widespread bias in the differential expression profiling field and the unreliability of statistical methods used to analyze HT-seq data.

Transcriptome analysis of mulberry (Morus alba L.) leaves to identify differentially expressed genes associated with post-harvest shelf-life elongation

Present study deals with molecular expression patterns responsible for post-harvest shelf-life extension of mulberry leaves. Quantitative profiling showed retention of primary metabolite and accumulation of stress markers in NS7 and CO7 respectively. The leaf mRNA profiles was sequenced using the Illumina platform to identify DEGs. A total of 3413 DEGs were identified between the treatments. Annotation with Arabidopsis database has identified 1022 DEGs unigenes. STRING generated protein-protein interaction, identified 1013 DEGs nodes with p < 1.0e-16. KEGG classifier has identified genes and their participating biological processes. MCODE and BiNGO detected sub-networking and ontological enrichment, respectively at p ≤ 0.05. Genes associated with chloroplast architecture, photosynthesis, detoxifying ROS and RCS, and innate-immune response were significantly up-regulated, responsible for extending shelf-life in NS7. Loss of storage sucrose, enhanced activity of senescence-related hormones, accumulation of xenobiotics, and development of osmotic stress inside tissue system was the probable reason for tissue deterioration in CO7. qPCR validation of DEGs was in good agreement with RNA sequencing results, indicating the reliability of the sequencing platform. Present outcome provides a molecular insight regarding involvement of genes in self-life extension, which might help the sericulture industry to overcome their pre-existing problems related to landless farmers and larval feeding during monsoon.