Misuse of RPKM or TPM normalization when comparing across samples and sequencing protocols

Differential gene expression analysis pipelines and bioinformatic tools for the identification of specific biomarkers: A review

In recent years, the role of bioinformatics and computational biology together with omics techniques and transcriptomics has gained tremendous importance in biomedicine and healthcare, particularly for the identification of biomarkers for precision medicine and drug discovery. Differential gene expression (DGE) analysis is one of the most used techniques for RNA-sequencing (RNA-seq) data analysis. This tool, which is typically used in various RNA-seq data processing applications, allows the identification of differentially expressed genes across two or more sample sets. Functional enrichment analyses can then be performed to annotate and contextualize the resulting gene lists. These studies provide valuable information about disease-causing biological processes and can help in identifying molecular targets for novel therapies. This review focuses on differential gene expression (DGE) analysis pipelines and bioinformatic techniques commonly used to identify specific biomarkers and discuss the advantages and disadvantages of these techniques.

A UTP3-dependent nucleolar translocation pathway facilitates pre-rRNA 5'ETS processing

The ribosome small subunit (SSU) is assembled by the SSU processome which contains approximately 70 non-ribosomal protein factors. Whilst the biochemical mechanisms of the SSU processome in 18S rRNA processing and maturation have been extensively studied, how SSU processome components enter the nucleolus has yet to be systematically investigated. Here, in examining the nucleolar localization of 50 human SSU processome components, we found that UTP3, together with another 24 proteins, enter the nucleolus autonomously. For the remaining 25 proteins we found that UTP3/SAS10 assists the nucleolar localization of five proteins (MPP10, UTP25, EMG1 and the two UTP-B components UTP12 and UTP13), likely through its interaction with nuclear importin α. This 'ferrying' function of UTP3 was then confirmed as conserved in the zebrafish. We also found that knockdown of human UTP3 impairs cleavage at the A0-site while loss-of-function of either utp3/sas10 or utp13/tbl3 in zebrafish causes the accumulation of aberrantly processed 5'ETS products, which highlights the crucial role of UTP3 in mediating 5'ETS processing. Mechanistically, we found that UTP3 facilitates the degradation of processed 5'ETS by recruiting the RNA exosome component EXOSC10 to the nucleolus. These findings lay the groundwork for studying the mechanism of cytoplasm-to-nucleolus trafficking of SSU processome components.

Transcriptional dynamics of Fusarium pseudograminearum under high fungicide stress and the important role of FpZRA1 in fungal pathogenicity and DON toxin production

Fusarium pseudograminearum, the causal agent of Fusarium crown rot, poses a significant threat to cereal crops. Building upon our previous investigation of the transcriptional response of this pathogen to four key fungicides (carbendazim, phenamacril, pyraclostrobin, and tebuconazole), this study delves into the impact of elevated fungicide concentrations using RNA-seq. Global transcriptomic analysis and gene clustering revealed significant enrichment of genes involved in the ABC transporter pathway. Among these transporters, FPSE_06011 (FpZRA1), a conserved gene in eukaryotes, exhibited consistent upregulation at both low and high fungicide concentrations. Targeted deletion of FpZRA1 resulted in reduced sporulation, spore germination, and tolerance to cell wall stress, osmotic stress, and oxidative stress. Furthermore, the FpZRA1 knockout mutants exhibited decreased pathogenicity on wheat coleoptiles and reduced production of the mycotoxin deoxynivalenol (DON), as evidenced by the markedly down-regulated expression of TRI5, TRI6, and TRI10 in the RT-qPCR analysis. In summary, our findings highlight the impact of fungicide concentration on transcriptional reprogramming in F. pseudograminearum and identify FpZRA1 as a critical regulator of fungal development, stress tolerance, and pathogenicity.

Comparative Transcriptome Analysis Unveils Regulatory Factors Influencing Fatty Liver Development in Lion-Head Geese under High-Intake Feeding Compared to Normal Feeding

The lion-head goose is the only large goose species in China, and it is one of the largest goose species in the world. Lion-head geese have a strong tolerance for massive energy intake and show a priority of fat accumulation in liver tissue through special feeding. Therefore, the aim of this study was to investigate the impact of high feed intake compared to normal feeding conditions on the transcriptome changes associated with fatty liver development in lion-head geese. In this study, 20 healthy adult lion-head geese were randomly assigned to a control group (CONTROL, n = 10) and high-intake-fed group (CASE, n = 10). After 38 d of treatment, all geese were sacrificed, and liver samples were collected. Three geese were randomly selected from the CONTROL and CASE groups, respectively, to perform whole-transcriptome analysis to analyze the key regulatory genes. We identified 716 differentially expressed mRNAs, 145 differentially expressed circRNAs, and 39 differentially expressed lncRNAs, including upregulated and downregulated genes. GO enrichment analysis showed that these genes were significantly enriched in molecular function. The node degree analysis and centrality metrics of the mRNA-lncRNA-circRNA triple regulatory network indicate the presence of crucial functional nodes in the network. We identified differentially expressed genes, including HSPB9, Pgk1, Hsp70, ME2, malic enzyme, HSP90, FADS1, transferrin, FABP, PKM2, Serpin2, and PKS, and we additionally confirmed the accuracy of sequencing at the RNA level. In this study, we studied for the first time the important differential genes that regulate fatty liver in high-intake feeding of the lion-head goose. In summary, these differentially expressed genes may play important roles in fatty liver development in the lion-head goose, and the functions and mechanisms should be investigated in future studies.

Occlusion enhanced pan-cancer classification via deep learning

Quantitative measurement of RNA expression levels through RNA-Seq is an ideal replacement for conventional cancer diagnosis via microscope examination. Currently, cancer-related RNA-Seq studies focus on two aspects: classifying the status and tissue of origin of a sample and discovering marker genes. Existing studies typically identify marker genes by statistically comparing healthy and cancer samples. However, this approach overlooks marker genes with low expression level differences and may be influenced by experimental results. This paper introduces "GENESO," a novel framework for pan-cancer classification and marker gene discovery using the occlusion method in conjunction with deep learning. we first trained a baseline deep LSTM neural network capable of distinguishing the origins and statuses of samples utilizing RNA-Seq data. Then, we propose a novel marker gene discovery method called "Symmetrical Occlusion (SO)". It collaborates with the baseline LSTM network, mimicking the "gain of function" and "loss of function" of genes to evaluate their importance in pan-cancer classification quantitatively. By identifying the genes of utmost importance, we then isolate them to train new neural networks, resulting in higher-performance LSTM models that utilize only a reduced set of highly relevant genes. The baseline neural network achieves an impressive validation accuracy of 96.59% in pan-cancer classification. With the help of SO, the accuracy of the second network reaches 98.30%, while using 67% fewer genes. Notably, our method excels in identifying marker genes that are not differentially expressed. Moreover, we assessed the feasibility of our method using single-cell RNA-Seq data, employing known marker genes as a validation test.

Geneapp: A web application for visualizing alternative splicing for biomedicine

Alternative Splicing (AS) is an essential mechanism for eukaryotes. However, the consequences of deleting a single exon can be dramatic for the organism and can lead to cancer in humans. Additionally, alternative 5' and 3' splice sites, which define the boundaries of exons, also play key roles to human disorders. Therefore, Investigating AS events is crucial for understanding the molecular basis of human diseases and developing therapeutic strategies. Workflow for AS event analysis can be sampling followed by data analysis with bioinformatics to identify the different AS events in the control and case samples, data visualization for curation, and selection of relevant targets for experimental validation. The raw output of the analysis software does not favor the inspection of events by bioinformaticians requiring custom scripts for data visualization. In this work, we propose the Geneapp application with three modules: GeneappScript, GeneappServer, and GeneappExplorer. GeneappScript is a wrapper that assists in identifying AS in samples compared in two different approaches, while GeneappServer integrates data from AS analysis already performed by the user. In GeneappExplorer, the user visualizes the previous dataset by exploring AS events in genes with functional annotation. This targeted screens that Geneapp allows to perform helps in the identification of targets for experimental validation to confirm the hypotheses under study. The Geneapp is freely available for non-commercial use at https://geneapp.net to advance research on AS for bioinformatics.

BBSdb, an open resource for bacterial biofilm-associated proteins

Bacterial biofilms are organized heterogeneous assemblages of microbial cells encased within a self-produced matrix of exopolysaccharides, extracellular DNA and proteins. Over the last decade, more and more biofilm-associated proteins have been discovered and investigated. Furthermore, omics techniques such as transcriptomes, proteomes also play important roles in identifying new biofilm-associated genes or proteins. However, those important data have been uploaded separately to various databases, which creates obstacles for biofilm researchers to have a comprehensive access to these data. In this work, we constructed BBSdb, a state-of-the-art open resource of bacterial biofilm-associated protein. It includes 48 different bacteria species, 105 transcriptome datasets, 21 proteome datasets, 1205 experimental samples, 57,823 differentially expressed genes (DEGs), 13,605 differentially expressed proteins (DEPs), 1,930 'Top 5% differentially expressed genes', 444 'Threshold-based DEGs' and a predictor for prediction of biofilm-associated protein. In addition, 1,781 biofilm-associated proteins, including annotation and sequences, were extracted from 942 articles and public databases via text-mining analysis. We used E. coli as an example to represent how to explore potential biofilm-associated proteins in bacteria. We believe that this study will be of broad interest to researchers in field of bacteria, especially biofilms, which are involved in bacterial growth, pathogenicity, and drug resistance. Availability and implementation: The BBSdb is freely available at http://124.222.145.44/#!/.

Unveiling G-protein coupled receptors as potential targets for ovarian cancer nanomedicines: from RNA sequencing data analysis to in vitro validation

Genetic heterogeneity in ovarian cancer indicates the need for personalised treatment approaches. Currently, very few G-protein coupled receptors (GPCRs) have been investigated for active targeting with nanomedicines such as antibody-conjugated drugs and drug-loaded nanoparticles, highlighting a neglected potential to develop personalised treatment. To address the genetic heterogeneity of ovarian cancer, a future personalised approach could include the identification of unique GPCRs expressed in cancer biopsies, matched with personalised GPCR-targeted nanomedicines, for the delivery of lethal drugs to tumour tissue before, during and after surgery. Here we report on the systematic analysis of public ribonucleic acid-sequencing (RNA-seq) gene expression data, which led to prioritisation of 13 GPCRs as candidates with frequent overexpression in ovarian cancer tissues. Subsequently, primary ovarian cancer cells derived from ascites and ovarian cancer cell lines were used to confirm frequent gene expression for the selected GPCRs. However, the expression levels showed high variability within our selection of samples, therefore, supporting and emphasising the need for the future development of case-to-case personalised targeting approaches.

Community Composition and Functional Characterization of Microorganisms in Surface Sediment of the New Britain Trench

The deep-sea harbors abundant prokaryotic biomass is a major site of organic carbon remineralization and long-term carbon burial in the ocean. Deep-sea trenches are the deepest part of the ocean, and their special geological and morphological features promoting the accumulation of organic matter and active organic carbon turnover. Despite the expanding reports about the organic matter inputs, limited information is known regarding microbial processes in deep-sea trenches. In this study, we investigated the species composition and metabolic potential in surface sediment of the New Britain Trench (NBT), using a metagenomic approach. The predominant microbial taxa in NBT sediment include Proteobacteria, Acidobacteria, Planctomycetes, Actinobacteria and Chloroflexota. The microbial communities showed highly diverse metabolic potentials. Particularly, genes encoding enzymes for degradation of aromatic compounds, as well as those encoding haloalkane dehalogenase and haloacetate dehalogenase were annotated in the NBT surface sediment, which indicate the potential of microorganisms to degrade different types of refractory organic matter. The functional genes encoding enzymes for dissimilatory nitrate reduction, denitrification, and nitrification were also represented in the NBT metagenome. Overall, the microbial communities show high diversity of heterotrophic lineages and metabolic features, supporting their potential contributions in organic carbon metabolism. Meanwhile, Nitrosopumilus, a dominant genus in the surface sediment of the NBT, is a typical ammonia-oxidizing archaea (AOA), with autotrophic CO2 fixation pathways including the 3-hydroxypropionate/4-hydroxybutylate (3HP/4HB) cycle, the reductive TCA (rTCA) cycle. The results demonstrate that autotrophic metabolic processes also play an important role in the surface sediment, by providing newly synthesized organic matter.

Homoeologs in Allopolyploids: Navigating Redundancy as Both an Evolutionary Opportunity and a Technical Challenge-A Transcriptomics Perspective

Allopolyploidy in plants involves the merging of two or more distinct parental genomes into a single nucleus, a significant evolutionary process in the plant kingdom. Transcriptomic analysis provides invaluable insights into allopolyploid plants by elucidating the fate of duplicated genes, revealing evolutionary novelties and uncovering their environmental adaptations. By examining gene expression profiles, scientists can discern how duplicated genes have evolved to acquire new functions or regulatory roles. This process often leads to the development of novel traits and adaptive strategies that allopolyploid plants leverage to thrive in diverse ecological niches. Understanding these molecular mechanisms not only enhances our appreciation of the genetic complexity underlying allopolyploidy but also underscores their importance in agriculture and ecosystem resilience. However, transcriptome profiling is challenging due to genomic redundancy, which is further complicated by the presence of multiple chromosomes sets and the variations among homoeologs and allelic genes. Prior to transcriptome analysis, sub-genome phasing and homoeology inference are essential for obtaining a comprehensive view of gene expression. This review aims to clarify the terminology in this field, identify the most challenging aspects of transcriptome analysis, explain their inherent difficulties, and suggest reliable analytic strategies. Furthermore, bulk RNA-seq is highlighted as a primary method for studying allopolyploid gene expression, focusing on critical steps like read mapping and normalization in differential gene expression analysis. This approach effectively captures gene expression from both parental genomes, facilitating a comprehensive analysis of their combined profiles. Its sensitivity in detecting low-abundance transcripts allows for subtle differences between parental genomes to be identified, crucial for understanding regulatory dynamics and gene expression balance in allopolyploids.

Transcriptome analysis of CpGV in midguts of type II resistant codling moth larvae and identification of contaminant infections by SNP mapping of RNA-Seq data

Various isolates of the Cydia pomonella granulovirus (CpGV) are used as insect pest control agents against codling moth (CM, Cydia pomonella L.), a predominant pest in apple orchards. Three different types (I-III) of dominantly inherited field resistance of CM larvae to CpGV have been recently identified. In this study, transcription of virus genes in midgut cells of type II-resistant CM larvae infected with different CpGV isolates, i.e., CpGV-M and CpGV-S (both prone to type II resistance) as well as CpGV-E2 (breaking type II resistance) was determined by strand-specific RNA sequencing (RNA-Seq) at an early infection stage (72 h post infection). Based on principal component analysis of read counts and the quantitative distribution of single nucleotide polymorphisms (SNPs) in the RNA-Seq data, a bioinformatics analysis pipeline was developed for an a posteriori identification of the infective agents. We report that (i) identification of infective agent is crucial, especially in in vivo infection experiments, when activation of covert virus infections is a possibility, (ii) no substantial difference between CpGV-M and CpGV-S transcription was found in type II-resistant CM larvae despite a different resistance mechanism, (iii) the transcription level of CpGV-M and CpGV-S was much lower than that of CpGV-E2, and (iv) orf59 (sod), orf89 (pif-6), orf92 (p18), and orf137 (lef-10) were identified as significantly downregulated genes in resistance-prone isolates CpGV-M and CpGV-S. For type II resistance of CM larvae, we conclude that CpGV-M and CpGV-S are both able to enter midgut cells, but viral transcription is significantly impaired at an early stage of infection compared to the resistance-breaking isolate CpGV-E2.

IMPORTANCE

CpGV is a highly virulent pathogen of codling moth, and it has been developed into one of the most successful commercial baculovirus biocontrol agents for pome fruit production worldwide. The emergence of field resistance in codling moth to commercial CpGV products is a threat toward the sustainable use of CpGV. In recent years, different types of resistance (type I-III) were identified. For type II resistance, very little is known regarding the infection process. By studying the virus gene expression patterns of different CpGV isolates in midguts of type II-resistant codling moth larvae, we found that the type II resistance mechanism is most likely based on intracellular factors rather than a receptor component. By applying SNP mapping of the RNA-Seq data, we further emphasize the importance of identifying the infective agents in in vivo experiments when activation of a covert infection cannot be excluded.

Time-series metagenomics reveals changing protistan ecology of a temperate dimictic lake

BACKGROUND

Protists, single-celled eukaryotic organisms, are critical to food web ecology, contributing to primary productivity and connecting small bacteria and archaea to higher trophic levels. Lake Mendota is a large, eutrophic natural lake that is a Long-Term Ecological Research site and among the world's best-studied freshwater systems. Metagenomic samples have been collected and shotgun sequenced from Lake Mendota for the last 20 years. Here, we analyze this comprehensive time series to infer changes to the structure and function of the protistan community and to hypothesize about their interactions with bacteria.

RESULTS

Based on small subunit rRNA genes extracted from the metagenomes and metagenome-assembled genomes of microeukaryotes, we identify shifts in the eukaryotic phytoplankton community over time, which we predict to be a consequence of reduced zooplankton grazing pressures after the invasion of a invasive predator (the spiny water flea) to the lake. The metagenomic data also reveal the presence of the spiny water flea and the zebra mussel, a second invasive species to Lake Mendota, prior to their visual identification during routine monitoring. Furthermore, we use species co-occurrence and co-abundance analysis to connect the protistan community with bacterial taxa. Correlation analysis suggests that protists and bacteria may interact or respond similarly to environmental conditions. Cryptophytes declined in the second decade of the timeseries, while many alveolate groups (e.g., ciliates and dinoflagellates) and diatoms increased in abundance, changes that have implications for food web efficiency in Lake Mendota.

CONCLUSIONS

We demonstrate that metagenomic sequence-based community analysis can complement existing efforts to monitor protists in Lake Mendota based on microscopy-based count surveys. We observed patterns of seasonal abundance in microeukaryotes in Lake Mendota that corroborated expectations from other systems, including high abundance of cryptophytes in winter and diatoms in fall and spring, but with much higher resolution than previous surveys. Our study identified long-term changes in the abundance of eukaryotic microbes and provided context for the known establishment of an invasive species that catalyzes a trophic cascade involving protists. Our findings are important for decoding potential long-term consequences of human interventions, including invasive species introduction. Video Abstract.

Antennal transcriptome analysis reveals sensory receptors potentially associated with host detection in the livestock pest Lucilia cuprina

BACKGROUND

Lucilia cuprina (Wiedemann, 1830) (Diptera: Calliphoridae) is the main causative agent of flystrike of sheep in Australia and New Zealand. Female flies lay eggs in an open wound or natural orifice, and the developing larvae eat the host's tissues, a condition called myiasis. To improve our understanding of host-seeking behavior, we quantified gene expression in male and female antennae based on their behavior.

METHODS

A spatial olfactometer was used to evaluate the olfactory response of L. cuprina mated males and gravid females to fresh or rotting beef. Antennal RNA-Seq analysis was used to identify sensory receptors differentially expressed between groups.

RESULTS

Lucilia cuprina females were more attracted to rotten compared to fresh beef (> fivefold increase). However, males and some females did not respond to either type of beef. RNA-Seq analysis was performed on antennae dissected from attracted females, non-attracted females and males. Transcripts encoding sensory receptors from 11 gene families were identified above a threshold (≥ 5 transcript per million) including 49 ATP-binding cassette transporters (ABCs), two ammonium transporters (AMTs), 37 odorant receptors (ORs), 16 ionotropic receptors (IRs), 5 gustatory receptors (GRs), 22 odorant-binding proteins (OBPs), 9 CD36-sensory neuron membrane proteins (CD36/SNMPs), 4 chemosensory proteins (CSPs), 4 myeloid lipid-recognition (ML) and Niemann-Pick C2 disease proteins (ML/NPC2), 2 pickpocket receptors (PPKs) and 3 transient receptor potential channels (TRPs). Differential expression analyses identified sex-biased sensory receptors.

CONCLUSIONS

We identified sensory receptors that were differentially expressed between the antennae of both sexes and hence may be associated with host detection by female flies. The most promising for future investigations were as follows: an odorant receptor (LcupOR46) which is female-biased in L. cuprina and Cochliomyia hominivorax Coquerel, 1858; an ABC transporter (ABC G23.1) that was the sole sensory receptor upregulated in the antennae of females attracted to rotting beef compared to non-attracted females; a female-biased ammonia transporter (AMT_Rh50), which was previously associated with ammonium detection in Drosophila melanogaster Meigen, 1830. This is the first report suggesting a possible role for ABC transporters in L. cuprina olfaction and potentially in other insects.

Nutri-cereal tissue-specific transcriptome atlas during development: Functional integration of gene expression to identify mineral uptake pathways in little millet (Panicum sumatrense)

Little millet (Panicum sumatrense Roth ex Roem. & Schult.) is an essential minor millet of southeast Asia and Africa's temperate and subtropical regions. The plant is stress-tolerant, has a short life cycle, and has a mineral-rich nutritional profile associated with unique health benefits. We report the developmental gene expression atlas of little millet (genotype JK-8) from ten tissues representing different stages of its life cycle, starting from seed germination and vegetative growth to panicle maturation. The developmental transcriptome atlas led to the identification of 342 827 transcripts. The BUSCO analysis and comparison with the transcriptomes of related species confirm that this study presents high-quality, in-depth coverage of the little millet transcriptome. In addition, the eFP browser generated here has a user-friendly interface, allowing interactive visualizations of tissue-specific gene expression. Using these data, we identified transcripts, the orthologs of which in Arabidopsis and rice are involved in nutrient acquisition, transport, and response pathways. The comparative analysis of the expression levels of these transcripts holds great potential for enhancing the mineral content in crops, particularly zinc and iron, to address the issue of "hidden hunger" and to attain nutritional security, making it a valuable asset for translational research.

Species-specific duplicated FMRFaR-like gene A62 regulates spontaneous locomotion in Apolygus lucorum

BACKGROUND

Apolygus lucorum, a major cotton pest, has undergone a significant expansion of the FMRFaR gene within the GPCR superfamily, resulting in two classes of GPCR, namely FMRFaR (A54-55) and newly duplicated FMRFaR-like (A56-62). Notably, FMRFaR-like genes, particularly A62, show enhanced expression in the legs and wings of adults, indicating their potential role in locomotion. Employing A62 as a representative of FMRFaR-like, our study investigates the influence of FMRFa, FMRFaR, and FMRFaR-like on locomotion and development of A. lucorum.

RESULTS

FMRFaR and FMRFa exhibit comparable temporal and tissue expression patterns, whereas the FMRFaR-like genes within A. lucorum exhibit completely distinct evolutionary and expression patterns compared to classical FMRFaR. RNA interference (RNAi) experiments revealed that suppressing FMRFa expression results in complete lethality in A. lucorum, but neither FMRFaR nor A62 exhibit the same effect after RNAi. Suppressing the expression of FMRFa only decreases the expression of the A54 gene simultaneously, suggesting that A54 may function as a classical FMRFaR activated by FMRFa. RNAi of A62 leads to wing malformation and a significant reduction in spontaneous movement behavior in A. lucorum. Further transcriptomic analysis revealed that A62 affects the A. lucorum's movement behavior through energy metabolism pathways and motor protein pathways.

CONCLUSION

Our study unveils the unique and complex roles of FMRFa and its receptor in A. lucorum. These findings provide valuable insights into potential targets for pest control strategies aimed at managing A. lucorum populations in cotton fields. © 2024 Society of Chemical Industry.

Haplotype-resolved genomes of octoploid species in Phyllanthaceae family reveal a critical role for polyploidization and hybridization in speciation

The Phyllanthaceae family comprises a diverse range of plants with medicinal, edible, and ornamental value, extensively cultivated worldwide. Polyploid species commonly occur in Phyllanthaceae. Due to the rather complex genomes and evolutionary histories, their speciation process has been still lacking in research. In this study, we generated chromosome-scale haplotype-resolved genomes of two octoploid species (Phyllanthus emblica and Sauropus spatulifolius) in Phyllanthaceae family. Combined with our previously reported one tetraploid (Sauropus androgynus) and one diploid species (Phyllanthus cochinchinensis) from the same family, we explored their speciation history. The three polyploid species were all identified as allopolyploids with subgenome A/B. Each of their two distinct subgenome groups from various species was uncovered to independently share a common diploid ancestor (Ancestor-AA and Ancestor-BB). Via different evolutionary routes, comprising various scenarios of bifurcating divergence, allopolyploidization (hybrid polyploidization), and autopolyploidization, they finally evolved to the current tetraploid S. androgynus, and octoploid S. spatulifolius and P. emblica, respectively. We further discuss the variations in copy number of alleles and the potential impacts within the two octoploids. In addition, we also investigated the fluctuation of metabolites with medical values and identified the key factor in its biosynthesis process in octoploids species. Our study reconstructed the evolutionary history of these Phyllanthaceae species, highlighting the critical roles of polyploidization and hybridization in their speciation processes. The high-quality genomes of the two octoploid species provide valuable genomic resources for further research of evolution and functional genomics.

Comparative Gene Signature of Nociceptors Innervating Mouse Molar Teeth, Cranial Meninges, and Cornea

BACKGROUND

The trigeminal ganglion (TG) collects afferent sensory information from various tissues. Recent large-scale RNA sequencing of neurons of the TG and dorsal root ganglion has revealed a variety of functionally distinct neuronal subpopulations, but organ-specific information is lacking.

METHODS

To link transcriptomic and tissue-specific information, we labeled small-diameter neurons of 3 specific subpopulations of the TG by local application of lipophilic carbocyanine dyes to their innervation site in the dental pulp, cornea, and meninges (dura mater). We then collected mRNA-sequencing data from fluorescent neurons. Differentially expressed genes (DEGs) were analyzed and subjected to downstream gene set enrichment analysis (GSEA), and ion channel profiling was performed.

RESULTS

A total of 10,903 genes were mapped to the mouse genome (>500 reads). DEG analysis revealed 18 and 81 genes with differential expression (log 2 fold change > 2, Padj < .05) in primary afferent neurons innervating the dental pulp (dental primary afferent neurons [DPAN]) compared to those innervating the meninges (meningeal primary afferent neurons [MPAN]) and the cornea (corneal primary afferent neurons [CPAN]). We found 250 and 292 genes differentially expressed in MPAN as compared to DPAN and to CPAN, and 21 and 12 in CPAN as compared to DPAN and MPAN. Scn2b had the highest log 2 fold change when comparing DPAN versus MPAN and Mmp12 was the most prominent DEG when comparing DPAN versus CPAN and, CPAN versus MPAN. GSEA revealed genes of the immune and mitochondrial oxidative phosphorylation system for the DPAN versus MPAN comparison, cilium- and ribosome-related genes for the CPAN versus DPAN comparison, and respirasome, immune cell- and ribosome-related gene sets for the CPAN versus MPAN comparison. DEG analysis for ion channels revealed no significant differences between the neurons set except for the sodium voltage-gated channel beta subunit 2, Scn2b . However, in each tissue a few ion channels turned up with robust number of reads. In DPAN, these were Cacna1b , Trpv2 , Cnga4 , Hcn1 , and Hcn3 , in CPAN Trpa1 , Trpv1 , Cacna1a , and Kcnk13 and in MPAN Trpv2 and Scn11a .

CONCLUSIONS

Our study uncovers previously unknown differences in gene expression between sensory neuron subpopulations from the dental pulp, cornea, and dura mater and provides the basis for functional studies, including the investigation of ion channel function and their suitability as targets for tissue-specific analgesia.

Assessing RNA-Seq Workflow Methodologies Using Shannon Entropy

RNA-seq faces persistent challenges due to the ongoing, expanding array of data processing workflows, none of which have yet achieved standardization to date. It is imperative to determine which method most effectively preserves biological facts. Here, we used Shannon entropy as a tool for depicting the biological status of a system. Thus, we assessed the measurement of Shannon entropy by several RNA-seq workflow approaches, such as DESeq2 and edgeR, but also by combining nine normalization methods with log2 fold change on paired samples of TCGA RNA-seq representing datasets of 515 patients and spanning 12 different cancer types with 5-year overall survival rates ranging from 20% to 98%. Our analysis revealed that TPM, RLE, and TMM normalization, coupled with a threshold of log2 fold change ≥1, for identifying differentially expressed genes, yielded the best results. We propose that Shannon entropy can serve as an objective metric for refining the optimization of RNA-seq workflows and mRNA sequencing technologies.

Transcriptomic Analysis Reveals the Effect of Urea on Metabolism of Nannochloropsis oceanica

The eukaryotic microalga Nannochloropsis oceanica represents a promising bioresource for the production of biofuels and pharmaceuticals. Urea, a crucial nutrient for the photosynthetic N. oceanica, stimulates the accumulation of substances such as lipids, which influence growth and physiology. However, the specific mechanisms by which N. oceanica responds and adapts to urea addition remain unknown. High-throughput mRNA sequencing and differential gene expression analysis under control and urea-added conditions revealed significant metabolic changes. This involved the differential expression of 2104 genes, with 1354 being upregulated and 750 downregulated, resulting in the reprogramming of crucial pathways such as carbon and nitrogen metabolism, photosynthesis, and lipid metabolism. The results specifically showed that genes associated with photosynthesis in N. oceanica were significantly downregulated, particularly those related to light-harvesting proteins. Interestingly, urea absorption and transport may depend not only on specialized transport channels such as urease but also on alternative transport channels such as the ABC transporter family and the CLC protein family. In addition, urea caused specific changes in carbon and lipid metabolism. Genes associated with the Calvin cycle and carbon concentration mechanisms were significantly upregulated. In lipid metabolism, the expression of genes associated with lipases and polyunsaturated fatty acid synthesis was highly activated. Furthermore, the expression of several genes involved in the tricarboxylic acid cycle and folate metabolism was enhanced, making important contributions to energy supply and the synthesis and modification of genes and macromolecules. Our observations indicate that N. oceanica actively and dynamically regulates the redistribution of carbon and nitrogen after urea addition, providing references for further research on the effects of urea on N. oceanica.

De novo assembly of transcriptomes and differential gene expression analysis using short-read data from emerging model organisms - a brief guide

Many questions in biology benefit greatly from the use of a variety of model systems. High-throughput sequencing methods have been a triumph in the democratization of diverse model systems. They allow for the economical sequencing of an entire genome or transcriptome of interest, and with technical variations can even provide insight into genome organization and the expression and regulation of genes. The analysis and biological interpretation of such large datasets can present significant challenges that depend on the 'scientific status' of the model system. While high-quality genome and transcriptome references are readily available for well-established model systems, the establishment of such references for an emerging model system often requires extensive resources such as finances, expertise and computation capabilities. The de novo assembly of a transcriptome represents an excellent entry point for genetic and molecular studies in emerging model systems as it can efficiently assess gene content while also serving as a reference for differential gene expression studies. However, the process of de novo transcriptome assembly is non-trivial, and as a rule must be empirically optimized for every dataset. For the researcher working with an emerging model system, and with little to no experience with assembling and quantifying short-read data from the Illumina platform, these processes can be daunting. In this guide we outline the major challenges faced when establishing a reference transcriptome de novo and we provide advice on how to approach such an endeavor. We describe the major experimental and bioinformatic steps, provide some broad recommendations and cautions for the newcomer to de novo transcriptome assembly and differential gene expression analyses. Moreover, we provide an initial selection of tools that can assist in the journey from raw short-read data to assembled transcriptome and lists of differentially expressed genes.

Metagenomic profiles of the antimicrobial resistance in traditional Chinese fermented meat products: Core resistome and co-occurrence patterns

Antimicrobial resistance (AMR) poses a significant challenge to global health, and the presence of antibiotic resistance genes (ARGs) in food poses a potential threat to public health. Traditional Chinese fermented meat products (FMPs) are highly favored because of their unique flavors and cultural value. However, microbial safety and the potential distribution and composition of AMR in these products remain unclear. In this study, a comprehensive analysis of bacterial composition and antibiotic-resistant populations in 216 samples of traditional fermented meat products from different regions of China was conducted using a metagenomic approach. Staphylococcus was the most abundant genus in the samples, accounting for an average abundance of 29.9 %, followed by Tetragenococcus (17.1 %), and Latilactobacillus (3.6 %). A core resistome of FMP samples was constructed for the first time using co-occurrence network analysis, which revealed the distribution and interrelationships of ARGs and bio/metal-resistant genes (BMRGs). Random forest analysis identified the lincosamide nucleotidyltransferase lnuA and the multidrug and toxic compound extrusion (MATE) transporter abeM as potential indicators for assessing the overall abundance of the core resistome. Additionally, Staphylococcus, Acinetobacter, and Pseudomonas were identified as hosts constituting the core resistome. Despite their low abundance, the latter two still serve as major reservoirs of antibiotic resistance genes. Notably, Lactococcus cremoris was identified as the key host for tetracycline resistance genes in the samples, highlighting the need for enhanced resistance monitoring in lactic acid bacteria. Based on our findings, in the microbial safety assessment of fermented meat products, beyond common foodborne pathogens, attention should be focused on detecting and controlling coagulase-negative Staphylococcus, Acinetobacter, and Pseudomonas, and addressing bacterial resistance. The quantitative detection of lnuA and abeM could provide a convenient and rapid method for assessing the overall abundance of the core resistome. Our findings have important implications for the control of bacterial resistance and prevention of pathogenic bacteria in fermented meat products.

BrainTACO: an explorable multi-scale multi-modal brain transcriptomic and connectivity data resource

Exploring the relationships between genes and brain circuitry can be accelerated by joint analysis of heterogeneous datasets from 3D imaging data, anatomical data, as well as brain networks at varying scales, resolutions, and modalities. Generating an integrated view, beyond the individual resources' original purpose, requires the fusion of these data to a common space, and a visualization that bridges the gap across scales. However, despite ever expanding datasets, few platforms for integration and exploration of this heterogeneous data exist. To this end, we present the BrainTACO (Brain Transcriptomic And Connectivity Data) resource, a selection of heterogeneous, and multi-scale neurobiological data spatially mapped onto a common, hierarchical reference space, combined via a holistic data integration scheme. To access BrainTACO, we extended BrainTrawler, a web-based visual analytics framework for spatial neurobiological data, with comparative visualizations of multiple resources. This enables gene expression dissection of brain networks with, to the best of our knowledge, an unprecedented coverage and allows for the identification of potential genetic drivers of connectivity in both mice and humans that may contribute to the discovery of dysconnectivity phenotypes. Hence, BrainTACO reduces the need for time-consuming manual data aggregation often required for computational analyses in script-based toolboxes, and supports neuroscientists by directly leveraging the data instead of preparing it.

Rhizobia-diatom symbiosis fixes missing nitrogen in the ocean

Nitrogen (N2) fixation in oligotrophic surface waters is the main source of new nitrogen to the ocean1 and has a key role in fuelling the biological carbon pump2. Oceanic N2 fixation has been attributed almost exclusively to cyanobacteria, even though genes encoding nitrogenase, the enzyme that fixes N2 into ammonia, are widespread among marine bacteria and archaea3-5. Little is known about these non-cyanobacterial N2 fixers, and direct proof that they can fix nitrogen in the ocean has so far been lacking. Here we report the discovery of a non-cyanobacterial N2-fixing symbiont, 'Candidatus Tectiglobus diatomicola', which provides its diatom host with fixed nitrogen in return for photosynthetic carbon. The N2-fixing symbiont belongs to the order Rhizobiales and its association with a unicellular diatom expands the known hosts for this order beyond the well-known N2-fixing rhizobia-legume symbioses on land6. Our results show that the rhizobia-diatom symbioses can contribute as much fixed nitrogen as can cyanobacterial N2 fixers in the tropical North Atlantic, and that they might be responsible for N2 fixation in the vast regions of the ocean in which cyanobacteria are too rare to account for the measured rates.

Metagenomics reveals differences in the composition of bacterial antimicrobial resistance and antibiotic resistance genes in pasteurized yogurt and probiotic bacteria yogurt from China

Antimicrobial resistance has become a global public health concern, and antibiotic resistance genes (ARG) in food are a research focus. In China, probiotics and pasteurized yogurts are the 2 main types of commercially available yogurt, but the distribution and differences of antibiotic-resistant bacteria and gene types in these products are not well known. This study used a shotgun metagenomic approach to analyze 22 different types of yogurt collected from 9 main yogurt-producing areas in China; each type of yogurt included 8 different batches of samples. The abundance and diversity of bacteria identified in probiotic yogurt were significantly higher than those in pasteurized yogurt, with Acetobacter, Raoultella, and Burkholderia identified as unique and highly abundant genera in probiotic yogurt. Similarly, the abundance of Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp. was higher than that in pasteurized yogurt. A total of 1,149 ARG subtypes belonging to 16 ARG types were identified, with the highest abundance of rifampicin, multidrug efflux pumps, and quinolone resistance genes detected. Network analysis revealed significant nonrandom co-occurrence relationships between different types and subtypes of ARG in yogurt samples. A total of 44 ARG subtypes in pasteurized yogurt were potentially hosted by 36 bacterial genera, and in probiotic yogurt, 63 ARG were expected to be hosted by 86 bacterial species from 37 genera. These findings indicate potential safety issues in fermented dairy products and emphasize the need for a more hygienic environment when processing probiotic yogurt.

PvGeneExpDB: An integrative gene expression database for in-depth understanding on the Pacific white shrimp (Litopenaeus vannamei)

The Pacific white shrimp (Litopenaeus vannamei) is a high-valued economic farming species. With the development of high-throughput sequencing technology, cumulative large-scale transcriptomic studies have been revealing molecular landscape of various biological conditions including genetic selection, breeding, evolution, disease landscape, etc. However, no single experiment or databases allow thorough investigations of transcriptomic dynamics for these progressions. Meanwhile, the available datasets are often scattered and lack management. Here, we have established PvGeneExpDB, the first gene expression database for L. vannamei (www.bio-marine-scau.com/pv_ex/), which encompasses gene expression profiles, differential expression, and co-expression analyses under various biological conditions. Based on the analyses of 7 datasets, which include 53 samples with accurate and detailed records, PvGeneExpDB identifies 20,599 novel transcripts, shows expression profiles of a total of 20,817 genes, and implements Gene Ontology (GO) reconstruction of 76.7 % of these genes. Besides, 26 co-expressed groups were first identified by large-scale, cross-sample Weighted Gene Co-expression Network Analysis (WGCNA). By integrating the gene expression data in the database, our goal is to deepen the biological understanding of L. vannamei.

Machine learning-derived immunosenescence index for predicting outcome and drug sensitivity in patients with skin cutaneous melanoma

The functions of immunosenescence are closely related to skin cutaneous melanoma (SKCM). The aim of this study is to uncover the characteristics of immunosenescence index (ISI) to identify novel biomarkers and potential targets for treatment. Firstly, integrated bioinformatics analysis was carried out to identify risk prognostic genes, and their expression and prognostic value were evaluated. Then, we used the computational algorithm to estimate ISI. Finally, the distribution characteristics and clinical significance of ISI in SKCM by using multi-omics analysis. Patients with a lower ISI had a favorable survival rate, lower chromosomal instability, lower somatic copy-number alterations, lower somatic mutations, higher immune infiltration, and sensitive to immunotherapy. The ISI exhibited robust, which was validated in multiple datasets. Besides, the ISI is more effective than other published signatures in predicting survival outcomes for patients with SKCM. Single-cell analysis revealed higher ISI was specifically expressed in monocytes, and correlates with the differentiation fate of monocytes in SKCM. Besides, individuals exhibiting elevated ISI levels could potentially receive advantages from chemotherapy, and promising compounds with the potential to target high ISI were recognized. The ISI model is a valuable tool in categorizing SKCM patients based on their prognosis, gene mutation signatures, and response to immunotherapy.

Comparative transcriptome analysis of canola carrying a single vs stacked resistance genes against clubroot

Pyramiding resistance genes may expand the efficacy and scope of a canola variety against clubroot (Plasmodiophora brassicae), a serious threat to canola production in western Canada. However, the mechanism(s) of multigenic resistance, especially the potential interaction among clubroot resistance (CR) genes, are not well understood. In this study, transcriptome was compared over three canola (Brassica napus L.) inbred/hybrid lines carrying a single CR gene in chromosome A03 (CRaM, Line 16) or A08 (Crr1rutb, Line 20), and both genes (CRaM+Crr1rutb, Line 15) inoculated with a field population (L-G2) of P. brassicae pathotype X, a new variant found in western Canada recently. The line16 was susceptible, while lines 15 and 20 were partially resistant. Functional annotation identified differential expression of genes (DEGs) involved in biosynthetic processes responsive to stress and regulation of cellular process; The Venn diagram showed that the partially resistant lines 15 and 20 shared 1,896 differentially expressed genes relative to the susceptible line 16, and many of these DEGs are involved in defense responses, activation of innate immunity, hormone biosynthesis and programmed cell death. The transcription of genes involved in Pathogen-Associated Molecular Pattern (PAMP)-Triggered and Effector-Triggered Immunity (PTI and ETI) was particularly up-regulated, and the transcription level was higher in line 15 (CRaM + Crr1rutb) than in line 20 (Crr1rutb only) for most of the DEGs. These results indicated that the partial resistance to the pathotype X was likely conferred by the CR gene Crr1rutb for both lines 15 and 20 that functioned via the activation of both PTI and ETI signaling pathways. Additionally, these two CR genes might have synergistic effects against the pathotype X, based on the higher transcription levels of defense-related DEGs expressed by inoculated line 15, highlighting the benefit of gene stacking for improved canola resistance as opposed to a single CR gene alone.

A multi-omics approach for biomarker discovery in neuroblastoma: a network-based framework

Neuroblastoma (NB) is one of the leading causes of cancer-associated death in children. MYCN amplification is a prominent genetic marker for NB, and its targeting to halt NB progression is difficult to achieve. Therefore, an in-depth understanding of the molecular interactome of NB is needed to improve treatment outcomes. Analysis of NB multi-omics unravels valuable insight into the interplay between MYCN transcriptional and miRNA post-transcriptional modulation. Moreover, it aids in the identification of various miRNAs that participate in NB development and progression. This study proposes an integrated computational framework with three levels of high-throughput NB data (mRNA-seq, miRNA-seq, and methylation array). Similarity Network Fusion (SNF) and ranked SNF methods were utilized to identify essential genes and miRNAs. The specified genes included both miRNA-target genes and transcription factors (TFs). The interactions between TFs and miRNAs and between miRNAs and their target genes were retrieved where a regulatory network was developed. Finally, an interaction network-based analysis was performed to identify candidate biomarkers. The candidate biomarkers were further analyzed for their potential use in prognosis and diagnosis. The candidate biomarkers included three TFs and seven miRNAs. Four biomarkers have been previously studied and tested in NB, while the remaining identified biomarkers have known roles in other types of cancer. Although the specific molecular role is yet to be addressed, most identified biomarkers possess evidence of involvement in NB tumorigenesis. Analyzing cellular interactome to identify potential biomarkers is a promising approach that can contribute to optimizing efficient therapeutic regimens to target NB vulnerabilities.

Genome-wide profiles of DNA damage represent highly accurate predictors of mammalian age

The identification of novel age-related biomarkers represents an area of intense research interest. Despite multiple studies associating DNA damage with aging, there is a glaring paucity of DNA damage-based biomarkers of age, mainly due to the lack of precise methods for genome-wide surveys of different types of DNA damage. Recently, we developed two techniques for genome-wide mapping of the most prevalent types of DNA damage, single-strand breaks and abasic sites, with nucleotide-level resolution. Herein, we explored the potential of genomic patterns of DNA damage identified by these methods as a source of novel age-related biomarkers using mice as a model system. Strikingly, we found that models based on genomic patterns of either DNA lesion could accurately predict age with higher precision than the commonly used transcriptome analysis. Interestingly, the informative patterns were limited to relatively few genes and the DNA damage levels were positively or negatively correlated with age. These findings show that previously unexplored high-resolution genomic patterns of DNA damage contain useful information that can contribute significantly to both practical applications and basic science.

Machine learning unveils immune-related signature in multicenter glioma studies

In glioma molecular subtyping, existing biomarkers are limited, prompting the development of new ones. We present a multicenter study-derived consensus immune-related and prognostic gene signature (CIPS) using an optimal risk score model and 101 algorithms. CIPS, an independent risk factor, showed stable and powerful predictive performance for overall and progression-free survival, surpassing traditional clinical variables. The risk score correlated significantly with the immune microenvironment, indicating potential sensitivity to immunotherapy. High-risk groups exhibited distinct chemotherapy drug sensitivity. Seven signature genes, including IGFBP2 and TNFRSF12A, were validated by qRT-PCR, with higher expression in tumors and prognostic relevance. TNFRSF12A, upregulated in GBM, demonstrated inhibitory effects on glioma cell proliferation, migration, and invasion. CIPS emerges as a robust tool for enhancing individual glioma patient outcomes, while IGFBP2 and TNFRSF12A pose as promising tumor markers and therapeutic targets.

Anthocyanin gene enrichment in the distal region of cotton chromosome A07: mechanisms of reproductive organ coloration

Introduction

The biosynthesis of secondary metabolites like anthocyanins is often governed by metabolic gene clusters (MGCs) in the plant ancestral genome. However, the existence of gene clusters specifically regulating anthocyanin accumulation in certain organs is not well understood.

Methods and results

In this study, we identify MGCs linked to the coloration of cotton reproductive organs, such as petals, spots, and fibers. Through genetic analysis and map-based cloning, we pinpointed key genes on chromosome A07, such as PCC/GhTT19, which is involved in anthocyanin transport, and GbBM and GhTT2-3A, which are associated with the regulation of anthocyanin and proanthocyanidin biosynthesis. Our results demonstrate the coordinated control of anthocyanin and proanthocyanidin pathways, highlighting the evolutionary significance of MGCs in plant adaptation. The conservation of these clusters in cotton chromosome A07 across species underscores their importance in reproductive development and color variation. Our study sheds light on the complex biosynthesis and transport mechanisms for plant pigments, emphasizing the role of transcription factors and transport proteins in pigment accumulation.

Discussion

This research offers insights into the genetic basis of color variation in cotton reproductive organs and the potential of MGCs to enhance our comprehension of plant secondary metabolism.

Exploration of vitamin D metabolic activity-related biological effects and corresponding therapeutic targets in prostate cancer

BACKGROUND

Previous studies have unequivocally demonstrated that the vitamin D (VD) metabolism pathway significantly influences prognosis and sensitivity to hormone therapy in prostate cancer (PCa). However, the precise underlying mechanism remains unclear.

METHODS

We performed molecular profiling of 1045 PCa patients, leveraging genes linked to VD synthesis and VD receptors. We then identified highly variable gene modules with substantial associations with patient stratification. Subsequently, we intersected these modules with differentially expressed genes between PCa and adjacent paracancerous tissues. Following a meticulous process involving single-factor regression and LASSO regression to eliminate extraneous variables and construct a prognostic model. Within the high-risk subgroup defined by the calculated risk score, we analyzed their differences in cell infiltration, immune status, mutation landscape, and drug sensitivity. Finally, we selected Apolipoprotein E (APOE), which featured prominently in this model for further experimental exploration to evaluate its potential as a therapeutic target.

RESULTS

The prognostic model established in this study had commendable predictive efficacy. We observed diminished infiltration of various T-cell subtypes and reduced expression of co-stimulatory signals from antigen-presenting cells. Mutation analysis revealed that the high-risk cohort harbored a higher frequency of mutations in the TP53 and FOXA genes. Notably, drug sensitivity analysis suggested the heightened responsiveness of high-risk patients to molecular inhibitors targeting the Bcl-2 and MAPK pathways. Finally, our investigation also confirmed that APOE upregulates the proliferative and invasive capacity of PCa cells and concurrently enhances resistance to androgen receptor antagonist therapy.

CONCLUSION

This comprehensive study elucidated the potential mechanisms through which this metabolic pathway orchestrates the biological behavior of PCa and findings hold promise in advancing the development of combination therapies in PCa.

Metabolomic and Transcriptomic Correlative Analyses in Germ-Free Mice Link Lacticaseibacillus rhamnosus GG-Associated Metabolites to Host Intestinal Fatty Acid Metabolism and β-Oxidation

Intestinal microbiota confers susceptibility to diet-induced obesity, yet many probiotic species that synthesize tryptophan (trp) actually attenuate this effect, although the underlying mechanisms are unclear. We monocolonized germ-free mice with a widely consumed probiotic Lacticaseibacillus rhamnosus GG (LGG) under trp-free or -sufficient dietary conditions. We obtained untargeted metabolomics from the mouse feces and serum using liquid chromatography-mass spectrometry and obtained intestinal transcriptomic profiles via bulk-RNA sequencing. When comparing LGG-monocolonized mice with germ-free mice, we found a synergy between LGG and dietary trp in markedly promoting the transcriptome of fatty acid metabolism and β-oxidation. Upregulation was specific and was not observed in transcriptomes of trp-fed conventional mice and mice monocolonized with Ruminococcus gnavus. Metabolomics showed that fecal and serum metabolites were also modified by LGG-host-trp interaction. We developed an R-Script-based MEtabolome-TRanscriptome Correlation Analysis algorithm and uncovered LGG- and trp-dependent metabolites that were positively or negatively correlated with fatty acid metabolism and β-oxidation gene networks. This high-throughput metabolome-transcriptome correlation strategy can be used in similar investigations to reveal potential interactions between specific metabolites and functional or disease-related transcriptomic networks.

Multilevel analysis between Physcomitrium patens and Mortierellaceae endophytes explores potential long-standing interaction among land plants and fungi

The model moss species Physcomitrium patens has long been used for studying divergence of land plants spanning from bryophytes to angiosperms. In addition to its phylogenetic relationships, the limited number of differential tissues, and comparable morphology to the earliest embryophytes provide a system to represent basic plant architecture. Based on plant-fungal interactions today, it is hypothesized these kingdoms have a long-standing relationship, predating plant terrestrialization. Mortierellaceae have origins diverging from other land fungi paralleling bryophyte divergence, are related to arbuscular mycorrhizal fungi but are free-living, observed to interact with plants, and can be found in moss microbiomes globally. Due to their parallel origins, we assess here how two Mortierellaceae species, Linnemannia elongata and Benniella erionia, interact with P. patens in coculture. We also assess how Mollicute-related or Burkholderia-related endobacterial symbionts (MRE or BRE) of these fungi impact plant response. Coculture interactions are investigated through high-throughput phenomics, microscopy, RNA-sequencing, differential expression profiling, gene ontology enrichment, and comparisons among 99 other P. patens transcriptomic studies. Here we present new high-throughput approaches for measuring P. patens growth, identify novel expression of over 800 genes that are not expressed on traditional agar media, identify subtle interactions between P. patens and Mortierellaceae, and observe changes to plant-fungal interactions dependent on whether MRE or BRE are present. Our study provides insights into how plants and fungal partners may have interacted based on their communications observed today as well as identifying L. elongata and B. erionia as modern fungal endophytes with P. patens.

Divergence in toxin antigenicity and venom enzymes in Tityus melici, a medically important scorpion, despite transcriptomic and phylogenetic affinities with problematic Brazilian species

The Brazilian scorpion Tityus melici, native to Minas Gerais and Bahia, is morphologically related to Tityus serrulatus, the most medically significant species in Brazil. Despite inhabiting scorpion-envenomation endemic regions, T. melici venom remains unexplored. This work evaluates T. melici venom composition and function using transcriptomics, enzymatic activities, and in vivo and in vitro immunological analyses. Next-Generation Sequencing unveiled 86 components putatively involved in venom toxicity: 39 toxins, 28 metalloproteases, seven disulfide isomerases, six hyaluronidases, three phospholipases and three amidating enzymes. T. serrulatus showed the highest number of toxin matches with 80-100 % sequence similarity. T. melici is of medical importance as it has a venom LD50 of 0.85 mg/kg in mice. We demonstrated venom phospholipase A2 activity, and elevated hyaluronidase and metalloprotease activities compared to T. serrulatus, paralleling our transcriptomic findings. Comparison of transcriptional levels for T. serrulatus and T. melici venom metalloenzymes suggests species-specific expression patterns in Tityus. Despite close phylogenetic association with T. serrulatus inferred from COI sequences and toxin similarities, partial neutralization of T. melici venom toxicity was achieved when using the anti-T. serrulatus antivenom, implying antigenic divergence among their toxins. We suggest that the Brazilian therapeutic scorpion antivenom could be improved to effectively neutralize T. melici venom.

Blood and cerebellar abundance of ATXN3 splice variants in spinocerebellar ataxia type 3/Machado-Joseph disease

Spinocerebellar ataxia type 3 (SCA3)/Machado-Joseph disease (MJD) is a heritable proteinopathy disorder, whose causative gene, ATXN3, undergoes alternative splicing. Ataxin-3 protein isoforms differ in their toxicity, suggesting that certain ATXN3 splice variants may be crucial in driving the selective toxicity in SCA3. Using RNA-seq datasets we identified and determined the abundance of annotated ATXN3 transcripts in blood (n = 60) and cerebellum (n = 12) of SCA3 subjects and controls. The reference transcript (ATXN3-251), translating into an ataxin-3 isoform harbouring three ubiquitin-interacting motifs (UIMs), showed the highest abundance in blood, while the most abundant transcript in the cerebellum (ATXN3-208) was of unclear function. Noteworthy, two of the four transcripts that encode full-length ataxin-3 isoforms but differ in the C-terminus were strongly related with tissue expression specificity: ATXN3-251 (3UIM) was expressed in blood 50-fold more than in the cerebellum, whereas ATXN3-214 (2UIM) was expressed in the cerebellum 20-fold more than in the blood. These findings shed light on ATXN3 alternative splicing, aiding in the comprehension of SCA3 pathogenesis and providing guidance in the design of future ATXN3 mRNA-lowering therapies.

RNA processing modification mediated subtypes illustrate the distinctive features of tumor microenvironment in hepatocellular carcinoma

Multiple transcript isoforms of genes can be formed by processing and modifying the 5' and 3' ends of RNA. Herein, the aim of this study is to uncover the characteristics of RNA processing modification (RPM) in hepatocellular carcinoma (HCC), and to identify novel biomarkers and potential targets for treatment. Firstly, integrated bioinformatics analysis was carried out to identify risk prognostic RPM regulators (RPMRs). Then, we used these RPMRs to identify subtypes of HCC and explore differences in immune microenvironment and cellular function improvement pathways between the sub-types. Finally, we used the principal component analysis algorithms to estimate RPMscore, which were applied to 5 cohorts. Lower RPMscore among patients correlated with a declined survival rate, increased immune infiltration, and raised expression of immune checkpoints, aligning with the "immunity tidal model theory". The RPMscore exhibited robust, which was validated in multiple datasets. Mechanistically, low RPMscore can create an immunosuppressive microenvironment in HCC by manipulating tumor-associated macrophages. Preclinically, patients with high RPMscore might benefit from immunotherapy. The RPMscore is helpful in clustering HCC patients with distinct prognosis and immunotherapy. Our RPMscore model can help clinicians to select personalized therapy for HCC patients, and RPMscore may act a part in the development of HCC.

Quantifying transcriptome diversity: a review

Following the central dogma of molecular biology, gene expression heterogeneity can aid in predicting and explaining the wide variety of protein products, functions and, ultimately, heterogeneity in phenotypes. There is currently overlapping terminology used to describe the types of diversity in gene expression profiles, and overlooking these nuances can misrepresent important biological information. Here, we describe transcriptome diversity as a measure of the heterogeneity in (1) the expression of all genes within a sample or a single gene across samples in a population (gene-level diversity) or (2) the isoform-specific expression of a given gene (isoform-level diversity). We first overview modulators and quantification of transcriptome diversity at the gene level. Then, we discuss the role alternative splicing plays in driving transcript isoform-level diversity and how it can be quantified. Additionally, we overview computational resources for calculating gene-level and isoform-level diversity for high-throughput sequencing data. Finally, we discuss future applications of transcriptome diversity. This review provides a comprehensive overview of how gene expression diversity arises, and how measuring it determines a more complete picture of heterogeneity across proteins, cells, tissues, organisms and species.

Exploring ecological effects of arsenic and cadmium combined exposure on cropland soil: from multilevel organisms to soil functioning by multi-omics coupled with high-throughput quantitative PCR

Arsenic (As) and cadmium (Cd) pose potential ecological threats to cropland soils; however, few studies have investigated their combined effects on multilevel organisms and soil functioning. Here, we used collembolans and soil microbiota as test organisms to examine their responses to soil As and Cd co-contamination at the gene, individual, and community levels, respectively, and further uncovered ecological relationships between pollutants, multilevel organisms, and soil functioning. At the gene level, collembolan transcriptome revealed that elevated As concentrations stimulated As-detoxifying genes AS3MT and GST, whereas the concurrent Cd restrained GST gene expression. At the individual level, collembolan reproduction was sensitive to pollutants while collembolan survival wasn't. At the community level, significant but inconsistent correlations were observed between the biodiversity of different soil keystone microbial clusters and soil As levels. Moreover, soil functioning related to nutrient (e.g., carbon, nitrogen, phosphorus, and sulfur) cycles was inhibited under As and Cd co-exposure only through the mediation of plant pathogens. Overall, these findings suggested multilevel bioindicators (i.e., AS3MT gene expression in collembolans, collembolan reproduction, and biodiversity of soil keystone microbial clusters) in cropland soils co-contaminated with As and Cd, thus improving the understanding of the ecotoxicological impact of heavy metal co-contamination on soil ecosystems.

(Re-)Viewing Role of Intracellular Glucose Beyond Extracellular Regulation of Glucose-Stimulated Insulin Secretion by Pancreatic Cells

For glucose-stimulated insulin secretion (GSIS) by pancreatic β-cells in animals, it is believed that ATP generated from glucose metabolism is primarily responsible. However, this ignores two well-established aspects in literature: (a) intracellular ATP generation from other sources resulting in an overall pool of ATP, regardless of the original source, and (b) that intracellular glucose transport is 10- to 100-fold higher than intracellular glucose phosphorylation in β-cells. The latter especially provides an earlier unaddressed, but highly appealing, observation pertaining to (at least transient) the presence of intracellular glucose molecules. Could these intracellular glucose molecules be responsible for the specificity of GSIS to glucose (instead of the widely believed ATP production from its metabolism)? In this work, we provide a comprehensive compilation of literature on glucose and GSIS using various cellular systems - all studies focus only on the extracellular role of glucose in GSIS. Further, we carried out a comprehensive analysis of differential gene expression in Mouse Insulinoma 6 (MIN6) cells, exposed to low and high extracellular glucose concentrations (EGC), from the existing whole transcriptome data. The expression of other genes involved in glycolysis, Krebs cycle, and electron transport chain was found to be unaffected by EGC, except Gapdh, Atp6v0a4, and Cox20. Remarkably, 3 upregulated genes (Atp6v0a4, Cacnb4, Kif11) in high EGC were identified to have an association with cellular secretion. Using glucose as a possible ligand for the 3 proteins, computational investigations were carried out (that will require future 'wet validation', both in vitro and in vivo, e.g., using primary islets and animal models). The glucose-affinity/binding scores (in kcal/mol) obtained were also compared with glucose binding scores for positive controls (GCK and GLUT2), along with negative controls (RPA1, KU70-80, POLA1, ACAA1A, POLR1A). The binding affinity scores of glucose molecules for the 3 proteins were found to be closer to positive controls. Therefore, we report the glucose binding ability of 3 secretion-related proteins and a possible direct role of intracellular glucose molecules in GSIS.

Differentially expressed genes of RNA-seq data are suggested on the intersections of normalization techniques

Data normalization is the critical step for the RNA-seq data analysis. Several techniques are suggested for the normalization of transcript reads in the samples. In this study, the differentially expressed genes (DEGs) are generated from the TCGA normalized laryngeal cancer data obtained using the TPM, FPKM, and DESeq2 techniques. The results showed that the reports of DEGs were different based on the normalization techniques. We suggested that the DEG intersections obtain the top transcripts from the normalized data in support of the pathway enrichment process.

Biomineralization in a cold environment: Insights from shield compositions and transcriptomics of polar sternaspids (Sternaspidae, Polychaeta)

The survival and physiological functions of polar marine organisms are impacted by global climate changes. Investigation of the adaptation mechanisms underlying biomineralization in polar organisms at low temperatures is important for understanding mineralized organismal sensitivity to climate change. Here, we performed electron probe analysis on the shields of Antarctic polychaete Sternaspis sendalli and Arctic polychaete Sternaspis buzhinskajae (Sternaspidae), and sequenced the transcriptomes of the tissues surrounding shields to examine biomineral characteristics and adaptive mechanisms in persistently cold environments. Compared to the temperate relative species, the relative abundance of iron, phosphorus, calcium, magnesium, nitrogen, sulfur and silicon in two polar sternaspid shields was similar to Sternaspis chinensis. However, the diversity and expression levels of biomineralization-related shell matrix proteins differed between the polar and temperate species, suggesting distinct molecular mechanisms underlying shield formation in cold environments. Tubulin and cyclophilin were upregulated compared to the temperate species. Furthermore, 42 positively selected genes were identified in Antarctic S. sendalli, with functions in cytoskeletal structure, DNA repair, immunity, transcription, translation, protein synthesis, and lipid metabolism. Highly expressed genes in both polar species were associated with cytoskeleton, macromolecular complexes and cellular component biosynthesis. Overall, this study reveals conserved elemental composition yet distinct biomineralization processes in the shields of polar sternaspids. The unique expression of biomineralization related genes and other cold-adaptation related genes provide molecular insights into biomineralization in cold marine environments.

Population-specific responses to developmental temperature in the arboviral vector Aedes albopictus: Implications for climate change

The increase of environmental temperature due to current global warming is not only favouring the expansion of the distribution range of many insect species, but it is also changing their phenology. Insect phenology is tightly linked to developmental timing, which is regulated by environmental temperatures. However, the degree to which the effects of developmental temperatures extend across developmental stages and their inter-stage relationships have not been thoroughly quantified in mosquitoes. Here, we used the mosquito Aedes albopictus, which is an aggressive invasive species and an arboviral vector, to study how developmental temperature influences fitness across developmental stages, thermal traits, energy reserves, transcriptome and Wolbachia prevalence in laboratory-reared populations originally collected from either temperate or tropical regions. We show that hatchability, larval and pupal viability and developmental speed are strongly influenced by temperature, and these effects extend to wing length, body mass, longevity and content of water, protein and lipids in adults in a population-specific manner. On the contrary, neither adult thermal preference nor heat resistance significantly change with temperature. Wolbachia density was generally lower in adult mosquitoes reared at 18°C than at other tested temperatures, and transcriptome analysis showed enrichment for functions linked to stress responses (i.e. cuticle proteins and chitin, cytochrome p450 and heat shock proteins) in mosquitoes reared at both 18 and 32°C. Our data showed an overall reduced vector fitness performance when mosquitoes were reared at 32°C, and the absence of isomorphy in the relationship between developmental stages and temperature in the laboratory population deriving from larvae collected in northern Italy. Altogether, these results have important implications for reliable model projections of the invasion potentials of Ae. albopictus and its epidemiological impact.

Blocking miR528 function promotes tillering and regrowth in switchgrass

MiRNAs have been reported to be the key regulators involving a wide range of biological processes in diverse plant species, but their functions in switchgrass, an important biofuel and forage crop, are largely unknown. Here, we reported the novel function of miR528, which has expanded to four copies in switchgrass, in controlling biomass trait of tillering number and regrowth rate after mowing. Blocking miR528 activity by expressing short tandem target mimic (STTM) increased tiller number and regrowth rate after mowing. The quadruple pvmir528 mutant lines derived from genome editing also showed such improved traits. Degradome and RNA-seq analysis, combined with in situ hybridization assay revealed that up-regulation of two miR528 targets coding for Cu/Zn-SOD enzymes, might be responsible for the improved traits of tillering and regrowth in pvmir528 mutant. Additionally, natural variations in the miR528-SOD interaction exist in C3 and C4 monocot species, implying the distinct regulatory strength of the miR528-SOD module during monocot evolution. Overall, our data illuminated a novel role of miR528 in controlling biomass traits and provided a new target for genetic manipulation-mediated crop improvement.

Subtelomeric plasticity contributes to gene family expansion in the human parasitic flatworm Schistosoma mansoni

BACKGROUND

The genomic region that lies between the telomere and chromosome body, termed the subtelomere, is heterochromatic, repeat-rich, and frequently undergoes rearrangement. Within this region, large-scale structural changes enable gene diversification, and, as such, large multicopy gene families are often found at the subtelomere. In some parasites, genes associated with proliferation, invasion, and survival are often found in these regions, where they benefit from the subtelomere's highly plastic, rapidly changing nature. The increasing availability of complete (or near complete) parasite genomes provides an opportunity to investigate these typically poorly defined and overlooked genomic regions and potentially reveal relevant gene families necessary for the parasite's lifestyle.

RESULTS

Using the latest chromosome-scale genome assembly and hallmark repeat richness observed at chromosome termini, we have identified and characterised the subtelomeres of Schistosoma mansoni, a metazoan parasitic flatworm that infects over 250 million people worldwide. Approximately 12% of the S. mansoni genome is classified as subtelomeric, and, in line with other organisms, we find these regions to be gene-poor but rich in transposable elements. We find that S. mansoni subtelomeres have undergone extensive interchromosomal recombination and that these sites disproportionately contribute to the 2.3% of the genome derived from segmental duplications. This recombination has led to the expansion of subtelomeric gene clusters containing 103 genes, including the immunomodulatory annexins and other gene families with unknown roles. The largest of these is a 49-copy plexin domain-containing protein cluster, exclusively expressed in the tegument-the tissue located at the host-parasite physical interface-of intramolluscan life stages.

CONCLUSIONS

We propose that subtelomeric regions act as a genomic playground for trial-and-error of gene duplication and subsequent divergence. Owing to the importance of subtelomeric genes in other parasites, gene families implicated in this subtelomeric expansion within S. mansoni warrant further characterisation for a potential role in parasitism.

Wolfberry genome database: integrated genomic datasets for studying molecular biology

Wolfberry, also known as goji berry or Lycium barbarum, is a highly valued fruit with significant health benefits and nutritional value. For more efficient and comprehensive usage of published L. barbarum genomic data, we established the Wolfberry database. The utility of the Wolfberry Genome Database (WGDB) is highlighted through the Genome browser, which enables the user to explore the L. barbarum genome, browse specific chromosomes, and access gene sequences. Gene annotation features provide comprehensive information about gene functions, locations, expression profiles, pathway involvement, protein domains, and regulatory transcription factors. The transcriptome feature allows the user to explore gene expression patterns using transcripts per kilobase million (TPM) and fragments per kilobase per million mapped reads (FPKM) metrics. The Metabolism pathway page provides insights into metabolic pathways and the involvement of the selected genes. In addition to the database content, we also introduce six analysis tools developed for the WGDB. These tools offer functionalities for gene function prediction, nucleotide and amino acid BLAST analysis, protein domain analysis, GO annotation, and gene expression pattern analysis. The WGDB is freely accessible at https://cosbi7.ee.ncku.edu.tw/Wolfberry/. Overall, WGDB serves as a valuable resource for researchers interested in the genomics and transcriptomics of L. barbarum. Its user-friendly web interface and comprehensive data facilitate the exploration of gene functions, regulatory mechanisms, and metabolic pathways, ultimately contributing to a deeper understanding of wolfberry and its potential applications in agronomy and nutrition.

Integration of bulk RNA sequencing to reveal protein arginine methylation regulators have a good prognostic value in immunotherapy to treat lung adenocarcinoma

Background

Given the differential expression and biological functions of protein arginine methylation (PAM) regulators in lung adenocarcinoma (LUAD), it may be of great value in the diagnosis, prognosis, and treatment of LUAD. However, the expression and function of PAM regulators in LUAD and its relationship with prognosis are unclear.

Methods

8 datasets including 1798 LUAD patients were selected. During the bioinformatic study in LUAD, we performed (i) consensus clustering to identify clusters based on 9 PAM regulators related expression profile data, (ii) to identify hub genes between the 2 clusters, (iii) principal component analysis to construct a PAM.score based on above genes, and (iv) evaluation of the effect of PAM.score on the deconstruction of tumor microenvironment and guidance of immunotherapy.

Results

We identified two different clusters and a robust and clinically practicable prognostic scoring system. Meanwhile, a higher PAM.score subgroup showed poorer prognosis, and was validated by multiple cohorts. Its prognostic effect was validated by ROC (Receiver operating characteristic curve) curve and found to have a relatively good prediction efficacy. High PAM.score group exhibited lower immune score, which associated with an immunosuppressive microenvironment in LUAD. Finally, patients exhibiting a lower PAM.score presented noteworthy therapeutic benefits and clinical advantages.

Conclusion

Our PAM.score model can help clinicians to select personalized therapy for LUAD patients, and PAM.score may act a part in the development of LUAD.

LncRNA 220, a newly discovered long non-conding RNA inhibiting apoptosis and autophagy in Kupffer cells in LPS-induced endotoxemic mice through the XBP1u-PI3K-AKT pathway

Sepsis is recognized as a potentially fatal condition characterized by acute organ dysfunction resulting from an imbalanced immune response to infection. Acute liver injury (ALI) arises as an inflammatory outcome of immune response dysregulation associated with sepsis. Kupffer cells, which are liver-specific macrophages, are known to have a significant impact on ALI, although the precise regulatory mechanism remains unclear. Numerous studies have showcased the regulatory impact of long non-coding RNAs (lncRNAs) on the progression of diverse ailments, yet their precise regulatory mechanisms remain predominantly unexplored. In this study, a novel long non-coding RNA (lncRNA), referred to as lncRNA 220, was discovered using high-throughput sequencing. The expression of lncRNA 220 was found to be significantly elevated in the livers of mice with lipopolysaccharide (LPS)-induced endotoxemia, specifically during the 8-hour time period. Furthermore, in Kupffer cells treated with LPS, lncRNA 220 was observed to inhibit apoptosis and autophagy by activating the PI3K-AKT-mTORC1 pathway. This effect was achieved through the reduction of X-box protein 1 unspliced (Xbp1u) mRNA stability and suppression of its translation in the context of endoplasmic reticulum stress (ERS). Ultimately, this intervention mitigated the progression of LPS-induced ALI. To summarize, our study establishes lncRNA 220 as a newly identified regulator that suppresses apoptosis and autophagy in Kupffer cells subjected to LPS treatment, indicating its potential as a molecular target for ALI in endotoxemic mice.

Proteotransciptomics of the Most Popular Host Sea Anemone Entacmaea quadricolor Reveals Not All Toxin Genes Expressed by Tentacles Are Recruited into Its Venom Arsenal

While the unique symbiotic relationship between anemonefishes and sea anemones is iconic, it is still not fully understood how anemonefishes can withstand and thrive within the venomous environment of their host sea anemone. In this study, we used a proteotranscriptomics approach to elucidate the proteinaceous toxin repertoire from the most common host sea anemone, Entacmaea quadricolor. Although 1251 different toxin or toxin-like RNA transcripts were expressed in E. quadricolor tentacles (0.05% of gene clusters, 1.8% of expression) and 5375 proteins were detected in milked venom, only 4% of proteins detected in venom were putative toxins (230), and they only represent on average 14% of the normalised protein expression in the milked venom samples. Thus, most proteins in milked venom do not appear to have a toxin function. This work raises the perils of defining a dominant venom phenotype based on transcriptomics data alone in sea anemones, as we found that the dominant venom phenotype differs between the transcriptome and proteome abundance data. E. quadricolor venom contains a mixture of toxin-like proteins of unknown and known function. A newly identified toxin protein family, Z3, rich in conserved cysteines of unknown function, was the most abundant at the RNA transcript and protein levels. The venom was also rich in toxins from the Protease S1, Kunitz-type and PLA2 toxin protein families and contains toxins from eight venom categories. Exploring the intricate venom toxin components in other host sea anemones will be crucial for improving our understanding of how anemonefish adapt to the venomous environment.

Impact of biochar on the antibiotic resistome and associated microbial functions in rhizosphere and bulk soil in water-saving and flooding irrigated paddy fields

The addition of biochar in paddies under the condition of water-saving irrigation can simultaneously achieve soil improvement and water conservation, but little is known about the role of these two regulations in mediating the fate of antibiotic resistome in paddy soils. Here, metagenomic analysis was conducted to investigate the effects and intrinsic mechanisms of biochar application and irrigation patterns on propagation of antibiotic resistance genes (ARGs) in paddy soils. The addition of biochar in paddy soil resulted in a reduction of approximately 1.32%-8.01% in the total absolute abundance of ARGs and 0.60%-22.09% in the numbers of ARG subtype. Compared with flooding irrigation, the numbers of detected ARG subtype were reduced by 1.60%-22.90%, but the total absolute abundance of ARGs increased by 0.06%-5.79% in water-saving irrigation paddy soils. Moreover, the combined treatments of flooding irrigation and biochar could significantly reduce the abundance of ARGs in paddy soils. The incremental antibiotic resistance in soil induced by water-saving irrigation was likewise mitigated by the addition of biochar. Correlation analyses indicated that, the differences in soil physicochemical properties under biochar addition or irrigation treatments contributed to the corresponding changes in the abundance of ARGs. Moreover, the variations of microbial community diversity, multidrug efflux abundance and transport system-related genes in paddy soil were also important for mediating the corresponding differences in the abundance of ARGs under the conditions of biochar addition or irrigation treatments. The findings of this study demonstrated the effectiveness of biochar application in mitigating antibiotic resistance in paddy soils. However, it also highlighted a potential concern relating to the elevated antibiotic resistance associated with water-saving irrigation in paddy fields. Consequently, these results contribute to a deeper comprehension of the environmental risks posed by ARGs in paddy soils.