A transcriptome software comparison for the analyses of treatments expected to give subtle gene expression responses

Stem lodging Resistance-1 controls stem strength by positively regulating the biosynthesis of cell wall components in Capsicum annuum L

Lodging presents a significant challenge in cultivating high-yield crops with extensive above-ground biomass, yet the molecular mechanisms underlying this phenomenon in the Solanaceae family remain largely unexplored. In this study, we identified a gene, CaSLR1 (Capsicum annuum Stem Lodging Resistance 1), which encodes a MYELOBLASTOSIS (MYB) family transcription factor, from a lodging-affected C. annuum EMS mutant. The suppression of CaSLR1 expression in pepper led to notable stem lodging, reduced thickness of the secondary cell wall, and decreased stem strength. A similar phenotype was observed in tomato with the knockdown of SlMYB61, the orthologous gene to CaSLR1. Further investigations demonstrated that CaNAC6, a gene involved in secondary cell wall (SCW) formation, is co-expressed with CaSLR1 and acts as a positive regulator of its expression, as confirmed through yeast one-hybrid, dual-luciferase reporter assays, and electrophoretic mobility shift assays. These findings elucidate the CaNAC6-CaSLR1 module that contributes to lodging resistance, emphasizing the critical role of CaSLR1 in the lodging resistance regulatory network.

Lysine 2-hydroxyisobutyrylation proteomics analyses reveal the regulatory mechanism of CaMYB61-CaAFR1 module in regulating stem development in Capsicum annuum L

Plant stems constitute the most abundant renewable resource on earth. The function of lysine (K)-2-hydroxyisobutyrylation (Khib), a novel post-translational modification (PTM), has not yet been elucidated in plant stem development. Here, by assessing typical pepper genotypes with straight stem (SS) and prostrate stem (PS), we report the first large-scale proteomics analysis for protein Khib to date. Khib-modifications influenced central metabolic processes involved in stem development, such as glycolysis/gluconeogenesis and protein translation. The high Khib level regulated gene expression and protein accumulation associated with cell wall formation in the pepper stem. Specially, we found that CaMYB61 knockdown lines that exhibited prostrate stem phenotypes had high Khib levels. Most histone deacetylases (HDACs, e.g., switch-independent 3 associated polypeptide function related 1, AFR1) potentially function as the "erasing enzymes" involved in reversing Khib level. CaMYB61 positively regulated CaAFR1 expression to erase Khib and promote cellulose and hemicellulose accumulation in the stem. Therefore, we propose a bidirectional regulation hypothesis of "Khib modifications" and "Khib erasing" in stem development, and reveal a novel epigenetic regulatory network in which the CaMYB61-CaAFR1 molecular module participating in the regulation of Khib levels and biosynthesis of cellulose and hemicellulose for the first time.

Single-Cell Sequencing Technology and Its Application in the Study of Central Nervous System Diseases

The mammalian central nervous system consists of a large number of cells, which contain not only different types of neurons, but also a large number of glial cells, such as astrocytes, oligodendrocytes, and microglia. These cells are capable of performing highly refined electrophysiological activities and providing the brain with functions such as nutritional support, information transmission and pathogen defense. The diversity of cell types and individual differences between cells have brought inspiration to the study of the mechanism of central nervous system diseases. In order to explore the role of different cells, a new technology, single-cell sequencing technology has emerged to perform specific analysis of high-throughput cell populations, and has been continuously developed. Single-cell sequencing technology can accurately analyze single-cell expression in mixed-cell populations and collect cells from different spatial locations, time stages and types. By using single-cell sequencing technology to compare gene expression profiles of normal and diseased cells, it is possible to discover cell subsets associated with specific diseases and their associated genes. Therefore, scientists can understand the development process, related functions and disease state of the nervous system from an unprecedented depth. In conclusion, single-cell sequencing technology provides a powerful technology for the discovery of novel therapeutic targets for central nervous system diseases.

Identification Drug Targets for Oxaliplatin-Induced Cardiotoxicity without Affecting Cancer Treatment through Inter Variability Cross-Correlation Analysis (IVCCA)

The successful treatment of side effects of chemotherapy faces two major limitations: the need to avoid interfering with pathways essential for the cancer-destroying effects of the chemotherapy drug, and the need to avoid helping tumor progression through cancer promoting cellular pathways. To address these questions and identify new pathways and targets that satisfy these limitations, we have developed the bioinformatics tool Inter Variability Cross-Correlation Analysis (IVCCA). This tool calculates the cross-correlation of differentially expressed genes, analyzes their clusters, and compares them across a vast number of known pathways to identify the most relevant target(s). To demonstrate the utility of IVCCA, we applied this platform to RNA-seq data obtained from the hearts of the animal models with oxaliplatin-induced CTX. RNA-seq of the heart tissue from oxaliplatin treated mice identified 1744 differentially expressed genes with False Discovery Rate (FDR) less than 0.05 and fold change above 1.5 across nine samples. We compared the results against traditional gene enrichment analysis methods, revealing that IVCCA identified additional pathways potentially involved in CTX beyond those detected by conventional approaches. The newly identified pathways such as energy metabolism and several others represent promising target for therapeutic intervention against CTX, while preserving the efficacy of the chemotherapy treatment and avoiding tumor proliferation. Targeting these pathways is expected to mitigate the damaging effects of chemotherapy on cardiac tissues and improve patient outcomes by reducing the incidence of heart failure and other cardiovascular complications, ultimately enabling patients to complete their full course of chemotherapy with improved quality of life and survival rates.

Transcriptome analysis reveals the peptide toxins diversity of Macrothele palpator venom

Spider venom is a large pharmacological repertoire of different bioactive peptide toxins. However, obtaining crude venom from some spiders is challenging. Thus, studying individual toxins through venom purification is a daunting task. In this study, we constructed the cDNA library and transcriptomic sequencing from the Macrothele palpator venom glands. Subsequently, 718 high-quality expressed sequence tags (ESTs) were identified, and grouped into three categories, including 449 toxin-like (62.53 %), 136 cellular component (18.94 %) and 133 non-matched (18.52 %) based on the gene function annotation. Additionally, 112 non-redundant toxin-like peptides were classified into 13 families (families A-M) based on their sequence homology and cysteine framework. Bioinformatics analysis revealed a high sequence similarity between families A-J and the toxins from Macrothele gigas in the NR database. In contrast, families K-M had a generally low sequence homology with known spider peptide toxins and unpredictable biological functions. Taken together, this study adds many new members to the spider toxin superfamily and provides a basis for identifying various potential biological tools in M. palpator venom.

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.

Evolutionary characterization and pathogenicity of Getah virus from pigs in Guangdong Province of China

Getah virus (GETV) is an emerging zoonotic virus that can infect humans and many mammals through mosquitoes. In this study, a novel pathogenic GETV strain, GDQY2022, was isolated from a pig farm in Guangdong Province, China. Sequence comparisons and phylogenetic analysis showed that GDQY2022 belongs to group III (GIII) and was most closely related to strain HeN202009-2, with 99.78% nucleotide sequence identity. Histopathological examination revealed significant pathological changes, such as widened alveolar septum in the lungs with mild congestion and hemorrhage. Differences in viral load between tissues were assessed by real-time RT-PCR, and significantly higher levels of GETV were found in abdominal lymph nodes and lungs of subclinically and clinically affected pigs (P < 0.01). This study provides valuable data for understanding the risk of GETV infection in the pig industry and a reliable basis for studying the pathogenic mechanisms and diagnostic surveillance of GETV.

Transcriptomics for Clinical and Experimental Biology Research: Hang on a Seq

Sequencing the human genome empowers translational medicine, facilitating transcriptome-wide molecular diagnosis, pathway biology, and drug repositioning. Initially, microarrays are used to study the bulk transcriptome; but now short-read RNA sequencing (RNA-seq) predominates. Positioned as a superior technology, that makes the discovery of novel transcripts routine, most RNA-seq analyses are in fact modeled on the known transcriptome. Limitations of the RNA-seq methodology have emerged, while the design of, and the analysis strategies applied to, arrays have matured. An equitable comparison between these technologies is provided, highlighting advantages that modern arrays hold over RNA-seq. Array protocols more accurately quantify constitutively expressed protein coding genes across tissue replicates, and are more reliable for studying lower expressed genes. Arrays reveal long noncoding RNAs (lncRNA) are neither sparsely nor lower expressed than protein coding genes. Heterogeneous coverage of constitutively expressed genes observed with RNA-seq, undermines the validity and reproducibility of pathway analyses. The factors driving these observations, many of which are relevant to long-read or single-cell sequencing are discussed. As proposed herein, a reappreciation of bulk transcriptomic methods is required, including wider use of the modern high-density array data-to urgently revise existing anatomical RNA reference atlases and assist with more accurate study of lncRNAs.

Gene Expression Analysis in gla-Mutant Zebrafish Reveals Enhanced Ca2+ Signaling Similar to Fabry Disease

Fabry disease (FD) is an X-linked inborn metabolic disorder due to partial or complete lysosomal α-galactosidase A deficiency. FD is characterized by progressive renal insufficiency and cardio- and cerebrovascular involvement. Restricted access on Gb3-independent tissue injury experimental models has limited the understanding of FD pathophysiology and delayed the development of new therapies. Accumulating glycosphingolipids, mainly Gb3 and lysoGb3, are Fabry specific markers used in clinical follow up. However, recent studies suggest there is a need for additional markers to monitor FD clinical course or response to treatment. We used a gla-knockout zebrafish (ZF) to investigate alternative biomarkers in Gb3-free-conditions. RNA sequencing was used to identify transcriptomic signatures in kidney tissues discriminating gla-mutant (M) from wild type (WT) ZF. Gene Ontology (GO) and KEGG pathways analysis showed upregulation of immune system activation and downregulation of oxidative phosphorylation pathways in kidneys from M ZF. In addition, upregulation of the Ca2+ signaling pathway was also detectable in M ZF kidneys. Importantly, disruption of mitochondrial and lysosome-related pathways observed in M ZF was validated by immunohistochemistry. Thus, this ZF model expands the pathophysiological understanding of FD, the Gb3-independent effects of gla mutations could be used to explore new therapeutic targets for FD.