Age-dependent cerebral small vessel disease (CSVD) is a common disease with a high social burden characterized by heterogeneity of forms and frequent comorbidity with Alzheimer\'s disease (AD). Previously, we identified two MRI types of CSVD with specific clinical presentation and, probably, different mechanisms. The present study included 34 patients with CSVD and white matter hyperintensity (WMH) of stage Fazekas (F) 3 (mean age 61.7 ± 8.9) and 11 volunteers (mean age 57.3 ± 9.7). Total RNA was isolated from peripheral blood leukocytes. The expression of 58 protein-coding genes associated with CSVD and/or AD and 4 reference genes were assessed as part of the original panel for the NanoString nCounter analyzer. Testing results were validated by real-time PCR. There was a significant decrease in the expression levels of the ACOX1, CD33, CD2AP, TNFR1, and VEGFC genes in MRI type 2 relative to the control group as well as a decrease in the expression level of the CD33 gene in MRI type 2 compared to MRI type 1. Processes associated with inflammatory pathways with decreased expression of the identified genes are important in the development of MRI type 2 of CSVD. Given the direct connection of the established genes with AD, the importance of this form of CSVD in comorbidity with AD has been assumed.

UNASSIGNED: Chagas disease, caused by the Trypanosoma cruzi parasite infection, is a potentially life-threatening neglected tropical disease with a worldwide distribution. During the chronic phase of the disease, there exists a fragile balance between the host immune response and parasite replication that keeps patients in a clinically-silent asymptomatic stage for years or even decades. However, in 40% of patients, the disease progresses to clinical manifestations mainly affecting and compromising the cardiac system. Treatment is recommended in the chronic phase, although there are no early markers of its effectiveness. The aim of this study is to identify differential expression changes in genes involved in the immune response in antigen-restimulated PBMC from chronic patients with Chagas disease due to benznidazole treatment.
UNASSIGNED: Thus, high-throughput real-time qPCR analysis has been performed to simultaneously determine global changes in the expression of 106 genes involved in the immune response in asymptomatic (IND) and early cardiac manifestations (CCC I) Chagas disease patients pre- and post-treatment with benznidazole.
UNASSIGNED: The results revealed that 7 out of the 106 analyzed genes were differentially expressed (4 up- and 3 downregulated) after treatment in IND patients and 15 out of 106 (3 up- and 12 downregulated) after treatment of early cardiac Chagas disease patients. Particularly in CCC I patients, regulation of the expression level of some of these genes towards a level similar to that of healthy subjects suggests a beneficial effect of treatment and supports recommendation of benznidazole administration to early cardiac Chagas disease patients. The data obtained also demonstrated that both in asymptomatic patients and in early cardiac chronic patients, after treatment with benznidazole there is a negative regulation of the proinflammatory and cytotoxic responses triggered as a consequence of T. cruzi infection and the persistence of the parasite. This downregulation of the immune response likely prevents marked tissue damage and healing in early cardiac patients, suggesting its positive effect in controlling the pathology.

Sperm undergo a series of changes in the epididymis region before acquiring the ability to move and fertilize, and the identification of genes expressed in a region-specific manner in the epididymis provides a valuable insight into functional differences between regions. We collected epididymal tissue from three yaks and cultured epithelial cells from the caput, corpus and cauda regions of the yak epididymis using the tissue block method. RNA sequencing analysis (RNA-seq) technology was used to detect gene expression in yak epididymal caput, corpus and cauda epithelial cells. The results showed that the DEGs were highest in the caput vs. corpus comparison, and lowest in the corpus vs. cauda comparison. Six DEGs were verified by real-time fluorescence quantitative PCR (qRT-PCR), consistent with transcriptome sequencing results. The significantly enriched DNA replication pathway in the caput vs. corpus was coordinated with cell proliferation, while upregulated DEGs such as POLD1 and MCM4 were found in the DNA replication pathway. The AMPK signaling pathway was found significantly enriched in the caput vs cauda, suggesting its involvement in sperm maturation and capacitation. The TGF beta signaling pathway was screened in the corpus vs cauda and is crucial for mammalian reproductive regulation. Upregulated DEGs (TGFB3, INHBA, INHBB) are involved in the TGF beta signaling pathway. This study provides a reference for culturing yak epididymal epithelial cells in vitro, and elucidates the transcriptional profiles of epithelial cells in different segments of the epididymis, revealing the regulatory and functional differences between different segments, providing basic data for exploring the molecular mechanism of yak sperm maturation and improving the reproductive capacity of high-altitude mammals.

MYC is a transcription factor crucial for maintaining cellular homeostasis, and its dysregulation is associated with highly aggressive cancers. Despite being considered \"undruggable\" due to its unstable protein structure, MYC gains stability through its interaction with its partner protein, MAX. The MYC-MAX heterodimer orchestrates the expression of numerous genes that contribute to an oncogenic phenotype. Previous efforts to develop small molecules, disrupting the MYC-MAX interaction, have shown promise in vitro but none have gained clinical approval. Our current computer-aided study utilizes an approach to explore drug repurposing as a strategy for inhibiting the c-MYC-MAX interaction. We have focused on compounds from DrugBank library, including Food and Drug Administration-approved drugs or those under investigation for other medical conditions. First, we identified a potential druggable site on flat interface of the c-MYC protein, which served as the target for virtual screening. Using both activity-based and structure-based screening, we comprehensively assessed the entire DrugBank library. Structure-based virtual screening was performed on AutoDock Vina and Glide docking tools, while activity-based screening was performed on two independent quantitative structure-activity relationship models. We focused on the top 2% of hit molecules from all screening methods. Ultimately, we selected consensus molecules from these screenings-those that exhibited both a stable interaction with c-MYC and superior inhibitory activity against c-MYC-MAX interaction. Among the evaluated molecules, we identified a protein kinase inhibitor (tyrosine kinase inhibitor [TKI]) known as nilotinib as a promising candidate targeting c-MYC-MAX dimer. Molecular dynamic simulations demonstrated a stable interaction between MYC and nilotinib. The interaction with nilotinib led to the stabilization of a region of the MYC protein that is distorted in apo-MYC and is important for MAX binding. Further analysis of differentially expressed gene revealed that nilotinib, uniquely among the tested TKIs, induced a gene expression program in which half of the genes were known to be responsive to c-MYC. Our findings provide the foundation for subsequent in vitro and in vivo investigations aimed at evaluating the efficacy of nilotinib in managing MYC oncogenic activity.

The development of next-generation sequencing technology has led to a burst of data in a single assay. Management of a large dataset requires high demands on bioinformatic skills and computing resources. Here we present two popular pipelines for RNA-seq data analysis, using open-source software tools HISAT-StringTie-Ballgown and TopHat-Cufflinks. To meet the need of plant scientist, we describe in detail how to perform such comprehensive analysis beginning with raw RNA-seq reads and available reference genome. It allows biologists to align short reads to a reference genome, measure the transcript abundance, and analyze gene differential expression under two or more conditions. We also discuss other RNA-seq tools that are comparable or alternative to this protocol.

Comparison of transcriptome for candidate gene discovery has become an important tool for biologists. While such studies lack the degree of resolution one gets from well-designed forward or reverse genetic studies, nevertheless, this has been a method of choice for giving coarse insight into the underlying biological processes or mechanisms. This was further accelerated with the availability of sequencing technologies. While many pipelines are available for RNA-seq data analysis, the protocol discussed here will guide the first-time users for conducting routine RNA-seq analysis using whole genome sequence as reference.

In this chapter, we present an established pipeline for analyzing RNA-Seq data, which involves a step-by-step flow starting from raw data obtained from a sequencer and culminating in the identification of differentially expressed genes with their functional characterization. The pipeline is divided into three sections, each addressing crucial stages of the analysis process. The first section covers the initial steps of the pipeline, including downloading of the data of interest and performing quality control assessment. Assessment ensures that the data used for analysis is reliable and suitable for downstream analyses. In the second section, gene-level quantification is performed, which entails quantification of expression levels of genes in the samples. The third and final section is focused on differential expression analysis, which involves comparing gene expression levels between two or more conditions. This step helps identify genes that show significant differences in expression levels under different experimental conditions. To facilitate accessibility and reproducibility, we have provided an online repository containing all scripts and files. Additionally, custom scripts are available, enabling users to modify the pipeline\'s output for various downstream analyses. By following this pipeline, researchers can effectively analyze RNA-Seq data and gain valuable insights into gene expression patterns and, furthermore, the understanding of biological processes.

Delta-12 fatty acid desaturases (FAD2s) actively regulate stress responses and cell differentiation in living organisms. In this study, six homologous FAD2 genes were identified based on the genome sequence of Lentinula edodes. Then, the six FAD2 protein sequences were analyzed using bioinformatics tools, including ExPASy ProtParam, SignalP, TMHMM, and TargetP. These analyses were performed to predict the physical and chemical properties, signal peptides, and transmembrane and conserved domains of these proteins. The polypeptide sequences were aligned, and a maximum likelihood phylogenetic tree was constructed using MEGA 7.0 software to elucidate the phylogenetic relationships between homologous FAD2 sequences. The results demonstrated that the FAD2 proteins contained three conserved histidine-rich regions (HXXXH, HXXHH, and HXXHH), which included eight histidine residues. The linoleic acid content and FAD2 enzyme activity were further analyzed, and the levels in the mutagenic heat-tolerant strain 18N44 were lower than those in the wild-type strain 18. Interestingly, the expression levels of the FAD2-2 and FAD2-3 genes under heat stress in strain 18N44 were lower than those in strain 18. These findings indicated that FAD2-2 and FAD2-3 may play major roles in the synthesis of linoleic acid during heat stress.

With the advent of next-generation sequencing (NGS), experimental techniques that capture the biological significance of DNA loci or RNA molecules have emerged as fundamental tools for studying the epigenome and transcriptional regulation on a genome-wide scale. The volume of the generated data and the underlying complexity regarding their analysis highlight the need for robust and easy-to-use computational analytic methods that can streamline the process and provide valuable biological insights. Our solution, aPEAch, is an automated pipeline that facilitates the end-to-end analysis of both DNA- and RNA-sequencing assays, including small RNA sequencing, from assessing the quality of the input sample files to answering meaningful biological questions by exploiting the rich information embedded in biological data. Our method is implemented in Python, based on a modular approach that enables users to choose the path and extent of the analysis and the representations of the results. The pipeline can process samples with single or multiple replicates in batches, allowing the ease of use and reproducibility of the analysis across all samples. aPEAch provides a variety of sample metrics such as quality control reports, fragment size distribution plots, and all intermediate output files, enabling the pipeline to be re-executed with different parameters or algorithms, along with the publication-ready visualization of the results. Furthermore, aPEAch seamlessly incorporates advanced unsupervised learning analyses by automating clustering optimization and visualization, thus providing invaluable insight into the underlying biological mechanisms.

To conduct differential gene expression analysis, ovaries from the cattle tick Rhipicephalus microplus were dissected at three distinct developmental stages (preingurgitated, immature ingurgitated, and mature ingurgitated). Additionally, undissected intact mature males and complete ingurgitated female ticks without ovaries (carcasses) were also collected to serve as reference samples for analysis. To perform total RNA purification, tissue from ten individuals representing each of the five previously described conditions was pooled. mRNA was isolated from the purified total RNA using the oligo (dT) method. Following fragmentation, double stranded cDNA was synthesized and ligated to sequencing adapters. Suitable-sized fragments were subsequently used for PCR amplification. Libraries were analyzed and quantified using an Agilent 2100 Bioanalyzer and an ABI StepOnePlus Real-Time PCR System. A total of 45.64 Gb bases were sequenced using the Illumina HiSeq sequencing platform. After assembling the samples and correcting for abundance, we obtained 82,877 unigenes. The total length, average length, N50, and GC content of the unigenes were 89,754,828 bp,1,082 bp,2,068 bp and 49.04 % respectively. For functional annotation, the unigenes were aligned with 7 functional databases. The number of unigenes identified in the functional databases were as follows: 32,518 (NR:39.24 %), 10,259 (NT:12.38 %), 23,624 (Swissprot:28.50 %), 22,203 (KOG:26.79 %), 25,072 (KEGG:30.25 %), 17,435(GO:21.04 %), and 23,220 (InterPro:28.02 %). Unigene candidate coding regions (CDS) among the unigenes were predicted using TransDecoder software and 42,143 CDS were detected. We also detected 10,522 simple sequence repeats (SSRs) distributed on 8,126 unigenes, and predicted 4,672 transcription factors (TF) coding unigenes. Our data can be used to identify genes that are important for male and female tick and arachnid reproduction and tick general physiology.