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Bioinformatics (Oxford, England) Jun 2024Ribosome profiling is a widely-used technique for measuring ribosome occupancy at nucleotide resolution. However, the need to analyze this data at nucleotide resolution...
MOTIVATION
Ribosome profiling is a widely-used technique for measuring ribosome occupancy at nucleotide resolution. However, the need to analyze this data at nucleotide resolution introduces unique challenges in data visualization and analyses.
RESULTS
In this study, we introduce RiboGraph, a dedicated visualization tool designed to work with .ribo files, a specialized and efficient format for ribosome occupancy data. Unlike existing solutions that rely on large alignment files and time-consuming preprocessing steps, RiboGraph operates on a purpose designed compact file type. This efficiency allows for interactive, real-time visualization at ribosome-protected fragment length resolution. By providing an integrated toolset, RiboGraph empowers researchers to conduct comprehensive visual analysis of ribosome occupancy data.
AVAILABILITY AND IMPLEMENTATION
Source code, step-by-step installation instructions and links to documentation are available on GitHub: https://github.com/ribosomeprofiling/ribograph. On the same page, we provide test files and a step-by-step tutorial highlighting the key features of RiboGraph.
Topics: Ribosomes; Software; Computational Biology; Ribosome Profiling
PubMed: 38897662
DOI: 10.1093/bioinformatics/btae369 -
Cancer Medicine Jun 2024Breast cancer is a heterogeneous disease categorized based on molecular characteristics, including hormone receptor (HR) and human epidermal growth factor receptor 2...
BACKGROUND
Breast cancer is a heterogeneous disease categorized based on molecular characteristics, including hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) expression levels. The emergence of profiling technology has revealed multiple driver genomic alterations within each breast cancer subtype, serving as biomarkers to predict treatment outcomes. This study aimed to explore the genomic landscape of breast cancer in the Taiwanese population through comprehensive genomic profiling (CGP) and identify diagnostic and predictive biomarkers.
METHODS
Targeted next-generation sequencing-based CGP was performed on 116 archived Taiwanese breast cancer specimens, assessing genomic alterations (GAs), including single nucleotide variants, copy number variants, fusion genes, tumor mutation burden (TMB), and microsatellite instability (MSI) status. Predictive variants for FDA-approved therapies were evaluated within each subtype.
RESULTS
In the cohort, frequent mutations included PIK3CA (39.7%), TP53 (36.2%), KMT2C (9.5%), GATA3 (8.6%), and SF3B1 (6.9%). All subtypes had low TMB, with no MSI-H tumors. Among HR + HER2- patients, 42% (27/65) harbored activating PIK3CA mutations, implying potential sensitivity to PI3K inhibitors and resistance to endocrine therapies. HR + HER2- patients exhibited intrinsic hormonal resistance via FGFR1 gene gain/amplification (15%), exclusive of PI3K/AKT pathway alterations. Aberrations in the PI3K/AKT/mTOR and FGFR pathways were implicated in chemoresistance, with a 52.9% involvement in triple-negative breast cancer. In HER2+ tumors, 50% harbored GAs potentially conferring resistance to anti-HER2 therapies, including PIK3CA mutations (32%), MAP3K1 (2.9%), NF1 (2.9%), and copy number gain/amplification of FGFR1 (18%), FGFR3 (2.9%), EGFR (2.9%), and AKT2 (2.9%).
CONCLUSION
This study presents CGP findings for treatment-naïve Taiwanese breast cancer, emphasizing its value in routine breast cancer management, disease classification, and treatment selection.
Topics: Humans; Female; Taiwan; Breast Neoplasms; Middle Aged; Mutation; Biomarkers, Tumor; Adult; Aged; High-Throughput Nucleotide Sequencing; DNA Copy Number Variations; Genomics; Class I Phosphatidylinositol 3-Kinases; Microsatellite Instability; Receptor, ErbB-2; Gene Expression Profiling
PubMed: 38895905
DOI: 10.1002/cam4.7384 -
Novel Transcriptional and DNA Methylation Abnormalities of SORT1 Gene in Non-Small Cell Lung Cancer.Cancers Jun 2024Sortilin is an important regulator with potential tumour-suppressor function by limiting EGFR signalling. In this study, we undertook a comprehensive expression analysis...
Sortilin is an important regulator with potential tumour-suppressor function by limiting EGFR signalling. In this study, we undertook a comprehensive expression analysis of sortilin transcript variants and the DNA methylation status of their corresponding promoters in human non-small cell carcinomas (NSCLCs). RNA/DNA was extracted from 81 NSCLC samples and paired normal tissue. mRNA expression was measured by qPCR and DNA methylation determined by pyrosequencing. BigDye-terminator sequencing was used to confirm exon-8 alternative splicing. Results demonstrated that both SORT1A and SORT1B variants were downregulated in lung tumours. The SORT1A/SORT1B expression ratio was higher in tumours compared to normal tissue. SORT1B promoter hypermethylation was detected in lung tumours compared to normal lung (median difference 14%, Mann-Whitney test = 10). Interestingly, SORT1B is hypermethylated in white blood cells, but a small and very consistent drop in methylation (6%, = 10) was observed in the lung cancer cases compared to control subjects. We demonstrate that the SORT1B exon-8 splice variation, reported in sequence databases, is also a feature of SORT1A. The significantly altered quantitative and qualitative characteristics of sortilin mRNA in NSCLC indicate a significant involvement in tumour pathogenesis and may have significant impact for its utility as a predictive marker in lung cancer management.
PubMed: 38893272
DOI: 10.3390/cancers16112154 -
Cancers Jun 2024: In cancer care, the MLH1 gene is crucial for DNA mismatch repair (MMR), serving as a vital tumor suppressor. Evaluating MLH1 protein expression status, followed by...
: In cancer care, the MLH1 gene is crucial for DNA mismatch repair (MMR), serving as a vital tumor suppressor. Evaluating MLH1 protein expression status, followed by analysis of MLH1 promoter methylation, has become a key diagnostic and prognostic approach. Our study investigates the complex link between MLH1 methylation and prognosis in endometrial adenocarcinoma (EA) patients. : MLH1 methylation status was accessed by a Pyrosequencing (PSQ) assay. Qualitative positivity for methylation was established if it exceeded the 11% cut-off; as well, a quantitative methylation analysis was conducted to establish correlations with clinicopathological data, relapse-free survival, and disease-free survival. Our study revealed that 33.3% of patients without MLH1 methylation experienced relapses, surpassing the 23.3% in patients with methylation. Furthermore, 16.7% of patients without methylation succumbed to death, with a slightly higher rate of 17.6% in methylated patients. Qualitative comparisons highlighted that the mean methylation rate in patients experiencing relapse was 35.8%, whereas in those without relapse, it was 42.2%. This pattern persisted in disease-specific survival (DSS), where deceased patients exhibited a higher mean methylation level of 49.1% compared to living patients with 38.8%. : Our findings emphasize the efficacy of PSQ for evaluating MLH1 methylation. While unmethylation appears to be associated with a higher relapse rate, the survival rate does not seem to be influenced by methylation. Quantitative percentages suggest that elevated MLH1 methylation is linked to relapse and mortality, though a study with a larger sample size would be essential for statistically significant results.
PubMed: 38893238
DOI: 10.3390/cancers16112119 -
International Journal of Molecular... Jun 2024For patients with hereditary breast and ovarian cancer, the probability of carrying two pathogenic variants (PVs) in dominant cancer-predisposing genes is rare. Using...
For patients with hereditary breast and ovarian cancer, the probability of carrying two pathogenic variants (PVs) in dominant cancer-predisposing genes is rare. Using targeted next-generation sequencing (NGS), we investigated a 49-year-old Caucasian woman who developed a highly aggressive breast tumor. Our analyses identified an intragenic germline heterozygous duplication in with an additional likely PV in the gene. The variant was confirmed by multiplex ligation probe amplification (MLPA), and genomic breakpoints were characterized at the nucleotide level (c.135-2578_442-1104dup). mRNA extracted from lymphocytes was amplified by RT-PCR and then Sanger sequenced, revealing a tandem duplication r.135_441dup; p.(Gln148Ilefs*20). This duplication results in the synthesis of a truncated and, most likely, nonfunctional protein. Following functional studies, the exon 5 c.472C > T; p.(Arg158Cys) missense variant was classified as likely pathogenic by the Li-Fraumeni Syndrome (LFS) working group. This type of unexpected association will be increasingly identified in the future, with the switch from targeted BRCA sequencing to hereditary breast and ovarian cancer (HBOC) panel sequencing, raising the question of how these patients should be managed. It is therefore important to record and investigate these rare double-heterozygous genotypes.
Topics: Humans; Female; Middle Aged; Tumor Suppressor Protein p53; BRCA1 Protein; Triple Negative Breast Neoplasms; Gene Duplication; Genetic Predisposition to Disease; Germ-Line Mutation; High-Throughput Nucleotide Sequencing
PubMed: 38892462
DOI: 10.3390/ijms25116274 -
International Journal of Molecular... Jun 2024RNA sequencing (RNA-Seq) is a powerful technique and is increasingly being used in clinical research and drug development. Currently, several RNA-Seq methods have been... (Comparative Study)
Comparative Study
RNA sequencing (RNA-Seq) is a powerful technique and is increasingly being used in clinical research and drug development. Currently, several RNA-Seq methods have been developed. However, the relative advantage of each method for degraded RNA and low-input RNA, such as RNA samples collected in the field of clinical setting, has remained unknown. The Standard method of RNA-Seq captures mRNA by poly(A) capturing using Oligo dT beads, which is not suitable for degraded RNA. Here, we used three commercially available RNA-Seq library preparation kits (SMART-Seq, xGen Broad-range, and RamDA-Seq) using random primer instead of Oligo dT beads. To evaluate the performance of these methods, we compared the correlation, the number of detected expressing genes, and the expression levels with the Standard RNA-Seq method. Although the performance of RamDA-Seq was similar to that of Standard RNA-Seq, the performance for low-input RNA and degraded RNA has decreased. The performance of SMART-Seq was better than xGen and RamDA-Seq in low-input RNA and degraded RNA. Furthermore, the depletion of ribosomal RNA (rRNA) improved the performance of SMART-Seq and xGen due to increased expression levels. SMART-Seq with rRNA depletion has relative advantages for RNA-Seq using low-input and degraded RNA.
Topics: Sequence Analysis, RNA; Humans; RNA Stability; Gene Expression Profiling; High-Throughput Nucleotide Sequencing; RNA; RNA, Ribosomal; RNA, Messenger; RNA-Seq
PubMed: 38892331
DOI: 10.3390/ijms25116143 -
International Journal of Molecular... Jun 2024The microbiome of the ocular surface has been characterised, but only limited information is available on a possible silent intraocular microbial colonisation in normal...
The microbiome of the ocular surface has been characterised, but only limited information is available on a possible silent intraocular microbial colonisation in normal eyes. Therefore, we performed next-generation sequencing (NGS) of 16S rDNA genes in the aqueous humour. The aqueous humour was sampled from three patients during cataract surgery. Air swabs, conjunctival swabs from patients as well as from healthy donors served as controls. Following DNA extraction, the V3 and V4 hypervariable regions of the 16S rDNA gene were amplified and sequenced followed by denoising. The resulting Amplicon Sequence Variants were matched to a subset of the Ribosomal Database Project 16S database. The deduced bacterial community was then statistically analysed. The DNA content in all samples was low (0-1.49 ng/µL) but sufficient for analysis. The main phyla in the samples were (48%), (26%), (14%), (8%), and (2%). Patients' conjunctival control samples and anterior chamber fluid showed similar patterns of bacterial species containing many waterborne species. Non-disinfected samples showed a different bacterial spectrum than the air swab samples. The data confirm the existence of an ocular surface microbiome. Meanwhile, a distinct intraocular microbiome was not discernible from the background, suggesting the absence of an intraocular microbiome in normal eyes.
Topics: Humans; Aqueous Humor; Microbiota; High-Throughput Nucleotide Sequencing; RNA, Ribosomal, 16S; Bacteria; DNA, Bacterial; Male; Female; Aged; Middle Aged; Sequence Analysis, DNA
PubMed: 38892316
DOI: 10.3390/ijms25116128 -
International Journal of Molecular... May 2024Muscular atrophy is a complex catabolic condition that develops due to several inflammatory-related disorders, resulting in muscle loss. Tumor necrosis factor alpha...
Muscular atrophy is a complex catabolic condition that develops due to several inflammatory-related disorders, resulting in muscle loss. Tumor necrosis factor alpha (TNF-α) is believed to be one of the leading factors that drive inflammatory response and its progression. Until now, the link between inflammation and muscle wasting has been thoroughly investigated, and the non-coding RNA machinery is a potential connection between the candidates. This study aimed to identify specific miRNAs for muscular atrophy induced by TNF-α in the C2C12 murine myotube model. The difference in expression of fourteen known miRNAs and two newly identified miRNAs was recorded by next-generation sequencing between normal muscle cells and treated myotubes. After validation, we confirmed the difference in the expression of one novel murine miRNA (nov-mmu-miRNA-1) under different TNF-α-inducing conditions. Functional bioinformatic analyses of nov-mmu-miRNA-1 revealed the potential association with inflammation and muscle atrophy. Our results suggest that nov-mmu-miRNA-1 may trigger inflammation and muscle wasting by the downregulation of LIN28A/B, an anti-inflammatory factor in the let-7 family. Therefore, TNF-α is involved in muscle atrophy through the modulation of the miRNA cellular machinery. Here, we describe for the first time and propose a mechanism for the newly discovered miRNA, nov-mmu-miRNA-1, which may regulate inflammation and promote muscle atrophy.
Topics: Animals; MicroRNAs; Mice; Tumor Necrosis Factor-alpha; Muscular Atrophy; Cell Line; Muscle, Skeletal; Muscle Fibers, Skeletal; Gene Expression Regulation; High-Throughput Nucleotide Sequencing
PubMed: 38892252
DOI: 10.3390/ijms25116064 -
International Journal of Molecular... May 2024Jeryak is the F1 generation of the cross between Gannan yak and Jersey cattle, which has the advantages of fast growth and high adaptability. The growth and development...
Jeryak is the F1 generation of the cross between Gannan yak and Jersey cattle, which has the advantages of fast growth and high adaptability. The growth and development of skeletal muscle is closely linked to meat production and the quality of meat. However, the molecular regulatory mechanisms of muscle growth differences between Gannan yak and Jeryak analyzed from the perspective of chromatin opening have not been reported. In this study, ATAC-seq was used to analyze the difference of chromatin openness in longissimus muscle of Gannan yak and Jeryak. It was found that chromatin accessibility was more enriched in Jeryak compared to Gannan yak, especially in the range of the transcription start site (TSS) ± 2 kb. GO and KEGG enrichment analysis indicate that differential peak-associated genes are involved in the negative regulation of muscle adaptation and the Hippo signaling pathway. Integration analysis of ATAC-seq and RNA-seq revealed overlapping genes were significantly enriched during skeletal muscle cell differentiation and muscle organ morphogenesis. At the same time, we screened , , and for possible involvement in skeletal muscle development, constructed a genes and transcription factors network map, and found that some transcription factors (TFs), including YY1, KLF4, KLF5 and Bach1, were involved in skeletal muscle development. Overall, we have gained a comprehensive understanding of the key factors that impact skeletal muscle development in various breeds of cattle, providing new insights for future analysis of the molecular regulatory mechanisms involved in muscle growth and development.
Topics: Animals; Cattle; Muscle, Skeletal; RNA-Seq; Chromatin Immunoprecipitation Sequencing; Muscle Development; Chromatin; Meat; Transcription Factors
PubMed: 38892214
DOI: 10.3390/ijms25116029 -
International Journal of Molecular... May 2024Single-cell RNA sequencing (scRNA-seq) is widely used to interpret cellular states, detect cell subpopulations, and study disease mechanisms. In scRNA-seq data analysis,...
Single-cell RNA sequencing (scRNA-seq) is widely used to interpret cellular states, detect cell subpopulations, and study disease mechanisms. In scRNA-seq data analysis, cell clustering is a key step that can identify cell types. However, scRNA-seq data are characterized by high dimensionality and significant sparsity, presenting considerable challenges for clustering. In the high-dimensional gene expression space, cells may form complex topological structures. Many conventional scRNA-seq data analysis methods focus on identifying cell subgroups rather than exploring these potential high-dimensional structures in detail. Although some methods have begun to consider the topological structures within the data, many still overlook the continuity and complex topology present in single-cell data. We propose a deep learning framework that begins by employing a zero-inflated negative binomial (ZINB) model to denoise the highly sparse and over-dispersed scRNA-seq data. Next, scZAG uses an adaptive graph contrastive representation learning approach that combines approximate personalized propagation of neural predictions graph convolution (APPNPGCN) with graph contrastive learning methods. By using APPNPGCN as the encoder for graph contrastive learning, we ensure that each cell's representation reflects not only its own features but also its position in the graph and its relationships with other cells. Graph contrastive learning exploits the relationships between nodes to capture the similarity among cells, better representing the data's underlying continuity and complex topology. Finally, the learned low-dimensional latent representations are clustered using Kullback-Leibler divergence. We validated the superior clustering performance of scZAG on 10 common scRNA-seq datasets in comparison to existing state-of-the-art clustering methods.
Topics: Single-Cell Analysis; Cluster Analysis; Humans; RNA-Seq; Sequence Analysis, RNA; Algorithms; Software; Deep Learning; Computational Biology; Single-Cell Gene Expression Analysis
PubMed: 38892162
DOI: 10.3390/ijms25115976