Genomics, proteomics & bioinformatics最新文献

Multiplexing across donors has emerged as a popular strategy to increase throughput, reduce costs, overcome technical batch effects, and improve doublet detection in single-cell genomic studies. To eliminate additional experimental steps, endogenous nuclear genome variants are used for demultiplexing pooled single-cell RNA sequencing (scRNA-seq) data by several computational tools. However, these tools have limitations when applied to single-cell sequencing methods that do not cover nuclear genomic regions well, such as single-cell assay for transposase-accessible chromatin with sequencing (scATAC-seq). Here, we demonstrate that mitochondrial germline variants are an alternative, robust, and computationally efficient endogenous barcode for sample demultiplexing. We propose MitoSort, a tool that uses mitochondrial germline variants to assign cells to their donor of origin and identify cross-genotype doublets in single-cell genomics datasets. We evaluate its performance by using in silico pooled mitochondrial scATAC-seq (mtscATAC-seq) libraries and experimentally multiplexed data with cell hashtags. MitoSort achieves high accuracy and efficiency in genotype clustering and doublet detection for mtscATAC-seq data, addressing the limitations of current computational techniques tailored for scRNA-seq data. Moreover, MitoSort exhibits versatility and can be applied to various single-cell sequencing approaches beyond mtscATAC-seq, provided the mitochondrial variants are reliably detected. Furthermore, we demonstrate the application of MitoSort in a case study where B cells from eight donors were pooled and assayed by single-cell multi-omics sequencing. Altogether, our results demonstrate the accuracy and efficiency of MitoSort, which enables reliable sample demultiplexing in various single-cell genomic applications. MitoSort is available at https://github.com/tangzhj/MitoSort.

The most common epigenetic modification of messenger RNAs (mRNAs) is N6-methyladenosine (m6A), which is mainly located near the 3' untranslated region of mRNAs, near the stop codons, and within internal exons. The biological effect of m6A is dynamically modulated by methyltransferases (writers), demethylases (erasers), and m6A-binding proteins (readers). By controlling post-transcriptional gene expression, m6A has a significant impact on numerous biological functions, including RNA transcription, translation, splicing, transport, and degradation. Hence, m6A influences various physiological and pathological processes, such as spermatogenesis, oogenesis, embryogenesis, placental function, and human reproductive system diseases. During gametogenesis and embryogenesis, genetic material undergoes significant changes, including epigenomic modifications such as m6A. From spermatogenesis and oogenesis to the formation of an oosperm and early embryogenesis, m6A changes occur at every step. m6A abnormalities can lead to gamete abnormalities, developmental delays, impaired fertilization, and maternal-to-zygotic transition blockage. Both mice and humans with abnormal m6A modifications exhibit impaired fertility. In this review, we discuss the dynamic biological effects of m6A and its regulators on gamete and embryonic development and review the possible mechanisms of infertility caused by m6A changes. We also discuss the drugs currently used to manipulate m6A and provide prospects for the prevention and treatment of infertility at the epigenetic level.

Magnesium (Mg) deficiency is associated with increased risk and malignancy in colorectal cancer (CRC), yet the underlying mechanisms remain elusive. Here, we used genomic, proteomic, and phosphoproteomic data to elucidate the impact of Mg deficiency on CRC. Genomic analysis identified 160 genes with higher mutation frequencies in Low-Mg tumors, including key driver genes such as KMT2C and ERBB3. Unexpectedly, initiation driver genes of CRC, such as TP53 and APC, displayed higher mutation frequencies in High-Mg tumors. Additionally, proteomic and phosphoproteomic data indicated that low Mg content in tumors may activate epithelial-mesenchymal transition (EMT) by modulating inflammation or remodeling the phosphoproteome of cancer cells. Notably, we observed a negative correlation between the phosphorylation of DBN1 at S142 (DBN1S142p) and Mg content. A mutation in S142 to D (DBN1S142D) mimicking DBN1S142p up-regulated MMP2 and enhanced cell migration, while treatment with MgCl2 reduced DBN1S142p, thereby reversing this phenotype. Mechanistically, Mg2+ attenuated the DBN1-ACTN4 interaction by decreasing DBN1S142p, which in turn enhanced the binding of ACTN4 to F-actin and promoted F-actin polymerization, ultimately reducing MMP2 expression. These findings shed new light on the crucial role of Mg deficiency in CRC progression and suggest that Mg supplementation may be a promising preventive and therapeutic strategy for CRC.

Cancer stem cells (CSCs) constitute a pivotal element within the tumor microenvironment (TME), driving the initiation and progression of cancer. However, the identification of CSCs and their underlying molecular mechanisms in laryngeal squamous cell carcinoma (LSCC) remains a formidable challenge. Here, we employed single-cell RNA sequencing of matched primary tumor tissues, paracancerous tissues, and local lymph nodes from three LSCC patients to comprehensively characterize the CSCs in LSCC. Two distinct clusters of stem cells originating from epithelial populations were delineated and verified as CSCs and normal stem cells (NSCs), respectively. CSCs were abundant in the paracancerous tissues compared to those in the tumor tissues. CSCs showed high expression of stem cell marker genes such as PROM1, ALDH1A1, and SOX4, and increased the activity of tumor-related hypoxia, Wnt/β-catenin, and Notch signaling pathways. We then explored the intricate crosstalk between CSCs and the TME cells and identified targets within the TME that related with CSCs. We also found eight marker genes of CSCs that were correlated significantly with the prognosis of LSCC patients. Furthermore, bioinformatics analyses showed that drugs such as erlotinib, OSI-027, and ibrutinib selectively targeted the CSC-specifically expressed genes. In conclusion, our results represent the first comprehensive characterization of CSC properties in LSCC at the single-cell level.

Integrin genes are widely involved in tumorigenesis. Yet, a comprehensive characterization of integrin family members and their interactome at the pan-cancer level is lacking. Here, we systematically analyzed integrin family in approximately 10,000 tumors across 32 cancer types. Globally, integrins represent a frequently altered and misexpressed pathway, with alteration and dysregulation overall being protumorigenic. Expression dysregulation, better than mutational landscape, of integrin family successfully identifies a subgroup of aggressive tumors with a high level of proliferation and stemness. The results reveal that several molecular mechanisms collectively regulate integrin expression in a context-dependent manner. For potential clinical usage, we constructed a weighted scoring system, integrinScore, to measure integrin signaling patterns in individual tumors. Remarkably, integrinScore was consistently correlated with predefined molecular subtypes in multiple cancers, with integrinScore-high tumors being more aggressive. Importantly, integrinScore was cancer-dependent and closely associated with proliferation, stemness, tumor microenvironment, metastasis, and immune signatures. IntegrinScore also predicted patients' response to immunotherapy. By mining drug databases, we unraveled an array of compounds that may modulate integrin signaling. Finally, we built a user-friendly database, Pan-cancer Integrin Explorer (PIExplorer; http://computationalbiology.cn/PIExplorer), to facilitate researchers to explore integrin-related knowledge. Collectively, we provide a comprehensive characterization of integrins across cancers and offer gene-specific and cancer-specific rationales for developing integrin-targeted therapy.

Methamphetamine (METH) is a highly addictive psychostimulant that causes physical and psychological damage and immune system disorder, especially in the liver which contains a significant number of immune cells. Dopamine, a key neurotransmitter in METH addiction and immune regulation, plays a crucial role in this process. Here, we developed a chronic METH administration model and conducted single-cell RNA sequencing (scRNA-seq) to investigate the effect of METH on liver immune cells and the involvement of dopamine receptor D1 (DRD1). Our findings reveal that chronic exposure to METH induces immune cell identity shifts from IFITM3+ macrophage (Mac) and CCL5+ Mac to CD14+ Mac, as well as from FYN+CD4+ T effector (Teff), CD8+ T, and natural killer T (NKT) to FOS+CD4+ T and RORα+ group 2 innate lymphoid cell (ILC2), along with the suppression of multiple functional immune pathways. DRD1 is implicated in regulating certain pathways and identity shifts among the hepatic immune cells. Our results provide valuable insights into the development of targeted therapies to mitigate METH-induced immune impairment.

DNA replication is a complex and crucial biological process in eukaryotes. To facilitate the study of eukaryotic replication events, we present a database of eukaryotic DNA replication origins (DeOri), which collects scattered data and integrates extensive sequencing data on eukaryotic DNA replication origins. With continuous updates of DeOri, the number of datasets in the new release increased from 10 to 151 and the number of sequences increased from 16,145 to 9,742,396. Besides nucleotide sequences and bed files, corresponding annotation files, such as coding sequences (CDS), mRNA, and other biological elements within replication origins, are also provided. The experimental techniques used for each dataset, as well as other statistical data, are also presented on web page. Differences in experimental methods, cell lines, and sequencing technologies have resulted in distinct replication origins, making it challenging to differentiate between cell-specific and non-specific replication. We combined multiple replication origins at the species level, scored them, and screened them. The screened regions were considered as species-conservative origins. They are integrated and presented as reference replication origins (rORIs), including Homo sapiens, Gallus gallus, Mus musculus, Drosophila melanogaster, and Caenorhabditis elegans. Additionally, we analyzed the distribution of relevant genomic elements associated with replication origins at the genome level, such as CpG island (CGI), transcription start site (TSS), and G-quadruplex (G4). These analysis results allow users to select the desired data based on it. DeOri is available at http://tubic.tju.edu.cn/deori/.

T cells and T-cell receptors (TCRs) are essential components of the adaptive immune system. Characterization of the TCR repertoire offers a promising and highly informative source for understanding the functions of T cells in the immune response and immunotherapy. Although TCR repertoire studies have attracted much attention, there are few online servers available for TCR repertoire analysis, especially for TCR sequence annotation or advanced analyses. Therefore, we developed TCRosetta, a comprehensive online server that integrates analytical methods for TCR repertoire analysis and visualization. TCRosetta combines general feature analysis, large-scale sequence clustering, network construction, peptide-TCR binding prediction, generation probability calculation, and k-mer motif analysis for TCR sequences, making TCR data analysis as simple as possible. The TCRosetta server accepts multiple input data formats and can analyze ∼ 20,000 TCR sequences in less than 3 min. TCRosetta is the most comprehensive web server available for TCR repertoire analysis and is freely available at https://guolab.wchscu.cn/TCRosetta/.

Long-range sequencing grants insight into additional genetic information beyond what can be accessed by both short reads and modern long-read technology. Several new sequencing technologies, such as "Hi-C" and "Linked Reads", produce long-range datasets for high-throughput and high-resolution genome analyses, which are rapidly advancing the field of genome assembly, genome scaffolding, and more comprehensive variant identification. In this review, we focused on five major long-range sequencing technologies: high-throughput chromosome conformation capture (Hi-C), 10X Genomics Linked Reads, haplotagging, transposase enzyme linked long-read sequencing (TELL-seq), and single- tube long fragment read (stLFR). We detailed the mechanisms and data products of the five platforms and their important applications, evaluated the quality of sequencing data from different platforms, and discussed the currently available bioinformatics tools. This work will benefit the selection of appropriate long-range technology for specific biological studies.