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      Comparative analysis of the testes from wild-type and Alkbh5-knockout mice using single-cell RNA sequencing


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          The RNA demethylase ALKBH5 is regarded as the “eraser” in N6-methyladenosine modification. ALKBH5 deficiency causes male infertility in mice; however, the mechanisms that confer disruption of spermatogenesis are not completely clear. In this study, we profiled testis samples from wild-type and Alkbh5-knockout mice using single-cell RNA sequencing. We obtained single-cell RNA sequencing data of 5,596 and 6,816 testis cells from a wild-type and a knockout mouse, respectively. There were differences detected between the transcriptional profiles of the groups at various germ cell developmental stages. This ranged from the development of spermatogonia to sperm cells, in macrophages, Sertoli cells, and Leydig cells. We identified the differentially expressed genes related to spermatogenesis in germ cells and somatic cells (Sertoli cells and Leydig cells) and evaluated their functions and associated pathways, such as chromatin-related functional pathways, through gene ontology enrichment analysis. This study provides the first single-cell RNA sequencing profile of the testes of ALKBH5-deficient mice. This highlights that ALKBH5 is an important gene for germ cell development and spermatogenesis and offers new molecular mechanistic insights. These findings could provide the basis for further research into the causes and treatment of male infertility.

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          clusterProfiler: an R package for comparing biological themes among gene clusters.

          Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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            featureCounts: an efficient general purpose program for assigning sequence reads to genomic features.

            Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.
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              Comprehensive Integration of Single-Cell Data

              Single-cell transcriptomics has transformed our ability to characterize cell states, but deep biological understanding requires more than a taxonomic listing of clusters. As new methods arise to measure distinct cellular modalities, a key analytical challenge is to integrate these datasets to better understand cellular identity and function. Here, we develop a strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities. After demonstrating improvement over existing methods for integrating scRNA-seq data, we anchor scRNA-seq experiments with scATAC-seq to explore chromatin differences in closely related interneuron subsets and project protein expression measurements onto a bone marrow atlas to characterize lymphocyte populations. Lastly, we harmonize in situ gene expression and scRNA-seq datasets, allowing transcriptome-wide imputation of spatial gene expression patterns. Our work presents a strategy for the assembly of harmonized references and transfer of information across datasets.

                Author and article information

                Role: Editor
                G3 (Bethesda)
                G3: Genes|Genomes|Genetics
                Oxford University Press
                August 2022
                02 June 2022
                02 June 2022
                : 12
                : 8
                : jkac130
                Institute of Reproductive Medicine, Medical School of Nantong University , Nantong 226001, China
                Institute of Reproductive Medicine, Medical School of Nantong University , Nantong 226001, China
                Institute of Reproductive Medicine, Medical School of Nantong University , Nantong 226001, China
                Institute of Reproductive Medicine, Medical School of Nantong University , Nantong 226001, China
                Author notes
                Corresponding author: Institute of Reproductive Medicine, Medical School of Nantong University, Nantong 226001, China. Email: sunfei@ 123456ntu.edu.cn

                Shihao Hong, Xiaozhong Shen, Chunhai Luo and Fei Sun contributed equally to this work.

                Author information
                © The Author(s) 2022. Published by Oxford University Press on behalf of Genetics Society of America.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                : 20 May 2022
                : 18 April 2022
                : 11 June 2022
                Page count
                Pages: 12
                Funded by: National Key Research and Development Program of China, DOI 10.13039/501100012166;
                Award ID: 2021YFC2700200
                Funded by: Key Research and Development Program of Ningxia Hui Autonomous Region, DOI 10.13039/100016692;
                Award ID: 2021BEG02029
                Funded by: Postgraduate Research & Practice Innovation Program of Jiangsu Province;
                Award ID: KYCX20_2841

                single-cell rna-seq,spermatogenesis,alkbh5,mouse testis,m6a methylation
                single-cell rna-seq, spermatogenesis, alkbh5, mouse testis, m6a methylation


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