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Nowoshilow S, Tanaka EM. Navigation and Use of Custom Tracks within the Axolotl Genome Browser. Methods Mol Biol 2023; 2562:273-289. [PMID: 36272083 DOI: 10.1007/978-1-0716-2659-7_19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
The availability of the chromosome-scale axolotl genome sequences has made it possible to explore genome evolution, perform cross-species comparisons, and use additional sequencing data to analyze both genome-wide features and individual genes. Here, we will focus on the UCSC genome browser and demonstrate in a step-by-step manner how to use it to integrate different data to approach a broad question of the Fgf8 locus evolution and analyze the neighborhood of a gene that was reported missing in axolotl - Pax3.
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Affiliation(s)
| | - Elly M Tanaka
- Research Institute of Molecular Pathology, Vienna, Austria.
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Ye F, Zhang G, E. W, Chen H, Yu C, Yang L, Fu Y, Li J, Fu S, Sun Z, Fei L, Guo Q, Wang J, Xiao Y, Wang X, Zhang P, Ma L, Ge D, Xu S, Caballero-Pérez J, Cruz-Ramírez A, Zhou Y, Chen M, Fei JF, Han X, Guo G. Construction of the axolotl cell landscape using combinatorial hybridization sequencing at single-cell resolution. Nat Commun 2022; 13:4228. [PMID: 35869072 PMCID: PMC9307617 DOI: 10.1038/s41467-022-31879-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 07/08/2022] [Indexed: 01/01/2023] Open
Abstract
The Mexican axolotl (Ambystoma mexicanum) is a well-established tetrapod model for regeneration and developmental studies. Remarkably, neotenic axolotls may undergo metamorphosis, a process that triggers many dramatic changes in diverse organs, accompanied by gradually decline of their regeneration capacity and lifespan. However, the molecular regulation and cellular changes in neotenic and metamorphosed axolotls are still poorly investigated. Here, we develop a single-cell sequencing method based on combinatorial hybridization to generate a tissue-based transcriptomic landscape of the neotenic and metamorphosed axolotls. We perform gene expression profiling of over 1 million single cells across 19 tissues to construct the first adult axolotl cell landscape. Comparison of single-cell transcriptomes between the tissues of neotenic and metamorphosed axolotls reveal the heterogeneity of non-immune parenchymal cells in different tissues and established their regulatory network. Furthermore, we describe dynamic gene expression patterns during limb development in neotenic axolotls. This system-level single-cell analysis of molecular characteristics in neotenic and metamorphosed axolotls, serves as a resource to explore the molecular identity of the axolotl and facilitates better understanding of metamorphosis. The Mexican axolotl is a well-established tetrapod model for regeneration and development. Here the authors report a scRNA-seq method to profile neotenic, metamorphic and limb development stages, highlighting unique perturbation patterns of cell type-related gene expression throughout metamorphosis.
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Zhang L, Huang Y, Wang M, Guo Y, Liang J, Yang X, Qi W, Wu Y, Si J, Zhu S, Li Z, Li R, Shi C, Wang S, Zhang Q, Tang Z, Wang L, Li K, Fei JF, Lan G. Development and Genome Sequencing of a Laboratory-Inbred Miniature Pig Facilitates Study of Human Diabetic Disease. iScience 2019; 19:162-176. [PMID: 31376679 PMCID: PMC6677790 DOI: 10.1016/j.isci.2019.07.025] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Revised: 06/11/2019] [Accepted: 07/13/2019] [Indexed: 01/10/2023] Open
Abstract
Pig has been proved to be a valuable large animal model used for research on diabetic disease. However, their translational value is limited given their distinct anatomy and physiology. For the last 30 years, we have been developing a laboratory Asian miniature pig inbred line (Bama miniature pig [BM]) from the primitive Bama xiang pig via long-term selective inbreeding. Here, we assembled a BM reference genome at full chromosome-scale resolution with a total length of 2.49 Gb. Comparative and evolutionary genomic analyses identified numerous variations between the BM and commercial pig (Duroc), particularly those in the genetic loci associated with the features advantageous to diabetes studies. Resequencing analyses revealed many differentiated gene loci associated with inbreeding and other selective forces. These together with transcriptome analyses of diabetic pig models provide a comprehensive genetic basis for resistance to diabetogenic environment, especially related to energy metabolism. Bama miniature pig (BM) is one of the pig lines with the highest inbreeding coefficient This atlas is a report on the chromosome-level genome assembly of miniature pig Genomic analyses revealed genetic basis underlying BM's advantages to study diabetes Some lncRNAs and mRNAs may be linked to resistance to diabetogenic environment
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Affiliation(s)
- Li Zhang
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China
| | - Yuemeng Huang
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China; College of Veterinary Medicine, Northwest A&F University, Yangling 712100, China
| | - Meng Wang
- Novogene Bioinformatics Institute, Beijing 100083, China
| | - Yafen Guo
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China
| | - Jing Liang
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China.
| | - Xiurong Yang
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China
| | - Wenjing Qi
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China
| | - Yanjun Wu
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China
| | - Jinglei Si
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China
| | - Siran Zhu
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China
| | - Zhe Li
- Novogene Bioinformatics Institute, Beijing 100083, China
| | - Ruiqiang Li
- Novogene Bioinformatics Institute, Beijing 100083, China
| | - Chao Shi
- Shandong Provincial Key Laboratory of Biochemical Engineering, College of Marine Science and Biological Engineering, Qingdao University of Science and Technology, Qingdao 266042, China.
| | - Shuo Wang
- Shandong Provincial Key Laboratory of Biochemical Engineering, College of Marine Science and Biological Engineering, Qingdao University of Science and Technology, Qingdao 266042, China
| | - Qunjie Zhang
- Institution of Genomics and Bioinformatics, South China Agricultural University, Guangzhou 510642, China
| | - Zhonglin Tang
- Research Centre for Animal Genome, Agricultural Genome Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China; Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genome Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Lixian Wang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Kui Li
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Ji-Feng Fei
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou 510631, China
| | - Ganqiu Lan
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China.
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