Longitudinal 16S rRNA data derived from limb regenerative tissue samples of axolotl Ambystoma mexicanum

被引:0
|
作者
Turan Demircan
Ayşe Elif İlhan
Guvanch Ovezmyradov
Gürkan Öztürk
Süleyman Yıldırım
机构
[1] İstanbul Medipol University,Department of Medical Biology, International School of Medicine
[2] Istanbul Medipol University,Department of Biostatistics and Medical Informatics, International School of Medicine
[3] İstanbul Medipol University,Department of Physiology, International School of Medicine
[4] İstanbul Medipol University,Department of Microbiology, International School of Medicine
[5] İstanbul Medipol University,Regenerative and Restorative Medicine Research Center, REMER
来源
关键词
D O I
暂无
中图分类号
学科分类号
摘要
The Mexican axolotl (Ambystoma mexicanum) is a critically endangered species and a fruitful amphibian model for regenerative biology. Despite growing body of research on the cellular and molecular biology of axolotl limb regeneration, microbiological aspects of this process remain poorly understood. Here, we describe bacterial 16S rRNA amplicon dataset derived from axolotl limb tissue samples in the course of limb regeneration. The raw data was obtained by sequencing V3–V4 region of 16S rRNA gene and comprised 14,569,756 paired-end raw reads generated from 21 samples. Initial data analysis using DADA2 pipeline resulted in amplicon sequence variant (ASV) table containing a total of ca. 5.9 million chimera-removed, high-quality reads and a median of 296,971 reads per sample. The data constitute a useful resource for the research on the microbiological aspects of axolotl limb regeneration and will also broadly facilitate comparative studies in the developmental and conservation biology of this critically endangered species.
引用
收藏
相关论文
共 50 条
  • [21] 16S rRNA gene amplicon sequencing data from an Australian wastewater treatment plant
    Romanis, C. S.
    Timms, V. J.
    Crosbie, N. D.
    Neilan, B. A.
    MICROBIOLOGY RESOURCE ANNOUNCEMENTS, 2024, 13 (06):
  • [22] 16S rRNA gene amplicon sequence data from sunflower endosphere bacterial community
    Babalola, Olubukola Oluranti
    Adeleke, Bartholomew Saanu
    Ayangbenro, Ayansina Segun
    DATA IN BRIEF, 2021, 39
  • [23] A nested PCR approach for improved recovery of archaeal 16S rRNA gene fragments from freshwater samples
    Vissers, Elisabeth W.
    Bodelier, Paul L. E.
    Muyzer, Gerard
    Laanbroek, Hendrikus J.
    FEMS MICROBIOLOGY LETTERS, 2009, 298 (02) : 193 - 198
  • [24] Identification of bacteria directly from positive blood culture samples by DNA pyrosequencing of the 16S rRNA gene
    Motoshima, Maiko
    Yanagihara, Katsunori
    Morinaga, Yoshitomo
    Matsuda, Junichi
    Hasegawa, Hiroo
    Kohno, Shigeru
    Kamihira, Shimeru
    JOURNAL OF MEDICAL MICROBIOLOGY, 2012, 61 (11) : 1556 - 1562
  • [25] An Investigation of 16S rRNA Gene Analysis Platforms for Processing Samples Acquired from Preterm Neonates.
    Jenkins, Holly J.
    Hyde, Matthew J.
    Modi, Neena
    Marchesi, Julian
    REPRODUCTIVE SCIENCES, 2019, 26 : 121A - 121A
  • [26] Multiplex 16S rRNA-derived geno-biochip for detection of 16 bacterial pathogens from contaminated foods
    Shin, Hwa Hui
    Hwang, Byeong Hee
    Cha, Hyung Joon
    BIOTECHNOLOGY JOURNAL, 2016, 11 (11) : 1405 - 1414
  • [27] 16S rRNA Gene Amplicon Sequence Data from Chicken Cecal Feces from Vietnam and Thailand
    Takeshita, Nachiko
    Kim, Hyunjung
    Witoonsatian, Kringkrai
    Tohya, Mari
    Tan Hung Vo
    Boonyong, Nuchjaree
    Thi Phuong Binh Nguyen
    Nakagawa, Ichiro
    Meekhanon, Nattakan
    Ngoc Hai Nguyen
    Sekizaki, Tsutomu
    MICROBIOLOGY RESOURCE ANNOUNCEMENTS, 2019, 8 (32):
  • [28] Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data
    Asshauer, Kathrin P.
    Wemheuer, Bernd
    Daniel, Rolf
    Meinicke, Peter
    BIOINFORMATICS, 2015, 31 (17) : 2882 - 2884
  • [29] MicFunPred: A conserved approach to predict functional profiles from 16S rRNA gene sequence data
    Mongad, Dattatray S.
    Chavan, Nikeeta S.
    Narwade, Nitin P.
    Dixit, Kunal
    Shouche, Yogesh S.
    Dhotre, Dhiraj P.
    GENOMICS, 2021, 113 (05) : 3635 - 3643
  • [30] Comprehensive 16S rRNA and metagenomic data from the gut microbiome of aging and rejuvenation mouse models
    Jongoh Shin
    Jung-Ran Noh
    Donghui Choe
    Namil Lee
    Yoseb Song
    Suhyung Cho
    Eun-Jung Kang
    Min-Jeong Go
    Seok Kyun Ha
    Jae-Hoon Kim
    Yong-Hoon Kim
    Kyoung-Shim Kim
    Byoung-Chan Kim
    Chul-Ho Lee
    Byung-Kwan Cho
    Scientific Data, 9