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Genom Data. 2014 Jun 11;2:132-4. doi: 10.1016/j.gdata.2014.06.003. eCollection 2014 Dec.

GeoChip as a metagenomics tool to analyze the microbial gene diversity along an elevation gradient.

Author information

1
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China.
2
Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100085, China.
3
Institute for Environmental Genomics, Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73019, USA.
4
Key Laboratory of Adaption and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810008, China.
5
Key Laboratory of Adaption and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810008, China ; Shapotou Desert Experiment and Research Station, Cold and Arid Regions and Environmental & Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China.
6
Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu 610041, China.
7
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China ; Institute for Environmental Genomics, Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73019, USA ; Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.

Abstract

To examine microbial responses to climate change, we used a microarray-based metagenomics tool named GeoChip 4.0 to profile soil microbial functional genes along four sites/elevations of a Tibetan mountainous grassland. We found that microbial communities differed among four elevations. Soil pH, temperature, NH4 (+)-N and vegetation diversity were four major attributes affecting soil microbial communities. Here we describe in details the experiment design, the data normalization process, soil and vegetation analyses associated with the study published on ISME Journal in 2014 [1], whose raw data have been uploaded to Gene Expression Omnibus (accession number GSM1185243).

KEYWORDS:

Gene diversity; Genomic technology; GeoChip 4.0; Soil microbial community

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