Articles | Volume 17, issue 10
https://doi.org/10.5194/essd-17-5165-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-17-5165-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A database of glacier prokaryotic genomes and genes for the Three Poles
Yongqin Liu
CORRESPONDING AUTHOR
Center for Pan-third Pole Environment, Lanzhou University, Lanzhou, China
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China
Songnian Hu
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China
State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
Tao Yu
Center for Pan-third Pole Environment, Lanzhou University, Lanzhou, China
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China
State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
Yingfeng Luo
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China
State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
Zhihao Zhang
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China
Yuying Chen
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China
Shunchao Guo
State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
Microbial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
Chinese National Microbiology Data Center (NMDC), Beijing, China
Qinglan Sun
State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
Microbial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
Chinese National Microbiology Data Center (NMDC), Beijing, China
Guomei Fan
State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
Microbial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
Chinese National Microbiology Data Center (NMDC), Beijing, China
Linhuan Wu
State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
Microbial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
Chinese National Microbiology Data Center (NMDC), Beijing, China
Juncai Ma
State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
Microbial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
Chinese National Microbiology Data Center (NMDC), Beijing, China
Keshao Liu
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
Pengfei Liu
Center for Pan-third Pole Environment, Lanzhou University, Lanzhou, China
Junzhi Liu
Center for Pan-third Pole Environment, Lanzhou University, Lanzhou, China
Ruyi Dong
Center for Pan-third Pole Environment, Lanzhou University, Lanzhou, China
Center for Pan-third Pole Environment, Lanzhou University, Lanzhou, China
Related authors
Junzhi Liu, Pengcheng Fang, Yefeng Que, Liang-Jun Zhu, Zheng Duan, Guoan Tang, Pengfei Liu, Mukan Ji, and Yongqin Liu
Earth Syst. Sci. Data, 14, 3791–3805, https://doi.org/10.5194/essd-14-3791-2022, https://doi.org/10.5194/essd-14-3791-2022, 2022
Short summary
Short summary
The management and conservation of lakes should be conducted in the context of catchments because lakes collect water and materials from their upstream catchments. This study constructed the first dataset of lake-catchment characteristics for 1525 lakes with an area from 0.2 to 4503 km2 on the Tibetan Plateau (TP), which provides exciting opportunities for lake studies in a spatially explicit context and promotes the development of landscape limnology on the TP.
Yongqin Liu, Pengcheng Fang, Bixi Guo, Mukan Ji, Pengfei Liu, Guannan Mao, Baiqing Xu, Shichang Kang, and Junzhi Liu
Earth Syst. Sci. Data, 14, 2303–2314, https://doi.org/10.5194/essd-14-2303-2022, https://doi.org/10.5194/essd-14-2303-2022, 2022
Short summary
Short summary
Glaciers are an important pool of microorganisms, organic carbon, and nitrogen. This study constructed the first dataset of microbial abundance and total nitrogen in Tibetan Plateau (TP) glaciers and the first dataset of dissolved organic carbon in ice cores on the TP. These new data could provide valuable information for research on the glacier carbon and nitrogen cycle and help in assessing the potential impacts of glacier retreat due to global warming on downstream ecosystems.
Junzhi Liu, Pengcheng Fang, Yefeng Que, Liang-Jun Zhu, Zheng Duan, Guoan Tang, Pengfei Liu, Mukan Ji, and Yongqin Liu
Earth Syst. Sci. Data, 14, 3791–3805, https://doi.org/10.5194/essd-14-3791-2022, https://doi.org/10.5194/essd-14-3791-2022, 2022
Short summary
Short summary
The management and conservation of lakes should be conducted in the context of catchments because lakes collect water and materials from their upstream catchments. This study constructed the first dataset of lake-catchment characteristics for 1525 lakes with an area from 0.2 to 4503 km2 on the Tibetan Plateau (TP), which provides exciting opportunities for lake studies in a spatially explicit context and promotes the development of landscape limnology on the TP.
Yongqin Liu, Pengcheng Fang, Bixi Guo, Mukan Ji, Pengfei Liu, Guannan Mao, Baiqing Xu, Shichang Kang, and Junzhi Liu
Earth Syst. Sci. Data, 14, 2303–2314, https://doi.org/10.5194/essd-14-2303-2022, https://doi.org/10.5194/essd-14-2303-2022, 2022
Short summary
Short summary
Glaciers are an important pool of microorganisms, organic carbon, and nitrogen. This study constructed the first dataset of microbial abundance and total nitrogen in Tibetan Plateau (TP) glaciers and the first dataset of dissolved organic carbon in ice cores on the TP. These new data could provide valuable information for research on the glacier carbon and nitrogen cycle and help in assessing the potential impacts of glacier retreat due to global warming on downstream ecosystems.
Yuying Chen, Keshao Liu, Yongqin Liu, Trista J. Vick-Majors, Feng Wang, and Mukan Ji
The Cryosphere, 16, 1265–1280, https://doi.org/10.5194/tc-16-1265-2022, https://doi.org/10.5194/tc-16-1265-2022, 2022
Short summary
Short summary
We investigated the bacterial communities in surface and subsurface snow samples in a Tibetan Plateau glacier using 16S rRNA gene sequences. Our results revealed rapid temporal changes in nitrogen (including nitrate and ammonium) and bacterial communities in both surface and subsurface snow. These findings advance our understanding of bacterial community variations and bacterial interactions after snow deposition and provide a possible biological explanation for nitrogen dynamics in snow.
Mukan Ji, Weidong Kong, Chao Liang, Tianqi Zhou, Hongzeng Jia, and Xiaobin Dong
The Cryosphere, 14, 3907–3916, https://doi.org/10.5194/tc-14-3907-2020, https://doi.org/10.5194/tc-14-3907-2020, 2020
Short summary
Short summary
Old permafrost soil usually has more carbohydrates, while younger soil contains more aliphatic carbons, which substantially impacts soil bacterial communities. However, little is known about how permafrost age and thawing drive microbial communities. We found that permafrost thawing significantly increased bacterial richness in young permafrost and changed soil bacterial compositions at all ages. This suggests that thawing results in distinct bacterial species and alters soil carbon degradation.
Cited articles
Alcock, B. P., Raphenya, A. R., Lau, T. T. Y., Tsang, K. K., Bouchard, M., Edalatmand, A., Huynh, W., Nguyen, A. V., Cheng, A. A., Liu, S., Min, S. Y., Miroshnichenko, A., Tran, H. K., Werfalli, R. E., Nasir, J. A., Oloni, M., Speicher, D. J., Florescu, A., Singh, B., Faltyn, M., Hernandez-Koutoucheva, A., Sharma, A. N., Bordeleau, E., Pawlowski, A. C., Zubyk, H. L., Dooley, D., Griffiths, E., Maguire, F., Winsor, G. L., Beiko, R. G., Brinkman, F. S. L., Hsiao, W. W. L., Domselaar, G. V., and McArthur, A. G.: CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database, Nucleic Acids Res., 48, D517–D525, https://doi.org/10.1093/nar/gkz935, 2020.
Anderson, M. J.: Permutational Multivariate Analysis of Variance (PERMANOVA), Wiley StatsRef: Statistics Reference Online, https://doi.org/10.1002/9781118445112.stat07841, 2017.
Anesio, A. M. and Laybourn-Parry, J.: Glaciers and ice sheets as a biome, Trends Ecol. Evol., 27, 219–225, https://doi.org/10.1016/j.tree.2011.09.012, 2012.
Anesio, A. M., Lutz, S., Chrismas, N. A. M., and Benning, L. G.: The microbiome of glaciers and ice sheets, NPJ Biofilms Microbi., 3, 10, https://doi.org/10.1038/s41522-017-0019-0, 2017.
Boetius, A., Anesio, A. M., Deming, J. W., Mikucki, J. A., and Rapp, J. Z.: Microbial ecology of the cryosphere: sea ice and glacial habitats, Nat. Rev. Microbiol., 13, 677–690, https://doi.org/10.1038/nrmicro3522, 2015.
Bowers, R. M., Kyrpides, N. C., Stepanauskas, R., Harmon-Smith, M., Doud, D., Reddy, T. B. K., Schulz, F., Jarett, J., Rivers, A. R., Eloe-Fadrosh, E. A., Tringe, S. G., Ivanova, N. N., Copeland, A., Clum, A., Becraft, E. D., Malmstrom, R. R., Birren, B., Podar, M., Bork, P., Weinstock, G. M., Garrity, G. M., Dodsworth, J. A., Yooseph, S., Sutton, G., Glöckner, F. O., Gilbert, J. A., Nelson, W. C., Hallam, S. J., Jungbluth, S. P., Ettema, T. J. G., Tighe, S., Konstantinidis, K. T., Liu, W. T., Baker, B. J., Rattei, T., Eisen, J. A., Hedlund, B., McMahon, K. D., Fierer, N., Knight, R., Finn, R., Cochrane, G., Karsch-Mizrachi, I., Tyson, G. W., Rinke, C., Lapidus, A., Meyer, F., Yilmaz, P., Parks, D. H., Eren, A. M., Schriml, L., Banfield, J. F., Hugenholtz, P., and Woyke, T.: Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea, Nat. Biotechnol., 35, 725–731, https://doi.org/10.1038/nbt.3893, 2017a.
Bowers, R. M., Kyrpides, N. C., Stepanauskas, R., Harmon-Smith, M., Doud, D., Reddy, T. B. K., Schulz, F., Jarett, J., Rivers, A. R., Eloe-Fadrosh, E. A., Tringe, S. G., Ivanova, N. N., Copeland, A., Clum, A., Becraft, E. D., Malmstrom, R. R., Birren, B., Podar, M., Bork, P., Weinstock, G. M., Garrity, G. M., Dodsworth, J. A., Yooseph, S., Sutton, G., Glöckner, F. O., Gilbert, J. A., Nelson, W. C., Hallam, S. J., Jungbluth, S. P., Ettema, T. J. G., Tighe, S., Konstantinidis, K. T., Liu, W.-T., Baker, B. J., Rattei, T., Eisen, J. A., Hedlund, B., McMahon, K. D., Fierer, N., Knight, R., Finn, R., Cochrane, G., Karsch-Mizrachi, I., Tyson, G. W., Rinke, C., Kyrpides, N. C., Schriml, L., Garrity, G. M., Hugenholtz, P., Sutton, G., Yilmaz, P., Meyer, F., Glöckner, F. O., Gilbert, J. A., Knight, R., Finn, R., Cochrane, G., Karsch-Mizrachi, I., Lapidus, A., Meyer, F., Yilmaz, P., Parks, D. H., Murat Eren, A., Schriml, L., Banfield, J. F., Hugenholtz, P., Woyke, T., and The Genome Standards, C.: Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea, Nat. Biotechnol., 35, 725–731, https://doi.org/10.1038/nbt.3893, 2017b.
Buchfink, B., Reuter, K., and Drost, H. G.: Sensitive protein alignments at tree-of-life scale using DIAMOND, Nat. Methods, 18, 366–368, https://doi.org/10.1038/s41592-021-01101-x, 2021.
Cameron, K. A., Hodson, A. J., and Osborn, A. M.: Carbon and nitrogen biogeochemical cycling potentials of supraglacial cryoconite communities, Polar Biol., 35, 1375–1393, https://doi.org/10.1007/s00300-012-1178-3, 2012.
Cauvy-Fraunié, S. and Dangles, O.: A global synthesis of biodiversity responses to glacier retreat, Nat. Ecol. Evol., 3, 1675–1685, https://doi.org/10.1038/s41559-019-1042-8, 2019.
Chaumeil, P. A., Mussig, A. J., Hugenholtz, P., and Parks, D. H.: GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database, Bioinformatics, 36, 1925–1927, https://doi.org/10.1093/bioinformatics/btz848, 2019.
Ciccazzo, S., Esposito, A., Borruso, L., and Brusetti, L.: Microbial communities and primary succession in high altitude mountain environments, Ann. Microbiol., 66, 43–60, https://doi.org/10.1007/s13213-015-1130-1, 2016.
Cook, J., Edwards, A., Takeuchi, N., and Irvine-Fynn, T.: Cryoconite: The dark biological secret of the cryosphere, Prog. Phys. Geogr., 40, 66–111, https://doi.org/10.1177/0309133315616574, 2016.
Delgado-Baquerizo, M., Oliverio, A. M., Brewer, T. E., Benavent-Gonzalez, A., Eldridge, D. J., Bardgett, R. D., Maestre, F. T., Singh, B. K., and Fierer, N.: A global atlas of the dominant bacteria found in soil, Science, 359, 320–325, https://doi.org/10.1126/science.aap9516, 2018.
Edgar, R. C.: Search and clustering orders of magnitude faster than BLAST, Bioinformatics, 26, 2460–2461, https://doi.org/10.1093/bioinformatics/btq461, 2010.
Fredriksson, N. J., Hermansson, M., and Wilén, B. M.: The Choice of PCR Primers Has Great Impact on Assessments of Bacterial Community Diversity and Dynamics in a Wastewater Treatment Plant, Plos One, 8, e76431, https://doi.org/10.1371/journal.pone.0076431, 2013.
Guo, B. X., Liu, Y. Q., Liu, K. S., Shi, Q., He, C., Cai, R. H., and Jiao, N. Z.: Different dissolved organic matter composition between central and southern glaciers on the Tibetan Plateau, Ecol. Indic., 139, 108888, https://doi.org/10.1016/j.ecolind.2022.108888, 2022.
Hood, E., Battin, T. J., Fellman, J., O'Neel, S., and Spencer, R. G. M.: Storage and release of organic carbon from glaciers and ice sheets, Nat. Geosci., 8, 91–96, https://doi.org/10.1038/ngeo2331, 2015.
Hotaling, S., Finn, D. S., Giersch, J. J., Weisrock, D. W., and Jacobsen, D.: Climate change and alpine stream biology: progress, challenges, and opportunities for the future, Biol. Rev. Camb. Philos. Soc., 92, 2024–2045, https://doi.org/10.1111/brv.12319, 2017.
Huerta-Cepas, J., Forslund, K., Coelho, L. P., Szklarczyk, D., Jensen, L. J., von Mering, C., and Bork, P.: Fast genome-wide functional annotation through orthology assignment by eggNOG-Mapper, Mol. Biol. Evol., 34, 2115–2122, https://doi.org/10.1093/molbev/msx148, 2017.
Huerta-Cepas, J., Szklarczyk, D., Heller, D., Hernández-Plaza, A., Forslund, S. K., Cook, H., Mende, D. R., Letunic, I., Rattei, T., Jensen, L. J., von Mering, C., and Bork, P.: eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses, Nucleic Acids Res., 47, D309–D314, https://doi.org/10.1093/nar/gky1085, 2019.
Hyatt, D., Chen, G. L., Locascio, P. F., Land, M. L., Larimer, F. W., and Hauser, L. J.: Prodigal: prokaryotic gene recognition and translation initiation site identification, BMC Bioinform., 11, 119, https://doi.org/10.1186/1471-2105-11-119, 2010.
Ji, M.: OTU tables with and without subsampling, figshare [data set], https://doi.org/10.6084/m9.figshare.28423781.v2, 2025.
Jia, B., Raphenya, A. R., Alcock, B., Waglechner, N., Guo, P., Tsang, K. K., Lago, B. A., Dave, B. M., Pereira, S., Sharma, A. N., Doshi, S., Courtot, M., Lo, R., Williams, L. E., Frye, J. G., Elsayegh, T., Sardar, D., Westman, E. L., Pawlowski, A. C., Johnson, T. A., Brinkman, F. S., Wright, G. D., and McArthur, A. G.: CARD 2017: expansion and model-centric curation of the comprehensive antibiotic resistance database, Nucleic Acids Res., 45, D566–D573, https://doi.org/10.1093/nar/gkw1004, 2017.
Kanehisa, M., Furumichi, M., Tanabe, M., Sato, Y., and Morishima, K.: KEGG: new perspectives on genomes, pathways, diseases and drugs, Nucleic Acids Res., 45, D353–D361, https://doi.org/10.1093/nar/gkw1092, 2017.
Kang, D. D., Li, F., Kirton, E., Thomas, A., Egan, R., An, H., and Wang, Z.: MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies, PeerJ, 7, e7359, https://doi.org/10.7717/peerj.7359, 2019.
Levasseur, A., Drula, E., Lombard, V., Coutinho, P. M., and Henrissat, B.: Expansion of the enzymatic repertoire of the CAZy database to integrate auxiliary redox enzymes, Biotechnol. Biofuels, 6, 41, https://doi.org/10.1186/1754-6834-6-41, 2013.
Liu, B., Zheng, D., Jin, Q., Chen, L., and Yang, J.: VFDB 2019: a comparative pathogenomic platform with an interactive web interface, Nucleic Acids Res., 47, D687–D692, https://doi.org/10.1093/nar/gky1080, 2019.
Liu, Y., Ji, M., Yu, T., Zaugg, J., Anesio, A. M., Zhang, Z., Hu, S., Hugenholtz, P., Liu, K., and Liu, P.: A genome and gene catalog of glacier microbiomes, Nat. Biotechnol., 40, 1341–1348, https://doi.org/10.1038/s41587-022-01367-2, 2022.
Liu, Y., Hu, S., Yu, T., Luo, Y., Zhang, Z., Chen, Y., Guo, S., S, Q., Fan, G., Wu, L., Ma, J., Liu, K., Liu, P., Liu, J., and Ji, M.: A database of glacier microbiomes for the Three Poles, National Tibetan Plateau Data Center, National Tibetan Plateau Data Center [data set], https://doi.org/10.11888/Cryos.tpdc.300830, 2023.
Mao, G., Ji, M., Jiao, N., Su, J., Zhang, Z., Liu, K., Chen, Y., and Liu, Y.: Monsoon affects the distribution of antibiotic resistome in Tibetan glaciers, Environ. Pollut., 317, 120809, https://doi.org/10.1016/j.envpol.2022.120809, 2023.
Mogrovejo-Arias, D. C., Brill, F. H. H., and Wagner, D.: Potentially pathogenic bacteria isolated from diverse habitats in Spitsbergen, Svalbard, Environ. Earth Sci., 79, 109, https://doi.org/10.1007/s12665-020-8853-4, 2020.
Nissen, J. N., Johansen, J., Allesøe, R. L., Sønderby, C. K., Armenteros, J. J. A., Grønbech, C. H., Jensen, L. J., Nielsen, H. B., Petersen, T. N., Winther, O., and Rasmussen, S.: Improved metagenome binning and assembly using deep variational autoencoders, Nat. Biotechnol., 39, 555–560, https://doi.org/10.1038/s41587-020-00777-4, 2021.
Ogle, D. H., Doll, J. C., Wheeler, P., and Dinno, A.: FSA: Fisheries Stock Analysis [code], https://doi.org/10.32614/CRAN.package.FSA, 2022.
Parks, D. H., Rinke, C., Chuvochina, M., Chaumeil, P. A., Woodcroft, B. J., Evans, P. N., Hugenholtz, P., and Tyson, G. W.: Recovery of nearly 8,000 metagenome-assembled genomes substantially expands the tree of life, Nat. Microbiol., 2, 1533–1542, https://doi.org/10.1038/s41564-017-0012-7, 2017.
Qiu, J.: China: The thrid pole, Nature, 454, 393–396, https://doi.org/10.1038/454393a, 2008.
Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P., Peplies, J., and Glöckner, F. O.: The SILVA ribosomal RNA gene database project: improved data processing and web-based tools, Nucleic Acids Res., 41, D590–D596, https://doi.org/10.1093/nar/gks1219, 2012.
Segawa, T. K., Ushida, K., Agata, K., Okada, N., and Kohshima, S.: Seasonal change in bacterial flora and biomass in mountain snow from the Tateyama mountains, Japan, analyzed by 16S rRNA gene sequencing and real-time PCR, Appl. Environ. Microbiol., 71, 123–130, https://doi.org/10.1128/AEM.71.1.123-130.2005, 2005.
Steinegger, M. and Söding, J.: MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets, Nat. Biotechnol., 35, 1026–1028, https://doi.org/10.1038/nbt.3988, 2017.
Stevens, I. T., Irvine-Fynn, T. D. L., Edwards, A., Mitchell, A. C., Cook, J. M., Porter, P. R., Holt, T. O., Huss, M., Fettweis, X., Moorman, B. J., Sattler, B., and Hodson, A. J.: Spatially consistent microbial biomass and future cellular carbon release from melting Northern Hemisphere glacier surfaces, Commun. Earth Environ., 3, 275, https://doi.org/10.1038/s43247-022-00609-0, 2022.
Stibal, M., Bradley, J. A., Edwards, A., Hotaling, S., Zawierucha, K., Rosvold, J., Lutz, S., Cameron, K. A., Mikucki, J. A., Kohler, T. J., Sabacka, M., and Anesio, A. M.: Glacial ecosystems are essential to understanding biodiversity responses to glacier retreat, Nat. Ecol. Evol., 4, 686–687, https://doi.org/10.1038/s41559-020-1163-0, 2020.
Taheran, M., Naghdi, M., Brar, S. K., Verma, M., and Surampalli, R. Y.: Emerging contaminants: Here today, there tomorrow!, Environ. Nanotechnol. Monit. Manag., 10, 122–126, https://doi.org/10.1016/j.enmm.2018.05.010, 2018.
Tatusov, R. L., Fedorova, N. D., Jackson, J. D., Jacobs, A. R., Kiryutin, B., Koonin, E. V., Krylov, D. M., Mazumder, R., Mekhedov, S. L., Nikolskaya, A. N., Rao, B. S., Smirnov, S., Sverdlov, A. V., Vasudevan, S., Wolf, Y. I., Yin, J. J., and Natale, D. A.: The COG database: an updated version includes eukaryotes, BMC Bioinform., 4, 41, https://doi.org/10.1186/1471-2105-4-41, 2003.
Telling, J., Anesio, A. M., Tranter, M., Irvine-Fynn, T., Hodson, A., Butler, C., and Wadham, J.: Nitrogen fixation on Arctic glaciers, Svalbard, J. Geophys. Res.-Biogeo., 116, G03039, https://doi.org/10.1029/2010JG001632, 2011.
Tremblay, J., Singh, K., Fern, A., Kirton, E. S., He, S., Woyke, T., Lee, J., Chen, F., Dangl, J. L., and Tringe, S. G.: Primer and platform effects on 16S rRNA tag sequencing, Front. Microbiol., 6, 00771, https://doi.org/10.3389/fmicb.2015.00771, 2015.
Trotsenko, Y. A. and Murrell, J. C.: Metabolic aspects of aerobic obligate methanotrophy, Adv. Appl. Microbiol., 63, 183–229, https://doi.org/10.1016/S0065-2164(07)00005-6, 2008.
Wu, Y. W., Simmons, B. A., and Singer, S. W.: MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets, Bioinformatics, 32, 605–607, https://doi.org/10.1093/bioinformatics/btv638, 2016.
Zerillo, M. M., Adhikari, B. N., Hamilton, J. P., Buell, C. R., Levesque, C. A., and Tisserat, N.: Carbohydrate-Active Enzymes in Pythium and their role in plant cell wall and storage polysaccharide degradation, Plos One, 8, 0072572, https://doi.org/10.1371/journal.pone.0072572, 2013.
Zhang, S., Karthikeyan, R., and Fernando, S. D.: Low-temperature biological activation of methane: structure, function and molecular interactions of soluble and particulate methane monooxygenases, Rev. Environ. Sci. Biotechnol., 16, 611–623, https://doi.org/10.1007/s11157-017-9447-9, 2017.
Zhang, Y. L., Kang, S. C., Wei, D., Luo, X., Wang, Z. Z., and Gao, T. G.: Sink or source? Methane and carbon dioxide emissions from cryoconite holes, subglacial sediments, and proglacial river runoff during intensive glacier melting on the Tibetan Plateau, Fundam. Res., 1, 232–239, https://doi.org/10.1016/j.fmre.2021.04.005, 2021.
Short summary
Based on amplicon sequencing, metagenome sequencing, and cultivated genome sequencing, the dataset contains 64,510 bacterial and archaeal species, 62,595,715 unique genes, and 4,501 microbial genomes of bacteria and archaea from glaciers of the Antarctic, Arctic, Tibetan Plateau, and other alpine regions. The data can be useful to ecologists, microbiologists, and policymakers regarding microbial distribution, evolution, and biohazard assessment for glacier microbiome under global climate change.
Based on amplicon sequencing, metagenome sequencing, and cultivated genome sequencing, the...
Altmetrics
Final-revised paper
Preprint