James Grace Lymie, Latif Mohd Talib, Isa Mohd Noor Mat, Bakar Mohd Faizal Abu, Yusuf Nurul Yuziana Mohd, Broughton William, Murad Abdul Munir, Abu Bakar Farah Diba
Department of Biological Sciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, UKM, Bangi 43600, Selangor, Malaysia.
Department of Earth Sciences and Environment, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, UKM, Bangi 43600, Selangor, Malaysia.
Data Brief. 2021 May 9;36:107124. doi: 10.1016/j.dib.2021.107124. eCollection 2021 Jun.
Transboundary emissions of smoke-haze from land and forest fires have recurred annually during the dry period (June to October, over the past few decades) in South East Asia. Hazardous air quality has been recorded in Malaysia during these episodes. Agricultural practices such as slash-and-burn of biomass and peat fires particularly in Sumatera and Kalimantan, Indonesia, have been implicated as the major causes of the haze. Past findings have shown that a diversity of microbes can thrive in air including in smoke-haze polluted air. In this study, metagenomic data were generated to reveal the diversity of microorganisms in air during days with and without haze. Air samples were collected during non-haze (2013A01) and two haze (2013A04 and 2013A05) periods in the month of June 2013. DNA was extracted from the samples, subjected to Multiple Displacement Amplification and whole genome sequencing (Next Generation Sequencing) using the HiSeq 2000 Platform. Extensive bio-informatic analyses of the raw sequence data then followed. Raw reads from these six air samples were deposited in the NCBI SRA databases under Bioproject PRJNA662021 with accession numbers SRX9087478, SRX9087479 and SRX9087480.
在东南亚,过去几十年间,旱季(6月至10月)每年都会出现陆地和森林火灾产生的跨境烟雾排放。在这些期间,马来西亚记录到了有害空气质量。农业活动,如生物质的刀耕火种以及泥炭火灾,特别是在印度尼西亚的苏门答腊和加里曼丹,被认为是雾霾的主要成因。过去的研究结果表明,包括在烟雾污染空气中在内,多种微生物能够在空气中茁壮成长。在本研究中,通过宏基因组数据揭示有雾霾和无雾霾日子里空气中微生物的多样性。于2013年6月在非雾霾期(2013A01)以及两个雾霾期(2013A04和2013A05)采集空气样本。从样本中提取DNA,使用HiSeq 2000平台进行多重置换扩增和全基因组测序(新一代测序)。随后对原始序列数据进行了广泛的生物信息学分析。这六个空气样本的原始读数存于NCBI SRA数据库中,生物项目编号为PRJNA662021,登录号分别为SRX9087478、SRX9087479和SRX9087480。