Metabarcoding successfully tracks temporal changes in eukaryotic communities in coastal sediments

被引:28
|
作者
Salonen, I. S. [1 ,2 ]
Chronopoulou, P. -M. [1 ,2 ]
Leskinen, E. [1 ,3 ]
Koho, K. A. [1 ,2 ]
机构
[1] Univ Helsinki, Ecosyst & Environm Res Program, Fac Biol & Environm Sci, Viikinkaari 1, FI-00790 Helsinki, Finland
[2] Helsinki Inst Sustainabil Sci HELSUS, Fac Biol & Environm Sci, Ylopistonkatu 3, FI-00014 Helsinki, Finland
[3] Univ Helsinki, Tvarminne Zool Stn, Fac Biol & Environm Sci, JA Palmenin Tie 260, FI-10900 Hango, Finland
基金
芬兰科学院;
关键词
metabarcoding; next-generation sequencing; sediment; 18S rRNA gene; temporal variation; V9; REGIONS; BALTIC SEA; DIVERSITY; BIODIVERSITY; V4;
D O I
10.1093/femsec/fiy226
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
Metabarcoding is a method that combines high-throughput DNA sequencing and DNA-based identification. Previously, this method has been successfully used to target spatial variation of eukaryote communities in marine sediments, however, the temporal changes in these communities remain understudied. Here, we follow the temporal changes of the eukaryote communities in Baltic Sea surface sediments collected from two coastal localities during three seasons of two consecutive years. Our study reveals that the structure of the sediment eukaryotic ecosystem was primarily driven by annual and seasonal changes in prevailing environmental conditions, whereas spatial variation was a less significant factor in explaining the variance in eukaryotic communities over time. Therefore, our data suggests that shifts in regional climate regime or large-scale changes in the environment are the overdriving factors in shaping the coastal eukaryotic sediment ecosystems rather than small-scale changes in local environmental conditions or heterogeneity in ecosystem structure. More studies targeting temporal changes are needed to further understand the long-term trends in ecosystem stability and response to climate change. Furthermore, this work contributes to the recent efforts in developing metabarcoding applications for environmental biomonitoring, proving a comprehensive option for traditional monitoring approaches.
引用
收藏
页数:11
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