Genetic diversity pattern of microeukaryotic communities and its relationship with the environment based on PCR-DGGE and T-RFLP techniques in Dongshan Bay, southeast China. (15th July 2018)

• Record Type: Journal Article
• Authors: Zhang, Wenjing; Mo, Yuanyuan; Yang, Jun; Zhou, Jing; Lin, Yuanshao; Isabwe, Alain; Zhang, Jian; Gao, Xiu; Yu, Zheng
• Is Part Of: Continental shelf research. Volume 164(2018)
• Page Start: 1
• Page End: 9
• Publication Date: 2018-07-15
• Subjects: DGGE -- T-RFLP -- Microeukaryotic communities -- Community ecology -- Redundancy analysis -- Spatial patterns -- Dongshan bay; Continental shelf -- Periodicals; Submarine geology -- Periodicals; 551.41
• DOI: 10.1016/j.csr.2018.05.006
• Languages: English
• ISSNs: 0278-4343

Abstract

Abstract: Microeukaryotes play important roles in aquatic ecosystems, and could act as drivers of the biological nutrient cycling processes. However, compared with prokaryotic ones, little is known about the genetic diversity pattern of their community, and the environmental factors affecting their ecological pattern, especially in marine ecosystems. In this study, we used denaturing gradient gel electrophoresis (DGGE) and terminal restriction fragment length polymorphism (T-RFLP) to explore the genetic diversity structure of microeukaryotic communities in Dongshan Bay, southeast China. Our results revealed that microeukaryotic diversity ranged from 31 to 48 phylotypes (on average, 42) using the DGGE approach, while from 22 to 38 phylotypes (on average, 30) based on T-RFLP method, and the Shannon-Wiener diversity (DGGE-based) was relatively higher, suggesting that DGGE displayed a slightly higher resolution than T-RFLP. Surprisingly, the DGGE showed significant horizontal difference among microeukaryotic communities, but was similar with T-RFLP analysis that had no significant influence on microeukaryotic diversity at vertical scale. Further, redundancy analysis (RDA) indicated that the DGGE-based microeukaryotic communities distribution was significantly correlated with three environmental factors (Chl-a, TP and salinity), whereas microeukaryotic community revealed by T-RFLP was affected by four environmental factors namely salinity, temperature, depth and NOX -N. Compared with RDA, BIO-ENV analysis showed that heterotrophic bacteria and NOX -N were important environmental variable influencing microeukaryotic communities in both methods. These differences may be attributed to the noisy effects caused by the relatively large number of environmental variables. Generally speaking, despite differences in beta-diversity ordination for both DGGE and T-RFLP methods, there exists some consistency in the results of both techniques in terms of microeukaryotes responses to the environmental variables. These results suggested that environmental parameters had a great effect on spatial distribution of microeukaryotic community and contributed to marine ecosystem health to be further evaluated. Graphical abstract: In this diagram, the environmental variables have an influence on genetic diversity patterns of microeukaryotic communities from significant to non-significant based on DGGE and T-RFLP techniques. Chl-a- Chlorophyll-a, TP- total phosphorus, HB- heterotrophic bacteria, RSi- reactive silicate. Highlights: Genetic diversity of microeukaryotic communities were analyzed in Dongshan Bay. DGGE-based community diversity was relatively higher than T-RFLP. Multiple environmental variables have significant impacts on microeukaryotic communities. PCR-DGGE and T-RFLP methods can be applied to assess marine environmental changes.