Plankton community composition in the Three Gorges Reservoir Region revealed by PCR-DGGE and its relationships with environmental factors

Yan, Qingyun; Yu, Yuhe; Feng, Weiyue; Yu, Zhigang; Chen, Hongtao

doi:10.1016/s1001-0742(08)62120-8

Cited by 38 publications

(32 citation statements)

References 26 publications

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“…Sun et al (2006) mentioned that the temperature and hydrodynamics in conjunction with the pattern of nutrients availability (dissolved inorganic nitrogen, dissolved inorganic phosphorus and the N/P) and depletion affected the phytoplankton composition. Yan et al (2008) indicated that the eukaryotic community composition was mainly correlated with the concentrations of DO, PO 4 -P, and SiO 3 -Si in the Three Gorges Reservoir Region. In the present study, the correlations of the first two RDA axes (0.851-0.952) indicated that eukaryotic ultraplankton was strongly correlated with environmental variables (temperature, salinity, PO 4 -P and SiO 3 -Si).…”

Section: Discussionmentioning

confidence: 96%

“…In recent years, DGGE has been widely applied to investigate the community analysis in different ecosystems, such as oceanic waters (Díez et al 2001a;López-García et al 2001;Moon-van der Staay et al 2001;Marie et al 2006;Ling et al 2012), fresh waters (Lindström 2004;Gremberghe et al 2008;Yan et al 2008), and soil Zaady et al 2010). It has been proven that the DGGE of 18S rDNA is a high efficient method for eukaryotic microorganisms' study (Díez et al 2001a;Savin et al 2004).…”

Section: Introductionmentioning

confidence: 99%

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Spatial structure of eukaryotic ultraplankton community in the northern South China Sea

2014

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Spatial distribution, diversity and composition of eukaryotic ultraplankton community of the northern South China Sea (nSCS) surface water and the relationship with the in situ water environment were investigated by the method of polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE). A total of 18 DGGE intensive bands were detected and the sequence analysis of these DGGE bands revealed that Alveolata was the dominant eukaryotic ultraplankton group of surface water in the nSCS (50%). Other species belonged to Bicoecea, Bolidophyceae, Polycystinea and Chlorophyta, which accounted for less proportion of eukaryotic ultraplankton in the study area. Unweighted pair group method with arithmetic averages clustering of the sampling stations indicated that all stations were classified mainly based on geographical proximity. Redundancy analysis (RDA) was employed to further investigate the relationships between DGGE band pattern and the environmental variables. Based on the RDA analysis, temperature, salinity, phosphorus and silicate were the important factors to shape the eukaryotic ultraplankton community composition in the nSCS.

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Section: Discussionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Spatial structure of eukaryotic ultraplankton community in the northern South China Sea

2014

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“…The relationship between the bacterioplankton community and the water environmental parameters has been investigated in other aquatic environments (Bai et al 2009;Gao et al 2005;Yan et al 2008;Zeng et al 2009). Analysis result suggested that the bacterial community composition was significantly correlated with the variables of nitrate, DO and silicate (Yan et al 2008).…”

Section: Discussionmentioning

confidence: 99%

Spatial variation of bacterial community structure of the Northern South China Sea in relation to water chemistry

Ling¹,

Dong²,

Wang³

et al. 2012

Ecotoxicology

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“…The limiting factors differ in different ecosystems or within the same ecosystem for different species. Yan et al [40] found that nitrate, DO, and silicate were the significant factors in the Three Gorges Reservoir. On the other hand, Zeng et al [41] reported that total nitrogen and ammonium were the determinants of bacterial distribution in eutrophic lakes.…”

Section: Discussionmentioning

confidence: 99%

“…The results showed that the Verrucomicrobia density was the highest in the control group which contained low nutrient concentration and lower in the higher concentration groups, whereas the lowest abundance of Synechococcuslike species was observed in the control group. Hence, further investigation should be conducted to examine the relationship between the seasonal variations in cyanobacterial composition and the physiochemical environmental parameters [40][41][42].…”

Section: Discussionmentioning

confidence: 99%

Spatial variability of cyanobacterial community composition in Sanya Bay as determined by DGGE fingerprinting and multivariate analysis

et al. 2012

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The cyanobacterial communities in the surface and bottom waters of Sanya Bay were investigated on April 24 and 25, 2010. Flow cytometry showed that the total cyanobacterial abundance in the surface and bottom layers ranged from 0.7×10 4 to 2.38×10 4 cells mL −1 and from 1×10 4 to 1.8×10 4 cells mL −1 , respectively. Cyanobacterial diversity was analyzed using a molecular fingerprinting technique called denaturing gradient gel electrophoresis (DGGE), followed by DNA sequencing. The results were then interpreted through multivariate statistical analysis. Differences in the compositions of cyanobacterial communities were observed in the surface and bottom waters at the same station, with some bands obtained from both the surface and bottom layers, whereas some bands were present only in one layer. The predominant cyanobacterial species of the excised DGGE bands were related to Synechococcus or Synechococcus-like species (56.2%). Other phylogenetic groups identified included Chroococcidiopsis (6.3%), Cyanobium (6.3%) and some unclassified cyanobacteria (31.2%). A redundancy analysis (RDA) was conducted to reveal the relationships between the cyanobacterial community composition and environmental factors. Analysis results showed that the spatial variations in the cyanobacterial community composition in surface waters was significantly related to chlorophyll a (Chla), the biochemical oxygen demand (BOD), nitrate and phosphate (P<0.05). Meanwhile, the spatial variations in the bottom waters was significantly affected by nitrate, nitrite, and phosphate (P<0.05). Environmental parameters could explain 99.3% and 58.3% of the variations in the surface and bottom layers, respectively. cyanobacterial community composition, PCR-DGGE, Synechococcus, redundancy analysis Citation:Ling J, Zhang Y Y, Dong J D, et al. Spatial variability of cyanobacterial community composition in Sanya Bay as determined by DGGE fingerprinting and multivariate analysis.

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Plankton community composition in the Three Gorges Reservoir Region revealed by PCR-DGGE and its relationships with environmental factors

Cited by 38 publications

References 26 publications

Spatial structure of eukaryotic ultraplankton community in the northern South China Sea

Spatial structure of eukaryotic ultraplankton community in the northern South China Sea

Spatial variation of bacterial community structure of the Northern South China Sea in relation to water chemistry

Spatial variability of cyanobacterial community composition in Sanya Bay as determined by DGGE fingerprinting and multivariate analysis

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