Fingerprint Analysis Of16s (18s) RDNA Nanoplankton And The Relationship With Environmental Factors In Lake Qiandaohu

The plankton abundance and biomass has has a very rich genetic diversity andphysiological and metabolic diversity，is an important part of water ecosystemsindispensable. Plankton plays a vital role in carbon fixation process, the communitystructure and biomass has a very sensitive response to environmental, so can be used asindicators of environmental changes. In recent years, it becomes a hot topic that therapid changes of freshwater plankton response to the aquatic environment, being moreand more attention. Lake Qiandaohu, located at the southwest of the Yangtze RiverDelta region, is a deep reservoir，playing a multi-functional role in water supply, powergeneration, tourism, shipping and aquaculture. So the quality of the water environmenthas an extremely important impact on the region’s economic and social development. Inthis paper,16S and18S rDNA nanoplankton in Lake Qiandaohu as the research object,using technical of denaturing gradient gel electrophoresis (DGGE), To explore the ofeukaryotic and prokaryotic nanoplankton distribution, community structure and and therelationship with environmental factors. Linked the ecological studies with molecularbiology techniques, to establish a relatively complete set of fast, reliable analysismethod of water nanoplankton.The main results and conclusions are as follows:1. Eukaryotic18S rDNA study, from samples at five stations obtained29recognizable bands in May to July2010,31bands in August to October2010,27bandsin November2010to January2011,38bands February to April2011. In the wholeyears maximum of the bands number was S4March2011, the minimum was S8May2010and September. Diversity index analysis showed that: Shannon-wiener index of thewhole lake was S3> S1> S4> S9> S8, the highest Shannon-wiener index is in March2011and the lowest in September2010throughout the year and. Simpson index was S8>S9>S4> S1> S3, the highest in July2010, the lowest in April2011. Species number was S3> S1> S4> S9> S8, the largest in March2011, at least in September2010. Margalefindex was S3> S1> S9> S4> S8, the highest in March2011, the lowest in September2010. The Pielou index was S4> S3> S1> S8> S9, the highest in November2010, thelowest in Julyand October2010. In addition to the Simpson index, the rest of the indexeswere a significant correlation with dissolved oxygen (DO), a significant negativecorrelation with PH and water temperature (T).2. Prokaryotic16S rDNA study, from samples at five stations obtained30recognizable bands in May to July2010,21bands in August to October2010,28bandsin November2010to January2011,33bands February to April2011. In the wholeyears maximum of the bands number was S4in May2010and April2011, the minimumwas S1in July and November2010. Diversity index analysis showed that: Shannondiversity index of the whole lake was S3> S1> S8> S4> S9, the highest Shannon-wienerindex was in March2011, the lowest in July and September2010. Simpson index wasS9> S4> S8> S1> S3, the highest in July and November2010, the lowest in March2011.Species number was S3>S8>S1>S9>S4, the highest in March2011, at least inSeptember2010. Margalef index was S3> S1> S9> S4> S8, the highest in March2011,the lowest in September2010. Pielou index was S3> S1> S8S9> S4, the highest inMarch2010, the lowest in September2010. In addition to the Simpson index, the rest ofthe indexes were a highly significant correlation with dissolved oxygen (DO), had ahighly significant negative correlation with PH and water temperature(T)3. By sequencing analysis,66eukaryotic sequences were identified, mainlyconcentrated in protozoa (29), the rotifers (4), freshwater crustaceans (20species), algae(7), and a small amount of fungi (3) and molluscs (1).61Prokaryoticsequences,including Proteobacteria(9), the actinomycetes (25), the Bacteroides (14), Cyanophyta(11), and a small amount of green bend bacteria and Firmicutes. By clustering analysiswhether prokaryotic or eukaryotic, based on the same month together, PCA analysisreach a conclusion that the similarity of the samples drawn in the same month werehigher than the samples drawn in the same station. CCA analysis reach a conclusion thatthe complexity of the limiting environmental factor in the community seasonalchanging.