Aureococcus anophagefferens,小 pelagophyte 水藻,在最近的年里在 Qinhuangdao 的沿海的水里引起了棕色的潮花蕾,在贝壳海洋生物养殖工业上介绍重要否定影响。在标准轻显微镜学下面,它由于它的极其小的尺寸与在地样品的另外的小水藻视觉上难区分。在这研究,基于 18S, rDNA 定序的量的聚合酶链反应(qPCR ) 被开发并且过去常检测并且枚举 A。anophagefferens。线性回归(R < 啜 class= “ a-plus-plus ” > 2 = 0.91 ) 基于周期阀值价值(Ct ) 被产生对知道 A 的集中。anophagefferens。在 Qinhuangdao 的沿海的水里收集的 22 件领域样品受到 DNA 抽取然后分析了使用 qPCR。结果显示出那 A。anophagefferens 沿着 Qinhuangdao 在沿海的水里有宽分布。提高的 A。anophagefferens 丰富,范畴 3 棕色的潮花蕾(> 200 000 cells/mL ) 在 2013 在 8 月发生在 Dongshan 沙滩和老虎石头沙滩。在沿着 Qinhuangdao 的沿海的水的贝壳海洋生物养殖区域, 4 个车站有范畴 3 花蕾,并且 6 个车站在 8 月有范畴 2 花蕾(35 000200 000 cells/mL ) ,所有车站有范畴 1 花蕾(> 0 ~ 35 000 cells/mL ) 在 10 月。量的 PCR 允许 A 的察觉。在在提起的样品的底层的 anophagefferens 房间,它对棕色的潮花蕾的有效管理和预言必要。
Aureococcus anophagefferens, a small pelagophyte algae, has caused brown tide blooms in coastal waters of Qinhuangdao in recent years, presenting significant negative impacts on the shellfish mariculture industry. Under standard light microscopy, it is visually indistinguishable from other small algae in field samples due to its extremely small size. In this study, quantitative polymerase chain reaction(q PCR) based on 18 S r DNA sequences was developed and used to detect and enumerate A. anophagefferens. A linear regression(R2 = 0.91) was generated based on cycle thresholds value(Ct) versus known concentrations of A. anophagefferens. Twenty-two field samples collected in coastal waters of Qinhuangdao were subjected to DNA extraction and then analyzed using q PCR. Results showed that A. anophagefferens had a wide distribution in coastal waters along Qinhuangdao. Elevated A. anophagefferens abundance, category 3 brown tide blooms(〉200 000 cells/m L) occurred at Dongshan Beach and Tiger-stone Beach in August in 2013. In shellfish mariculture areas along coastal waters of Qinhuangdao, 4 stations had category 3 blooms, and 6 stations had category 2 blooms(35 000–200 000 cells/m L) in August and all stations had category 1 blooms(〉0 to ≤35 000 cells/m L) in October. Quantitative PCR allows for detection of A. anophagefferens cells at low levels in filed samples, which is essential to effective management and prediction of brown tide blooms.