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引用本文:刘奎艳,王洪淑,刘峰,陈楠生.2021~2022年荣成海域多相赤潮的分子鉴定.海洋与湖沼,2023,54(6):1645-1655.
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2021~2022年荣成海域多相赤潮的分子鉴定
刘奎艳1,2,3,4, 王洪淑1,2,3, 刘峰1,2,3, 陈楠生1,2,3,4
1.中国科学院海洋研究所 海洋生态与环境科学重点实验室 山东青岛 266071;2.崂山实验室 山东青岛 266237;3.中国科学院海洋大科学研究中心 山东青岛 266071;4.中国科学院大学 北京 100049
摘要:
山东半岛濒临渤海和黄海, 海岸带复杂, 海岸线长, 近岸海域赤潮事件频发。然而, 由于部分赤潮物种的形态难以识别, 或易降解不稳定, 加上形态鉴定专业要求高, 导致致灾赤潮物种未得到准确鉴定。2021年11月至2022年4月间山东荣成海域海带养殖区暴发严重赤潮事件, 面积达1 440 km2,导致海带白化、溃烂, 造成严重经济损失。对该海域水样固定样本的观察鉴定到两种致灾赤潮物种, 红色赤潮藻(Akashiwo sanguinea)和多纹膝沟藻(Gonyaulax polygramma), 二者均为山东近海常见的致灾赤潮物种。该研究通过对赤潮样本中活体单细胞的显微观察和单细胞测序分析, 根据藻细胞形态特征与分子标记序列相似性鉴定到三种优势致灾赤潮物种, 包括红色赤潮藻、多纹膝沟藻和灰白下沟藻(Katodinium glaucum)。其中灰白下沟藻由于在固定过程中不稳定而较少得到鉴定。对该赤潮海域水样开展宏条形码分析, 除了发现上述三种致灾赤潮物种外, 还发现了另外一个致灾赤潮物种纺锤环沟藻(Gyrodinium fusiforme)。纺锤环沟藻也由于在固定过程中不稳定而较少得到鉴定。由此可见, 宏条形码分析方法更加准确系统地鉴定了该赤潮事件的致灾赤潮物种。由于宏条形码分析流程比较便于规范化, 并且该方法可以获得比仅利用细胞形态特征进行鉴定, 或兼用基于形态特征和分子标记方法进行鉴定更加全面的结果, 研究表明宏条形码分析可以准确系统地鉴定组成较为复杂的多相赤潮事件的致灾赤潮物种。
关键词:  赤潮  甲藻  宏条形码分析  红色赤潮藻  多纹膝沟藻
DOI:10.11693/hyhz20230300062
分类号:
基金项目:崂山实验室科技创新项目,LSKJ202203700号;国家自然科学基金项目,42176162号;国家重点研发计划,2022YFC3105200号;中国科学院战略性先导科技专项(B类),XDB42000000号;荣成市海洋与渔业监测减灾中心委托项目,2022-2023。
附件
MOLECULAR ANALYSIS OF A POLYPHASIC RED TIDE IN RONGCHENG OFFSHORE, SHANDONG PENINSULA IN 2021~2022
LIU Kui-Yan1,2,3,4, WANG Hong-Shu1,2,3, LIU Feng1,2,3, CHEN Nan-Sheng1,2,3,4
1.CAS Key Laboratory of Marine Ecology and Environmental science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China;2.Laoshan Laboratory, Qingdao 266237, China;3.Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao 266071, China;4.University of Chinese Academy of Sciences, Beijing 100049, China
Abstract:
Shandong Peninsula is surrounded by the Bohai Sea and Yellow Sea, features complex coastal zoning and long coastline, and suffers from frequent red tide outbreaks in the recent decade. Some red tide species are small in cell size or have inconspicuous morphological characteristics, and are often fragile and unstable during fixation, making it a challenge work for experts to identify the causative red tide species based only on morphological features. Therefore, causative species of many red tides have not been accurately identified, especially for those polyphasic red tide events. From November 2021 to April 2022, a devastating red tide event of 1 440 km2 occurred in Rongcheng offshore in a kelp Saccharina japonica aquaculture region, resulting in the bleaching or rotting of the kelp and serious economic losses. Considering both morphological features of live algal cells in water samples and molecular marker sequences amplified from single cells, three dominant causative red tide species were identified, including Akashiwo sanguinea, Gonyaulax polygramma, and Katodinium glaucum, which was different from a recent report in which only the former two were identified in this region. Katodinium glaucum is easily missed out as it is fragile and unstable during fixation. Metabarcoding analysis of water samples identified another causative species, Gyrodinium fusiforme, being also fragile and unstable during fixation. This study showed that the metabarcoding analysis is standardized and more accurate in species identification, and can accurately and systematically identify red tide causative species especially for complex polyphasic red tide events.
Key words:  harmful algal bloom (HAB)  Dinoflagellata  metabarcoding analysis  Akashiwo sanguinea  Gonyaulax polygramma
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