海洋生态与环境科学重点实验室知识库

黄海位于中国大陆和朝鲜半岛之间，除了靠近济州岛的部分地区较深之外，这片半封闭的海域大体上较浅。该海域为众多鱼类提供了优良的生存与繁衍环境。青岛海域位于黄海南部，是许多重要经济物种的产卵场、索饵场，具有丰富的渔业资源。但近年来，随着青岛经济的不断发展、人类活动的不断增强，青岛近海的鱼类生物多样性降低，大型经济鱼类物种数量减少、个体小型化现象明显，鱼类群落结构日趋简单化。因此，需要开展准确可靠的生物多样性监测，来确定目标区域的物种丰度和群落结构，以此实现生态保护和资源可持续利用。环境DNA技术（eDNA）作为一种非入侵性的新手段，正在迅速发展，该技术成本低、破坏性小、准确性高的特点使其越来越频繁的应用于水生生态监测，其中包括生物多样性监测及生物量定量评估，但该技术也存在一些问题，如易出现假阳性及假阴性，这导致实时生物多样性监测不准确。相较于eDNA技术，环境RNA技术（eRNA）由于RNA分子结构，降解更快，因而能够更准确的监测研究区域内代谢活跃的、近期存在的生物多样性，这一特性使得eRNA技术具有减少环境DNA技术监测结果中假阳性的潜在优势。然而，利用eRNA技术探究水生生态系统的鱼类生物多样性的研究非常有限，特别是在海洋生态系统中的应用更是鲜有报道。

为了研究基于eRNA技术开展海洋鱼类多样性研究的有效，本研究开发了一套通用的eRNA采样方法并进行了验证。基于建立的采样方法，本研究于黄海南部青岛近海（35º7¢-36º3¢N, 120º-120º7¢E）开展季节性调查，在2022年秋季、2023年冬季及2024年夏季，分布采集了19个eRNA样品，并同步采集了eDNA样品。经过后续的宏条形码分析，取得的成果如下：

1. 在2022年8月，开展了预实验。结果发现，实验应全程在低温条件下进行并不使用任何保存液，采集3 L海水作为eRNA样品，尽量避免实验过程中的反复冻融，以最大限度的减缓eRNA的降解并增加eRNA的提取浓度。

2. 在2022年11月的秋季调查中，基于eRNA技术共检出80种鱼类，隶属于43科68属，eDNA技术中共检出71种鱼类，隶属于34科58属。整体看来，eRNA技术所得的鱼类物种中，优势种为鲻鱼（Mugil cephalus），黄鲫（Setipinna taty），方氏云鳚（Pholis fangi），石鲽（Kareius bicoloratus），斑头鱼（Hexagrammos agrammus）。eDNA技术所得的鱼类物种中，优势种为斑头鱼，方氏云鳚，鲻鱼，鳀鱼（Engraulis japonicus）及星康吉鳗（Conger myriaster），两种方法的共有种共52种。

3. 在2023年2月的冬季调查中，基于eRNA技术共检出49种鱼类，隶属于26科39属，eDNA技术共检出59种鱼类，隶属于24科41属。eRNA技术所得的鱼类物种中，优势种为鲻鱼、玉筋鱼（Ammodytes personatus）、斑头鱼、黄鳍刺虾虎鱼（Acanthogobius flavimanus）、石鲽；eDNA技术所得的鱼类物种中，相对丰度较高的物种为鲻鱼、褐篮子鱼（Siganus fuscescens）、玉筋鱼、黄鮟鱇（Lophius litulon）、黄鳍刺虾虎鱼，两者重叠的物种共36种。

4. 在2023年6月的夏季调查中，eRNA技术共检出74种鱼类，隶属于36科63属，eDNA技术共检出57种鱼类，隶属于29科48属。eRNA技术所得的鱼类物种中，优势种为鲻鱼、伯氏网鳚（Dictyosoma burgeri）、褐菖鲉（Sebastiscus marmoratus）、棘头梅童鱼（Collichthys lucidus）、拉氏狼牙虾虎鱼（Odontamblyopus lacepedii）；eDNA技术所得的鱼类物种中，占优势地位的鱼类物种为铅点东方鲀（Takifugu alboplumbeus）、小头栉孔虾虎鱼（Paratrypauchen microcephalus）、鳀鱼、棱鮻（Liza carinata）、黄鳍刺虾虎鱼，两种分子技术的共同物种有48种。

5. 在三个季度的鱼类调查结果，eRNA技术及eDNA技术所监测到的鱼类物种均存在显著重叠。其中，三个季度基于不同分子技术的监测结果显示，虾虎鱼类最多，这与传统监测方法的结果相似，与近年来虾虎鱼类在黄海所占地位发生的变化有关。此外，eRNA技术所得优势种均为近海鱼类，多为底栖物种，且有一些鱼类物种具有群栖性和较佳的游泳能力，为青岛水产市场和渔业资源中的常见经济种。然而，有些物种在过往的基于拖网捕捞等传统监测方法的文献及记录中并不多见，是eRNA技术的特有种。因此，研究推断eRNA提取浓度与海水中该物种的物种多样性有一定关系。另外，eRNA技术也可以监测到一些传统监测方法甚至eDNA技术无法监测到的物种。此外，除夏季调查外，eRNA技术所监测到的非本地物种比eDNA技术更少，研究推测这与eRNA的快速降解有关，因此，eRNA技术有潜力更准确的监测到海洋中实际存在的鱼类物种。

综上所述，本研究是首次利用eRNA技术在海洋生态系统中进行鱼类生物多样性监测的研究，建立了一套eRNA采样及提取方法，并验证了eRNA技术在监测海洋鱼类多样性上的可靠性及其作为eDNA技术的补充方法的有效性。将二者结合使用，能够降低假阳性及假阴性的可能，为目标区域的渔业管理和自然保护提供有关鱼类生物多样性的宝贵信息。

The Yellow Sea is located between mainland China and the Korean Peninsula. Apart from the deep areas near Jeju Island, this semi-enclosed sea is generally shallow. The sea area provides an excellent habitat for numerous fish species to thrive and reproduce. Located in the southern part of the Yellow Sea. The Qingdao marine area is located in the southern part of the Yellow Sea and serves as spawning and feeding grounds for many economically important species, possessing abundant fishery resources. However, in recent years, with Qingdao's economic development and increasing human activities, there has been a decline in fish biodiversity in the offshore, a noticeable reduction in the size and number of large economic fish species, and a simplification of the fish community structure. Accurate and reliable biodiversity monitoring is necessary to ascertain species abundance and community structure in the target area, facilitating ecological protection and sustainable resource utilization. Environmental DNA (eDNA) technique, as a non-invasive new method, is rapidly developing. Its low cost, minimal destructiveness, and high accuracy have led to its increasing application in aquatic ecological monitoring, including biodiversity monitoring and biomass quantitative assessment. However, this technology has some issues, such as the potential for false positives and negatives, leading to inaccurate real-time biodiversity monitoring. Compared to eDNA technique, environmental RNA (eRNA) technique, due to the rapid degradation of RNA molecules, can more accurately monitor the metabolically active and recent biodiversity in a study area. This characteristic gives eRNA technique a potential advantage in reducing false positives in the monitoring results of eDNA technique. However, the use of eRNA technique to explore fish biodiversity in aquatic ecosystems is very limited, especially in marine ecosystems, where reports are scarce.

To investigate the effectiveness of marine fish diversity studies based on eRNA technique, this study developed and validated a universal eRNA sampling method. Utilizing the established sampling method, the study conducted seasonal surveys in the Qingdao offshore in the southern Yellow Sea (35º7'–36º3'N, 120º–120º7'E) during the autumn 2022, the winter 2023, and the summer 2024. A total of 19 eRNA samples were collected respectively, along with simultaneous eDNA samples collection. The results, following subsequent macro-barcode analysis, are as follows:

1. A preliminary experiment was conducted in August 2022. The findings suggest that the experiment should be conducted entirely at low temperatures without using any preservatives. 3 L of seawater should be collected as the eRNA samples, avoiding repeated freeze-thaw cycles during the experiment to maximally slow down eRNA degradation and increase the concentration of eRNA extraction.

2. In the autumn survey of November 2022, a total of 80 fish species were detected using eRNA technique, belonging to 43 families and 68 genera, while eDNA technique detected 71 fish species, belonging to 34 families and 58 genera. Overall, the dominant species identified by eRNA technique were Mugil cephalus, Setipinna taty, Pholis fangi, Kareius bicoloratus, and Hexagrammos agrammus. The dominant species identified by eDNA technique were H. agrammus, P. fangi, M. cephalus, Engraulis japonicus, and Conger myriaster, with 52 common species detected by both methods.

3. In the winter survey of February 2023, eRNA technique detected 49 fish species, belonging to 26 families and 39 genera, while eDNA technique detected 59 fish species, belonging to 24 families and 41 genera. The dominant species identified by eRNA technique were M. cephalus, Ammodytes personatus, H. agrammus, Acanthogobius flavimanus, and K. bicoloratus. The relatively abundant species identified by eDNA technique were M. cephalus, Siganus fuscescens, A. personatus, Lophius litulon, and A. flavimanus, with 36 overlapping species detected by both methods.

4. In the summer survey of June 2023, eRNA technique detected 74 fish species, belonging to 36 families and 63 genera, while eDNA technique detected 57 fish species, belonging to 29 families and 48 genera. The dominant species identified by eRNA technique were M. cephalus, Dictyosoma burger, Sebastiscus marmoratus, Collichthys lucidus, and Odontamblyopus lacepedii. The dominant species identified by eDNA technique were Takifugu alboplumbeus, Paratrypauchen microcephalus, E. japonicus, Liza carinata, and A. flavimanus, with 48 common species detected by both molecular techniques.

5. Across the three seasonal fish surveys, significant overlaps were observed in the fish species detected by both eRNA and eDNA techniques. The results from the different molecular techniques over the three seasons showed that Gobiidae were the most abundant, similar to the results from traditional monitoring surveys (TFS) method, and related to the changes in the status of gobies in the Yellow Sea in recent years. Moreover, the dominant species identified by eRNA technique were offshore fish, mostly benthic species, many of which are gregarious and have good swimming abilities, representing common economic species in the Qingdao seafood market and fisheries resources. However, some species were unique to eRNA technique, not commonly seen in TFS method like trawling, Therefore, the research infers that there is a correlation between eRNA extraction concentration and species diversity in seawater. eRNA technique could also detect some species not identifiable by TFS method or even eDNA technique. Besides, except for the summer survey, fewer non-native species were detected by eRNA technique compared to eDNA technique. The study speculates that this is related to the rapid degradation of eRNA. Therefore, eRNA technique has the potential to more accurately detect the actual marine fish species present.

In summary, this study is the first to utilize eRNA technique for monitoring fish biodiversity in marine ecosystems, establishing a standardized method for eRNA sampling and extraction. It validated the reliability of eRNA technique in monitoring marine fish diversity and its effectiveness as a complementary method to eDNA technique. Combining both methods can reduce the likelihood of false positives and negatives, providing valuable information on fish biodiversity for fisheries management and conservation in the target area.

第1章 绪论 1

1.1 青岛近海环境概况       1

1.2 环境DNA技术介绍     1

1.3 环境RNA技术介绍     2

1.3.1 有效性研究 3

1.3.2 存在的问题及改进措施    6

1.4 基于环境RNA技术的生物多样性研究进展       8

1.4.1 在小型生物多样性监测中的应用    9

1.4.2 在大型生物多样性监测中的应用    13

1.4.3 与环境DNA技术结合的应用  14

1.5 研究目的及意义   15

第2章 环境RNA技术方法建立      17

2.1 引言       17

2.2 预实验   17

2.2.1 样品采集及过滤 21

2.2.2 环境RNA提取   22

2.3 结果       23

2.4 基于环境RNA技术的海洋鱼类多样性监测的创新和潜力       24

第3章 基于环境RNA及环境DNA技术的青岛近海秋季鱼类多样性研究    27

3.1 材料与方法   27

3.1.1 采样站点    27

3.1.2 样品采集及过滤 27

3.1.3 环境RNA的提取、扩增及测序      27

3.1.4 环境DNA的提取、扩增及测序      28

3.1.5 数据分析    28

3.1.6 鱼类物种鉴定    29

3.1.7 鱼类群落结构分析    29

3.2 结果       30

3.2.1 基于环境RNA技术的鱼类物种组成      30

3.2.2 基于环境DNA技术的鱼类物种组成      34

3.2.3 基于环境RNA技术的鱼类群落结构      38

3.2.4 基于环境DNA技术的鱼类群落结构      40

3.3 讨论       42

第4章 基于环境RNA及环境DNA技术的青岛近海冬季鱼类多样性研究    45

4.1 材料与方法   45

4.1.1 采样站点    45

4.1.2 样品采集及过滤 45

4.1.3 环境RNA的提取、扩增及测序      45

4.1.4 环境DNA的提取、扩增及测序      45

4.1.5 数据分析    45

4.1.6 鱼类物种鉴定    45

4.1.7 鱼类群落结构分析    45

4.2 结果       45

4.2.1 基于环境RNA技术的鱼类物种组成      45

4.2.2 基于环境DNA技术的鱼类物种组成      48

4.2.3 基于环境RNA技术的鱼类群落结构      52

4.2.4 基于环境DNA技术的鱼类群落结构      54

4.3 讨论       56

第5章 基于环境RNA及环境DNA技术的青岛近海夏季鱼类多样性研究    59

5.1 材料与方法   59

5.1.1 采样站点    59

5.1.2 样品采集及过滤 59

5.1.3 环境RNA的提取、扩增及测序      59

5.1.4 环境DNA的提取、扩增及测序      59

5.1.5 数据分析    59

5.1.6 鱼类物种鉴定    59

5.1.7 鱼类群落结构分析    59

5.2 结果       59

5.2.1 基于环境RNA技术的鱼类物种组成      59

5.2.2 基于环境DNA技术的鱼类物种组成      64

5.2.3 基于环境RNA技术的鱼类群落结构      67

5.2.4 基于环境DNA技术的鱼类群落结构      69

5.3 讨论       71

第6章 结论与展望    73

参考文献      75

致谢      85

作者简历及攻读学位期间发表的学术论文与其他相关学术成果    87