Genomics approaches to the management of mixed stock fisheries in Canada: developing tools for promoting fishery stability and the protection of biodiversity

加拿大混合渔业管理的基因组学方法：开发促进渔业稳定和保护生物多样性的工具

• 批准号: 447168-2013
• 负责人: Bentzen, Paul
• 金额: $ 14.56万
• 依托单位: Dalhousie University
• 依托单位国家: 加拿大
• 项目类别: Strategic Projects - Group
• 财政年份: 2013
• 资助国家: 加拿大
• 起止时间: 2013-01-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=536754
• 关键词: Genomics; approaches; management; mixed; stock

Species usually consist of multiple populations, each associated with a particular environment, and often harbouring adaptations to the local environment or a particular ecological context. Fisheries that target multiple populations can benefit from this adaptive diversity by being more productive, stable, resilient to environmental change, and subject to fewer closures, a set of benefits known as the portfolio effect. However, to benefit from the portfolio effect, mixed stock fisheries must target individual populations in a controlled fashion; this in turn requires tools that enable identification of those populations. Genetic methods have long been used for this purpose, but traditional approaches often fail to resolve stocks and critical units of adaptive diversity. Recently, ('next generation', NGS) DNA sequencing technologies that examine millions of DNA bases and thousands of genes have proven capable of fine-scale resolution of local populations and their genetic traits. The novelty of these methods and the complexity of the data they produce have so far limited their application in fisheries management. We will develop DNA and software tools to identify important populations, enable management of mixed-stock fisheries and conservation of biodiversity within economically and culturally important fish species. We will use NGS to address these objectives in Atlantic salmon in Lake Melville and coastal Labrador, and Atlantic cod along Newfoundland and Labrador's coast. These species support mixed stock harvests, have suffered major declines, and risk losing important diversity. Salmon are important for aboriginal food fisheries, and may be affected by a planned hydroelectric dam. We will also develop a software package to ease analysis of NGS data and testing for associations between DNA variations and environmental or phenotypic features, thus enabling scientists without bioinformatic training to more easily access the power of NGS data. Using extensive genomic analyses, we will identify strains or populations that may be especially well suited to support stable fisheries, and produce tools that that can be used to conserve diverse adaptive portfolios, including software tools for other scientists to pursue similar objectives.

物种通常由多个种群组成，每个种群都与一个特定的环境有关，并且往往具有适应当地环境或特定生态环境的能力。以多种群为目标的渔业可以从这种适应性多样性中受益，因为它们更有生产力，更稳定，对环境变化有更强的适应力，更少受到关闭，这一系列好处被称为组合效应。然而，为了从组合效应中获益，混合种群渔业必须以有控制的方式针对个别种群;这反过来又需要能够识别这些种群的工具。遗传方法长期以来一直用于这一目的，但传统的方法往往无法解决股票和适应多样性的关键单位。最近，（“下一代”，NGS）DNA测序技术可以检查数百万个DNA碱基和数千个基因，已被证明能够对当地人群及其遗传特征进行精细分辨率。这些方法的新奇及其产生的数据的复杂性迄今限制了它们在渔业管理中的应用。我们将开发DNA和软件工具，以确定重要的种群，从而能够管理混合种群渔业，并保护具有经济和文化重要性的鱼类物种的生物多样性。我们将使用NGS来解决这些目标，在梅尔维尔湖和拉布拉多海岸的大西洋鲑鱼，以及沿着纽芬兰和拉布拉多海岸的大西洋鳕鱼。这些物种支持混合库存收获，遭受了重大的下降，并有可能失去重要的多样性。鲑鱼对原住民的食物渔业很重要，可能会受到计划中的水电大坝的影响。 我们还将开发一个软件包，以简化对NGS数据的分析，并测试DNA变异与环境或表型特征之间的关联，从而使没有接受过生物信息学培训的科学家能够更容易地获得NGS数据的力量。利用广泛的基因组分析，我们将确定可能特别适合支持稳定渔业的菌株或种群，并生产可用于保护多种适应性组合的工具，包括其他科学家追求类似目标的软件工具。