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Application of Computational Methods and Multiomic Techniques to the Analysis of Marine Life

Application of Computational Methods and Multiomic Techniques to the Analysis of Marine Life
计算方法和多组学技术在海洋生物分析中的应用
批准号:
2282275
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2019
资助国家:
英国
项目状态:
已结题
起止时间:
2019 至 --

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中文摘要
翻译
众所周知,对海洋环境的了解仍然很少。这部分是由于海洋生态系统和生物庞大而复杂的性质;世界上大约有15000种鱼类,还有数千种来自其他门。因此,计算方法对于获得对海洋生物过程的关键见解至关重要,因为它们可以帮助我们整合和理解大量的数据,否则这些数据是不可能或不可解释的。这些方法的应用与来自前沿研究的多组学数据相结合,可以在许多方面产生重大影响。欧洲鱼类的可持续性正日益引起人们的关注,过度捕捞造成鱼类资源枯竭,低于可维持的限度。许多鱼是作为副渔获物捕获的,不能用于人类消费,但目前有许多鱼被丢弃在海上,以免影响船只的总允许捕获量。改革后的共同渔业政策于2013年达成一致,该政策规定了如何、在何处以及谁可以开发鱼类以实现可持续捕捞,其中包括关于登陆义务的规定,这将有效地禁止在海上丢弃TAC鱼类。因此,捕捞量需要按物种级别进行分类,分为运往人类消费市场的所需捕捞量、必须保留在船上和上岸的配额物种的不需要捕捞量,以及可以丢弃在海上的非配额物种的不需要捕捞量。当不想要的渔获物聚集在一起时,往往会分解,特别是在长途捕鱼旅行中,这使得它们难以识别。鉴于配额下鱼类的所有渔获量将从这些鱼类的配额中扣除,因此有必要开发多组方法,以便在渔获物遭到破坏时识别/核实渔获物中的物种。新计划亦包括采用法定的最低保育参考尺寸,以防止最小的鱼类进入人类消费市场。如果被捕获,它们将不得不以其他方式加以利用,例如用于能源生产、堆肥、青贮饲料和鱼粉。在每一种情况下,都需要在码头上设置储物箱来收集废物并运输它们进行处理。大多数将弃置物转化为可用产品(例如鱼粉)的商业销售点都表示,他们需要知道弃置物的来源,因为他们不接受非法、未报告和不受管制的鱼类。拟议的项目将探索先进的计算方法的应用,如机器学习,以及来自“组学”方法的数据,如蛋白质组学和基因组学,用于高通量物种鉴定以及生物年龄估计。理想情况下,这些方法将被证明是有用的,从加工产品(鱼粉)追踪物种,与船长的记录交叉核对,从而监测/执行登陆义务,以及监测过度捕捞对人口统计的影响。还有许多其他生物因素影响着全球鱼类种群,特别是随着对水产养殖的日益依赖。在英国尤其如此,水产养殖鲑鱼在苏格兰经济中发挥着巨大的作用,为英国提供了大量的鱼类消费。因此,非常重要的是能够研究水产养殖面临的生物挑战,例如鲑鱼虱或微生物窝藏生物,其细节水平只能通过使用应用于多组学数据的计算方法的组合来获得。这项研究可以进一步应用于渔业,通过分析导致捕获的鱼类变质的海洋微生物群的来源和储量,以期减少接触,从而减少浪费的可能性。
英文摘要
It is well known that the marine environment remains poorly understood. This is partially due to the large, complex nature of marine ecosystems and organisms; there are around 15,000 species of fish in the world, and many thousands more from other phyla. Computational approaches can therefore be essential in gaining key insights into marine biological processes, as they can help us integrate and understand vast amounts of data, which would otherwise be impossible or infeasible to interpret. The application of these methods combined with multiomics data from cutting edge research can have significant impacts in a number of ways.The sustainability of fish within Europe is becoming an increasing concern, with overfishing creating a depletion of fish stocks below maintainable limits. Numerous fish are caught as bycatch that cannot be used for human consumption, but many are currently discarded at sea so that they do not impact on the vessels' total allowable catches. The reformed common fisheries policy, agreed in 2013, which states how, where and who can exploit fish to enable sustainable fishing, includes provisions for a landings obligation which will effectively ban the discarding at sea of TAC fish species. The catch will therefore need to be sorted to species level, separated into the wanted catch destined for the human consumption market, the unwanted catch of quota species that has to be retained onboard and landed, and the unwanted catch of non-quota species that can be discarded at sea. When the unwanted catch is lumped together as bulk it often decomposes, especially on long fishing trips, making them difficult to identify. Given that all catches of species under quota will be subtracted from the quota of those species there is need to develop multiomic methods to identify/verify the species in the catch when the catch is spoiled.The new CFP also includes the application of legal minimum conservation reference sizes in order to prevent the smallest fish entering the human consumption market. If caught they will have to be utilized in some other way, such as for energy production, composting, silage and fish meal. In each case storage bins will be required at the quay to collect the discards and transport them for processing. Most of the commercial outlets who would convert the discards into usable products, e.g. fish meal, have indicated that they would need to know the source of the discards since they do not accept illegal, unreported and unregulated fish.The proposed project will explore the applications of advanced computational methods, such as machine learning, along with data derived from 'omics' methodologies such as proteomics and genomics for high-throughput species identification well as biological age estimation. Ideally these methods would prove to be useful to trace the species from the processed product (fish meal) to cross check with skipper's records and therefore monitoring/enforce the landing obligation, as well as to monitor the impacts on overfishing on population demography.There are many other biological factors affecting global fish stocks, especially with an ever increasing reliance on aquaculture. This is particularly true in the UK, with aquaculture Salmon playing a huge part in the Scottish economy and providing a large fish consumed in the UK. It is therefore highly important to be able to study the biotic challenges facing aquaculture, such as Salmon lice or microbe-harboring organisms, to a level of detail which can only be gained through the use of a combination of computational methods being applied to multiomics data. This research can be further applied to fisheries by analyzing the sources and reserves of marine microbiota which contribute to the spoilage of caught fish, with a view to reducing exposure and therefore reducing the potential for wastage.
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Computational Methods for Analyzing Toponome Data