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
• 金额: --
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2282275
• 关键词: Application; Computational; Methods; Multiomic; Techniques

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.

众所周知，人们对海洋环境仍然知之甚少。这在一定程度上是由于海洋生态系统和生物的庞大而复杂的性质；世界上大约有15,000种鱼，还有数千种来自其他门。因此，计算方法对于深入了解海洋生物过程至关重要，因为它们可以帮助我们整合和理解海量数据，否则这些数据是不可能或无法解释的。这些方法的应用与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。欧洲境内鱼类的可持续性正成为一个日益令人担忧的问题，过度捕捞导致鱼类种群枯竭，低于可维持的限度。许多鱼是作为副渔获物捕捞的，不能供人食用，但许多鱼目前被丢弃在海上，这样它们就不会影响船只的总允许捕获量。2013年商定的改革后的共同渔业政策规定了如何、在哪里以及谁可以开发鱼类以实现可持续捕捞，其中包括上岸义务的规定，这将有效地禁止在海上丢弃TAC鱼种。因此，渔获量需要按物种分类，分为运往人类消费市场的想要的渔获量、必须保留在船上和上岸的不想要的配额鱼种、以及可以丢弃在海上的非配额鱼种的不想要的渔获量。当不想要的渔获物被混合在一起作为散装时，它往往会腐烂，特别是在长途捕鱼旅行中，这使得它们很难识别。鉴于配额下物种的所有渔获量将从这些物种的配额中减去，因此需要发展多种方法，在渔获量被破坏时识别/核实渔获量中的物种。新的CFP还包括适用法定的最低养护参考大小，以防止最小的鱼进入人类消费市场。如果被捕获，它们将不得不以其他方式被利用，例如用于能源生产、堆肥、青贮和鱼粉。在每一种情况下，码头都需要储藏箱来收集废物并将其运输进行处理。大部分将废物转化为可用产品(例如鱼粉)的商业机构表示，他们需要知道废物的来源，因为他们不接受非法、未报告和未受管制的鱼类。拟议的项目将探索应用先进的计算方法，如机器学习，以及从蛋白质组学和基因组学等‘组学’方法获得的数据，用于高通量物种鉴定和生物年龄估计。理想情况下，这些方法将被证明有助于从加工产品(鱼粉)跟踪物种，与船长的记录交叉核对，从而监测/执行上岸义务，以及监测过度捕捞对种群人口的影响。还有许多其他生物因素影响全球鱼类种群，特别是在对水产养殖的依赖日益增加的情况下。这在英国尤其如此，水产养殖三文鱼在苏格兰经济中发挥着巨大的作用，并提供了英国消费的大型鱼类。因此，非常重要的是，能够研究水产养殖面临的生物挑战，如鲑鱼虱子或携带微生物的生物体，达到只能通过使用应用于多组学数据的计算方法的组合才能获得的详细程度。这项研究可进一步应用于渔业，方法是分析导致捕捞鱼类变质的海洋微生物的来源和储量，以期减少暴露，从而减少浪费的可能性。