首页> 美国卫生研究院文献>Annales de G n ;tique et de S lection Animale >Multi-omic data integration and analysis using systems genomics approaches: methods and applications in animal production health and welfare
【2h】

Multi-omic data integration and analysis using systems genomics approaches: methods and applications in animal production health and welfare

机译:使用系统基因组学方法进行多基因组数据集成和分析:动物生产健康和福利中的方法和应用

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

In the past years, there has been a remarkable development of high-throughput omics (HTO) technologies such as genomics, epigenomics, transcriptomics, proteomics and metabolomics across all facets of biology. This has spearheaded the progress of the systems biology era, including applications on animal production and health traits. However, notwithstanding these new HTO technologies, there remains an emerging challenge in data analysis. On the one hand, different HTO technologies judged on their own merit are appropriate for the identification of disease-causing genes, biomarkers for prevention and drug targets for the treatment of diseases and for individualized genomic predictions of performance or disease risks. On the other hand, integration of multi-omic data and joint modelling and analyses are very powerful and accurate to understand the systems biology of healthy and sustainable production of animals. We present an overview of current and emerging HTO technologies each with a focus on their applications in animal and veterinary sciences before introducing an integrative systems genomics framework for analysing and integrating multi-omic data towards improved animal production, health and welfare. We conclude that there are big challenges in multi-omic data integration, modelling and systems-level analyses, particularly with the fast emerging HTO technologies. We highlight existing and emerging systems genomics approaches and discuss how they contribute to our understanding of the biology of complex traits or diseases and holistic improvement of production performance, disease resistance and welfare.
机译:在过去的几年中,高通量组学(HTO)技术取得了令人瞩目的发展,例如整个生物学各个方面的基因组学,表观基因组学,转录组学,蛋白质组学和代谢组学。这带动了系统生物学时代的进步,包括在动物生产和健康特征方面的应用。但是,尽管有了这些新的HTO技术,数据分析仍然面临着新的挑战。一方面,根据自身优点判断的不同HTO技术适用于识别致病基因,预防疾病的生物标志物和用于治疗疾病的药物靶标,以及对性能或疾病风险进行个性化的基因组预测。另一方面,整合多组数据和联合建模与分析对于了解动物健康和可持续生产的系统生物学非常有力和准确。在介绍用于分析和整合多组学数据以改善动物生产,健康和福利的集成系统基因组学框架之前,我们将概述当前和新兴的HTO技术,并重点关注其在动物和兽医学中的应用。我们得出的结论是,在多组数据集成,建模和系统级分析中,尤其是快速出现的HTO技术面临着巨大的挑战。我们着重介绍现有和新兴的系统基因组学方法,并讨论它们如何有助于我们对复杂性状或疾病的生物学理解以及生产性能,抗病性和福利的全面改善。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号