Hocquette J F
INRA, Herbivore Research Unit, Muscle Growth and Metabolism Group, Theix, 63122 Saint-Genĕs Champanelle, France.
J Physiol Pharmacol. 2005 Jun;56 Suppl 3:37-70.
Genomic studies provide scientists with methods to quickly analyse genes and their products en masse. The first high-throughput techniques to be developed were sequencing methods. A great number of genomes from different organisms have thus been sequenced. Genomics is now shifting to the study of gene expression and function. In the past 5-10 years genomics, proteomics and high-throughput microarray technologies have fundamentally changed our ability to study the molecular basis of cells and tissues in health and diseases, giving a new comprehensive view. For example, in cancer research we have seen new diagnostic opportunities for tumour classification, and prognostication. A new exciting development is metabolomics and lab-on-a-chip techniques (which combine miniaturization and automation) for metabolic studies. However, to interpret the large amount of data, extensive computational development is required. In the coming years, we will see the study of biological networks dominating the scene in Physiology. The great accumulation of genomics information will be used in computer programs to simulate biologic processes. Originally developed for genome analysis, bioinformatics now encompasses a wide range of fields in biology from gene studies to integrated biology (i.e. combination of different data sets from genes to metabolites). This is systems biology which aims to study biological organisms as a whole. In medicine, scientific results and applied biotechnologies arising from genomics will be used for effective prediction of diseases and risk associated with drugs. Preventive medicine and medical therapy will be personalized. Widespread applications of genomics for personalized medicine will require associations of gene expression pattern with diagnoses, treatment and clinical data. This will help in the discovery and development of drugs. In agriculture and animal science, the outcomes of genomics will include improvement in food safety, in crop yield, in traceability and in quality of animal products (dairy products and meat) through increased efficiency in breeding and better knowledge of animal physiology. Genomics and integrated biology are huge tasks and no single lab can pursue this alone. We are probably at the end of the beginning rather than at the beginning of the end because Genomics will probably change Biology to a greater extent than previously forecasted. In addition, there is a great need for more information and better understanding of genomics before complete public acceptance.
基因组研究为科学家提供了大规模快速分析基因及其产物的方法。最早开发的高通量技术是测序方法。因此,已对大量来自不同生物体的基因组进行了测序。如今,基因组学正转向基因表达和功能的研究。在过去5到10年中,基因组学、蛋白质组学和高通量微阵列技术从根本上改变了我们研究健康和疾病状态下细胞与组织分子基础的能力,带来了全新的全面视角。例如,在癌症研究中,我们看到了肿瘤分类和预后诊断的新机遇。代谢组学以及用于代谢研究的芯片实验室技术(结合了小型化和自动化)是一项令人兴奋的新进展。然而,要解读大量数据,就需要广泛的计算技术发展。在未来几年,我们将看到生物网络的研究在生理学领域占据主导地位。基因组学信息的大量积累将被用于计算机程序来模拟生物过程。生物信息学最初是为基因组分析而开发的,如今涵盖了生物学从基因研究到整合生物学(即整合从基因到代谢物的不同数据集)的广泛领域。这就是系统生物学,其旨在将生物有机体作为一个整体来研究。在医学领域,基因组学产生的科学成果和应用生物技术将用于有效预测疾病以及与药物相关的风险。预防医学和医学治疗将实现个性化。基因组学在个性化医疗中的广泛应用需要将基因表达模式与诊断、治疗及临床数据相关联。这将有助于药物的发现与开发。在农业和动物科学领域,基因组学的成果将包括通过提高育种效率和更好地了解动物生理学来改善食品安全、提高作物产量、实现可追溯性以及提升动物产品(乳制品和肉类)质量。基因组学和整合生物学是艰巨的任务,没有哪个单一实验室能够独自完成。我们或许正处于开始阶段的尾声而非结束阶段的开端,因为基因组学对生物学的改变程度可能会比之前预测的更大。此外,在公众完全接受之前,非常需要更多关于基因组学的信息以及更好地理解它。