从结构基因组学到功能基因组学

基因组学研究随着模式生物基因组全序列测定的完成由结构基因组学阶段发展到功能基因组学阶段,基因组学成为当今最为活跃、最有影响的前沿学科.以结构基因组学的研究成果为基础,功能基因组学中各学科因其原理不同及其关键技术的特点和优势,具有各自的应用范畴和发展趋势.功能基因组学不断渗透入现代科学的各领域,促成了适用于不同研究目的新兴学科的诞生.     

人类基因组计划的机遇和挑战：Ⅰ.从结构基因组学到功能基因组学

人类基因组计划的机遇和挑战：Ⅰ．从结构基因组学到功能基因组学陈竺＊李伟俞曼熊慧陈赛娟（上海第二医科大学附属瑞金医院、血液学研究所、卫生部暨上海市人类基因组研究重点实验室＊上海人类基因组研究中心、上海生命科学研究中心）关键词人类基因组计划结构基因组学功...     

从基因组学到蛋白质组学

介绍了蛋白质的概念,产生背景,发展过程;比较了蛋白质组学与基因组学研究之间的差异;对结构蛋白质组学和功能蛋白质组学研究的内容以及相应的主要研究手段与技术加以简单评述,阐述了蛋白质组学研究的理论意义,应用前景及对国计民生的影响。     

结构基因组学研究概述

随着蛋白质数据库、基因组序列数据库和自动化技术的迅速发展,结构基因组学作为新的预测蛋白质结构的技术显得越发重要。本文对结构基因组学的产生发展进行概述,分别介绍结构基因组技术的功能、实验流程、蛋白质功能的预测方法,并对该学科发展进行了展望。     

三维基因组学与精准生物学

三维基因组学是以研究真核生物核内基因组空间构象,及其对不同基因转录调控的生物学效应为主要研究内容的一个新的学科方向;也是后基因组学时代研究的一个热门领域。它的研究重点是空间构象与基因转录调控间的关系。通过三维基因组学技术,科学家将能对基因组的折叠和空间构象、转录调控机制、复杂生物学性状、信号传导通路和基因组的运行机制等一系列重要问题进行更深入的探讨和研究,为系统解读生命百科全书和精准生物学的实施奠定坚实基础。本文综述了目前三维基因组学研究领域中的主要技术、研究现状、科研进展、存在问题、未来及与精准生物学的关系等内容。以期能较系统地展示三维基因组学取得的一系列成果,解读从三维空间构象信息到不同基因功能研究的路径,精准决定在转录调控网络中不同基因表达的时空特异性的可能模式。     

微量元素蛋白质组的比较基因组学研究

微量元素指需要量很少（人体中含量在0．01％以下）,但却是所有生物体所必需的元素。它们参与了生物体中各种复杂的生物过程,因此不同生物必须依赖相应的微量元素才能生存。过去大量的工作主要放在微量元素代谢通路和微量元素结合蛋白的实验研究上,由此凸显出微量元素对生命的重要性。然而,微量元素的计算生物学研究工作却非常有限。着重介绍当前利用比较基因组学的理论和方法来研究不同微量元素的利用、代谢、功能和进化方面问题的最新进展。对于所讨论的元素,大多数利用它们的蛋白已经基本确定,并且这些蛋白对于特定元素的依赖性也是非常保守的。通过比较基因组学分析,有助于帮助我们进一步认识微量元素领域很多基本问题（如在古菌、细菌和真核生物中的代谢、功能和动态进化规律等）及其重要特征。     

从蛋白质基因组学视角出发的精准肿瘤学

癌症是一种机制复杂的异质性疾病,需要有针对性的精准医疗策略。精准医疗的发展离不开基因组学的飞速发展,但基因组学在分子表型分析中具有一定的局限性,蛋白质基因组学应运而生。蛋白质基因组学是蛋白质组学和基因组学的融合学科。文中描述了基因组学分析的局限性,强调了蛋白质基因组学的重要性,旨在从蛋白质基因组的视角重新了解精准肿瘤学。此外,还简要介绍了蛋白质基因组学在精准肿瘤学中的应用,对相关的公共数据项目进行了描述,最后,提出了现阶段需要克服的困难。     

林木基因组学研究进展

林木基因组学研究进展迅速。结构基因组学方面,已构建了近40个主要造林树种的遗传连锁图谱,在不同树种中定位了30余个重要的数量性状位点,在部分树种中开展了基因组比较和综合图谱构建研究,杨树的全基因组测序已经完成,桉树的全基因组测序正在进行。功能基因组学方面,已分析了主要造林树种多种组织的转录组EST序列,对林木次生生长与木材形成、开花和抗寒性的形成等过程开展了功能基因组学研究。另外,探讨了林木基因组学研究的发展趋势,以期为我国林木基因组学研究提供有益的参考。     

Unique opportunities for NMR methods in structural genomics

This Perspective, arising from a workshop held in July 2008 in Buffalo NY, provides an overview of the role NMR has played in the United States Protein Structure Initiative (PSI), and a vision of how NMR will contribute to the forthcoming PSI-Biology program. NMR has contributed in key ways to structure production by the PSI, and new methods have been developed which are impacting the broader protein NMR community.     

Towards miniaturization of a structural genomics pipeline using micro-expression and microcoil NMR

In structural genomics centers, nuclear magnetic resonance (NMR) screening is in increasing use as a tool to identify folded proteins that are promising targets for three-dimensional structure determination by X-ray crystallography or NMR spectroscopy. The use of 1D ¹H NMR spectra or 2D [¹H,¹⁵N]-correlation spectroscopy (COSY) typically requires milligram quantities of unlabeled or isotope-labeled protein, respectively. Here, we outline ways towards miniaturization of a structural genomics pipeline with NMR screening for folded globular proteins, using a high-density micro-fermentation device and a microcoil NMR probe. The proteins are micro-expressed in unlabeled or isotope-labeled media, purified, and then subjected to 1D ¹H NMR and/or 2D [¹H,¹⁵N]-COSY screening. To demonstrate that the miniaturization is functioning effectively, we processed nine mouse homologue protein targets and compared the results with those from the “macro-scale” Joint Center of Structural Genomics (JCSG) high-throughput pipeline. The results from the two pipelines were comparable, illustrating that the data were not compromised in the miniaturized approach.     

Parallel screening and optimization of protein constructs for structural studies

A major challenge in structural biology remains the identification of protein constructs amenable to structural characterization. Here, we present a simple method for parallel expression, labeling, and purification of protein constructs (up to 80 kDa) combined with rapid evaluation by NMR spectroscopy. Our approach, which is equally applicable for manual or automated implementation, offers an efficient way to identify and optimize protein constructs for NMR or X‐ray crystallographic investigations.     

Automated search of natively folded protein fragments for high-throughput structure determination in structural genomics

Structural genomic projects envision almost routine protein structure determinations, which are currently imaginable only for small proteins with molecular weights below 25,000 Da. For larger proteins, structural insight can be obtained by breaking them into small segments of amino acid sequences that can fold into native structures, even when isolated from the rest of the protein. Such segments are autonomously folding units (AFU) and have sizes suitable for fast structural analyses. Here, we propose to expand an intuitive procedure often employed for identifying biologically important domains to an automatic method for detecting putative folded protein fragments. The procedure is based on the recognition that large proteins can be regarded as a combination of independent domains conserved among diverse organisms. We thus have developed a program that reorganizes the output of BLAST searches and detects regions with a large number of similar sequences. To automate the detection process, it is reduced to a simple geometrical problem of recognizing rectangular shaped elevations in a graph that plots the number of similar sequences at each residue of a query sequence. We used our program to quantitatively corroborate the premise that segments with conserved sequences correspond to domains that fold into native structures. We applied our program to a test data set composed of 99 amino acid sequences containing 150 segments with structures listed in the Protein Data Bank, and thus known to fold into native structures. Overall, the fragments identified by our program have an almost 50% probability of forming a native structure, and comparable results are observed with sequences containing domain linkers classified in SCOP. Furthermore, we verified that our program identifies AFU in libraries from various organisms, and we found a significant number of AFU candidates for structural analysis, covering an estimated 5 to 20% of the genomic databases. Altogether, these results argue that methods based on sequence similarity can be useful for dissecting large proteins into small autonomously folding domains, and such methods may provide an efficient support to structural genomics projects.     

Computer-aided NMR assay for detecting natively folded structural domains

Structural genomics projects require strategies for rapidly recognizing protein sequences appropriate for routine structure determination. For large proteins, this strategy includes the dissection of proteins into structural domains that form stable native structures. However, protein dissection essentially remains an empirical and often a tedious process. Here, we describe a simple strategy for rapidly identifying structural domains and assessing their structures. This approach combines the computational prediction of sequence regions corresponding to putative domains with an experimental assessment of their structures and stabilities by NMR and biochemical methods. We tested this approach with nine putative domains predicted from a set of 108 Thermus thermophilus HB8 sequences using PASS, a domain prediction program we previously reported. To facilitate the experimental assessment of the domain structures, we developed a generic 6-hour His-tag-based purification protocol, which enables the sample quality evaluation of a putative structural domain in a single day. As a result, we observed that half of the predicted structural domains were indeed natively folded, as judged by their HSQC spectra. Furthermore, two of the natively folded domains were novel, without related sequences classified in the Pfam and SMART databases, which is a significant result with regard to the ability of structural genomics projects to uniformly cover the protein fold space.     

生理学与基因组学:走向系统生物学

近十年来,生理学与基因组学达到了空前的融合。尽管生理基因组学还是一个非常年轻的研究领域,系统生物学概念的引入必将推进生理基因组学达到全新的水平。本文概要地叙述了这个令人振奋的生理科学的新时代给生理学家带来的机遇和挑战,并以我们自己近十年来的经验为例,讨论了怎样通过扩展和延伸生理学与基因组学的结合,从而对生物学得到系统的理解。     

Solution NMR structure determination of proteins revisited

This 'Perspective' bears on the present state of protein structure determination by NMR in solution. The focus is on a comparison of the infrastructure available for NMR structure determination when compared to protein crystal structure determination by X-ray diffraction. The main conclusion emerges that the unique potential of NMR to generate high resolution data also on dynamics, interactions and conformational equilibria has contributed to a lack of standard procedures for structure determination which would be readily amenable to improved efficiency by automation. To spark renewed discussion on the topic of NMR structure determination of proteins, procedural steps with high potential for improvement are identified.     

Protein family clustering for structural genomics

A major goal of structural genomics is the provision of a structural template for a large fraction of protein domains. The magnitude of this task depends on the number and nature of protein sequence families. With a large number of bacterial genomes now fully sequenced, it is possible to obtain improved estimates of the number and diversity of families in that kingdom. We have used an automated clustering procedure to group all sequences in a set of genomes into protein families. Bench-marking shows the clustering method is sensitive at detecting remote family members, and has a low level of false positives. This comprehensive protein family set has been used to address the following questions. (1) What is the structure coverage for currently known families? (2) How will the number of known apparent families grow as more genomes are sequenced? (3) What is a practical strategy for maximizing structure coverage in future? Our study indicates that approximately 20% of known families with three or more members currently have a representative structure. The study indicates also that the number of apparent protein families will be considerably larger than previously thought: We estimate that, by the criteria of this work, there will be about 250,000 protein families when 1000 microbial genomes have been sequenced. However, the vast majority of these families will be small, and it will be possible to obtain structural templates for 70-80% of protein domains with an achievable number of representative structures, by systematically sampling the larger families.     

Structure-based protein NMR assignments using native structural ensembles

An important step in NMR protein structure determination is the assignment of resonances and NOEs to corresponding nuclei. Structure-based assignment (SBA) uses a model structure ("template") for the target protein to expedite this process. Nuclear vector replacement (NVR) is an SBA framework that combines multiple sources of NMR data (chemical shifts, RDCs, sparse NOEs, amide exchange rates, TOCSY) and has high accuracy when the template is close to the target protein's structure (less than 2 A backbone RMSD). However, a close template may not always be available. We extend the circle of convergence of NVR for distant templates by using an ensemble of structures. This ensemble corresponds to the low-frequency perturbations of the given template and is obtained using normal mode analysis (NMA). Our algorithm assigns resonances and sparse NOEs using each of the structures in the ensemble separately, and aggregates the results using a voting scheme based on maximum bipartite matching. Experimental results on human ubiquitin, using four distant template structures show an increase in the assignment accuracy. Our algorithm also improves the robustness of NVR with respect to structural noise. We provide a confidence measure for each assignment using the percentage of the structures that agree on that assignment. We use this measure to assign a subset of the peaks with even higher accuracy. We further validate our algorithm on data for two additional proteins with NVR. We then show the general applicability of our approach by applying our NMA ensemble-based voting scheme to another SBA tool, MARS. For three test proteins with corresponding templates, including the 370-residue maltose binding protein, we increase the number of reliable assignments made by MARS. Finally, we show that our voting scheme is sound and optimal, by proving that it is a maximum likelihood estimator of the correct assignments.