植物功能基因组学研究进展

植物基因组研究已经由以全基因组测序为目标的结构基因组学转向以基因功能鉴定为目标的功能基因组学研究.本简要介绍了植物功能基因组的主要研究方法,如基因表达系列分析法、表达序列标签法、差异表达谱基因芯片法、蛋白质组学分析法以及生物信息学等及其研究现状,并展望了植物功能基因组学的应用前景.     

功能基因组学研究概述

21世纪是生物时代和信息时代,基因组学的研究已从结构基因组学转向功能基因组学,功能基因组学时代对于基因功能的研究也由单一基因转向大规模、批量分析。对功能基因组学及相关学科的概念作了概述,综述了功能基因组学的研究内容与方法,主要包括应用差异显示反转录PCR、基因表达序列分析（SAGE）、微点阵、蛋白质组学和生物信息学等方法来研究基因组表达概况、基因组多样性和模式生物学等。     

植物功能基因组研究进展

随着植物基因组计划的深入,植物基因组学研究的重点已经转变为基因组功能的研究,即利用基因组序列的信息和高通量的系统分析技术,在基因组水平研究植物结构和组织与植物功能在细胞、有机体和进化上的关系.对功能基因组学研究的内容、方法以及最新研究进展进行了综述.     

泛基因组及其在植物功能基因组学研究中的应用

参考基因组是现代功能基因组学的核心框架,以此为基础的现代基因组学技术在过去20年对植物遗传变异发掘、功能基因克隆等研究起了巨大的推动作用。然而,越来越多的研究发现,单一或少数参考基因组不能完整代表和呈现物种或特定群体内的所有基因组变异,因此其在功能基因组学研究中应用存在很大的局限性,甚至会导致错误的结果。泛基因组是指物种或特定群体内全部基因或基因组序列的总和。泛基因组通过完整捕获和呈现群体内全部的基因或基因组序列,代替单一参考基因组应用于功能基因组学研究,可以突破单一参考基因组的局限性。泛基因组在植物功能基因组学研究中有广泛的应用,以泛基因组为基础,结合最新的基因组学技术可以高效、精准鉴定种质资源中的遗传变异。泛基因组研究是目前植物基因组学研究的前沿和热点。本文综述了泛基因组概念的起源和发展,泛基因组组装的技术和策略,以及泛基因组在植物基因组学研究和分子育种方面的应用和最新进展,最后对植物泛基因组研究目前存在的问题和今后研究方向进行了展望。本综述可为植物泛基因组研究和应用提供参考。     

植物功能基因组学的研究策略

植物基因组学是一门研究植物基因组内基因与遗传信息是如何有机结合并如何决定其功能的一门科学。随着植物基因组计划的顺利进行 ,植物基因组学的研究已从结构基因组学转向功能基因组学。近年来 ,多采用高通量 (highthroughput,HTP)序列分析技术、大规模实验技术及计算机统计分析技术研究植物基因组功能。概述了植物功能基因组学的最新进展。     

主要禾谷类作物比较基因组学研究策略与进展

随着拟南芥、水稻等模式植物基因组测序计划的完成, 比较基因组学作为一门新兴学科, 近年来发展迅速, 为植物基因组的进化、结构和功能研究开辟了新的途径。文章综述了比较基因组学在作物比较遗传作图、基因结构区域的微共线性、ESTs和蛋白质水平的比较以及基于比较基因组学的基因和QTL的克隆等方面内容与研究进展, 分析了不同水平上比较基因组学研究策略的原理、特点、可行性, 以期为利用模式生物的基因和基因组数据、采用比较基因组学策略克隆作物重要性状功能基因、阐明基因组结构与进化提供帮助。     

小麦的比较基因组学和功能基因组学

小麦是异源多倍体植物,具有大的染色体组,并且基因组中重复序列所占比例较高,这些特征限制了小麦基因组研究的进展。比较基因组学方法为运用模式植物进行小麦基因组学研究提供了一个操作平台。功能基因组学的研究集中于基因组中转录表达的部分,基因功能的确定是功能基因组学研究的主要内容。对比较基因组学在小麦基因组研究中的应用和小麦功能基因组学的研究内容和方法进行了综述。     

嗜酸氧化亚铁硫杆菌基因组学研究进展

嗜酸氧化亚铁硫杆菌(Acidithiobacillus ferrooxidan,A.ferrooxidans)广泛存在于酸性矿物废水中,与生物冶金和环境净化紧密相关。不同来源嗜酸氧化亚铁硫杆菌全基因组的测序,为我们利用比较基因组学和功能基因组学的方法去洞察嗜酸氧化亚铁硫杆菌功能基因,提供了坚实的研究基础和丰富的科研信息。简述了嗜酸氧化亚铁硫杆菌基因组学的基本特征;从比较基因组学和功能基因组学发现了嗜酸氧化亚铁硫杆菌菌株基因组水平的差异;通过生物信息学概述了该菌的铁和硫代谢机制,并从细菌的功能基因组学对其在生物冶金与环境治理等应用进行了展望。     

高效特异的CRISPR/dCas9转录激活系统——flySAM系统

正随着人类等物种的基因组计划的完成,关于基因组的研究已经从结构基因组学转向了功能基因组学。将基因组的序列信息转化为功能信息,解密生命的密码,完成基因组的功能注释对于全面理解生长发育、疾病衰老、学习记忆等过程具有重大意义。黑腹果蝇(Drosophila melanogaster)具有易于饲养、     

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.     

Use of genome information for the study of the pathogenesis of fungal infections and the development of diagnostic tools

One of the most exciting advances in Mycology is the application of genomic approaches. The advent of genomics, together with post-genomic studies, promises to revolutionize the studies on the pathogenesis of fungal infections. Approaches include comparative genomics to identify sequences that contribute to infection and disease and functional genomics and proteomics to analyze global patterns of gene and protein expression involved in fungal pathogenesis.     

基于mRNA水平的差异表达基因筛选技术

随着分子生物学技术的深入发展,基因组研究重点已经由基因组测序转向基因功能鉴定,即由结构基因组学向功能基因组学转变。研究获得不同处理下基因的差异表达谱是功能基因组学的重要一环,目前已经有多种检测基因差异表达的技术可供选用。在减法杂交技术和PCR基础上发展起来的DDRT—PCR、cDNA—RDA、cDNA—AFLP和SSH技术因其实用性而得到广泛的应用,并取得了令人满意的结果。     

Finding and decrypting of promoters contributes to the elucidation of gene function

The combination of full-scale genomic sequencing with high throughput expression analysis provides a new and largely unexploited basis for in silico functional genomics. Recent break through developments in locating and analyzing promoters now allow extending functional genomics in silico far beyond identification of protein sequences into the complex regulatory structures and mechanisms of the genome. However, only first examples of this new type of approach are emerging at present and intensive further developments of bioinformatics tools will be required before such analysis can become large-scale routine in genomic sequence analysis. Nevertheless, the door to a new dimension of functional analysis of the genomic sequence is open. Finally, only the tight integration of the enormous amount of knowledge gained from proteins sequence analysis with the complementary information about gene regulation will afford us with a more complete picture of the networks than constitute life.     

Genetical genomics in livestock: potentials and pitfalls

Genetical genomics combines gene mapping and gene expression approaches to identify loci controlling gene expression (eQTLs) that may underlie functional trait variation. The combination of genomic tools has great potential to facilitate dissection of complex traits, but studies need careful design and interpretation. Here we explore both the potential and the pitfalls of this approach with illustrations from actual studies. There are now an appreciable number of studies in model species and even humans demonstrating the feasibility of genetical genomics. However, most studies are too limited in size and design to unlock the full potential of the approach. Limited statistical power of studies exacerbates the problem of detection of false-positive eQTL and some reported results should be interpreted with caution. As one approach to more successful implementation of genetical genomics, we propose to combine expression studies with fine mapping of functional trait loci. This synergistic approach facilitates the implementation of genetical genomics for species without inbred resources but is equally applicable to model species. These properties make it particularly suitable for livestock populations where many QTL are already in the public domain and potentially very large pedigreed populations can be accessed.     

大麦基因组和分子育种研究进展

大麦(Hordeum vulgare L.)是世界上重要的谷类作物之一,其二倍体特性使其成为麦类作物基因组研究的重要材料。随着大量分子标记图谱、BACs文库、突变集合和DNA阵列技术的应用,大麦基因组测序工作已不断深入,越来越多的大麦基因组信息使综合分析大麦基因组结构和功能,了解基因表达网络同重要农艺性状之间的关系成为可能。就大麦基因组研究内容,如ESTs系统、物理图谱的构建、功能基因组学研究和大麦分子育种研究作简要综述,为进一步阐述大麦基因组结构和功能特性,提高大麦分子育种能力提供理论依据。     

Functional genomics of wood quality and properties

Genomics promises to enrich the investigations of biology and biochemistry. Current advancements in genomics have major implications for genetic improvement in animals, plants, and microorganisms, and for our understanding of cell growth, development, differentiation, and communication. Significant progress has been made in the understanding of plant genomics in recent years, and the area continues to     

Genomic expression discovery predicts pathways and opposing functions behind phenotypes

Discovering states of genetic expression that are true to a high degree of certainty is likely to predict gene function behind biological phenotypes. The states of expression (up- or down-regulated) of 19200 cDNAs in 10 meningiomas are compared with normal brain by an algorithm that detects only 1 false measurement per 192000; 364 genes are discovered. The expression data accurately predict activation of signaling pathways and link gene function to specific phenotypes. Meningiomas appear to acquire aberrant phenotypes by disturbing the balanced expression of molecules that promote opposing functions. The findings expose interconnected genes and propose a role of genomic expression discovery in functional genomics of living systems.     

GOing from functional genomics to biological significance

The chicken genome is sequenced and this, together with microarray and other functional genomics technologies, makes post-genomic research possible in the chicken. At this time, however, such research is hindered by a lack of genomic structural and functional annotations. Bio-ontologies have been developed for different annotation requirements, as well as to facilitate data sharing and computational analysis, but these are not yet optimally utilized in the chicken. Here we discuss genomic annotation and bio-ontologies. We focus specifically on the Gene Ontology (GO), chicken GO annotations and how these can facilitate functional genomics in the chicken. The GO is the most developed and widely used bio-ontology. It is the de facto standard for functional annotation. Despite its critical importance in analyzing microarray and other functional genomics data, relatively few chicken gene products have any GO annotation. When these are available, the average quality of chicken gene products annotations (defined using evidence code weight and annotation depth) is much less than in mouse. Moreover, tools allowing chicken researchers to easily and rapidly use the GO are either lacking or hard to use. To address all of these problems we developed ChickGO and AgBase. Chicken GO annotations are provided by complementary work at MSU-AgBase and EBI-GOA. The GO tools pipeline at AgBase uses GO to derive functional and biological significance from microarray and other functional genomics data. Not only will improved genomic annotation and tools to use these annotations benefit the chicken research community but they will also facilitate research in other avian species and comparative genomics.