Name: comprehensive workflow for the genome-wide identification and expression meta-analysis of the atl e3 ubiquitin ligase gene family in grapevine
Uploaded: 2017-12-22T12:30:00.000+00:00
Duration: 10 min 40 s
Description: Watch this Scientific Journal Video about Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine at JoVE.com

这项工作得到了维罗纳大学在联合项目2014的框架内的支持 (在葡萄藤中的 ATL 基因家族的特性及其对霜霉病霜霉病的抗性)。

<ol>
	<li>Jaillon, O., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+grapevine+genome+sequence+suggests+ancestral+hexaploidization+in+major+angiosperm+phyla.">The grapevine genome sequence suggests ancestral hexaploidization in major angiosperm phyla.</a> Nature. 449 (7161), 463-467 (2007).</li><li>Adam-Blondon, A. -. F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Genetics, Genomics, and Breeding of Grapes. , 211-234 (2011).</li><li>Chen, L., Hellmann, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Plant+E3+Ligases:+Flexible+Enzymes+in+a+Sessile+World.">Plant E3 Ligases: Flexible Enzymes in a Sessile World.</a> Mol. Plant. 6 (5), 1388-1404 (2013).</li><li>Vierstra, R. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+ubiquitin-26S+proteasome+system+at+the+nexus+of+plant+biology.">The ubiquitin-26S proteasome system at the nexus of plant biology.</a> Nat. Rev. Mol. Cell Biol. 10 (6), 385-397 (2009).</li><li>Serrano, M., Parra, S., Alcaraz, L. D., Guzm&#225;n, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+ATL+Gene+Family+from+Arabidopsis+thaliana+and+Oryza+sativa+Comprises+a+Large+Number+of+Putative+Ubiquitin+Ligases+of+the+RING-H2+Type.">The ATL Gene Family from Arabidopsis thaliana and Oryza sativa Comprises a Large Number of Putative Ubiquitin Ligases of the RING-H2 Type.</a> J. Mol. Evol. 62 (4), 434-445 (2006).</li><li>Aguilar-Hern&#225;ndez, V., Aguilar-Henonin, L., Guzm&#225;n, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Diversity+in+the+Architecture+of+ATLs,+a+Family+of+Plant+Ubiquitin-Ligases,+Leads+to+Recognition+and+Targeting+of+Substrates+in+Different+Cellular+Environments.">Diversity in the Architecture of ATLs, a Family of Plant Ubiquitin-Ligases, Leads to Recognition and Targeting of Substrates in Different Cellular Environments.</a> PLoS One. 6 (8), e23934 (2011).</li><li>Guzm&#225;n, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+prolific+ATL+family+of+RING-H2+ubiquitin+ligases.">The prolific ATL family of RING-H2 ubiquitin ligases.</a> Plant Signal Behav. 7 (8), 1014-1021 (2012).</li><li>Grimplet, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+grapevine+gene+nomenclature+system.">The grapevine gene nomenclature system.</a> BMC Genomics. 15, 1077 (2014).</li><li>Prince, V. E., Pickett, F. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Splitting+pairs:+the+diverging+fates+of+duplicated+genes.">Splitting pairs: the diverging fates of duplicated genes.</a> Nat. Rev. Genet. 3 (11), 827-837 (2002).</li><li>Magadum, S., Nerjee, U., Murugan, P., Gangapur, D., Ravikesavan, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gene+duplication+as+a+major+force+in+evolution.">Gene duplication as a major force in evolution.</a> J. Gen. 92 (1), 155-161 (2013).</li><li>Wang, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Patterns+of+Gene+Duplication+and+Their+Contribution+to+Expansion+of+Gene+Families+in+Grapevine.">Patterns of Gene Duplication and Their Contribution to Expansion of Gene Families in Grapevine.</a> Plant Mol. Biol. Rep. 31 (4), 852-861 (2013).</li><li>Fasoli, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Grapevine+Expression+Atlas+Reveals+a+Deep+Transcriptome+Shift+Driving+the+Entire+Plant+into+a+Maturation+Program.">The Grapevine Expression Atlas Reveals a Deep Transcriptome Shift Driving the Entire Plant into a Maturation Program.</a> Plant Cell. 24 (9), 3489-3505 (2012).</li><li>. BLAST2.6.0 Available from: <a target="_blank" href="https://blast.ncbi.nlm.nih.gov/Blast.cgi">https://blast.ncbi.nlm.nih.gov/Blast.cgi</a> (2016)</li><li>. Vitis vinifera cv. Corvina gene expression Atlas Available from: <a target="_blank" href="https://www.researchgate.net/publication/273383414_54sample_datamatrix_geneIDs_Fasoli2012">https://www.researchgate.net/publication/273383414_54sample_datamatrix_geneIDs_Fasoli2012</a> (2015)</li><li>. Sequence Read Archive (SRA) Available from: <a target="_blank" href="https://www.ncbi.nlm.nih.gov/sra">https://www.ncbi.nlm.nih.gov/sra</a> (2017)</li><li>Bolger, A. M., Lohse, M., Usadel, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Trimmomatic:+a+flexible+trimmer+for+Illumina+sequence+data.">Trimmomatic: a flexible trimmer for Illumina sequence data.</a> Bioinformatics. 30 (15), 2114-2120 (2014).</li><li>Langmead, B., Salzberg, S. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fast+gapped-read+alignment+with+Bowtie+2.">Fast gapped-read alignment with Bowtie 2.</a> Nat Meth. 9 (4), 357-359 (2012).</li><li>Anders, S., Pyl, P. T., Huber, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=HTSeq-a+Python+framework+to+work+with+high-throughput+sequencing+data.">HTSeq-a Python framework to work with high-throughput sequencing data.</a> Bioinformatics. 31 (2), 166-169 (2015).</li><li>. Version 3.4.1 Available from: <a target="_blank" href="https://www.r-project.org/">https://www.r-project.org/</a> (2017)</li><li>Ritchie, M. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=limma+powers+differential+expression+analyses+for+RNA-sequencing+and+microarray+studies.">limma powers differential expression analyses for RNA-sequencing and microarray studies.</a> Nucleic Acids Res. 43 (7), e47 (2015).</li><li>Love, M. I., Huber, W., Anders, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Moderated+estimation+of+fold+change+and+dispersion+for+RNA-seq+data+with+DESeq2.">Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.</a> Genome Biology. 15 (12), 550 (2014).</li><li>Ariani, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome-wide+characterisation+and+expression+profile+of+the+grapevine+ATL+ubiquitin+ligase+family+reveal+biotic+and+abiotic+stress-responsive+and+development-related+members.">Genome-wide characterisation and expression profile of the grapevine ATL ubiquitin ligase family reveal biotic and abiotic stress-responsive and development-related members.</a> Sci. Rep. 6, 38260 (2016).</li><li>Vitulo, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+deep+survey+of+alternative+splicing+in+grape+reveals+changes+in+the+splicing+machinery+related+to+tissue,+stress+condition+and+genotype.">A deep survey of alternative splicing in grape reveals changes in the splicing machinery related to tissue, stress condition and genotype.</a> BMC Plant Biol. 14 (1), 99 (2014).</li><li>Overbeek, R., Fonstein, M., D'Souza, M., Pusch, G. D., Maltsev, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+use+of+gene+clusters+to+infer+functional+coupling.">The use of gene clusters to infer functional coupling.</a> Proc. Natl. Acad. Sci. USA. 96 (6), 2896-2901 (1999).</li><li>Dalquen, D. A., Dessimoz, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bidirectional+Best+Hits+Miss+Many+Orthologs+in+Duplication-Rich+Clades+such+as+Plants+and+Animals.">Bidirectional Best Hits Miss Many Orthologs in Duplication-Rich Clades such as Plants and Animals.</a> Genome Biol. Evol. 5 (10), 1800-1806 (2013).</li><li>Remm, M., Storm, C. E. V., Sonnhammer, E. L. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automatic+clustering+of+orthologs+and+in-paralogs+from+pairwise+species+comparisons1.">Automatic clustering of orthologs and in-paralogs from pairwise species comparisons1.</a> J. Mol. Biol. 314 (5), 1041-1052 (2001).</li><li>Kaduk, M., Sonnhammer, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Improved+orthology+inference+with+Hieranoid+2.">Improved orthology inference with Hieranoid 2.</a> Bioinformatics. 33 (8), (2017).</li><li>Cramer, G. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transcriptomic+analysis+of+the+late+stages+of+grapevine+(Vitis+vinifera+cv.+Cabernet+Sauvignon)+berry+ripening+reveals+significant+induction+of+ethylene+signaling+and+flavor+pathways+in+the+skin.">Transcriptomic analysis of the late stages of grapevine (Vitis vinifera cv. Cabernet Sauvignon) berry ripening reveals significant induction of ethylene signaling and flavor pathways in the skin.</a> BMC Plant Biol. 14, 370 (2014).</li><li>Juretic, N., Hoen, D. R., Huynh, M. L., Harrison, P. M., Bureau, T. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+evolutionary+fate+of+MULE-mediated+duplications+of+host+gene+fragments+in+rice.">The evolutionary fate of MULE-mediated duplications of host gene fragments in rice.</a> Genome Res. 15 (9), 1292-1297 (2005).</li><li>Filichkin, S. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome-wide+mapping+of+alternative+splicing+in+Arabidopsis+thaliana.">Genome-wide mapping of alternative splicing in Arabidopsis thaliana.</a> Genome Res. 20 (1), 45-58 (2010).</li><li>Quesada, V., Macknight, R., Dean, C., Simpson, G. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Autoregulation+of+FCA+pre-mRNA+processing+controls+Arabidopsis+flowering+time.">Autoregulation of FCA pre-mRNA processing controls Arabidopsis flowering time.</a> EMBO J. 22 (12), 3142-3152 (2003).</li><li>Wong, D. C. J., Gutierrez, R. L., Gambetta, G. A., Castellarin, S. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome-wide+analysis+of+cis-regulatory+element+structure+and+discovery+of+motif-driven+gene+co-expression+networks+in+grapevine.">Genome-wide analysis of cis-regulatory element structure and discovery of motif-driven gene co-expression networks in grapevine.</a> DNA Res. 24 (3), 311-326 (2017).</li><li>Wong, D. C. J., Matus, J. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Constructing+Integrated+Networks+for+Identifying+New+Secondary+Metabolic+Pathway+Regulators+in+Grapevine:+Recent+Applications+and+Future+Opportunities.">Constructing Integrated Networks for Identifying New Secondary Metabolic Pathway Regulators in Grapevine: Recent Applications and Future Opportunities.</a> Front. Plant Sci. 8, 505 (2017).</li></ol>

作者没有什么可透露的。

在基因组时代, 许多植物物种被深深地刻画了。这些信息是初步的功能研究, 并提供一个框架, 进一步调查不同成员在一个家庭中的作用。在这方面, 还需要一个命名系统, 允许唯一地识别家庭中的每个成员, 避免在不同的研究组独立于不同的基因分配姓名时可能出现的冗余和混乱。
经过深思熟虑的考虑, 葡萄科学界同意命名的葡萄基因在一个家庭的基础上与拟南芥基因的相似性, 并建立了一系列的规则, 必须用于描述新的基因家族的葡萄,基本上从系统发育比较葡萄和拟南芥家族成员的核苷酸序列8。因此, 只有在拟南芥中已经标注并正确命名的基因才能在葡萄藤命名中使用。因此, 本文所描述的拟南芥葡萄 orthologues 的鉴定方法, 仅是为了满足指定正确的葡萄基因家族命名的要求。然而, 对于其他植物物种, 替代方法可能是一种选择。例如, orthology 可以被推断使用双向爆炸命中 (BBH), 在那里 orthologues 被定义作为两个种类更相似的基因的对 (即, 与最高的对准线比分) 对彼此比其他基因在另一个种类44。然而, 这种方法可能会错过许多 orthologues 的情况下, 基因重复率高, 如在植物和动物的45。此外, 在 atl 编码基因的情况下, BBH 可能会检索缺乏精确的 atl 型 RING-H2 结构 (包括脯氨酸残留物) 或未在拟南芥中注明为 ATLs 的基因。虽然从进化论的角度来看, 这种搜索可能是相关的, 但没有标注的 orthologues 的检索将不会满足葡萄的 ATL 基因家族注释和命名的范围, 而 orthologues 不被注释为 ATLs不能用来命名葡萄家族成员。另一种可能性是根据氨基酸而不是核苷酸序列来推断 orthology, 使用 InParanoid46, 或者最近的 Hieranoid 247, 虽然这些工作流不是科学界明确推荐的。
表达 meta 分析, 可以定义为一个系统的方法来研究和组合不同的公开可用的数据集的表达资料, 允许强调共享和不同的分子机制在各种条件。因此, 从多个 large-scale 组实验中整合基因表达信息, 可以通过在实验中定义家庭成员的表达谱, 从而改善基因家族的特征, 从而减少实验特定因素的影响, 支持在特定过程中假定基因功能的更稳健假设。然而, 利用微阵列数据需要将表达数据与不同的平台相结合, 考虑到它们自身的局限性。例如, 在小道消息 Nimblegen 微阵列平台中, 在阵列 (约1.3万基因) 上所代表的相应基因中, 有相当比例的 probesets 有可能 cross-hybridization 问题48。在葡萄树的情况下, 15 基因可能会受到这种现象的影响。不过, 正如克莱默et al.所讨论的48, 同一探针的高度相似基因家族成员的交叉可以提供有关表达的有趣信息, 在特定条件下, 不仅是单个基因, 而是两个以上基因共享高序列相似性, 从而可能共享目标和功能。与微阵列数据集相关的另一个潜在问题是微阵列平台的表达检测限制, 它们并不十分敏感。为了解决这两个问题, i. e., cross-hybridization 和信号灵敏度, 一个可能的解决方案可能是只考虑 RNAseq 表达式数据集。然而, 从许多不同的研究中 RNAseq 数据的 meta 分析可能会耗费大量的时间, 需要大量的计算资源和高的专业知识。
虽然这里提出的方法是详尽无遗的, 但可以肯定地补充其他分析。首先, 为了进一步了解植物基因家族成员之间的分子进化和亲缘关系, 系统进化分析可以通过家庭成员的多序列排列来扩展生成系统树从几个植物种类。也可以计算家族基因的进化时间, 在进化过程中对它们同义和同义替代率的估计, 通过确定值 Ks (在给定时间) 和 Ka (同一期间内每个同义站点的同义替换数)。Ka/Ks 比率是用来推断基因重复事件的机制后, 从他们的祖先分歧。ka/ks 值 = 1 建议中性选择, ka/ks 值和 #60; 1 建议净化选择, 和 ka/ks 值的和 #62; 1 建议积极选择49。此外, 如果基因结构分析揭示了内含子的存在, 基因家族的表征可以进一步扩展到其他剪接变体的检测。事实上, 基于对不同组织的 RNA 序列数据的深入调查, 压力条件和基因型43, 21 (96) ATLs 是替代剪接事件的强有力候选者, 这些 ATLs 的潜在数量从2到16不等 (见补充表 1)。替代的成绩单经常产生蛋白质异构体, 不同的氨基酸序列, 这些变化可能会改变细胞性质的蛋白质, 并可能导致改变从微妙的调制功能丧失的基因产品。为此, 可选剪接事件参与了重要的植物功能, 包括应力响应, 抗病性, 光合作用和开花50,51。ATL 基因启动子信息的集成包含假定的cis-管理元素52或查找分子 (,如, rna 和长编码 RNA) 可能目标 ATLs53也可以补充揭示了对葡萄 ATLs 的复杂分子调控和相互作用的系统洞察。
最后, 选择的分析, 以及适用的程序来表征一个新的基因家族的植物物种主要是由科学的社区规则和范围的基因家族鉴定。重要的是要记住可能的后续调查步骤, 这将利用这组信息, 其中包括植物物种之间的基因进化, 基因组结构描述, 或可靠的候选人选择在功能研究.

在过去的十年中, 对葡萄基因组学进行了大量的研究。葡萄是一种公认的经济相关作物, 它已成为研究果实发育和木本植物对生物和非生物学胁迫反应的模型。在此上下文中,葡萄亚种cv. PN40024 基因组在 2007年1及其更新版本2中的发布导致了 "学" 数据的快速积累和大量高通量的研究。根据所公布的序列数据, 对某一特定基因家族 (通常由分享保守主题的蛋白质、结构和/或功能相似性和进化关系) 的综合分析, 现在可以进行, 以揭示其分子功能, 进化和基因表达谱。这些分析有助于理解基因家族如何控制整个基因组的生理过程。
植物生命周期的许多方面是由泛素介导的关键蛋白降解, 这需要一个 fine-tuned 的营业额, 以确保正常的细胞过程。泛素介导的降解过程的重要组成部分是 E3 泛素酶, 这是负责系统的灵活性, 由于具体目标的招聘3。因此, 这些酶代表一个巨大的基因家族, 约 1400 E3 连接编码基因预测在拟南芥基因组4, 每 E3 泛素连接作用于特定靶蛋白泛。尽管基质特异泛在植物细胞调控中的重要性, 但很少有人知道如何调节泛通路和目标蛋白只在少数情况下被识别。对这种特异性和调节机制的破译首先依赖于系统的不同组成部分的识别和定性, 特别是 E3 酶。在泛素酶中, ATL 亚科的特征是: 在a. 南芥中, 显示一个 RING-H2 手指域5,6, 其中一些在防御和荷尔蒙应答中扮演了一个角色7。
定义新基因家族成员的第一个关键步骤是对家庭特征的精确定义, 如一致主题、关键域和蛋白质序列特征。事实上, 基于爆炸分析的所有基因家族成员的可靠检索需要一些强制性的序列特性, 特别是蛋白质的功能/活动, 作为蛋白质的签名。这可以通过先前对其他植物物种的同一基因家族的描述来促进, 或者通过分析不同植物物种中属于同一家族的不同基因认定来分离共同的序列。然后, 家庭成员可以根据国际财团为某种特定植物所定的共同规则, 单独命名。例如, 在小道消息, 这种程序受到了葡萄基因注释 (sNCGGa) 的超级命名委员会的建议, 建立了一个系统系统树的构建, 包括五亚种和a. 南芥基因家族成员允许基于核苷酸序列的基因注释8。
染色体定位的家庭成员和基因重复调查允许突出的存在, 全基因组或串联复制基因。这种信息似乎有助于解开假定的基因功能, 因为它可能显示功能冗余或揭示不同的情况,即, non-functionalization, 新官能化, 或 sub-functionalization9。新的和 sub-functionalization 都是重要的事件, 创造了基因的新奇, 为植物适应变化的环境提供了新型的细胞组件10。特别是, 在葡萄基因组的进化过程中, 祖先基因的重复和新基因的产生是非常频繁的, 而新形成的基因则是来自葡萄的近端和串联重叠, 更有可能产生新函数11。
破译基因家族功能的另一个关键因素是组剖面。因此, 可以利用公共数据库访问大量的组数据, 从而利用 large-scale在 "硅片" 表达式分析中为基因家族成员分配假定函数。的确, 特定植物器官中某些基因的奇特表达或对某些压力的反应, 可以给出一些关于在定义条件下相应蛋白质的假定作用的提示, 并支持关于可能的假设sub-functionalization 重复的基因来应对不同的挑战。为此, 重要的是要考虑几个数据集: 这些可以已经可用的基因表达矩阵, 如葡萄器官的全基因组组图谱和发育阶段12, 或者可以通过以下方式生成ad hoc检索特定植物物种的组数据集的定义应力。此外, 一个简单的方法使用两个矩阵, 一个具有成对相似性的数据和另一个具有两两表达系数, 可以用来评价序列相似性和表达模式之间的关系在一个基因家族。
这项工作的目的是提供一个全球性的方法, 定义基因结构, 保守的蛋白质主题, 染色体位置, 基因重复, 和表达模式, 以及预测蛋白质本地化和磷酸化的网站, 以达到植物基因家族的详尽描述。这种综合的方法在这里适用于描述的 ATL E3 泛素连接家族的葡萄。根据 ATL 亚科成员在调控关键细胞过程中的新作用7, 这项工作可以很好地帮助识别功能性研究的强候选者, 并最终解开控制这一重要作物对其环境的适应。

<table><tbody><tr><td>Personal computer</td><td></td><td></td><td></td></tr><tr><td>Basic Local Alignment Search Tool (BLAST)</td><td></td><td></td><td>https://blast.ncbi.nlm.nih.gov/Blast.cgi</td></tr><tr><td>Molecular Evolutionary Genetics Analysis (MEGA)</td><td></td><td></td><td>http://www.megasoftware.net/</td></tr><tr><td>Motif-based sequence analysis tools (MEME)</td><td></td><td></td><td>http://meme-suite.org/</td></tr><tr><td>Geneious</td><td>Biomatters Limited</td><td></td><td>http://www.geneious.com/</td></tr><tr><td>ProtParam Tool</td><td></td><td></td><td>http://web.expasy.org/protparam/</td></tr><tr><td>ngLOC</td><td></td><td></td><td>http://genome.unmc.edu/ngLOC/index.html</td></tr><tr><td>TargetP v1.1 Server</td><td></td><td></td><td>http://www.cbs.dtu.dk/services/TargetP/</td></tr><tr><td>Protein Prowler</td><td></td><td></td><td>http://bioinf.scmb.uq.edu.au:8080/pprowler_webapp_1-2/</td></tr><tr><td>MUsite</td><td></td><td></td><td>http://musite.sourceforge.net/</td></tr><tr><td>Pfam</td><td></td><td></td><td>http://pfam.xfam.org/</td></tr><tr><td>TMHMM Server v. 2.0</td><td></td><td></td><td>http://www.cbs.dtu.dk/services/TMHMM/</td></tr><tr><td>ProtScale</td><td></td><td></td><td>http://web.expasy.org/protscale/</td></tr><tr><td>Grape Genome Database (CRIBI)</td><td></td><td></td><td>http://genomes.cribi.unipd.it/grape/</td></tr><tr><td>PhenoGram</td><td></td><td></td><td>http://visualization.ritchielab.psu.edu/phenograms/plot</td></tr><tr><td>MCScanX</td><td></td><td></td><td>http://chibba.pgml.uga.edu/mcscan2/</td></tr><tr><td>Interactive Tree Of Life (iTOL)</td><td></td><td></td><td>http://itol.embl.de/</td></tr><tr><td>UniProt</td><td></td><td></td><td>http://www.uniprot.org/</td></tr><tr><td>Phylogeny.fr</td><td></td><td></td><td>http://www.phylogeny.fr/index.cgi</td></tr><tr><td>MUSCLE</td><td></td><td></td><td>http://www.ebi.ac.uk/Tools/msa/muscle/</td></tr><tr><td>Gblocks Server</td><td></td><td></td><td>http://molevol.cmima.csic.es/castresana/Gblocks_server.html</td></tr><tr><td>&lt;em&gt;Vitis vinifera&lt;/em&gt; cv. Corvina gene expression Atlas datamatrix</td><td></td><td></td><td>https://www.researchgate.net/publication/273383414_54sample_&lt;br /&gt;datamatrix_geneIDs_Fasoli2012</td></tr><tr><td>Multi Experiment Viewer (MeV)</td><td></td><td></td><td>http://mev.tm4.org/#/welcome</td></tr><tr><td>Sequence Read Archive (SRA)</td><td></td><td></td><td>https://www.ncbi.nlm.nih.gov/sra</td></tr><tr><td>R</td><td></td><td></td><td>https://www.r-project.org/</td></tr><tr><td>EMBOSS Needle (EMBL-EBI)</td><td></td><td></td><td>http://www.ebi.ac.uk/Tools/psa/emboss_needle/</td></tr></tbody></table>

comprehensive workflow for the genome-wide identification and expression meta-analysis of the atl e3 ubiquitin ligase gene family in grapevine

家庭中基因的分类和命名可以显著地有助于描述编码蛋白质的多样性, 以及基于几个特征的家庭功能的预测, 如序列主题的存在或特定修饰修改的网站和家庭成员在不同条件下的表达谱。这项工作描述了一个关于基因家族特性的详细的协议。在这里, 这个过程被应用到在 Levadura 中的拟南芥 Tóxicos的描述 (ATL) E3 泛素连接家族的葡萄。这些方法包括家庭成员的全基因组鉴定、基因定位、结构和复制的特征、保守蛋白的分析、蛋白质定位和磷酸化的预测以及基因表达谱在不同的数据集的整个家族。这种程序可以扩展到根据实验目的进一步分析, 可适用于任何基因组的任何植物物种, 为其提供基因数据, 并提供有价值的信息, 以确定感兴趣的候选人为功能性研究, 提供对植物适应环境的分子机制的洞察。

VIT_05s0077g01970 基因, 被确定为最相似的a. 南芥 ATL2 (At3g16720) 通过 BLASTp 搜索, 被用作探针, 以调查的 ATL 家族成员在葡萄基因组 (五亚种cv 皮诺 PN40024)。PSI-爆炸分析在几个周期之后汇合, 揭示了属于葡萄树 ATL 基因家族 (图 1A) 的假定基因列表。在分析中确定的所有条目的肌肉对齐方式的视觉检查 (图 1B) 中, 对每个候选项的规范 RING-H2 域的存在进行了评估。在拟南芥5中, 只有那些含有正确间隔的保守氨基酸、两组氨酸残留物以及在第三半胱氨酸之前的脯氨酸残留的基因被视为 ATLs。共有96葡萄的基因满足了要求, 并考虑进一步的定性。对每个 ATL 家族成员进行了分析, 以定义该基因的特定特征和相应的编码蛋白,即, 除了 RING-H2、跨膜或疏水性丰富的区域外, 还有其他已知的域的存在, 亚细胞本地化和假定的磷酸化站点 (表 1和表 2)。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/56626/56626fig1.jpg"> 
图 1: PSI-爆炸调查和假定的葡萄 ATLs 的对准.(A) 第一个 PSI-爆炸迭代搜索的前10命中的截图, 使用蛋白质序列 VIT_05s0077g01970 作为诱饵。(B) 96 所选葡萄藤的部分对齐方式假定 ATLs 显示其 RING-H2 域以及使用分子生物学套件获得的相应徽标 (参见材料表)。转载自 Ariani et al.在创作共用归属4.0 国际许可证42下获得许可。<a href="//ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/56626/56626fig1large.jpg" target="_blank">请点击这里查看更大版本的这个数字。</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td colspan="2">名称</td>
			<td colspan="2">基因 ID</td>
			<td>基因长度 (bp)</td>
			<td>内含子数</td>
			<td>UniProt ID</td>
			<td>蛋白质长度 (aa)</td>
			<td>RING-H2 主题</td>
			<td>TM/H 域编号</td>
			<td>其他域</td>
		</tr>
		<tr>
			<td colspan="2">VviATL3</td>
			<td colspan="2">VIT_09s0002g00220</td>
			<td>1245</td>
			<td>0</td>
			<td>F6HXK6</td>
			<td>304</td>
			<td>PxC</td>
			<td>1</td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">VviATL4 [VviRHX1A]</td>
			<td colspan="2">VIT_15s0021g00890</td>
			<td>1827</td>
			<td>3</td>
			<td>D7SM36</td>
			<td>203</td>
			<td>PxC</td>
			<td>0</td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">VviATL18</td>
			<td colspan="2">VIT_11s0118g00780</td>
			<td>1113</td>
			<td>2</td>
			<td>F6HCI8</td>
			<td>193</td>
			<td>pc</td>
			<td>0</td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">VviATL23a</td>
			<td colspan="2">VIT_18s0001g01060</td>
			<td>935</td>
			<td>0</td>
			<td>F6H0E4</td>
			<td>114</td>
			<td>PxC</td>
			<td>0。5</td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">VviATL23b</td>
			<td colspan="2">VIT_18s0001g01050</td>
			<td>399</td>
			<td>0</td>
			<td>E0CQX3</td>
			<td>132</td>
			<td>PxC</td>
			<td>1</td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">VviATL24</td>
			<td colspan="2">VIT_17s0000g06460</td>
			<td>4466</td>
			<td>4</td>
			<td>D7SI89</td>
			<td>217</td>
			<td>PxC</td>
			<td>1</td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">VviATL27</td>
			<td colspan="2">VIT_00s0264g00020</td>
			<td>2554</td>
			<td>4</td>
			<td>D7T1R5</td>
			<td>235</td>
			<td>PxC</td>
			<td>1</td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">VviATL43</td>
			<td colspan="2">VIT_11s0052g00530</td>
			<td>1576</td>
			<td>2</td>
			<td>D7SQD9</td>
			<td>457</td>
			<td>PxC</td>
			<td>3</td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">VviATL54a</td>
			<td colspan="2">VIT_18s0001g06640</td>
			<td>3221</td>
			<td>1</td>
			<td>F6H0Y5</td>
			<td>405</td>
			<td>PxC</td>
			<td>1</td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">VviATL54b</td>
			<td colspan="2">VIT_03s0017g00670</td>
			<td>2774</td>
			<td>1</td>
			<td>F6HTI0</td>
			<td>427</td>
			<td>PxC</td>
			<td>1</td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">VviATL55 [VviRING1]</td>
			<td colspan="2">VIT_07s0191g00230</td>
			<td>1844</td>
			<td>0</td>
			<td>F6HRP9</td>
			<td>372</td>
			<td>PxC</td>
			<td>1</td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">VviATL63</td>
			<td colspan="2">VIT_06s0004g06930</td>
			<td>804</td>
			<td>0</td>
			<td>D7SJU6</td>
			<td>267</td>
			<td>PxC</td>
			<td>1</td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">VviATL65</td>
			<td colspan="2">VIT_03s0063g01890</td>
			<td>2068</td>
			<td>0</td>
			<td>F6HQI8</td>
			<td>396</td>
			<td>PxC</td>
			<td>1</td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">VviATL82</td>
			<td colspan="2">VIT_01s0026g02540</td>
			<td>820</td>
			<td>0</td>
			<td>F6HPQ9</td>
			<td>233</td>
			<td>pc</td>
			<td>0。5</td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">VviATL83</td>
			<td colspan="2">VIT_17s0000g08400</td>
			<td>1887</td>
			<td>0</td>
			<td>F6GSQ4</td>
			<td>143</td>
			<td>pc</td>
			<td>0</td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">VviATL84</td>
			<td colspan="2">VIT_06s0004g00120</td>
			<td>1853</td>
			<td>0</td>
			<td>F6GUP5</td>
			<td>368</td>
			<td>pc</td>
			<td>0。5</td>
			<td>zf-RING_3</td>
		</tr>
		<tr>
			<td colspan="2">VviATL85</td>
			<td colspan="2">VIT_12s0034g01400</td>
			<td>786</td>
			<td>0</td>
			<td>F6H965</td>
			<td>261</td>
			<td>pc</td>
			<td>0。5</td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">VviATL86</td>
			<td colspan="2">VIT_12s0034g01390</td>
			<td>1434</td>
			<td>1</td>
			<td>D7T016</td>
			<td>451</td>
			<td>pc</td>
			<td>0。5</td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">VviATL87</td>
			<td colspan="2">VIT_18s0001g03270</td>
			<td>1002</td>
			<td>0</td>
			<td>F6H0T2</td>
			<td>333</td>
			<td>pc</td>
			<td>0。5</td>
			<td>zf-RING_3</td>
		</tr>
		<tr>
			<td colspan="2">VviATL88</td>
			<td colspan="2">VIT_08s0040g00590</td>
			<td>1320</td>
			<td>0</td>
			<td>F6HQR2</td>
			<td>314</td>
			<td>pc</td>
			<td>0</td>
			<td>zf-RING_3</td>
		</tr>
	</tbody>
</table>
表 1: 前 20 VviATL 基因和相应蛋白质的序列特征.TM: 跨膜;H: 疏水性;0.5 表示一个或多个疏水区域的存在。转载自 Ariani et al.在创作共用归属4.0 国际许可证42下获得许可。
<img alt="Table 2" src="/files/ftp_upload/56626/56626table2.jpg"> 
表 2: 前20的详细信息VviATL基因定位v 亚种基因组、复制状态和 ATL 蛋白物理化学特性和位置(a) 由 Musite 预测的磷酸化点的数量;(b) 至少用两个软件获得的类似预测以黑体突出显示;ngLOC 用于默认设置, 而 TargetP v1.1 和蛋白质的潜行亚细胞定位使用的概率为0.5 的截止。校正, 核;麻省理工学院, 线粒体;智利, 叶绿体;聚乳酸、等离子体膜;S, 分泌通路 (存在一个信号肽);M, 线粒体;C、叶绿体;O 或-, 其他地点;nd, 未确定 (即, 低于阈值)。转载自 Ariani et al.在创作共用归属4.0 国际许可证42下获得许可。<a href="https://ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/56626/Table_2.xlsx">请单击此处下载此文件.</a>
系统发育分析, 包括被辨认的葡萄的核苷酸序列与参考A. 南芥atl 基因家族的序列一起被用于葡萄 atl 命名, 根据指南sNCGGa8。九十六和83核苷酸序列从v 亚种和一. 南芥, 分别受到了系统发展史. fr 管道获得可靠的系统进化树。后一个序列后来被用来注释和命名葡萄基因的基础上坚实的关系 (图 2)。按照这种方法, 13 的96葡萄 ATLs 收到一个特定的标识符, 考虑它们与a. 南芥ATL 的一对一 orthology。其他83基因的名称是根据系统进化树分配的, 从上到下进行递增编号, 从高于a. 南芥中使用的最高数字的 ATL 基因数开始。
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/56626/56626fig2.jpg"> 
图 2: v 亚种和一. 南芥ATL E3 泛素连接编码基因的系统进化树.无树是由发展史产生的. fr 套件 (v 亚种(绿色) 和A. 南芥的 83 ATL 基因在 UniProt 数据库中报告 (黄色)。从100引导复制中获得了分支支持值。红星表示在相应的蛋白质中存在一个 BCA2 锌指 (BZF) 域。转载自 Ariani et al.在创作共用归属4.0 国际许可证42下获得许可。<a href="//ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/56626/56626fig2large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
将 atl 编码基因映射到葡萄染色体上, 显示了整个基因组的广泛分布, 表明全基因组重复是葡萄树中 atl 基因家族扩展的主要进化力量。事实上, 31 ATLs 在同源染色体区域中发现, 可能来源于节段性或全基因组复制事件。此外, 同样的分析突出显示了13串联复制的基因, 一个近端复制, 和51分散重复 (图 3)。考虑到在 ATL 家族中有大量的重复基因, 我们进行了一次浓缩试验 (Fisher 的精确测试), 以检查基因组分离过程中重复基因的优先保留。使用p值和 #60; 0.001, 此测试证实了重复的 atl 基因保留的假设比随机预期的多, 这表明在葡萄的适应和进化过程中, atl 基因家族扮演了一个角色。
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/56626/56626fig3.jpg"> 
图 3: 葡萄树 ATL-编码基因分布在v 亚种染色体和复制状态.在数据库中有确切的染色体信息的96葡萄树的 ATL 基因被映射到 19 v 亚种染色体。颜色表示原始复制事件。垂直黑线和红线分别从串联重叠和全基因组复制中识别成对。转载自 Ariani et al.在创作共用归属4.0 国际许可证42下获得许可。<a href="//ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/56626/56626fig3large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
为了进一步研究 ATLs 在葡萄中的生物学功能, 在亚种cv. Corvina 全球基因表达图谱12中进行了 meta 分析。该数据集包括54不同葡萄器官的全基因组表达值和发育阶段, 并用于进行分层双聚类分析。结果不仅证实了所有 96 ATLs 在54组织/阶段中至少有一个表达, 而且还指出了五主要表达式配置文件的存在 (图 4A)。简单地, 星团 a 和 E 显示了相反的行为, 特别是第一个特点是一般下调的 ATL 基因在少年样本, 包括早期浆果阶段, 幼叶, 卷须, 花序, 和大部分的芽阶段。另一方面, 在同一个星团中, 成熟的浆果和收获后的枯萎阶段, 木本组织, 和后期的种子发育的 ATL 基因显示了一个主要的上调。在大多数样品中, 聚丙 downregulated 中的基因主要是上调的, 而在浆果发育后期, 群 D 中的 ATL 基因通常是在早期的。最后, 群集 B 没有在表达式配置文件中显示任何相关的变体。
采用类似的方法研究葡萄树 ATL 家族成员的表达, 以响应生物和非生物学的压力, 使用专门的数据集为此目的。从基因表达综合 (GEO) 和 ArrayExpress 等公共访问数据库中可以获得大量的表达数据, 从微阵列和 RNA 序列实验中得到。一旦收集和方便地正常化, 这些信息被用来进一步洞察 ATLs 在植物对胁迫的反应中的潜在作用。通过分析葡萄 ATLs 在生物胁迫下的表达谱, 发现62的96种转录记录在至少两个条件下显示出显著的调制 (log2 褶皱-变化 (FC) 和 #62; | 0.5 |), 有假发现率 (罗斯福) 和 #60; 0.05 (图 4B)。数字增加到81只考虑罗斯福门限在一个单独情况。这些结果强烈提示了 ATL 基因家族直接参与了对葡萄病原体的反应。特别是, 一组12基因 (VviATL3-27-54b-55-90-97-123-144-148-149-156) 强烈上调反应的大多数病原体, 包括 biotrophic 和 necrotrophic 真菌和草食动物, 因此, 值得注意的进一步功能分析.
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/56626/56626fig4.jpg"> 
图 4: 葡萄图谱中的分层 clusteringof ATL 基因表达及葡萄生物胁迫相关数据集.(A) 将葡萄树的 ATL 基因在葡萄树上的表达值转换为基于皮尔逊距离度量的层次聚类分析.颜色比例代表了较高 (红色) 或较低 (绿色) 的表达水平, 相对于每一个基因的平均转录丰度的所有样本。右侧的字母 A 到 E 表示标识的不同簇。AB: 爆裂后;B: 爆裂;芽 W: 冬芽;F: 开花;花期开始;财政司司长: 水果套装;G: 绿色;先生: mid-ripening;PFS: post-fruit 集;PHWI II. III: 收获后枯萎 1, 2 和3月;R: 成熟;S: 衰老;茎 W: 木质茎;V: veraison;WD: 开发良好;杨: 年轻人。(B) 颜色比例表示在受感染样本中葡萄 ATL 基因表达的增加 (红色) 或减少 (蓝色) 褶皱的变化与每个条件的对照。星号表示每个 ATL 在相应条件下的显著差异表达式 (罗斯福和 #60; 0.05)。转载自 Ariani et al.在创作共用归属4.0 国际许可证42下获得许可。<a href="//ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/56626/56626fig4large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
补充表 1: 用于替代剪接的 ATL 基因候选.(a) atl 基因 id 根据 V1 葡萄基因预测和注释, (b) atl 基因 id 根据 V2 葡萄基因预测和注释43, (c) 假定 atl 替代拼接变体的数量, (d)有关每个假定的 ATL 变体的编码顺序的信息。<a href="https://ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/56626/Supplementary_Table_I.xlsx">请单击此处下载此文件.</a>
补充表 2:<a href="https://ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/56626/Supplementary_Table_II.xlsx">请单击此处下载此文件.</a>
补充文件 1:<a href="https://ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/56626/Supplementary_File_1.txt">请单击此处下载此文件.</a>

Watch this Scientific Journal Video about Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine at JoVE.com

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

本文介绍了一个基因家族的鉴定和描述的程序, 适用于在 Levadura 的家庭的葡萄Tóxicos 的拟南芥(ATL) E3 泛素酶。

葡萄全基因组鉴定与表达的综合工作流 E3 泛素连接基因家族的 Meta 分析

Classification and nomenclature of genes in a family can significantly contribute to the description of the diversity of encoded proteins and to the ...

comprehensive-workflow-for-genome-wide-identification-expression-meta

Universidad San Sebastian

Research

JoVE Journal

Biology

10.4K 次观看.  Università degli Studi di Verona. 本文介绍了一个基因家族的鉴定和描述的程序, 适用于在 Levadura 的家庭的葡萄Tóxicos 的拟南芥(ATL) E3 泛素酶。

视频: Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics

Terroir refers to the combination of environmental factors that affect the characteristics of crops such as grapevine (Vitis vinifera) according to particular habitats and management practices. This article shows how certain terroir signatures can be detected in the berry metabolome and transcriptome of the grapevine cultivar Corvina using multivariate statistical analysis. The method first requires an appropriate sampling plan. In this case study, a specific clone of the Corvina cultivar was selected to minimize genetic differences, and samples were collected from seven vineyards representing three different macro-zones during three different growing seasons. An untargeted LC-MS metabolomics approach is recommended due to its high sensitivity, accompanied by efficient data processing using MZmine software and a metabolite identification strategy based on fragmentation tree analysis. Comprehensive transcriptome analysis can be achieved using microarrays containing probes covering ~99% of all predicted grapevine genes, allowing the simultaneous analysis of all differentially expressed genes in the context of different terroirs. Finally, multivariate data analysis based on projection methods can be used to overcome the strong vintage-specific effect, allowing the metabolomics and transcriptomics data to be integrated and analyzed in detail to identify informative correlations.

This article describes the application of untargeted metabolomics, transcriptomics and multivariate statistical analysis to grape berry transcripts and metabolites in order to gain insight into the terroir concept, i.e., the impact of the environment on berry quality traits.

风土通过概念葡萄果实代谢组学和转录组解释的

Terroir refers to the combination of environmental factors that affect the characteristics of crops such as grapevine (Vitis vinifera) according to ...

科研

遗传学

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Next generation sequencing (NGS) technologies have revolutionized the nature of biological investigation. Of these, RNA Sequencing (RNA-Seq) has emerged as a powerful tool for gene-expression analysis and transcriptome mapping. However, handling RNA-Seq datasets requires sophisticated computational expertise and poses inherent challenges for biology researchers. This bottleneck has been mitigated by the open access Galaxy project that allows users without bioinformatics skills to analyze RNA-Seq data, and the Database for Annotation, Visualization, and Integrated Discovery (DAVID), a Gene Ontology (GO) term analysis suite that helps derive biological meaning from large data sets. However, for first-time users and bioinformatics' amateurs, self-learning and familiarization with these platforms can be time-consuming and daunting. We describe a straightforward workflow that will help C. elegans researchers to isolate worm RNA, conduct an RNA-Seq experiment and analyze the data using Galaxy and DAVID platforms. This protocol provides stepwise instructions for using the various Galaxy modules for accessing raw NGS data, quality-control checks, alignment, and differential gene expression analysis, guiding the user with parameters at every step to generate a gene list that can be screened for enrichment of gene classes or biological processes using DAVID. Overall, we anticipate that this article will provide information to C. elegans researchers undertaking RNA-Seq experiments for the first time as well as frequent users running a small number of samples.

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Galaxy and DAVID have emerged as popular tools that allow investigators without bioinformatics training to analyze and interpret RNA-Seq data. We describe a protocol for C. elegans researchers to perform RNA-Seq experiments, access and process the dataset using Galaxy and obtain meaningful biological information from the gene lists using DAVID.

的转录分析<em&gt;ç</em&gt;。<em&gt;线虫</em&gt; RNA测序数据通过炫套房的银河项目

Next generation sequencing (NGS) technologies have revolutionized the nature of biological investigation. Of these, RNA Sequencing (RNA-Seq) has emerged ...

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Both gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) are widely used metabolomics approaches to detect and quantify hundreds of thousands of metabolite features. However, the application of these techniques to a large number of samples is subject to more complex interactions, particularly for genome-wide association studies (GWAS). This protocol describes an optimized metabolic workflow, which combines an efficient and fast sample preparation with the analysis of a large number of samples for legume crop species. This slightly modified extraction method was initially developed for the analysis of plant and animal tissues and is based on extraction in methyl tert-butyl ether: methanol solvent to allow the capture of polar and lipid metabolites. In addition, we provide a step-by-step guide for reducing analytical variations, which are essential for the high-throughput evaluation of metabolic variance in GWAS.

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization

In this protocol, we present an optimized workflow, which combines an efficient and fast sample preparation of many samples. In addition, we provide a step-by-step guide to reduce analytical variations for high-throughput evaluation of metabolic GWAS studies.

大规模多组学全基因组关联研究 （Mo-GWAS）:样品制备和归一化指南

Both gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) are widely used metabolomics approaches to detect ...

生物化学

Determining Genetic Expression Profiles in C. elegans Using Microarray and Real-time PCR

Synapses are composed of a presynaptic active zone in the signaling cell and a postsynaptic terminal in the target cell. In the case of chemical synapses, messages are carried by neurotransmitters released from presynaptic terminals and received by receptors on postsynaptic cells. Our previous research in Caenorhabditis elegans has shown that VSM-1 negatively regulates exocytosis. Additionally, analysis of synapses in vsm-1 mutants showed that animals lacking a fully functional VSM-1 have increased synaptic connectivity. Based on these preliminary findings, we hypothesized that C. elegans VSM-1 may play a crucial role in synaptogenesis. To test this hypothesis, double-labeled microarray analysis was performed, and gene expression profiles were determined. First, total RNA was isolated, reversely transcribed to cDNA, and hybridized to the DNA microarrays. Then, in-silico analysis of fluorescent probe hybridization revealed significant induction of many genes coding for members of the major sperm protein family (MSP) in mutants with enhanced synaptogenesis. MSPs are the major component of sperm in C. elegans and appear to signal nematode oocyte maturation and ovulation . In fruit flies, Chai and colleagues 1 demonstrated that MSP-like molecules regulate presynaptic bouton number and size at the neuromuscular junction. Moreover, analysis performed by Tsuda and coworkers 2 suggested that MSPs may act as ligands for Eph receptors and trigger receptor tyrosine kinase signaling cascades. Lastly, real time PCR analysis corroborated that the gene coding for MSP-32 is induced in vsm-1(ok1468) mutants. Taken together, research performed by our laboratory has shown that vsm-1 mutants have a significant increase in synaptic density, which could be mediated by MSP-32 signaling.

Determining Genetic Expression Profiles in C. elegans Using Microarray and Real-time PCR

Microarray analysis was conducted to determine genetic expression profiles in C. elegans, and real-time PCR was used to validate and quantify microarray data.

确定基因表达概况 C。线虫使用微阵列和实时PCR

Synapses are composed of a presynaptic active zone in the signaling cell and a postsynaptic terminal in the target cell. In the case of chemical synapses, ...

生物学

Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics

Given the ever expanding number of model plant species for which complete genome sequences are available and the abundance of bio-resources such as knockout mutants, wild accessions and advanced breeding populations, there is a rising burden for gene functional annotation. In this protocol, annotation of plant gene function using combined co-expression gene analysis, metabolomics and informatics is provided (Figure 1). This approach is based on the theory of using target genes of known function to allow the identification of non-annotated genes likely to be involved in a certain metabolic process, with the identification of target compounds via metabolomics. Strategies are put forward for applying this information on populations generated by both forward and reverse genetics approaches in spite of none of these are effortless. By corollary this approach can also be used as an approach to characterise unknown peaks representing new or specific secondary metabolites in the limited tissues, plant species or stress treatment, which is currently the important trial to understanding plant metabolism.

Combination of genomics, co-expression gene analysis and the identification of target compounds via metabolism give gene functional annotation.

联合基因组学，代谢组学和信息通过植物基因功能的注解

Given the ever expanding number of model plant species for which complete genome sequences are available and the abundance of bio-resources such as ...

Fluorescence-microscopy Screening and Next-generation Sequencing: Useful Tools for the Identification of Genes Involved in Organelle Integrity

This protocol describes a fluorescence microscope-based screening of Arabidopsis seedlings and describes how to map recessive mutations that alter the subcellular distribution of a specific tagged fluorescent marker in the secretory pathway. Arabidopsis is a powerful biological model for genetic studies because of its genome size, generation time, and conservation of molecular mechanisms among kingdoms. The array genotyping as an approach to map the mutation in alternative to the traditional method based on molecular markers is advantageous because it is relatively faster and may allow the mapping of several mutants in a really short time frame. This method allows the identification of proteins that can influence the integrity of any organelle in plants. Here, as an example, we propose a screen to map genes important for the integrity of the endoplasmic reticulum (ER). Our approach, however, can be easily extended to other plant cell organelles (for example see1,2), and thus represents an important step toward understanding the molecular basis governing other subcellular structures.

A fundamental quest in cell biology is to define the mechanisms that underlie the identity of the organelles that make eukaryotic cells. Here we propose a method to identify the genes responsible for the morphological and functional integrity of plant organelles using fluorescence microscopy and next-generation sequencing tools.

荧光显微镜筛选和新一代测序：参与细胞器完整性的基因鉴定的有用工具

This protocol describes a fluorescence microscope-based screening of Arabidopsis seedlings and describes how to map recessive mutations that alter the ...

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Powerful next generation sequencing techniques offer robust and comprehensive analysis to investigate how retinal gene regulatory networks function during development and in disease states. Single-cell RNA sequencing allows us to comprehensively profile gene expression changes observed in retinal development and disease at a cellular level, while single-cell ATAC-Seq allows analysis of chromatin accessibility and transcription factor binding to be profiled at similar resolution. Here the use of these techniques in the developing retina is described, and MULTI-Seq is demonstrated, where individual samples are labeled with a modified oligonucleotide-lipid complex, enabling researchers to both increase the scope of individual experiments and substantially reduce costs.

Here, the authors showcase the utility of MULTI-seq for phenotyping and subsequent paired scRNA-seq and scATAC-seq in characterizing the transcriptomic and chromatin accessibility profiles in retina.

使用 scRNA-Seq 和 scATAC-Seq 对视网膜基因表达和染色质可及性进行多重分析

Powerful next generation sequencing techniques offer robust and comprehensive analysis to investigate how retinal gene regulatory networks function during ...

神经科学

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Distilling and reporting large datasets, such as whole genome or transcriptome data, is often a daunting task. One way to break down results is to focus on one or more gene families that are significant to the organism and study. In this protocol, we outline bioinformatic steps to generate a phylogeny and to quantify the expression of genes of interest. Phylogenetic trees can give insight into how genes are evolving within and between species as well as reveal orthology. These results can be enhanced using RNA-seq data to compare the expression of these genes in different individuals or tissues. Studies of molecular evolution and expression can reveal modes of evolution and conservation of gene function between species. The characterization of a gene family can serve as a springboard for future studies and can highlight an important gene family in a new genome or transcriptome paper.

The purpose of this protocol is to investigate the evolution and expression of candidate genes using RNA sequencing data.

使用RNA-seq研究分子进化和基因表达的生物信息学管道

Distilling and reporting large datasets, such as whole genome or transcriptome data, is often a daunting task. One way to break down results is to focus ...

Genome-wide Profiling of Transcription Factor-DNA Binding Interactions in Candida albicans: A Comprehensive CUT&amp;RUN Method and Data Analysis Workflow

Regulatory transcription factors control many important biological processes, including cellular differentiation, responses to environmental perturbations and stresses, and host-pathogen interactions. Determining the genome-wide binding of regulatory transcription factors to DNA is essential to understanding the function of transcription factors in these often complex biological processes. Cleavage under targets and release using nuclease (CUT&amp;RUN) is a modern method for genome-wide mapping of in vivo protein-DNA binding interactions that is an attractive alternative to the traditional and widely used chromatin immunoprecipitation followed by sequencing (ChIP-seq) method. CUT&amp;RUN is amenable to a higher-throughput experimental setup and has a substantially higher dynamic range with lower per-sample sequencing costs than ChIP-seq. Here, a comprehensive CUT&amp;RUN protocol and accompanying data analysis workflow tailored for genome-wide analysis of transcription factor-DNA binding interactions in the human fungal pathogen Candida albicans are described. This detailed protocol includes all necessary experimental procedures, from epitope tagging of transcription factor-coding genes to library preparation for sequencing; additionally, it includes a customized computational workflow for CUT&amp;RUN data analysis.

Genome-wide Profiling of Transcription Factor-DNA Binding Interactions in Candida albicans: A Comprehensive CUT&RUN Method and Data Analysis Workflow

This protocol describes an experimental method and data analysis workflow for cleavage under targets and release using nuclease (CUT&amp;RUN) in the human fungal pathogen Candida albicans.

白色念珠菌中转录因子-DNA结合相互作用的全基因组分析:全面的CUT&amp;RUN方法和数据分析工作流程

Regulatory transcription factors control many important biological processes, including cellular differentiation, responses to environmental perturbations ...

Isolation and Transcriptome Analysis of Plant Cell Types

In multicellular organisms, developmental programming and environmental responses can be highly divergent in different cell types or even within cells, which is known as cellular heterogeneity. In recent years, single-cell and cell-type isolation combined with next-generation sequencing (NGS) techniques have become important tools for studying biological processes at single-cell resolution. However, isolating plant cells is relatively more difficult due to the presence of plant cell walls, which limits the application of single-cell approaches in plants. This protocol describes a robust procedure for fluorescence-activated cell sorting (FACS)-based single-cell and cell-type isolation with plant cells, which is suitable for downstream multi-omics analysis and other studies. Using Arabidopsis root fluorescent marker lines, we demonstrate how particular cell types, such as xylem-pole pericycle cells, lateral root initial cells, lateral root cap cells, cortex cells, and endodermal cells, are isolated. Furthermore, an effective downstream transcriptome analysis method using Smart-seq2 is also provided. The cell isolation method and transcriptome analysis techniques can be adapted to other cell types and plant species and have broad application potential in plant science.

The feasibility and effectiveness of high-throughput scRNA-seq methods herald a single-cell era in plant research. Presented here is a robust and complete procedure for isolating specific Arabidopsis thaliana root cell types and subsequent transcriptome library construction and analysis.

植物细胞类型的分离和转录组分析

In multicellular organisms, developmental programming and environmental responses can be highly divergent in different cell types or even within cells, ...

葡萄全基因组鉴定与表达的综合工作流 E3 泛素连接基因家族的 Meta 分析

摘要

探索更多视频

此视频中的章节

风土通过概念葡萄果实代谢组学和转录组解释的

的转录分析

大规模多组学全基因组关联研究（Mo-GWAS）:样品制备和归一化指南

确定基因表达概况 C。线虫使用微阵列和实时PCR

联合基因组学，代谢组学和信息通过植物基因功能的注解

荧光显微镜筛选和新一代测序：参与细胞器完整性的基因鉴定的有用工具

使用 scRNA-Seq 和 scATAC-Seq 对视网膜基因表达和染色质可及性进行多重分析

使用RNA-seq研究分子进化和基因表达的生物信息学管道

白色念珠菌中转录因子-DNA结合相互作用的全基因组分析:全面的CUT&RUN方法和数据分析工作流程

植物细胞类型的分离和转录组分析

葡萄全基因组鉴定与表达的综合工作流 E3 泛素连接基因家族的 Meta 分析

摘要

探索更多视频

此视频中的章节

风土通过概念葡萄果实代谢组学和转录组解释的

的转录分析

大规模多组学全基因组关联研究 （Mo-GWAS）:样品制备和归一化指南

确定基因表达概况 C。线虫使用微阵列和实时PCR

联合基因组学，代谢组学和信息通过植物基因功能的注解

荧光显微镜筛选和新一代测序：参与细胞器完整性的基因鉴定的有用工具

使用 scRNA-Seq 和 scATAC-Seq 对视网膜基因表达和染色质可及性进行多重分析

使用RNA-seq研究分子进化和基因表达的生物信息学管道

白色念珠菌中转录因子-DNA结合相互作用的全基因组分析:全面的CUT&RUN方法和数据分析工作流程

植物细胞类型的分离和转录组分析

大规模多组学全基因组关联研究（Mo-GWAS）:样品制备和归一化指南