일 공동 프로젝트 2014 (grapevine에 ATL 유전자 가족의 그리고 Plasmopara viticola저항에의 참여의 특성화) 프레임 내 베로나의 대학에 의해 지원 되었다.

<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>

저자는 공개 없다.

게놈 시대에 많은 유전자 가족 깊이 여러 종의 식물에 특징 되어 있다. 이 정보 기능 연구 예비 이며 가족의 다른 구성원의 역할을 자세히 조사 하는 프레임을 제공 합니다. 이러한 맥락에서 중복 때 이름을 할당 하지 독립적으로 다른 유전자를 다양 한 연구 그룹에 의해 발생할 수 있는 혼란을 피하는 가족의 각 구성원을 고유 하 게 식별 하는 명명법 시스템 허용에 대 한 필요 또한 있다.
<p class...

지난 10 년 동안 많은 연구 grapevine 유전체학에서 실시 했다. Grapevine 인정된 경제적으로 관련 작물 이다, 과일 개발 연구 biotic 및 abiotic 스트레스에 나무가 우거진 식물의 응답에 대 한 모델 되고있다. 이러한 맥락에서 20071 왕 vinifera cv PN40024. 게놈 및 20112 의 업데이트 된 버전의 릴리스 "Omics"-규모 데이터의 급속 한 축적 하 고 높은 처리량 연구의 주도. 게시 된 시퀀스 데이터를 바탕으로, 주어진된 유전자 가족 (일반적으로 보존된 모티브, 구조적 및 기능적 유사성과 진화 관계를 공유 하는 단백질의 구성)의 포괄적인 분석 수행할 수 있는 지금 밝히기는 분자 기능, 진화, 고 진 식 프로필. 이러한 분석은 유전자 가족 게놈 넓은 수준에 생리 적 프로세스를 제어 하는 방법을 이해 하는 데 기여할 수 있다.
플랜트 라이프 사이클의 여러 측면 유비퀴틴 중재 일반 세포 프로세스를 미세 조정된 회전율을 필요로 하는 주요 단백질의 저하에 의해 통제 된다. 중요 한 저하 유비퀴틴 중재 프로세스의 구성 요소는 E3 유비퀴틴 ligases는 특정 대상3의 채용 덕분에 시스템 유연성에 대 한 책임이 있습니다. 따라서 이러한 효소 예측 애기 thaliana 게놈4, 각 E3 유비퀴틴 리가 특정 대상 단백질의 ubiquitination에 대 한 행동에 약 1400 E3 리가 인코딩 유전자와 거 대 한 유전자 가족을 나타냅니다. 식물에 있는 세포 기질-관련 ubiquitination의 중요성에도 불구 하 고 약간 ubiquitination 통로 규제 하는 방법에 대 한 알려져 있다 하 고 대상 단백질 몇 가지 경우에만 확인 되었습니다. 이러한 특이성 및 규제 메커니즘의 해독 의존 먼저 식별 하 고 특히에서 시스템의 다른 구성 요소의 E3 ligases 합니다. 유비퀴틴 ligases 중 ATL 인도의 91 회원 A. thaliana 반지-h 2 손가락 도메인5,6, 방어와 호르몬 응답7역할 그들 중 일부를 표시에서 확인 된 특징 이다.
새로운 유전자 가족의 구성원을 정의 하는 첫 번째 중요 한 단계 합의 모티프, 주요 도메인, 단백질 시퀀스 특성 등 가족 기능의 정확한 정의 이다. 실제로, 모든 유전자 가족의 폭발 분석에 따라 신뢰할 수 있는 검색 일부 필수 시퀀스 특성을 단백질 기능/활동, 단백질 서명으로 봉사에 대 한 책임 특정 단백질 도메인에 필요 합니다. 이 상 일반적인 시퀀스를 격리 하기 위해 다른 식물 종, 동일한 가족에 속하는 다른 유전자를 분석 하 여 달성 하거나 다른 식물 종에는 동일한 유전자 가족의 이전 특성에 의해 촉진 될 수 있습니다. 가족 구성원 수 있습니다 다음 개별적으로 작성 된 특정된 식물 종에 대 한 국제 컨소시엄에 의해 해결 하는 일반적인 규칙에 따라. Grapevine에 예를 들어, 이러한 절차 수립 등 V. vinifera A. thaliana 계통 발생 나무의 건설 포도 유전자 주석 (sNCGGa)에 대 한 슈퍼 전문 어 위원회의 권고를 복종 된다 유전자 가족 유전자 주석 있도록 뉴클레오티드 시퀀스8에 따라.
가족 구성원 및 유전자 중복 조사 염색체 현지화 전체 게놈 또는 협동 중복된 유전자의 존재를 강조 하실 수 있습니다. 이러한 정보가 나타납니다 이후 표시 기능 중복 되거나 다른 상황, 즉, 비 기능화, 네오-기능화, 또는 하위 기능화9공개 될 상 상속 유전자 기능을 해명 하는 데 유용. 두 네오-및 하위-functionalization는 환경10변화에 적응 하는 식물에 대 한 새로운 세포 구성 요소를 제공 하는 유전 참신을 만드는 중요 한 이벤트. 특히, 조상의 유전자의 중복과 새로운 유전자의 생산 매우 자주 grapevine 게놈의 진화 하는 동안 되었고 grapevine에 인접 하 고 협동 중복에서 발생 하는 새로 형성된 된 유전자를 새로운 생산 가능성이 있었다 함수11.
또 다른 주요 요소 유전자 가족 기능 해독 transcriptomic 프로필입니다. Transcriptomic 데이터의 엄청난 금액을 액세스를 부여 하는 공용 데이터베이스의 가용성은 대규모 철에 식 분석을 사용 하 여 유전자 가족에 상 상속 기능을 할당 하 따라서 악용 될 수 있습니다. 실제로, 특정 식물 기관 또는 특정 스트레스에 대 한 응답에 일부 유전자의 독특한 표현 정의 된 조건에서 해당 단백질의 상 상속 역할에 관한 몇 가지 힌트를 줄 수 있고 가능한에 대 한 가설에 지원을 제공합니다 다른도 전에 대응 하는 유전자 중복된의 하위 기능화. 그 목적, 여러 데이터 집합을 고려 하는 것이 중요 하다:이 식을 행렬, grapevine 기관과 발달 단계12, 게놈 넓은 transcriptomic 아틀라스 등 이미 유전자 수 또는 애드혹 으로 건축 될 수 있다 transcriptomic를 정의 거쳤다 특정 식물 종에 대 한 데이터 집합을 검색 합니다. 또한, 두 행렬을 사용 하는 간단한 방법, 인덱스도 유사성 데이터와 인덱스도 공동 식 계수와 함께 다른 하나 적용할 수 있는 유전자 가족 내에서 시퀀스 유사성과 표현의 패턴 간의 관계를 평가 하.
이 작품의 목적은 잘 달성 하기 위해 단백질 현지화 및 인 산화 사이트의 예측으로 유전자 구조, 보존된 단백질 모티프, 염색체 위치, 유전자 중복, 및 식 패턴을 정의 하는 글로벌 접근 방식을 제공 하는 식물에서 유전자 가족의의 완전 한 특성화 이러한 포괄적인 접근 방식은 여기 소문에 ATL E3 유비퀴틴 리가 가족의 특성에 적용 됩니다. 신흥 멤버 역할의 ATL 인도의 주요 세포질 과정7조절에,에 따르면이 작품 수 있습니다 잘 기능 연구에 대 한 강한 후보자의 식별을 지원 하 고 결국 경 세 하는 분자 메커니즘을 해명는 이 중요 한 작물의 환경에의 적응입니다.

<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

분류 및 명명법 가족에 있는 유전자의 인코딩된 단백질의 다양성의 설명 하 고 특히 또는 시퀀스 모티프의 존재 등 여러 가지 기능에 대해 가족 기능 예측에 크게 기여할 수 있다 포스트 번역 상 수정 및 다른 조건에서 가족 구성원의 식 프로 파일에 대 한 사이트. 이 작품에서는 유전자 가족 특성에 대 한 상세한 프로토콜을 설명합니다. 여기, 프로시저 Levadura에서 애기 Tóxicos (ATL) E3 유비퀴틴 리가 소문에는 가족의 특성에 적용 됩니다. 단백질 지역화 및 인 산화 위치의 예측, 보존된 단백질 모티프의 분석, 유전자 지역화, 구조, 그리고 복제의 특성, 가족 구성원의 게놈 넓은 id를 포함 하는 방법 뿐만 아니라 유전자 표현에서 서로 다른 데이터 집합에 가족 프로 파일링. 실험 목적에 따라 추가 분석 연장 될 수 있는, 그런 절차는 게놈 데이터 사용할 수 있습니다, 어떤 식물 종에 어떤 유전자 가족에 적용 될 수 하 고 재미 있는 후보를 식별 하기 위해 귀중 한 정보를 제공 합니다. 기능 연구에 대 한 그들의 환경에 적응 하는 식물의 분자 메커니즘에 대 한 통찰력을 주는.

VIT_05s0077g01970 유전자, 식별 되는 가장 비슷한 A. thaliana ATL2 (At3g16720) BLASTp 검색을 통해이 포도 게놈에서 ATL 가족 구성원 조사에 프로브로 사용 되었다 (V. vinifera 이력서 피노 누아 PN40024). PSI 폭발 분석 융합 몇 주기 (그림 1A) grapevine ATL 유전자 가족에 속하는 상 상속 유전자의 목록이 공개 후. 각 후보에 대 한 정식 반지-H2 도메인의 존재 분?...

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

이 문서에서는 식별 및 Levadura에 애기 Tóxicos (ATL) E3 유비퀴틴 ligases 제품군에 적용 하는 소문에 유전자 가족의 특성에 대 한 절차를 설명 합니다.

게놈 넓은 식별 및 소문의 ATL E3 유비퀴틴 리가 유전자 가족의 식 메타 분석을 위한 포괄적인 워크플로

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

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Biology

10.4K 조회수.  Università degli Studi di Verona. 이 문서에서는 식별 및 Levadura에 애기 Tóxicos (ATL) E3 유비퀴틴 ligases 제품군에 적용 하는 소문에 유전자 가족의 특성에 대 한 절차를 설명 합니다.

비디오: 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.

포도 베리 대사 체학 및 Transcriptomics을 통해 해석 떼루아 개념

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

연구

유전학

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.

의 Transcriptomic 분석<em&gt; C</em&gt;.<em&gt; 간스</em갤럭시 프로젝트에 턱시도 제품군을 통해&gt; RNA 시퀀싱 데이터

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.

대규모 다중 오믹스 게놈 전체 연관 연구 (Mo-GWAS) : 샘플 준비 및 정상화에 대한 지침

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

생화학

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.

의 유전자 표현 프로필 결정 C. 엘레간스 Microarray 및 실시간 PCR을 사용하여

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, ...

생물학

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.

결합 지노 믹스, Metabolomics와 정보학 통해 식물 유전자 기능의 주석

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.

형광 - 현미경 검사와 차세대 장면 : Organelle 무결성에 관련된 유전자의 식별을위한 유용한 도구

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.

scRNA-Seq 및 scATAC-Seq 를 이용한 망막 유전자 발현 및 크로마틴 접근성의 다중화 분석

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

신경과학

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.

RNA-seq를 사용하여 분자 진화 및 유전자 발현을 조사하기 위한 생물정보학 파이프라인

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.

칸디다 알비칸스에서의 전사 인자-DNA 결합 상호작용의 게놈 전체 프로파일링: 포괄적인 CUT&amp;RUN 방법 및 데이터 분석 워크플로우

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.

식물 세포 유형의 분리 및 전사체 분석

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

게놈 넓은 식별 및 소문의 ATL E3 유비퀴틴 리가 유전자 가족의 식 메타 분석을 위한 포괄적인 워크플로

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