CG020 Genomika Přednáška 12 Nástroje systémové biologie Modelové organismy, PCR a zásady navrhování primerů Jan Hejátko Funkční genomika a proteomika rostlin, Mendelovo centrum genomiky a proteomiky rostlin, Středoevropský technologický institut (CEITEC), Masarykova univerzita, Brno hejatko@sci.muni.cz, www.ceitec.muni.cz  Zdrojová literatura  Wilt, F.H., and Hake, S. (2004). Principles of Developmental Biology. (New York ; London: W. W. Norton)  Roscoe B. Jackson Memorial Laboratory., and Green, E.L. (1966). Biology of the laboratory mouse. (New York: Blakiston Division) http://www.informatics.jax.org/greenbook/index.shtml  Eden, E., Navon, R., Steinfeld, I., Lipson, D., and Yakhini, Z. (2009). GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists. BMC Bioinformatics 10, 48.  The Arabidopsis Genome Initiative. (2000). Analysis of the genome sequence of the flowering plant Arabidopsis thaliana. Nature 408, 796-815.  Gregory, S.G., Sekhon, M., Schein, J., Zhao, S., Osoegawa, K., Scott, C.E., Evans, R.S., Burridge, P.W., Cox, T.V., Fox, C.A., Hutton, R.D., Mullenger, I.R., Phillips, K.J., Smith, J., Stalker, J., Threadgold, G.J., Birney, E., Wylie, K., Chinwalla, A., Wallis, J., Hillier, L., Carter, J., Gaige, T., Jaeger, S., Kremitzki, C., Layman, D., Maas, J., McGrane, R., Mead, K., Walker, R., Jones, S., Smith, M., Asano, J., Bosdet, I., Chan, S., Chittaranjan, S., Chiu, R., Fjell, C., Fuhrmann, D., Girn, N., Gray, C., Guin, R., Hsiao, L., Krzywinski, M., Kutsche, R., Lee, S.S., Mathewson, C., McLeavy, C., Messervier, S., Ness, S., Pandoh, P., Prabhu, A.L., Saeedi, P., Smailus, D., Spence, L., Stott, J., Taylor, S., Terpstra, W., Tsai, M., Vardy, J., Wye, N., Yang, G., Shatsman, S., Ayodeji, B., Geer, K., Tsegaye, G., Shvartsbeyn, A., Gebregeorgis, E., Krol, M., Russell, D., Overton, L., Malek, J.A., Holmes, M., Heaney, M., Shetty, J., Feldblyum, T., Nierman, W.C., Catanese, J.J., Hubbard, T., Waterston, R.H., Rogers, J., de Jong, P.J., Fraser, C.M., Marra, M., McPherson, J.D., and Bentley, D.R. (2002). A physical map of the mouse genome. Nature 418, 743-750.  Benitez, M. and Hejatko, J. Dynamics of cell-fate determination and patterning in the vascular bundles of Arabidopsis thaliana (submitted) Genomika 12  Nástroje systémové biologie  Analýza genové ontologie  Modelování molekulárních regulačních sítí  Modelové organismy  Mus musculus  Arabidopsis thaliana  Vybrané metody molekulární biologie  Příprava transgenních organismů  PCR  Design a příprava primerů (Dr. Hana Konečná) Osnova  Nástroje systémové biologie  Analýza genové ontologie Osnova Results of –omics Studies vs Biologically Relevant Conclusions □ Results of –omics studies are representred by huge amount of data, e.g. differential gene expression. But how to get any biologically relevant conclusions? gene locus sample_1 sample_2 status value_1 value_2 log2(fold_change) test_stat p_value q_value significant AT1G07795 1:2414285-2414967 WT MT OK 0 1,1804 1.79769e+308 1.79769e+ 308 6.88885e-05 0,00039180 1 yes HRS1 1:4556891-4558708 WT MT OK 0 0,696583 1.79769e+308 1.79769e+ 308 6.61994e-06 4.67708e- 05 yes ATMLO14 1:9227472-9232296 WT MT OK 0 0,514609 1.79769e+308 1.79769e+ 308 9.74219e-05 0,00053505 5 yes NRT1.6 1:9400663-9403789 WT MT OK 0 0,877865 1.79769e+308 1.79769e+ 308 3.2692e-08 3.50131e- 07 yes AT1G27570 1:9575425-9582376 WT MT OK 0 2,0829 1.79769e+308 1.79769e+ 308 9.76039e-06 6.647e-05 yes AT1G60095 1:22159735- 22162419 WT MT OK 0 0,688588 1.79769e+308 1.79769e+ 308 9.95901e-08 9.84992e- 07 yes AT1G03020 1:698206-698515 WT MT OK 0 1,78859 1.79769e+308 1.79769e+ 308 0,00913915 0,0277958 yes AT1G13609 1:4662720-4663471 WT MT OK 0 3,55814 1.79769e+308 1.79769e+ 308 0,00021683 0,00108079 yes AT1G21550 1:7553100-7553876 WT MT OK 0 0,562868 1.79769e+308 1.79769e+ 308 0,00115582 0,00471497 yes AT1G22120 1:7806308-7809632 WT MT OK 0 0,617354 1.79769e+308 1.79769e+ 308 2.48392e-06 1.91089e- 05 yes AT1G31370 1:11238297- 11239363 WT MT OK 0 1,46254 1.79769e+308 1.79769e+ 308 4.83523e-05 0,00028514 3 yes APUM10 1:13253397- 13255570 WT MT OK 0 0,581031 1.79769e+308 1.79769e+ 308 7.87855e-06 5.46603e- 05 yes AT1G48700 1:18010728- 18012871 WT MT OK 0 0,556525 1.79769e+308 1.79769e+ 308 6.53917e-05 0,00037473 6 yes AT1G59077 1:21746209- 21833195 WT MT OK 0 138,886 1.79769e+308 1.79769e+ 308 0,00122789 0,00496816 yes AT1G60050 1:22121549- 22123702 WT MT OK 0 0,370087 1.79769e+308 1.79769e+ 308 0,00117953 0,0048001 yes Ddii et al., unpublished AT4G15242 4:8705786-8706997 WT MT OK 0,00930712 17,9056 10,9098 -4,40523 1.05673e-05 7.13983e-05 yes AT5G33251 5:12499071- 12500433 WT MT OK 0,0498375 52,2837 10,0349 -9,8119 0 0yes AT4G12520 4:7421055-7421738 WT MT OK 0,0195111 15,8516 9,66612 -3,90043 9.60217e-05 0,000528904yes AT1G60020 1:22100651- 22105276 WT MT OK 0,0118377 7,18823 9,24611 -7,50382 6.19504e-14 1.4988e-12 yes AT5G15360 5:4987235-4989182 WT MT OK 0,0988273 56,4834 9,1587 -10,4392 0 0yes Molecular Regulatory Networks Modeling □ Vascular tissue as a developmental model for GO analysis and MRN modeling Lehesranta etal., Trends in Plant Sci (2010) Hormonal Regulation in Plant Biotechnology WT hormonal mutant Hormonal Control Over Vascular Tissue Development □ Plant Hormones Regulate Lignin Deposition in Plant Cell Walls and Xylem Water Conductivity WT mutant lignified cell walls Water Conductivity WT hormonal mutants Hormonal Regulation in Plant Biotechnology WT hormonal mutant Hormonal Control Over Vascular Tissue Development □ Transcriptional profiling via RNA sequencing mRNA Sequencing by Illumina and number of transcripts determination mRNA cDNA cDNA Hormonal Regulation in Plant Biotechnology Results of –omics Studies vs Biologically Relevant Conclusions □ Transcriptional profiling yielded more then 7K differentially regulated genes… gene locus sample_1 sample_2 status value_1 value_2 log2(fold_change) test_stat p_value q_value significant AT1G07795 1:2414285-2414967 WT MT OK 0 1,1804 1.79769e+308 1.79769e+ 308 6.88885e-05 0,00039180 1 yes HRS1 1:4556891-4558708 WT MT OK 0 0,696583 1.79769e+308 1.79769e+ 308 6.61994e-06 4.67708e- 05 yes ATMLO14 1:9227472-9232296 WT MT OK 0 0,514609 1.79769e+308 1.79769e+ 308 9.74219e-05 0,00053505 5 yes NRT1.6 1:9400663-9403789 WT MT OK 0 0,877865 1.79769e+308 1.79769e+ 308 3.2692e-08 3.50131e- 07 yes AT1G27570 1:9575425-9582376 WT MT OK 0 2,0829 1.79769e+308 1.79769e+ 308 9.76039e-06 6.647e-05 yes AT1G60095 1:22159735- 22162419 WT MT OK 0 0,688588 1.79769e+308 1.79769e+ 308 9.95901e-08 9.84992e- 07 yes AT1G03020 1:698206-698515 WT MT OK 0 1,78859 1.79769e+308 1.79769e+ 308 0,00913915 0,0277958 yes AT1G13609 1:4662720-4663471 WT MT OK 0 3,55814 1.79769e+308 1.79769e+ 308 0,00021683 0,00108079 yes AT1G21550 1:7553100-7553876 WT MT OK 0 0,562868 1.79769e+308 1.79769e+ 308 0,00115582 0,00471497 yes AT1G22120 1:7806308-7809632 WT MT OK 0 0,617354 1.79769e+308 1.79769e+ 308 2.48392e-06 1.91089e- 05 yes AT1G31370 1:11238297- 11239363 WT MT OK 0 1,46254 1.79769e+308 1.79769e+ 308 4.83523e-05 0,00028514 3 yes APUM10 1:13253397- 13255570 WT MT OK 0 0,581031 1.79769e+308 1.79769e+ 308 7.87855e-06 5.46603e- 05 yes AT1G48700 1:18010728- 18012871 WT MT OK 0 0,556525 1.79769e+308 1.79769e+ 308 6.53917e-05 0,00037473 6 yes AT1G59077 1:21746209- 21833195 WT MT OK 0 138,886 1.79769e+308 1.79769e+ 308 0,00122789 0,00496816 yes AT1G60050 1:22121549- 22123702 WT MT OK 0 0,370087 1.79769e+308 1.79769e+ 308 0,00117953 0,0048001 yes Ddii et al., unpublished AT4G15242 4:8705786-8706997 WT MT OK 0,00930712 17,9056 10,9098 -4,40523 1.05673e-05 7.13983e-05 yes AT5G33251 5:12499071- 12500433 WT MT OK 0,0498375 52,2837 10,0349 -9,8119 0 0yes AT4G12520 4:7421055-7421738 WT MT OK 0,0195111 15,8516 9,66612 -3,90043 9.60217e-05 0,000528904yes AT1G60020 1:22100651- 22105276 WT MT OK 0,0118377 7,18823 9,24611 -7,50382 6.19504e-14 1.4988e-12 yes AT5G15360 5:4987235-4989182 WT MT OK 0,0988273 56,4834 9,1587 -10,4392 0 0yes Gene Ontology Analysis □ One of the possible approaches is to study gene ontology, i.e. previously demonstrated association of genes to biological processes Ddii et al., unpublished Gene Ontology Analysis □ Several tools allow statistical evaluation of enrichment for genes associated with specific processes Eden et al., BMC Biinformatics (2009) Gene Ontology Analysis □ Several tools allow statistical evaluation of enrichment for genes associated with specific processes Gene Ontology Analysis □ Several tools allow statistical evaluation of enrichment for genes associated with specific processes Gene Ontology Analysis □ Several tools allow statistical evaluation of enrichment for genes associated with specific processes Gene Ontology Analysis □ Several tools allow statistical evaluation of enrichment for genes associated with specific processes Gene Ontology Analysis □ Several tools allow statistical evaluation of enrichment for genes associated with specific processes  Nástroje systémové biologie  Analýza genové ontologie  Modelování molekulárních regulačních sítí Osnova □ Vascular tissue as a developmental model for MRN modeling Benitez and Hejatko, submitted Molecular Regulatory Networks Modeling Signaling and Hormonal Regulation of Plant Development Molecular Regulatory Networks Modeling □ Literature search for published data and creating own database Interaction Evidence References A-ARRs –| CK signaling Double and higher order type-A ARR mutants show increased sensitivity to CK. Spatial patterns of A-type ARR gene expression and CK response are consistent with partially redundant function of these genes in CK signaling. A-type ARRs decreases B-type ARR6-LUC. Note: In certain contexts, however, some A-ARRs appear to have effects antagonistic to other A-ARRs. [27] [27] [13] [27] AHP6 –| AHP ahp6 partially recovers the mutant phenotype of the CK receptor WOL. Using an in vitro phosphotransfer system, it was shown that, unlike the AHPs, native AHP6 was unable to accept a phosphoryl group. Nevertheless, AHP6 is able to inhibit phosphotransfer from other AHPs to ARRs. [9] [9] Benitez and Hejatko, submitted Signaling and Hormonal Regulation of Plant Development Molecular Regulatory Networks Modeling □ Formulating logical rules defining the model dynamics Network node Dynamical rule CK 2 If ipt=1 and ckx=0 1 If ipt=1 and ckx=1 0 else CKX 1 If barr>0 or arf=2 0 else AHKs ahk=ck AHPs 2 If ahk=2 and ahp6=0 and aarr=0 1 If ahk=2 and (ahp6+aarr<2) 1 If ahk=1 and ahp6<1 0 else B-Type ARRs 1 If ahp>0 0 else A-Type ARRs 1 If arf<2 and ahp>0 0 else Benitez and Hejatko, submitted Signaling and Hormonal Regulation of Plant Development Molecular Regulatory Networks Modeling □ Specifying mobile elements and their model behaviour Signaling and Hormonal Regulation of Plant Development Molecular Regulatory Networks Modeling □ Preparing the first version of the model and its testing Signaling and Hormonal Regulation of Plant Development Molecular Regulatory Networks Modeling □ Specifying of missing interactions via informed predictions Interaction Evidence References A-ARRs –| CK signaling Double and higher order type-A ARR mutants show increased sensitivity to CK. Spatial patterns of A-type ARR gene expression and CK response are consistent with partially redundant function of these genes in CK signaling. A-type ARRs decreases B-type ARR6-LUC. Note: In certain contexts, however, some A-ARRs appear to have effects antagonistic to other A-ARRs. [27] [27] [13] [27] AHP6 –| AHP ahp6 partially recovers the mutant phenotype of the CK receptor WOL. Using an in vitro phosphotransfer system, it was shown that, unlike the AHPs, native AHP6 was unable to accept a phosphoryl group. Nevertheless, AHP6 is able to inhibit phosphotransfer from other AHPs to ARRs. [9] [9] CK → PIN7 radial localization Predicted interaction (could be direct or indirect) Informed by the following data: During the specification of root vascular cells in Arabidopsis thaliana, CK regulates the radial localization of PIN7. Expression of PIN7:GFP and PIN7::GUS is upregulated by CK with no significant influence of ethylene. In the root, CK signaling is required for the CK regulation of PIN1, PIN3, and PIN7. Their expression is altered in wol, cre1, ahk3 and ahp6 mutants. [18] [18,20] [19] CK→ APL Predicted interaction (could be direct or indirect) Consistent with the fact that APL overexpression prevents or delays xylem cell differentiation, as does CKs. Partially supported by microarray data and phloem-specific expression patterns of CK response factors. [21] (TAIR, ExpressionSet:1 005823559, [22]) Signaling and Hormonal Regulation of Plant Development Molecular Regulatory Networks Modeling □ Preparing the next version of the model and its testing Benitez and Hejatko, PlosONE, 2013 Signaling and Hormonal Regulation of Plant Development □ Good model should be able to simulate reality Benitez and Hejatko, PlosONE, 2013 Molecular Regulatory Networks Modeling Signaling and Hormonal Regulation of Plant Development □ Formulating equations describing the relationships in the model Molecular Regulatory Networks Modeling Static nodes: gn(t+1)=Fn(gn1(t),gn2(t),..., gnk(t)) Mobile nodes: g(t+1)T [i]= H(g(t) [i]+ D (g(t) [i+1]+g(t) [i-1] – N(g(t) [i]))-b) state in the time t+1 state in the time tlogical rule function state in the time t+1 Amount if TDIF or MIR165 in cell i proportion of movable element constant corresponding to a degradation term Signaling and Hormonal Regulation of Plant Development □ Good model should be able to simulate reality Benitez and Hejatko, submitted Molecular Regulatory Networks Modeling Static nodes: gn(t+1)=Fn(gn1(t),gn2(t),..., gnk(t)) Mobile nodes: g(t+1)T [i]= H(g(t) [i]+ D (g(t) [i+1]+g(t) [i-1] – N(g(t) [i]))-b) Signaling and Hormonal Regulation of Plant Development Molecular Regulatory Networks Modeling Benitez and Hejatko, submitted □ The good model should be able to simulate reality Signaling and Hormonal Regulation of Plant Development Molecular Regulatory Networks Modeling Benitez and Hejatko, submitted □ Simulation of mutants Signaling and Hormonal Regulation of Plant Development  Nástroje systémové biologie  Analýza genové ontologie  Modelování molekulárních regulačních sítí  Modelové organismy  Mus musculus Osnova  malé nároky na chovnou plochu  relativně velké množství mláďat (3-14, v průměru 6-8)  velikost genomu se blíží velikosti genomu člověka (cca 3000 Mbp), podobně jako počet genů (cca 24K)  20 chromozomů (19+1)  vhodná pro široké spektrum fyziologických experimentů (anatomicky i fyziologicky podobná člověku)  možno poměrně snadno získávat K.O. mutanty i transgenní linie Mus musculus myš domácí, house mouse  Genom známý od roku 2002 (http://www.ncbi.nlm.nih.gov/projects/genome/assembly/grc/mouse/) Mus musculus myš domácí, house mouse  Nástroje systémové biologie  Analýza genové ontologie  Modelování molekulárních regulačních sítí  Modelové organismy  Mus musculus  Arabidopsis thaliana Osnova  malé nároky na kultivační plochu Arabidopsis thaliana huseníček polní, mouse-ear cress  velké množství semen (20.000/rostlinu a více)  malý a kompaktní genom, (125 MBp, cca 25.000 genů, prům. velikost 3 kb)  5 chromozomů  vhodná pro široké spektrum fyziologických experimentů  velká přirozená variabilita (cca 750 ekotypů (Nottingham Arabidopsis Seed Stock Centre)) Columbia 0 Landsberg 0 Wassilewskija 0 http://seeds.nottingham.ac.uk/ Arabidopsis thaliana huseníček polní, mouse-ear cress  Genom známý od roku 2000 (http://www.arabidopsis.org/)  Nástroje systémové biologie  Analýza genové ontologie  Modelování molekulárních regulačních sítí  Modelové organismy  Mus musculus  Arabidopsis thaliana  Vybrané metody molekulární biologie  Příprava transgenních organismů Osnova Transformace Arabidopsis prostřednictvím Agrobacteria tumefaciens Transformace Arabidopsis prostřednictvím Agrobacteria tumefaciens přenos bakteriální DNA do rostlinné buňky Transformace kokultivací listových disků Transformace kokultivací kalusů Transformace „nastřelováním“ DNA Transformace květenství http://www.bch.msu.edu/pamgreen/green.htm Transformace květenství http://www.bch.msu.edu/pamgreen/green.htm  Nástroje systémové biologie  Analýza genové ontologie  Modelování molekulárních regulačních sítí  Modelové organismy  Mus musculus  Arabidopsis thaliana  Vybrané metody molekulární biologie  Příprava transgenních organismů  PCR Osnova PCR  Nástroje systémové biologie  Analýza genové ontologie  Modelování molekulárních regulačních sítí  Modelové organismy  Mus musculus  Arabidopsis thaliana  Vybrané metody molekulární biologie  Příprava transgenních organismů  PCR  Design a příprava primerů (Dr. Hana Konečná) Osnova  Nástroje systémové biologie  Analýza genové ontologie  Modelování molekulárních regulačních sítí  Modelové organismy  Mus musculus  Arabidopsis thaliana  Vybrané metody molekulární biologie  Příprava transgenních organismů  PCR  Design a příprava primerů (Dr. Hana Konečná) Shrnutí Diskuse