CG920 Genomics
Lesson 5
Gene Expression and Chemical Genetics
Jan Hejátko
Functional Genomics and Proteomics of Plants,
Mendel Centre for Plant Genomics and Proteomics,
Central European Institute of Technology (CEITEC), Masaryk University, Brno
hejatko@sci.muni.cz, www.ceitec.muni.cz
 Literature sources for Chapter 05:
 Surpin, M. and Raikhel, N. (2004) Traffic jams affect plant development and
signal transduction. Nature Reviews/Molecular Cell Biology 5,100-109
 Zouhar, J., Hicks, G.R. and Raikhel, N.V. (2004) Sorting inhibitors (Sortins):
Chemical compounds to study vacuolar sorting in Arabidopsis. Proceedings of
the National Academy of Sciences of the U.S.A., 101, 9497–9501
 Nevo-Dinur, K., Nussbaum-Shochat, A., Ben-Yehuda, S., and Amster-Choder,
O. (2011). Translation-independent localization of mRNA in E. coli. Science 331,
1081-1084.
 Lecuyer, E., Yoshida, H., Parthasarathy, N., Alm, C., Babak, T., Cerovina, T.,
Hughes, T.R., Tomancak, P., and Krause, H.M. (2007). Global analysis of mRNA
localization reveals a prominent role in organizing cellular architecture and
function. Cell 131, 174-187.
 Schonberger, J., Hammes, U.Z., and Dresselhaus, T. (2012). In vivo
visualization of RNA in plants cells using the lambdaN(22) system and a
GATEWAY-compatible vector series for candidate RNAs. The Plant journal : for
cell and molecular biology 71, 173-181.
Literature
2
 Methods of gene expression analysis
 Qualitative analysis of gene expression
 Preparation of transcriptional fusion of promoter of analysed gene
with a reporter gene
 Preparation of translational fusion of the coding region of the analysed
gene with reporter gene
 Use of the data available in public databases
 Tissue- and cell-specific gene expression analysis
 Quantitative analysis of gene expression
 DNA and protein chips
 Next generation transcriptional profiling
 Regulation of gene expression in the identification of
gene function by gain-of-function approaches
 T-DNA activation mutagenesis
 Ectopic expression and regulatable gene expression
systems
 Chemical genetics
Outline
3
 Methods of gene expression analysis
 Qualitative analysis of gene expression
 Preparation of transcriptional fusion of promoter of analysed gene
with a reporter gene
Outline
4
□ Transcriptional fusion with a promoter region
 Identification and cloning of the promoter region of the gene
 Preparation of recombinant DNA carrying the promoter and the
reporter gene (uidA, GFP)
TATA box
Iniciation of transcription
promoter
5’ UTR
ATG…ORF of reporter gene
Gene expression
5
□ Transcriptional fusion with a promoter region
 Identification and cloning of the promoter region of the gene
 Preparation of recombinant DNA carrying the promoter and the
reporter gene (uidA, GFP)
 Preparation of transgenic organisms carrying this recombinant DNA
and their histological analysis
Gene expression
6
GUS reporter in mouse
embryos
7
 Methods of gene expression analysis
 Qualitative analysis of gene expression
 Preparation of transcriptional fusion of promoter of analysed gene
with a reporter gene
 Preparation of translational fusion of the coding region of the analysed
gene with reporter gene
Outline
8
□ Translational fusion of coding region of analysed gene with a
reporter gene
 Identification and cloning of the promoter and coding region of the
analysed gene
 Preparation of a recombinant DNA carrying the promoter and the coding
sequence of the studied gene in fusion with the reporter gene (uidA, GFP)
TATA box
promoter
5’ UTR
ATG…ORF of analysed gene…..….ATG…ORF of reporter gene….….....STOP
Gene expression
9
□ Translational fusion of coding region of analysed gene with a
reporter gene
 Preparation of transgenic organisms carrying the recombinant DNA and
their histological analysis
 Compared to transcriptional fusion, translation fusion allows analysis of e.g.
Intercellular localization of gene product (protein) or its dynamics
Histone 2A-GFP in Drosophila embryo by PAM
Gene expression
PIN1-GFP in Arabidopsis
10
 Methods of gene expression analysis
 Qualitative analysis of gene expression
 Preparation of transcriptional fusion of promoter of analysed gene
with a reporter gene
 Preparation of translational fusion of the coding region of the analysed
gene with reporter gene
 Use of the data available in public databases
Outline
11
Gene expression
□ Analysis of expression using Genevestigator (AHP1 and
AHP2, Arabidopsis, Affymetrix ATH 22K Array)
12
Gene expression
□ Analysis of expression using Genevestigator (AHP1 and
AHP2, Arabidopsis, Affymetrix ATH 22K Array)
13
Gene expression
□ Analysis of expression using Genevestigator (AHP1 and
AHP2, Arabidopsis, Affymetrix ATH 22K Array)
14
 Methods of gene expression analysis
 Qualitative analysis of gene expression
 Preparation of transcriptional fusion of promoter of analysed gene
with a reporter gene
 Preparation of translational fusion of the coding region of the analysed
gene with reporter gene
 Use of the data available in public databases
 Tissue- and cell-specific gene expression analysis
Outline
15
Fluorescence-Activated Cell Sorting (FACS)
□ High-Resolution Expression Map in Arabidopsis Root
Expression Maps - RNA
Brady et al., Science, 2007
Microarray expression profiles of 19
fluorescently sorted GFP-marked lines
were analyzed (3–9, 23, 24). The
colors associated with each marker line
reflect the developmental stage and
cell types sampled. Thirteen transverse
sections were sampled along the root's
longitudinal axis (red lines) (10). CC,
companion cells.
16
□ High-Resolution Expression Map in Arabidopsis Root
Expression Maps - RNA
Brady et al., Science, 2007
17
(A) The majority of enriched GO terms (hierarchically clustered) are associated with individual
cell types (blue bar). A smaller number are present across multiple cell types (green bar). (fig.
S2) (B) GO category enrichment for hair cells confirms a previous report (15). Enriched ciselements
and an enriched TF family were also identified. (C) From the top 50% of varying probe
sets, 51 dominant radial patterns were identified. Pattern expression values were meannormalized
(rows) and log2 transformed to yield relative expression indices for each marker line
(columns). Marker line order is the same for all figures; see table S1 for marker line
abbreviations. (D) Pattern expression peaks were found across one to five cell types. (E to G)
Patterns where expression is enriched in single and multiple cell types support transcriptional
regulation of auxin flux and synthesis. In all heat maps with probe sets, expression values were
mean-normalized and log2 transformed. Expression is false-colored in representations of a root
transverse section, a cut-away of a root tip, and in a lateral root primordium. (E) Auxin
biosynthetic genes (CYP79B2, CYP79B3, SUPERROOT1, and SUPERROOT2) are
transcriptionally enriched in the QC, lateral root primordia, pericycle, and phloem-pole pericycle
(P = 1.99E–11
, pattern 5). All AGI identifiers and TAIR descriptions are found in table S14. (F)
Auxin amido-synthases GH3.6 and GH3.17 that play a role in auxin homeostasis show enriched
expression in the columella, just below the predicted auxin biosynthetic center of the QC (P =
8.82E–4
, pattern 13). (G) The expression of the auxin transporter, PIN-FORMED2, and auxin
transport regulators (PINOID, WAG1) are enriched in the columella, hair cells, and cortex (P =
1.03E–4
, pattern 31).
18
Expression Maps - Proteins
Ponten et al., J Int Med, 2011
□ Human Protein Atlas
19
Schematic flowchart of the Human Protein Atlas. For each gene, a signature
sequence (PrEST) is defined from the human genome sequence, and following
RT-PCR, cloning and production of recombinant protein fragments, subsequent
immunization and affinity purification of antisera results inmunospecific
antibodies. The produced antibodies are tested and validated in various
immunoassays. Approved antibodies are used for protein profiling in cells
(immunofluorescence) and tissues (immunohistochemistry) to generate the
images and protein expression data that are presented in the Human Protein
Atlas (Ponten et al., J Int Med, 2011).
20
□ Human Protein Atlas
(http://www.proteinatlas.org/)
Expression Maps - Proteins
21
□ Human Protein Atlas
(http://www.proteinatlas.org/)
Expression Maps - Proteins
22
 Methods of gene expression analysis
 Qualitative analysis of gene expression
 Preparation of transcriptional fusion of promoter of analysed gene
with a reporter gene
 Preparation of translational fusion of the coding region of the analysed
gene with reporter gene
 Use of the data available in public databases
 Tissue- and cell-specific gene expression analysis
 Quantitative analysis of gene expression
 DNA and protein chips
Outline
23
 DNA chips
 Method, which provides quick comparison of a large
number of genes/proteins between the test sample and
control
 Oligo DNA chips are used the most
 There are commercialy available kits for the whole genome
 company Operon (Qiagen), 29.110 of 70-mer oligonucleotides representing
26.173 genes coding proteins, 28.964 transcripts and 87 microRNA genes
of Arabidopsis thaliana
 Possibility of use for the preparation of photolithography chips – facilitation
of oligonucletide synthesis e.g. for the whole human genome (about 3,1 x
109 bp) jit is possible to prepare 25-mers in only 100 steps, by this
technique
Affymetrix ATH1 Arabidopsis genome array
 Chips not only for the analysis of
gene expression, but also for e.g.
Genotyping (SNPs, sequencing
with chips, …)
DNA Chips
24
 DNA chips, analysis of results
 For the correct interpretation of the results, good knowledge
of advanced statistical methods is required
 Control of accuracy of the measurement (repeated
measurements on several chips with the same
sample, comparing the same samples analysed on
different chips with each other)
 It is necessary to include a sufficient number of controls and
repeats
 Control of reproducibility of measurements
(repeated measurements with different samples
isolated under the same conditions on the same
chip – comparing with each other)
Che et al., 2002
 Identification of reliable measurement treshold
nespolehlivé
spolehlivé
 Finally comparing the experiment with the control or
comparing different conditions with each other ->
the result
 Currently there‘s been a great number of results of various
experiments in publicly accessible databases
DNA Chips
25
 Protein chips
 Chips with high density containing 104 proteins
 Analysis of protein-protein interactions, kinase substrates
and interactions with small molecules
 Possibility of using antibodies – more stable than proteins
Protein Chips
26
 Identification of proteins interacting with integrin αIIbβ3
cytoplasmic domain of platelets
 Expression of cytoplasmic part as a
fusion peptide biotin-KVGFFKR
 Analysis of binding to the protein
chip containing 37.000 clones of E.
coli expressing human recombinant
proteins
 Confirmation of interaction by pulldown
analysis of peptides and by
coprecipitation of whole proteins as
well (e.g. chloride channel Icln)
 Other use: e.g. in the identification of
kinase substrates, when substrates
are bound to the chip and exposed to
kinases in the presense of
radiolabeled ATP (786 purified
proteins of barely, of which 21 were
identified as CK2α kinase substrates;
Kramer et al., 2004)
Lueking et al., 2005
Protein Chips
27
 Methods of gene expression analysis
 Qualitative analysis of gene expression
 Preparation of transcriptional fusion of promoter of analysed gene
with a reporter gene
 Preparation of translational fusion of the coding region of the analysed
gene with reporter gene
 Use of the data available in public databases
 Tissue- and cell-specific gene expression analysis
 Quantitative analysis of gene expression
 DNA and protein chips
 Next generation transcriptional profiling
Outline
28
WT hormonal mutant
Next Gen Transcriptional
Profiling
□ Transcriptional profiling via RNA sequencing
mRNA
Sequencing by Illumina and
number of transcripts determination
mRNA
cDNA cDNA
29
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
30
 Methods of gene expression analysis
 Qualitative analysis of gene expression
 Preparation of transcriptional fusion of promoter of analysed gene
with a reporter gene
 Preparation of translational fusion of the coding region of the analysed
gene with reporter gene
 Use of the data available in public databases
 Tissue- and cell-specific gene expression analysis
 Quantitative analysis of gene expression
 DNA and protein chips
 Next generation transcriptional profiling
 Regulation of gene expression in the identification of
gene function by gain-of-function approaches
 T-DNA activation mutagenesis
Outline
31
 Methods for identification of gene function using gain-of-function
approaches
 T-DNA activation mutagenesis
 Method enabling isolation of dominant mutants by random
insertion of constitutive promoter, resulting in
overexpression of the gene and therefore in corresponding
phenotypic changes
 First step: preparation of mutant library prepared by
tansformation of a strong constitutive promoter or enhancer
 Next step: search of interesting phenotypes
 Identification of the affected gene, e.g. by plasmid-rescue
Gain-of-Function Approaches
32
TF TF
TF
40S
60S
TF TF TF TF
40S
60S
40S
60S
40S
60S
40S
60S
TF TF
TF
Activation Mutagenesis
33
Isolation of CKI1 gene
- Isolation of the gene using activation mutagenesis
- Mutant phenotype is a phenocopy of
exogenous application of cytokinins (CKI1,
CYTOKININ INDEPENDENT 1)
*- Tatsuo Kakimoto, Science 274 (1996), 982-985 *
*
no hormones
t-zeatin
K1 K2plasmid
rescue
35S::CK1
cDNA
34
 Methods of gene expression analysis
 Qualitative analysis of gene expression
 Preparation of transcriptional fusion of promoter of analysed gene
with a reporter gene
 Preparation of translational fusion of the coding region of the analysed
gene with reporter gene
 Use of the data available in public databases
 Tissue- and cell-specific gene expression analysis
 Quantitative analysis of gene expression
 DNA and protein chips
 Next generation transcriptional profiling
 Regulation of gene expression in the identification of
gene function by gain-of-function approaches
 T-DNA activation mutagenesis
 Ectopic expression and regulatable gene expression
systems
Outline
35
 Regulatable gene expression systems
 Time- or site-specific regulation of gene expression, leading
to a change in phenotype and thereby identification of the
natural function of the gene
 pOP system
Regulated Expression Systems
36
35S
LhG4
pOP
TATA
CKI1
activator
reporter
activator x reporter
x
Regulated Expression Systems
37
35S
LhGR
pOP
TATA
CKI1
activator
reporter
activator x reporter
DEX DEX
+DEX DEX
DEX
DEX
x
Regulated Expression Systems
38
35S
LhGR
pOP
TATA
CKI1
activator
reporter
activator x reporter
DEX DEX
+DEX DEX
DEX
DEX
x
pOP
TATA
GUS
DEX DEX
wt Col-0
4C
Regulated Expression Systems
39
 UAS system
http://www.plantsci.cam.ac.uk/Haseloff/
Regulated Expression Systems
 Regulatable gene expression systems
 Time- or site-specific regulation of gene expression, leading
to a change in phenotype and thereby identification of the
natural function of the gene
 pOP system
40
 Methods of gene expression analysis
 Qualitative analysis of gene expression
 Preparation of transcriptional fusion of promoter of analysed gene
with a reporter gene
 Preparation of translational fusion of the coding region of the analysed
gene with reporter gene
 Use of the data available in public databases
 Tissue- and cell-specific gene expression analysis
 Quantitative analysis of gene expression
 DNA and protein chips
 Next generation transcriptional profiling
 Regulation of gene expression in the identification of
gene function by gain-of-function approaches
 T-DNA activation mutagenesis
 Ectopic expression and regulatable gene expression
systems
 Chemical genetics
Outline
41
 New trends
 „chemical genetics“ – more than 50.000/89.631 records in PubMed
database (16.10. 2008/29.10. 2015, an increase of 65 %)
 Chemical genetics
Chemical Genetics
42
 Like in the case of genetics, there are also „forward“ and
„reverse“ genetics approaches
 Unlike in „classical“ genetics approaches, the subject of
study is not a gene, but a protein
 Chemical genetics tries to identify either the target protein
after a chemical treatment and after following phenotypic
changes („forward“ chemical genetics) or chemicals able
to interact with protein of interest („reverse“ chemical
genetics)
 For that purpose there are carried out searches in the
libraries of various chemicals (thousands of entries,
comercially available)
 example: analysis of endomembrane transport in plants
Chemical Genetics
 New trends
 „chemical genetics“ – more than 50.000/89.631 records in PubMed
database (16.10. 2008/29.10. 2015, an increase of 65 %)
 Chemical genetics
43
 Analysis of mechanisms of endomembrane transport by
chemical genetics approaches
 In plants cells there occurr very dynamic processes mediated mainly
by endomembrane transport (see film, GFP targeting to the ER)
Chemical Genetics
44
 Endomembrane transport is an important regulatory mechanism in
signal transduction and regulation of cellular processes
Chemical Genetics
 Analysis of mechanisms of endomembrane transport by
chemical genetics approaches
 In plants cells there occurr very dynamic processes mediated mainly
by endomembrane transport (see film, GFP targeting to the ER)
45
Richter et al., E J Cell Biol (2010)
Anterograde
transport
Retrograde
transport
Trans-Golgi
network
Multivesicular
bodies-late
endosome
(prevacuolar
compartment)
Recycling
endosome
46
In the figure, there is simplified scheme of vesicle trafficking pathways, regulated by GNOM and
its closest relative, GNOM-LIKE1 (GNL1).
Secretory and membrane proteins are synthesised at the ER (blue) and passed onto the Golgi
apparatus (green) by anterograde trafficking in COPII-coated vesicles.
The retrograde route from the Golgi apparatus to the ER is regulated by the ARF-GEFs GNOM
(GN) and GNL1, which regulate the recruitment of COPI coats to the Golgi membrane. On the
secretory route, proteins are transported to the sorting station, the trans-Golgi network (TGN;
lilac).
From there, proteins are either transported to the vacuole (grey) via multivesicular bodies (MVB,
also called prevacuolar compartment, PVC, which corresponds to the late endosome; deep
blue) or trafficked to the plasma membrane (PM).
Plasma membrane proteins like the auxin efflux carrier PIN1 (red), which accumulates at the
basal PM at steady state, are continually internalised and trafficked to the TGN, which
resembles the early endosome (EE) in plants.
From the TGN, PIN1 is recycled to the plasma membrane via the recycling endosome (RE; light
blue). This pathway is regulated by the ARF-GEF GNOM.
47
 Analysis of mechanisms of endomembrane transport by
chemical genetics approaches
 By searching in the „library“ of chemicals there were
identified those, that lead to the secretion of enzyme
(carboxypeptidase Y) in yeast (S. cerevisiae) – this
enzyme is normally transported to the vacuole via the
endomembrane transport
 Analysis of changes in secretion using dotblot
and immunodetection of
carboxypeptidase Y in the culture medium
with monoclonal antibodies
Zouhar et al., 2004
Chemical structure of sortins
Detection of vacuole phenotype (tonoplast shape) of
yeast by staining with a specific color (MDY-64)
Immunodetection of carboxypeptidase
Chemical Genetics
48
 Analysis of mechanisms of endomembrane transport by
chemical genetics approaches
 Identified compounds („sortins“) were able to induce
similar changes in Arabidopsis as well – transport
mechanisms are conserved in yeast and in plants
 For detailed identification of the molecular proces
affected by one of the identified „sortins“, the analysis
of its influence on a secretion of a marker protein
(AtCPY) was performed – sortin 1 specifically inhibits
only this secretory pathway
 Identifcation of mutants with altered sensitivity to
sortin 1 (hyper- or hypo-sensitive mutants) by EMS
mutagenesis
Zouhar et al., 2004
Shape of plant vacuoles using EGFP:-TIP
Phenotype of seedlings in the presence of sortins
Sortin 1
Sortin 2
Chemical Genetics
 By searching in the „library“ of chemicals there were
identified those, that lead to the secretion of enzyme
(carboxypeptidase Y) in yeast (S. cerevisiae) – this
enzyme is normally transported to the vacuole via the
endomembrane transport
 Analysis of changes in secretion using dotblot
and immunodetection of
carboxypeptidase Y in the culture medium
with monoclonal antibodies
49
 Analysis of mechanisms of endomembrane
transport by chemical genetics approaches –
summary
 GFP::d-TIP vacuole membrane
(tonoplast) labelling and identification
of mutations leading to altered
tonoplast morphology
 Chemical genetics in combination with
classical genetics – identification of
proteins participating in regulation of
endomembrane transport
 Proteomics approaches –
identification and analysis of vacuole
proteome
Chemical Genetics
50