Plant epigenetic
memory in plant
growth behavior
and stress
response

Genetic vs epigenetic variation in
plants
• Epigenetic effects are often associated with
environmental interactions
• Short term memory: associated with
chromatin changes that facilitate rapid
redeployment of gene networks that have
been activated previously
• Long-term memory: This would be
transgenerational. Does it exist?

Genetic vs epigenetic variation in
plants
• Epigenetic effects are often associated with
environmental interactions
• Short term memory: associated with
chromatin changes that facilitate rapid
redeployment of gene networks that have
been activated previously
• Long-term memory: This would be
transgenerational. Does it exist?

Genetic vs epigenetic variation in
plants
• Epigenetic effects are often associated with
environmental interactions
• Short term memory: associated with
chromatin changes that facilitate rapid
redeployment of gene networks that have
been activated previously
• Long-term memory: This would be
transgenerational. Does it exist?

Anecdotal examples
• Plants in the forest understory
• Turf variety instability
• Corals in warming oceans
CHRONIC
STRESS
CONDITIONS

Introduction to MSH1 (MutS Homolog 1)
Abdelnoor et al. J Mol Evol. 2006.
• Plant specific MutS homolog with 22 exons and 6 protein domains
• Nuclear-encoded but dual organelle-targeted
• Mitochondria - suppresses illegitimate recombination
• Plastids – developmental reprogramming

Col-0
msh1
msh1 Arabidopsis =
developmental reprogramming
(msh1-dr)
Xu et al. Plant Physiol, 2012
Cold, heat, high
light, drought

Global transcriptome changes
GO:0009851 auxin biosynthetic process
GO:0007623 circadian rhythm
GO:0006952 defense response
GO:0009595 detection of biotic stimulus
GO:0010286 heat acclimation
GO:0016572 histone phosphorylation
GO:0042538 hyperosmotic salinity response
GO:0006955 immune response
GO:0009694 jasmonic acid metabolic process
GO:0000165 MAPK cascade
GO:0009765 photosynthesis, light harvesting
GO:0072593 reactive oxygen species metab
GO:0009628 response to abiotic stimulus
GO:0009607 response to biotic stimulus
GO:0006979 response to oxidative stress
GO:0009697 salicylic acid biosynthesis
Select from shared Variegated and Dwarf DEG’s
# DEG’s (FDR < 0.05, |log2FC|≥1)
The msh1-associated developmental reprogramming involves a
heightened global stress response
msh1 S1
msh1 S2 Var-
dwarf
msh1 S2
Variegated

msh1 memory

msh1
memory
effects on
gene
expression
and
methylome

Putative signature loci for msh1 memory based on methylome-RNAseq-
network analysis

msh1
memory
effects on
circadian
clock

Methylation
inhibitor 5-
azacytidine
obviates the
signature gene
expression
changes for msh1
memory

msh1 memory effects recapitulate in tomato

Molecular Plant 8:1135, 2015
Candidate genes demonstrating altered methylation and gene
expression in the msh1-dr memory lines
Circadian rhythm (10%)
Response to stress (67%)
Starch, glucan, polysaccharide
metabolism (23%)

Tomato Soybean Tobacco SorghumMillet
+GA-GA
MSH1 suppression results in developmental reprogramming in
all plant species tested to date
These developmental changes are subsequently heritable independent of transgene:
“msh1-memory line”

Isogenic WT x msh1 F3

Rutgers wt
Rutgers EpiF3

30 uM5-azacytidine
0 uM5-azacytidine
wt
wt
wt wt
wt
wt
F4
F4
F4 F4
F4 F4
Chemical demethylation effects in tomato

W
T
F4
30mM 5-azacytidine 10 mM ethionine
WT F4 WT F4
0 mM Control
Yang et al. 2015 Plant Physiol

Scion :Rutgers
Stock :T20-4-4-2(+)
Scion :Rutgers
Stock : Rutgers
T20-4-4-2(+) Rutgers
Grafted progeny Parentals
Grafting Effects In Tomato

2014 Soybean Field Test Demonstrates up to 15% Yield Increases
Soybean 2014 Field Trial Results
Parental crosses of lines tested
Yield normalized
to control at 100%
Mean weight per plot Standard Error
WT- Bulk (30 plants) 100% 914.5 18.2
WT- Top 50% 100% 913.25 74.63
(T8 x Wt) Bulk F2:4 R-10 106% 967.5 65.75
(T8 x Wt) Bulk F2:4 R-34 110% 1004.5 37.24
(T8 x Wt) Bulk F2:4 R-38 101% 923.75 32.87
(T8 x Wt) Top 50% F2:4 R-10 115% 1048.5 16.35***
(T8 x Wt) Top 50% F2:4 R-34 114% 1046.25 63.11
(T8 x Wt) Top 50% F2:4 R-38 109% 994.5 36.33
(Wt x T9) Bulk F2:4 P-37 110% 1010.5 30.44*
(Wt x T9) Bulk F2:4 P-38 102% 936.5 23.05
(Wt x T9) Top 50% F2:4 P-34 105% 955.75 47.19
(Wt x T9) Top 50% F2:4 P-37 108% 990 22.85
Parental
Controls
T8
epigenetic
lines
T9
epigenetic
lines
23

Large-scale field testing:
Gen % above WT
F3 13%
F4 14%
F5 2-6%
F6 0%

Key questions:
• Specificity and reproducibility of the
phenomenon: Who came first, the
transcription factor response, or the
chromatin configuration?
• Origin of the epigenetic trigger: organellar
signal?

MSH1 localizes to mitochondrial
and plastid nucleoids
DAPI GFP
MSH1 resides
within the plastid
nucleoid
Virdi et al. 2016
Mol Plant

Virdi et al, Molecular Plant 2016.
MSH1 localizes predominantly to a subset of plastids: ‘sensory plastids’
Epidermal
Sensory
plastid
Mesophyll
plastid
MSH1::GFP
MSH1 is present in epidermal and vascular parenchyma plastids and reproductive tissues.
About 30% the size of a mesophyll chloroplast
Less extensive thylakoid membrane and granal stacking
Fewer visible plastoglobules
Lower autoflorescense signal

Col 0 (WT) MSH1::GFP PPD3::GFP
MSH1 interacting partner PPD3 localizes to ‘sensory plastids’
MSH1::GFP
PPD3::RFP
MSH1 overexpression PPD3 overexpression

GFP + GFP -
Fluorescence-activated cell sorting (FACS)
‘Sensory plastids’ in planta ‘Sensory plastids’ sorted
‘Sensory plastids’ Chloroplasts

Chloroplasts‘Sensory plastids’
Chlorophyll mean fluorescence intensity
‘Sensory plastids’

‘Sensory plastid’Chloroplast
Proteome of sensory plastids vs chloroplasts
Term P-value
Oxidation-reduction process 1.3E-17
Response to cadmium ion 4.2E-67
Translation 9.8E-9
Response to cytokinin 8.5E-57
Response to stress 4.8E-19
Response to cold 3.1E-26
Photosynthesis 1.3E-33
Term P-value
Photosynthesis 2.5E-49
Oxidation-reduction 2.7E-6
Response to cold 2.6E-15
Response to cadmium ion 3.5E-12
Response to cytokinin 8.7E-16
Translation 6.3 E-2
Transport 1.1E-7
Proteome experiments suggest that sensory plastid main function is not photosynthesis

Floral stems
TRAP-Seq
MSH1 cell-specific translatome
Seq
Transcriptome
Total RNA
MSH1 cell-specific translatomes
msh1 vs WT
mRNAs associated with ribosomes

Translating Ribosome Affinity Purification (TRAP) Followed by
RNA Sequencing Technology (TRAP-SEQ)
mRNAs associated to actively translating ribosomes
MSH1 cell-type profiling
AAAA
FLAG
AAAA
RNA-Seq
Affinity purification
MSH1 P RPL-18
(P758bp:: FLAG::RPL-18)
FLAG

( msh1_IP_vs_msh1_total ) vs (WT_IP_vs_WT_total)
msh1 WT
Nucleosome assembly
- Histones
Signaling
-Calcium–binding proteins
-Proteins kinases
Oxidative stress
-Peroxidases
-Thioredoxin
-Methionine superoxide dismutase
-Glutathione peroxidase
Hormones
Stress
Transcription
Circadian rhythm
MSH1 cell-specific translatome
RNA processing
DNA replication
Protein autophosphorylation

Circadian rhythm
Response to stress
Hormones
Regulation of transcription
Others
msh1 transcriptome msh1 translatome
Memory line
PV < 0.05
Some signature genes in the memory line

PC-8
0
2
4
6
8
10
12
14
Col-0 msh1
nmoles/gFW
leaf
0
0.5
1
1.5
2
2.5
3
Col-0 msh1
*
stem
0
20
40
60
80
100
120
Col-0 msh1
nmoles/gFW
PQ9
PQ9H2
leaf
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00
16.00
18.00
20.00
Col-0 msh1
*
stem
Plastoquinone Plastochromanol-8
Demethylated K1
MSH1 depletion alters redox homeostasis

Association of ‘sensory plastids’ and MSH1 in all plants
Loss of MSH1 results in programmed phenotypic change. Xu et al 2012, Plant Physiology.

MSH1
depletion
ROS/redox
Ca 2+
CaMs
CBKs
PKC
Working model based on Sun & Guo 2016 ,Plant Science and our data
MAPKs
Nucleus
MSH1 cell
‘Sensory plastid’
Target genes:
Histones
Redox-reduction
Circadian rhythm
Hormones
Stress
Methylation changes
Gene expression changes
Phenotypes
Developmental reprogramming
Global stress response
‘msh1 memory’
Cytosol

A working model for MSH1 action:
Abiotic stress
MSH1
suppression
Heritable effects via
methylome repatterning of
a subset of pathways
Plastid perturbation = global
stress response
Ca2+------MAPK3------Altered TF
Recruitment of methylation machinery

Ray Shao, transcriptome analyses
Sunil Kumar, stress response studies, soybean
Hardik Kundariya, RNAi- studies
Xiaodong Yang, memory gene expression
and tomato msh1 studies
Jesus Beltran, sensory plastid studies
Robersy Sanchez, computation
Jose Raul Barreras, computation