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Evolutionary Genetics of a
Complex Plant Genome
Jeffrey Ross-Ibarra
@jrossibarra • www.rilab.org
Dept. Plant Sciences • Center for Population Biology • Genome Center
University of California Davis
https://commons.wikimedia.org/wiki/File:Diversity_of_plants_image_version_5.png
hard
sweep
how do genomes adapt?
hard
sweep
how do genomes adapt?
hard
sweep
how do genomes adapt?
hard
sweep
multiple
mutations
“soft” sweeps
how do genomes adapt?
hard
sweep
multiple
mutations
standing
variation
“soft” sweeps
how do genomes adapt?
M T G P H R L
GGTCGAC ATG ACT GGT CCA CAT CGA CTG TAG
M T G P H R L
GGTCGAC ATG ACT GGT CCA CAT CGA CTG TAG
M T N P H R L
GGTCGAC ATG ACT GAT CCA CAT CGA CTG TAG
structural
change to protein
M T G P H R L
GGTAAAC ATG ACT GGT CCA CAT CGA CTG TAG
GG—-AC ATG ACT GGT CCA CAT CGA CTG TAG
regulatory change to
expression
Lowry & Willis 2010 PLoS Biology
Gaut and Ross-Ibarra 2008
Kew C-Value Database
Paris Japonica
150GB Genome
Genlisia aurea
63MB Genome Michal Rubeš
Michal Rubeš
1.5
2.5
3.5
4.5
Angiosperm
average
6400 Mb
Non-TE DNA
TE DNALog(genomesizeinMb)
0
1,500
3,000
4,500
6,000
0 1500 3000 4500 6000
Genomesize(Mb)
TE content (Mb)
r = 0.99
Arabidopsisthaliana
Arabidopsislyrata
Brachypodiumdistachyon
Papaya
Rice
Lotusjaponicus
Blackcottonwood
Grapevine
Cabbage
Medicagotrunculata
Sorghum
Soybean
Levantcotton
Maize
Aegilopsspeltoides
Barley
Thursday, May 6, 2010
Tenaillon et al. 2010 TIP
Suketoshi Taba
44.6 Mb 44.7 Mb 44.8 Mb 44.9 Mb
Gene
LTR
Retrotransposon
maize - 2300 Mb
50 kb
7.4 Mb 7.5 Mb 7.6 Mb 7.7 Mb 7.8 Mb 7.9 Mb
50 kb
Gene
LTR
Retrotransposon
arabidopsis - 130 Mb
Zea maysA. thaliana
Angiosperm 1C genome size (Mb)
MbDNA
1
10
100
1000
10000
Arabidopsis Maize
15.5
3.4
70
50
2,300
135
Genome
CDs
Intergenic open chromatin
Sullivan et al. Cell Reports 2014
Rodgers-Melnick et al. PNAS 2016
MbDNA
1
10
100
1000
10000
Arabidopsis Maize
15.5
3.4
70
50
2,300
135
Genome
CDs
Intergenic open chromatin "Functional" DNA
0%
25%
50%
75%
100%
Arabidopsis maize
81%93%
19%7%
Intergenic
CDs
Sullivan et al. Cell Reports 2014
Rodgers-Melnick et al. PNAS 2016
Ne individuals, µ beneficial mutation rate per trait
bigger genome, larger mutation target, higher µ
predict that larger genomes adapt via
standing variation, noncoding variants
Ne individuals, µ beneficial mutation rate per trait
bigger genome, larger mutation target, higher µ
predict that larger genomes adapt via
standing variation, noncoding variants
selection from standing variation when 2Neµ > 1
Ne individuals, µ beneficial mutation rate per trait
bigger genome, larger mutation target, higher µ
predict that larger genomes adapt via
standing variation, noncoding variants
selection from standing variation when 2Neµ > 1
larger % of µ should be noncoding
maizeteosinte
1 2 3 4 5
6 7 8 9 10
Briggs et al. 2007 Genetics
1 2 3 4 5
6 7 8 9 10
tb1
Studer et al. 2011 Nature Genetics.; Vann et al. 2015 PeerJ
GENETICS ADVANCE ONLINE PUBLICATION 3
nguish maize and teosinte. Both the maize and teosinte
s for the distal component repressed luciferase expression
luc
luc
luc
luc
luc
luc
Hopscotch
mpCaMV
M-dist
T-prox
M-prox
0 0.5 1.0 1.5 2.0
∆M-dist
∆M-prox
ProximalcontrolregionDistal
Constructs and corresponding normalized luciferase expression
nsient assays were performed in maize leaf protoplast. Each
is drawn to scale. The construct backbone consists of the
romoter from the cauliflower mosaic virus (mpCaMV, gray box),
ORF (luc, white box) and the nopaline synthase terminator
). Portions of the proximal and distal components of the
gion (hatched boxes) from maize and teosinte were cloned
ction sites upstream of the minimal promoter. “ ” denotes
on of either the Tourist or Hopscotch element from the maize
Horizontal green bars show the normalized mean with s.e.m.
onstruct.
relative expressionconstruct
1 2 3 4 5
6 7 8 9 10
tb1
Figure 2 Map of parviglumis Populations and Hopscotch allele frequency. Map showing the frequency
of the Hopscotch allele in populations of parviglumis where we sampled more than 6 individuals. Size of
circles reflects number of individuals sampled. The Balsas River is shown, as the Balsas River Basin is
believed to be the center of domestication of maize.
as our independent trait for phenotyping analyses. SAS code used for analysis is available at
http://dx.doi.org/10.6084/m9.figshare.1166630.
RESULTS
Genotyping for the Hopscotch insertion
The genotype at the Hopscotch insertion was confirmed with two PCRs for 837 individuals
of the 1,100 screened (Table S1 and Table S2). Among the 247 maize landrace accessions
genotyped, all but eight were homozygous for the presence of the insertion Within
our parviglumis and mexicana samples we found the Hopscotch insertion segregating
in 37 (n = 86) and four (n = 17) populations, respectively, and at highest frequency
within populations in the states of Jalisco, Colima, and Michoac´an in central-western
Mexico (Fig. 2). Using our Hopscotch genotyping, we calculated diVerentiation between
populations (FST) and subspecies (FCT) for populations in which we sampled sixteen
or more chromosomes. We found that FCT = 0, and levels of FST among populations
within each subspecies (0.22) and among all populations (0.23) (Table 1) are similar to
genome-wide estimates from previous studies Pyh¨aj¨arvi, HuVord & Ross-Ibarra, 2013.
Although we found large variation in Hopscotch allele frequency among our populations,
BayEnv analysis did not indicate a correlation between the Hopscotch insertion and
environmental variables (all Bayes Factors < 1).
Studer et al. 2011 Nature Genetics.; Vann et al. 2015 PeerJ
GENETICS ADVANCE ONLINE PUBLICATION 3
nguish maize and teosinte. Both the maize and teosinte
s for the distal component repressed luciferase expression
luc
luc
luc
luc
luc
luc
Hopscotch
mpCaMV
M-dist
T-prox
M-prox
0 0.5 1.0 1.5 2.0
∆M-dist
∆M-prox
ProximalcontrolregionDistal
Constructs and corresponding normalized luciferase expression
nsient assays were performed in maize leaf protoplast. Each
is drawn to scale. The construct backbone consists of the
romoter from the cauliflower mosaic virus (mpCaMV, gray box),
ORF (luc, white box) and the nopaline synthase terminator
). Portions of the proximal and distal components of the
gion (hatched boxes) from maize and teosinte were cloned
ction sites upstream of the minimal promoter. “ ” denotes
on of either the Tourist or Hopscotch element from the maize
Horizontal green bars show the normalized mean with s.e.m.
onstruct.
relative expressionconstruct
Wang et al. 2005 Nature
Wang et al 2015 Genetics
1 2 3 4 5
6 7 8 9 10
Figure 1.
Phenotypes. a. Maize ear showing the cob (cb) exposed at top. b. Teosinte e
internode (in) and glume (gl) labeled. c. Teosinte ear from a plant with a m
introgressed into it. d. Close-up of a single teosinte fruitcase. e. Close-up o
teosinte plant with a maize allele of tga1 introgressed into it. f. Ear of maiz
(Tga1-maize allele) with the cob exposed showing the small white glumes a
of maize inbred W22:tga1 which carries the teosinte allele, showing enlarge
h. Ear of maize inbred W22 carrying the tga1-ems1 allele, showing enlarged g
NIH-PAAuthorManuscriptNIH-PAAuthorManuscriptNIH-P
tga1tb1
Wang et al. 2005 Nature
Wang et al 2015 Genetics
1 2 3 4 5
6 7 8 9 10
Figure 1.
Phenotypes. a. Maize ear showing the cob (cb) exposed at top. b. Teosinte e
internode (in) and glume (gl) labeled. c. Teosinte ear from a plant with a m
introgressed into it. d. Close-up of a single teosinte fruitcase. e. Close-up o
teosinte plant with a maize allele of tga1 introgressed into it. f. Ear of maiz
(Tga1-maize allele) with the cob exposed showing the small white glumes a
of maize inbred W22:tga1 which carries the teosinte allele, showing enlarge
h. Ear of maize inbred W22 carrying the tga1-ems1 allele, showing enlarged g
NIH-PAAuthorManuscriptNIH-PAAuthorManuscriptNIH-P
tga1tb1
1 2 3 4 5
6 7 8 9 10
gt1 tga1
Wills et al. 2013 PLoS Genetics
tb1
1 2 3 4 5
6 7 8 9 10
gt1 tga1
Wills et al. 2013 PLoS Genetics
teosinte maize
Clint Whipple, BYU
tb1
1 2 3 4 5
6 7 8 9 10
gt1 tga1
Wills et al. 2013 PLoS Genetics
tb1
T/T
M/T
M/M
T/T
M/T
M/M
A B
T/T
M/T
M/M
T/T
M/T
M/M
3’ UTR
5’ control region
hard sweep
M T N P H R L
GGTCGA ATG ACT GAT CCA CAT CGA CTG TAG
tga1
gt1
tb1
Multiple
Mutations
Standing
Variation
M T G P H R L
GGTAAA ATG ACT GGT CCA CAT CGA CTG TAG
Hufford et al. 2012 Nat. Gen.
Chia et al. 2012 Nat. Gen
13 teosinte
23 maize
genomes:
Hufford et al. 2012 Nat. Gen.
Chia et al. 2012 Nat. Gen
13 teosinte
23 maize
genomes:
5-10% selected regions intergenic
E
D
Mb
nd targets of selection during improvement and/or domestication. (A) Venn diagram
that occur in genomic regions that have evidence for selective sweeps during maize
oexpression networks for three genes (GRMZM2G068436, GRMZM2G137947, and
pression networks are shown. Although the differentially expressed gene (red node) is
ize. However, some parts of the teosinte network are still conserved in maize. (C) Cross-
vidence for a selective sweep that occurs on chromosome 9. The tick marks along the x
ZM2G448355) that was chosen as the candidate target of selection and is differentially
ExpressionGenealogy
teosinte
maize
• ~500 selected regions
• 11M shared vs 3000 fixed SNPs
• Candidates differentially
expressed, decreased
expression variation
selection on regulatory sequence, standing variation
Hufford et al. 2012 Nat. Gen.
Swanson-Wagner et al. 2012 PNAS
Mexico lowland
9,000 BP
Matsuoka et al. 2002; Piperno 2006
Perry et al. 2006; Piperno et al. 2009
Mexico highland6,000 BP
Mexico lowland
9,000 BP
Matsuoka et al. 2002; Piperno 2006
Perry et al. 2006; Piperno et al. 2009
Mexico highland6,000 BP
S.	America	
lowland
6,000	BP
Mexico lowland
9,000 BP
Matsuoka et al. 2002; Piperno 2006
Perry et al. 2006; Piperno et al. 2009
Mexico highland6,000 BP
S.	America	
lowland
6,000	BP
S.	America	
Highland
4,000	BP
Mexico lowland
9,000 BP
Matsuoka et al. 2002; Piperno 2006
Perry et al. 2006; Piperno et al. 2009
Mexico
photobyMonthonWachirasettakul
Andes
photobyMattHufford
Beissinger et al. Unpublished
SA MEX SA MEX
SA MEX SA MEX SA MEX SA
Ear Height Plant Height
Tassel Br. Number
T
Days to Anthesis
SA MEX SA MEX
SA MEX SA MEX
LowlandHighland
Beissinger et al. Unpublished
Mexico
Lowland
Mexico
Highland
NA
NB
NC
N1 N2
N2P
tD
tE
tF
NA
NB
NC
N1 N2
N2P
tD
tE
tF
tmex
Nmex
N
tD
tE
tF
NC NA
N1 NC
N2 NC
N2P N2
NC NA
N1 NC
N2 NC
N2P N2
N
N
N
N
N
N
tG
Lowland Highland mexicana Mex
Lowla
Model IA Model IB Mod
Figure 2 Demographic models of maize low
land populations. Parameters in bold were
this study. See text for details.
A HWE cut-off of P < 0.005 was used for e
lation due to our under-calling of heterozygotes
included 18,745 silent SNPs for the Mexican p
Models IA and IB, 14,508 for the S. American p
Model I and 11,305 for the Mexican lowland p
the S. American populations in Model II. We ob
results under more or less stringent thresholds fo
(P < 0.05 ⇠ 0.0005; data not shown), though t
SNPs was very small at P < 0.005. Demograph
Mexico
Lowland
Mexico
Highland
NA
NB
NC
N1 N2
N2P
tD
tE
tF
NA
NB
NC
N1 N2
N2P
tD
tE
tF
tmex
Nmex
NA
NB
NC
N1 N2
tD
tE
tF
N3 N4
NC NA
N1 NC
N2 NC
N2P N2
NC NA
N1 NC
N2 NC
N2P N2
NC NA
N1 1NC
N2 1 NC
N3 2N2
N4 2 N2
N4P N4
tG
N4P
Lowland Highland mexicana Mexico
Lowland
SA
Lowland
SA
Highland
Model IA Model IB Model II
Figure 2 Demographic models of maize low- and high-
land populations. Parameters in bold were estimated in
this study. See text for details.
A HWE cut-off of P < 0.005 was used for each subpopu-
lation due to our under-calling of heterozygotes. In total, we
included 18,745 silent SNPs for the Mexican populations in
Models IA and IB, 14,508 for the S. American populations in
Model I and 11,305 for the Mexican lowland population and
the S. American populations in Model II. We obtained similar
results under more or less stringent thresholds for significance
(P < 0.05 ⇠ 0.0005; data not shown), though the number of
SNPs was very small at P < 0.005. Demographic parameters
were inferred with the software a i (Gutenkunst et al. 2009),
likelihoo
Model IB
by incor
highland
”Mexican”
consistent p
The time
occurs at
is assum
the Mex
between
from the
Model I
America
was used
below).
populatio
after spl
ican low
and the
2. As i
assumed
Estim
able from
mates of
lumis (E
Wright e
of the m
Inference of demographic parameters
Model I Model II
Likelihood 5592.80 Likelihood 4654.79
↵ 0.92 ↵ 1.5
0.38 0.76
1 1
ca Model I Model III
Likelihood 3855.28 Likelihood 8044.71
↵ 0.52 ↵ 1.0
A
Lowlands
Highlands
Observation Expectation Res
Mexico
Model IA
Model IB
–1
Table 2 Inference of demographic parameters
Mexico Model I Model II
Likelihood 5592.80 Likelihood 4654.79
↵ 0.92 ↵ 1.5
0.38 0.76
1 1
South America Model I Model III
Likelihood 3855.28 Likelihood 8044.71
↵ 0.52 ↵ 1.0
0.97 1 0.64
88 2 0.95
54
Population structure
A
B
Lowlands
Highlands
Observatio
Mexico
South Ame
Density
10
–4
0
10
–3
10
–2
10
–1
Observatio
lowlands
highlands
density
Mexico
observed	 expected
95 samples
~100K SNPs
Takuno et al. 2015 Genetics
-Logp-valueFstS.America
-Log p-value Fst Mexico
shared SNPs
unique S.America
unique Mexico
Takuno et al. 2015 Genetics
-Logp-valueFstS.America
-Log p-value Fst Mexico
shared SNPs
unique S.America
unique Mexico
Takuno et al. 2015 Genetics
39%
61%
Intergenic
Genic
19%
81%
Standing Variation
New mutation
Pyhäjärvi et al. GBE 2013
Figures
Pyhäjärvi et al. GBE 2013
Pyhäjärvi et al. GBE 2013
environment allele frequency
Beissinger et al. 2016 Nature Plants (pending rev)
nucleotidediversity
distance to nearest substitution (cM)
hard sweeps in genes play minor role in Zea
Beissinger et al. 2016 Nature Plants (pending rev)
nucleotidediversity
distance to nearest substitution (cM)
hard sweeps in genes play minor role in Zea
Beissinger et al. 2016 Nature Plants (pending rev)
nucleotidediversity
distance to nearest substitution (cM)
hard sweeps in genes play minor role in Zea
Wallace et al. 2014 PLoS Genetics
Rodgers-Melnick et al. 2016 PNAS
GWAS candidate SNPs
Wallace et al. 2014 PLoS Genetics
Rodgers-Melnick et al. 2016 PNAS
Variance PartitioningGWAS candidate SNPs
how to adapt: Zea mays
M T G P H R L
GGTAAA ATG ACT GGT CCA CAT CGA CTG TAG
noncoding/regulatory variation
multiple
mutations
“soft” sweeps
standing
variation
Sattah et al. 2011 PLoS Gen.
Williamson et al. 2014 PLoS Gen
Hernandez et al. 2011 ScienceRoss-Ibarra et al. 2009 Genetics
Sattah et al. 2011 PLoS Gen.
Williamson et al. 2014 PLoS Gen
Hernandez et al. 2011 ScienceRoss-Ibarra et al. 2009 Genetics
Sattah et al. 2011 PLoS Gen.
Williamson et al. 2014 PLoS Gen
Hernandez et al. 2011 Science
diversity
distance from substitution
Ross-Ibarra et al. 2009 Genetics
Sattah et al. 2011 PLoS Gen.
Williamson et al. 2014 PLoS Gen
Hernandez et al. 2011 Science
diversity
distance from substitution
20% nonsyn. adaptive 10% nonsyn. adaptive
50% nonsyn. adaptive 40% nonsyn. adaptive
Ross-Ibarra et al. 2009 Genetics
Sattah et al. 2011 PLoS Gen.
Williamson et al. 2014 PLoS Gen
Hernandez et al. 2011 Science
diversity
distance from substitution
Ross-Ibarra et al. 2009 Genetics
µ ∝ 2,500 Mbp µ ∝ 3,100 Mbp
µ ∝ 130 Mbp µ ∝ 220 Mbp
Pyhäjärvi et al. GBE 2013
enrichment
no<———>yes
larger genomes enriched in noncoding
adaptive variants
intergenic
synonymous
nonsynonymous
enrichment
intergenic<———>coding
Hancock et al 2011 Science
Fraser et al. 2013 Gen. Research
Pyhäjärvi et al. GBE 2013
larger genomes enriched in noncoding
adaptive variantsenrichment
intergenic<———>coding
excessadaptiveSNPs
Hancock et al 2011 Science
Fraser et al. 2013 Gen. Research
WHAT IS ATE?
Credit: Robert Martienssen, CSHL
Doebley 2004, Studer et al., 2011
tb1
Hopscotch
Doebley 2004, Studer et al., 2011
tb1
Hopscotch
ZmCCT
CACTA
Yang et al., 2013
Mu
KNOTTED1
kn1
Greene, et al., 1994
http://pmb.berkeley.edu/sites/default/files/users/Knotted1%20mutant.jpgDoebley 2004, Studer et al., 2011
tb1
Hopscotch
ZmCCT
CACTA
Yang et al., 2013
Makarevitch et al. 2015 PLoS Genetics
Makarevitch et al. 2015 PLoS Genetics
vate expression
GRMZM2G071206
tress/control)
2
4
6
8
10
12
-2
0
2
4
6
8
10
12
14
Lines with the
TE insertion
Lines without the
TE insertion
GRMZM2G108149
A
B
Log2(stress/control)
on September 9, 2014http://biorxiv.org/Downloaded from
Zm05382
er 9, 2014
nsertions activate expression
Lines with the
TE insertion
Lines without the
TE insertion
GRMZM2G071206
Log2(stress/control)
-2
0
2
4
6
8
10
12
2
4
6
8
10
12
tress/control)
GRMZM2G400718
C
-2
0
2
4
6
8
10
12
14
Lines with the
TE insertion
Lines without the
TE insertion
GRMZM2G108149
A
B
Log2(stress/control)
http://biorxiv.orgDownloaded from
4 5 6 7 8 9 10
Oh43
B73
Mo17
- - ++ - - + - - + - - + - - + - - + - - +
flip
gyma
ipiki
jeli
joemon
naiba
nihep
odoj
pebi
raider
riiryl
ubel
uwum
Zm00346
Zm02117
Zm03238
Zm05382
Salt
UV
Heat
Cold
*
**
*
*
*
** *
Fedoroff 2012, Wang and Dooner 2006
Homologous	(loop)	34%
No	pairing	20%Nonhomologous	46%
Maguire	1966	Gene=cs
Homologous	(loop)	34%
No	pairing	20%Nonhomologous	46%
Fang et al. Genetics 2012
Pyhäjärvi et al. GBE 2013
Figure S4 LD in chromosome 9 among mexicana populations based on SNPs with minor
allele frequency >0.1.
Inv9d
Inv9e
Fang et al. Genetics 2012
Pyhäjärvi et al. GBE 2013
0.0
0.4
0.8
0 1000 2000
Elevation (m)
InversionFrequency
Inv4n
Figure S4 LD in chromosome 9 among mexicana populations based on SNPs with minor
allele frequency >0.1.
Inv9d
Inv9e
Fang et al. Genetics 2012
Pyhäjärvi et al. GBE 2013
0.0
0.4
0.8
0 1000 2000
Elevation (m)
InversionFrequency
Inv4n
Figure S4 LD in chromosome 9 among mexicana populations based on SNPs with minor
allele frequency >0.1.
Inv9d
Inv9e
Inv1n
Lauter et al. 2004 Genetics
Inv4n
mexicana parviglumis
Figu
freq
tion
perc
by a
ted
twe
5%
Fang et al. Genetics 2012
Hufford et al. PLoS Genetics 2013
culm diameter
macrohairs, anthocyanin
Inv1n
Pyhäjärvi et al. GBE 2013
El Porvenir
Opopeo
Xochimilco
Puruandiro
Tenango del Aire
Ixtlan
Nabogame
Santa Clara
San Pedro
Allopatric
Inv4n
Fst high vs. low elevation maize
Hufford et al. PLoS Gen 2013
4%	of	B73	
~8%	absent
✓⇡
n 1X
i=1
1
i
= S
reference	genome	~70%		
low	copy	sequenceθπ	~	8%	pairwise	diff	
1-S%	pan-genome	in	ref
%readsunmappedreads
Gore	et	al.	2009	Science	
Chia	et	al	2012	Nat	Gen
4%	of	B73	
~8%	absent
✓⇡
n 1X
i=1
1
i
= S
reference	genome	~70%		
low	copy	sequenceθπ	~	8%	pairwise	diff	
1-S%	pan-genome	in	ref
%readsunmappedreads
Gore	et	al.	2009	Science	
Chia	et	al	2012	Nat	Gen
0%#
20%#
40%#
60%#
80%#
100%#
Angle# Length# NLB# SLB# Width#
10kb%RDV% Gene%RDV% HapMap2%genic%
HapMap2%Intergenic% HapMap1%genic% HapMap1%Intergenic%
0#
2#
4#
6#
8#
10#
12#
14#
16#
18#
20#
Angle# Length# NLB# SLB# Width# 0#
20#
25#
30#
35#
#(Hlog10)#
Intergenic# Intronic#SNPs#
UTR# UP/Down#Stream#
Syn#SNP# Splice#Site#
NonSyn#SNP# 10Kb#RDV#
Gene#RDV#
.# B.# C
.#
0%#
20%#
40%#
60%#
80%#
100%#
Angle# Length# NLB# SLB# Width#
10kb%RDV% Gene%RDV%
HapMap2%Intergenic% HapMap1%geni
10#
15#
20#
25#
30#
35#
pHvalue#(Hlog10)#
Intergenic# Intronic#SNPs#
UTR# UP/Down#Stream#
Syn#SNP# Splice#Site#
NonSyn#SNP# 10Kb#RDV#
Gene#RDV#
A.# B
D.#
0%#
20%#
40%#
60%#
80%#
100%#
Angle# Length# NLB# SLB# Width#
10kb%RDV% Gene%RDV% HapMap2%geni
HapMap2%Intergenic% HapMap1%genic% HapMap1%Inte
0#
2#
4#
6#
8#
10#
12#
14#
16#
18#
20#
Angle# Length# NLB#
15#
20#
25#
30#
35#
pHvalue#(Hlog10)#
Intergenic# Intronic#SNPs#
UTR# UP/Down#Stream#
Syn#SNP# Splice#Site#
NonSyn#SNP# 10Kb#RDV#
Gene#RDV#
A.# B.#
D.#
0%#
20%#
40%#
60%#
80%#
100%#
Angle# Length# NLB# SLB# Width#
10kb%RDV% Gene%RDV% HapMap2%genic%
HapMap2%Intergenic% HapMap1%genic% HapMap1%Intergenic%
0#
2#
4#
6#
8#
10#
12#
14#
16#
18#
20#
Angle# Length# NLB# SLB# Width#
Interge
0# 0.5#
5#
10#
15#
20#
25#
30#
35#
pHvalue#(Hlog10)#
Intergenic# Intronic#SNPs#
UTR# UP/Down#Stream#
Syn#SNP# Splice#Site#
NonSyn#SNP# 10Kb#RDV#
Gene#RDV#
A.# B.# C.#
D.#
foldenrichment
Renny-Byfield et al. In Prep
Chr 6 (Mb)
NOR repeat array
Bilinski et al. In Prep
2.50
2.75
3.00
3.25
3.50
3.75
MH ML SAH SAL mexicana parviglumis
1CGenomeSize(Gb)
Altitude
highland
lowland
SAL mexicana parviglumis
Altitude
highland
lowland
Bilinski et al. In Prep
2.50
2.75
3.00
3.25
3.50
3.75
MH ML SAH SAL mexicana parviglumis
1CGenomeSize(Gb)
Altitude
highland
lowland
SAL mexicana parviglumis
Altitude
highland
lowland
2.50
2.75
3.00
3.25
3.50
3.75
MH ML SAH SAL mexicana parviglu
1CGenomeSize(Gb)
2.50
2.75
3.00
3.25
3.50
3.75
MH ML SAH SAL mexicana parviglumis
1CGenomeSize(Gb)
Altitude
highland
lowland
2.50
2.75
3.00
3.25
3.50
3.75
MH ML SAH SA
1CGenomeSize(Gb)
Bilinski et al. In Prep
2.50
2.75
3.00
3.25
3.50
3.75
MH ML SAH SAL mexicana parviglumis
1CGenomeSize(Gb)
Altitude
highland
lowland
SAL mexicana parviglumis
Altitude
highland
lowland
2.50
2.75
3.00
3.25
3.50
3.75
MH ML SAH SAL mexicana parviglu
1CGenomeSize(Gb)
2.50
2.75
3.00
3.25
3.50
3.75
MH ML SAH SAL mexicana parviglumis
1CGenomeSize(Gb)
Altitude
highland
lowland
2.50
2.75
3.00
3.25
3.50
3.75
MH ML SAH SA
1CGenomeSize(Gb)
mixed model for selection on genome size
altitudemean
slope (selection)
kinshipgenome size
error
β1 < 0
11MB decrease per 100 meter gained
Bilinski et al. In Prep
Bilinski et al. In Prep
Bilinski et al. In Prep
Bilinski et al. In Prep
bpofknob
Rayburn et al. 1994 Plant Breeding
Francis et al. 2008. Ann. Bot.
excluded. Indeed, if we ignore the marked dis
of the y-axis caused by their inclusion, then the n
effect is strong for all species regardless of phyl
test the rigour of these hypotheses would requi
plug the gap between Trillium grandiflorum
majority of C-value/cell cycle times analysed he
Separate plots for diploids and polyploids show
nucleotypic effect on CCT in diploids (Fig. 3;
Removing the five diploid outliers (.25 pg) re
slope (b ¼ 0.27) by approximately four-fold
regression continued to be significant (P , 0.
the polyploids, a nucleotypic effect on CCT
detected (Fig. 3; Table 2); however, removing the
ploid outliers rendered the regression non-signifi
0.03x 2 13.5). This confirms previous work in
slope/rate of increase in CCT with increasing
higher in diploids than in autopolyploids (Eva
1972). With the exception of Scilla sibirica, CC
FIG. 3. DNA C-value (pg) and cell cycle time (h) in the roo
istem of a range of diploid and polyploid angiosperms. See
regression analyses.
2. DNA C-value (pg) and cell cycle time (h) in the root apical mer-
m of a range of (A) eudicots and monocots (n ¼ 110), and (B) eudicots
(n ¼ 60). See Table 2 for regression analyses.
LE 2. Regression analyses of all data presented in
s. 2–4 together with the percentage variance accounted
by the regression (R2
), the level of probability (P) for
each regression
late flowering
early flowering
0
10
20
30
100 105 110
DNA
plants
cycle
0
6
smaller genome, faster development?
Bilinski et al. In Prep
2.50
2.75
3.00
3.25
3.50
3.75
MH ML SAH SAL mexicana parviglumis
1CGenomeSize(Gb)
Altitude
highland
lowland
2.50
2.75
3.00
3.25
3.50
3.75
MH ML SAH SAL mexicana parviglumis
1CGenomeSize(Gb)
Altitude
highland
lowland
Bilinski et al. In Prep
2.50
2.75
3.00
3.25
3.50
3.75
MH ML SAH SAL mexicana parviglumis
1CGenomeSize(Gb)
Altitude
highland
lowland
2.50
2.75
3.00
3.25
3.50
3.75
MH ML SAH SAL mexicana parviglumis
1CGenomeSize(Gb)
Altitude
highland
lowland
2.50
2.75
3.00
3.25
3.50
3.75
MH ML SAH SAL mexicana parviglumis
1CGenomeSize(Gb)
Altitude
highland
lowland
Bilinski et al. In Prep
2.50
2.75
3.00
3.25
3.50
3.75
MH ML SAH SAL mexicana parviglumis
1CGenomeSize(Gb)
Altitude
highland
lowland
2.50
2.75
3.00
3.25
3.50
3.75
MH ML SAH SAL mexicana parviglumis
1CGenomeSize(Gb)
Altitude
highland
lowland
2.50
2.75
3.00
3.25
3.50
3.75
MH ML SAH SAL mexicana parviglumis
1CGenomeSize(Gb)
Altitude
highland
lowland
Bilinski et al. In Prep
• Adaptation in maize occurs from standing variation
and targets regulatory variants
• Large genomes may have more targets, more standing
variation, and more regulatory adaptation
• Adaptation in complex plant genomes likely involves
many kinds of variation including transposable
elements, inversions, copy number variation, and even
genome size?
Evolutionary Genetics in a
Complex Genome
Kew C-Value Database
photo by lady_lbrty
Acknowledgments
Maize Diversity Group
Peter Bradbury
Ed Buckler
John Doebley
Theresa Fulton
Sherry Flint-Garcia
Jim Holland
Sharon Mitchell
Qi Sun
Doreen Ware
Collaborators
CSI Davis
Nathan Springer
Lab Alumni
Tim Beissinger (USDA-ARS, Mizzou)
Kate Crosby (Monsanto)
Matt Hufford (Iowa State)
Tanja Pyhäjärvi (Oulu)
Shohei Takuno (Sokendai)
Joost van Heerwaarden (Wageningen)
Evolutionary Genetics of Complex Genome

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Evolutionary Genetics of Complex Genome

  • 1. Evolutionary Genetics of a Complex Plant Genome Jeffrey Ross-Ibarra @jrossibarra • www.rilab.org Dept. Plant Sciences • Center for Population Biology • Genome Center University of California Davis
  • 8. M T G P H R L GGTCGAC ATG ACT GGT CCA CAT CGA CTG TAG
  • 9. M T G P H R L GGTCGAC ATG ACT GGT CCA CAT CGA CTG TAG M T N P H R L GGTCGAC ATG ACT GAT CCA CAT CGA CTG TAG structural change to protein
  • 10. M T G P H R L GGTAAAC ATG ACT GGT CCA CAT CGA CTG TAG GG—-AC ATG ACT GGT CCA CAT CGA CTG TAG regulatory change to expression
  • 11. Lowry & Willis 2010 PLoS Biology
  • 12. Gaut and Ross-Ibarra 2008 Kew C-Value Database Paris Japonica 150GB Genome Genlisia aurea 63MB Genome Michal Rubeš
  • 13. Michal Rubeš 1.5 2.5 3.5 4.5 Angiosperm average 6400 Mb Non-TE DNA TE DNALog(genomesizeinMb) 0 1,500 3,000 4,500 6,000 0 1500 3000 4500 6000 Genomesize(Mb) TE content (Mb) r = 0.99 Arabidopsisthaliana Arabidopsislyrata Brachypodiumdistachyon Papaya Rice Lotusjaponicus Blackcottonwood Grapevine Cabbage Medicagotrunculata Sorghum Soybean Levantcotton Maize Aegilopsspeltoides Barley Thursday, May 6, 2010 Tenaillon et al. 2010 TIP
  • 15. 44.6 Mb 44.7 Mb 44.8 Mb 44.9 Mb Gene LTR Retrotransposon maize - 2300 Mb 50 kb 7.4 Mb 7.5 Mb 7.6 Mb 7.7 Mb 7.8 Mb 7.9 Mb 50 kb Gene LTR Retrotransposon arabidopsis - 130 Mb
  • 16. Zea maysA. thaliana Angiosperm 1C genome size (Mb)
  • 17. MbDNA 1 10 100 1000 10000 Arabidopsis Maize 15.5 3.4 70 50 2,300 135 Genome CDs Intergenic open chromatin Sullivan et al. Cell Reports 2014 Rodgers-Melnick et al. PNAS 2016
  • 18. MbDNA 1 10 100 1000 10000 Arabidopsis Maize 15.5 3.4 70 50 2,300 135 Genome CDs Intergenic open chromatin "Functional" DNA 0% 25% 50% 75% 100% Arabidopsis maize 81%93% 19%7% Intergenic CDs Sullivan et al. Cell Reports 2014 Rodgers-Melnick et al. PNAS 2016
  • 19. Ne individuals, µ beneficial mutation rate per trait bigger genome, larger mutation target, higher µ predict that larger genomes adapt via standing variation, noncoding variants
  • 20. Ne individuals, µ beneficial mutation rate per trait bigger genome, larger mutation target, higher µ predict that larger genomes adapt via standing variation, noncoding variants selection from standing variation when 2Neµ > 1
  • 21. Ne individuals, µ beneficial mutation rate per trait bigger genome, larger mutation target, higher µ predict that larger genomes adapt via standing variation, noncoding variants selection from standing variation when 2Neµ > 1 larger % of µ should be noncoding
  • 23. 1 2 3 4 5 6 7 8 9 10 Briggs et al. 2007 Genetics
  • 24. 1 2 3 4 5 6 7 8 9 10 tb1 Studer et al. 2011 Nature Genetics.; Vann et al. 2015 PeerJ GENETICS ADVANCE ONLINE PUBLICATION 3 nguish maize and teosinte. Both the maize and teosinte s for the distal component repressed luciferase expression luc luc luc luc luc luc Hopscotch mpCaMV M-dist T-prox M-prox 0 0.5 1.0 1.5 2.0 ∆M-dist ∆M-prox ProximalcontrolregionDistal Constructs and corresponding normalized luciferase expression nsient assays were performed in maize leaf protoplast. Each is drawn to scale. The construct backbone consists of the romoter from the cauliflower mosaic virus (mpCaMV, gray box), ORF (luc, white box) and the nopaline synthase terminator ). Portions of the proximal and distal components of the gion (hatched boxes) from maize and teosinte were cloned ction sites upstream of the minimal promoter. “ ” denotes on of either the Tourist or Hopscotch element from the maize Horizontal green bars show the normalized mean with s.e.m. onstruct. relative expressionconstruct
  • 25. 1 2 3 4 5 6 7 8 9 10 tb1 Figure 2 Map of parviglumis Populations and Hopscotch allele frequency. Map showing the frequency of the Hopscotch allele in populations of parviglumis where we sampled more than 6 individuals. Size of circles reflects number of individuals sampled. The Balsas River is shown, as the Balsas River Basin is believed to be the center of domestication of maize. as our independent trait for phenotyping analyses. SAS code used for analysis is available at http://dx.doi.org/10.6084/m9.figshare.1166630. RESULTS Genotyping for the Hopscotch insertion The genotype at the Hopscotch insertion was confirmed with two PCRs for 837 individuals of the 1,100 screened (Table S1 and Table S2). Among the 247 maize landrace accessions genotyped, all but eight were homozygous for the presence of the insertion Within our parviglumis and mexicana samples we found the Hopscotch insertion segregating in 37 (n = 86) and four (n = 17) populations, respectively, and at highest frequency within populations in the states of Jalisco, Colima, and Michoac´an in central-western Mexico (Fig. 2). Using our Hopscotch genotyping, we calculated diVerentiation between populations (FST) and subspecies (FCT) for populations in which we sampled sixteen or more chromosomes. We found that FCT = 0, and levels of FST among populations within each subspecies (0.22) and among all populations (0.23) (Table 1) are similar to genome-wide estimates from previous studies Pyh¨aj¨arvi, HuVord & Ross-Ibarra, 2013. Although we found large variation in Hopscotch allele frequency among our populations, BayEnv analysis did not indicate a correlation between the Hopscotch insertion and environmental variables (all Bayes Factors < 1). Studer et al. 2011 Nature Genetics.; Vann et al. 2015 PeerJ GENETICS ADVANCE ONLINE PUBLICATION 3 nguish maize and teosinte. Both the maize and teosinte s for the distal component repressed luciferase expression luc luc luc luc luc luc Hopscotch mpCaMV M-dist T-prox M-prox 0 0.5 1.0 1.5 2.0 ∆M-dist ∆M-prox ProximalcontrolregionDistal Constructs and corresponding normalized luciferase expression nsient assays were performed in maize leaf protoplast. Each is drawn to scale. The construct backbone consists of the romoter from the cauliflower mosaic virus (mpCaMV, gray box), ORF (luc, white box) and the nopaline synthase terminator ). Portions of the proximal and distal components of the gion (hatched boxes) from maize and teosinte were cloned ction sites upstream of the minimal promoter. “ ” denotes on of either the Tourist or Hopscotch element from the maize Horizontal green bars show the normalized mean with s.e.m. onstruct. relative expressionconstruct
  • 26. Wang et al. 2005 Nature Wang et al 2015 Genetics 1 2 3 4 5 6 7 8 9 10 Figure 1. Phenotypes. a. Maize ear showing the cob (cb) exposed at top. b. Teosinte e internode (in) and glume (gl) labeled. c. Teosinte ear from a plant with a m introgressed into it. d. Close-up of a single teosinte fruitcase. e. Close-up o teosinte plant with a maize allele of tga1 introgressed into it. f. Ear of maiz (Tga1-maize allele) with the cob exposed showing the small white glumes a of maize inbred W22:tga1 which carries the teosinte allele, showing enlarge h. Ear of maize inbred W22 carrying the tga1-ems1 allele, showing enlarged g NIH-PAAuthorManuscriptNIH-PAAuthorManuscriptNIH-P tga1tb1
  • 27. Wang et al. 2005 Nature Wang et al 2015 Genetics 1 2 3 4 5 6 7 8 9 10 Figure 1. Phenotypes. a. Maize ear showing the cob (cb) exposed at top. b. Teosinte e internode (in) and glume (gl) labeled. c. Teosinte ear from a plant with a m introgressed into it. d. Close-up of a single teosinte fruitcase. e. Close-up o teosinte plant with a maize allele of tga1 introgressed into it. f. Ear of maiz (Tga1-maize allele) with the cob exposed showing the small white glumes a of maize inbred W22:tga1 which carries the teosinte allele, showing enlarge h. Ear of maize inbred W22 carrying the tga1-ems1 allele, showing enlarged g NIH-PAAuthorManuscriptNIH-PAAuthorManuscriptNIH-P tga1tb1
  • 28. 1 2 3 4 5 6 7 8 9 10 gt1 tga1 Wills et al. 2013 PLoS Genetics tb1
  • 29. 1 2 3 4 5 6 7 8 9 10 gt1 tga1 Wills et al. 2013 PLoS Genetics teosinte maize Clint Whipple, BYU tb1
  • 30. 1 2 3 4 5 6 7 8 9 10 gt1 tga1 Wills et al. 2013 PLoS Genetics tb1 T/T M/T M/M T/T M/T M/M A B T/T M/T M/M T/T M/T M/M 3’ UTR 5’ control region
  • 31. hard sweep M T N P H R L GGTCGA ATG ACT GAT CCA CAT CGA CTG TAG tga1 gt1 tb1 Multiple Mutations Standing Variation M T G P H R L GGTAAA ATG ACT GGT CCA CAT CGA CTG TAG
  • 32. Hufford et al. 2012 Nat. Gen. Chia et al. 2012 Nat. Gen 13 teosinte 23 maize genomes:
  • 33. Hufford et al. 2012 Nat. Gen. Chia et al. 2012 Nat. Gen 13 teosinte 23 maize genomes: 5-10% selected regions intergenic
  • 34. E D Mb nd targets of selection during improvement and/or domestication. (A) Venn diagram that occur in genomic regions that have evidence for selective sweeps during maize oexpression networks for three genes (GRMZM2G068436, GRMZM2G137947, and pression networks are shown. Although the differentially expressed gene (red node) is ize. However, some parts of the teosinte network are still conserved in maize. (C) Cross- vidence for a selective sweep that occurs on chromosome 9. The tick marks along the x ZM2G448355) that was chosen as the candidate target of selection and is differentially ExpressionGenealogy teosinte maize • ~500 selected regions • 11M shared vs 3000 fixed SNPs • Candidates differentially expressed, decreased expression variation selection on regulatory sequence, standing variation Hufford et al. 2012 Nat. Gen. Swanson-Wagner et al. 2012 PNAS
  • 35. Mexico lowland 9,000 BP Matsuoka et al. 2002; Piperno 2006 Perry et al. 2006; Piperno et al. 2009
  • 36. Mexico highland6,000 BP Mexico lowland 9,000 BP Matsuoka et al. 2002; Piperno 2006 Perry et al. 2006; Piperno et al. 2009
  • 37. Mexico highland6,000 BP S. America lowland 6,000 BP Mexico lowland 9,000 BP Matsuoka et al. 2002; Piperno 2006 Perry et al. 2006; Piperno et al. 2009
  • 38. Mexico highland6,000 BP S. America lowland 6,000 BP S. America Highland 4,000 BP Mexico lowland 9,000 BP Matsuoka et al. 2002; Piperno 2006 Perry et al. 2006; Piperno et al. 2009
  • 40. SA MEX SA MEX SA MEX SA MEX SA MEX SA Ear Height Plant Height Tassel Br. Number T Days to Anthesis SA MEX SA MEX SA MEX SA MEX LowlandHighland Beissinger et al. Unpublished
  • 41. Mexico Lowland Mexico Highland NA NB NC N1 N2 N2P tD tE tF NA NB NC N1 N2 N2P tD tE tF tmex Nmex N tD tE tF NC NA N1 NC N2 NC N2P N2 NC NA N1 NC N2 NC N2P N2 N N N N N N tG Lowland Highland mexicana Mex Lowla Model IA Model IB Mod Figure 2 Demographic models of maize low land populations. Parameters in bold were this study. See text for details. A HWE cut-off of P < 0.005 was used for e lation due to our under-calling of heterozygotes included 18,745 silent SNPs for the Mexican p Models IA and IB, 14,508 for the S. American p Model I and 11,305 for the Mexican lowland p the S. American populations in Model II. We ob results under more or less stringent thresholds fo (P < 0.05 ⇠ 0.0005; data not shown), though t SNPs was very small at P < 0.005. Demograph Mexico Lowland Mexico Highland NA NB NC N1 N2 N2P tD tE tF NA NB NC N1 N2 N2P tD tE tF tmex Nmex NA NB NC N1 N2 tD tE tF N3 N4 NC NA N1 NC N2 NC N2P N2 NC NA N1 NC N2 NC N2P N2 NC NA N1 1NC N2 1 NC N3 2N2 N4 2 N2 N4P N4 tG N4P Lowland Highland mexicana Mexico Lowland SA Lowland SA Highland Model IA Model IB Model II Figure 2 Demographic models of maize low- and high- land populations. Parameters in bold were estimated in this study. See text for details. A HWE cut-off of P < 0.005 was used for each subpopu- lation due to our under-calling of heterozygotes. In total, we included 18,745 silent SNPs for the Mexican populations in Models IA and IB, 14,508 for the S. American populations in Model I and 11,305 for the Mexican lowland population and the S. American populations in Model II. We obtained similar results under more or less stringent thresholds for significance (P < 0.05 ⇠ 0.0005; data not shown), though the number of SNPs was very small at P < 0.005. Demographic parameters were inferred with the software a i (Gutenkunst et al. 2009), likelihoo Model IB by incor highland ”Mexican” consistent p The time occurs at is assum the Mex between from the Model I America was used below). populatio after spl ican low and the 2. As i assumed Estim able from mates of lumis (E Wright e of the m Inference of demographic parameters Model I Model II Likelihood 5592.80 Likelihood 4654.79 ↵ 0.92 ↵ 1.5 0.38 0.76 1 1 ca Model I Model III Likelihood 3855.28 Likelihood 8044.71 ↵ 0.52 ↵ 1.0 A Lowlands Highlands Observation Expectation Res Mexico Model IA Model IB –1 Table 2 Inference of demographic parameters Mexico Model I Model II Likelihood 5592.80 Likelihood 4654.79 ↵ 0.92 ↵ 1.5 0.38 0.76 1 1 South America Model I Model III Likelihood 3855.28 Likelihood 8044.71 ↵ 0.52 ↵ 1.0 0.97 1 0.64 88 2 0.95 54 Population structure A B Lowlands Highlands Observatio Mexico South Ame Density 10 –4 0 10 –3 10 –2 10 –1 Observatio lowlands highlands density Mexico observed expected 95 samples ~100K SNPs Takuno et al. 2015 Genetics
  • 42. -Logp-valueFstS.America -Log p-value Fst Mexico shared SNPs unique S.America unique Mexico Takuno et al. 2015 Genetics
  • 43. -Logp-valueFstS.America -Log p-value Fst Mexico shared SNPs unique S.America unique Mexico Takuno et al. 2015 Genetics 39% 61% Intergenic Genic 19% 81% Standing Variation New mutation
  • 44. Pyhäjärvi et al. GBE 2013 Figures
  • 45. Pyhäjärvi et al. GBE 2013
  • 46. Pyhäjärvi et al. GBE 2013 environment allele frequency
  • 47. Beissinger et al. 2016 Nature Plants (pending rev) nucleotidediversity distance to nearest substitution (cM) hard sweeps in genes play minor role in Zea
  • 48. Beissinger et al. 2016 Nature Plants (pending rev) nucleotidediversity distance to nearest substitution (cM) hard sweeps in genes play minor role in Zea
  • 49. Beissinger et al. 2016 Nature Plants (pending rev) nucleotidediversity distance to nearest substitution (cM) hard sweeps in genes play minor role in Zea
  • 50. Wallace et al. 2014 PLoS Genetics Rodgers-Melnick et al. 2016 PNAS GWAS candidate SNPs
  • 51. Wallace et al. 2014 PLoS Genetics Rodgers-Melnick et al. 2016 PNAS Variance PartitioningGWAS candidate SNPs
  • 52. how to adapt: Zea mays M T G P H R L GGTAAA ATG ACT GGT CCA CAT CGA CTG TAG noncoding/regulatory variation multiple mutations “soft” sweeps standing variation
  • 53. Sattah et al. 2011 PLoS Gen. Williamson et al. 2014 PLoS Gen Hernandez et al. 2011 ScienceRoss-Ibarra et al. 2009 Genetics
  • 54. Sattah et al. 2011 PLoS Gen. Williamson et al. 2014 PLoS Gen Hernandez et al. 2011 ScienceRoss-Ibarra et al. 2009 Genetics
  • 55. Sattah et al. 2011 PLoS Gen. Williamson et al. 2014 PLoS Gen Hernandez et al. 2011 Science diversity distance from substitution Ross-Ibarra et al. 2009 Genetics
  • 56. Sattah et al. 2011 PLoS Gen. Williamson et al. 2014 PLoS Gen Hernandez et al. 2011 Science diversity distance from substitution 20% nonsyn. adaptive 10% nonsyn. adaptive 50% nonsyn. adaptive 40% nonsyn. adaptive Ross-Ibarra et al. 2009 Genetics
  • 57. Sattah et al. 2011 PLoS Gen. Williamson et al. 2014 PLoS Gen Hernandez et al. 2011 Science diversity distance from substitution Ross-Ibarra et al. 2009 Genetics µ ∝ 2,500 Mbp µ ∝ 3,100 Mbp µ ∝ 130 Mbp µ ∝ 220 Mbp
  • 58. Pyhäjärvi et al. GBE 2013 enrichment no<———>yes larger genomes enriched in noncoding adaptive variants intergenic synonymous nonsynonymous enrichment intergenic<———>coding Hancock et al 2011 Science Fraser et al. 2013 Gen. Research
  • 59. Pyhäjärvi et al. GBE 2013 larger genomes enriched in noncoding adaptive variantsenrichment intergenic<———>coding excessadaptiveSNPs Hancock et al 2011 Science Fraser et al. 2013 Gen. Research
  • 60. WHAT IS ATE? Credit: Robert Martienssen, CSHL
  • 61. Doebley 2004, Studer et al., 2011 tb1 Hopscotch
  • 62. Doebley 2004, Studer et al., 2011 tb1 Hopscotch ZmCCT CACTA Yang et al., 2013
  • 63. Mu KNOTTED1 kn1 Greene, et al., 1994 http://pmb.berkeley.edu/sites/default/files/users/Knotted1%20mutant.jpgDoebley 2004, Studer et al., 2011 tb1 Hopscotch ZmCCT CACTA Yang et al., 2013
  • 64. Makarevitch et al. 2015 PLoS Genetics
  • 65. Makarevitch et al. 2015 PLoS Genetics vate expression GRMZM2G071206 tress/control) 2 4 6 8 10 12 -2 0 2 4 6 8 10 12 14 Lines with the TE insertion Lines without the TE insertion GRMZM2G108149 A B Log2(stress/control) on September 9, 2014http://biorxiv.org/Downloaded from Zm05382 er 9, 2014 nsertions activate expression Lines with the TE insertion Lines without the TE insertion GRMZM2G071206 Log2(stress/control) -2 0 2 4 6 8 10 12 2 4 6 8 10 12 tress/control) GRMZM2G400718 C -2 0 2 4 6 8 10 12 14 Lines with the TE insertion Lines without the TE insertion GRMZM2G108149 A B Log2(stress/control) http://biorxiv.orgDownloaded from 4 5 6 7 8 9 10 Oh43 B73 Mo17 - - ++ - - + - - + - - + - - + - - + - - + flip gyma ipiki jeli joemon naiba nihep odoj pebi raider riiryl ubel uwum Zm00346 Zm02117 Zm03238 Zm05382 Salt UV Heat Cold * ** * * * ** *
  • 66. Fedoroff 2012, Wang and Dooner 2006
  • 69. Fang et al. Genetics 2012 Pyhäjärvi et al. GBE 2013 Figure S4 LD in chromosome 9 among mexicana populations based on SNPs with minor allele frequency >0.1. Inv9d Inv9e
  • 70. Fang et al. Genetics 2012 Pyhäjärvi et al. GBE 2013 0.0 0.4 0.8 0 1000 2000 Elevation (m) InversionFrequency Inv4n Figure S4 LD in chromosome 9 among mexicana populations based on SNPs with minor allele frequency >0.1. Inv9d Inv9e
  • 71. Fang et al. Genetics 2012 Pyhäjärvi et al. GBE 2013 0.0 0.4 0.8 0 1000 2000 Elevation (m) InversionFrequency Inv4n Figure S4 LD in chromosome 9 among mexicana populations based on SNPs with minor allele frequency >0.1. Inv9d Inv9e Inv1n
  • 72. Lauter et al. 2004 Genetics Inv4n mexicana parviglumis Figu freq tion perc by a ted twe 5% Fang et al. Genetics 2012 Hufford et al. PLoS Genetics 2013 culm diameter macrohairs, anthocyanin Inv1n
  • 73. Pyhäjärvi et al. GBE 2013
  • 74. El Porvenir Opopeo Xochimilco Puruandiro Tenango del Aire Ixtlan Nabogame Santa Clara San Pedro Allopatric Inv4n Fst high vs. low elevation maize Hufford et al. PLoS Gen 2013
  • 76. 4% of B73 ~8% absent ✓⇡ n 1X i=1 1 i = S reference genome ~70% low copy sequenceθπ ~ 8% pairwise diff 1-S% pan-genome in ref %readsunmappedreads Gore et al. 2009 Science Chia et al 2012 Nat Gen 0%# 20%# 40%# 60%# 80%# 100%# Angle# Length# NLB# SLB# Width# 10kb%RDV% Gene%RDV% HapMap2%genic% HapMap2%Intergenic% HapMap1%genic% HapMap1%Intergenic% 0# 2# 4# 6# 8# 10# 12# 14# 16# 18# 20# Angle# Length# NLB# SLB# Width# 0# 20# 25# 30# 35# #(Hlog10)# Intergenic# Intronic#SNPs# UTR# UP/Down#Stream# Syn#SNP# Splice#Site# NonSyn#SNP# 10Kb#RDV# Gene#RDV# .# B.# C .# 0%# 20%# 40%# 60%# 80%# 100%# Angle# Length# NLB# SLB# Width# 10kb%RDV% Gene%RDV% HapMap2%Intergenic% HapMap1%geni 10# 15# 20# 25# 30# 35# pHvalue#(Hlog10)# Intergenic# Intronic#SNPs# UTR# UP/Down#Stream# Syn#SNP# Splice#Site# NonSyn#SNP# 10Kb#RDV# Gene#RDV# A.# B D.# 0%# 20%# 40%# 60%# 80%# 100%# Angle# Length# NLB# SLB# Width# 10kb%RDV% Gene%RDV% HapMap2%geni HapMap2%Intergenic% HapMap1%genic% HapMap1%Inte 0# 2# 4# 6# 8# 10# 12# 14# 16# 18# 20# Angle# Length# NLB# 15# 20# 25# 30# 35# pHvalue#(Hlog10)# Intergenic# Intronic#SNPs# UTR# UP/Down#Stream# Syn#SNP# Splice#Site# NonSyn#SNP# 10Kb#RDV# Gene#RDV# A.# B.# D.# 0%# 20%# 40%# 60%# 80%# 100%# Angle# Length# NLB# SLB# Width# 10kb%RDV% Gene%RDV% HapMap2%genic% HapMap2%Intergenic% HapMap1%genic% HapMap1%Intergenic% 0# 2# 4# 6# 8# 10# 12# 14# 16# 18# 20# Angle# Length# NLB# SLB# Width# Interge 0# 0.5# 5# 10# 15# 20# 25# 30# 35# pHvalue#(Hlog10)# Intergenic# Intronic#SNPs# UTR# UP/Down#Stream# Syn#SNP# Splice#Site# NonSyn#SNP# 10Kb#RDV# Gene#RDV# A.# B.# C.# D.# foldenrichment
  • 77. Renny-Byfield et al. In Prep Chr 6 (Mb) NOR repeat array
  • 78. Bilinski et al. In Prep 2.50 2.75 3.00 3.25 3.50 3.75 MH ML SAH SAL mexicana parviglumis 1CGenomeSize(Gb) Altitude highland lowland SAL mexicana parviglumis Altitude highland lowland
  • 79. Bilinski et al. In Prep 2.50 2.75 3.00 3.25 3.50 3.75 MH ML SAH SAL mexicana parviglumis 1CGenomeSize(Gb) Altitude highland lowland SAL mexicana parviglumis Altitude highland lowland 2.50 2.75 3.00 3.25 3.50 3.75 MH ML SAH SAL mexicana parviglu 1CGenomeSize(Gb) 2.50 2.75 3.00 3.25 3.50 3.75 MH ML SAH SAL mexicana parviglumis 1CGenomeSize(Gb) Altitude highland lowland 2.50 2.75 3.00 3.25 3.50 3.75 MH ML SAH SA 1CGenomeSize(Gb)
  • 80. Bilinski et al. In Prep 2.50 2.75 3.00 3.25 3.50 3.75 MH ML SAH SAL mexicana parviglumis 1CGenomeSize(Gb) Altitude highland lowland SAL mexicana parviglumis Altitude highland lowland 2.50 2.75 3.00 3.25 3.50 3.75 MH ML SAH SAL mexicana parviglu 1CGenomeSize(Gb) 2.50 2.75 3.00 3.25 3.50 3.75 MH ML SAH SAL mexicana parviglumis 1CGenomeSize(Gb) Altitude highland lowland 2.50 2.75 3.00 3.25 3.50 3.75 MH ML SAH SA 1CGenomeSize(Gb)
  • 81. mixed model for selection on genome size altitudemean slope (selection) kinshipgenome size error β1 < 0 11MB decrease per 100 meter gained Bilinski et al. In Prep
  • 82. Bilinski et al. In Prep
  • 83. Bilinski et al. In Prep
  • 84. Bilinski et al. In Prep bpofknob
  • 85. Rayburn et al. 1994 Plant Breeding Francis et al. 2008. Ann. Bot. excluded. Indeed, if we ignore the marked dis of the y-axis caused by their inclusion, then the n effect is strong for all species regardless of phyl test the rigour of these hypotheses would requi plug the gap between Trillium grandiflorum majority of C-value/cell cycle times analysed he Separate plots for diploids and polyploids show nucleotypic effect on CCT in diploids (Fig. 3; Removing the five diploid outliers (.25 pg) re slope (b ¼ 0.27) by approximately four-fold regression continued to be significant (P , 0. the polyploids, a nucleotypic effect on CCT detected (Fig. 3; Table 2); however, removing the ploid outliers rendered the regression non-signifi 0.03x 2 13.5). This confirms previous work in slope/rate of increase in CCT with increasing higher in diploids than in autopolyploids (Eva 1972). With the exception of Scilla sibirica, CC FIG. 3. DNA C-value (pg) and cell cycle time (h) in the roo istem of a range of diploid and polyploid angiosperms. See regression analyses. 2. DNA C-value (pg) and cell cycle time (h) in the root apical mer- m of a range of (A) eudicots and monocots (n ¼ 110), and (B) eudicots (n ¼ 60). See Table 2 for regression analyses. LE 2. Regression analyses of all data presented in s. 2–4 together with the percentage variance accounted by the regression (R2 ), the level of probability (P) for each regression late flowering early flowering 0 10 20 30 100 105 110 DNA plants cycle 0 6 smaller genome, faster development?
  • 86. Bilinski et al. In Prep
  • 87. 2.50 2.75 3.00 3.25 3.50 3.75 MH ML SAH SAL mexicana parviglumis 1CGenomeSize(Gb) Altitude highland lowland 2.50 2.75 3.00 3.25 3.50 3.75 MH ML SAH SAL mexicana parviglumis 1CGenomeSize(Gb) Altitude highland lowland Bilinski et al. In Prep
  • 88. 2.50 2.75 3.00 3.25 3.50 3.75 MH ML SAH SAL mexicana parviglumis 1CGenomeSize(Gb) Altitude highland lowland 2.50 2.75 3.00 3.25 3.50 3.75 MH ML SAH SAL mexicana parviglumis 1CGenomeSize(Gb) Altitude highland lowland 2.50 2.75 3.00 3.25 3.50 3.75 MH ML SAH SAL mexicana parviglumis 1CGenomeSize(Gb) Altitude highland lowland Bilinski et al. In Prep
  • 89. 2.50 2.75 3.00 3.25 3.50 3.75 MH ML SAH SAL mexicana parviglumis 1CGenomeSize(Gb) Altitude highland lowland 2.50 2.75 3.00 3.25 3.50 3.75 MH ML SAH SAL mexicana parviglumis 1CGenomeSize(Gb) Altitude highland lowland 2.50 2.75 3.00 3.25 3.50 3.75 MH ML SAH SAL mexicana parviglumis 1CGenomeSize(Gb) Altitude highland lowland Bilinski et al. In Prep
  • 90. • Adaptation in maize occurs from standing variation and targets regulatory variants • Large genomes may have more targets, more standing variation, and more regulatory adaptation • Adaptation in complex plant genomes likely involves many kinds of variation including transposable elements, inversions, copy number variation, and even genome size? Evolutionary Genetics in a Complex Genome Kew C-Value Database
  • 91. photo by lady_lbrty Acknowledgments Maize Diversity Group Peter Bradbury Ed Buckler John Doebley Theresa Fulton Sherry Flint-Garcia Jim Holland Sharon Mitchell Qi Sun Doreen Ware Collaborators CSI Davis Nathan Springer Lab Alumni Tim Beissinger (USDA-ARS, Mizzou) Kate Crosby (Monsanto) Matt Hufford (Iowa State) Tanja Pyhäjärvi (Oulu) Shohei Takuno (Sokendai) Joost van Heerwaarden (Wageningen)