Shelby Ellison, PhD
Dec. 14th, 2015
CIAT seminar

• Introduction to carrots and their domestication history
• Traits we are interested in mapping
• Carotenoids
• Root System Architecture (RSA)
• Part I - Utilizing Genotyping-by-Sequencing (GBS) and
RNA-Seq to identify carotenoid traits of interest
• Part II – Utilizing 2D imaging to identify RSA traits
• Ongoing work and future directions

• Carrots are the 7th most economically
important vegetable crop in the United States
• The majority of carrot consumption is fresh market
• In 2014, on average, one person consumed 8.5lbs
(~4kg) of carrots
• Total production was valued at almost 700 million
US dollars (2.3 trillion COP) in 2013, up from 550
million in 2004
• California produces 85% of all carrots grown in the
U.S.NASS, 2014

• Historical
• Pre-900s purple and yellow carrot varieties
in Afghanistan and surrounding vicinity
• 1100 AD domesticated carrots moved into
SW Europe
• European cultivated carrots found in
Americas soon after Columbus’ first visit
• 1600s orange colored carrots frequently
described
• Molecular
• Clear separation between wild and
domesticated; Eastern and Western
• Wild carrots from Central Asia are the
closest genetic relatives to domesticated
carrots
• Domesticated carrot maintains a high level Iorizzo et al., 2013

Wild carrot has a heavily
branched, small, white
taproot
Domestication

Wild carrot has a heavily
branched, small, white
taproot
Accumulation of lutein and β-carotene
Domestication

Wild carrot has a heavily
branched, small, white
taproot
Accumulation of lutein and β-carotene
Reduction of lateral branching and
increased tap root mass/depth
Domestication

Part I

• Play an essential role in plant life…
• Light collection
• Photoprotection
• Biosynthesis of abscisic acid
• Production of strigolactones
• …and animal life
• Provitamin A
• Anti-cancer effects
• Healthy immune system
• Reduced heart disease
• Can also be used as food colorants, for cosmetics, or in pharmaceuticals

• Carrots are one of the highest naturally
occurring sources of β-carotene, an
essential vitamin A precursor
• Carrots can also be red and yellow which
contain lycopene and lutein, respectively
• Carrots have relatively few genomic
resources and the carrot community could
benefit greatly with better tools to improve
key agronomic traits

• Transcriptional regulations of genes
controlling carotenoid biosynthesis
and carotenoid degradation
Maize – PSY, ZDS, LCYE, CRTRB, ZEP
K Chandler et al. (2012) Crop Sci

• Transcriptional regulations of genes
controlling carotenoid biosynthesis
and carotenoid degradation
Maize – PSY, ZDS, LCYE, CRTRB, ZEP
• Regulation of storage structures
(chromoplasts) that act as
carotenoid sinks
Cauliflower - Or
Lu S et al. (2006) Plant
Cell
K Chandler et al. (2012) Crop Sci

• No studies to date, in carrot, have
found a direct link between a
carotenoid biosynthetic gene with
increased lycopene, lutein or β-
carotene accumulation
• Some of these mechanisms require
looking outside of the pathway to
identify potential carotenoid
accumulation candidate genes

• No studies to date, in carrot, have
found a direct link between a
carotenoid biosynthetic gene with
increased lycopene, lutein or β-
carotene accumulation
• Some of these mechanisms require
looking outside of the pathway to
identify potential carotenoid
accumulation candidate genes
Need a genome-wide approach!

DNA from a
segregating
population
GBS Run the Tassel
GBS Pipeline
SNPs
Genomic
regions of
interest
GLM with
phenotypic data

DNA from a
segregating
population
RNA from 3 white, 3
yellow and 3 orange
genotypes
GBS
RNA-
Seq
Run the Tassel
GBS Pipeline
SNPs
Identify
differentially
expressed
genes
Cross reference
and identify
candidates
Genomic
regions of
interest
GLM with
phenotypic data
Run the
Tophat/Cufflinks
Pipeline

• 74146 (Wild x Orange)
• 240 F4 individuals
• Segregating for β-
carotene accumulation
• 97837 (White Belgian x
Yellow)
• 270 F2 individuals
• Segregating for lutein
accumulation

Visual - Binary
HPLC – Carotenoid Concentration

• 23,650 SNPs
• 5% missing data for marker, 10%
missing data for genotype
Phenotypic class Lutein (μg/g)
1) White (3) 6.90 ± 4.10*
2) Yellow (1) 33.78 ± 13.86
*Values are mean ± standard deviation.

• 23,650 SNPs
• 5% missing data for marker, 10%
missing data for genotype
• Region of interest on Chr 5 =
198Kb
Phenotypic class Lutein (μg/g)
1) White (3) 6.90 ± 4.10*
2) Yellow (1) 33.78 ± 13.86
*Values are mean ± standard deviation.
0
2
4
6
8
10
12
-log(P-value)
Genome location
Lutein Accumulation Chr1
Chr2
Chr3
Chr4
Chr5
Chr6
Chr7
Chr8
Chr9

• Only one differentially expressed gene in region of interest
• Gene contains 212bp insertion in 2nd exon
• Homologous to Arabidopsis PEL gene – where overexpression
leads to Pseudo-Etiolation in Light

• 31,180 SNPs
• 5% missing data for marker, 10%
missing data for genotype
Phenotypic class β-carotene (μg/g)
1) Yellow (3) 0.44 ± 0.49*
2) Orange (1) 99.75 ± 62.05
*Values are mean ± standard deviation.

0
2
4
6
8
10
12
14
16
18
20
-log(P-value)
Genome location
β-Carotene Accumulation Chr1
Chr2
Chr3
Chr4
Chr5
Chr6
Chr7
Chr8
Chr9
• 31,180 SNPs
• 5% missing data for marker, 10%
missing data for genotype
• Region of interest on Chr 7 =
1Mb
Phenotypic class β-carotene (μg/g)
1) Yellow (3) 0.44 ± 0.49*
2) Orange (1) 99.75 ± 62.05
*Values are mean ± standard deviation.

DCARv2_Chr7:33261159-33271538 replication protein A1
DCARv2_Chr7:33272106-33274379 pseudogene, similar to putative helicase
DCARv2_Chr7:33294672-33296044 Chalcone synthase
DCARv2_Chr7:33414357-33416815 Polygalacturonase -1
DCARv2_Chr7:33630387-33633403 Plant protein of unknown function (DUF869)
60 Genes in
ROI
Five DEGs
One ROI gene
in
MEP/Caroteno
id pathway
Phenotype 33.0 33.2 33.31 33.36 33.41 33.47 33.63 33.80 33.87 33.94 34.30
Or S Y G T C C T T T . T
Or G C G T C C T T T A K
Or G C G T C C T Y W R K
Y S Y R Y Y Y Y Y W R T
Y S Y R Y Y Y Y Y W R K
Y C T A C T T C C . G T
Y S Y R Y Y Y Y Y W R K
Y S Y R Y Y Y Y Y W R K
Y S Y R Y Y Y Y T T A T
Y S Y R Y Y Y Y C A G T
Y S Y R Y Y Y Y Y W R T
Y S Y R Y Y Y Y Y W R K
1-Deoxy-d-xylulose 5-phosphate reductoisomerase (DXR) catalyzes the first committed
step of the 2-C-methyl-d-erythritol 4-phosphate (MEP) pathway for isoprenoid
biosynthesis

chlorophylls
tocopherols
gibberellins
phylloquinones
plastoquinones
β-ionone
Stringolactone
isopentenyl pyrophosphate
geranylgeranyl pyrophosphate
phytoene
ζ-carotene
α-carotene
zeaxanthin
antheraxanthin
neoxanthin
abscisic acid
xanthoxin
Carotenes
Xanthophylls
3X
PSY*(3)
PDS, Z-ISO
ZDS(2), CRTISO
PTOX
LCYBLCYE*, LCYB
CHXB*(2)
CYP97A3*
CYP97A3*
CYP97B3
CHXB*(2)
CHXE
ZEPVDE*
NSY*(2)NCED*(9)
Cleavable
by CCD*(6)
violaxanthin
VDE* ZEP
lycopene
β-carotene
lutein
pyruvate + glyceraldehyde 3-phosphate
1-deoxy-D-xylulose-5-phosphate
2-C-methyl-D-erythritol 4-phosphate
4-diphosphocytidyl-2-C-methyl-D-erythritol
4-diphosphocytidyl-2-C-methly-D-erythritol 2-phosphate
2-C-methyl-D-erythritol 2,4-cyclodiphosphate
1-hydroxy-2-methyl-s-(E)-butenyl 4-diphosphate
MEP
DXS*(4)
DXR(1)
MCT(2)
CMK
MDS
HDS(2)
HDR*(2)
GGPS(6)
NCED*(9)
PREA, GGPR, KSB
sesquiterpenes
sterols
triterpenes
polyterpenesIDI, GPS, FPS
monoterpenoids
IPPI, GPPS, TPS
Or : Y Or : W Y : W
DXS 0.24 1.71* 1.47*
HDR 0.79 1.34* 0.55
PSY1 0.40 3.33* 2.93*
PSY2 0.70 2.85* 2.14*
LCYE 0.49 4.30* 3.81*
CYP97A3 -5.00* -5.00* 0.20
CHXB 2.33* 2.61* 0.28
VDE 0.42 1.83* 1.41*
NSY1 0.86 1.70* 0.84
NCED4 -1.46 -2.15* -0.69
CCD7 -2.35* -3.48 -1.13
CCD8 -2.72* -4.14* -1.42*
-LOG2(fold_change)
-5 -4 -3 -2 -1 0 1 2 3 4 5

• GWAS in ~300 PIs to further fine-map and analyze
linkage disequilibrium around domestication loci
• Verification of differentially expressed genes with qPCR
• Use the CRISPR/Cas9 system to knockout candidate
genes
• Utilize SNPs within candidate genes to create robust co-
dominant markers to be used to evaluate the carrot PI
collection and breeding populations for β-carotene and
lutein accumulation
• Increase breeding efficiency and genebank characterization

Part II

• Wild carrots have a thin taproot that is
highly branched
• These traits are highly undesirable in current
cultivars and heavily selected against in wide-
crosses
• There are many different carrot cultivar
shapes that are important in different
regions of the world
• Understanding RSA can improve
water- and nutrient-use efficiency
• Need an effective way to phenotype
• 2D imaging!

Create, image and genotype F2
mapping population
Adapt existing 2D software, RootNav
and SmartRoot, for carrot
Analyze correlations between RSA
traits and hand-measured traits
Identify genomic regions or genes
associated with economically important
root architecture traits

• Create new F2 mapping
population
• B493 (orange inbred) x QAL (wild from
Uzbekistan)
• n = 262
• Wash, label, sample for leaf
tissue (DNA), scan, sample for
root tissue (HPLC)
• Images as saved as JPEGs and
ready to be imported in 2D
image analysis software
Epson Expression 10000XL
~31cm
600 dpi
~44cm

Need to convert to real value (dpi to cm)

Length, number, area, convex hull

length
latlength
nlats
Lengthm
Surface
Surfacem
LatSurface
Volume
LatVolume
LatDiameter
TotalLength
TotalLengthm
AverageLengthAllRoots
AverageLengthPrimaryRoots
PrimaryLengthm
AverageLengthLateralRoots
LateralRootCount
ConvexHull
MaximumWidth
MaximumDepth
TotLatHM
AveLatHM
LengthHM
MaxWidthHM
length
latlength
nlats 0.72
Lengthm 0.97
Surface 0.72 0.84
Surfacem 0.81 0.84 1.00
LatSurface 0.98
Volume 0.74 0.97 0.98
LatVolume 0.93 0.96
LatDiameter 0.72 0.97
TotalLength 0.91 0.77 0.90 0.88 0.77
TotalLengthm 0.92 0.79 0.91 0.91 0.81 1.00
AverageLengthAllRoots
AverageLengthPrimaryRoots 0.93 0.77 0.86
PrimaryLengthm 0.93 0.97 0.86 0.86 0.76 1.00
AverageLengthLateralRoots 0.76 0.69 0.74 0.71 0.76 0.78
LateralRootCount 0.70 0.87 0.88 0.82 0.86 0.71
ConvexHull 0.79 0.78 0.76 0.74 0.75 0.89 0.90 0.75 0.79
MaximumWidth 0.75 0.81 0.72 0.72 0.80 0.82 0.85 0.87 0.85 0.86
MaximumDepth 0.92 0.95 0.77 0.85 0.98 0.98
TotLatHM 0.87 0.86 0.73 0.72 0.85 0.73 0.76
AveLatHM 0.89 0.88 0.71 0.72 0.86 0.72 0.76 0.97
LengthHM 0.91 0.93 0.80 0.87 0.95 0.94 0.95
MaxWidthHM 0.82 0.82 0.87
RootNav
Hand
Measured
SmartRoot

length
latlength
nlats
Lengthm
Surface
Surfacem
LatSurface
Volume
LatVolume
LatDiameter
TotalLength
TotalLengthm
AverageLengthAllRoots
AverageLengthPrimaryRoots
PrimaryLengthm
AverageLengthLateralRoots
LateralRootCount
ConvexHull
MaximumWidth
MaximumDepth
TotLatHM
AveLatHM
LengthHM
MaxWidthHM
length
latlength
nlats 0.72
Lengthm 0.97
Surface 0.72 0.84
Surfacem 0.81 0.84 1.00
LatSurface 0.98
Volume 0.74 0.97 0.98
LatVolume 0.93 0.96
LatDiameter 0.72 0.97
TotalLength 0.91 0.77 0.90 0.88 0.77
TotalLengthm 0.92 0.79 0.91 0.91 0.81 1.00
AverageLengthAllRoots
AverageLengthPrimaryRoots 0.93 0.77 0.86
PrimaryLengthm 0.93 0.97 0.86 0.86 0.76 1.00
AverageLengthLateralRoots 0.76 0.69 0.74 0.71 0.76 0.78
LateralRootCount 0.70 0.87 0.88 0.82 0.86 0.71
ConvexHull 0.79 0.78 0.76 0.74 0.75 0.89 0.90 0.75 0.79
MaximumWidth 0.75 0.81 0.72 0.72 0.80 0.82 0.85 0.87 0.85 0.86
MaximumDepth 0.92 0.95 0.77 0.85 0.98 0.98
TotLatHM 0.87 0.86 0.73 0.72 0.85 0.73 0.76
AveLatHM 0.89 0.88 0.71 0.72 0.86 0.72 0.76 0.97
LengthHM 0.91 0.93 0.80 0.87 0.95 0.94 0.95
MaxWidthHM 0.82 0.82 0.87
RootNav
Hand
Measured
SmartRoot
• Significant correlations (p<0.0001, r2 >
0.7) found between both programs and
with hand measurements
• Interesting correlations between total
width and convex hull with total number
of lateral roots

• Establish correlations between root traits that can be
integrated into future phenotyping work
• Identify genomic regions or genes associated with
economically important root architecture traits
• Develop molecular markers for desirable root traits to utilize
in the USDA carrot breeding program

• People
• Dr. Philipp Simon
• Dr. Douglas Senalik
• Dr. Massimo Iorizzo
• Dr. Megan Bowman
• Rob Kane
• Stephanie Miller
• Dr. Malcolm Bennett
• Dr. Jonathan Atkinson
• Dr. Michael Pound
• Dr. Guillaume Lobet
• Brianna Fochs
• Funding
• National Science Foundation award
1202666
• European Research Council-NSF
Initiative
• Carrot Genome Sequencing Project
• California Fresh Carrot Advisory
Board