1. 1
TILLING by Sequencing in Mung bean
( (Vigna radiata (L.) R. Wilczek) for altered Plant
Architecture.
Anusheela Varadaraju, Ramadoss Bharathi Raja, Venkatesan Thiruvengadam,
Kulandaivelu Ganesamurthy, Sundaram Ganesh Ram.
Presented by
Dr. Anusheela Varadaraju,
Research Associate, TNAU, Coimbatore.
International Conference & Expo on Agriculture &
Veterinary Sciences: Research and Technology
2nd green revolution call for sustainable agriculture
2. 2
Pulses Production, Productivity and its Demand
Area
(in ‘000 ha)
Production
(in ‘000 tonnes)
Productivity
(in kg/ ha)
3827.6 1592.9 416
Source: Ministry of Agriculture and Farmers Welfare, Govt. of India.
As
on
21.10.2017
http://livechennai.com/Rice_dal_price_chennai.asp
Area, Production and Productivity of total pulses in India (2015-16)
3. 3
Importance of Mung bean
Mung beans are a high source of nutrients including: manganese, potassium,
magnesium, folate, copper, zinc and various B vitamins.
• Reduces the risk of heart
disorders
• High protein source
• Reduces blood pressure
• Prevents cancer development
• Type 2 diabetes
• Increases immunity
• Weight loss
• Detox
• Healthy eye sight
• Prevents constipation
• Anti-ageing qualities
• Prevents acne
• Exfoliates skin
• Strengthens hair and nail
https://www.morphemeremedies.com
4. Introduction
More intensive interventions is required
CONSTRIANTS
1 . Inefficient plant type and low yielding potential
2. Poor productivity which does not support intensive
labour utilization
3. Non synchronous maturity and pod shattering
4
5. Scientific premises of my study
Available Plant type in mung bean
Determinant type
Indeterminant type
Why not suited to MH and low productivity?
1.Early flowering
2.Less number of branches
1.Continous flowering
2.Pods present throughout the plant
5
6. Targeted Plant type suite d to MH and to increase productivity
1.Late flowering
2.Profuse branching
3.Top pod bearing
4.Moderate height
Amenable for MH and increase productivity
Role of genes involved in controlling
flowering and branching architecture and
suitable methods to manipulate these genes
How it can be
achieve?
6
7. Role of candidate genes
S.No Gene name Function
Consequence
of disruption
1 GIGANTEA(GI) Regulating the expression of flowering
time genes during the promotion of
flowering by photoperiod
Late flowering
2 RAMOSUS(RMS) Inhibit branching habit Increased
branching at
basal vegetative
nodes
3 CONSTANS(CO) It is a central regulator of photoperiod
pathway, triggering the production of
the mobile florigen hormone FT
(FLOWERING LOCUS T) that induces
flower differentiation
Delayed
flowering
4 LEAFY(LFY) It promotes the transition from
inflorescence to floral meristem
Delays floral
primordial
initiation
5 TERMINAL
FLOWERING
(TFL)
It maintains the indeterminate growth
of the SAM by inhibiting the
expression of the floral meristem
identity genes LFY and AP1
Promotes
terminal
flowering
7
8. Supported evidence Method Crops Reported by
Late-flowering has been
produced by the
expression of an
antisense GIGANTEA
(GI) gene fragment
transgenic radish Curtis et al.
2002
Mutation in the
GIGANTEA gene delay
flowering
transgenic Arabidopsis Flowler et al.,
1999
GIGANTEA (GI)
specifically
activate FT expression in
leaves under long day
lengths
transgenic Soybean Turck et
al.,2008
GI delays flowering
8
9. Co inducing long day plant
Supported evidence Method Crops Reported by
CO–FT module is conserved
in all known plants.
CO promotes the
expression of FT under
inducing long days.
Transgenic Arabidopsis
thaliana
Lopez et al.,
2001
LFY promotes Flowering
Supported evidence Method Crops Reported by
The LEAFY gene is an
important element of the
transition from the
vegetative to the
reproductive phase, as
LEAFY
Transgenic Arabidopsis
thaliana
Blázquez et al.,
1997
9
10. Supported evidence Method Crops Reported by
Rmsl is one of the series of
five ramosus loci in pea in
which recessive mutant
alleles confer increased
branching at basal and aerial
vegetative nodes
Transgenic Pea Foo et al., 2005;
Johnson et al.,
2006
Demonstrated the inability of
exogenous auxin applications
to rescue the increased
branching phenotypes of the
rms mutants
Grafting studies pea Beveridge et al.,
2000
Investigate the expression of
the RMS1 gene
RT–PCR
classical apical
dominance test
involving decapitation
and replacement of the
apex by exogenous
auxin
pea Sorefan et al.,
2003
RMS Increases branching
10
11. Supported evidence Method Crops Reported by
Mutant plants have a
determinant meristem.
Transgenic Arabidopsis Shannon and
Meeks-Wagner
1991
Dt 1 is an ortholog of
Arabidopsis Terminal Flower
(TFl 1) gene
Transgenic Soybean Jun abe et al.,
2010
TFL1 belongs to the CETS
(CENTRORADIALIS/TERMINAL
FLOWER 1/SELF-PRUNING)
family of genes that encode
PEBPs
(phosphatidylethanolamine
binding proteins)
Transgenic Arabidopsis Pnueli et al.,
2001
TFL 1 Terminal bearing
11
13. Need for TILLING
Plant heterozygous for a mutation can be detected
Both mis-sense and non-sense mutations can be recovered
No transgenic manipulation required
Cost effective than genetic engineering
No associated biosafety issues
Bypass sophisticated tissue culture barriers
13
14. Optimal density of induced mutations by carefully adjusting
mutagenesis conditions
Generation of M1 Population
Generation of M2Population and banking their seeds
Isolation of genomic DNA from M2 population
DNA quantification, normalization, pooling and super pooling
Fishing out genomic, amino acid and protein sequence of candidate
genes for trait of interest
Setting up bioinformatic workflow for fixing TILLING fragments
and primer synthesis
PCR amplification of TILLING fragments and preparation of
sequencing libraries
DNA sequencing using Illumina Myseq and bioinformatic
assembly for mutation discovery
Evaluation of mutant plants
EMS
TILLING workflow by sequencing
14
15. TILLING by sequencing work flow
Optimal density of induced mutations by
carefully adjusting mutagenesis conditions
15
17. TILLING by sequencing work flow
Isolation of genomic DNA
from M2 population
DNA Extraction methods was optimised
Spin column based extraction
with silica loaded binding
buffer
Bernhard Hofinger and Bradley
Till (2013)
Modified method of Murray and
Thompson (1980)
CTAB method of DNA extraction
by (Doyle and Doyle 1987)
768 mutant samples were extracted and stored in 96 well plates in 8*8*12 format
17
18. TILLING by sequencing work flow
DNA quantification,
Normalization and pooling
The DNA concentration was measured with
Tecan Nano Quant Infinite M200 pro (Tecan,
Switzerland)multimode reader using a nano
quant plate designed for DNA quantification.
The software Tecan i-control provides the
DNA concentration in ng/ µl along with
A260nm/A280nm purity ratio.
DNA quantification
18
19. DNA quantification,
Normalization and pooling
After assessment of the
concentration, DNA samples were
normalized with different volume of
water addition computed by using the
formula
V1 C1/C2 = V2.
With final concentration = 100ng/µl
For dispensing different volumes of water in
768 samples in the deep well plates, a Tecan
Freedom Evo75 (Tecan, Switzerland) robotic
liquid handling system was employed
TILLING by sequencing work flow
DNA Normalization
19
20. TILLING by sequencing work flow
DNA quantification,
Normalization and pooling
DNA pooling and super pooling
Till et al. ,2007(in rice mutants populations )
& Uauy et al. 2009 (in wheat mutants populations)
20
21. TILLING by sequencing work flow
Selection of candidate genes
Fishing out genomic, amino acid
and protein sequence of candidate
genes for trait of interest
The first draft genome sequence
Vigna radiate var. radiata Kang et al. (2014)
Conservation of Arabidopsis Flowering Genes in
Model Legumes (Hecth et al.,2005)
http://www.ncbi.nlm.nih.gov/
Selection of candidate genes
21
22. TILLING by sequencing work flow
Setting up bioinformatic workflow
for fixing TILLING fragments and
primer synthesis
Prediction of TILLING fragment
The five amplicons covering five key
candidate genes with maximum mutation
probability for missense mutation were fixed
using the bioinformatic pipeline CODDLE.
The Primers for PCR amplification of five
TILLING fragments were designed with
PRIMER 3 software embedded with CODDLE.
22
23. TILLING by sequencing work flow
Setting up bioinformatic workflow for
fixing TILLING fragments and
primer synthesis
Gene Models of candidate genes
23
24. Amplification of TILLING fragments
a. GIGANTEA (GI) b. RAMOSUS (RMS)
c. CONSTANS (CO) d. LEAFY (LFY)
24
26. NGS Sequencing
Most commonly used NGS platforms
1.454 Genome Sequencer FLX Ti
2. Illumina (Solexa)
Illumina sequencing has also been adapted to high-throughput TILLING, and has
been used to screen bread-wheat, durum-wheat, and rice populations (Tsai et al.,
2011).
26
27. S.No
Gene
Name
Variant ID
Nucleotide
position
change*
Referenc
e Base
Calle
d
Base
Type of
variant
Position
of
Variant
1. GI MTP-M1 630 C A/T SNP Exon
2 GI MTP-M2 605 G A SNP Exon
3. RMS MTP-M3 1511 T A SNP Exon
4. RMS MTP-M4 1520 C A/T SNP Exon
5 CO MTP-M5 732 C T SNP Intron
6 CO MTP-M6 1351 C T SNP Intron
7 CO MTP-M7 734 A T SNP Intron
8 TFL1b MTP-M10 165 G A SNP Exon
SNP discovery and detection
* Variant position based on TILLING fragment
8 SNP
5-Exon
3-Intron
27
28. Functional analysis of sequence variants
Discovered sequence variants were analysed by the PARSESNP program
(http://www.proweb.org/parsesnp/),
SIFT (http://sift.jcvi.org/www/ SIFT_seq_ submit2.html.)
Ng and Henikoff, 2002)
The predicted SIFT score ranges from 0 to 1. The amino acid substitution is
predicted damaging is the score is < 0.05, and tolerated if the score is > 0.05.
28
29. TILLING by sequencing work flow
Deconvolution
TFL1b–R4,C2
MTP-38,MTP-134, MTP-230,
MTP-326MTP-422,MTP-518,
MTP-614,MTP-710
GI -R2,C3
MTP-15,MTP-111,
MTP-207,MTP-303,
MTP-399,MTP-495,
MTP-591,MTP-687
RMS-R1,C4
MTP-4,MTP-100,
MTP-196,MTP-292,
MTP-388,MTP-484,
MTP-580,MTP-676
29
33. Implications of the current investigation for attaining
ideal plant type for Mechanical harvesting and high
productivity
MTP-134-03
MTP-134-15
MTP-399-11
MTP-399-16
MTP-580-07
MTP-580-19
MTP-580-21
GI
RMS
33
