1

1. 1
TILLING by Sequencing (T by S) in Mung bean (Vigna
radiata (L.) R. Wilczek) for altered plant architecture
Varadaraju Anusheela, Ramadoss Bharathi Raja, Venkatesan Thiruvengadam,
Kulandaivelu Ganesamurthy, Sundaram Ganesh Ram.
Centre for plant breeding and Genetics, TNAU, Coimbatore-641003.
Presented by
Dr. Anusheela
Varadaraju

2. 2
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
• Helps reduce PMS symptoms
• Detox
• Healthy eye sight
• Prevents constipation
• Anti-ageing qualities
• Prevents acne
• Exfoliates skin
• Strengthens hair and nail

3. 3
Introduction
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. (ON1394)

4. 4
DHAL PRICE - 21/OCT/2017
₹ 99 /kg
₹ 99 /kg
₹ 116 /kg
₹ 109 /kg
₹ 102 /kg
₹ 95 /kg
CHENNA BLACK
TUR DHAL
GRAM DHAL
MUNG BEAN
MUNG BEAN DHAL
RAJMA
http://livechennai.com/Rice_dal_price_chennai.asp

5. Introduction
More intensive interventions is required
CONSTRIANTS
1. Manual harvesting is very expensive and time-consuming
2. Inefficient plant type and low yielding potential
3. Poor productivity which does not support intensive labour
utilization
5

6. 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
6

7. 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 disturb the genes
How it can be
achieve?
7

8. Photoperiod
pathway
GI CO
LFY AP1
FT
TFL
SAM
Genetic Pathways
8
GI-GIGANTEA;CO-CONSTANS;FT-FLOWERING LOCUS T;LFY-LEAFY;AP1-APETALA;
TFL-TERMINAL FLOWERING;SAM-SHOOT APICAL MERISTEM;RMS-RAMOSUS;
MAX-MORE AUXILIARY GROWTH.

9. 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
9

10. 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
10

11. 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
11

12. 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
12

13. 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
13

14. CG
Flowering
genes
LFY
GI
CO
Shoot
Branching
genes
RMS
TFL
Key Candidate genes fixed for manipulation
14

15. 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
15

16. 1.To produce mutant populations in mung bean with the optimal density of
induced-mutations by choosing the most suitable variety and carefully
adjusting mutagenesis conditions
2.To use the optimal mutagenesis protocol to treat and grow 3000
individuals, bank their seeds
3.To use a high throughput sequencing technologies for detecting functional
mutations of the target genes involved in flowering time and morphogenesis
in TILLING populations
4.To evaluate discovered mutants in M3 generation and record the
biometrical characters to identify altered phenotype suitable for mechanical
harvesting.
Objectives
16

17. 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
Phenotyping of selected mutant plants
EMS
TILLING workflow by sequencing
17

18. TILLING by sequencing work flow
Optimal density of induced mutations by
carefully adjusting mutagenesis conditions
18

19. TILLING by sequencing work flow
Generation of M1 and
M2 TILLING populations
19

20. TILLING by sequencing work flow
Generation of M1 and M2
TILLING populations and
banking their seeds in RGB
Process involved in banking Mungbean TILLING
Population at Ramiah Gene Bank, PGR.
20

21. 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
21

22. 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
22

23. 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
23

24. 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)
24

25. 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
25

26. 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.
26

27. TILLING by sequencing work flow
Setting up bioinformatic workflow for
fixing TILLING fragments and
primer synthesis
Gene Models of candidate genes
27

28. TILLING by sequencing work flow
PCR amplification of TILLING fragments
and preparation of sequencing libraries
Amplication in cross species primer-
difficult
Need optimization
A unified LR-PCR approach was applied
to amplify all the TILLING fragments (with
few exceptions).
The touchdown PCR protocol was
performed to minimize off-target
amplification
PCR Amplification
28

29. Amplification of TILLING fragments
a. GIGANTEA (GI) b. RAMOSUS (RMS)
c. CONSTANS (CO) d. LEAFY (LFY)
29

30. e. TERMINAL FLOWERING 1b
(TFL1b)
30

31. The concentration of PCR products
were quantified using the Qubit dsDNA
BR assays system (Invitrogen, Carlsbad,
CA) to avoid errors from free
nucleotides, excess enzymes present in
the PCR product.
Normalized PCR products were
equimolarly pooled across the genes on
the predicted length of the
individual TILLING fragments
Normalization and equimolar pooling of PCR products
TILLING by sequencing work flow
PCR amplification of TILLING fragments
and preparation of sequencing libraries
31

32. TILLING by sequencing work flow
DNA sequencing using Illumina Myseq and bio
informatic assembly for mutation discovery
NGS Sequencing
Commonly used method to identify mutations in a
TILLING population = Li-Cor system
fluorescent dye primer
DNA concentrations
ratio between the cleavage enzyme and PCR
product concentrations
affect the results and need to be optimized
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).
32

33. TILLING by sequencing work flow
NGS Sequencing-Contd.,
Outsourced-Genotypic Technology Pvt. Ltd, Bangalore
DNA sequencing using Illumina Myseq
and bioinformatic assembly for mutation
discovery
NGS
Library
preparatipn
Template
preparation Sequencing
Primary
analysis
De
multiplexing
Base
calling
Secondary
analysis
Read
mapping
Variant
calling
Tertiary
analysis
Variant
Annotation
Variant
filtering
33

34. TILLING by sequencing work flow
DNA sequencing using Illumina
Myseq and bioinformatic assembly
for mutation discovery
approximately 1000x which has surpassed the minimum of 50x
required for unambiguous discrimination of error from the true
variant(s)
all the variants discovered in this investigation possess very high
confidence limits
NGS Sequencing efficiency
Liu et al., 2012
34

35. TILLING by sequencing work flow
DNA sequencing using Illumina
Myseq and bioinformatic assembly
for mutation discovery
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 LFY MTP-M8 512 TTCTTC T INDEL Intron
9 LFY MTP-M9 464 GTT GT INDEL Intron
10 TFL1b MTP-M10 165 G A SNP Exon
SNP/Indel discovery and detection
* Variant position based on TILLING fragment
10 variants
8 SNP
5-Exon
3-Intron
2 INDEL 2-Intron
35

36. 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.
36

37. 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
37

38. S.
No
Mutation
Id
Genotype
deconvolved
through
Sanger
sequencing
Sequence alignment
1
MTP-M2
GI
(G605A)
MTP-399
2
MTP-M3
RMS
(T1511A)
MTP-580
3
MTP-
M10
TFL1b
(G165A
MTP-134
Sanger sequencing
38

39. TILLING by sequencing work flow
Biometrical characterization of the
discovered mutants suitable for flowering
time and branching habit
Phenotyping of
selected mutant plants 39

40. Evaluation of GI mutants in M3 generation
40

41. Evaluation of RMS mutants in M3 generation
41

42. Evaluation of TFL1b mutants in M3 generation
42

43. Implications of the current investigation for attaining
ideal plant type for Mechanical harvesting
MTP-134-03
MTP-134-15
MTP-399-11
MTP-399-16
MTP-580-07
MTP-580-19
MTP-580-21
GI
RMS
43

44. Currently, TILLING service centers are available for Model legumes
large numbers of ESTs,
deep-coverage large insert libraries with extensive contig assemblies,
both targeted and complete genome sequencing and annotation,
will allow for the efficient identification of gene (s) controlling
phenotypes in both model systems and economically important plants
This aspiration of geneticists to unravel and elucidate the function
of coded DNA may eventually lead to the development of public
TILLING / Eco TILLING services in numerous plant and animal
species, which will facilitate streamlining the process of functional
genomics for all researchers.
CONCLUSION
44

45. 45