1. CSIR-National Botanical Research Institute
Genomics of Gossypium spp. for Development of Genetic Markers and Discovery of Genes Related to Fiber and Drought Traits
Samir V. Sawant
Principal Scientist
CSIR-National Botanical Research Institute
Rana Prarap Marg
Lucknow

2. Synopsis of Presentation:
Large Scale Genomic Resource Development in Cotton.
Genes Underlying Drought Tolerance & Fiber Quality Traits.

3. Large Scale Genomic Resource Development in Cotton though Sequencing of HMPR libraries

4. Selection of Six Diverse Germplasms of
G. hirsutum (based on AFLP genetic diversity)
Genotypes
Species
Source of Collection
JKC 703
G. hirsutum
JK Agri., Hyderabad, Andhra Pradesh
JKC 725
JKC 737
JKC 770
LRA 5166
TNAU, Coimbatore, Tamilnadu
MCU5
UASD, Dharwad, Karnataka
Jena et al. (2011) Crop & Pasture Science 62:859-75

5. Genic-Enrichment by Methylation Sensitive Restriction Digestion
In-sensitive
M BstBI HpaII ClaI HindIII EcoRV
Uncut DNA
Enriched DNA
Digestion of genomic DNA with different
enzymes for methylation pattern
Rai et al. (2013) Plant Biotechnology J.

6. Reads Generated for Various Genic-enriched
Cotton Genotypes
Germplasms
Enzymes used
Total Reads
(in millions)
Total Bases
(in Mb)
JKC 703
HpaII
1.50
429.1
ClaI
1.64
474.6
JKC 725
1.36
372.9
1.87
533.5
JKC 737
1.45
407.7
1.69
542.9
JKC 770
1.30
376.1
1.76
481.1
MCU5
1.15
316.8
1.47
416.6
LRA 5166
433.9
1.70
513.4
Total
18.47
5298.8

7. Genotype wise Comparison of Genic-enriched
reads using gsMapper v2.5.3
Germplams
JKC 725
JKC 737
JKC 770
MCU5
LRA 5166
% of mapped
Reads
Bases
JKC 703 89 70 87 68 66 75 60 90 69 76 61 77 88 67 59 79 63

8. Enzyme wise comparison of Genic-enriched reads using gsMapper v2.5.3
Enzyme wise comparison of HMPR enriched reads
Germplams
% reads mapped
% bases mapped
JKC 703
78.1
61.1
JKC 725
83.2
62.3
JKC 737
 83.8
66.4
JKC 770
82.3
63.8
MCU5
80.5
64.4
LRA 5166
77.3 
56.5

9. De novo Assembly using Newbler v2.5.3
Assembler
Parameters
Cotton Genotypes
JKC 703
JKC 725
JKC 737
JKC 770
MCU5
LRA 5166
Super assembly
All Contigs (>100 bp)
58,142
61,862
54,731
53,419
27,952
63,002
533271
Singletons (millions)
1.23
1.43
1.33
1.29
0.80
1.24
3.56
Total bases (Mb)
377.9
428.1
427.3
378.4
233.4
398.9
1272.6
Large contigs (>500 bp)
21,920
20255
17,960
17,657
8,663
25,084
215504
Largest contig size (Kb)
29.7
30.9
30.4
31.0
36.0
29.6
24.3
Avg. contig size (bases)
826
808
809
815
868
900
N50 contig size (bases)
785
787
802
771
861
894
Q40 plus bases
92.78
92.6
92.25
92.63
94.25
92.99
93.8

10. Gene Prediction and Annotations
AUGUSTUS
90294
GenScan
125422
GlimmmerHMM
97533
Reciprocal Blast
Common gene models
(present in any of two or more prediction tools)
93363
Full length genes
21399
Annotation
NCBI nr
Total hits:
Unique: 38645
TAIR 10
Total hits:
Unique:
Cotton EST
Total hits:
Unique:

11. Similarity of Predicted Gene Models with Other Plant Genomes
V. vinifera
R. communis
G. raimondii
A. thaliana

12. qRT PCR Validation of 12 Randomly Selected Predicted Gene Models in G
qRT PCR Validation of 12 Randomly Selected Predicted Gene Models in G. hirsutum
Y- axis: Fold Expression in Fiber and Root as compared to Leaf tissues

13. Identification of Transcription Factor
Encoding Genes

14. qRT PCR Validation of 12 Randomly Selected Predicted Transcription factor encoding Gene Models in G. hirsutum
Y- axis: Fold Expression in Fiber and Root as compared to Leaf tissues

15. Genome-wide SNP Discovery in G. hirsutum
Pooling contigs from each germplasm
Super contigs
Output of AutoSNP
Filtered out False SNP
Detected SNP
contigs
Assembly
(Newbler v2.5.3)
AutoSNP
Using customized program
SNP discovery using Newbler v2.5.3 Assembler
Assembly of individual germplasms
Assembly (Newbler v2.5.3)

16. Strategy for SNP Discovery in G. hirsutum
G. hirsutum genotype-1
Allelic SNP (Taken)
Non-Allelic SNP (Discarded)
Assembly using gsAssembler v (40 bp overlap with 97% identity) G C
autoSNP v2.0 for contigs with minimum six reads (≥3 reads from each genotype) ×
G. hirsutum genotype-2

17. Genome-wide SNP Discovery in G. hirsutum…
Cultivars SNP summary Sequence alignment
JKC 703
LRA 5166
JKC 725
JKC 770

18. Genome-wide SNP Discovery in G. hirsutum…
Details of SNP discovery v
Distribution of identified SNPs
Total identified SNPs
4,22,617
True SNPs called
75,714
Non-redundant SNPs
66,444
Novel SNPs
66,364
UTRs, 4446
Intronic, 4518
Annotated Exonic SNPs
Synonymous
2604
Non-synonymous SNPs
6506

19. Validation of Identified SNPs in G. hirsutum
JKC 703
T C
JKC 725
JKC 770
LRA 5166
JKC 737
MCU5
SNPs used for Validation : 30
Germplasms used : 6
SNPs Detected : 30

20. SSRs distribution on the basis of Motifs
SSRs identification and Novelty comparison against Cotton Marker Database
SSRs distribution on the basis of Motifs
SSR novelty analysis
Number of SSRs
Unit size of different repeat type
47,093 Novel
SSRs
Total SSRs Identified
1,48,930
Unmatched whole sequence wise
Unmatched primer sequence wise
SSRs Successful in designing primers
56,142
Unmatched flanking sequence wise
Novel SSRs developed
47,093

21. Validation of Identified SSRs in G. hirsutum
291/297/300 bp
JKC 703
291/300 bp
JKC 770
291/297 bp
JKC 725
JKC 737
LRA 5166
MCU 5
SSRs used for Validation : 40
Germplasms used : 12
Polymorphic SSRs : 6
% Polymorphism : 15

22. Distribution of G. hirsutum SSRs and SNPs containing sequences on G
Distribution of G. hirsutum SSRs and SNPs containing sequences on G. raimondii reference genome
G. raimondii
(JGI)
(Chinese draft)
SSRs
SNPs

23. miRNA Novel to Gossypium (on the basis of miRBase)
miRNAs in Gossypium
(on the basis of miRBase)
Total miRNAs identified 78
miRNA families identified 42
miRNA novel to G. hirsutum 17
Novel
miRNAs
miR-1713
miR-2112
miR-2675
miR-3522
miR-3696
miR-165
miR-437
miR-477
miR-536
miR-950
miR-1070
miR-4343
miR-4371
miR-5023
miR-5065
miR-5555
miR-3963

24. Promoters and Cis Regulatory Elements
Promoters identified
24839
≥ 1000 bp
826
≥ 500 bp
3135
Fiber developmental stage specific Promoters
Initiation
184
Elongation 28
Secondary cell wall
 110
Size Distribution of Identified Promoters
No. of Promoters
Size in bases
Initiation (184)
Elongation (28)
Sec. Cell Wall Synthesis (110)

25. Genomic Resources Developed for G. hirsutum An Overview
Assembled
Sequences
AssembledBases
1272 Mb
Novel SNPs
66364
GC Content
37.76 %
Novel SSRs
47093
Repetitive content
12.16 %
TF’s
1093
Gene Models
93363
Promoters
3135
Full length genes
21399
Rai et al. (2013) Plant Biotechnology J.

26. Total SSRs from G. herbaceum
Development & Characterization of gSSRs and eSSRs in Diploid Cotton (G. herbaceum)
Total SSRs from G. herbaceum
UPGMA tree of 15 genotypes of G. herbaceum based on Nei’s genetic distance using 200 SSRs
263 gSSRs
1970 eSSRs
Repeat
Enriched Genomic Libraries
Drought
Transcriptome Sequencing
SSR “NBRI_gB010” among four species of cotton
Cross-species transferability of G. herbaceum derived gSSRs and eSSRs
Jena et al. (2012) Theoretical Applied Genetics 124 (3):565-76

27. (superior in fibre quality) (inferior in fibre quality)
Development of molecular markers from Indian genotypes of two Gossypium L. species
G. hirsutum
G. herbaceum
JKC 703
(superior in fibre quality)
JKC 777
(inferior in fibre quality)
Vagad
(Drought tolerant)
RAHS-14
(Drought Sensitive)
GujCot
(Drought tolerant)
RAHSIPS-187
(Drought Sensitive)
1440 SSRs
2608 SNPs
10,947 SNPs
SSR Sequence
50bp Flanking
NBRI SNPs
Public Domain SNPs
NBRI SNPs
Public Domain SNPs
111 20 2
1,847 2
38,780
334
307 15
10,947
206
Primers
334 Novel SSRs
1,847 Novel SNPs
10,947 Novel SNPs
Srivastava et al., Journal Plant Breeding doi: /pbr (In Press)

28. Microarray Based Single Feature Polymorphisms (SFPs) in
Gossypium hirsutum
Superior fiber quality
Inferior fiber quality
In Silico analysis of 37,473 SFPs in six crosses
(JKC703)
(JKC737)
(JKC783)
(JKC725)
(JKC770)
Biological replicate 1, 2,3
Biological replicate 1, 2,3
RNA extraction/microarray hybridization
Validation of SFPs in two germplasm
(JKC 703 x JKC 770)
No. of Selected SFPs
No. of SNPs found
No. of indels found
RMA background correction
“770-1,2,3.CEL”
“703-1,2,3.CEL”
“725-1,2,3.CEL”
“737-1,2,3.CEL”
“783-1,2,3.CEL”
Further analysis for SFPs
Srivastava et al. (2012) Communicated

29. SSRs/SNPs/SFPs development from Cotton
at NBRI
NBRI COTTON MARKERS
A-genome derived SSRs (genomic & expressed)
2,233
Total SSRs
59,805
AD-genome derived SSRs (Genic enrichment)
56,142
AD-Genome derived SSRs (Transcriptome sequencing)
1440
A-Genome derived SNPs (Transcriptome sequencing)
592
AD-genome derived SNPs (Genic enrichment)
66,444
Total SNPs 69,768
AD-genome derived SNPs (Transcriptome sequencing)
2,600
AD-genome derived SFPs (Microarray based)
132
Total Novel Markers
1,29,573

30. Axiom™ myDesign™ Array: Targeted genotyping, tailored for our study
COTTON SNP CHIP
(Affymetrix’s Axiom® myDesign Cotton Array)
(CSIR-NBRI)
Axiom myDesign TG Array Plates enable us to:
Easily select relevant SNPs from our SNP database
Creating panels of 500,000 markers per sample
Axiom™ myDesign™ Array: Targeted genotyping, tailored for our study
A streamlined assay:
Total genomic DNA (200 ng) is amplified and randomly fragmented into 25 to 125 base pair (bp) fragments.
These fragments are purified, re-suspended, and hybridized to Axiom Genome-Wide and myDesign Array Plates.
Following hybridization, the bound target is washed under stringent conditions to remove non-specific background to minimize background noise caused by random ligation events.
Each polymorphic nucleotide is queried via a multi-color ligation event carried out on the array surface.
After ligation, the arrays are stained and imaged on the Gene Titan MC Instrument.
Targeting 50,000 SNPs for Genotyping with Mapping Population

31. Deployment of COTTON SNP CHIP on
Mapping Populations
CICR, Nagpur:
a. H X H RIL population (Fiber Traits)
b. A X He RIL population (Mapping and Fiber Traits)
2. UAS, Dharwad:
a. H X B RIL population (Fiber Traits)
b. Core Collection (Association Mapping)
3. TNAU, Coimbatore:
a. H X H RIL population (Fiber Traits)
b. H X H RIL population (Sap sucking pests)

32. NBRI’s Cotton Database A Webpage for Cotton Resources

33. Drought Tolerance & Fiber Quality Traits
II. Genes Underlying
Drought Tolerance & Fiber Quality Traits

34. Screening of Cotton Genotypes for Drought Tolerance and Sensitivity
Screening of G. herbaceum genotypes
on different concentrations of mannitol
Effect of drought on tolerant and sensitive genotype
Mannitol percentage
Accessions
Control 2% 4% 6% 8%
Vagad
100 86
Guj cot-21 82 66
RAHS-14 76 12
RAHS-IPS-187 16
H-17 84 62 14
AH-7GP
AH-127 22 4
AH-41 18
RAS-45
DB-3-12 64 30
RAHS-131
JYLEHAR 2
GH-18-2LC
RAHS-132 34 10
Tolerant genotype (Vagad)
Sensitive genotype (RAHS-14)
Drought sensitive
Continuous watering
1 week alternate watering
Drought Tolerant
Ranjan et.al., BMC Genomics (2012) 13:94

35. Physiological Parameters in Response to Drought in Vagad and RAHS- 14
Properties of Vagad
Reduced stomatal conductance (gs)
Decreased transpiration rate (E)
Reduced water potential (WP)
Higher realtive water content (RWC)
Leading to better water use efficiency (WUE).
Vagad has inherent ability to sense the drought at much early stage and respond to it in much efficiently.
Ranjan A et.al., BMC genomics 2012 March

36. Differentially up regulated genes (Fold change ≥ 2)
Transcriptional profiling during drought and water condition in Leaf tissue of Vagad and RAHS-14
Pyrosequencing data
Microarray data
Parameters
Vagad library
RAHS-14 library
Total reads (overlap size of 100 bp and 96% identity)a
85368
56354
Total contigs (100 bp or greater)b
11439
6313
Singletone
24087
20780
Exemplar
31244
23155
Average length of contigs
350 bp
180 bp
Number of contigs with greater than 500 bp
946
705
cNumber of genes with significant hit in NCBI NR database
10772
10408
dNumber of genes with significant hit in cotton EST database
16301
13822
Genotypes
Differentially up regulated genes (Fold change ≥ 2)
Vagad water
656
RAHS- 14 water
535
Vagad drought
430
RAHS- 14 drought
411
Ranjan A et.al., BMC genomics 2012 March

37. Genome wide gene expression profiling of leaf tissue of Vagad and RAHS-14
Propanoid pathway
Pigment biosynthesis
Polyketide biosynthesis
Responses to various abiotic stresses
Secondary metabolite pathways
RAHS-14
Ethylene responsive factor
WRKY
Programmed cell death
Senescence
Lipid metabolism
Ranjan A et.al., BMC genomics 2012 March

38. Differentially up regulated genes (Fold change ≥ 2)
Comparative root Transcriptome Analysis of Drought Tolerant and Sensitive Genotypes of G. herbaceum
Root architectures
Pyrosequencing data
Drought tolerant
Drought sensitive
Reads
Bases
Contigs
Singleton
Av. Contig length
Av. S. length
GujCot-21
55, 620
13, 020, 140
1,281
30, 501
481.7bp
237.8bp
RAHS-IPS 187
49, 308
11, 199, 207
858
30, 776
532.9bp
228.6bp
Supercontigs
1, 04, 928
24,219, 347
2, 664
50, 531
508.7bp
231.7bp
Microarray data
Genotypes
Differentially up regulated genes (Fold change ≥ 2)
Vagad water
165
RAHS- 14 water
156
Vagad drought
256
RAHS- 14 drought
538
Ranjan A et.al., BMC genomics 2012 November

39. Functional enrichment of genes of root tissue in
drought tolerant and sensitive genotypes
Tolerant genotype
Sensitive genotype
Regulation of Transcription factors (TFs) under drought stress
Ranjan A et.al., BMC genomics 2012 November

40. Differentially expressed genes analyzed by Genevestigator in mapping the specific expression of genes in
different root zones
Ranjan et.al., BMC Genomics (2012) 13: 680

41. Selection of Candidate Gene for Studying the
Abiotic Response
Identification of Transcription Activator (TA) from Cotton Transcriptome of root tissue
Expression of TA
Library name TL TR SL SR
Number of Transcript (tpm) 72
(TL-tolerant leaf, TR-tolerant root, SL-sensitive leaf, SR-sensitive root)

42. Increased tolerance to drought and salt stress and better root development in tobacco over expressing GheTA WT
GheTA
control
50 mM Mannitol
150 mM Mannitol
200 mM Mannitol
250 mM Mannitol WT
GheTA
control
50 mM NaCl
75 mM NaCl
100 mM NaCl
150 mM NaCl
GheTA WT
GheTA WT

43. Abiotic stress tolerance of the GheTA over-expressing
tobacco transgenic plants by leaf disk assay
Control
5 % PEG
10 % PEG
100 mM NaCl
150 mM NaCl
250 mM Mannitol
500 mM Mannitol
WT GheTA
WT GheTA

44. Over-Expression of GheTA leads to increased root biomass and better WUE in cotton transgenic plants
Wild type
Cotton Transgenic
Carbon Isotope Discrimination ratio shows higher water use efficiency (WUE) of cotton TA transgenic plants

45. Expressional Reprogramming During Fiber Development In Contrasting Genotypes of G. hirsutum
Fiber quality of genotypes
Fiber Quality Parameters
Superior genotypes
Inferior genotypes
JKC 725
JKC 777
JKC 703
JKC 737
JKC 783
2.5% span length (mm)
Fiber strength (g/tex)
Fineness (micronaire)
Fiber lignin content
Fiber cellulose content
Nigam et al. (2013) Communicated

46. Microarray data analysis
Method used for Analyzing Microarray Data from Contrasting Cotton Genotypes
Microarray data analysis
Two way ANOVA study

47. Singular Enrichment Analysis (SEA)
Genotype significant genes
DPA significant genes
Interaction significant genes

48. MapMan Bins Cluster Analysis
0DPA
9DPA
12DPA
19DPA
25DPA
6DPA
Cluster-4
Cluster-6
Cluster-5 A B
Superior genotypes
Inferior genotypes

49. Enrichment of Transcription factors

50. 25 DPA Fiber Transcriptome: Assembly and Annotations
de novo and merged assembly
Annotation of unigenes
Parameters
Merged assembly of both genotypes
JKC 703
JKC 777
Total reads generated
547939
488128
Total bases generated (Mb)
168.4
160.9
329.3
Average read size (bp)
307
330
318
High Quality reads used in assembly
529496
473666
972907
All Contigs (>100 bp)
17900
16457
21308
Singletons
53983
45023
81120
Total bases after assembly (MB)
24.7
22.3
37.2
Large contigs (>500 bp)
8752
8153
12947
Largest contig size (bp)
3560
4991
5008
Average contig size (bp)
860
823
936
N50 contig sizea (bp)
893
838
987
Aligned Reads (%)
86.8
88.0
86.9
Aligned Bases (%)
86.4
87.4
85.6
Inferred read errorb (%)
2.0
1.8
Q40 plus basesc (%)
94.0
94.1
95.5
Parameters
Genotypes
Merged assembly of both genotypes
JKC 703
JKC 777
Total unigenesa
71883
61480
102428
Hits in 'NCBI nr' database
40134
36844
56390
Hits in 'tair9' database
33,359
37,017
51120 
Hits in ESTScan
44592
40570
20,852
Differential unigenes
2156
2076 -

51. Correlation between Cotton Fiber Microarray and Transcriptome Sequencing
R2 =0.68, p-value = 0.001

52. Hypothetical regulatory model showing over-represented genes and pathways in Superior and Inferior genotypes
SA ?
ABA 25 19 12 9 6
C2C2-GATA
NAC BR
Increased Stress Tolerance to facilitate elongation process up to its completion
Barssinosteroid signalling
WRKY
Auxin GA
Fibre Cells Continuative Elongation JA
Increased Stress Environment within fibre cell and complete end of cell elongation process
H202
POX
Transcription factors
Oxiplipins
Continued Barssinosteroid Signalling
SCW
ABI3/VP1
SPL5
Phospholipases
Pat5, Pat6
AGPs
Flavonoid Biosynthesis
DET2
BES1
End of Cell Elongation
Energy Exhaust
Efficient energy source for fast elongating fiber (Oxidative Phosphorylation e.g.TCA ,Glycolysis)
Transporter Machinery
BIN2
DET2
BES1
ABC transporter
Barssinosteroid Targeted Gene Expression
Barssinosteroid Targeted Gene Expression
Elongation
CSEA
Asp family
Continued Energy Providing Machinery
Cell wall Enzymes
Pectin Modification
SCW formation Starts
PG,PAE,PME,PMEI
Cell wall loosening
ALDH
LIM domain S3
mRNA and Protein degradation
Ubiquitin ligase, Proteasome, Splisosome
Large number of ribosomal subunits (Better Protein synthesizing machinery )
MEE 59
PRF5
EXL5
Decreased high elongation rate of fibre cells during elongation period
APY2
AGPs
SPL3
Cell death
HSF
Calcium Signalling
Induction of Stress Hormones signal like, Ethylene and ABA
Lipid peroxidation
HSPs,
Ca ++ /CAM1
Initiation
AP2-EREBP
H2O2
Oxidative stress
ROS
ROS
Ascorbate peroxidase
Glutathione-S-Transferase
WRKY
Oxidative stress
SUPERIOR GENOTYPE
INFERIOR GENOTYPE

53. Positions of mapped differentially expressed genes on QTL
QTL start
QTL end
QTL size
QTL size (MB)
chr size
chr size (MB)
% covered by QTL in a chr
QTL location
Total No. of genes in the QTL region
Completely Mapped genes in QTL region (Our data)
Total mapped gene on Chromomosome (our data)
27.91
55.86
49.9
Chr 1
2757 50
138
19.31
62.76
30.7
Chr 2
2148 49
130
32.24
45.76
70.4
Chr 3.1
2986 29 92
3.707
8.1
Chr 3.2
884 18
8.37
62.17
13.47
Chr 4
1008 32
133
58.37
64.14
91.0
Chr 5
11474 77
109
42.01
51.07
82.2
Chr 6
1334 45
114
2.11
60.98
3.4
Chr 7.1
295 13
172
43.42
71.2
Chr 7.2
4441 68
18.69
57.12
32.7
Chr 08
4592 79
147
24.78
70.71
35.0
Chr 09
3146
245
642463
0.64
62.68
1.0
Chr 11 95 2
140
600
1684
Percentage of genes mapped in QTL
600/1684 = ~35%
Circos Plot of all the differential genes mapped on the cotton jgi genome with all the QTL.

54. Heat map of 9 TA5 transcription factors
microRNA156 Targeted Transcription Factor (TA5) Governs the Boll Number, Size and Lint Yield in G. hirsutum
Heat map of 9 TA5 transcription factors
q-RT PCR measurement
Ghi S1_s_at
(GhSPL5)
Gra A1_at
(GhSPL13)
Gra A1_at
(GhSPL14)

55. GhTA5 produce transcripts that are targeted by miR156
Northern blot of miR156 & miR172 in cotton fiber

56. Phenotypic evaluation of overexpression and knockdown lines
Overexpression Lines Wild Type Knockdown Lines
Overexpression lines
Knockdown lines 1 2 3 5 4 6
Wild Type
Number of Cotton Bolls
Overexpression line
Knockdown line
Lint cotton weight (gm) /plant
Seed cotton weight (gm) /plant
Average of cotton boll per plant

57. Identification and characterization of fiber specific promoter in G
Identification and characterization of fiber specific promoter in G. hirsutum (NBRI_2800)
Fold Change
Fiber developmental stages
Expression pattern of NBRI 2800 gene in different fiber developmental stages

58. Histochemical localization of GUS expression in NBRI_2800 transgenic cotton plant

59. & Epigenetic regulation
Acknowledgments
HMPR Sequencing
& Epigenetic regulation
Sunil K. Singh
Krishan M. Rai
Verandra Kumar
Functional Genomics
Neha Pandey
Rajiv Tripathi
Vrijesh Yadav
Anshulika Sable
Bioinformatics
Dr. Mehar Asif
Dr. Sumit K. Bag
Dipti Nigam
Archana Bhardwaj
Ridhi Goel
Pooman Pant
Cotton Marker
Dr. S N Jena
Anukool Srivastava
Ravi P. Shukla
Collaborators
J K Agrigenetics Tierra Seed Science
TNAU, Coimbatore CICR, Nagpur
UAS, Dharwad

60. Thank You