These high quality genomes are global resource and are being used by all the genomics and breeding researchers across the world including ICRISAT. High density genotyping assays developed and currently been deployed for generating high throughput and high density genotyping data on germplasm and breeding lines.

1. Groundnut genomic tools and
integration in breeding
Manish K. Pandey
Senior Scientist-Groundnut Genomics
Email Id: m.pandey@cgiar.org

2. Key areas of research
 Genomic resources and genotyping assays
 Trait discovery and diagnostic markers
 Integration of genomics in groundnut breeding

3. Genomic resources
and genotyping
assays…

4. Genomic Resources:
Reference genomes,
gene expression atlas
and genetic markers in
cultivated groundnut
 From only ~1000 SSRs in 2012 to >300K genome-
wide SSR markers
 >100K InDel markers and primers
 Millions of genome-wide SNP markers
 These genetic markers are now in use for conducting
genetic, genomics and breeding research
Global gene
expression atlas
of cultivated
groundnut (Pl
Biotech J 2020
18:2187-2200
ICRISAT co-led (4)/contributed (3) in 7 of 8
genome sequencing efforts. These high quality
genomes are global resource and are being used
by all the genomics and breeding researchers
across the world including ICRISAT
2016 2018 2019 2020

5. High-density genotyping assays/platforms
Scientific Reports 2016, 7:40577; Molecular Plant 2016;10:309-322; Theor Appl Genet 2019, 132(4):1001-1016; The Crop Journal 2020, 8:1-15; Theor Appl Genet 2020,
133:3101–3117; Pl Biotechnol J 2020; 18:992-1003; Pl Biotechnol J 2020; 18:1457-1471; Genes 2021, 12:37.
High density genotyping assays developed
and currently been deployed for generating
high throughput and high density
genotyping data on germplasm and
breeding lines
58K SNPs Axiom_Arachis assay Genotyping-by-Sequencing (GBS)
Applications
Fingerprinting & genetic diversity
Trait mapping
Genomic selection
 Marker-based varietal adoption
Whole genome sequencing

6. Mid-density genotyping assays/ platforms
Mid-density genotyping assay with 5000 SNPs
including 160 associated SNPs for 8-10 traits
as part of bilateral project. This assay will
become available for use from Feb 2021
onwards with just USD 6/sample.
SNP calling from WGRS data on a set
of 264 cultivated genotypes using
cultivated tetraploid genome completed
 10,000 highly informative uniformly
distributed SNPs identified and shared
with EiB
 Assay with 4K SNPs with financial
support from EiB in very early stage
Thermo Fisher’s AgriSeq Targeted GBS
KASP assay @ Intertek platform
Mid-density genotyping assay with 4000 SNPs
@Intertek platform with tentative cost of
genotyping of US$11/ sample (384 samples) and
US$10/ sample (1536 samples). Hopefully this
assay will become available in early 2022.

7. Quality check (AhQC) panel to check hybridity in SA,
WCA & ESA groundnut breeding programs
 Sequencing, SNP discovery and shortlisting of 48 most promising
SNPs in addition to 10 more informative SNPs for KASP assay`.
 A set of 20 SNPs showed high level of discriminative features and
thus forms the first set of QC SNPs.
 Tested successfully the initial quality check (AhQC) panel with 20
SNPs among founder parents of IC-Asia and IC-WCA GN breeding
programs; while genotyping of samples from IC-ESA and ICAR-DGR
is in progress at Intertek.
 IC-Asia GN breeding program deployed QC panel of 20 SNPs for
checking hybridity among a set of 700 F1 plants from 35 cross
combinations and their parental genotypes during post-rainy 2020.
In addition to IC-Asia, this QC panel is ready for deployment in IC-WCA
groundnut breeding program while it will become available from Feb 2021 for
ESA as well. Also developing for 3 major breeding programs in India (ICAR-
DGR, UAS-Dharwad and RARS-Tirupati) during 2021.
S. No. Intertek SNP ID S. No.Intertek SNP ID
1 snpAH0030 11 snpAH00053
2 snpAH0031 12 snpAH00059
3 snpAH0033 13 snpAH00064
4 snpAH0035 14 snpAH00066
5 snpAH0037 15 snpAH00067
6 snpAH0038 16 snpAH00071
7 snpAH0041 17 snpAH00079
8 snpAH0042 18 snpAH00087
9 snpAH0048 19 snpAH00088
10 snpAH0049 20 snpAH00091

8. Trait discovery &
diagnostic markers…

9. Groundnut
PCN1
Groundnut
PCN2
Groundnut
PCN3

10. Target traits for marker discovery
Must have traits
Nice to have traits
Leaf rust resistance
Seed coat color and shelling percentage
Late Leaf spot resistance
Iron deficiency tolerance
Oil & protein content (NIRS phenotyping)
Fresh seed dormancy
Haulm weight
Aflatoxin contamination
Stem rot resistance
Blanchability, sugar content, salinity tolerance
Heat tolerance (wilting@ high temp)
Others/New traits
Growth habit
Fatty acid (Oleic, linoleic, and palmitic acids)
Seed weight
Validated markers
available at
Intertek platform
Under validation
process at
Intertek platform
Significant lead

11. Marker (GMRQ517) for rust resistance
Marker (GMLR975) for late leaf spot resistance

12. 10-SNP panel for FDR and high oleic acid
SNP ID
Position
(bp)
Chrom
Resistant
parent
allele
Susceptible
parent allele
Trait
GKAMA03QR517 131739517 A03 A C Rust
GKAMA03QR786 133497786 A03 T A Rust
GKAMA03GR173 134613173 A03 C A Rust
GKAMA03GR429 134225429 A03 C A Rust
GKAMA03QR843 131788843 A03 C T Rust
GKAMA03QL975 131784975 A03 G A Rust
GKAMA02GL975 789755 A02 G C LLS
GKAMA02GL582 1271582 A02 G C LLS
GKAMA02GL779 436779 A02 T C LLS
GKAMFAD2B 63041191 B09 A - Oleic acid
Genotyping cost reduced from 13 to 1.5 USD/sample for FDR and
oil quality
Used so far generating ~704, 256 datapoints (Dec 2020)..highest
among ICRISAT crops
ICRISAT India
ICAR-DGR India
UAS-Dharwad & Raichur India
RARS-ANGRAU, Tirupati India
ICRISAT Mali
ICRISAT Malawi
ICRISAT Nairobi
NaSARRI Uganda
CRI, CERAAS Ghana
ISRA/ CERAAS Senegal
Uni of Southern Queensland Australia
Peanut Company of Australia (PCA) Australia
AgResearch Consultants Georgia

13. Validated diagnostic markers for seed
weight available in 2020 @Intertek platform

14. Diagnostic markers under validation @Intertek
 Sequencing-based analysis for QTLseq samples completed with tetraploid
genome; associated SNPs identified for foliar disease resistance and
verification in progress with Intertek for 38 SNPs
 Sequenced and analysed high oleic varieties Girnar 4 (ICGV 15083) and
Girnar 5 (ICGV 15090); new marker developed for FAD2A and verification
in progress with Intertek for 4 SNPs.
 Associated SNPs identified and verification is in progress with Intertek for:
flowering duration (1 SNP), fresh seed dormancy (13 SNPs),
plant habit (3 SNPs), shelling percentage (5 SNPs),
seed weight (8 SNPs), testa color (3 SNPs),
net blotch resistance (13 SNPs) and blanchibility (13).

15. Project Title: Identifying the genomic regions and
genes for drought and heat tolerance
P Latha, AN Kumar, RP Vasanthi,
KVN Madhuri, ARS-ANGRAU,
Tirupati, Andhra Pradesh
Ramesh Bhat, Spurthi
Nayak, Babu Motagi, VP
Chimmad
UAS-Dharwad, Karnataka
Manish Pandey, Rajeev
Varshney, P Janila
ICRISAT, Hyderabad, Telangana
 MAGIC population and two RIL populations
Field before heat stress Field during heat stress Field after heat stress
Susceptible parent Tolerant parent

16. Exploring haplotypes for key traits
Bevan et al. 2017, Nature
Example: Haplotype discovery for A. flavus infection

17. Project Title: A strategy to exploit genomic selection for
achieving higher genetic gains in groundnut
T Radhakrishnan, Chandramohan
ICAR-DGR, Junagadh, Gujarat
Ramesh Bhat, Babu Motagi
UAS-Dharwad, Karnataka
Manish Pandey, Rajeev Varshney,
P Janila, Abhishek Rathore
ICRISAT, Hyderabad, Telangana
John Hickey
The Roslin Institute,
The University of Edinburgh, UK
 4-part GS prediction strategy for
crops…optimized for groundnut
 2-part GS prediction strategy with available dataset of
groundnut training population & 2000 advanced breeding lines
 5K mid-density genotyping assay for routine use in groundnut genomic selection

18. Optimization of genomic prediction based selection in
groundnut
 Naïve interaction model (E+L+G+GE) and naïve and
informed interaction model (E+L+G+LE+GE) identified as
promising GS models for improving traits with high G x E.
 High prediction accuracies (>0.600) were observed for days to
hundred seed weight, oil content, rust@90days, rust@105days
and late leaf spot@90days while medium prediction
accuracies (0.400-0.600) could be obtained for pods/plant,
shelling %, total yield/plant.
 Groundnut training
population includes 440 elite
breeding lines from ICRISAT
& UAS-Dharwad breeding
program
 Has variation for key
agronomical traits focused by
the Indian groundnut
breeding programs.
 High density genotyping
data generated with 58K
Axiom_Arachis SNP
array

19. Genomic selection implementation plan in groundnut
 Working with GN-breeding and SBDM to initiate GS using training population more relevant to ICRISAT GN-breeding
 DNA from 2000 advanced breeding lines from ICRISAT & NARS breeding programs (including AICRP lines) ready for
genotyping with mid-density assay which will help in expanding existing training population

20. Parmar et al. 2021. Unpublished
Single seed-based (chipping) genotyping
 Optimized in
groundnut
breeding
@ICRISAT
Cost saving
Time saving

21. Integration of genomics in
groundnut breeding…

22. Improved rust and late leaf spot resistance lines in
groundnut
56- 96% Yield advantage in
improved groundnut lines
Theor Appl Genet, 2014
TAG 24
Susceptible
GPBD 4
Resistant
TAG 24 + rust QTL
Resistant introgression

23. Three MABC lines completed final year of testing in Indian
National Trial (AICRP-G) for varietal release
Six best MABC lines (ICGV 13192, ICGV
13193, ICGV 13200, ICGV 13206, ICGV
13228 and ICGV 13229 selected with 39–
79% higher mean pod yield and 25–89%
higher mean haulm yield over their
respective recurrent parents.

24. Improved lines with high oleic acid @ICRISAT
 Girnar 4 (ICGV 15083) and Girnar 5
(ICGV 15090) released as first high
oleic varieties in six major groundnut
growing states of India
 Also first molecular breeding bred
variety among oilseed crops
 ICGV 15074 set to release as first
high oleic varieties in Gujarat State
of India

25. GJG 9 (Spanish bunch), GG 20 (Virginia
Bunch), GJGHPS 1 (Virginia Runner).
Marker-assisted improvement of GJG 9, GG 20 and GJGHPS 1
for resistance to rust and LLS and high oleic acid

26.  Kadiri 6 (K 6) is a popular Spanish Bunch groundnut variety has high pod yield, uniform pod size, preferred
pod and kernel features
 K 6 covers over 46% Breeder Seed demand in India through public sector seed distribution (AICRP-G, 2018)
and is the most popular variety.
Marker-assisted improvement of K6 for resistance to rust
and LLS and high oleic acid

27. Traits improved Improved varieties Reference (ICRISAT & NARS-India)
Rust resistance TAG 24, JL 24 and
ICGV 91114
ICRISAT (Theor Appl Genet 2016, 127(8):1771-81; Plant Breeding 2016,
135(3): 355-366; Euphytica 2020 216:85)
High oleic acid ICGV 06110, ICGV 06142 and
ICGV 06420
ICRISAT (Plant Science 2016, 242:203-213)
High oleic acid, resistance to rust and
late leaf spot (LLS)
GJG 9, GG 20 and GJGHPS 1 ICRISAT (The Crop Journal 2020, 8:1-15;
doi.org/10.1016/j.cj.2019.07.001 2020)
High oleic acid, resistance to rust and
LLS
Dh86, ICGV 87846, ICGV
00351 and Kadiri 6
ICRISAT (Frontiers in Genetics 2020, 11:514)
Rust and LLS resistance JL24 UAS-Dharwad, India (Electron J Plant 2016 7:37–41 )
Rust and LLS resistance TMV 2 UAS-Dharwad, India (Plant Breed 2017 136(6):948–953)
High oleic acid ICGV 05141 ICAR-DGR, Junagadh, India (Euphytica 2018, 214:1622018)
High oleic acid and resistance to rust
and LLS
GPBD 4 ICAR-DGR, Junagadh, India (Nawade et al. 2019)
High oleic acid ICGV 06100 ICAR-DGR, Junagadh, India (PLoS ONE 2019 14(12): e0226252)
Molecular breeding products @ICRISAT and NARS: Genes/QTLs
from genome to farmers field

28. ICRISAT bred molecular breeding products
 Three high oleic Spanish Bunch lines ICGV
16668, ICGV 16697 and ICGV 16690
completed AVT-2 trial and found promising
based on yield superiority over checks and
have >80% oleic acid
 Three rust resistant Spanish Bunch lines
ICGV 14421, ICGV 13189 and ICGV 13207
completed AVT-2 trial and found promising
based on yield trial and superiority over
recurrent parent and checks
 >300 breeding lines from marker-based
early generation selection for resistance to
rust and LLS and high oleic acid at different
stage of selection and evaluation
 High-oleic Virginia Bunch varieties Girnar
4 (ICGV 15083) and Girnar 5 (ICGV 15090)
released in 2020 and dedicated to nation by
Prime Minister Modi on 16th Oct, 2020

29. WGRS
2017
58K SNPs
array
2017
Progenitor
Genomes
2016
DArT
2014
KASP
2013
GBS
2016
5K SNPs
assay
2020
Seed
chipping
2020
QC-SA &
WCA
2020
4X
genomes
2019
10 SNP
panel
2017
Gene
expression
atlas
2020
Where we are today…

30. QC IC
varieties ?
2022
Haplotype
assay
2022
QC HOL
2021
New
Diagnostic
markers
2021
4K SNPs
@Intertek
2021
???
Custamized
assays
2023
Planned/possible assays...
QC ESA
NARS
2021
New
Diagnostic
markers
2022
New
Diagnostic
markers
2023

31. Mid-density assay with 4/5K SNPs (2021) for genetic purity testing among founder parents
10-SNPs panel (2017) for rust and LLS resistance and high oleic acid for early
generation selection
Seed weight & fresh
seed dormancy 2021
Mid-density assay with 4K/5K SNPs (2021) for genomic selection breeding
Integration of genomic tools in breeding
QC panel with 20 SNPs (2020/21) for hybridity testing in F1 plants
Mid-density assay with 4K/5K SNPs (2021) for checking homozygosity within line
• Mid-density assay with 4K/5K SNPs (2021) for tracking ICRISAT
bred material in seed chain/varietal adoption in farmers field
• Genetic purity testing kit with 10 SNPs for high oleic varietiesSeed chipping preference
Customized assay for foreground selection, background
selection and genomic selection

32. Data management
 Datasets are being regularly made publicly available by submitting data in open access
platforms including NCBI, CEGSB and ICRISAT Dataverse

33. Challenges & Opportunities…
• Current structure is multi-layered and it should be flattened by
bringing crop scientists together
• Non-inclusiveness in core institutional activities
• Lack of recognition and funding support from institutional
initiatives such as CtEH, AVISA, ICAR-ICRISAT and CRP-
GLDC
• Further opportunities in modernization of breeding program
such as multipart GS & haplotype-based breeding

34. Team, Collaborators & Funders
Rajeev Varshney
P Janila
Hari Sudini
Abhishek Rathore
Anu Chitikineni
Prasad Bajaj
Damaris Odeny
Sunil Gangurde
Vinay Sharma
Pushpesh Joshi
Sejal Parmar
Aamir Khan
T Radhakrishnan
KL Ratnakumar
SK Bera
Scott Jackson
Peggy Ozias-Akins
David Bertioli
Soraya Bertioli
Richard Michelmore
Lutz Froenicke
Baozhu Guo
Corley Holbrook
Steven Cannon
Guahao He
Xuanquiang Liang
Xiaoping Chen
Yanbin Hong
Xing Jun
Shanlin Yu
Shi Hua Shan
Mei Yuan
Xiao Yuan Chi
Wang Shuping
Honge Li
Xun Xu
Liu Xin
Obarley Yu
Wei Zhang
Changhoon Kim
Shaun An
Bellbull Kim
Sachiko Isobe
Kenta Shirashawa
Ramesh Bhat
Spurthi Nayak
HL Nadaf
Hasan Khan
R Vasanthi
D Latha
K NagaMadhuri

35. Thank You