1) The document describes the development and validation of 90 Groundnut KASPar Assay Markers (GKAMs) for peanut genotyping using a KASPar assay platform. 2) Validation testing found 73 GKAMs were polymorphic across 94 validation genotypes and 71 were polymorphic between parental lines of 27 mapping populations. 3) Genotyping 280 reference peanut varieties found polymorphism information content ranged from 0.01 to 0.37, with four main clusters corresponding to subspecies and genome type.

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KASPar genotyping assay and SNP call
Pawan Khera1, Manda Sriswathi1, Manish Roorkiwal1, Manish K Pandey1,2, Hari D Upadhyaya1, Pasupuleti Janila1,
Peggy Ozias-Akins2, Rajeev Varshney1,3,*
1International Crops Research Institute for the Semi-Arid Tropics, Hyderabad, India
2The University of Georgia, Tifton, USA
3CGIAR Generation Challenge Programme, c/o CIMMYT, Mexico DF, Mexico
*Address for correspondence: r.k.varshney@cgiar.org
Next generation sequencing and faster genotyping technologies have led to the development of a range of SNP genotyping platforms such
as VeraCode, GoldenGate or Infinium assays of Illumina, dynamic allele-specific hybridization (DASH), arrayed primer extension reaction (APEX) and
competitive allele-specific PCR (KASPar) assays. KASPar assays however seem to be the most promising cost-effective genotyping platform especially
when only a few SNPs need to be genotyped with only few samples. Therefore, a set of 96 SNPs identified in cultivated peanut lines at UGA, was used
for developing Groundnut KASPar Assay Markers (GKAMs). GKAMs were validated on a validation set (94 genotypes), that includes parental lines of
mapping populations and wild genotypes. High quality SNP calling could be obtained for 90 GKAMs of which 73 GKAMs were polymorphic across
validation set while 71 GKAMs between parental lines of the mapping populations. The effectiveness of GKAMs for elucidating genetic relationships was
also assessed by genotyping the reference set (280 genotypes) of peanut. The polymorphism information content (PIC) ranged from 0.01 to 0.37 with a
mean of 0.31. Discrete clusters were obtained according to the genome type, subspecies and botanical variety. Interestingly, the subspecies fastigiata
comprising of four botanical varieties fastigiata, peruviana, vulgaris and aequatoriana (not used in the study) formed a single cluster while the subspecies
hypogaea containing botanical varieties hirsuta and hypogaea formed another cluster with frequent overlaps between the groups, an evidence of inter-
crossing during the course of evolution. Furthermore, the wild species of peanut having diploid genomes AA, BB, EE, EX and PP were grouped into a
single cluster. Developed set of GKAMs is expected to supplement available SSR repertoire for genetics studies and breeding applications in peanut.
Financial support from CGIAR Generation Challenge
Programme (Theme Leader Discretionary Grant) and
The Bill & Melinda Gates Foundation (Tropical
Legumes I & II) is gratefully acknowledged.
Development and utility of cost-effective SNP genotyping platform
for genetics research and breeding applications in peanut
Abstract
GKAM0010
[C/C], [C/T], [T/T]
GKAM0049
[G/T]
 Of the 96 GKAMs, 90 were successfully (93.8% SNP-to-assay
conversion rate) validated and 73 (81.1%) showed polymorphism
on validation set
 71 polymorphic GKAMs between parental lines of 27 mapping populations
 Maximum polymorphic markers for the combination ICG 00350 × ISATGR 5B (44 GKAMs)
 PIC ranged from 0.01 (GKAM0036) to 0.37 (38 GKAM), with mean of 0.31 in reference set
 By and large, the Cl I, II, III and IV contains genotypes of subspecies fastigiata, subspecies
hypogaea, wild species and intermediate , respectively
 Maximum dissimilarity of 45% was obtained for the genotypes ICG 8200 (A genome, A.
duranensis) and ICG 8206 (B genome, A. ipaënsis)
 GKAM markers developed in the present study have undoubtedly demonstrated its use in
molecular breeding applications and genetic diversity studies.
280 genotypes
representing 48 countries
Taxonomic distribution observed in reference
set genotypes showed four main clusters
Parental genotypes of mapping
populations
Segregating trait (s) Polymorphic
markers
Polymorphism
rate (%)
Interspecific mapping populations
TMV 2 × TxAG 6 Agronomic traits 40 44.4
ICGV 87846 × ISATGR 265-5 Agronomic traits 36 40.0
ICG 0350 × ISATGR 184 Agronomic traits 37 41.1
ICG 0350 × ISATGR 9B Agronomic traits 36 40.0
ICG 0350 × ISATGR 5B Agronomic traits 44 48.9
ICG 0350 × ISATGR 90B Agronomic traits 36 40.0
Intraspecific mapping populations
TG 26 × GPBD 4 Rust and LLS resistance 19 21.1
TAG 24 × GPBD 4* Rust and LLS resistance 18 20.0
ICG 11337 × JL 24 LLS resistance 22 24.4
ICGV 93437 × ICGV 95714 ELS resistance 20 22.2
Robut 33-1 × ICGV 95714 ELS resistance 23 25.6
ICGV 93437 × ICGV 91114 Rust resistance 9 10.0
ICGV 93437 × ICGVSM 95342 Rust resistance 23 25.6
ICGS 76 × CSMG 84-1 Drought tolerance 9 10.0
ICGS 44 × ICGS 76 Drought tolerance 5 5.6
TAG 24 × ICGV 86031 Drought tolerance 0 0.0
Chalimbana × ICGVSM 90704 Resistance to GRD 2 2.2
CG 7 × ICGVSM 90704 Resistance to GRD 6 6.7
ICGV 07368 × ICGV 06420 High & low oil content 12 13.3
ICGV 07166 × ICGV 06188 High & low oil content 10 11.1
ICGV 06420 × SunOleic 95R* O/L ratio 13 14.4
Intraspecific marker-assisted backcrossing (MABC) populations
ICGV 91114 × GPBD 4 Rust resistance 15 16.7
JL 24 × GPBD 4 Rust resistance 17 18.9
ICGV 03042 × SunOleic 95R O/L ratio 12 13.3
ICGV 02411 × SunOleic 95R O/L ratio 15 16.7
ICGV 05141 × SunOleic 95R O/L ratio 12 13.3
ICGV 05100 × SunOleic 95R O/L ratio 10 11.1
Significant outcome
Acknowledgements
GKAMs based polymorphisms in some
segregating populations
Graphical representation showing global
coverage of reference set in peanut
hypogaea
Cl I