Marker Assisted Breeding in Groundnut – need to assess cost effectiveness

1. Marker Assisted Breeding in Groundnut – need to assess cost effectiveness JanilaPasupuleti Principal Scientist (Groundnut Breeding) & Cluster of Activity Leader of ‘Breeding Pipelines’ of CRP-GLDC International Crops Research Institute for Semi-Arid Tropics (ICRISAT) Hyderabad – 502324 Acknowledgements to the researchers who have contributed to the work reported in presentation ICAR-DGR: Radhakrishnan, Bera, Rathnakumar, Thirumalaiswamy, Mishra JAU – KL Dobariya MPKV – Deshmuk, SudamaPatil PJTSAU – Nagesh Kumar TNAU – Manivannan, Premalatha, Sundaravadana ANGRAU – R Vasanthi, KS Naik, Vemana UAS-D: HL Nadaf, ICRISAT: Murali, Surendra, Sunil, Manish, Rajeev, Hari, Nigam

2. The presentation discusses about… • Current MAB breeding workflow using SNPs • MAB to develop High oleic groundnut varieties • Process innovations that resulted in high rate of genetic gain • MAB to successfully combining early maturity with foliar fungal disease • Development, validation and verification of SNPs • Logistics, Reliability, Cost-effectively of MAB

3. Breeding work flows using MAB using SNPs High Throughput Genotyping Platform (HTGP) @ 1.5 USD per sample for genotyping including DNA isolation Select parents and design hybridization nursery Hybridization F1 ::::::::::: Confirm F1 hybridity Use markers for resistance to rust, LLS and high oleic in relevant crosses F2 ::::::::::: Phenotype selection from F3 onwards till F6-7 Peanut processing Genotype confirmed plant progeny rows F3 I IIIIII Leaf sample collection Genotyping Plant tagging Decision on advancing, backcrossing Genotyping data

4. High oleic groundnut lines developed in India for the first time through partnerships • First high oleic trail in National Testing in India with 16 high oleic lines (ca. 80% oleic acid content) and O/L ratio of 16-41. • The national testing underway at locations High Oleic lines ICRISAT, DGR and JAU team at MLT of high oleic trial at Junagadh, Nov 2017 GC estimation done at RK Labs, Gujarat

5. Agronomic performance of ‘High Oleic’ lines Agronomic performance of high oleic lines during Rainy 2016 at the respective location of testing

6. Process innovations in breeding and testing pipelines that resulted in development of high oleic lines in 6 years Early generation testing target sites enabled fixing of superior allele combinations that contribute to agronomic performance Early generation testing Rapid generation advancement NIRS Phenotyping Genotyping Recycling of elite parents The fixed lines in F4 and F5 generation with high oleic acid and superior agronomy were recycled as parent to enhance genetic gain

7. Allele specific markers developed at University of Georgia, USA were validated and optimized for MAB

8. Robust, cost-effective and non-destructive seed quality assessment using NIRS Calibration equation for estimating different quality traits in whole groundnut kernels using NIRS NIRS machine and absorption spectrum

9. Rapid generation advancement Rapid generation advancement allowed to take 3 cycle per year in place of 2 cycles per year contributing to enhanced rate of genetic gain

10. Combine early maturity and foliar fungal diseases resistance enabled by MAB First ever NIL trail at National Level constituted in India TAG 24 TAG 24 + QTL GPBD 4

11. Multi-location testing in 2015 • 3 popular varieties improved for disease resistance • TAG 24, JL 24 and ICGV 91114 • MLT in 7 locations conducted in 2015 rainy season Pod and kernel features of selected Introgression lines at UAS-Dharwad Aliyarnagar, Tamil Nadu MLT at Jalgoan, Maharashtra MLT sites, 2015 rainy season

12. Resistance from Arachis cardenasii A. hypogaea (AABB) x A. Cardenasii (AA) (resistance to foliar fungal diseases) KRG 1 x ICGV 86855 (AABB) A.hypogaea subsp. fastigiataA. hypogaea subsp. hypogaea var. vulgaris (Spanish bunch) var. hypogaea(Virginia) Early maturing, local cultivar, Interspecific derivative resistant to rust and susceptible to foliar diseases late leaf spot developed at ICRISAT, Patancheru ` GPBD 4

13. SNP markers development, validation and verification Plant material: A panel of 94 genotypes consisting introgression lines, advanced breeding lines, F1s, susceptible and resistant parental lines for rust and LLS were used Moderately good SNP call Uncallable Ideal SNP call • Features of snpAH0004 • Clear differentiation of target allele in a clusters • Depicts zygocity of the genotype • Features of snpAH0003 • Target alleles are scattered but represents the clusters • Depicts zygocity of the genotype snpAH0008 Uncallable

14. Selected SNPs used for high throughput genotyping *NBS-LRR: nucleotide-binding site (NBS) and leucine-rich repeat

15. Considerations before we deploy MAB in breeding workflows SNPs for high oleic trait are 90% reliable, so they are cost-effective and can be used in breeding workflows to optimize resources and time Did we miss to phenotype at right stage for the early maturing plants/progenies? Is MAB Cost-effective? Are the markers reliable? Logistics? Lessons learnt from the MAB work for foliar fungal disease resistance - selections based on phenotype were largely based on disease scores at 90 and 105 days while the early maturity duration is expected to be 90-100 days possibly missing to select the early lines as they have higher scores at 90 & 105 compared to late maturing. Thus, disease score for early maturing lines should be based on 80/85 days.

16. Logistics to deploy MAB is critical • Plant tagging • Leaf sample collection, dispatch • Genotype data on time – turnover time • Go to the selected plant and harvest it • Decision support tool like GOBII/BMS • Human resources for above Breeding Management System Data capturing devices, barcode labels

17. Assessing reliability- Phenotyping of individual F3 plants progenies of positive plants selected in F2 through SNP genotyping

18. Cost effectiveness Generation wise cost involved in genotypic + phenotypic selection and phenotypic selection alone. Note – The cost of maintenance and evaluation of single plant progenies will be more compare to generation advancement through single seed decent (SSD) and then phenotypic selection can be performed @15-20% intensity in F5.

19. MAB vs Single seed decent + phenotyping MAB + phenotyping SSD+ phenotyping MAB approach will become cost-effective if the markers are reliable and when more than one trait is selected

20. Selection accuracy - Foliar fungal disease screening nursery – Infector row + artificial inoculation Infector row – highly susceptible variety, TMV 2 Disease score on 1-9 scale, 1 = no disease, and 9 = 81-100% foliage destroyed (Subrahmanyam et al 1983)

21. Groundnut field day, 28 Feb 2017 Thank you for your attention! Groundnut Network Group-Asia, 30-31 March 2018