1. iMAS 1.9 – An Integrated Decision Support System for MAB Abhishek Rathore 1, Mallikarjuna, G. 1, Manna, S. 1, Hoisington, D 1, McLaren, G 2, Davenport, G 2, Crossa, J 3 1 International Crops Research Institute for the Semi Arid Tropics, Hyderabad, India 2 International Rice Research Institute, Manila, Philippines 3 International Wheat and Maize Improvement Centre, Mexico Abhishek Rathore 1, Mallikarjuna, G. 1, Manna, S. 1, Hoisington, D 1, McLaren, G 2, Davenport, G 2, Crossa, J 3 1 International Crops Research Institute for the Semi Arid Tropics, Hyderabad, India 2 International Rice Research Institute, Manila, Philippines 3 International Wheat and Maize Improvement Centre, Mexico Contact:a.rathore@cgiar.org Click to Download iMAS

2. MABC -Marker Assisted Back Cross QTL-Quantitative Trait Loci MAB-Marker Assisted Breeding BLUP-Best Linear Unbiased Prediction Few Acronyms Used

3. iMAS iMAS is a single unified computing and decision support platform Facilitate identification of trait-linked markers for use in marker-aided selection and breeding –Integrating and implementing the required computational processes, –Providing guidelines for correct application and interpretation of computational tools

4. A Standalone system : Keeping NARS needs in mind Pipelining freely available quality software / statistical tools Biometrical Analysis –IRRISTAT (G McLaren, IRRI, Philippines ) Linkage and QTL Mapping –GMendel (JL Holloway & SJ Knapp, Oregon State University, Oregon, USA) –PlabQTL (HF Utz & AE Melchinger, University of Hohenheim, Germany) iMAS

5. Visualization of Linkage and QTL Map Linkage Map –MapChart (RE Voorrips, Plant Research International, The Netherlands) Linkage Map & QTL –GGT (R van Berloo, Laboratory of Plant Breeding, Wageningen University, The Netherlands) –FLAPJACK(Iain Milne, Micha Bayer, Paul Shaw, Linda Cardle and David Marshal, SCRI, Scotland) MABC Sample Size PopMin (F Hospital, Ferme du Moulon, France) QUGene (Scott Chapman, The University of Queensland, Australia) ( Experimental )

6. iMAS Advantages Genotypic and phenotypic data analysis involves a number of different software All have different input data format requirements Manual input file preparation –Time-consuming –Error-prone Which some time results in: –Use of inappropriate methods –Incorrect use of appropriate methods

7. Phenotypic Data Genotypic Data iMAS

8. Biometrical AnalysisLinkage Map BuildingQTL AnalysisVisualization MABC Sample Size Phenotypic Data Genotypic Data

9. iMAS currently implements a mapping-population-based approach to identify trait-linked markers The system consists of six modules - Data Validation module - Phenotyping module - Linkage Map Building module - QTL Analysis module - Genome / QTL Display module - MABC Sample Size module iMAS - Modules

10. The Data Validation module provides some facilities to 1.Check basic background information on your data files 2.Gives an opportunity to correct your data files if necessary, before starting to use iMAS. iMAS - Data Validation

11. Two sub-modules: Experimental Design Biometric Analysis The Experimental Design sub-module helps you select and generate a suitable experimental design for phenotyping The Biometric Analysis sub-module helps you perform appropriate biometric analysis of resulting phenotyping data to obtain accurate and precise average phenotypic values iMAS – Phenotyping

12. The Linkage Map Building module generates a linkage map. The QTL Analysis module undertakes QTL analysis based on a linkage map and the average phenotypic values. The required linkage map and the average phenotypic values could either be obtained from inside iMAS or from some other software outside iMAS iMAS – Linkage & QTL Mapping

13. The Genome Display module facilitates graphical display of genomic content of progenies The MABC Sample Size module helps determine the optimal sample size for marker-aided backcrossing iMAS – Genome Display

14. Data Validation Genotypic Phenotypic Analysis Mixed Model Biometrical Analysis

15. Data Validation - Phenotypic Biometrical Analysis

16. Data Validation - Phenotypic Biometrical Analysis

17. Data Validation - Phenotypic Biometrical Analysis

18. Data Validation - Genotypic Biometrical Analysis

19. Data Validation - Genotypic Biometrical Analysis

20. Analysis - BLUPS Biometrical Analysis

21. Analysis - BLUPS Biometrical Analysis

22. Analysis - BLUPS Biometrical Analysis

23. Analysis - BLUPS Biometrical Analysis

24. Analysis - BLUPS Biometrical Analysis

25. Linkage Map - GMendel

28. QTL Mapping PLABQTL By default Identified QTLs are visualized in Ghost View However, for more appealing visualization GGT and FLAPJACK can be used from within iMAS By default Identified QTLs are visualized in Ghost View However, for more appealing visualization GGT and FLAPJACK can be used from within iMAS

29. iMAS - Visualization GGT

31. iMAS - Visualization FLAPJACK

32. Thanks