1. Advances in breeding and genetics to improve carotenoids content in cassava roots. International Center for Tropical Agriculture (CIAT). Cali, Colombia

2. Why Cassava A basic staple where both poverty and malnutrition are widespread 70 million people rely on cassava for basic sustenance. Cassava grows in poor marginal soils, where other crops will fail.

3. Why CIAT Located in the center of diversity for the crop: access to in situ germplasm. Holds the largest ex-situ cassava germplasm collection >6,000 accessions. Well-established cassava breeding and genetics programs, and supporting lab facilities.

4. Sampling and processing protocols Pre-selection based on NIRS Genetics of carotenoids Genetic progress Next steps: the pathway to impact 

5. Two challenges of root sampling and processing procedures for carotenoids: a)Variation among roots from the same plant and/or roots from different plants within the same genotype (Ortiz et al., 2011). b) In some cases a drastic variation in levels of pigmentation within a root (following slides). This section describes solutions that have been implemented to overcome some of the problems listed above, and alternative approaches to quantify carotenoids in fresh roots of cassava. Some key background work on protocols:

6. Variation of levels of pigmentation within the root

7. Source: Peter Kulakow (IITA)

8. Addressing the issue of root to root variation Former standard procedure: only one root per plant was taken Beginning in 2011: three roots per plant used in carotenoids quantification. Uniform homogenized subsamples taken as follows: a.Two capsules for Near Infrared Spectroscopy (NIRs) screening b.Two samples (≈ 80g and 30g) for dry matter content estimation c.One sample (≈ 100g) for chromameter reading d.One sample (5g) for carotenoid extraction and quantification in spectrophotometer and HPLC

9. Food processor used to grind the roots rather than chopping them

10. Examples of the texture in ground root samples

11. Root sample ground, not chopped Minolta Chromameter CR 410

12. Sampling and processing protocols Analysis & pre-selection based on NIRS Genetics of carotenoids Genetic progress Next steps: the pathway to impact 

13. Scatter plot of total carotenoids NIRS predicted values vs. laboratory values (HPLC and spectrophotometer).

14. Scatter plot of β-carotene NIRS predicted values (based on equations developed from 2009-2011 data) vs. laboratory values (from 2012 nursery)

15. Scatter plot of Dry Matter Content NIRS predicted values (from equations developed using 2009-2011 data) vs. laboratory values (from 2012 nursery)

16. Sampling and processing protocols Analysis & pre-selection based on NIRS Genetics of carotenoids Genetic progress Next steps: the pathway to impact 

17. The Molecular Genetics Approach -- Requires: Understanding of the factors affecting high β-carotene accumulation. Understanding of the β-carotene biosynthetic pathway. A good segregating mapping population (F1 vs. Fn). Large number of molecular markers (e.g. SNPs) Good field design. A high-fidelity phenotyping system.

18. Carotene biosynthetic pathway isopentenyl diphosphate

19. Segregation for beta carotene and its building blocks in an F2 population

20. Carotenoid distribution in GM373X Carotenoid Gained Carotenoid Potential Potential of intermediate products that are being retained in the pathway (not converted to beta carotene)

21. Carotenoid distribution in GM373X Carotenoid Gained Carotenoid Potential Potential contributions of carotenoids not being converted to pro-vitamin A (degraded)

22. Carotenoid distribution in GM373X Carotenoid Gained Carotenoid Potential Unknown Carotenoids

23. Identification of unknown carotenoids

24. Molecular Genetics Generate high density markers (SSRs and SNPs) Build a consensus genetic map. Conduct statistical association between trait values and the genotypes of marker loci Evaluate changes at the DNA sequence level on genes involved in the carotenoid that may explain high β- carotene varietal improvement (MePSY2 SNP-AC) 1. 1 Welsch, R. et al. Provitamin A Accumulation in Cassava (Manihot esculenta) Roots Driven by a Single Nucleotide Polymorphism in a Phytoene Synthase Gene. The Plant Cell Online 22, 3348-3356, doi:10.1105/tpc.110.077560 (2010).

25. Conclusions from genetics studies Potential both to promote synthesis of beta carotene and stop the degradation Fully characterizing beta carotene biosynthesis pathway to maximize genetic gains Explored one mutation associated with the color trait. Yellow color determined by more than one gene.

26. Sampling and processing protocols Analysis & pre-selection based on NIRS Genetics of carotenoids Genetic progress Next steps: the pathway to impact 

27. high-carotenoids progenitors crossed Seed germinated, F1 plants evaluated at 11 MAP Visual selection in the field. Pre-selection by NIRS. Selection based on total carot. content and total beta carotene Planting of a new crossing nursery RAPID CYCLING RECURRENT SELECTION (3-year cycle) Clonal evaluation trial Preliminary yield trial Advanced yield trial Regional trial IN PALMIRA TO ACID SOIL SAVANNAS FOR SED AND CBB

28. Dry Matter % Total carot. (spectroph.) Total carot. (HPLC) Total β- carotene Total carot. (DW basis) Y EAR OF ORIGINAL NURSERY 2004357.88.25.325 2005389.29.65.526 2006367.57.34.721 20073710.310.97.230 20083710.410.96.230 2009A3811.812.47.532 2009B3913.013.88.636 A GE OF PLANTS SAMPLED (MAP) 8389.510.06.526 93810.411.17.129 103810.610.76.728 113510.110.55.830 Nutritional traits across years and plant ages

29. Human consumption: Results of evaluation nurseries for high-carotenoids roots 45 40 35 30 Evolution of dry matter content Evolution of total carotenoids content Total carotenoids content (μg/g FW) Dry matter content (%) Year

30. DM Content Total carot. (spectro.) Total carot. (HPLC) Total β-carotene Total carot. (DW basis) Across Locs0.490.820.900.542.03 Uni. Nac.0.130.720.940.642.47 CIAT0.660.840.860.481.76 Regression for carotenes and carotenoids on year of selection (Independent variable is year of original nursery) Results indicate that an indirect effect of selection for high-carotenoids content was an increase in DMC !!!

31. Fresh root yield Harvest Index Dry matter content Dry matter yield Plant type score (t/ha)(0-1)(%)(t/ha)(1-5) Data from 46 selected genotypes Max 640.7442244.0 Min 230.373291.0 Mean 400.5136142.8 Data from 170 genotypes evaluated Max 640.7442245.0 Min 2.20.122111.0 Mean 260.433593.3 Clonal Evaluation Trial Results, 2011/12 (First step in the selection for agronomic performance; based on single row plots with 6-8 plants, no replications)

32. Evaluation Trials, Palmira, 2012 Clonal Evaluation Trials Planted May 2012 426 entries Planted August 2012 452 entries Preliminary Yield Trials Planted August 2012 60 entries Advanced Yield Trials Planted August 2012 30 entries

33. Results of evaluations for disease resistance in the acid soil savannas (Materials in preliminary and advanced trials, Palmira) Disease score, 1= Excellent; 5= Very poor Super Elongation Disease (SED) = 2.1 1.0 5.0 Cassava Bacterial Blight (CBB) = 1.0 1.0 3.0 Average Minimum Maximum

34. Sampling and processing protocols Analysis & pre-selection based on NIRS Genetics of carotenoids Genetic progress Next steps: the pathway to impact 

35. Select high performance materials in multi-location yield trials Tentative Partners: Corpoica (Colombia) Prepare pathogen-free in-vitro materials for international shipment CIAT GRU Plant Health Laboratory Send selected clones to Haiti for recovery from in vitro culture and multiplication, and testing Tentative partners: Catholic Relief Services Processing trials and acceptability studies; studies on gender differentiation Tentative partners: Catholic Relief Services; CRP 3.4 (Roots, Tubers and Bananas)

36. Ortiz, D., T. Sánchez, N. Morante, H. Ceballos, H. Pachón, M.C. Duque, A.L. Chávez, and A.F. Escobar (2011). Sampling strategies for proper quantification of carotenoids content in cassava breeding. Journal of Plant Breeding and Crop Science 3(1):14-23. Morillo-C., A. C., Y. Morillo-C., M. Fregene, H. Ramirez, A.L. Chávez, T. Sánchez, N. Morante and H. Ceballos-L. (2011). Diversidad genética y contenido de carotenos totales en accesiones del germoplasma de yuca (Manihot esculenta Crantz). Acta Agronómica 60(2): 97-107. Ceballos, H., J. Luna, A.F. Escobar, J.C. Pérez, D. Ortiz, T. Sánchez, H. Pachón and D. Dufour (2012). Spatial distribution of dry matter in yellow fleshed cassava roots and its influence on carotenoids retention upon boiling. Food Research International (45:52-59). Morillo-C., Y., T. Sánchez, N. Morante, A.L. Chávez, A.C. Morillo-C., A. Bolaños, and H. Ceballos (2012). Estudio preliminar de herencia del contenido de carotenoides en raíces de poblaciones segregantes de yuca (Manihot esculenta Crantz). Acta Agronómica 61(3):253-264. Recent publications:

37. Contributors CIAT’s breeding team (Hernan Ceballos, Fernando Calle and Nelson Morante) CIAT’s starch quality lab (Dominique Dufour, Teresa Sanchez, Monica Pizarro) CIAT’s nutritional lab (Darwin Ortiz, Moralba Dominguez) CIAT’s cassava genetics lab (Luis Augusto Bececerra, Tatiana Ovalle, Adriana Alzate) CIARAD collaboration (Fabricio Davrieux )