solGS: A Bioinformatics Solution for Genomic Selection

1. solGS: A Bioinformatics Solution for Genomic Selection Isaak Y Tecle, Naama Menda, Jeremy Edwards, Lukas Mueller

2. Genomic Selection Genotyped Lines Phenotyped & Genotyped Lines Prediction Model Predicted Breeding Values

3. What solGS does… • Builds prediction models • Predicts breeding values • Calculates selection index • Correlation analysis • Interactive data visualization

4. Building a prediction model...3 options

5. http://cassavabase.org/solgs

6. Building a prediction model Option 1: Search using a trait name

15. Estimating breeding values of a selection population Applying the model

18. Building a prediction model Option 2: using a trial as a training population

21. Building a prediction model Option 3: use your own list of clones

24. Build multiple models simultaneously

27. Estimating breeding values of a selection population for multiple traits Applying the models

30. Calculating selection index

33. Statistical method • Ridge regression, mixed-model • rrBLUP(Endelman , Plant Genome (2010)) • Kinship-BLUP • Marker-based realized relationship matrix • Model accuracy • Based on 10-fold cross-validation

34. Database • Chado ND Schema • Co-developed by SGN, GDR, VectorBase and Medicago • Jung et al. Database 2011.

35. To sum up… • Build models • Estimate breeding values • Additional tools: • correlation analysis • selection index • http://cassavabase.org/solgs • Feedback

36. Next... • Incorporate G x E effects • Correlation analyses: phenotype values vs. breeding values, selection indices vs breeding values. • PCA and clustering • Add more prediction methods • Computational speed improvement

37. Thanks to…

38. Cassavabase team

39. Many thanks!! Background image: nextgencassava.org