1. Unlocking breeding potential of African
crops through data management an
example with CASSAVABASE
Guillaume Bauchet
Plant and Animal Genome Conference
San Diego January 2016
gjb99@cornell.edu

2. OUTLINE
http://nextgencassava.org/
CASSAVABASE , What for?
CASSAVABASE , a user perspective
CASSAVABASE , search, manage, analyze
CASSAVABASE , a view

3. The Central data store for NEXTGEN CASSAVA :
Genomic selection in African cassava breeding programs
http://nextgencassava.org/

4. NEXTGEN CASSAVA

5. What are the major challenges?

6. ● Multi trait and Multi breeding environments for cassava
phenotypic data collection
● Large scale production of genomic data using GBS
● Integrate Genomic Selection tool via web interface
What are the major challenges?
● Make the most of this resource for cassava breeders:
speed up the analysis and decision making

7. What are the needs?
● Search various data types (phenotypes and germplasm) in a large datastore
● Manage data and daily breeding activity through comprehensive interface
● Analyse and retrieve data for genomic assisted breeding
What are our solutions?
● Integrate phenomic & genomic data with breeding tools
● Use Perl with the Bio::Chado::Schema and Natural Diversity
module as database architecture
● Retrieve genomic information
● Sequence visualization ● Open source
https://github.com/solgenomics/

8. http://cassavabase.org/

9. New search bar
Navigation bar always visible on top Expandable search box

10. Caroussel

11. New responsive design

12. CASSAVABASE
by numbers
2016: + 80,000 accessions, 2,5 billion genetic observations
2014:
+360 registered users

13. From Phenotype to Genotype to Breeding:
Harvesting the fruits of CASSAVABASE

14. CASSAVABASE, an Office perspective: Search
Search breeding program, location, trial, trait, year, accession

15. CASSAVABASE, a field perspective: Manage Phenotypes
Define phenotypic traits via Cassava
trait dictionaryin CASSAVABASE
Data
collection
via FieldBook
app*
Design trials, barcodes &
field maps
in CASSAVABASE*
Data uploading in
CASSAVABASE
via .xls and .txt file *
*See Alex Ogbonna PAG presentation
“Managing Phenotypic Data through Cassavabase with Fieldbook App”
“
Data analysis in
CASSAVABASE
-Sum. stat
-ANOVA
-BLUP
-GS
In CASSAVABASE

16. Design genotyping
Trial in CASSAVABASE
TASSEL
pipeline
Data filtering
&
imputation
GBS data uploading
In CASSAVABASE
GS Analysis
& Visualization
in
CASSAVABASE
GBS facility @ Cornell
CASSAVABASE, a lab perspective: Manage Genotypes

17. CASSAVABASE an office perspective: Manage
Breeding programs, trial, accession

18. CASSAVABASE : Analyze with SolGS
Phenotypic values Population Structure GEBV vs phenotypes
See Isaak Tecle PAG presentation & poster 342
“solGS: A Web-based Solution for Genomic Selection”
GEBV

19. CASSAVABASE : Analyze with SolGS

20. CASSAVABASE from the Office: Analyze phenotypes
QC to phenotypes
Single trial

21. CASSAVABASE from the Office: Analyze phenotypes
QC to phenotypes
Single trial

22. CASSAVABASE tools: Analyze pedigree

23. CASSAVABASE from the Office: Analyze phenotypes
data_2011_B1
4 6 8 10
r= 0.68
p<0.001
r= 0.66
p<0.001
4 6 8 10 14
r= 0.70
p<0.001
4681012
r= 0.63
p<0.001
46810
data_2011_B2
r= 0.76
p<0.001
r= 0.79
p<0.001
r= 0.73
p<0.001
data_2011_B3
r= 0.76
p<0.001
46810
r= 0.68
p<0.001
4681014
data_2012_B1
r= 0.75
p<0.001
4 6 8 10 12 4 6 8 10 4 6 8 12
46812
data_2012_B2
30 31 32 33 34 35 36 37
-1.5-0.50.51.5
Fitted values
Residuals
Residuals vs Fitted
26
9
15
-2 -1 0 1 2
-1012
Theoretical Quantiles
Standardizedresiduals
Normal Q-Q
26
9
15
30 31 32 33 34 35 36 37
0.00.40.81.2
Fitted values
Standardizedresiduals
Scale-Location
269
15
0.0 0.1 0.2 0.3 0.4 0.5
-2-1012
Leverage
Standardizedresiduals
Cook's distance
Residuals vs Leverage
9
26
15
ANOVA, h2,
BLUP, GxE
QC phenotypes
Multiple trials

24. JBrowse
CASSAVABASE tools: Analyze sequence
Variant
effects
prediction

25. VIGS tool
CASSAVABASE tools: Analyze sequence
BLAST

26. CASSAVABASE, a User perspective: support & interaction

27. CASSAVABASE, a User perspective: support & interaction
-> Provide support on technical issues ( data management)
-> Gather user request for tool improvement and new developments
(pedigree queries, VIGS)
-> 2016: Install Mirror site @ IITA Ibadan, Nigeria
Weekly meetings with users in Africa: Wiki, FB pages & mailing list:

28. CASSAVABASE Upcoming developments
Search: Integrate trait & values in the wizard search
Manage: extract data subset according to their phenotypic
values, conditionnal choices
Analyze: -Phenotypic analysis developments (ANOVA, GxE)
-Pedigree analysis
-Jbrowse: Mutation prediction of genetic variants
-SolGS: Jobs queuing, trial selection improvement

29. Lukas
Mueller
Alex
Ogbonna
Bryan
Ellerbrock
Naama
Menda
Isaak
Tecle
Nick
Morales
AKNOWLEDGEMENTS
Jeremy
Edwards
BMGF
Chiedozie
Egesi
Peter
Kulakow
Robert
Kawuki
Ismail
Rabbi

30. Questions?