The document discusses genotyping work being done on root, tuber and banana crops (RTB) to understand genetic diversity and enhance breeding. It describes genotyping by sequencing (GBS) efforts on banana, cassava, potato, sweet potato and yam accessions. For cassava, over 3,000 African clones were genotyped, revealing population structure. For yams, over 1,500 accessions were genotyped to understand diversity and the relationship to wild relatives. The goals are to enable targeted use of genetic resources for breeding programs.

1. Theme 1 Overview - Unlocking the value and use potential of genetic resources
Nicolas Roux
RTB Annual Meeting, Entebbe
29 September, 2014

2. Introduction – Project Overview
Project Title: Enhancing global RTB productivity through more targeted use of global RTB genetic diversity
3 Components:
1. Genotyping towards conservation and use of RTB genetic resources for breeding – Nicolas Roux
2. High-throughput/high-density phenotyping for characterization of RTB genetic resources – Luis Augusto Becerra
3. Breeding applications for exploiting RTB crop evolution and domestication traits – Luis Augusto Becerra

3. GENOTYPING BY SEQUENCING (GBS)
Component 1

4. Genotyping By Sequencing
Banana
•520 accessions by GBS (Cornell) (including Cv, CWR and hybrids)
•650 accessions by RADseq (BGI)
Cassava
•3,000 cassava Sub-Saharan African clones by GBS (Cornell)
•300 cassava LAC Landraces by RADseq (BGI) analysed out of the 800 acc.
Potato
•96 accessions by GBS (Cornell) (wild ancestors of diploid cultivars)
•170 diploid landraces and 187 derived diploid hybrid progenies
•1,190 tetraploid breeding lines for genome-wide representation of SNPs
Sweet Potato
•~90 F1 plants from a mapping population
Yam
•1,587 accessions by GBS (Cornell) including 810 D. rotundata genotypes + 470 germplasm accessions from the core collection; and 307 breeding lines selected for key target traits (awaiting results)

5. Research Topics
•Understanding genetic diversity and population structure
•Phylogenetic analysis with wild ancestors
•Clonal differentiation
•Gap analysis
•High-density genetic maps
•GWAS: Genome Wide Association Studies
•Bioinformatics

6. Pattern of heterozygosity and allele sharing
 Contribution of wild relatives to cultivated species
 Confirmation on the previous suggestions to treat D. cayenensis as a subspecies of D. rotundata.
Understanding genetic diversity: Yam

7. Understanding genetic diversity:
African cassava
3,000 cassava clones have been
genotyped using GBS
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tmeb 419
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Admixture analysis detected nine subpopulations
(Rabbi et al, in prep)

8. Understanding genetic diversity: potato
170 diploid landraces of Groups Phureja, Stenotomum and Goniocalyx, and 187 derived diploid hybrid progenies of III cycles of recurrent selection were genotyped by GBS
Results: 41,591 and 35,116 SNPs were identified in the diploid landraces and hybrid progenies, respectively, at an allele frequency greater than 5% and with more than 90% data
Objective: Application of Genomic Selection for early prediction of breeding values for improving yield, micronutrient content and Vitamin C in a background of high yielding heterotic hybrids
(Bonierbale et al, in prep)

9. Phylogenetic analysis: wild potatoes
GBS, 151,601 SNPs
Preliminary results:
•RAxML tree
•Using GTR+GAMMA
•100 pseudoreplicates
Genome B
Genome P
Genome A
(Rodriguez et al, in prep)

10.  a wide phenotypic diversity
but little or no genetic diversity with usual molecular markers
Is a high density SNP coverage of the genome able to reveal genetic variations within somaclonal subgroups?
235,425 polymorphic SNPs of 29 African plantains
and ‘plantain-like’
•What consequence on gene expression?
•What implications for plantain improvement?
Clonal differentiation: plantain subgroup
(Perrier et al, in prep)
French Plantain False Horn Plantain Horn Plantain

11. Gap analysis: potato
A) Species richness map
B) Prediction of HPS species
presence for gap filling
(De Haan et al, to be submitted to PLOS One)

12. Gap analysis: banana
Using RADseq to target Musa collecting within a triangular area of Indonesia (MusaNet)
AAB
BB
ABB
AA/AAA
M. acuminata
(Triangle Banana Exploration Reports , 2014)

13. High-density genetic map: cassava
Using GBS to rapidly discover and genotype thousands of SNP markers in cassava.
These SNPs are used to develop high-density genetic maps for genetic studies and improvement of reference genomes.
High-density cassava map with 6756 SNPs
(Rabbi et al. (2013) Virus Research)
150100500Chromosome Location (cM) 12345678910111213141516171819Genetic map

14. High-density genetic map: banana
Contribution to the production of Musa genome reference sequences
 Through genotyping by sequencing of mapping populations used to assemble the sequenced fragments (scaffolds) in chromosomes
1) Contribution to the improvement of the Musa acuminata reference sequence
(Martin et al. in prep)
2) Contribution to the production of the Musa balbisiana reference sequence
(Jin et al. in prep)
Genetic map
Anchoring
on genetic
map
Chromosomes
Sequence
scaffolds

15. GWAS for domestication: banana/plantain
E. Fondi – CARBAP Wild M. acuminata Calcutta 4
E. Fondi – CARBAP Cultivated AA P. Mas
Selection of samples
Candidate region detection
Candidate gene predictions
Available for distribution and further studies
(Sardos et al. in prep)

16. Bioinformatics: architecture
Next-Generation Sequencing Eclipse Plug-in (NGSEP)
(Duitama et al, NAR, 2014)

17. GBS vs RADseq : preliminary comparison
25,000
Filtering
Mapping & calling
Quality
Trimming
1,700,000
Filtering
Mapping & calling
Quality
Trimming
GBS
RADseq
Raw data (reads) for Musa accessions (2x)
#SNPs
MAF
Missingness
Bi-allelic
Polymorphic
#SNPs

18. Bioinformatics: visualization and interoperability
Diversity tree based on GBS
(linked to passport data)
Details of SNPs along the chromosome of the Musa reference genome
Genes
SNPs
0
0

19. In the pipeline…
•Characterization of chromosome structural variation
•Characterization of somatic mutants, dwarfism
•Genomic Selection for accelerated breeding
•Common RTB Bioinformatics Platform

20. Lessons learned
•Expertise acquired/improved on Next Generation Sequencing technologies
•Need to develop a data management plan (of Terabytes of raw data generated)
•Demanding logistics to analyse samples
•Access to new and unknown material (e.g. Japan, Philippines)
•Large datasets are paving the way to many promising research studies for RTB GR

21. So what…..?
•Theme 1 research lays the foundation for improved use of RTB GR in NextGen breeding – Theme 2
•Increased knowledge on domestication, genepool diversity, clonal diversification, candidates genes ( abiotic and biotic stresses) – Theme 3
•Increased access to characterized material. Distribution of high quality material – Theme 4
•Diversity in production systems – Theme 5
•Gene discovery related to quality traits – Theme 6
•Collaboration strengthened within and between RTB centers and new initiated and genetic, genomics and bioinformatics tools ready to be shared with National partners – Theme 7

22. THANK YOU
Augusto Becerra Lopez-Lavalle
Claudia Perea
Clair Hershey
Joe Tohme
and colleagues
Ranjana Bhattacharjee
Tessema, Gezahegn
Ismail Rabbi
Rony Swennen
and colleagues
Julie Sardos
Rachel Chase
Mathieu Rouard
Nicolas Roux
and colleagues
Angelique D’Hont
Jean Pierre Horry
Xavier Perrier
Frank Christophe Baurens
and colleagues
Stef de Haan
Flor Rodriguez
Awais Khan
Merideth Bonierbale
and colleagues