Association Mapping Identifies QTLs Underlying Cassava Brown Streak Disease

Resistance

Kayondo S.I , Dunia P.D.C., Ozimati A.A, Lozano R,Osingada F., Baguma Y., Vernon Gracen V.E, Offei S.K,

Kawuki R.S., Jannink J.L

The First World Congress on Root and Tuber Crops

CBSD: A Thread to Africa Session

Guangxi, Nanning China

Jan 18th – 24th 2016

• Considerable genome diversity

within isolates of a species

CBSV>UCBSV

Cassava Brown Streak Disease….

• Two monopartite +ssRNA

viruses of genus Ipomovirus(Family Potyviridae)

• Two major strains reported

•Uganda cassava Brown

Streak Virus

•Cassava brown streak Virus

Winter et. al.

CBSD: A threat….

Herrera Campo et al., (2011) Food Security, 3:329-345

CBSD: Successful colonization….

• Re-emerges in the SSA region in 2001

• Resistance sources un-adapted & rare but could be explored.

• Reports of Quantitative (Multi-genic) inheritance of CBSD resistance

• Phenotyping protocol still challenging

Virus – Plant relations……Plant resistance

Forms

Virus

Resistance

Disease

Resistance

Experiences with Molecular markers in cassava

Breeding Material

QTL mappingFine Mapping

& Gene Discovery

Recurrent & Genomic selection

QTL detection in bi-parental

crosses

Only allelic variation present in the two parents captured

Best suited for traits with high heritability

Complex hybrids from 2 heterozygous parents

Bi-parental

mapping

QTL studies in cassava…..

Trait / study Markers used Key findings

CBB (Jorge et al. 1999)

68 RFLPs 120QTLs (8 in female + 4 in male)

CMD

(Akano et al. 2002)

186 SSRs 1 SSR linked to a QTL (SSRY28)

Productivity(Fregene et al. 1997)

250 markers 114 QTLs

CBB(Wydra et al. 2004)

63 SSRs 11 QTLs identified

CNP and dry matter(Kizito et al. 2007)

110 SSRs 2 QTLs for CNP & 6 QTLs for DMC

Anthracnose 53 RAPDs 2 RAPDs (single Dominant gene)

CBSD(Kanju et al.)

500 SSRs 3 Markers reported; EST-SSRY75, NS149 &

SSR83

Ferguson et al. (2012) Theor. Appl. Genet. 124:685-695

Are Association approaches complimentary?

Allelic variation in a breeders’ population captured

Most current target traits are multi-genic Difficult to get

statistical power to detect

LD or association mapping by-passes the need for bi-parental mapping populations

Association

mapping

Breeding Material

QTL MappingFine Mapping

& Gene Discovery

Recurrent & Genomic selection

Identify genetic variants explain differences in phenotype among individuals in a study population

Association mapping data sets• 429 accessions

• Phenotyped 3 years (3trials)

• Based on foliar and root phenotypes

• 3MAP, 6MAP, 9MAP, 12MAP

• Infector rows used to augment disease pressure (TME 204)

• Standard and local checks

Year NaCRRI Kasese Lira

2012 308 - -

2013 429 429 429

2014 429 429 429

Score Root Symptom Description Pictorial

1 No symptoms on storage roots

2less than 5% of storage root

tissue is necrotic

35-10% of storage root tissue is

necrotic

4

10-50% of storage root tissue is

necrotic

5More than 75% of storage root

tissue is necrotic

CBSD Root Severity Scoring Scale

Association mapping data sets

• Genotyped 429 using the GBS pipeline

• ≈ 36,000 SNPs at a 0.05% MAF

• Analysis• Used Gapit package under R

Population structure & Kinship?

CBSD root Incidence

What do GWAS results say….CBSD root Severity

CBSD _3MAP Severity

What do GWAS results say….

CBSD_3MAP Incidence

What do GWAS results say….

CBSD_6MAP Incidence

CBSD _6MAP Severity

Top ten SNPs…..

Genomic predictions……

Allelic variation in a breeders’ population captured

Breeding success measured as prediction

accuraciesMarker effects

estimated simultaneously

Shortening the breeding cycle

Breeding Material

QTL mappingFine Mapping

& Gene Discovery

Recurrent & Genomic selection

GWAS meets GS

Genomic Prediction for CBSD….

Summary….…

• We identified SNPs with strong association to CBSD resistance on chromosomes; 5 and 11

• Significant SNPs could be weighted for genome wide predictions for better accuracies in GS.

• Fine mapping for gene discovery underway• Identify and validate key genes involved in resistant

response to CBSD

• Further evaluation of virus resistance based on virus titres could be complimentary

• Stability of resistance across environments is being explored.

Project Members / Support

• NEXTGEN/NaCRRI.

• Dr. Baguma Yona

• Dr. Kawuuki Robert

• Dr. Titus Alicai

• Osingada F.

• Mukiibi D.

• Adiga. G.

• Kyaligonza V.

• Kaweesi T.

• Majara C.

• Orone J.

• WACCI• Prof. Vernon G.

• Prof. Offei Samuel

• Prof. Tongoona P.

• Dr. Dzidzienyo D.

• Cornell University• Dr. Hamblin M. T.

(RIP)

• Dr. Hale Tufan

• Dr. Jean-Luc J.

• Dr. Dunia P.D.C

• Dr. Wolfe. M

• Ozimati Alfred

• Lozano R.

Thanks for listening