Diseases of cacao in Colombia: What we know and what we need to know.

Transcription

1 Diseases of cacao in Colombia: What we know and what we need to know. Bryan A. Bailey a, Shahin S. Ali a, Mary D. Strem a, Alina Campbell b, Osman GuAerrez b, Dapeng Zhang a, Lyndel W. Meinhardt a a Sustainable Perennial Crops Laboratory, USDA-Agricultural Research Service, Beltsville, MD, USA b Subtropical HorAcultural Research StaAon, USDA-Agricultural Research Service, Miami FL, USA

2 (A, B, C) Biotrophic Mr Mycelia from malformed green pods (3) (D,E) Necrotrophic Mr mycelia from necroac sporulaang pods (4) (F) Meiophore? from sporulaang pod (4) A C B D 3 4 E F

3 The pathogen occasionally infects and causes disease on even highly tolerant clones. How? CATIE CATIE 1 CATIE CATIE 1 CATIE Pound 7 Pound 7 R4 R4 Jayne Crozier (CABI) and Wilbert Philips (CATIE)

4 Log 1 of Mr Actin (%TcActin) Log 1 of MrP45(%MrActin) CATIE R4 (T) CATIE R7 (T) CATIE 1 (S) POUND 7 (S) UF273 (T)

5 So, the pathogen is altering its gene expression pa^ern during infecaon of tolerant clones. What is happening to the plant s gene expression? What responses does the pathogen elicit from the host when causing disease in a tolerant clone?

6 Figure 2. Shift in the number of differentially expressed gens among key biological processes involved in disease response between tolerant and susceptible Theobroma cacao clones in response to Moniliophthora roreri infection in pods. Differentially expressed genes were identified using RNA-Seq analysis between two tolerant clone CATIE-R4 and CATIE-R7 and two susceptible clones CATIE-1 and Pound-7.

7 The M. roreri geneac diversity in Costa Rica is very narrow. How does this compare to other countries? Why is this an important quesaon?

8 Combination of RNAseq and SNP nanofluidic array reveals the center of genetic diversity of cacao pathogen Moniliophthora roreri in the upper Magdalena Valley of Colombia and its clonality. Wilbert Philips (CATIE) The overview of the SNP mining strategy from M. roreri RNASeq libraries Genetic relationships based on 88 SNP markers among 172 M. roreri isolates collected from frosty pod rot affected areas of South and Central America Ali et al., Fron.ers in Microbiology 215, 6:85.

9 Moniliophthora roreri SNP Geographical distributions of M. roreri isolates collected from frosty pod rot affected areas of South and Central America and their relation. Ali et al., Fron.ers in Microbiology 215, 6:85.

10 Black pod Phytophthora palmivora, P. megakarya Phytophthora Species Causing Black Pod Rot on Cacao

11 P. megakarya and black pod in Africa Ø P. megakarya was first identified in Nigeria in 1979 and by 1981 became the predominant. Ø In recent years, P. megakarya seems to have displaced P. palmivora from Cameroon and Nigeria. The Ghana situation Ø Until the mid 198s, black pod disease was known to be caused by P. palmivora only causing % pod loss. Ø From 1985, pod loss due to black pod increased to 6-1% in the infected areas. Ø In the year 212 it lost more than 2, MT of cacao beans (25% of annual output) due to black pod. P. megakarya P. palmivora Difference in black pod lesions caused by P. megakarya and P. palmivora under similar conditions Ishmael Amoako-A^ah, Andrews Y. Akrofi (CRIG) Ali et al., Plant Pathology 216, /ppa.12496

12 P. Palmivora Cld. 4 Ivory Cost 1324, 25, WR BAR AR , ER , , CR 24 NR GA Phytophthora palmivora ,18,,22 131,2,5, 6,9,14,16,17,19, ,7,11, 93 12,13,21,23,36 W Phytophthora megakarya VR N S E Togo Molecular phylogenetic analysis of Phytophthora isolates collected from infected cacao pods from West Africa, Central and South America Geographical distributions of Phytophthora megakarya and P. palmivora isolates causing black pod of cacao in Ghana.

13 Comparative genomics of Phytophthora megakarya and P. palmivora Thanks to all our collaborators Brett Tyler, Brent Kronmiller and Mark Guiltinan David Lary Danyu Shen Funding source Other collaborators 1. Cocoa Research Institute of Ghana, Akim New-Tafo, Ghana 2. Cocoa Research Centre, the University of the West Indies, St Augustine, Trinidad and Tobago 3. Cocoa Research Institute of Nigeria, Ibadan, Nigeria 4. Plant Pathology Department, University of Florida, Gainesville, FL, USA 5. Regional Laboratory for Biological and Applied Microbiology, IRAD, Yaoundé, Cameroon 6. CIRAD, UPR 16 Bioagresseurs, Montpellier, France 7. Department of Agriculture and Agroforestry, CATIE, Turrialba, Costa Rica

14 P. megakarya P. palmivora Genome Estimated genome sizes Mb Mb Total Contig length 11,182,312 17,423,419 Contig numbers 27,143 28,632 CEGMA Completeness (%) GC content 48.92% 48.91% N5 Contig length 6,92 6,456 Scaffold number 24,7 24,815 K-mer analysis Read data 5,233 Mb 8,53 Mb Average read length 9 9 K-mer length Coverage depth K-mer number 4,388,28,112 5,57,947,212 K-mer depth Contig representation 64.58% 59.53% Gene model Gene number 41,992 44,35 Total gene length 42,723,254 45,995,141 Average gene length Average gene density # Number of expressed genes* 14,615,319 Genes with GO annotation 15,431,276 Genes within KEGG pathway 14,789 15,717 Core orthologous genes ± 15,88 15,88 Genes with unknown functions/hypothetical protein 27,133 22,28 # CDS bases/total genome bases * Only gene models with 1 reads, either in mycelia, zoospore or in planta are reported. Gene models with E<1-4 for BLASTn against Uniport Gene Ontology database. ± Core orthologous were estimated based on bidirectional best BLASTp hits. To be considered as ortholog, BLASTp with least 5% of the sequence should align with E-value less than 1e-1. Table 1 Genome assembly and annotation statistics

15 A Class 1 (479 genes) 2 1 Class 2 (2753 genes) Class 3 (181 genes) Class 4 (734 genes) RxLR NPP Pectinase Elicitin CRN EF trna 4s RP Class 5 (994 genes) 6 1 Class 6 (782 genes) 4 Class 7 (1435 genes) 5 Class 8 (3362 genes) P. meg P. pal P. meg P. pal P. meg P. pal P. meg P. pal P. meg P. pal P. meg P. pal P. meg P. pal P. meg P. pal Average read numbers 3 Class 9 (3699 genes) 2 1 Class 13 (732 genes) Class 17 (131 genes) 4 5 Class 1 (225 genes) 1 5 Class 14 (118 genes) 4 2 Class 18 (1451 genes) 12 2 Class 11 (1461 genes) 2 1 Class 15 (3699 genes) Class 19 (681 genes) 25 Class 12 (2239 genes) 5 25 Class 16 (348 genes) 1 5 Class 2 (1271 genes) 12 96% 81% Induced in all Class 21 Class ( genes) Class 22 Class (281 1 genes) Class 23 Class ( genes) Class 24 Class (855 1 genes) B PCA_3 Induced in mycelium & zoospore Induced in zoospore PCA_1-4 Cl-19 Cl-18 Cl-24 Cl-11 Cl-23 Cl-22 Cl-21 Cl-17 Cl-12 Cl-16 Cl-5 Cl-15 Cl-2 Cl-1 Cl-8 Cl-9 Cl-6 Cl-13 Cl-14 Cl-4 Cl-2 Cl-3 Cl-7 Cl PCA_ % of genes in each SMO class Induced in zoospore & in planta Induced in in planta Self-organizing map (SOM) classification of P. megakarya and P. palmivora gene models based on the RNA-Seq count data and their relationship. 6 4 Differential distributions of gene models among the 24 self-organizing map (SOM) classes for different gene families.

16 Basic differences in the biology of P. megakarya and P. palmivora.

17 P. megakarya P. palmivora

18 Breeders are working on a moving playing field where the pathogens they are trying to manage and the geneac diversity within those pathogens are always changing.

19 Ivory Cost 1324, 25, WR BAR AR , ER , , CR 24 NR GA Phytophthora megakarya Phytophthora palmivora 1315,18,,22 131,2,5, 6,9,14,16,17,19, ,7,11, 12,13,21,23 93,36 W VR N S E Togo We need to know the geneac diversity of all major pathogens of cacao in Colombia and the region relaave to the areas where germplasm selecaon and breeding is being carried out. Imagine figures like those above detailing the diversity of Moniliophthora spp., Phytophthora spp., Lasiodiplodia spp., Ceratocys.s spp., etc. overlaid onto the cacao geneac diversity being screened for resistance.

20 Thank You