Donald Livingstone

The genome sequence of the most widely cultivated cacao type and its use to identify candidate genes regulating pod color

BackgroundTheobroma cacao L. cultivar Matina 1-6 belongs to the most cultivated cacao type. The availability of its genome sequence and methods for identifying genes responsible for important cacao traits will aid cacao researchers and breeders.ResultsWe describe the sequencing and assembly of the genome of Theobroma cacao L. cultivar Matina1-6. The genome of the Matina 1-6 cultivar is 445 Mbp, which is significantly larger than a sequenced Criollo cultivar, and more typical of other cultivars. The chromosome-scale assembly, version 1.1, contains 711 scaffolds covering 346.0 Mbp, with a contig N50 of 84.4 kbp, a scaffold N50 of 34.4 Mbp, and an evidence-based gene set of 29,408 loci. Version 1.1 has 10x the scaffold N50 and 4x the contig N50 as Criollo, and includes 111 Mb more anchored sequence. The version 1.1 assembly has 4.4% gap sequence, while Criollo has 10.9%. Through a combination of haplotype, association mapping and gene expression analyses, we leverage this robust reference genome to identify a promising candidate gene responsible for pod color variation. We demonstrate that green/red pod color in cacao is likely regulated by the R2R3 MYB transcription factor TcMYB113, homologs of which determine pigmentation in Rosaceae, Solanaceae, and Brassicaceae. One SNP within the target site for a highly conserved trans-acting siRNA in dicots, found within TcMYB113, seems to affect transcript levels of this gene and therefore pod color variation.ConclusionsWe report a high-quality sequence and annotation of Theobroma cacao L. and demonstrate its utility in identifying candidate genes regulating traits.

Development of single nucleotide polymorphism markers in Theobroma cacao and comparison to simple sequence repeat markers for genotyping of Cameroon clones

Single nucleotide polymorphism (SNP) markers are increasingly being used in crop breeding programs, slowly replacing simple sequence repeats (SSR) and other markers. SNPs provide many benefits over SSRs, including ease of analysis and unambiguous results across various platforms. We have identified and mapped SNP markers in the tropical tree crop Theobroma cacao, and here we compare SNPs to SSRs for the purpose of determining off-types in clonal collections. Clones are used as parents in breeding programs and the presence of mislabeled clones (off-types) can lead to the propagation of undesired traits and limit genetic gain from selection. Screening was performed on 186 trees representing 19 Theobroma cacao clones from the Institute of Agricultural Research for Development (IRAD) breeding program in Cameroon. Our objectives were to determine the correct clone genotypes and off-types using both SSR and SNP markers. SSR markers that amplify 11 highly polymorphic loci from six linkage groups and 13 SNP markers that amplify eight loci from seven linkage groups were used to genotype the 186 trees and the results from the two different marker types were compared. The SNP assay identified 98% of the off-types found via SSR screening. SNP markers spread across multiple linkage groups may serve as a more cost-effective and reliable method for off-type identification, especially in cacao-producing countries where the equipment necessary for SSR analysis may not be available.

Making a chocolate chip: development and evaluation of a 6K SNP array for Theobroma cacao

Theobroma cacao, the key ingredient in chocolate production, is one of the worlds most important tree fruit crops, with ∼4,000,000 metric tons produced across 50 countries. To move towards gene discovery and marker-assisted breeding in cacao, a single-nucleotide polymorphism (SNP) identification project was undertaken using RNAseq data from 16 diverse cacao cultivars. RNA sequences were aligned to the assembled transcriptome of the cultivar Matina 1-6, and 330,000 SNPs within coding regions were identified. From these SNPs, a subset of 6,000 high-quality SNPs were selected for inclusion on an Illumina Infinium SNP array: the Cacao6kSNP array. Using Cacao6KSNP array data from over 1,000 cacao samples, we demonstrate that our custom array produces a saturated genetic map and can be used to distinguish among even closely related genotypes. Our study enhances and expands the genetic resources available to the cacao research community, and provides the genome-scale set of tools that are critical for advancing breeding with molecular markers in an agricultural species with high genetic diversity.

Optimization of a SNP assay for genotyping Theobroma cacao under field conditions

The tropical tree crop Theobroma cacao L. is grown commercially for its beans, which are used in the production of cocoa butter and chocolate. Although the upper Amazon region is the center of origin for cacao, 70% of the world’s supply of cacao beans currently comes from small farms in West Africa. While cacao breeding programs in producer nations are the source of improved planting material, modern marker-based breeding is difficult to perform due to the lack of genotyping facilities in these countries. While DNA extraction can be routinely performed, the equipment needed to analyze simple sequence repeats (SSRs) is seldom available, forcing the outsourcing of genotyping to foreign laboratories and delaying the breeding process. We describe a 5′ nuclease (TaqMan)-based single nucleotide polymorphism (SNP) assay for genotyping cacao plants under conditions similar to those found in most cacao-producing areas. The assay was tested under field conditions by planting open pollinated seeds of seven pods from four different maternal plants. The resulting 171 seedlings were successfully genotyped with 18 SNP markers representing 12 loci. The ability to use temperature-stable reagents and rapid DNA extraction methods is also explored. Additionally, by examining the seedling genotypes for the SNP markers and 14 additional SSR markers, we investigated whether seeds in a pod are the result of single or multiple pollination events. This simple, effective method of genotyping cacao seedlings in the field should allow for more efficient resource management of seed gardens and is currently being implemented in Ghana.

Evaluating Theobroma grandiflorum for comparative genomic studies with Theobroma cacao

The seeds of Theobroma cacao (cacao) are the source of cocoa, the raw material for the multi-billion dollar chocolate industry. Cacao’s two most important traits are its unique seed storage triglyceride (cocoa butter) and the flavor of its fermented beans (chocolate). The genome of T. cacao is being sequenced, and to expand the utility of the genome sequence to the improvement of cacao, we are evaluating Theobroma grandiflorum, the closest economically important species of Theobroma for its potential use in a comparative genomic study. T. grandiflorum differs from cacao in important agronomic traits such as flavor of the fermented beans, disease resistance to witches’ broom and abscission of mature fruits. By comparing genomic sequences and analyzing viable inter-specific hybrids, we hope to identify the key genes that regulate cacao’s most important traits. We have investigated the utility in T. grandiflorum of three types of markers (microsatellite markers, single-strand conformational polymorphism markers and single nucleotide polymorphism (SNP) markers) developed in cacao. Through sequencing of amplicons of 12 diverse individuals of both cacao and T. grandiflorum, we have identified new intra- and inter-specific SNPs. Two markers which had no overlap of alleles between the species were used to genotype putative inter-specific hybrid seedlings. Sequence conservation was significant and species-specific differences numerous enough to suggest that comparative genomics of T. grandiflorum and T. cacao will be useful in elucidating the genetic differences that lead to a variety of important agronomic trait differences.

iXora: exact haplotype inferencing and trait association.

BackgroundWe address the task of extracting accurate haplotypes from genotype data of individuals of large F1 populations for mapping studies. While methods for inferring parental haplotype assignments on large F1 populations exist in theory, these approaches do not work in practice at high levels of accuracy.ResultsWe have designed iXora (Identifying crossovers and recombining alleles), a robust method for extracting reliable haplotypes of a mapping population, as well as parental haplotypes, that runs in linear time. Each allele in the progeny is assigned not just to a parent, but more precisely to a haplotype inherited from the parent. iXora shows an improvement of at least 15% in accuracy over similar systems in literature. Furthermore, iXora provides an easy-to-use, comprehensive environment for association studies and hypothesis checking in populations of related individuals.ConclusionsiXora provides detailed resolution in parental inheritance, along with the capability of handling very large populations, which allows for accurate haplotype extraction and trait association. iXora is available for non-commercial use from http://researcher.ibm.com/project/3430.

Application of genome wide association and genomic prediction for improvement of cacao productivity and resistance to black and frosty pod diseases

Chocolate is a highly valued and palatable confectionery product. Chocolate is primarily made from the processed seeds of the tree species Theobroma cacao. Cacao cultivation is highly relevant for small-holder farmers throughout the tropics, yet its productivity remains limited by low yields and widespread pathogens. A panel of 148 improved cacao clones was assembled based on productivity and disease resistance, and phenotypic single-tree replicated clonal evaluation was performed for 8 years. Using high-density markers, the diversity of clones was expressed relative to 10 known ancestral cacao populations, and significant effects of ancestry were observed in productivity and disease resistance. Genome-wide association (GWA) was performed, and six markers were significantly associated with frosty pod disease resistance. In addition, genomic selection was performed, and consistent with the observed extensive linkage disequilibrium, high predictive ability was observed at low marker densities for all traits. Finally, quantitative trait locus mapping and differential expression analysis of two cultivars with contrasting disease phenotypes were performed to identify genes underlying frosty pod disease resistance, identifying a significant quantitative trait locus and 35 differentially expressed genes using two independent differential expression analyses. These results indicate that in breeding populations of heterozygous and recently admixed individuals, mapping approaches can be used for low complexity traits like pod color cacao, or in other species single gene disease resistance, however genomic selection for quantitative traits remains highly effective relative to mapping. Our results can help guide the breeding process for sustainable improved cacao productivity.

ARG-based genome-wide analysis of cacao cultivars

BackgroundAncestral recombinations graph (ARG) is a topological structure that captures the relationship between the extant genomic sequences in terms of genetic events including recombinations. IRiS is a system that estimates the ARG on sequences of individuals, at genomic scales, capturing the relationship between these individuals of the species. Recently, this system was used to estimate the ARG of the recombining X Chromosome of a collection of human populations using relatively dense, bi-allelic SNP data.ResultsWhile the ARG is a natural model for capturing the inter-relationship between a single chromosome of the individuals of a species, it is not immediately apparent how the model can utilize whole-genome (across chromosomes) diploid data. Also, the sheer complexity of an ARG structure presents a challenge to graph visualization techniques. In this paper we examine the ARG reconstruction for (1) genome-wide or multiple chromosomes, (2) multi-allelic and (3) extremely sparse data. To aid in the visualization of the results of the reconstructed ARG, we additionally construct a much simplified topology, a classification tree, suggested by the ARG.As the test case, we study the problem of extracting the relationship between populations of Theobroma cacao. The chocolate tree is an outcrossing species in the wild, due to self-incompatibility mechanisms at play. Thus a principled approach to understanding the inter-relationships between the different populations must take the shuffling of the genomic segments into account. The polymorphisms in the test data are short tandem repeats (STR) and are multi-allelic (sometimes as high as 30 distinct possible values at a locus). Each is at a genomic location that is bilaterally transmitted, hence the ARG is a natural model for this data. Another characteristic of this plant data set is that while it is genome-wide, across 10 linkage groups or chromosomes, it is very sparse, i.e., only 96 loci from a genome of approximately 400 megabases. The results are visualized both as MDS plots and as classification trees. To evaluate the accuracy of the ARG approach, we compare the results with those available in literature.ConclusionsWe have extended the ARG model to incorporate genome-wide (ensemble of multiple chromosomes) data in a natural way. We present a simple scheme to implement this in practice. Finally, this is the first time that a plant population data set is being studied by estimating its underlying ARG. We demonstrate an overall precision of 0.92 and an overall recall of 0.93 of the ARG-based classification, with respect to the gold standard. While we have corroborated the classification of the samples with that in literature, this opens the door to other potential studies that can be made on the ARG.

A Larger Chocolate Chip—Development of a 15K Theobroma cacao L. SNP Array to Create High-Density Linkage Maps

[This corrects the article on p. 2008 in vol. 8, PMID: 29259608.].

Genetic Parameters and the Impact of Off-Types for Theobroma cacao L. in a Breeding Program in Brazil

Breeding programs of cacao (Theobroma cacao L.) trees share the many challenges of breeding long-living perennial crops, and genetic progress is further constrained by both the limited understanding of the inheritance of complex traits and the prevalence of technical issues, such as mislabeled individuals (off-types). To better understand the genetic architecture of cacao, in this study, 13 years of phenotypic data collected from four progeny trials in Bahia, Brazil were analyzed jointly in a multisite analysis. Three separate analyses (multisite, single site with and without off-types) were performed to estimate genetic parameters from statistical models fitted on nine important agronomic traits (yield, seed index, pod index, % healthy pods, % pods infected with witches broom, % of pods other loss, vegetative brooms, diameter, and tree height). Genetic parameters were estimated along with variance components and heritabilities from the multisite analysis, and a trial was fingerprinted with low-density SNP markers to determine the impact of off-types on estimations. Heritabilities ranged from 0.37 to 0.64 for yield and its components and from 0.03 to 0.16 for disease resistance traits. A weighted index was used to make selections for clonal evaluation, and breeding values estimated for the parental selection and estimation of genetic gain. The impact of off-types to breeding progress in cacao was assessed for the first time. Even when present at <5% of the total population, off-types altered selections by 48%, and impacted heritability estimations for all nine of the traits analyzed, including a 41% difference in estimated heritability for yield. These results show that in a mixed model analysis, even a low level of pedigree error can significantly alter estimations of genetic parameters and selections in a breeding program.