Genome to Phenome Mapping in Apple Using Historical Data

Prediction of Cacao (Theobroma cacao) Resistance to Moniliophthora spp. Diseases via Genome-Wide Association Analysis and Genomic Selection

Cacao (Theobroma cacao) is a globally important crop, and its yield is severely restricted by disease. Two of the most damaging diseases, witches' broom disease (WBD) and frosty pod rot disease (FPRD), are caused by a pair of related fungi: Moniliophthora perniciosa and Moniliophthora roreri, respectively. Resistant cultivars are the most effective long-term strategy to address Moniliophthora diseases, but efficiently generating resistant and productive new cultivars will require robust methods for screening germplasm before field testing. Marker-assisted selection (MAS) and genomic selection (GS) provide two potential avenues for predicting the performance of new genotypes, potentially increasing the selection gain per unit time. To test the effectiveness of these two approaches, we performed a genome-wide association study (GWAS) and GS on three related populations of cacao in Ecuador genotyped with a 15K single nucleotide polymorphism (SNP) microarray for three measures of WBD infection (vegetative broom, cushion broom, and chirimoya pod), one of FPRD (monilia pod) and two productivity traits (total fresh weight of pods and % healthy pods produced). GWAS yielded several SNPs associated with disease resistance in each population, but none were significantly correlated with the same trait in other populations. Genomic selection, using one population as a training set to estimate the phenotypes of the remaining two (composed of different families), varied among traits, from a mean prediction accuracy of 0.46 (vegetative broom) to 0.15 (monilia pod), and varied between training populations. Simulations demonstrated that selecting seedlings using GWAS markers alone generates no improvement over selecting at random, but that GS improves the selection process significantly. Our results suggest that the GWAS markers discovered here are not sufficiently predictive across diverse germplasm to be useful for MAS, but that using all markers in a GS framework holds substantial promise in accelerating disease-resistance in cacao.

Contrasting Transcriptional Programs Control Postharvest Development of Apples (Malus x domestica Borkh.) Submitted to Cold Storage and Ethylene Blockage

Apple is commercially important worldwide. Favorable genomic contexts and postharvest technologies allow year-round availability. Although ripening is considered a unidirectional developmental process toward senescence, storage at low temperatures, alone or in combination with ethylene blockage, is effective in preserving apple properties. Quality traits and genome wide expression were integrated to investigate the mechanisms underlying postharvest changes. Development and conservation techniques were responsible for transcriptional reprogramming and distinct programs associated with quality traits. A large portion of the differentially regulated genes constitutes a program involved in ripening and senescence, whereas a smaller module consists of genes associated with reestablishment and maintenance of juvenile traits after harvest. Ethylene inhibition was associated with a reversal of ripening by transcriptional induction of anabolic pathways. Our results demonstrate that the blockage of ethylene perception and signaling leads to upregulation of genes in anabolic pathways. We also associated complex phenotypes to subsets of differentially regulated genes.

Genome re-sequencing reveals the history of apple and supports a two-stage model for fruit enlargement

Human selection has reshaped crop genomes. Here we report an apple genome variation map generated through genome sequencing of 117 diverse accessions. A comprehensive model of apple speciation and domestication along the Silk Road is proposed based on evidence from diverse genomic analyses. Cultivated apples likely originate from Malus sieversii in Kazakhstan, followed by intensive introgressions from M. sylvestris. M. sieversii in Xinjiang of China turns out to be an "ancient" isolated ecotype not directly contributing to apple domestication. We have identified selective sweeps underlying quantitative trait loci/genes of important fruit quality traits including fruit texture and flavor, and provide evidences supporting a model of apple fruit size evolution comprising two major events with one occurring prior to domestication and the other during domestication. This study outlines the genetic basis of apple domestication and evolution, and provides valuable information for facilitating marker-assisted breeding and apple improvement.Apple is one of the most important fruit crops. Here, the authors perform deep genome resequencing of 117 diverse accessions and reveal comprehensive models of apple origin, speciation, domestication, and fruit size evolution as well as candidate genes associated with important agronomic traits.

LinkImputeR: user-guided genotype calling and imputation for non-model organisms

Background

Genomic studies such as genome-wide association and genomic selection require genome-wide genotype data. All existing technologies used to create these data result in missing genotypes, which are often then inferred using genotype imputation software. However, existing imputation methods most often make use only of genotypes that are successfully inferred after having passed a certain read depth threshold. Because of this, any read information for genotypes that did not pass the threshold, and were thus set to missing, is ignored. Most genomic studies also choose read depth thresholds and quality filters without investigating their effects on the size and quality of the resulting genotype data. Moreover, almost all genotype imputation methods require ordered markers and are therefore of limited utility in non-model organisms.

Results

Here we introduce LinkImputeR, a software program that exploits the read count information that is normally ignored, and makes use of all available DNA sequence information for the purposes of genotype calling and imputation. It is specifically designed for non-model organisms since it requires neither ordered markers nor a reference panel of genotypes. Using next-generation DNA sequence (NGS) data from apple, cannabis and grape, we quantify the effect of varying read count and missingness thresholds on the quantity and quality of genotypes generated from LinkImputeR. We demonstrate that LinkImputeR can increase the number of genotype calls by more than an order of magnitude, can improve genotyping accuracy by several percent and can thus improve the power of downstream analyses. Moreover, we show that the effects of quality and read depth filters can differ substantially between data sets and should therefore be investigated on a per-study basis.

Conclusions

By exploiting DNA sequence data that is normally ignored during genotype calling and imputation, LinkImputeR can significantly improve both the quantity and quality of genotype data generated from NGS technologies. It enables the user to quickly and easily examine the effects of varying thresholds and filters on the number and quality of the resulting genotype calls. In this manner, users can decide on thresholds that are most suitable for their purposes. We show that LinkImputeR can significantly augment the value and utility of NGS data sets, especially in non-model organisms with poor genomic resources.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3873-5) contains supplementary material, which is available to authorized users.

Exploiting Wild Relatives for Genomics-assisted Breeding of Perennial Crops

Perennial crops are vital contributors to global food production and nutrition. However, the breeding of new perennial crops is an expensive and time-consuming process due to the large size and lengthy juvenile phase of many species. Genomics provides a valuable tool for improving the efficiency of breeding by allowing progeny possessing a trait of interest to be selected at the seed or seedling stage through marker-assisted selection (MAS). The benefits of MAS to a breeder are greatest when the targeted species takes a long time to reach maturity and is expensive to grow and maintain. Thus, MAS holds particular promise in perennials since they are often costly and time-consuming to grow to maturity and evaluate. Well-characterized germplasm that breeders can tap into for improving perennials is often limited in genetic diversity. Wild relatives are a largely untapped source of desirable traits including disease resistance, fruit quality, and rootstock characteristics. This review focuses on the use of genomics-assisted breeding in perennials, especially as it relates to the introgression of useful traits from wild relatives. The identification of genetic markers predictive of beneficial phenotypes derived from wild relatives is hampered by genomic tools designed for domesticated species that are often ill-suited for use in wild relatives. There is therefore an urgent need for better genomic resources from wild relatives. A further barrier to exploiting wild diversity through genomics is the phenotyping bottleneck: well-powered genetic mapping requires accurate and cost-effective characterization of large collections of diverse wild germplasm. While genomics will always be used in combination with traditional breeding methods, it is a powerful tool for accelerating the speed and reducing the costs of breeding while harvesting the potential of wild relatives for improving perennial crops.

Patterns of genomic and phenomic diversity in wine and table grapes

Grapes are one of the most economically and culturally important crops worldwide, and they have been bred for both winemaking and fresh consumption. Here we evaluate patterns of diversity across 33 phenotypes collected over a 17-year period from 580 table and wine grape accessions that belong to one of the world's largest grape gene banks, the grape germplasm collection of the United States Department of Agriculture. We find that phenological events throughout the growing season are correlated, and quantify the marked difference in size between table and wine grapes. By pairing publicly available historical phenotype data with genome-wide polymorphism data, we identify large effect loci controlling traits that have been targeted during domestication and breeding, including hermaphroditism, lighter skin pigmentation and muscat aroma. Breeding for larger berries in table grapes was traditionally concentrated in geographic regions where Islam predominates and alcohol was prohibited, whereas wine grapes retained the ancestral smaller size that is more desirable for winemaking in predominantly Christian regions. We uncover a novel locus with a suggestive association with berry size that harbors a signature of positive selection for larger berries. Our results suggest that religious rules concerning alcohol consumption have had a marked impact on patterns of phenomic and genomic diversity in grapes.

Genome-Wide Association Mapping of Flowering and Ripening Periods in Apple

Deciphering the genetic control of flowering and ripening periods in apple is essential for breeding cultivars adapted to their growing environments. We implemented a large Genome-Wide Association Study (GWAS) at the European level using an association panel of 1,168 different apple genotypes distributed over six locations and phenotyped for these phenological traits. The panel was genotyped at a high-density of SNPs using the Axiom®Apple 480 K SNP array. We ran GWAS with a multi-locus mixed model (MLMM), which handles the putatively confounding effect of significant SNPs elsewhere on the genome. Genomic regions were further investigated to reveal candidate genes responsible for the phenotypic variation. At the whole population level, GWAS retained two SNPs as cofactors on chromosome 9 for flowering period, and six for ripening period (four on chromosome 3, one on chromosome 10 and one on chromosome 16) which, together accounted for 8.9 and 17.2% of the phenotypic variance, respectively. For both traits, SNPs in weak linkage disequilibrium were detected nearby, thus suggesting the existence of allelic heterogeneity. The geographic origins and relationships of apple cultivars accounted for large parts of the phenotypic variation. Variation in genotypic frequency of the SNPs associated with the two traits was connected to the geographic origin of the genotypes (grouped as North+East, West and South Europe), and indicated differential selection in different growing environments. Genes encoding transcription factors containing either NAC or MADS domains were identified as major candidates within the small confidence intervals computed for the associated genomic regions. A strong microsynteny between apple and peach was revealed in all the four confidence interval regions. This study shows how association genetics can unravel the genetic control of important horticultural traits in apple, as well as reduce the confidence intervals of the associated regions identified by linkage mapping approaches. Our findings can be used for the improvement of apple through marker-assisted breeding strategies that take advantage of the accumulating additive effects of the identified SNPs.

QTL analysis of soft scald in two apple populations

The apple (Malus×domestica Borkh.) is one of the world's most widely grown and valuable fruit crops. With demand for apples year round, storability has emerged as an important consideration for apple breeding programs. Soft scald is a cold storage-related disorder that results in sunken, darkened tissue on the fruit surface. Apple breeders are keen to generate new cultivars that do not suffer from soft scald and can thus be marketed year round. Traditional breeding approaches are protracted and labor intensive, and therefore marker-assisted selection (MAS) is a valuable tool for breeders. To advance MAS for storage disorders in apple, we used genotyping-by-sequencing (GBS) to generate high-density genetic maps in two F1 apple populations, which were then used for quantitative trait locus (QTL) mapping of soft scald. In total, 900 million DNA sequence reads were generated, but after several data filtering steps, only 2% of reads were ultimately used to create two genetic maps that included 1918 and 2818 single-nucleotide polymorphisms. Two QTL associated with soft scald were identified in one of the bi-parental populations originating from parent 11W-12-11, an advanced breeding line. This study demonstrates the utility of next-generation DNA sequencing technologies for QTL mapping in F1 populations, and provides a basis for the advancement of MAS to improve storability of apples.