A manually annotated Actinidia chinensis var. chinensis (kiwifruit) genome highlights the challenges associated with draft genomes and gene prediction in plants.

BACKGROUND: Most published genome sequences are drafts, and most are dominated by computational gene prediction. Draft genomes typically incorporate considerable sequence data that are not assigned to chromosomes, and predicted genes without quality confidence measures. The current Actinidia chinensis (kiwifruit) 'Hongyang' draft genome has 164 Mb of sequences unassigned to pseudo-chromosomes, and omissions have been identified in the gene models. RESULTS: A second genome of an A. chinensis (genotype Red5) was fully sequenced. This new sequence resulted in a 554.0 Mb assembly with all but 6 Mb assigned to pseudo-chromosomes. Pseudo-chromosomal comparisons showed a considerable number of translocation events have occurred following a whole genome duplication (WGD) event some consistent with centromeric Robertsonian-like translocations. RNA sequencing data from 12 tissues and ab initio analysis informed a genome-wide manual annotation, using the WebApollo tool. In total, 33,044 gene loci represented by 33,123 isoforms were identified, named and tagged for quality of evidential support. Of these 3114 (9.4%) were identical to a protein within 'Hongyang' The Kiwifruit Information Resource (KIR v2). Some proportion of the differences will be varietal polymorphisms. However, as most computationally predicted Red5 models required manual re-annotation this proportion is expected to be small. The quality of the new gene models was tested by fully sequencing 550 cloned 'Hort16A' cDNAs and comparing with the predicted protein models for Red5 and both the original 'Hongyang' assembly and the revised annotation from KIR v2. Only 48.9% and 63.5% of the cDNAs had a match with 90% identity or better to the original and revised 'Hongyang' annotation, respectively, compared with 90.9% to the Red5 models. CONCLUSIONS: Our study highlights the need to take a cautious approach to draft genomes and computationally predicted genes. Our use of the manual annotation tool WebApollo facilitated manual checking and correction of gene models enabling improvement of computational prediction. This utility was especially relevant for certain types of gene families such as the EXPANSIN like genes. Finally, this high quality gene set will supply the kiwifruit and general plant community with a new tool for genomics and other comparative analysis.

Random Tagging Genotyping by Sequencing (rtGBS), an Unbiased Approach to Locate Restriction Enzyme Sites across the Target Genome.

UNLABELLED: Genotyping by sequencing (GBS) is a restriction enzyme based targeted approach developed to reduce the genome complexity and discover genetic markers when a priori sequence information is unavailable. Sufficient coverage at each locus is essential to distinguish heterozygous from homozygous sites accurately. The number of GBS samples able to be pooled in one sequencing lane is limited by the number of restriction sites present in the genome and the read depth required at each site per sample for accurate calling of single-nucleotide polymorphisms. Loci bias was observed using a slight modification of the Elshire et al. METHOD: some restriction enzyme sites were represented in higher proportions while others were poorly represented or absent. This bias could be due to the quality of genomic DNA, the endonuclease and ligase reaction efficiency, the distance between restriction sites, the preferential amplification of small library restriction fragments, or bias towards cluster formation of small amplicons during the sequencing process. To overcome these issues, we have developed a GBS method based on randomly tagging genomic DNA (rtGBS). By randomly landing on the genome, we can, with less bias, find restriction sites that are far apart, and undetected by the standard GBS (stdGBS) method. The study comprises two types of biological replicates: six different kiwifruit plants and two independent DNA extractions per plant; and three types of technical replicates: four samples of each DNA extraction, stdGBS vs. rtGBS methods, and two independent library amplifications, each sequenced in separate lanes. A statistically significant unbiased distribution of restriction fragment size by rtGBS showed that this method targeted 49% (39,145) of BamH I sites shared with the reference genome, compared to only 14% (11,513) by stdGBS.

A microRNA allele that emerged prior to apple domestication may underlie fruit size evolution.

The molecular genetic mechanisms underlying fruit size remain poorly understood in perennial crops, despite size being an important agronomic trait. Here we show that the expression level of a microRNA gene (miRNA172) influences fruit size in apple. A transposon insertional allele of miRNA172 showing reduced expression associates with large fruit in an apple breeding population, whereas over-expression of miRNA172 in transgenic apple significantly reduces fruit size. The transposon insertional allele was found to be co-located with a major fruit size quantitative trait locus, fixed in cultivated apples and their wild progenitor species with relatively large fruit. This finding supports the view that the selection for large size in apple fruit was initiated prior to apple domestication, likely by large mammals, before being subsequently strengthened by humans, and also helps to explain why signatures of genetic bottlenecks and selective sweeps are normally weaker in perennial crops than in annual crops.

Genetic analysis of resistance to Pseudomonas syringae pv. actinidiae (Psa) in a kiwifruit progeny test: an application of generalised linear mixed models (GLMMs).

Linear Mixed models (LMMs) that incorporate genetic and spatial covariance structures have been used for many years to estimate genetic parameters and to predict breeding values in animal and plant breeding. Although the theoretical aspects for extending LMM to generalised linear mixed models (GLMMs) have been around for some time, suitable software has been developed only within the last decade or so. The GLIMMIX procedure in SAS® is becoming popular for fitting GLMMs in various disciplines. Applications of GLMMs to genetic analysis have been limited, probably because of the complexity of the models used. This is particularly so for Proc GLIMMIX because, unlike ASReml software, it is not specifically tailored for analysis of breeding data and some pre-procedure coding is necessary. Binary data that fits the GLMM framework is commonly encountered in breeding experiments, such as when evaluating individuals for resistance by observing the presence or absence of disease. Bacterial canker (Psa) caused by Pseudomonas syringae pv. actinidiae is a serious disease of kiwifruit in New Zealand and other kiwifruit-producing countries. Data from a progeny test trial was available to identify parents with high breeding values for resistance. We successfully applied the GLIMMIX procedure for this purpose. Heritability for resistance was moderate, and we identified two parents and their family as having high potential for Psa resistance breeding. There are several potential pitfalls when using GLMMs with binary data and these are briefly discussed.

An ancient duplication of apple MYB transcription factors is responsible for novel red fruit-flesh phenotypes.

Anthocyanin accumulation is coordinated in plants by a number of conserved transcription factors. In apple (Malus × domestica), an R2R3 MYB transcription factor has been shown to control fruit flesh and foliage anthocyanin pigmentation (MYB10) and fruit skin color (MYB1). However, the pattern of expression and allelic variation at these loci does not explain all anthocyanin-related apple phenotypes. One such example is an open-pollinated seedling of cv Sangrado that has green foliage and develops red flesh in the fruit cortex late in maturity. We used methods that combine plant breeding, molecular biology, and genomics to identify duplicated MYB transcription factors that could control this phenotype. We then demonstrated that the red-flesh cortex phenotype is associated with enhanced expression of MYB110a, a paralog of MYB10. Functional characterization of MYB110a showed that it was able to up-regulate anthocyanin biosynthesis in tobacco (Nicotiana tabacum). The chromosomal location of MYB110a is consistent with a whole-genome duplication event that occurred during the evolution of apple within the Maloideae family. Both MYB10 and MYB110a have conserved function in some cultivars, but they differ in their expression pattern and response to fruit maturity.

Putative resistance gene markers associated with quantitative trait loci for fire blight resistance in Malus 'Robusta 5' accessions.

BACKGROUND: Breeding of fire blight resistant scions and rootstocks is a goal of several international apple breeding programs, as options are limited for management of this destructive disease caused by the bacterial pathogen Erwinia amylovora. A broad, large-effect quantitative trait locus (QTL) for fire blight resistance has been reported on linkage group 3 of Malus 'Robusta 5'. In this study we identified markers derived from putative fire blight resistance genes associated with the QTL by integrating further genetic mapping studies with bioinformatics analysis of transcript profiling data and genome sequence databases. RESULTS: When several defined E.amylovora strains were used to inoculate three progenies from international breeding programs, all with 'Robusta 5' as a common parent, two distinct QTLs were detected on linkage group 3, where only one had previously been mapped. In the New Zealand 'Malling 9' X 'Robusta 5' population inoculated with E. amylovora ICMP11176, the proximal QTL co-located with SNP markers derived from a leucine-rich repeat, receptor-like protein (MxdRLP1) and a closely linked class 3 peroxidase gene. While the QTL detected in the German 'Idared' X 'Robusta 5' population inoculated with E. amylovora strains Ea222_JKI or ICMP11176 was approximately 6 cM distal to this, directly below a SNP marker derived from a heat shock 90 family protein gene (HSP90). In the US 'Otawa3' X 'Robusta5' population inoculated with E. amylovora strains Ea273 or E2002a, the position of the LOD score peak on linkage group 3 was dependent upon the pathogen strains used for inoculation. One of the five MxdRLP1 alleles identified in fire blight resistant and susceptible cultivars was genetically associated with resistance and used to develop a high resolution melting PCR marker. A resistance QTL detected on linkage group 7 of the US population co-located with another HSP90 gene-family member and a WRKY transcription factor previously associated with fire blight resistance. However, this QTL was not observed in the New Zealand or German populations. CONCLUSIONS: The results suggest that the upper region of 'Robusta 5' linkage group 3 contains multiple genes contributing to fire blight resistance and that their contributions to resistance can vary depending upon pathogen virulence and other factors. Mapping markers derived from putative fire blight resistance genes has proved a useful aid in defining these QTLs and developing markers for marker-assisted breeding of fire blight resistance.