Mapping QTL associated with resistance to Pseudomonas syringae pv. actinidiae in kiwifruit (Actinidia chinensis var. chinensis)

Pseudomonas syringae pv. actinidiae (Psa) is a bacterial pathogen of kiwifruit. This pathogen causes leaf-spotting, cane dieback, wilting, cankers (lesions), and in severe cases, plant death. Families of diploid A. chinensis seedlings grown in the field show a range of susceptibilities to the disease with up to 100% of seedlings in some families succumbing to Psa. But the effect of selection for field resistance to Psa on the alleles that remain in surviving seedlings has not been assessed. The objective of this work was to analyse, the effect of plant removal from Psa on the allele frequency of an incomplete-factorial-cross population. This population was founded using a range of genotypically distinct diploid A. chinensis var. chinensis parents to make 28 F1 families. However, because of the diversity of these families, low numbers of surviving individuals, and a lack of samples from dead individuals, standard QTL mapping approaches were unlikely to yield good results. Instead, a modified bulk segregant analysis (BSA) overcame these drawbacks while reducing the costs of sampling and sample processing, and the complexity of data analysis. Because the method was modified, part one of this work was used to determine the signal strength required for a QTL to be detected with BSA. Once QTL detection accuracy was known, part two of this work analysed the 28 families from the incomplete-factorial-cross population that had multiple individuals removed due to Psa infection. Each family was assigned to one of eight bulks based on a single parent that contributed to the families. DNA was extracted in bulk by grinding sampled leaf discs together before DNA extraction. Each sample bulk was compared against a bulk made up of WGS data from the parents contributing to the sample bulk. The deviation in allele frequency from the expected allele frequency within surviving populations using the modified BSA method was able to identify 11 QTLs for Psa that were present in at least two analyses. The identification of these Psa resistance QTL will enable marker development to selectively breed for resistance to Psa in future kiwifruit breeding programs.

Genomic architecture of resistance to latania scale (H. lataniae) in kiwifruit (A. chinensis var. chinensis)

BACKGROUND

Latania scale (Hemiberlesia lataniae Signoret) is an armoured scale insect known to cause damage to kiwifruit plants and fruit, which ultimately reduces crop values and creates post-harvest export and quarantine issues. Resistance to H. lataniae does exist in some commercial cultivars of kiwifruit. However, some of the commercial cultivars bred in New Zealand have not inherited alleles for resistance to H. lataniae carried by their parents. To elucidate the architecture of resistance in the parents and develop molecular markers to assist breeding, these experiments analysed the inheritance of resistance to H. lataniae from families related to commercial cultivars.

RESULTS

The first experiment identified a 15.97 Mb genomic region of interest for resistance to H. lataniae in rtGBS data of 3.23 to 19.20 Mb on chromosome 10. A larger population was then QTL mapped, which confirmed the region of interest as the sole locus contributing to H. lataniae resistance. inDel markers mapping the region of low recombination under the QTL peak further narrowed the region associated with H. lataniae resistance to a 5.73 Mb region.

CONCLUSIONS

The kiwifruit populations and genomic methods used in this study identify the same non-recombinant region of chromosome 10 which confers resistance of A. chinensis var. chinensis to H. lataniae. The markers developed to target the H. lataniae resistance loci will reduce the amount of costly and time-consuming phenotyping required for breeding H. lataniae scale resistance into new kiwifruit cultivars.

Predictive ability of genomic selection models in a multi-population perennial ryegrass training set using genotyping-by-sequencing

KEY MESSAGE

Genomic prediction models for multi-year dry matter yield, via genotyping-by-sequencing in a composite training set, demonstrate potential for genetic gain improvement through within-half sibling family selection. Perennial ryegrass (Lolium perenne L.) is a key source of nutrition for ruminant livestock in temperate environments worldwide. Higher seasonal and annual yield of herbage dry matter (DMY) is a principal breeding objective but the historical realised rate of genetic gain for DMY is modest. Genomic selection was investigated as a tool to enhance the rate of genetic gain. Genotyping-by-sequencing (GBS) was undertaken in a multi-population (MP) training set of five populations, phenotyped as half-sibling (HS) families in five environments over 2 years for mean herbage accumulation (HA), a measure of DMY potential. GBS using the ApeKI enzyme yielded 1.02 million single-nucleotide polymorphism (SNP) markers from a training set of n = 517. MP-based genomic prediction models for HA were effective in all five populations, cross-validation-predictive ability (PA) ranging from 0.07 to 0.43, by trait and target population, and 0.40-0.52 for days-to-heading. Best linear unbiased predictor (BLUP)-based prediction methods, including GBLUP with either a standard or a recently developed (KGD) relatedness estimation, were marginally superior or equal to ridge regression and random forest computational approaches. PA was principally an outcome of SNP modelling genetic relationships between training and validation sets, which may limit application for long-term genomic selection, due to PA decay. However, simulation using data from the training experiment indicated a twofold increase in genetic gain for HA, when applying a prediction model with moderate PA in a single selection cycle, by combining among-HS family selection, based on phenotype, with within-HS family selection using genomic prediction.