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Open Access Publications from the University of California

Scholarly Works (33 results)

  • Thesis
  • Peer Reviewed
UC Davis Electronic Theses and Dissertations (2024)

This thesis explores advanced strategies to enhance strawberry breeding by applying genomic prediction, harnessing underutilized genetic diversity, and investigating key genetic mutations affecting fruit quality traits. The first chapter focuses on enhancing strawberry resistance to Phytophthora crown rot (PhCR), a soil-borne disease that thrives in warm, wet conditions and severely impacts yields. It addresses the limited genetic gains in breeding for PhCR resistance and the discovery of a significant locus, RPc2, which explains a substantial portion of genetic variance. Incorporating underutilized gene bank resources doubled additive genetic variance and improved genomic prediction accuracy, highlighting the potential of genomic selection for enhancing PhCR resistance.

The second chapter further solidifies the success of these strategies, evaluating the use of useful heterosis and genomic prediction to improve fruit quality traits and shelf life in strawberries. It examines the introgression of favorable alleles from exotic genetic resources into elite breeding pools, resulting in significant improvements in total soluble solids and titratable acidity. The study not only highlights the genetic correlations among fruit traits and the impact of genotype combinations on hybrid performance but also underscores the importance of genomic prediction in efficiently selecting superior genotypes and optimizing breeding programs.

The third chapter investigates the domestication of strawberry for improved fruit firmness and shelf life. It identifies a loss-of-function mutation in the polygalacturonase gene PG1-6A1, significantly increasing fruit firmness and reducing perishability. This mutation and several structural variants have been positively correlated with fruit firmness and negatively with gene expression. Developing high-throughput genotyping assays for these mutations facilitates marker-assisted selection, enabling the breeding of firmer and longer-lasting strawberry cultivars.

Collectively, these studies provide valuable insights into the genetic basis of key traits in strawberries and showcase the potential of genomic technologies to accelerate breeding efforts and improve fruit quality and disease resistance.

    Cover page: Genome-Wide Analysis of Phytophthora cactorum Resistance and Fruit Quality Traits in Cultivated Strawberry (Fragaria x ananassa)
    • Article
    • Peer Reviewed
    UC Davis Previously Published Works (2022)
    Many important traits in plants, animals, and microbes are polygenic and challenging to improve through traditional marker-assisted selection. Genomic prediction addresses this by incorporating all genetic data in a mixed model framework. The primary method for predicting breeding values is genomic best linear unbiased prediction, which uses the realized genomic relationship or kinship matrix (K) to connect genotype to phenotype. Genomic relationship matrices share information among entries to estimate the observed entries' genetic values and predict unobserved entries' genetic values. One of the main parameters of such models is genomic variance (σg2), or the variance of a trait associated with a genome-wide sample of DNA polymorphisms, and genomic heritability (hg2); however, the seminal papers introducing different forms of K often do not discuss their effects on the model estimated variance components despite their importance in genetic research and breeding. Here, we discuss the effect of several standard methods for calculating the genomic relationship matrix on estimates of σg2 and hg2. With current approaches, we found that the genomic variance tends to be either overestimated or underestimated depending on the scaling and centering applied to the marker matrix (Z), the value of the average diagonal element of K, and the assortment of alleles and heterozygosity (H) in the observed population. Using the average semivariance, we propose a new matrix, KASV, that directly yields accurate estimates of σg2 and hg2 in the observed population and produces best linear unbiased predictors equivalent to routine methods in plants and animals.
      Cover page: Average semivariance directly yields accurate estimates of the genomic variance in complex trait analyses.
      • Article
      • Peer Reviewed
      UC Davis Previously Published Works (2024)
      The annual production of strawberry has increased by one million tonnes in the US and 8.4 million tonnes worldwide since 1960. Here we show that the US expansion was driven by genetic gains from Green Revolution breeding and production advances that increased yields by 2,755%. Using a California population with a century-long breeding history and phenotypes of hybrids observed in coastal California environments, we estimate that breeding has increased fruit yields by 2,974-6,636%, counts by 1,454-3,940%, weights by 228-504%, and firmness by 239-769%. Using genomic prediction approaches, we pinpoint the origin of the Green Revolution to the early 1950s and uncover significant increases in additive genetic variation caused by transgressive segregation and phenotypic diversification. Lastly, we show that the most consequential Green Revolution breeding breakthrough was the introduction of photoperiod-insensitive, PERPETUAL FLOWERING hybrids in the 1970s that doubled yields and drove the dramatic expansion of strawberry production in California.
        Cover page: Genetic gains underpinning a little-known strawberry Green Revolution.
        • Article
        • Peer Reviewed
        UC Davis Previously Published Works (2019)
        The fungal pathogen Botrytis cinerea causes grey mould, a commercially damaging disease of strawberry. This pathogen affects fruit in the field, storage, transport and market. The presence of grey mould is the most common reason for fruit rejection by growers, shippers and consumers, leading to significant economic losses. Here, we review the biology and epidemiology of the pathogen, mechanisms of infection and the genetics of host plant resistance. The development of grey mould is affected by environmental and genetic factors; however, little is known about how B. cinerea and strawberry interact at the molecular level. Despite intensive efforts, breeding strawberry for resistance to grey mould has not been successful, and the mechanisms underlying tolerance to B. cinerea are poorly understood and under-investigated. Current control strategies against grey mould include pre- and postharvest fungicides, yet they are generally ineffective and expensive. In this review, we examine available research on horticultural management, chemical and biological control of the pathogen in the field and postharvest storage, and discuss their relevance for integrative disease management. Additionally, we identify and propose approaches for increasing resistance to B. cinerea in strawberry by tapping into natural genetic variation and manipulating host factors via genetic engineering and genome editing.
          Cover page: Grey mould of strawberry, a devastating disease caused by the ubiquitous necrotrophic fungal pathogen Botrytis cinerea
          • Article
          • Peer Reviewed
          UC Davis Previously Published Works (2015)
          The seed oil of meadowfoam, a new crop in the Limnanthaceae family, is highly enriched in very long chain fatty acids that are desaturated at the Δ5 position. The unusual oil is desirable for cosmetics and innovative industrial applications and the seed meal remaining after oil extraction contains glucolimnanthin, a methoxylated benzylglucosinolate whose degradation products are herbicidal and anti-microbial. Here we describe EST analysis of the developing seed transcriptome that identified major genes involved in biosynthesis and assembly of the seed oil and in glucosinolate metabolic pathways. mRNAs encoding acyl-CoA Δ5 desaturase were notably abundant. The library was searched for simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs). Fifty-four new SSR markers and eight candidate gene markers were developed and combined with previously developed SSRs to construct a new genetic map for Limnanthes alba. Mapped genes in the lipid biosynthetic pathway encode 3-ketoacyl-CoA synthase (KCS), Δ5 desaturase (Δ5DS), lysophosphatidylacyl-acyl transferase (LPAT), and acyl-CoA diacylglycerol acyl transferase (DGAT). Mapped genes in glucosinolate biosynthetic and degradation pathways encode CYP79A, myrosinase (TGG), and epithiospecifier modifier protein (ESM). The resources developed in this study will further the domestication and improvement of meadowfoam as an oilseed crop.
            Cover page: Genes affecting novel seed constituents in Limnanthes alba Benth: transcriptome analysis of developing embryos and a new genetic map of meadowfoam
            • Article
            • Peer Reviewed
            UC Davis Previously Published Works (2021)
            The development of genome-informed methods for identifying quantitative trait loci (QTL) and studying the genetic basis of quantitative variation in natural and experimental populations has been driven by advances in high-throughput genotyping. For many complex traits, the underlying genetic variation is caused by the segregation of one or more 'large-effect' loci, in addition to an unknown number of loci with effects below the threshold of statistical detection. The large-effect loci segregating in populations are often necessary but not sufficient for predicting quantitative phenotypes. They are, nevertheless, important enough to warrant deeper study and direct modelling in genomic prediction problems. We explored the accuracy of statistical methods for estimating the fraction of marker-associated genetic variance (p) and heritability ([Formula: see text]) for large-effect loci underlying complex phenotypes. We found that commonly used statistical methods overestimate p and [Formula: see text]. The source of the upward bias was traced to inequalities between the expected values of variance components in the numerators and denominators of these parameters. Algebraic solutions for bias-correcting estimates of p and [Formula: see text] were found that only depend on the degrees of freedom and are constant for a given study design. We discovered that average semivariance methods, which have heretofore not been used in complex trait analyses, yielded unbiased estimates of p and [Formula: see text], in addition to best linear unbiased predictors of the additive and dominance effects of the underlying loci. The cryptic bias problem described here is unrelated to selection bias, although both cause the overestimation of p and [Formula: see text]. The solutions we described are predicted to more accurately describe the contributions of large-effect loci to the genetic variation underlying complex traits of medical, biological, and agricultural importance.
              Cover page: Average semivariance yields accurate estimates of the fraction of marker-associated genetic variance and heritability in complex trait analyses.
              • Article
              • Peer Reviewed
              UC Davis Previously Published Works (2021)

              Premise

              Polyploid species often have complex evolutionary histories that have, until recently, been intractable due to limitations of genomic resources. While recent work has further uncovered the evolutionary history of the octoploid strawberry (Fragaria L.), there are still open questions. Much is unknown about the evolutionary relationship of the wild octoploid species, Fragaria virginiana and Fragaria chiloensis, and gene flow within and among species after the formation of the octoploid genome.

              Methods

              We leveraged a collection of wild octoploid ecotypes of strawberry representing the recognized subspecies and ranging from Alaska to southern Chile, and a high-density SNP array to investigate wild octoploid strawberry evolution. Evolutionary relationships were interrogated with phylogenetic analysis and genetic clustering algorithms. Additionally, admixture among and within species is assessed with model-based and tree-based approaches.

              Results

              Phylogenetic analysis revealed that the two octoploid strawberry species are monophyletic sister lineages. The genetic clustering results show substructure between North and South American F. chiloensis populations. Additionally, model-based and tree-based methods support gene flow within and among the two octoploid species, including newly identified admixture in the Hawaiian F. chiloensis subsp. sandwicensis population.

              Conclusions

              F. virginiana and F. chiloensis are supported as monophyletic and sister lineages. All but one of the subspecies show extensive paraphyly. Furthermore, phylogenetic relationships among F. chiloensis populations supports a single population range expansion southward from North America. The inter- and intraspecific relationships of octoploid strawberry are complex and suggest substantial gene flow between sympatric populations among and within species.
                Cover page: Diversification, spread, and admixture of octoploid strawberry in the Western Hemisphere
                • Article
                • Peer Reviewed
                UC Davis Previously Published Works (2014)
                Knowledge of the nature and extent of karyotypic differences between species provides insight into the evolutionary history of the genomes in question and, in the case of closely related species, the potential for genetic exchange between taxa. We constructed high-density genetic maps of the silverleaf sunflower (Helianthus argophyllus) and Algodones Dune sunflower (H. niveus ssp. tephrodes) genomes and compared them to a consensus map of cultivated sunflower (H. annuus) to identify chromosomal rearrangements between species. The genetic maps of H. argophyllus and H. niveus ssp. tephrodes included 17 linkage groups each and spanned 1337 and 1478 cM, respectively. Comparative analyses revealed greater divergence between H. annuus and H. niveus ssp. tephrodes (13 inverted segments, 18 translocated segments) than between H. annuus and H. argophyllus (10 inverted segments, 8 translocated segments), consistent with their known phylogenetic relationships. Marker order was conserved across much of the genome, with 83 and 64% of the H. argophyllus and H. niveus ssp. tephrodes genomes, respectively, being syntenic with H. annuus. Population genomic analyses between H. annuus and H. argophyllus, which are sympatric across a portion of the natural range of H. annuus, revealed significantly elevated genetic structure in rearranged portions of the genome, indicating that such rearrangements are associated with restricted gene flow between these two species.
                  Cover page: Chromosomal Evolution and Patterns of Introgression in Helianthus
                  • Article
                  • Peer Reviewed
                  UC Davis Previously Published Works (2023)
                  The development of strawberry (Fragaria × ananassa Duchesne ex Rozier) cultivars resistant to Phytophthora crown rot (PhCR), a devastating disease caused by the soil-borne pathogen Phytophthora cactorum (Lebert & Cohn) J. Schröt., has been challenging partly because the resistance phenotypes are quantitative and only moderately heritable. To develop deeper insights into the genetics of resistance and build the foundation for applying genomic selection, a genetically diverse training population was screened for resistance to California isolates of the pathogen. Here we show that genetic gains in breeding for resistance to PhCR have been negligible (3% of the cultivars tested were highly resistant and none surpassed early 20th century cultivars). Narrow-sense genomic heritability for PhCR resistance ranged from 0.41 to 0.75 among training population individuals. Using multivariate genome-wide association studies (GWAS), we identified a large-effect locus (predicted to be RPc2) that explained 43.6-51.6% of the genetic variance, was necessary but not sufficient for resistance, and was associated with calcium channel and other candidate genes with known plant defense functions. The addition of underutilized gene bank resources to our training population doubled additive genetic variance, increased the accuracy of genomic selection, and enabled the discovery of individuals carrying favorable alleles that are either rare or not present in modern cultivars. The incorporation of an RPc2-associated single-nucleotide polymorphism (SNP) as a fixed effect increased genomic prediction accuracy from 0.40 to 0.55. Finally, we show that parent selection using genomic-estimated breeding values, genetic variances, and cross usefulness holds promise for enhancing resistance to PhCR in strawberry.
                    Cover page: Harnessing underutilized gene bank diversity and genomic prediction of cross usefulness to enhance resistance to Phytophthora cactorum in strawberry.Creative Commons 'BY-NC-ND' version 4.0 license
                    • Article
                    • Peer Reviewed
                    UC Davis Previously Published Works (2020)
                    Shape is a critical element of the visual appeal of strawberry fruit and is influenced by both genetic and non-genetic determinants. Current fruit phenotyping approaches for external characteristics in strawberry often rely on the human eye to make categorical assessments. However, fruit shape is an inherently multi-dimensional, continuously variable trait and not adequately described by a single categorical or quantitative feature. Morphometric approaches enable the study of complex, multi-dimensional forms but are often abstract and difficult to interpret. In this study, we developed a mathematical approach for transforming fruit shape classifications from digital images onto an ordinal scale called the Principal Progression of k Clusters (PPKC). We use these human-recognizable shape categories to select quantitative features extracted from multiple morphometric analyses that are best fit for genetic dissection and analysis. We transformed images of strawberry fruit into human-recognizable categories using unsupervised machine learning, discovered 4 principal shape categories, and inferred progression using PPKC. We extracted 68 quantitative features from digital images of strawberries using a suite of morphometric analyses and multivariate statistical approaches. These analyses defined informative feature sets that effectively captured quantitative differences between shape classes. Classification accuracy ranged from 68% to 99% for the newly created phenotypic variables for describing a shape. Our results demonstrated that strawberry fruit shapes could be robustly quantified, accurately classified, and empirically ordered using image analyses, machine learning, and PPKC. We generated a dictionary of quantitative traits for studying and predicting shape classes and identifying genetic factors underlying phenotypic variability for fruit shape in strawberry. The methods and approaches that we applied in strawberry should apply to other fruits, vegetables, and specialty crops.
                      Cover page: Multi-dimensional machine learning approaches for fruit shape phenotyping in strawberry
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