Biology subjects

Feldmann, M. J.

Publications and source records attributed to Feldmann, M. J..

15 recordsLinked to original sources

bioRxiv2025

Genome-Wide Discovery and Characterization of Terpene Synthases Contributing to Strawberry Aroma Metabolism

Strawberry (Fragaria X ananassa) is a globally cultivated fruit crop valued for its unique flavor and aroma. Major groups of volatile organic compounds that contribute to strawberry aroma include terpenes, fatty acid esters, furanones, and benzenoids. Understanding the biosynthetic genes and pathways underlying strawberry terpene metabolism provides resources for developing precision breeding strategies to improve strawberry aroma traits. Here we describe the genome-wide identification and functional analysis of the terpene synthase (TPS) family that governs terpene chemical diversity in strawberries. Mining of the allo-octoploid genome of the cultivar Royal Royce identified 75 TPS gene candidates. Biochemical characterization of 27 predicted mono-, sesqui- and di-TPS enzymes via in vitro activity assays and in vivo enzyme co-expression studies demonstrated a range of TPS activities that are relevant for the biosynthesis of two thirds of known strawberry terpenes as well as products not previously described in octoploid strawberry. Complementary metabolomic and transcriptomic studies across a diversity panel of strawberry accessions demonstrated substantial variation in the composition and abundance of more than 30 detected accession-specific and common terpene aromas, nine of which matching characterized TPS products. Analysis of a developmental time series of two accessions with contrasting aroma further revealed accession-specific alterations of terpene metabolism during fruit ripening. These results expand our understanding of strawberry aroma metabolism and characterized terpene aroma genes as a resource for the molecular breeding of desirable aroma traits. One-sentence summaryDiscovery and characterization of the terpene synthase family that controls the diversity of terpene aroma metabolism in accessions of strawberry. Significance StatementThe diverse class of terpenoids contributes to complex crop traits, including plant growth, stress resilience, pollination, nutrition, and aroma. The discovery of terpene-biosynthetic pathways in octoploid strawberry (Fragaria X ananassa) provides foundational knowledge of the diversity of terpenoid metabolism in this important specialty crop toward applications in improving aroma traits.

plant biology↗

bioRxiv2025

The PERPETUAL FLOWERING Locus: Necessary But Insufficient for Genomic Prediction of Runnerless and Other Asexual Reproduction Phenotypes in Strawberry

Strawberry (Fragaria x ananassa) reproduces sexually through seeds and asexually through stolons. The ability to cost-effectively clonally propagate hybrid individuals on a large scale has profoundly shaped strawberry breeding and production practices. Despite the technical and economic importance of clonal propagation, little is known about the genetic regulation of runnering in strawberry, other than the photoperiod-dependent pleiotropic effects of PERPETUAL FLOWERING (PF), a dominant, yield-doubling gene introgressed from a wild relative that knocks out temperature-dependent photoperiod sensitivity and partially suppresses runnering. Herewe showthat runnering phenotypes are highly variable and heritable, ranging from runnerless to prolific and unrestrained in both short-day (pfpf) and day-neutral (PF_) plants. We physically mapped the PF locus to Mb 26.4-27.3 on chromosome 4B using high-density SNP haplotypes and historical recombination among 932 individuals. PF was the only runneringassociated locus uncovered by genome-wide association studies among diverse clonal genetic resources and progeny from narrow and wide crosses (1,537 individuals). However, PF explained only 22% of the genetic variance for runnering. Genomic-estimated breeding values for runnering were accurately estimated especially among runnerless to near-runnerless individuals. Genomic prediction accuracies were greater within than between populations, increased when corrected for PF, and are sufficient for implementing genomic selection. These results pave the way for enhancing the productivity of strawberry by creating runnerless cultivars for seed-propagation and near-runnerless and reduced runnering cultivars for clone-propagation through phenotypic or genomic selection. 1 CORE IDEASO_LIGenetic variation for runnering is substantial and heritable C_LIO_LIThe dominant PERPETUAL FLOWERING (PF) allele does not uniformly or ubiquitously suppress asexual reproduction C_LIO_LISubstantial wild donor DNA has persisted in day-neutral and summer-plant cultivars carrying the Wasatch PF allele C_LIO_LIThe accuracy of PF-corrected breeding values for runnering are sufficient for implementing genomic selection C_LIO_LIStrawberry productivity can be improved by introducing cultivars with runnerless or near-runnerless phenotypes C_LI

genetics↗

bioRxiv2025

Why Accuracy Metrics Fall Short in Comparing Phenomic and Genomic Prediction Models

Phenomic selection is a new paradigm in plant breeding that uses high-throughput phenotyping technologies and machine learning models to predict traits of new individuals and make selections. This can allow breeders to evaluate more plants in higher throughput more accurately, resulting in faster rates of gain and reduced labor costs. However, phenomic prediction models are frequently benchmarked against genomic prediction models using cross-validation to demonstrate their usefulness to breeders. We argue that this is inappropriate for two reasons: 1) differences in the accuracy statistic measured by cross-validation do not reliably indicate differences in the accuracy parameter of the breeders equation, which we show analytically and through re-analysis of data from three representative phenomic prediction studies, and 2) phenomic and genomic selection tools influence other parameters of the breeders equation, so comparing accuracy, even if done properly, is insufficient to advocate for one approach over the other. We conclude that phenomic selection may be useful, but comparisons of accuracy between genomic prediction and phenomic prediction models are not.

genetics↗

bioRxiv2024

Genomic Architecture of the Resistance to Phytophthora Cactorum 2 (RPc2) Locus in Strawberry (Fragaria x ananassa)

Phytophthora crown rot (PhCR), caused by Phytophthora cactorum, is a soilborne disease with broad impacts to cultivated strawberries in the United States and worldwide. While a resistance locus, RPc2, has been identified in octoploid strawberries, the underlying genomic architecture and mechanism remain unclear. Here, we fine-mapped the RPc2 region to 546 kb, containing 92 genes, and constructed a chromosome-scale haplotype-phased genome of resistant breeding selection FL 16.33-8. Comparative genome analyses with high-quality octoploid reference genomes, Florida Brilliance (FaFB1) and Royal Royce (FaRR1), identified two candidate genes, Wall Associated Kinase 1 (WAK1) and Cyclic Nucleotide Gated Channel 1 (CNGC1). Gene functions were validated using an Agrobacterium-mediated transient expression assay. Furthermore, by leveraging the population structure of the RPc2 locus among genetically diverse breeding populations, we unveiled the complexity of genetic architecture and recent selective sweeps associated with RPc2. Notably, the predominant resistant haplotype (RPc2-H3) is prevalent in most commercial strawberry varieties in the US. The findings from this study are facilitating the advancement of genome-assisted breeding strategies for resistance to PhCR in strawberries. SummaryO_LIPhytophthora crown rot (PhCR), caused by the soilborne pathogen Phytophthora cactorum, is a disease with broad impacts to cultivated strawberries worldwide. The Resistance to Phytophthora Cactorum 2 (RPc2) locus is widespread in important cultivars and is a target of selection in breeding programs. Despite its importance, the genomic architecture and mechanisms of RPc2 remain poorly characterized. C_LIO_LIWe performed fine-mapping and delimited the genomic region to a 546 kb segment containing 92 genes. We developed a chromosome-scale haplotype-phased genome from an elite resistant line, FL16.33-8, and made comparisons to reference genomes of Florida Brilliance (FaFB1) and Royal Royce (FaRR1) to uncover gene sequence and structural variants in resistant accessions. C_LIO_LIThrough comparative genomics and transcriptome profiling, we identified three candidate genes, Wall Associated Kinase 1 (WAK1) and Cyclic Nucleotide Gated Channel 1 (CNGC1) and CNGC2. The functions of these genes were validated using a simplified Agrobacterium-mediated transformation method for transient gene expression in strawberry crowns and roots. C_LIO_LIAn examination of the population structure of the RPc2 locus among genetically diverse accessions (N=1029) revealed that the predominant H3 resistant haplotype is widespread in breeding accessions in the US, supporting the findings of a previous study on recent selective sweeps associated with RPc2. Results from this study are advancing genome-assisted breeding strategies for enhancing resistance to PhCR in strawberry. C_LI

plant biology↗

bioRxiv2024

Why is usefulness rarely useful?

Mate selection plays an important role in breeding programs. The usefulness criterion was proposed as a criterion for mate selection, combining information on both the mean and standard deviation of the potential offspring, particularly in clonally propagated outbred species where large family sizes are possible. Predicting mean values of offspring of a cross is generally easier than predicting the standard deviation, especially in outbred species where the linkage of alleles is often unknown and phasing is required. In this study, we developed a method for estimating phasing accuracy from unphased genotype data on possible parental lines and evaluated whether the accuracy was sufficient to predict family standard deviations of possible crosses using a set of simulations spanning a wide range of genetic architectures and genotypes from a real strawberry breeding population. We find that despite highly accurate computational phasing, predicting family standard deviations and using predicted values of the usefulness criterion per possible cross confers little benefit relative to simply selecting parents based on predicted family means. Therefore even in this species, which is clonally propagated, outbred, and produces large families, we find the usefulness criterion unlikely to be useful.

genetics↗

bioRxiv2022

Complex Traits and Candidate Genes: Estimation of Genetic Variance Components Across Modes of Inheritance

Large-effect loci--those discovered by genome-wide association studies or linkage mapping--associated with key traits segregate amidst a background of minor, often undetectable genetic effects in both wild and domesticated plants and animals. Accurately attributing mean differences and variance explained to the correct components in the linear mixed model (LMM) analysis is important for both selecting superior progeny and parents in plant and animal breeding, but also for gene therapy and medical genetics in humans. Marker-assisted prediction (MAP) and its successor, genomic prediction (GP), have many advantages for selecting superior individuals and understanding disease risk. However, these two approaches are less often integrated to simultaneously study the modes of inheritance of complex traits. This simulation study demonstrates that the average semivariance can be applied to models incorporating Mendelian, oligogenic, and polygenic terms, simultaneously, and yields accurate estimates of the variance explained for all relevant terms. Our previous research focused on large-effect loci and polygenic variance exclusively, and in this work we want to synthesize and expand the average semivariance framework to a multitude of different genetic architectures and the corresponding mixed models. This framework independently accounts for the effects of large-effect loci and the polygenic genetic background and is universally applicable to genetics studies in humans, plants, animals, and microbes.

genetics↗

bioRxiv2022

Quantitative Evaluation of Nonlinear Methods for Population Structure Visualization & Inference

Population structure (also called genetic structure and population stratification) is the presence of a systematic difference in allele frequencies between sub-populations in a population as a result of non-random mating between individuals. It can be informative of genetic ancestry, and in the context of medical genetics it is an important confounding variable in genome wide association studies. Recently, many nonlinear dimensionality reduction techniques have been proposed for the population structure visualization task. However, an objective comparison of these techniques has so far been missing from the literature. In this paper, we discuss the previously proposed nonlinear techniques and some of their potential weaknesses. We then propose a novel quantitative evaluation methodology for comparing these nonlinear techniques, based on populations for which pedigree is either known a-priori through artificial selection or simulation. Based on this evaluation metric, we find graph-based algorithms such as t-SNE and UMAP to be superior to PCA, while neural network based methods fall behind.

bioinformatics↗

bioRxiv2021

Novel Fusarium Wilt Resistance Genes Uncovered in the Wild Progenitors and Heirloom Cultivars of Strawberry

Fusarium wilt, a soilborne disease caused by Fusarium oxysporum f. sp. fragariae, poses a significant threat to strawberry (Fragaria x ananassa) production in many parts of the world. This pathogen causes wilting, collapse, and death in susceptible genotypes. We previously identified a dominant gene (FW1) on chromosome 2B that confers resistance to race 1 of the pathogen and hypothesized that gene-for-gene resistance to Fusarium wilt was widespread in strawberry. To explore this, a genetically diverse collection of heirloom and modern cultivars and wild octoploid ecotypes were screened for resistance to Fusarium wilt races 1 and 2. Here we show that resistance to both races is widespread and that resistance to race 1 is mediated by dominant genes (FW1, FW2, FW3, FW4, and FW5) on three non-homoeologous chromosomes (1A, 2B, and 6B). The resistance proteins encoded by these genes are not yet known; however, plausible candidates were identified that encode pattern recognition receptor or other proteins known to mediate gene-for-gene resistance in plants. High-throughput genotyping assays for SNPs in linkage disequilibrium with FW1-FW5 were developed to facilitate marker-assisted selection and accelerate the development of race 1 resistant cultivars. This study laid the foundation for identifying the genes encoded by FW1-FW5, in addition to exploring the genetics of resistance to race 2 and other races of the pathogen, as a precaution to averting a Fusarium wilt pandemic. Key MessageSeveral race-specific resistance genes were identified and rapidly deployed via marker-assisted selection to develop strawberry cultivars resistant to Fusarium wilt, a devastating soil-borne disease.

plant biology↗

bioRxiv2021

Blueprint for Phasing and Assembling the Genomes of Heterozygous Polyploids: Application to the Octoploid Genome of Strawberry

The challenge of allelic diversity for assembling haplotypes is exemplified in polyploid genomes containing homoeologous chromosomes of identical ancestry, and significant homologous variation within their ancestral subgenomes. Cultivated strawberry (Fragaria x ananassa) and its wild progenitors are outbred octoploids (2n = 8x = 56) in which up to eight homologous and homoeologous alleles are preserved. This introduces significant risk of haplotype collapse, switching, and chimeric fusions during assembly. Using third generation HiFi sequences from PacBio, we assembled the genome of the day-neutral octoploid F. x ananassa hybrid Royal Royce from the University of California. Our goal was to produce subgenome-and haplotype-resolved assemblies of all 56 chromosomes, accurately reconstructing the parental haploid chromosome complements. Previous work has demonstrated that partitioning sequences by parental phase supports direct assembly of haplotypes in heterozygous diploid species. We leveraged the accuracy of HiFi sequence data with pedigree-informed sequencing to partition long read sequences by phase, and reduce the downstream risk of subgenomic chimeras during assembly. We were able to utilize an octoploid strawberry recombination breakpoint map containing 3.6 M variants to identify and break chimeric junctions, and perform scaffolding of the phase-1 and phase-2 octoploid assemblies. The N50 contiguity of the phase-1 and phase-2 assemblies prior to scaffolding and gap-filling was 11 Mb. The final haploid assembly represented seven of 28 chromosomes in a single contiguous sequence, and averaged fewer than three gaps per pseudomolecule. Additionally, we re-annotated the octoploid genome to produce a custom F. x ananassa repeat library and improved set of gene models based on IsoSeq transcript data and an expansive RNA-seq expression atlas. Here we present FaRR1, a gold-standard reference genome of F. x ananassa cultivar Royal Royce to assist future genomic research and molecular breeding of allo-octoploid strawberry.

genomics↗

bioRxiv2021

Cost-effective, high-throughput phenotyping system for 3D reconstruction of fruit form

Reliable phenotyping methods that are simple to operate and inexpensive to deploy are critical for studying quantitative traits in plants. Traditional fruit shape phenotyping relies on human raters or 2D analyses to assess form, e.g., size and shape. Systems for 3D imaging using multi-view stereo have been implemented, but frequently rely on commercial software and/or specialized hardware, which can lead to limitations in accessibility and scalability. We present a complete system constructed of consumer-grade components for capturing, calibrating, and reconstructing the 3D form of small-to-moderate sized fruits and tubers. Data acquisition and image capture sessions are 9 seconds to capture 60 images. The initial prototype cost was $1600 USD. We measured accuracy by comparing reconstructed models of 3D printed ground truth objects to the original digital files of those same ground truth objects. The R2 between length of the primary, secondary, and tertiary axes, volume, and surface area of the ground-truth object and the reconstructed models was > 0.97 and root-mean square error (RMSE) was <3mm for objects without locally concave regions. Measurements from 1mm and 2mm resolution reconstructions were consistent (R2 > 0.99). Qualitative assessments were performed on 48 fruit and tubers, including 18 strawberries, 12 potatoes, 5 grapes, 7 peppers, and 4 Bosc and 2 red Anjou pears. Our proposed phenotyping system is fast, relatively low cost, and has demonstrated accuracy for certain shape classes, and could be used for the 3D analysis of fruit form.

plant biology↗

bioRxiv2021

Genomic Heritability: A Ragged Diagonal Between Bias and Variance

Many important traits in plants, animals, and microbes are polygenic and are therefore difficult to improve through traditional marker-assisted selection. Genomic prediction addresses this by enabling the inclusion of all genetic data in a mixed model framework. The main method for predicting breeding values is genomic best linear unbiased prediction (GBLUP), which uses the realized genomic relationship or kinship matrix (K) to connect genotype to phenotype. The use of relationship matrices allows information to be shared for estimating the genetic values for observed entries and predicting genetic values for unobserved entries. One of the key parameters of such models is genomic heritability [Formula], or the variance of a trait associated with a genome-wide sample of DNA polymorphisms. Here we discuss the relationship between several common methods for calculating the genomic relationship matrix and propose a new matrix based on the average semivariance that yields accurate estimates of genomic variance in the observed population regardless of the focal population quality as well as accurate breeding value predictions in unobserved samples. Notably, our proposed method is highly similar to the approach presented by Legarra (2016) despite different mathematical derivations and statistical perspectives and only deviates from the classic approach presented in VanRaden (2008) by a scaling factor. With current approaches, we found that the genomic heritability tends to be either over- 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 and that, unlike its predecessors, our newly proposed kinship matrix KASV yields accurate estimates of [Formula] in the observed population, generalizes to larger populations, and produces BLUPs equivalent to common methods in plants and animals.

genetics↗

bioRxiv2021

Genomic Prediction of Strawberry Resistance to Postharvest Fruit Decay Caused by the Fungal Pathogen Botrytis cinerea

Gray mold, a disease of strawberry (Fragaria x ananassa) caused by the ubiquitous necrotroph Botrytis cinerea, renders fruit unmarketable and causes economic losses in the postharvest supply chain. To explore the feasibility of selecting for increased resistance to gray mold, we undertook genetic and genomic prediction studies in strawberry populations segregating for fruit quality and shelf life traits hypothesized to pleiotropically affect susceptibility. As predicted, resistance to gray mold was heritable but quantitative genetically complex. While every individual was susceptible, the speed of symptom progression and severity differed. Narrow-sense heritability ranged from 0.38-0.71 for lesion diameter (LD) and 0.39-0.44 for speed of emergence of external mycelium (EM). Even though significant additive genetic variation was genome wide observed for LD and EM, the phenotypic ranges were comparatively narrow and genome-wide analyses did not identify any large effect loci. Genomic selection accuracy ranged from 0.28-0.59 for LD and 0.37-0.47 for EM. Additive genetic correlations between fruit quality and gray mold resistance traits were consistent with prevailing hypotheses: LD decreased as titratable acidity increased, whereas EM increased as soluble solid whole genome content decreased and firmness increased. We concluded that phenotypic and genomic selection could be regression effective for reducing LD and increasing EM, especially in long shelf life populations, but that a significant fraction of the genetic variation for resistance to gray mold was caused by the pleiotropic effects of fruit quality traits that differ among market and shelf life classes.

genetics↗

bioRxiv2019

Chromosome Evolution of Octoploid Strawberry

The allo-octoploid cultivated strawberry (Fragaria x ananassa) originated through a combination of polyploid and homoploid hybridization, domestication of an interspecific hybrid lineage, and continued admixture of wild species over the last 300 years. While genes appear to flow freely between the octoploid progenitors, the genome structures and diversity of the octoploid species remain poorly understood. The complexity and absence of an octoploid genome frustrated early efforts to study chromosome evolution, resolve subgenomic structure, and develop a single coherent linkage group nomenclature. Here, we show that octoploid Fragaria species harbor millions of subgenome-specific DNA variants. Their diversity was sufficient to distinguish duplicated (homoeologous and paralogous) DNA sequences and develop 50K and 850K SNP genotyping arrays populated with co-dominant, disomic SNP markers distributed throughout the octoploid genome. Whole-genome shotgun genotyping of an interspecific segregating population yielded 1.9M genetically mapped subgenome variants in 5,521 haploblocks spanning 3,394 cM in F. chiloensis subsp. lucida, and 1.6M genetically mapped subgenome variants in 3,179 haploblocks spanning 2,017 cM in F. x ananassa. These studies provide a dense genomic framework of subgenome-specific DNA markers for seamlessly cross-referencing genetic and physical mapping information, and unifying existing chromosome nomenclatures. Through comparative genetic mapping, we show that the genomes of geographically diverse wild octoploids are effectively diploidized and completely collinear. The preservation of genome structure among allo-octoploid taxa is a critical factor in the unique history of garden strawberry, where unimpeded gene flow supported both its origin and domestication through repeated cycles of interspecific hybridization.

genomics↗

bioRxiv2019

Multi-Dimensional Machine Learning Approaches for Fruit Shape Recognition and Phenotyping in Strawberry

BackgroundShape is a critical element of the visual appeal of strawberry fruit and determined by both genetic and non-genetic factors. Current fruit phenotyping approaches for external characteristics in strawberry rely on the human eye to make categorical assessments. However, fruit shape is multi-dimensional, continuously variable, and not adequately described by a single quantitative variable. Morphometric approaches enable the study of complex 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 features extracted from multiple morphometric analyses that are best fit for genome-wide and forward genetic analyses.\n\nResultsWe transformed images of strawberry fruit into human-recognizable categories using unsupervised machine learning, discovered four principal shape categories, and inferred progression using PPKC. We extracted 67 quantitative features from digital images of strawberries using a suite of morphometric analyses and multi-variate approaches. These analyses defined informative feature sets that effectively captured quantitative differences between shape classes. Classification accuracy ranged from 68.9 - 99.3% for the newly created, genetically correlated phenotypic variables describing a shape.\n\nConclusionsOur 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 we applied in strawberry should apply to other fruits, vegetables, and specialty crops.

plant biology↗

bioRxiv2017

Genetic variants affecting plant size and chemical defenses jointly shape herbivory in Arabidopsis

Herbivorous insects exhibit strong feeding preferences when choosing among plant genotypes, yet experiments to map loci mediating plant susceptibility to herbivory rarely incorporate host choice. To address this gap, we applied genome-wide association (GWA) mapping to uncover genetic polymorphisms mediating damage from foraging insects (two populations of Scaptomyza flava) across a mixture of Arabidopsis thaliana genotypes in experimental enclosures. The effect of chemical defenses (glucosinolates) on herbivory depended on herbivore genotype. Unlike many studies that minimize the effects of host choice behavior, we also found a large effect of plant size on herbivory--likely through its effect on plant apparency--that was independent of herbivore genotype. These herbivory-associated loci are polymorphic at fine spatial scales, and thus have potential to shape variation in herbivory within natural populations. We also show that the polymorphism with the largest effect on herbivory underlies adaptive latitudinal variation in Arabidopsis plant size across Europe. Overall, our results provide genetic support for ecological observations that variation in both chemical defenses and non-canonical defense traits (e.g., plant size and phenology) jointly shapes plant-herbivore interactions.

plant biology↗