Biology subjects

Famula, R. A.

Publications and source records attributed to Famula, R. A..

5 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↗

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

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

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↗