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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2017

Sugar metabolism of the first thermophilic Planctomycetes Thermogutta terrifontis: comparative genomic and transcriptomic approache

Xanthan gum, a complex polysaccharide comprising glucose, mannose and glucuronic acid residues, is involved in numerous biotechnological applications in cosmetics, agriculture, pharmaceuticals, food and petroleum industries. Additionally, its oligosaccharides were shown to possess antimicrobial, antioxidant and few other properties. Yet, despite its extensive usage, little is known about xanthan gum degradation pathways and mechanisms.\n\nThermogutta terrifontis R1 was described as the first thermophilic representative of the Planctomycetes phylum. As other cultivated planctomycetes, it grows well on various carbohydrates including oligo- and polysaccharides, however, its capability of anaerobic growth with or without electron acceptors was a novel finding among the representatives of this phylum.\n\nThe aim of this work is to examine T. terrifontis catabolic pathways with a special focus on the xanthan gum degradation pathway using genomic and transriptomic sequencing. Genomic analysis revealed more than a hundred glycosidases, polysaccharide lyases and other CAZymes, involved in oligo- and polysaccharide degradation by T. terrifontis, proteins of central carbohydrate metabolism and aerobic and anaerobic respiration. Furthermore, the combination of genomic and transcriptomic approaches revealed a putative novel xanthan gum degradation pathway involving unusual catalytic steps and enzymes: novel glycosidase(s) of DUF1080 family, hydrolyzing xanthan gum beta-glucosidic backbone linkages and beta-mannosidases instead of xanthan lyases for degradation of terminal beta-mannosidic linkages. Surprisingly, the genes coding DUF1080 proteins were found in high number in T. terrifontis and in many other Planctomycetes genomes, which, together with our observation that xanthan gum being a selective substrate for many planctomycetes, supports the important role of DUF1080 in xanthan gum degradation. Our findings shed light on the metabolism of the first thermophilic planctomycete, capable to degrade a number of polysaccharides, either aerobically or anaerobically, including the biotechnologically important bacterial polysaccharide xanthan gum. The results serve as good foundation for future exploration of T. terrifontis and its enzymes in biotechnological applications.

microbiology↗

bioRxiv2017

mosdepth: quick coverage calculation for genomes and exomes

Mosdepth is a new command-line tool for rapidly calculating genome-wide sequencing coverage. It measures depth from BAM (Li et al. 2009) or CRAM files at either each nucleotide position in a genome or for sets of genomic regions. Genomic regions may be specified as either a BED file to evaluate coverage across capture regions, or as a fixed-size window as required for copy-number calling. Mosdepth uses a simple algorithm that is computationally efficient and enables it to quickly produce optional coverage summaries. We demonstrate that mosdepth is faster than existing tools and provides flexibility in the types of coverage profiles produced.\n\nAvailabilitymosdepth is available from https://github.com/brentp/mosdepth under the MIT license..\n\nContactbpederse@gmail.com, aaronquinlan@gmail.com\n\nSupplementary informationDetailed documentation is available at https://github.com/brentp/mosdepth

bioinformatics↗

bioRxiv2017

Selective and mechanistic sources of recurrent rearrangements across the cancer genome

Cancer cells can acquire profound alterations to the structure of their genomes, including rearrangements that fuse distant DNA breakpoints. We analyze the distribution of somatic rearrangements across the cancer genome, using whole-genome sequencing data from 2,693 tumor-normal pairs. We observe substantial variation in the density of rearrangement breakpoints, with enrichment in open chromatin and sites with high densities of repetitive elements. After accounting for these patterns, we identify significantly recurrent breakpoints (SRBs) at 52 loci, including novel SRBs near BRD4 and AKR1C3. Taking into account both loci fused by a rearrangement, we observe different signatures resembling either single breaks followed by strand invasion or two separate breaks that become joined. Accounting for these signatures, we identify 90 pairs of loci that are significantly recurrently juxtaposed (SRJs). SRJs are primarily tumor-type specific and tend to involve genes with tissue-specific expression. SRJs were frequently associated with disruption of topology-associated domains, juxtaposition of enhancer elements, and increased expression of neighboring genes. Lastly, we find that the power to detect SRJs decreases for short rearrangements, and that reliable detection of all driver SRJs will require whole-genome sequencing data from an order of magnitude more cancer samples than currently available.

cancer biology↗

bioRxiv2017

Generation and validation of homozygous fluorescent knock-in cells using genome editing

Gene tagging with fluorescent proteins is essential to investigate the dynamic properties of cellular proteins. CRISPR/Cas9 technology is a powerful tool for inserting fluorescent markers into all alleles of the gene of interest (GOI) and permits functionality and physiological expression of the fusion protein. It is essential to evaluate such genome-edited cell lines carefully in order to preclude off-target effects caused by either (i) incorrect insertion of the fluorescent protein, (ii) perturbation of the fusion protein by the fluorescent proteins or (iii) non-specific genomic DNA damage by CRISPR/Cas9. In this protocol1, we provide a step-by-step description of our systematic pipeline to generate and validate homozygous fluorescent knock-in cell lines.\n\nWe have used the paired Cas9D10A nickase approach to efficiently insert tags into specific genomic loci via homology-directed repair with minimal off-target effects. It is time- and cost-consuming to perform whole genome sequencing of each cell clone. Therefore, we have developed an efficient validation pipeline of the generated cell lines consisting of junction PCR, Southern Blot analysis, Sanger sequencing, microscopy, Western blot analysis and live cell imaging for cell cycle dynamics. This protocol takes between 6-9 weeks. Using this protocol, up to 70% of the targeted genes can be tagged homozygously with fluorescent proteins and result in physiological levels and phenotypically functional expression of the fusion proteins.\n\nEditorial SummaryThis protocol provides a detailed workflow describing how to insert fluorescent markers into all alleles of a gene of interest using CRISPR/Cas 9 technology and how to generate and validate homozygous fluorescent knock-in cell lines.

molecular biology↗

bioRxiv2017

miRNAgFree: prediction and profiling of novel microRNAs without genome assembly

The prediction of novel miRNA genes generally requires the availability of genome sequences in order to assess important properties such as the characteristic hairpin-shaped secondary structure. However, although the sequencing costs have decreased over the last years, still many important species lack an assembled genome of certain quality. We implemented an algorithm which for the first time exploits characteristic biogenesis features like the 5 homogeneity that can be assessed without genome sequences. We used a phylogenetically broad spectrum of well annotated animal genomes for benchmarking. We found that between 90-100% of the most expressed miRNA candidates (top quartile) corresponded to known miRNA sequences.

bioinformatics↗

bioRxiv2017

Genome-wide interaction study of stress-sensitivity and its prediction of major depressive disorder in UK Biobank and Generation Scotland

Individual response to stress is correlated with neuroticism and is an important predictor of both neuroticism and the onset of major depressive disorder (MDD). Identification of the genetics underpinning individual differences in response to negative events (stress-sensitivity) may improve our understanding of the molecular pathways involved, and its association with stress-related illnesses. We sought to generate a proxy for stress-sensitivity through modelling the interaction between SNP allele and MDD status on neuroticism score in order to identify genetic variants that contribute to the higher neuroticism seen in individuals with a lifetime diagnosis of depression compared to unaffected individuals. Meta-analysis of genome-wide interaction studies (GWIS) in UK Biobank (N = 23,092) and Generation Scotland: Scottish Family Health Study (N = 7,155) identified no genome-wide significance SNP interactions. However, gene-based tests identified a genome-wide significant gene, ZNF366, a negative regulator of glucocorticoid receptor function implicated in alcohol dependence (p = 1.48x10-7; Bonferroni-corrected significance threshold p < 2.79x10-6). Using summary statistics from the stress-sensitivity term of the GWIS, SNP heritability for stress-sensitivity was estimated at 5.0%. In models fitting polygenic risk scores of both MDD and neuroticism derived from independent GWAS, we show that polygenic risk scores derived from the UK Biobank stress-sensitivity GWIS significantly improved the prediction of MDD in Generation Scotland. This study may improve interpretation of larger genome-wide association studies of MDD and other stress-related illnesses, and the understanding of the etiological mechanisms underpinning stress-sensitivity.

genetics↗

bioRxiv2017

Mutational signatures reveal the role of RAD52 in p53-independent p21 driven genomic instability

BackgroundGenomic instability promotes evolution and heterogeneity of tumors. Unraveling its mechanistic basis is essential to design appropriate therapeutic strategies. In a recent study we reported an unexpected oncogenic property of p21WAF1/Cip1 showing that its chronic expression, in a p53-deficient environment, causes genomic instability by deregulating the replication licensing machinery.\n\nResultsExtending on this work we now demonstrate that p21WAF1/Cip1 can further fuel genomic instability by suppressing the repair capacity of low and high fidelity pathways that deal with nucleotide abnormalities. Consequently, fewer single nucleotide substitutions (SNSs) occur, while formation of highly deleterious DNA double-strand breaks (DSBs) is enhanced, crafting a characteristic mutational signature landscape. Guided by the mutational signatures formed, we found at the mechanistic level that the DSBs were repaired by Rad52-dependent Break-Induced Replication (BIR) and Single-Strand Annealing (SSA). Conversely, the error-free synthesis-dependent strand annealing (SDSA) repair route was deficient. Surprisingly, Rad52 was activated transcriptionally in an E2F1-dependent manner, rather than post-translationally as is common for DNA repair factor activation.\n\nConclusionsOur results signify the importance of mutational signatures as guides to disclose the \"repair history\" leading to genomic instability. In this vein, following this approach we unveiled how chronic p21WAF1/Cip1 expression rewires the repair process, identifying Rad52 as a source of genomic instability and a candidate therapeutic target.

cancer biology↗

bioRxiv2017

A unified computational framework for modeling genome-wide nucleosome landscape

Nucleosomes form the fundamental building blocks of eukaryotic chromatin, and previous attempts to understand the principles governing their genome-wide distribution have spurred much interest and debate in biology. In particular, the precise role of DNA sequence in shaping local chromatin structure has been controversial. This paper rigorously quantifies of the contribution of hitherto-debated sequence features - including G+C content, 10.5-bp periodicity, and poly(dA:dT) tracts - to three distinct aspects of genome-wide nucleosome landscape: occupancy, translational positioning and rotational positioning. Our computational framework simultaneously learns nucleosome number and nucleosome-positioning energy from genome-wide nucleosome maps. In contrast to other previous studies, our model can predict both in-vitro and in-vivo nucleosome maps in S. cerevisiae. We find that although G+C content is the primary determinant of MNase-derived nucleosome occupancy, MNase digestion biases may substantially influence this GC dependence. By contrast, poly(dA:dT) tracts are seen to deter nucleosome formation, regardless of the experimental method used. We further show that the 10.5-bp nucleotide periodicity facilitates rotational but not translational positioning. Applying our method to in-vivo nucleosome maps demonstrates that, for a subset of genes, the regularly-spaced nucleosome arrays observed around transcription start sites can be partially recapitulated by DNA sequence alone. Finally, in-vivo nucleosome occupancy derived from MNase-seq experiments around transcription termination sites can be mostly explained by the genomic sequence. Implications of these results and potential extensions of the proposed computational framework are discussed

bioinformatics↗

bioRxiv2017

Genomic Locus Modulating IOP in the BXD RI Mouse Strains

PurposeIntraocular pressure (IOP) is the primary risk factor for developing glaucoma. The present study examines genomic contribution to the normal regulation of IOP in the mouse.\n\nMethodsThe BXD recombinant inbred (RI) strain set was used to identify genomic loci modulating IOP. We measured the IOP from 532 eyes from 33 different strains. The IOP data will be subjected to conventional quantitative trait analysis using simple and composite interval mapping along with epistatic interactions to define genomic loci modulating normal IOP.\n\nResultsThe analysis defined one significant quantitative trait locus (QTL) on Chr.8 (100 to 106 Mb). The significant locus was further examined to define candidate genes that modulate normal IOP. There are only two good candidate genes within the 6 Mb over the peak, Cdh8 (Cadherin 8) and Cdh11 (Cadherin 11). Expression analysis on gene expression and immunohistochemistry indicate that Cdh11 is the best candidate for modulating the normal levels of IOP.\n\nConclusionsWe have examined the genomic regulation of IOP in the BXD RI strain set and found one significant QTL on Chr. 8. Within this QTL that are two potential candidates for modulating IOP with the most likely gene being Cdh11.

genetics↗

bioRxiv2017

Complete assembly of a dengue virus type 3 genome from a recent genotype III clade by metagenomic sequencing of serum

BackgroundMosquito-borne flaviviruses causing diseases such as dengue and Japanese encephalitis are devastating, particularly in the tropics. Although, multiple flaviviruses are known to co-circulate in India, when a patient presents with febrile illness, testing is usually limited to specific pathogens. Unbiased metagenomic sequencing of febrile cases can reveal the presence of multiple pathogens and provide complete genome information. Sequence information, a cornerstone for tracing virus evolution, is relevant for the design of vaccines and therapeutics. In order to assess the usefulness of unbiased metagenomic sequencing for the identification of viruses associated with febrile illness, we sequenced serum from four individuals and plasma from one individual, all hospitalized at a tertiary care centre in South India with severe or prolonged febrile illnesses, together with one healthy control in 2014.\n\nResultsWe identified and assembled a complete dengue virus type 3 (DENV3) sequence from the serum of a case classified as severe dengue. We also found a small number of Japanese encephalitis virus (JEV) sequences in the serum of two adults with febrile illness, including the one who had dengue. Phylogenetic analysis of the dengue sequence indicates that it belongs to a predominantly Asian, DENV3, genotype III clade. It had an estimated divergence time of 13.86 years (95% Highest Posterior Densities 12.94 - 14.83 years) with the closest Indian strain. Amino acid substitutions were present throughout the sequenced genome, including 11 substitutions in the antigenic envelope protein compared to the strain used for the development of the first commercial dengue vaccine. Of these one substitution (E361D) was unique and six were in critical antigenic sites.\n\nConclusionsWe demonstrate that both genome assembly and detection of a low number of viral sequences are possible by unbiased sequencing of clinical material. Complete dengue virus sequence analysis places the sequenced genome in a recent, predominantly Asian clade within genotype III of DENV3. The detection of JEV, an agent not routinely tested in febrile illness in India, warrants further analysis and highlights the need to study co-circulating flaviviruses in parallel.

microbiology↗

bioRxiv2017

Preovulatory oocyte aging in mice affects fertilization rate and embryonic genome activation

Delayed ovulation, or preovulatory aging, can seriously compromise the developmental competence of oocytes. In the present study, we have investigated the effect of preovulatory aging on preimplantation embryos. Delaying ovulation with the gonadotropin releasing hormone (GnRH) antagonist Cetrorelix led to a decline in 2-cell rate from 76 to 46%. From control mice, an average of 17 embryos per mouse was retrieved. This number decreased to a mean of 5 embryos per mouse after preovulatory aging, suggesting that fertilization is impaired by aging. For analysis of zygotic genome activation, 2-cell embryos were incubated with BrUTP, which was incorporated into nascent RNA and detected by immunohistochemistry. A 2.85-fold increase in fluorescence intensity was detected after aging, pointing to a precocious activation of the genome. A possible effect of preovulatory aging on genomic imprint maintenance was investigated at the 8-cell stage. Deep amplicon bisulfite sequencing of Igf2r, Snrpn, H19 and Pou5f1 showed no significant changes between embryos derived from preovulatory-aged oocytes and control embryos, indicating stable imprint maintenance throughout epigenetic reprogramming. We conclude that preovulatory aging of the oocyte affects fertilization and embryonic genomic activation.

developmental biology↗

bioRxiv2017

Robust identification of deletions in exome and genome sequence data based on clustering of Mendelian errors

Multiple tools have been developed to identify copy number variants (CNVs) from whole exome (WES) and whole genome sequencing (WGS) data. Current tools such as XHMM for WES and CNVnator for WGS identify CNVs based on changes in read depth. For WGS, other methods to identify CNVs include utilizing discordant read pairs and split reads and genome-wide local assembly with tools such as Lumpy and SvABA, respectively. Here, we introduce a new method to identify deletion CNVs from WES and WGS trio data based on the clustering of Mendelian errors (MEs). Using our Mendelian Error Method (MEM), we identified 127 deletions (inherited and de novo) in 2,601 WES trios from the Pediatric Cardiac Genomics Consortium, with a validation rate of 88% by digital droplet PCR. MEM identified additional de novo deletions compared to XHMM, and also identified sample switches, DNA contamination, a significant enrichment of 15q11.2 deletions compared to controls and eight cases of uniparental disomy. We applied MEM to WGS data from the Genome In A Bottle Ashkenazi trio and identified deletions with 97% specificity. MEM provides a robust, computationally inexpensive method for identifying deletions, and an orthogonal approach for verifying deletions called by other tools.

genetics↗

bioRxiv2017

Genomic Loci Modulating Retinal Ganglion Cell Death Following Elevated IOP in the Mouse

The present study was designed to identify genomic loci modulating the susceptibility of retinal ganglion cells (RGC) to elevated intraocular pressure (IOP) in the BXD recombinant inbred mouse strain set. IOP was elevated by injecting magnetic microspheres into the anterior chamber and blocking the trabecular meshwork using a handheld magnet to impede drainage. The IOP was then measured over the next 21 days. Only animals with IOP greater than 25 mmHg for two consecutive days or an IOP above 30 mmHg on a single day after microsphere-injection were used in this study. On day 21, mice were sacrificed and the optic nerve was processed for histology. Axons were counted for both the injected and the control eye in 49 BXD strains, totaling 181 normal counts and 191 counts associated with elevated IOP. The axon loss for each strain was calculated and the data were entered into genenetwork.org. The average number of normal axons in the optic nerve across all strains was 54,788 {+/-} 16% (SD), which dropped to 49,545 {+/-} 20% in animals with artificially elevated IOP. Interval mapping demonstrated a relatively similar genome-wide map for both conditions with a suggestive Quantitative Trait Locus (QTL) on proximal Chromosome 3. When the relative axon loss was used to generate a genome-wide interval map, we identified one significant QTL (p<0.05) on Chromosome 18 between 53.6 and 57 Mb. Within this region, the best candidate gene for modulating axon loss was Aldh7a1. Immunohistochemistry demonstrated ALDH7A1 expression in mouse RGCs. ALDH7A1 variants were not significantly associated with glaucoma in the NEIGHBORHOOD GWAS dataset, but this enzyme was identified as part of the butanoate pathway previously associated with glaucoma risk. Our results suggest that genomic background influences susceptibility to RGC degeneration and death in an inducible glaucoma model.

genetics↗

bioRxiv2017

Whole genome analysis reveals pathogenic potential of multi-drug resistant wastewater Escherichia coli

Wastewater treatment plants play an important role in the release of antibiotic resistance into the environment. It has been shown that wastewater contains multi-drug resistant Escherichia coli, but information on strain diversity is surprisingly scarce. Here we present an exceptionally large dataset on multidrug resistant Escherichia coli, originating from wastewater, over a thousand isolates were phenotypically characterized for twenty antibiotics and for 103 isolates whole genomes were sequenced. To our knowledge this is the first study documenting such a comprehensive diversity of multi-drug resistant Escherichia coli in wastewater. The genomic diversity of the isolates was unexpectedly high and contained a high number of resistance and virulence genes. To illustrate the genomic diversity of the isolates we calculated the pan genome of the wastewater Escherichia coli and found it to contain over sixteen thousand genes. To analyse this diverse dataset, we devised a computational approach correlating genotypic variation and resistance phenotype, this way we were able to identify not only known, but also candidate resistance genes. Finally, we could verify that the effluent of a wastewater treatment plant will contain multi-drug resistant Escherichia coli belonging to clinically important clonal groups.

bioinformatics↗

bioRxiv2017

The genome sequence of the wild tomato Solanum pimpinellifolium provides insights into salinity tolerance

Solanum pimpinellifolium, a wild relative of cultivated tomato, offers a wealth of breeding potential for several desirable traits such as tolerance to abiotic and biotic stresses. Here, we report the genome and annotation of S. pimpinellifolium LA0480. The LA0480 genome size (811 Mb) and the number of annotated genes (25,970) are within the range observed for other sequenced tomato species. We developed and utilized the Dragon Eukaryotic Analyses Platform (DEAP) to functionally annotate the LA0480 protein-coding genes. Additionally, we used DEAP to compare protein function between S. pimpinellifolium and cultivated tomato. Our data suggest enrichment in genes involved in biotic and abiotic stress responses. Moreover, we present phenotypic data from one field experiment that demonstrate a greater salinity tolerance for fruit-and yield-related traits in S. pimpinellifolium compared with cultivated tomato. To understand the genomic basis for these differences in S. pimpinellifolium and S. lycopersicum, we analyzed 15 genes that have previously been shown to mediate salinity tolerance in plants. We show that S. pimpinellifolium has a higher copy number of the inositol-3-phosphate synthase and phosphatase genes, which are both key enzymes in the production of inositol and its derivatives. Moreover, our analysis indicates that changes occurring in the inositol phosphate pathway may contribute to the observed higher salinity tolerance in LA0480. Altogether, our work provides essential resources to understand and unlock the genetic and breeding potential of S. pimpinellifolium, and to discover the genomic basis underlying its environmental robustness.

plant biology↗

bioRxiv2018

Fast automated reconstruction of genome-scale metabolic models for microbial species and communities

Genome-scale metabolic models are instrumental in uncovering operating principles of cellular metabolism and model-guided re-engineering. Recent applications of metabolic models have also demonstrated their usefulness in unraveling cross-feeding within microbial communities. Yet, the application of genome-scale models, especially to microbial communities, is lagging far behind the availability of sequenced genomes. This is largely due to the time-consuming steps of manual cura-tion required to obtain good quality models and thus physiologically meaningful simulation results. Here, we present an automated tool - CarveMe - for reconstruction of species and community level metabolic models. We introduce the concept of a universal model, which is manually curated and simulation-ready. Starting with this universal model and annotated genome sequences, CarveMe uses a top-down approach to build single-species and community models in a fast and scalable manner. We build reconstructions for two model organisms, Escherichia coli and Bacillus subtillis, as well as a collection of human gut bacteria, and show that CarveMe models perform similarly to manually curated models in reproducing experimental phenotypes. Finally, we demonstrate the scalability of CarveMe through reconstructing 5587 bacterial models. Overall, CarveMe provides an open-source and user-friendly tool towards broadening the use of metabolic modeling in studying microbial species and communities.

bioinformatics↗

bioRxiv2018

Genome analysis and data sharing informs timing of molecular events in pancreatic neuroendocrine tumour

Neuroendocrine tumours (NETs) are rare, slow growing cancers that present in a diversity of tissues. To understand molecular underpinnings of gastrointestinal (GINET) and pancreatic NETs (PNETs), we profiled 45 tumours combining exome, RNA, and shallow whole genome sequencing, as well as fluorescent in situ hybridization. In addition to expected somatic mutations and copy number alterations, we found that PNETs contained a highly consistent copy neutral loss-of-heterozygosity (CN-LOH) profile affecting over half of the genome; a greater percentage than any cancer analyzed to date. Our data indicates that onset of extreme autozygosity may be progressive, associated with metastasis, and initially triggered by the loss of DAXX/ATRX, and subsequent biallelic loss of MEN1. We confirmed this molecular timing model using targeted clinical sequencing data from an additional 43 NETs made available by the AACR GENIE project. Against this background of CN-LOH, several chromosomal regions consistently retained heterozygosity, suggesting selection for crucial allele-specific components specific to PNET progression and potential new therapeutic targets.\n\nStatement of significanceWe have discovered that pancreatic neuroendocrine tumours contain a characteristic pattern of copy neutral loss-of-heterozygosity affecting the majority of the genome following mutations of MEN1 and ATRX/DAXX. Against this background of loss-of-heterozygosity, specific genomic regions are consistently retained and may therefore contain vulnerable therapeutic targets for pancreatic neuroendocrine tumours.

cancer biology↗

bioRxiv2017

Genomic heritability estimates in sweet cherry reveal non-additive genetic variance is relevant for industry-prioritized traits

BackgroundSweet cherry is consumed widely across the world and provides substantial economic benefits in regions where it is grown. While cherry breeding has been conducted in the Pacific Northwest for over half a century, little is known about the genetic architecture of important traits. We used a genome-enabled mixed model to predict the genetic performance of 505 individuals for 32 phenological, disease response and fruit quality traits evaluated in the RosBREED sweet cherry crop data set. Genome-wide predictions were estimated using a repeated measures model for phenotypic data across 3 years, incorporating additive, dominance and epistatic variance components. Genomic relationship matrices were constructed with high-density SNP data and were used to estimate relatedness and account for incomplete replication across years.\n\nResultsHigh broad-sense heritabilities of 0.83, 0.77, and 0.75 were observed for days to maturity, firmness, and fruit weight, respectively. Epistatic variance exceeded 40% of the total genetic variance for maturing timing, firmness and powdery mildew response. Dominance variance was the largest for fruit weight and fruit size at 34% and 27%, respectively. Omission of non-additive sources of genetic variance from the genetic mode resulted in inflation of narrow-sense heritability but minimally influenced prediction accuracy of genetic values in validation. Predicted genetic rankings of individuals from single-year models were inconsistent across years, likely due to incomplete sampling of the population genetic variance.\n\nConclusionsPredicted breeding values and genetic values a measure revealed many high-performing individuals for use as parents and the most promising selections to advance for cultivar release consideration, respectively. This study highlights the importance of using the appropriate genetic model for calculating breeding values to avoid inflation of expected parental contribution to genetic gain. The genomic predictions obtained will enable breeders to efficiently leverage the genetic potential of North American sweet cherry germplasm by identifying high quality individuals more rapidly than with phenotypic data alone.

genetics↗