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Fruit rot is a fungal disease complex that threatens cranberry yields in North American growing operations. Management of fruit rot is especially difficult because of the diversity of the infecting fungal species, and although infections take place early in the season, the pathogens usually remain latent in the ovary until the fruit ripen. Control methods heavily rely on fungicide applications, a practice that may be limited in viability long term. Breeding for fruit rot resistance (FRR) is essential for sustainable production. It is likely that field resistance is multifaceted and involves a myriad of traits that fortify cranberry plants against the biotic and abiotic stresses contributing to fruit rot. In this study, we identified quantitative trait loci (QTL) for FRR in a segregating population. Interestingly, a QTL associated with resistance was found to overlap with one associated with fruit epicuticular wax (ECW). A single-nucleotide polymorphism genotyping assay successfully identified accessions that exhibit the desired phenotypes (i.e., less rot and more ECW), thus making it a useful tool for marker-assisted selection. Candidate genes that may contribute to FRR and ECW were also identified. This work will expedite breeding for improved cranberry fruit quality.

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It has long been recognized that the community of organisms associated with plant roots is a critical component of the phytobiome and can directly or indirectly contribute to the overall health of the plant. The rhizosphere microbial community is influenced by a number of factors including the soil type, the species of plants growing in those soils, and in the case of cultivated plants, the management practices associated with crop production. Vaccinium species, such as highbush blueberry and American cranberry, are woody perennials that grow in sandy, acidic soils with low to moderate levels of organic matter and a paucity of nutrients. When properly maintained, fields planted with these crops remain productive for many years. In some cases, however, yields and fruit quality decline over time, and it is suspected that degenerating soil health and/or changes in the rhizosphere microbiome are contributing factors. Determining the assemblage of bacterial and fungal microorganisms typically associated with the rhizosphere of these crops is a critical first step toward addressing the complex issue of soil health. We hypothesized that since blueberry and cranberry are in the same genus and grow in similar soils, that their associated rhizosphere microbial communities would be similar to each other. We analyzed the eukaryotic (primarily fungal) and bacterial communities from the rhizosphere of representative blueberry and cranberry plants growing in commercial fields in New Jersey. The data presented herein show that while the bacterial communities between the crops is very similar, the fungal communities associated with each crop are quite different. These results provide a framework for examining microbial components that might contribute to the health of Vaccinium spp. crops in New Jersey and other parts of the northeastern U.S.

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BACKGROUND: As the global climate changes, periods of abiotic stress throughout the North American cranberry growing regions will become more common. One consequence of high temperature extremes and drought conditions is sunscald. Scalding damages the developing berry and reduces yields through fruit tissue damage and/or secondary pathogen infection. Irrigation runs to cool the fruit is the primary approach to controlling sunscald. However, it is water intensive and can increase fungal-incited fruit rot. Epicuticular wax functions as a barrier to various environmental stresses in other fruit crops and may be a promising feature to mitigate sunscald in cranberry. In this study we assessed the function of epicuticular wax in cranberries to attenuate stresses associated with sunscald by subjecting high and low epicuticular wax cranberries to controlled desiccation and light/heat exposure. A cranberry population that segregates for epicuticular wax was phenotyped for epicuticular fruit wax levels and genotyped using GBS. Quantitative trait loci (QTL) analyses of these data identified a locus associated with epicuticular wax phenotype. A SNP marker was developed in the QTL region to be used for marker assisted selection. RESULTS: Cranberries with high epicuticular wax lost less mass percent and maintained a lower surface temperature following heat/light and desiccation experiments as compared to fruit with low wax. QTL analysis identified a marker on chromosome 1 at position 38,782,094 bp associated with the epicuticular wax phenotype. Genotyping assays revealed that cranberry selections homozygous for a selected SNP have consistently high epicuticular wax scores. A candidate gene (GL1-9), associated with epicuticular wax synthesis, was also identified near this QTL region. CONCLUSIONS: Our results suggest that high cranberry epicuticular wax load may help reduce the effects of heat/light and water stress: two primary contributors to sunscald. Further, the molecular marker identified in this study can be used in marker assisted selection to screen cranberry seedlings for the potential to have high fruit epicuticular wax. This work serves to advance the genetic improvement of cranberry crops in the face of global climate change.

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Cranberry (Vaccinium macrocarpon) is a member of the Heath family (Ericaceae) and is a temperate low-growing woody perennial native to North America that is both economically important and has significant health benefits. While some native varieties are still grown today, breeding programs over the past 50 years have made significant contributions to improving disease resistance, fruit quality and yield. An initial genome sequence of an inbred line of the wild selection 'Ben Lear,' which is parent to multiple breeding programs, provided insight into the gene repertoire as well as a platform for molecular breeding. Recent breeding efforts have focused on leveraging the circumboreal V. oxycoccos, which forms interspecific hybrids with V. macrocarpon, offering to bring in novel fruit chemistry and other desirable traits. Here we present an updated, chromosome-resolved V. macrocarpon reference genome, and compare it to a high-quality draft genome of V. oxycoccos. Leveraging the chromosome resolved cranberry reference genome, we confirmed that the Ericaceae has undergone two whole genome duplications that are shared with blueberry and rhododendron. Leveraging resequencing data for 'Ben Lear' inbred lines, as well as several wild and elite selections, we identified common regions that are targets of improvement. These same syntenic regions in V. oxycoccos, were identified and represent environmental response and plant architecture genes. These data provide insight into early genomic selection in the domestication of a native North American berry crop.

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BACKGROUND: Bilberry (Vaccinium myrtillus L.) is one of the most abundant wild berries in the Northern European ecosystems. This species plays an important ecological role as a food source for many vertebrate and invertebrate herbivores. It is also well-recognized for its bioactive compounds, particularly substances involved in natural defenses against herbivory. These defenses are known to be initiated by leaf damage (e.g. chewing by insects) and mediated by activation of the jasmonic acid (JA) signaling pathway. This pathway can be activated by exogenous application of methyl jasmonate (MeJA), the volatile derivative of JA, which is often used to stimulate plant defense responses in studies of plant-herbivore interactions at ecological, biochemical, and molecular organismal levels. As a proxy for herbivore damage, wild V. myrtillus plants were treated in the field with MeJA and changes in gene expression were compared to untreated plants. RESULTS: The de novo transcriptome assembly consisted of 231,887 unigenes. Nearly 71% of the unigenes were annotated in at least one of the databases interrogated. Differentially expressed genes (DEGs), between MeJA-treated and untreated control bilberry plants were identified using DESeq. A total of 3590 DEGs were identified between the treated and control plants, with 2013 DEGs upregulated and 1577 downregulated. The majority of the DEGs identified were associated with primary and secondary metabolism pathways in plants. DEGs associated with growth (e.g. those encoding photosynthesis-related components) and reproduction (e.g. flowering control genes) were frequently down-regulated while those associated with defense (e.g. encoding enzymes involved in biosynthesis of flavonoids, lignin compounds, and deterrent/repellent volatile organic compounds) were up-regulated in the MeJA treated plants. CONCLUSIONS: Ecological studies are often limited by controlled conditions to reduce the impact of environmental effects. The results from this study support the hypothesis that bilberry plants, growing in natural conditions, shift resources from growth and reproduction to defenses while in a MeJA-induced state, as when under insect attack. This study highlights the occurrence of this trade-off at the transcriptional level in a realistic field scenario and supports published field observations wherein plant growth is retarded and defenses are upregulated.

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Ancient DNA (aDNA) studies often rely on standard methods of mutation calling, optimized for high-quality contemporary DNA but not for excessive contamination, time- or environment-related damage of aDNA. In the absence of validated datasets and despite showing extreme sensitivity to aDNA quality, these methods have been used in many published studies, sometimes with additions of arbitrary filters or modifications, designed to overcome aDNA degradation and contamination problems. The general lack of best practices for aDNA mutation calling may lead to inaccurate results. To address these problems, we present ARIADNA (ARtificial Intelligence for Ancient DNA), a novel approach based on machine learning techniques, using specific aDNA characteristics as features to yield improved mutation calls. In our comparisons of variant callers across several ancient genomes, ARIADNA consistently detected higher-quality genome variants with fast runtimes, while reducing the false positive rate compared with other approaches.

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Current human whole genome sequencing projects produce massive amounts of data, often creating significant computational challenges. Different approaches have been developed for each type of genome variant and method of its detection, necessitating users to run multiple algorithms to find variants. We present Genome Rearrangement OmniMapper (GROM), a novel comprehensive variant detection algorithm accepting aligned read files as input and finding SNVs, indels, structural variants (SVs), and copy number variants (CNVs). We show that GROM outperforms state-of-the-art methods on 7 validated benchmarks using 2 whole genome sequencing (WGS) data sets. Additionally, GROM boasts lightning-fast run times, analyzing a 50× WGS human data set (NA12878) on commonly available computer hardware in 11 minutes, more than an order of magnitude (up to 72 times) faster than tools detecting a similar range of variants. Addressing the needs of big data analysis, GROM combines in 1 algorithm SNV, indel, SV, and CNV detection, providing superior speed, sensitivity, and precision. GROM is also able to detect CNVs, SNVs, and indels in non-paired-read WGS libraries, as well as SNVs and indels in whole exome or RNA sequencing data sets.

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Segmented worms (Annelida) are among the most successful animal inhabitants of extreme environments worldwide. An unusual group of enchytraeid oligochaetes of genus Mesenchytraeus are abundant in the Pacific northwestern region of North America and occupy geographically proximal ecozones ranging from low elevation rainforests and waterways to high altitude glaciers. Along this altitudinal transect, Mesenchytraeus representatives from disparate habitat types were collected and subjected to deep mitochondrial and nuclear phylogenetic analyses. Our data identify significant topological discordance among gene trees, and near equivalent interspecific divergence levels indicative of a rapid radiation event. Collectively, our results identify a Mesenchytraeus 'explosion' coincident with mountain building in the Pacific northwestern region that gave rise to closely related aquatic, ice, snow and terrestrial worms.

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Comparative genomics studies typically limit their focus to single nucleotide variants (SNVs) and that was the case for previous comparisons of woolly mammoth genomes. We extended the analysis to systematically identify not only SNVs but also larger structural variants (SVs) and indels and found multiple mammoth-specific deletions and duplications affecting exons or even complete genes. The most prominent SV found was an amplification of RNase L (with different copy numbers in different mammoth genomes, up to 9-fold), involved in antiviral defense and inflammasome function. This amplification was accompanied by mutations affecting several domains of the protein including the active site and produced different sets of RNase L paralogs in four mammoth genomes likely contributing to adaptations to environmental threats. In addition to immunity and defense, we found many other unique genetic changes in woolly mammoths that suggest adaptations to life in harsh Arctic conditions, including variants involving lipid metabolism, circadian rhythms, and skeletal and body features. Together, these variants paint a complex picture of evolution of the mammoth species and may be relevant in the studies of their population history and extinction.

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Amplifications or deletions of genome segments, known as copy number variants (CNVs), have been associated with many diseases. Read depth analysis of next-generation sequencing (NGS) is an essential method of detecting CNVs. However, genome read coverage is frequently distorted by various biases of NGS platforms, which reduce predictive capabilities of existing approaches. Additionally, the use of read depth tools has been somewhat hindered by imprecise breakpoint identification. We developed GROM-RD, an algorithm that analyzes multiple biases in read coverage to detect CNVs in NGS data. We found non-uniform variance across distinct GC regions after using existing GC bias correction methods and developed a novel approach to normalize such variance. Although complex and repetitive genome segments complicate CNV detection, GROM-RD adjusts for repeat bias and uses a two-pipeline masking approach to detect CNVs in complex and repetitive segments while improving sensitivity in less complicated regions. To overcome a typical weakness of RD methods, GROM-RD employs a CNV search using size-varying overlapping windows to improve breakpoint resolution. We compared our method to two widely used programs based on read depth methods, CNVnator and RDXplorer, and observed improved CNV detection and breakpoint accuracy for GROM-RD. GROM-RD is available at http://grigoriev.rutgers.edu/software/.