A practical examination of RNA isolation methods for European pear (Pyrus communis)

Improved SARS-CoV-2 RNA recovery in wastewater matrices using a CTAB-based extraction method

Wastewater-based epidemiology has allowed tracking the magnitude and distribution of SARS-CoV-2 in communities, allowing public health officials to prepare for impending outbreaks. While many factors influence recovery of SARS-CoV-2 from wastewater, proper extraction, concentration, and purification of RNA are key steps to ensure accurate detection of viral particles. The aim of this study was to compare the efficiency of four commonly used RNA extraction methods for detection of the SARS-CoV-2 RNA genome in sewage samples artificially inoculated with the virus, in order to identify a protocol that improves viral recovery. These methods included CTAB-based, TRIzol-based, and guanidinium thiocyanate (GTC)-based extraction procedures coupled with silica spin column-based purification, and an automated extraction/purification protocol using paramagnetic particles. Following RNA extraction, virus recovery rates were compared using RT-qPCR-based detection. The CTAB-based approach yielded the highest recovery rates and was the only method to consistently demonstrate stable virus recovery percentages regardless of the specific physicochemical characteristics of the samples tested. The TRIzol method proved to be the second most effective, yielding significantly higher recovery rates compared to both the GTC-based and the automated extraction methods. These results suggest that the CTAB-based approach could be a useful tool for the recovery of viral RNA from complex wastewater matrices.

Towards identification of postharvest fruit quality transcriptomic markers in Malus domestica

Gene expression is highly impacted by the environment and can be reflective of past events that affected developmental processes. It is therefore expected that gene expression can serve as a signal of a current or future phenotypic traits. In this paper we identify sets of genes, which we call Prognostic Transcriptomic Biomarkers (PTBs), that can predict firmness in Malus domestica (apple) fruits. In apples, all individuals of a cultivar are clones, and differences in fruit quality are due to the environment. The apples transcriptome responds to these differences in environment, which makes PTBs an attractive predictor of future fruit quality. PTBs have the potential to enhance supply chain efficiency, reduce crop loss, and provide higher and more consistent quality for consumers. However, several questions must be addressed. In this paper we answer the question of which of two common modeling approaches, Random Forest or ElasticNet, outperforms the other. We answer if PTBs with few genes are efficient at predicting traits. This is important because we need few genes to perform qPCR, and we answer the question if qPCR is a cost-effective assay as input for PTBs modeled using high-throughput RNA-seq. To do this, we conducted a pilot study using fruit texture in the 'Gala' variety of apples across several postharvest storage regiments. Fruit texture in 'Gala' apples is highly controllable by post-harvest treatments and is therefore a good candidate to explore the use of PTBs. We find that the RandomForest model is more consistent than an ElasticNet model and is predictive of firmness (r2 = 0.78) with as few as 15 genes. We also show that qPCR is reasonably consistent with RNA-seq in a follow up experiment. Results are promising for PTBs, yet more work is needed to ensure that PTBs are robust across various environmental conditions and storage treatments.

Transcriptomic approach to uncover dynamic events in the development of mid-season sunburn in apple fruit

Apples grown in high heat, high light, and low humidity environments are at risk for sun injury disorders like sunburn and associated crop losses. Understanding the physiological and molecular mechanisms underlying sunburn will support improvement of mitigation strategies and breeding for more resilient varieties. Numerous studies have highlighted key biochemical processes involved in sun injury, such as the phenylpropanoid and reactive oxygen species (ROS) pathways, demonstrating both enzyme activities and expression of related genes in response to sunburn conditions. Most previous studies have focused on at-harvest activity of a small number of genes in response to heat stress. Thus, it remains unclear how stress events earlier in the season affect physiology and gene expression. Here, we applied heat stress to mid-season apples in the field and collected tissue along a time course-24, 48, and 72 h following a heat stimulus-to investigate dynamic gene expression changes using a transcriptomic lens. We found a relatively small number of differentially expressed genes (DEGs) and enriched functional terms in response to heat treatments. Only a few of these belonged to pathways previously described to be involved in sunburn, such as the AsA-GSH pathway, while most DEGs had not yet been implicated in sunburn or heat stress in pome fruit.

A phased, chromosome-scale genome of 'Honeycrisp' apple (Malus domestica)

The apple cultivar 'Honeycrisp' has superior fruit quality traits, cold hardiness, and disease resistance, making it a popular breeding parent. However, it suffers from several physiological disorders, production, and postharvest issues. Despite several available apple genome sequences, understanding of the genetic mechanisms underlying cultivar-specific traits remains lacking. Here, we present a highly contiguous, fully phased, chromosome-level genome of 'Honeycrisp' apples, using PacBio HiFi, Omni-C, and Illumina sequencing platforms, with two assembled haplomes of 674 Mbp and 660 Mbp, and contig N50 values of 32.8 Mbp and 31.6 Mbp, respectively. Overall, 47,563 and 48,655 protein-coding genes were annotated from each haplome, capturing 96.8-97.4% complete BUSCOs in the eudicot database. Gene family analysis reveals most 'Honeycrisp' genes are assigned into orthogroups shared with other genomes, with 121 'Honeycrisp'-specific orthogroups. This resource is valuable for understanding the genetic basis of important traits in apples and related Rosaceae species to enhance breeding efforts.

Transcriptomics of Differential Ripening in 'd'Anjou' Pear (Pyrus communis L.)

Estimating maturity in pome fruits is a critical task that directs virtually all postharvest supply chain decisions. This is especially important for European pear (Pyrus communis) cultivars because losses due to spoilage and senescence must be minimized while ensuring proper ripening capacity is achieved (in part by satisfying a fruit chilling requirement). Reliable methods are lacking for accurate estimation of pear fruit maturity, and because ripening is maturity dependent it makes predicting ripening capacity a challenge. In this study of the European pear cultivar 'd'Anjou', we sorted fruit at harvest based upon on-tree fruit position to build contrasts of maturity. Our sorting scheme showed clear contrasts of maturity between canopy positions, yet there was substantial overlap in the distribution of values for the index of absorbance difference (I AD ), a non-destructive spectroscopic measurement that has been used as a proxy for pome fruit maturity. This presented an opportunity to explore a contrast of maturity that was more subtle than I AD could differentiate, and thus guided our subsequent transcriptome analysis of tissue samples taken at harvest and during storage. Using a novel approach that tests for condition-specific differences of co-expressed genes, we discovered genes with a phased character that mirrored our sorting scheme. The expression patterns of these genes are associated with fruit quality and ripening differences across the experiment. Functional profiles of these co-expressed genes are concordant with previous findings, and also offer new clues, and thus hypotheses, about genes involved in pear fruit quality, maturity, and ripening. This work may lead to new tools for enhanced postharvest management based on activity of gene co-expression modules, rather than individual genes. Further, our results indicate that modules may have utility within specific windows of time during postharvest management of 'd'Anjou' pear.

Selection of reference genes for RT-qPCR normalization in blueberry (Vaccinium corymbosum × angustifolium) under various abiotic stresses

As a small fruit rich in anthocyanins, blueberry (Vaccinium corymbosum × angustifolium) has become a focus of research in recent years for identifying genes related to anthocyanin transport and stress resistance mechanisms based on transcriptome sequencing. However, the lack of validated, stably expressed reference genes greatly limits the functional study of blueberry genes. Therefore, in this study, we selected 14 candidate reference genes from a blueberry transcriptome database and used three algorithms (geNorm, NormFinder and BestKeeper) to evaluate the expression stability of these genes in various organs at different fruit developmental stages under five abiotic stress conditions. EF1α, EIF and TBP were observed to be the most stable and were thus chosen as reference genes for quantitative real-time PCR. Measurement of the relative expression of VcMATE1 (European Nucleotide Archive accession number KF875433) in blueberry further verified the reliability of these reference genes, which may have great utility for determining the accuracy of gene expression analyses in future research on blueberry.

Transcriptome sequencing of Himalayan Raspberry (Rubus ellipticus) and development of simple sequence repeat markers

KEY MESSAGE

Rubus ellipticus is a wild crop having less number of EST-SSR markers. First attempt was made towards the transcriptomics data analysis and generation of EST-SSR markers which were used in genetic diversity and transferability studies.

ABSTRACT

Rubus ellipticus is a raspberry with yellow fruits, native to tropical and subtropical India and Asia. Leaves of Rubus ellipticus 'Kumarhatti' collection were utilized for cDNA library construction. More than 15 million sequencing reads were generated using NextSeq 500 Illumina RNA-seq technology. The DNASTAR software was used for de novo assembly from which 7777 unigenes with an average length of 500 bp was obtained. These unigenes were annotated using public databases, including NCBI non-redundant and gene ontology. De novo assembly of R. ellipticus unigenes found the highest similarity to apple than to other members of Rosaceae. This is the first attempt to use the Illumina platform of RNA sequencing and de novo assembly for R. ellipticus without a reference genome. In this study, unigenes were used for SSR marker development. ESTs containing SSR motifs were extracted using an online Microsatellite Identification Tool (MISA). SSR primers were designed from the SSR containing 704 EST sequences using the Websat software. Total 304 EST-SSRs primers were successfully designed, out of which 68 randomly selected primer pairs were custom synthesized and used for validation. Real-time PCR was also performed to analyze the relationship of transcriptional factors with fruit ripening. Out of 68 primer pairs, 61 were found to be informative in R. ellipticus, whereas 65 primer pairs were informative in the five tested genera of Rosaceae, i.e., pear, peach, apple, rose, and strawberry with 95.3% and 93.5% polymorphism, leading to the conclusion that these marker systems are very efficient to carryout diversity and cross transferability study in Rosaceae genera.