Evidence for the Involvement of Vernalization-related Genes in the Regulation of Cold-induced Ripening in ‘D’Anjou’ and ‘Bartlett’ Pear Fruit

Abstract

European pear (Pyrus communis L.) cultivars require a genetically pre-determined duration of cold-temperature exposure to induce autocatalytic system 2 ethylene biosynthesis and subsequent fruit ripening. The physiological responses of pear to cold-temperature-induced ripening have been well characterized, but the molecular mechanisms underlying this phenomenon continue to be elucidated. This study employed previously established cold temperature conditioning treatments for ripening of two pear cultivars, ‘D’Anjou’ and ‘Bartlett’. Using a time-course transcriptomics approach, global gene expression responses of each cultivar were assessed at four stages of developmental during the cold conditioning process. Differential expression, functional annotation, and gene ontology enrichment analyses were performed. Interestingly, evidence for the involvement of cold-induced, vernalization-related genes and repressors of endodormancy release was found. These genes have not previously been described to play a role in fruit during the ripening transition. The resulting data provide insight into cultivar-specific mechanisms of cold-induced transcriptional regulation of ripening in European pear, as well as a unique comparative analysis of the two cultivars with very different cold conditioning requirements.

Introduction

Pear (Pyrus spp.) is an economically important and nutritionally valuable tree fruit genus worldwide. European pear (Pyrus communis L.) cultivars are among the most widespread, commercially grown Pyrus members, and are cultivated in Europe, North America, South America, Africa, and Australia⁷⁹.

Functional annotation with Blast2GO

The master transcriptome fasta produced from the Illumina assembly was imported into OmicsBox version 1.1.135 (BioBam Bioinformatics S.L., Valencia, Spain) for functional annotation of expressed contigs using the Blast2GO feature⁸⁰. Contig sequences were identified by a blastx alignment against the NCBI ‘Viridiplantae’ database with and e-value specification of 10.0E-3. Gene ontology (GO) annotation was assigned using the ‘Map**’ and ‘Annotation’ features. Expression analysis was limited to the consensus sequence for each contig, and therefore in this paper we do not distinguish between specific alleles, highly similar gene family members.

Differential expression analysis

An Excel file was prepared containing ‘D’Anjou’ and ‘Bartlett’ RPKM data for each contig, treatment, and replicate. The data was imported into OmicsBox as a count table for use with a time course differential expression analysis feature, which employs the maSigPro R package⁷⁹. An additional experimental design matrix was imported, which dictated the number of time points and replicates (Supplementary File 10). The level of FDR control was set to 0.05, resulting in identification of significantly differentially expressed genes. A stepwise regression was employed to model the data and generate a list of all genes displaying significant linear or quadratic trends over the cold conditioning time course (R > 0.8)⁸⁰ (Supplementary File 3).

GO enrichment analysis

OmicsBox gene ontology (GO) enrichment analysis utilizing the Fisher’s Exact Test was employed⁸⁰. Due to many enriched GO terms, the resulting terms were reduced to only the most specific ontologies (p < 0.00001). Ontologies shared between ‘D’ Anjou’ and ‘Bartlett’ and unique to each cultivar were identified (Supplementary File 9).

qRT-PCR validation

qRT-PCR was performed as reported earlier²⁵. Briefly, RNA samples were treated with DNAseI to eliminate any DNA contamination according to the manufacturer’s methods (NEB, Ipswich, MA USA), prior to cDNA synthesis. RNA concentration was determined for each sample using a Nanodrop ND-8000 (ThermoFisher, MA, USA). RNA quality was verified using a denaturing gel and BioAnalyzer 2100 (Agilent, CA USA). For each sample, 500 ng of total RNA was used to generate first strand cDNA using the Invitrogen VILO kit (Life Technologies, Carlsbad, CA USA). Each cDNA preparation was quantified using a Qubit fluorimeter (Life Technologies - Carlsbad, CA, USA). The samples were diluted to a final concentration of 50 ng/uL. Initial qRT-PCR technical replicate reactions were prepared for each of the 90 selected genes using the iTaq Universal SYBR Green Supermix (BioRad, Hercules, CA). Primers for quantitative reverse transcriptase PCR (qRT-PCR) were designed from Pyrus ESTs or sequences derived from Malus × domestica transcripts related to various hormonal and environmental signaling pathways. 500 ng RNA for each sample (same as used for RNAseq) was used to generate 1st strand cDNA using the Invitrogen VILO kit (Life Technologies, Carlsbad, CA USA). cDNA preparations were then diluted to 50 ng/uL. qRT-PCR technical replicate reactions were prepared for each of the genes using the iTAq Universal SYBR Green Supermix with ROX reference dye (BioRad, Hercules, CA) per the manufacturer’s protocols with 100 ng of template cDNA. In a Strategene MX3005P, the following thermocycle profile was used: 95 °C initial disassociation for 150 s followed by 50 amplification cycles (95 °C for 30 s, 60 °C for 30 s, and 72 °C for 30 s) and a final, single cycle phase to generate a dissociation curve (95 °C for 150 s, 95 °C for 30 s, and 60 °C for 30 s). Using the LinRegPCR tool, we calculated the Cq values for each reaction^81,82 (Supplementary File 11).