Comparative transcriptome profiling in a segregating peach

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Comparative transcriptome profiling in a segregating peach population with contrasting juiciness phenotypes Talia del Pozo, Simon Miranda, Mauricio Latorre, Felipe Olivares, Leonardo Pavez, Ricardo Gutiérrez, Jonathan Maldonado, Patricio Hinrichsen, Bruno Giorgio Defilippi, Ariel Orellana, and Mauricio Gonzalez J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.8b05177 • Publication Date (Web): 11 Jan 2019 Downloaded from http://pubs.acs.org on January 12, 2019

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Journal of Agricultural and Food Chemistry

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TITLE: Comparative transcriptome profiling in a segregating peach population with

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contrasting juiciness phenotypes.

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Talía del Pozo1,3, Simón Miranda1,2, Mauricio Latorre3,4,5,6, Felipe Olivares3, Leonardo Pavez7,8,

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Ricardo Gutiérrez9, Jonathan Maldonado3, Patricio Hinrichsen10, Bruno G. Defilippi11, Ariel

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Orellana4,12, Mauricio González*3,4.

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Chile. Camino La Pirámide 5750, Huechuraba, Santiago, Chile.

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Macul, Santiago, Chile.

Centro Tecnológico de Recursos Vegetales, Faculty of Sciences, Universidad Mayor, Santiago,

Laboratorio de Genética Molecular Vegetal, INTA, Universidad de Chile. Av. El Líbano 5524,

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Alimentos, Universidad de Chile. Av. El Líbano 5524, Santiago, Chile.

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Rancagua, Chile.

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851, 7th Floor, Santiago, Chile.

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Chile.

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Gana 1702, Santiago, Chile.

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(CECAD), University of Cologne, Cologne, Germany.

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Santa Rosa 11610, Santiago, Chile.

Laboratorio de Bioinformática y Expresión Génica, Instituto de Nutrición y Tecnología de los

FONDAP Center for Genome Regulation. Av. Blanco Encalada 2085, Santiago, Chile. Instituto de Ingeniería, Universidad de O’Higgins. Av. Libertador Bernardo O’Higgins 611,

Mathomics, Center for Mathematical Modeling, Universidad de Chile. Av. Almirante Beauchef

Instituto de Ciencias Naturales, Universidad de Las Américas. Av. Manuel Montt 948, Santiago,

Departamento de Ciencias Químicas y Biológicas, Universidad Bernardo O′Higgins. General

Cologne Excellence Cluster for Cellular Stress Responses in Aging-Associated Diseases

Laboratorio de Biotecnología, Instituto de Investigaciones Agropecuarias, INIA La Platina.

ACS Paragon Plus Environment

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11

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11610, Santiago, Chile.

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Santiago, Chile.

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*

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INTA,

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(+56)229781440. Avenida Macul 5524, Casilla 138-11, Santiago, Chile.

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Unidad de Poscosecha, Instituto de Investigaciones Agropecuarias, INIA La Platina. Santa Rosa

Centro de Biotecnología Vegetal, Facultad de Ciencias de la Vida, Universidad Andrés Bello,

Correspondence and requests for materials should be addressed to: Mauricio González, Ph.D. Universidad

de

Chile.

E-mail:

[email protected].


Telephone

number:

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ABSTRACT

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Cold storage of fruit is one of the methods most commonly employed to extend the postharvest

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lifespan of peaches (Prunus persica (L.) Batsch). However, fruit quality in this species is affected

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negatively by mealiness, a physiological disorder triggered by chilling injury after long periods of

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exposure to low temperature during storage and manifested mainly as a lack of juiciness, which

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ultimately modifies the organoleptic properties of peach fruit. The aim of this study was to identify

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molecular components and metabolic processes underlying mealiness in susceptible and non-

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susceptible segregants. Transcriptome and qRT-PCR profiling were applied to individuals with

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contrasting juiciness phenotypes in a segregating F2 population. Our results suggest that mealiness

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is a multiscale phenomenon, since juicy and mealy fruit display distinctive reprogramming

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processes affecting translational machinery and lipid, sugar and oxidative metabolism. The

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candidate genes identified may be useful tools for further crop improvement.

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Keywords: mealiness, gene expression, Prunus persica, cold storage, transcriptome.


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INTRODUCTION

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Peach and nectarine production in the Southern Hemisphere occurs in the opposite season to their

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final destination markets. Therefore, long-term cold storage (CS) is often applied during shipping

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in order to prevent postharvest deterioration. However, cold may induce chilling injury (CI) in

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fruit, affecting their quality during this period1. Manifestations of CI in peach fruit include hard-

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textured fruit with no juice (leatheriness), internal browning, red flesh pigmentation (bleeding),

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loss of flavor and mealiness or woolliness, which is the consumer perception of a dry and wooly

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texture due to lack of free juice1. Mealiness as a physiological disorder represents a major problem

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because its symptoms remain unnoticed until peaches reach customers at a ready-to-eat stage1.

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Different strategies have been attempted during the postharvest period to alleviate symptoms and

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reduce the economic impact of mealiness losses, such as storage in a controlled atmosphere with

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elevated CO2 and reduced O2 levels, as well as preconditioning and intermittent warming during

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shelf life2, 3 and/or exogenous pre-harvest hormone applications4, 5. Although these treatments may

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modify the moment of appearance or the severity of chilling injury symptoms1, mealiness still

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represents a major challenge, because its incidence and progression involve multiple factors such

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as cultivar type, seasonal variations, agricultural practices within each orchard and molecular

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determinants1.

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One of the classical hypotheses to explain this physiological disorder states that acclimation during

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CS would induce changes in cell wall polysaccharide composition, ultimately causing a reduction

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in tissue fragmentation and juice release, which is perceived as mealy texture6, 7. At a molecular

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level, mealiness would be associated with incomplete solubilizing of cell wall macromolecules due

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to an imbalance in the expression of transcripts and enzymatic activity of cell wall-modifying

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enzymes such as pectin methylesterases (PMEs) and polygalacturonases (PGs)6. This evidence

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emphasizes the importance of cell wall metabolism in the incidence of mealiness. However, recent


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reports have found the relevance of other processes operating in chilling injury symptoms,

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including phenolic metabolism and modification of fatty acid desaturation8, 9. Additionally, omic

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approaches suggest that mealiness is a more intricate disorder related to several metabolic

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rearrangements, involving hormonal control of ripening and differential accumulation of raffinose,

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xylose and amino acids10, 11. Previous global analyses performed by our group have been focused

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on unraveling the mealiness disorder by subjecting peaches to several storage conditions12-14, and

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comparing cultivar-specific responses to cold15. Contrasting genotypes can be an important

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approach for the comprehension of physiological and molecular mechanisms involved in the mealy

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phenotype. To explore the genetic factors involved in mealiness we recently analyzed a ‘Venus’ x

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‘Venus’ F2 population (VxV herein) to identify QTLs and proteins correlated with this

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physiological alteration16,

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reconfiguration operating in the mealiness syndrome, here we expanded our previous studies in

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VxV peach progeny, combining instrumental, molecular and genetic analysis. A comparison of the

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transcriptome was performed of individuals representing contrasting phenotypes for mealiness in

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the framework of an intra-specific population cross. The integrative approach sheds light on the

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understanding of molecular determinants governing this postharvest quality trait. Identification of

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candidate genes as molecular markers may also allow selecting cultivars less prone to develop

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mealiness symptoms.

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To get deeper insight into the molecular determinants and genic


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MATERIALS AND METHODS

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Plant material and genotyping

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To achieve a more homogeneous genetic background to study mealiness, this research was

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conducted on a F2 segregating population composed of 200 siblings resulting from self-pollination

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of a P. persica cv. ‘Venus’ (freestone, melting and yellow-flesh nectarine) individual. This

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population is referred to as VxV throughout this paper. The seedlings obtained were planted in a

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nursery located in Paine, close to Santiago, Chile (-33°48’11,6”S, 70°40’04,9”W; 407 m

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elevation). To confirm that each field-labeled plant effectively derived from the selfing of ‘Venus’,

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a set of 19 microsatellite (SSR) markers was used, with emphasis on those heterozygous in the

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parent. The complete population was genotyped with at least 12 of these markers used in

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fingerprinting of peaches and nectarines. The heterozygous informative markers used to confirm

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the VxV selfing condition were the following (ordered according to their assigned linkage groups):

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LG1: BPPCT-006, BPPCT-016; LG2: UDP98-025, UDP97-402; LG3: BPPCT-007, UDP97-403;

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LG4: UDP96-003, UDP98-024, CPPCT-028 and UDP97-402; LG 6: LG8: BPPCT-006, UDP98-

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409. We also used UDP98-420, a marker not yet localized. Note that two of these markers are

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multi-locus (BPPCT-006 and UDP97-402). The complete population was tested with this

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informative set of markers, discarding those genotypes that did not fit the corresponding

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segregation pattern (heterozygotes exhibiting the same allele combination as ‘Venus’ or

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homozygotes for either of the parent alleles) for at least one of the markers. Using this criterion,

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the rate of plants not belonging to the VxV population was below 5%. From the F2 population, 68

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individuals were selected and phenotyped for mealiness by instrumental analysis during two

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consecutive seasons (2008 and 2009).

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Fruit sampling

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To select the most homogeneous samples at optimum maturity, fruits were harvested at the

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commercially mature stage (H). 5 - 10 fruit per tree were collected from the middle part of the

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canopy according to skin background color and pulp firmness. Color, total soluble solids (TSS)

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and firmness were measured at harvest and after CS (Table S1). A color chart was used to measure

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the ground color with a scale (from DN1 = green to DN7 = orange) currently used by the peach

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industry, and all fruit were harvested at DN = 2 and 3 values. TSS was measured by a temperature-

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compensated refractometer and expressed as the percent of soluble solids in juice. Firmness was

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assessed in ten fruits per plant, using a penetrometer with an 8 mm plunger in two opposite sides of

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each previously peeled fruit, avoiding its suture. Fruits of each segregant were subjected to CS in a

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chamber at 4 °C (RH 95%) for 21 days, plus three days at 20 °C until reaching a ready-to-eat stage

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(shelf life). In this stage, mealiness was assessed in five to ten fruits per segregant in each season.

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At least three individuals of the population were selected among the trees whose fruit classified

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consistently as mealy or juicy in both seasons (the 5% extreme phenotypes). Mesocarp tissue of

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five fruits per selected individual was pooled and immediately frozen in liquid nitrogen for

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transcriptome and real time PCR analyses. The conditions for growing, harvesting, sample

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preparation and analysis were similar in the two seasons considered in this study.

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Instrumental assessment of mealiness

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Quantitative determination of mealiness was performed as previously described18. Briefly, 40 g of

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fruit tissue was placed into four layers of cheesecloth for juice extraction with a self-made press.

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Juice obtained by pressing was centrifuged at 6000 g for 10 min and the supernatant was recovered

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and weighed to determine the percentage of juice relative to the original fresh weight of the

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sample. Mealiness was evaluated after CS (21 days at 4 ºC plus three days at 20 ºC), when fruits


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reached a degree of softening equivalent to the ripening and eating stage (i.e. softening to about 1

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kg force = 9.8 N), which reflects the maximum expression of the disorder. Thus differences in

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juiciness are to be attributed to the incidence of mealiness, without significant distortion owing to

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lack of adequate ripeness. According to previous reports17, 18, fruits were classified as follows:

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mealy, which showed no more than 10% free juice w/w; partially mealy (10-20% w/w) and non-

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mealy or juicy (>20% w/w).

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RNA extraction, cDNA synthesis and qRT-PCR

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Total RNA was isolated according to Meisel et al19 from pools of fruits of each selected segregant

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in two consecutive seasons. RNA quality and quantity were assessed prior to and after DNase

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digestion by denaturing gel electrophoresis and photometric analysis (A260/280 ratio),

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respectively. Initially, 7 µg of total RNA was treated with Turbo DNase (Ambion) according to the

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manufacturer’s instructions. Total RNA (2 µg) was used as a template for reverse transcription

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reactions to synthesize single-stranded cDNA using M-MLV reverse transcriptase (Promega) and

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an oligo(dT)15 primer according to standard procedures. Gene-specific primer sets (Table S2) were

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designed by Primer3Plus to amplify DNA products between 70 and 200 bp. Quantitative RT-PCR

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(qRT-PCR) reactions were performed in a LightCycler (Roche) using SYBR Green to monitor

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cDNA amplification. A 1:20 dilution of cDNA was used in each reaction along with 1 µL of

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FastStart DNA Master SYBR Green I (Roche), 0.8 µL MgCl2 (25 mM) and 2.5 pmol of forward

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and reverse primers in a total volume of 10 µL. The following standard thermal profile was used:

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10 min at 95 °C, 40 cycles of 10 s at 95 °C and 15 s at 60 °C, with a final 10 s stage at 72 °C. Data

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were analyzed using LightCycler Software v.3 (Roche). Efficiency was determined for each

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sample and gene by LinRegPCR v.7.5 using data obtained from the exponential phase of each

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amplification plot. The quality of PCR reactions was determined by analysis of the dissociation


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and amplification curves. The products were resolved by 3% agarose gel electrophoresis to

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confirm the amplification of DNA fragments of expected sizes. The constitutively expressed genes

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RPII (RNA polymerase subunit), TEF2 (Translation elongation factor 2) and UBQ10 (Ubiquitin

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10)20 were evaluated for stability, to normalize qRT-PCR reactions. Transcript levels of genes of

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interest were normalized to the expression values of RPII, which was the most stably expressed

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gene under the tested conditions according to GeNorm software. qRT-PCR analysis was performed

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in three biological replicates, corresponding to fruits from three representative segregants (mealy

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and juicy phenotypes), and differences in gene expression levels between mealy and non-mealy

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fruits were analyzed by non-parametric Mann-Whitney U-tests, considering p < 0.05 as statistically

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significant.

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Microarray experiments

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For microarray experiments, the μPEACH 1.0 platform consisting of 4806 oligos (described in

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ESTree Consortium, 2005) was used to analyze transcriptome variation. Fruits from each

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previously selected segregant were subjected to RNA extraction. 1 µg of RNA was amplified and

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aminoallyl labeled using a MessageAmp II aRNA kit (Ambion) and 5-(3-aminoallyl)-2’-dUTP and

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then labeled with Cy3 or Cy5 for mealy and juicy genotypes, respectively (Reactive Dye Pack;

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Amersham). Two slides were used per sample for each comparison. Pre-hybridizations were

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carried out by soaking whole glass slides in a solution containing 5x SSC, 0.1% SDS and BSA

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0.1% at 55 ºC for at least 90 min. Then the slides were washed five times with distilled water and

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dried by centrifuging for 2 min at 800 g. Hybridizations were carried out in 50 µL of hybridization

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solution (5x SSC, 0.1% SDS, 40% formamide) containing 90 to 100 pmol of Cy3- and Cy5-

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labelled target cDNA. The glass slides were placed in a hybridization chamber and incubated at 49

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ºC in a thermal bath for 16 h. Then the slides were washed with 2x SSC 0.1% SDS four times for


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10 min. Six additional washes (three with 0.1x SSC 0.1% SDS and three with 0.1x SSC, for 10

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min each) at room temperature were performed before drying the glass slides by a brief

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centrifugation.

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Microarray images were acquired at 10 µm pixel resolution and quantified using a Scan Array

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Express system (PerkinElmer). Array data were analyzed using the R statistical environment,

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specifically with the microarray analysis tools available from Bioconductor Project. Data were

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background-subtracted and normalized using the LIMMA Bioconductor package. Data obtained

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from biological replicates were averaged, then linear models were applied. Differentially expressed

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genes (DEGs) were determined by a false discovery rate (FDR) ≤5% using empirical Bayesian

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methods, and p < 0.05 was considered statistically significant. Genes described here have been

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deposited in NCBI’s Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) and are

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accessible through GEO number GSE33027. Log2 ratios of average microarray expression in

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mealy and juicy tissues were calculated from DEGs and the resulting file was loaded onto the

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MapMan platform to generate the overview (Table S3). An enrichment analysis of bin categories

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was performed for the DEGs using Fisher’s exact test with Benjamini–Hochberg multiple testing

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correction. Categories with corrected p < 0.05 were considered enriched in relation to the total

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represented categories present in the μPEACH 1.0 platform.

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RESULTS

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Cold storage induces contrasting phenotypes of juiciness in the segregating VxV population.

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Our aim was to compare the transcription profiles within a cohort of genotypes in a segregating

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population, whose differences were due only to a contrasting phenotype of juiciness after CS. For

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this purpose, we selected fruits derived from a F2 population segregating for mealiness: they were


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analyzed for juice content after three weeks at 4 °C plus three days at 20 ºC. Figure 1A shows the

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juice content distribution of individuals. According to previous reports17, fruit showing no more

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than 10% w/w juice after the quantitative measurement were classified as mealy, whereas those

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with more than 20% w/w were considered juicy. Using this criterion, a noticeable seasonal

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influence on mealiness incidence was observed for most of the genotypes analyzed. During the

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first harvesting season, 44 genotypes (64%) exhibited juicy behavior versus 13 genotypes (20%)

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which became mealy after CS. However, this ratio was reversed during the second year (44%

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mealy genotypes versus 7% juicy). Therefore, to minimize the environmental factor in the analysis,

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fruits from genotypes consistently exhibiting a mealy or juicy phenotype after CS in both

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harvesting seasons were sampled. These fruits represented the extreme phenotypes for the trait of

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the segregating population (5% mealiest and 5% juiciest fruits). The samples were as

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homogeneous as possible in their maturity parameters (Table S1), since fruit maturity also has

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been reported to affect chilling injury susceptibility1. Consistent differences in these parameters

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were not detected either at harvest or after CS (Table S1).

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Quantitation of juice (Figure 1B) showed that samples with contrasting phenotypes for juiciness

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exhibited a remarkable difference in juice content, 26.6 ± 2.3% w/w to 32.0 ± 2.3% w/w for juicy

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fruit, compared to 2.1 ± 1.1% w/w to 2.5 ± 1.5% w/w for mealy fruit. In order to strengthen the

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characterization of the contrasting phenotypes, we analyzed by qRT-PCR the levels of expression

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of endopolygalacturonase (PG). Several studies have reported that lower activity, protein

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accumulation and transcript level of PG correlates with mealiness in peach fruit21, 22. As expected,

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fruit defined as mealy consistently showed lower levels of PG transcript (Figure 1C): nearly 50%

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of its expression compared to juicy fruit (0.45 ± 0.09 and 0.46 ± 0.05) in both seasons, confirming

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our initial fruit classification but also stressing the relevance of this gene as a molecular marker for

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the mealy phenotype.


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In summary, combining instrumental, genetic and molecular analyses in the VxV progeny we

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obtained a set of fruit representative of contrasting phenotypes for juiciness among the F2

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segregating population, which were selected for transcriptome analysis and qRT-PCR profiling.

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Expression profiles in mealy fruit reveal multiple alterations in functional categories of genes

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compared to juicy fruit

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The gene expression effect of CS on the occurrence of mealiness symptoms was assessed by

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comparing the transcriptome profiles, characterizing juicy and mealy fruit by microarray analysis.

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To focus on genes responsive to CS, only those with a false discovery rate (FDR) ≤5% and ≥1.5-

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fold change were considered in subsequent analyses. In total, we found 438 differentially

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expressed genes (DEGs) in the contrasting phenotypes evaluated (Table S3). Of these, 238 genes

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(54.3%) were up-regulated and 200 genes (45.7%) were down-regulated in juicy fruit compared to

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fruit exhibiting mealiness.

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To obtain a better understanding of transcriptome data, genes were classified functionally using

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MapMan categories. More than 70% of expressed transcripts could be assigned to functional

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categories and illustrated on pathway overview diagrams (Figure 2). An enrichment analysis of

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DEGs found in juicy and mealy fruit was also conducted to achieve better comprehension of

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functional categories correlated with each phenotype (Figure 3; Supplemental Table S3). The

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overview revealed several up- and down-regulated metabolic pathways operating on contrasting

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phenotypes after CS. Fruit of the juicy phenotype showed modifications in processes related to cell

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wall metabolism (Figure 2), such as cellulose and pectin metabolism (Supplemental Table S3).

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Genes involved in lipid metabolism and fatty acid desaturation were predominantly increased in

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juicy fruits, along with an important decrease in lipid breakdown, showing transcriptome

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modulation of cell structural components in response to CS. Interestingly, induction of genes


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encoding for enzymes involved in starch-sucrose interconversion was observed in juicy fruit, along

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with up-regulation of biosynthetic genes of sugars (raffinose, sorbitol and trehalose).

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Transcriptional induction of genes involved in terpene and phenylpropanoid biosynthesis was also

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observed in fruit of the juicy phenotype (Supplemental Table S3). By contrast, mealy fruit showed

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a general induction of pathways associated with redox impairment, such as the ascorbate-

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glutathione cycle and mitochondrial electron transport (Figure 2), as well as a general shutdown of

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minor CHO (Supplemental Table S3). Genes coding for UDP-glycosyltransferases, peroxidases

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and oxidases also accounted for substantial differences between juicy and mealy fruit.

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Our analysis revealed genome-wide changes in the transcriptome of fruit in response to CS,

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leading to differential transcription profiles in contrasting phenotypes. Juicy fruit showed changes

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in cell wall and lipid components, along with the activation of secondary and sugar metabolism,

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while mealy fruit exhibited transcription alterations related to redox and energetic processes.

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qRT-PCR profiling of contrasting phenotypes for juiciness

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Among the differentially expressed genes obtained by transcriptome analysis, we chose those

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representative of different functional categories for subsequent validation by qRT-PCR. Figure 4

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summarizes the genes that showed statistically significant differences in expression levels between

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mealy and juicy fruit in both harvest seasons. Cell wall-related genes coding for putative ß-D-

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xylosidase (BXL1, Figure 4A), cinnamyl alcohol dehydrogenase (CAD, Figure 4B) and pectin

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acetylesterase (PAE, Figure 4C) were differentially altered after CS. In mealy fruit, we observed an

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increase of 3.3 to 3.8- and 2.4 to 3.0-fold for BXL1 and PAE, respectively. CAD was up-regulated

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by 1.8 to 2.1-fold in juicy peaches. Similarly, genes related to stress response exhibited noticeable

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changes between juicy and mealy fruit. Following cold exposure, heat shock protein 70 (Hsp70,

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Figure 4F) and dehydration-induced protein 22 (RD22, Figure 4G) transcripts were significantly


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down-regulated nearly 2-fold in fruits with mealiness in both seasons. In contrast, stress-responsive

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genes coding for metallothionein (MT, Figure 4D) and pathogen-related protein 4B (PR-4B, Figure

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4E) increased between 1.5 to 2.7-fold in mealy fruit compared to healthy fruit. Transcriptome

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profiling showed that contrasting phenotypes of juiciness resulted in the alteration of lipid

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metabolism (Figure 3). Genes coding for C-4 sterol methyl oxidase (SMO), ceramide

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glucosyltransferase (CGT), 3-oxacyl-[acyl-carrier-protein] synthase (FAB1) and lipid transfer

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protein (LTP) showed higher expression levels in juicy fruit compared to mealy fruit (Figure 4H to

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K). Global analysis also showed that juicy and mealy fruit had differential transcription patterns

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for sugar and osmoprotectant metabolism (Figure 3). Among these alterations, proline

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dehydrogenase (ProDH, Figure 4L), sorbitol dehydrogenase (SDH, Figure 4H) and trehalose 6-

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phosphate phosphatase (TPP, Figure 4I) were induced in non-mealy fruit. The expression profile

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obtained by qRT-PCR agrees with transcriptome analysis, validating the transcriptional changes

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observed after storage at low temperature.

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DISCUSSION

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Cold storage is a common method for delaying metabolic processes involved in the senescence of

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peaches, thereby extending the postharvest lifespan of fruit. However, peaches frequently develop

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chilling injury symptoms during this period. Among these, the mealiness syndrome represents a

297

major problem, because its symptoms are only evident when the fruit is consumed. Mealiness

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characterization has been often addressed by comparing susceptible and tolerant varieties instead

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of focusing on the molecular response of individuals with closely related genetic background. We

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applied a global transcription profiling to individuals representing the contrasting phenotypes of

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juiciness in a segregating F2 population to identify components and features of molecular

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reprogramming processes occurring in susceptible and non-mealy fruit. After analyzing this


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population during two seasons, we observed differential transcriptional profiles in juicy and mealy

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fruit previously exposed to CS. Genes and distinctive metabolic processes were identified in juicy

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and mealy fruit, which may be involved in adaptation or cold-responsive mechanisms, as discussed

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below.

307 308

Juicy and mealy fruit display distinctive global profiles of cell wall remodeling

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Mealiness is characterized by a disruption of cell wall architecture associated with an imbalance of

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cell wall disassembly1, 6. The alteration of expression, enzymatic activity and abundance of cell

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wall-degrading and modifying enzymes has been previously described in mealiness susceptibility

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and progression21. Transcriptome analysis showed that juicy fruit exhibited higher expression of

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genes encoding for enzymes involved in the synthesis and degradation of cell wall components

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such as cellulose synthase, cellulase, pectate lyase and ß-1,4-glucanases (Table S3). Among the

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genes evaluated by qRT-PCR, BXL1 and PAE were induced in mealy fruit. A recent report showed

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that xylose content increased only in susceptible peach varieties10, which is consistent with the

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hydrolysis of xylose from hemicellulose substrates due to BXL1 activity. Previous studies have

318

suggested a possible role of BXL1 in chilling injury10,

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modification of cell wall properties and BXL1 in mealy phenotype deserves further analysis. Cold

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also induces changes in the activity of pectin-modifying enzymes, which may impact the rigidity

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of cell wall by changes in the Ca+2-pectin interactions24. Although the role of pectin methylesterase

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(PME) in the mealy phenotype has been previously addressed1, the role of PAE in the mealiness

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syndrome has not been yet investigated. PAE affects the physicochemical properties of cell wall

324

polysaccharides, decreasing digestibility of pectins and altering cell extensibility25. Thus PAE

325

could be associated with abnormal pectin depolymerization in the mealy phenotype, acting

326

similarly to PME. However, we found a significant increase of CAD expression in juicy fruit,

23.

However, the link between the


15


Page 16 of 38

327

which is involved in phenylpropanoid and lignin biosynthesis in fruit26. Juicy fruit may up-regulate

328

transcript levels in these routes as a protective mechanism to cold. Similar responses have been

329

previously observed in other fruit models27, 28.

330

Considering that mealy and juicy fruit exhibited differential transcription profiles of processes

331

involved in synthesis and degradation of cell wall components, specific reconfigurations of cell

332

wall structure would occur in fruit susceptible to developing mealiness. Cell wall mechanical

333

properties involve pectate modification mediated by ROS signaling29. It is possible that ROS

334

imbalance observed in mealy fruit, as discussed in the following sections, might affect ROS

335

signaling, leading to an alteration in the metabolism of pectins. However, the impact of this

336

mechanism on the actual cell wall remodeling affecting susceptible fruit remains to be elucidated.

337 338

Cold storage activates differential stress response in contrasting phenotypes for juiciness

339

Fruit exposed to cold temperatures for long periods usually perceive stress signals, activating

340

complex signaling cascades that ultimately induce defense mechanisms. Following exposure to

341

abiotic stress, levels of phytohormones and reactive oxygen species (ROS) are altered, triggering a

342

multiscale response characterized by changes in transcripts, metabolites and proteins that lead to

343

the re-establishment of cell homeostasis30. Phytohormones such as jasmonic acid (JA), abscisic

344

acid (ABA) and ethylene play pivotal roles among the defense mechanisms in regulating stress-

345

response processes that may confer cold tolerance30, 31. Our transcriptome comparison revealed

346

significant up-regulation of JA-responsive elements in juicy fruit (Table S3). Additionally, a

347

remarkable induction of genes involved in terpene and phenylpropanoid synthesis was found in

348

fruit with the ability to retain juice after CS (Figure 2, Table S3). In another report, grapefruit

349

exposed to chilling conditions showed transcriptional alteration of biosynthetic pathways of

350

secondary metabolites, presumably as part of a chilling tolerance response32. Both hormonal and


16

Page 17 of 38


351

secondary metabolism changes observed in this study are likely linked to cold stress response,

352

since components of both categories have been previously associated with abiotic stress in other

353

species33. However, it is also feasible that some of these changes could be involved in ripening

354

processes occurring in fruit susceptible or non-susceptible to mealiness, which may have

355

differential abilities to resume normal ripening, as previously discussed34.

356

Among the molecular responses activated by cold exposure in the contrasting phenotypes, we

357

evaluated the expression profile of stress-related genes. We observed increased abundance of heat

358

shock protein 70 (Hsp70) transcript in juicy fruit (Figure 4D). The induction of heat shock

359

proteins, most notably those of the hsp70 and hsp20 families, has been previously reported as a

360

possible factor contributing to decrease chilling injury in different crops35. Since heat shock

361

proteins may mitigate plasma membrane oxidative damages by enhancing antioxidant enzyme

362

activity at chilling temperatures36, juicy fruits may be capable of inducing larger amounts of Hsp70

363

as an adaptive mechanism, achieving higher cellular stability to withstand cold-induced oxidative

364

stress. A previous study found that small heat shock proteins were up-regulated during CS14,

365

suggesting that early induction of heat shock proteins may contribute to prevent chilling injury in

366

juicy fruit. Global analysis applied to juicy and mealy fruit identified other stress-responsive genes,

367

including pathogen-related protein 4B (PR-4B, Figure 4E) and dehydration-related protein 22

368

(RD22, Figure 4G). Dehydration-induced stress and abscisic acid increase the expression of RD22

369

transcript37. Thus it is possible that cold-triggered induction of Hsp70 and RD22 could be part of

370

an adaptive mechanism after long-term cold exposure. Juicy fruits display protective responses to

371

cope with stress, probably allowing them to resume normal ripening processes after CS16,

372

Interestingly, RD22 co-localizes with EPCCU8503, the nearest molecular marker to QTLs

373

associated with flesh bleeding and endocarp staining identified in linkage group 4 of the

374

‘Venus’x‘BigTop’ genetic map38. EPPCU8503 flanks the Melting Flesh locus (M), which includes


34.

17


Page 18 of 38

375

endoPG, responsible for a major QTL in linkage group 4 controlling both mealiness and

376

bleeding22, 39. Pathogen-related proteins are frequently associated with pathogen defense, but PR-4

377

proteins are inducible by wounding, phytohormones such as abscisic acid (ABA) or ethylene, and

378

sugar starvation40, 41. Members of the PR family are part of response mechanisms to cold stress,

379

since they are induced by chilling injury42. The exacerbated mitochondrial response in the mealy

380

phenotype (Figure 2) may suggest greater oxidative damage mediated by ROS, which would

381

correlate with the induction of PR gene expression.

382 383

Juicy fruits display lipid rearrangements conferring membrane stability that decreases

384

chilling injury

385

Lipid metabolism plays an important role in regulating the fluidity of the plasma membrane; its

386

participation in cold stress tolerance has been well documented43. Plants often respond to low

387

temperature exposure by increasing unsaturation or decreasing chain length of membrane lipid

388

components43. Cold stress-triggered membrane remodeling has been described as a complex

389

process that includes modifying lipid composition and protein abundance in the plasma membrane,

390

which maintains structural stability but also regulates signaling processes43,

391

transcriptome analysis showed that several genes involved in lipid metabolism were differentially

392

expressed in juicy fruit. These genes are involved in fatty acid and sphingolipid synthesis and lipid

393

degradation (Figure 2, Table S3). Sterols and sphingolipids such as sitosterol, stigmasterol and

394

ceramide glucoside participate in the regulation of the fluidity of the plasma membrane, since they

395

can form lipid microdomains with membrane-stabilizing properties in plant cold acclimation45.

396

Interestingly, DEGs involved in the synthesis of these molecules were found to be up-regulated in

397

juicy fruit (Table S3), including SMO and CGT (Figure 4H, I), two genes encoding for enzymes

398

involved in the last steps of phytosterol and ceramide glucoside biosynthesis, respectively. In


44.

In this study,

18

Page 19 of 38


399

addition, a member of the lipid transfer protein (LTP) family was also enhanced in juicy fruits

400

(Figure 4M). These proteins form a hydrophobic cavity that binds to acyl chains of fatty acids,

401

leading to lipid stabilizing effects46. Another LTP gene was found to be induced during and after

402

CS14, indicating that LTP plays a protective role in peach fruit both in cold acclimation and after

403

storage. Thus increased gene expression level in lipid metabolism observed in juicy fruits agrees

404

with its protective role in preserving membrane structure during temperature transition from CS to

405

normal ripening. Alternatively, it is also possible that modulation of lipid components of plasma

406

membrane could have a signaling role during cold stress perception17, 43.

407 408

Cold triggers differential gene expression profiles of sugar and oxidative metabolism

409

Cold produces complex modifications in redox state, ultimately leading to oxidative stress

410

responses. Cold stress increases reactive oxygen species (ROS) generated as an intermediate

411

cellular stress response47, which is one of the main factors leading to chilling injury. ROS can

412

affect membrane lipids, proteins and DNA and promote transcriptional changes in diverse target

413

genes, but also induce mechanisms of cold acclimation47. Transcription profiling showed induction

414

of oxidative stress-related processes such as the ascorbate-glutathione cycle and mitochondrial

415

electron transport in mealy fruit (Figure 3, Table S3), suggesting that cold exposure generates an

416

important oxidative imbalance in susceptible fruit. Several transcripts including thioredoxins

417

(TRXs) and glutaredoxins (GRXs) were up-regulated in juicy fruit (Table S3). GRXs are small

418

ubiquitous oxidoreductases of the TRX family, usually defined as redox regulators playing a role

419

in maintaining cellular redox homeostasis48. Interestingly, ectopic expression of AtGRXS17 in

420

tomato plants generates an acquired tolerance to chilling stress49. Transgenic plants exhibited

421

lower ion leakage, increased photochemical efficiency and accumulated higher levels of soluble

422

sugar compared to wild-type plants after chilling stress. Moreover, chilling tolerance correlated


19


Page 20 of 38

423

with increased antioxidant enzyme activities and lower levels of H2O2. Thus the accumulation of

424

these proteins may be an important factor in fine-tuning ROS levels under stressful conditions49.

425

Similarly, higher ascorbate peroxidase and MT transcript levels in mealy fruit (Figure 4D, Table

426

S3) may play a role in coping with high levels of oxidative stress in fruit exhibiting an impaired

427

redox state. Previous reports showed that ascorbate peroxidase and other ROS scavengers are up-

428

regulated after CS, suggesting that mealy fruit respond to the excess of ROS generated by ripening

429

and/or chilling injury12,

430

Arabidopsis thaliana, acting as H2O2 scavengers under cold stress50. An Arabidopsis mt2a

431

insertion mutant exhibited lower tolerance to cold stress, while a catalase cat2 mutant had higher

432

expression of the metallothionein gene after exposure to low temperature51. We also showed in the

433

Mapman overview (Figure 2) and Table S3 that several genes involved in saccharide-related

434

pathways were up-regulated in juicy fruit. Transcript levels involved in trehalose biosynthesis

435

showed increased levels in juicy fruit. Trehalose has been traditionally considered as an

436

osmoprotectant, since high levels of trehalose correlate with membrane and protein integrity52. A

437

previous transcriptome study proposed that trehalose can act as a putatively compatible solute that

438

may function together with other solutes while tolerance is induced53. Interestingly, several genes

439

related to the intermediate trehalose-6-phosphate (T6P) were up-regulated (Table S3). T6P has

440

been recently described as a sensor for available sucrose, shaping the kind of response to changing

441

environmental conditions54.

442

The transcriptional up-regulation of the raffinose oligosaccharide pathway found in juicy fruit may

443

result in an increase of monosaccharides and disaccharides53. A metabolomic analysis showed that

444

resistance to mealiness specifically correlated with higher levels of raffinose10. A number of

445

reports have suggested that disaccharides, galactinol, fructans and sugar alcohols may function

14.

MT proteins have also been shown to mediate ROS balance in


20

Page 21 of 38


446

directly as antioxidants rather than as osmoprotectants55,

56.

447

control damage due to ROS overproduction.

448

Our results also showed an important up-regulation of genes encoding for enzymes involved in the

449

biosynthesis of osmoprotectant metabolites. The transcript level of ProDH was decreased in mealy

450

fruit, which should lead to a higher level of proline as a possible mechanism. Other authors

451

reported that the oxidative-alleviating molecule GABA exogenously applied to peach fruits

452

reduces chilling injury by increasing proline levels due to decreased ProDH enzymatic activity

453

together with increased activity of proline biosynthetic enzymes57.

Thus trehalose and raffinose could

454 455

Cold induces global changes in protein metabolism

456

Intriguingly, a large number of transcripts involved in protein synthesis, degradation and

457

modification were enhanced in mealy fruit (Figure 3, Table S3). Our results agree with previous

458

studies that have also shown alterations in protein metabolism differentially affecting susceptible

459

and non-susceptible fruit12,

460

characterized by preferential synthesis of specific proteins functionally connected to cold stress

461

would occur in susceptible fruit. Considering that translation is a highly energy-demanding

462

process, it is possible that under severe stress conditions such as CS the translation machinery is

463

reduced, which correlates with the down-regulation of mitochondrial electron transport and ATP

464

synthesis components observed in juicy fruit (Figures 2, 3 and Table S3). Interestingly, the

465

extremophile Thellungiella halophila, a plant model for stress-tolerance58, shows expansion of the

466

ubiquitin-dependent protein modification gene family compared to its salt-sensitive relative A.

467

thaliana, suggesting that abiotic stresses trigger translational adjustment as a stress-regulatory

468

response59. Considering that over-represented processes in juicy fruit included other functional

469

categories, these metabolic rearrangements would probably confer increased tolerance to stress,

34.

As previously proposed34, a feasible ribosome response


21


Page 22 of 38

470

whereas mealy fruit may display other strategies to counteract this condition, such as increasing

471

preferential translational machinery.

472

Examining the genetic resources and discerning the molecular mechanisms of mealiness are

473

needed to implement an efficient strategy for the breeding of cultivars less prone to develop

474

mealiness symptoms. In this study we performed a transcriptome analysis after CS, comparing the

475

contrasting juiciness phenotypes in a P. persica segregating population with identical genetic

476

background. Our results reveal that complex gene networks are tightly connected to juiciness,

477

deepening our understanding of this quality trait. The set of genes identified could be validated in

478

other peach cultivars with different sensitivities to CS to prospect for breeding tools in order to

479

improve less tolerant cultivars. Integrating our findings with other information layers involving

480

broader omics data will improve the selection of molecular markers for breeding purposes.

481 482

Abbreviations

483

CS, Cold Storage; CI, Chilling Injury; RH, Relative Humidity; LG, Linkage Group; TSS, Total

484

Soluble Solids; SSC, Saline-Sodium Citrate buffer; SDS, Sodium Dodecyl Sulfate; BSA, Bovine

485

Serum Albumin; qRT-PCR, quantitative reverse transcription PCR; DEG, Differentially Expressed

486

Gene; FDR, False Discovery Rate; ABA, Abscisic Acid; SA, Salicylic Acid; JA, Jasmonic Acid;

487

GABA, Gamma-Aminobutyric Acid; T6P, Trehalose-6-Phosphate; M-MLV, Moloney Murine

488

Leukemia Virus.

489 490

Funding Sources

491

This study was supported by Funding Agency Grant CONICYT-Fondecyt 11160899, Redes

492

REDI170422 and PEP I-2018033 to TdP, Fondecyt 11150679 to ML, Basal Program AFB 170004

493

to AO and FONDAP 15090007 to MG and AO.


22

Page 23 of 38


494 495

Conflict of interest

496

The authors declare no competing financial interest.

497 498

Supporting information

499

The Supporting Information is available free of charge on the ACS Publications website at DOI:

500

Table S1. Fruit quality parameters for juicy and mealy fruits in both harvest seasons. Table S2.

501

Primer set used for RT-qPCR analysis. Table S3. Up- and down-regulated DEGs in mealy and

502

juicy fruits.


23


Page 24 of 38

503

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responses in the Arabidopsis photorespiratory mutant cat2 demonstrate that redox state is a key

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modulator of daylength-dependent gene expression, and define photoperiod as a crucial factor in

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Figure captions

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Figure 1. Characterization of VxV F2 segregating population. A) The population assayed was a

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F2 segregating population obtained from a controlled intra-specific cross of P. persica VxV.

680

Frequency of individuals (y-axis) and juice content (x-axis, informed as the percentage of juice)

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for 68 F2 genotypes in two consecutive harvest seasons (Seasons 1 and 2, respectively) evaluated

682

after CS for 21 days at 4 °C plus three days at 20 ºC are shown. Dashed line indicates the criterion

683

used to establish mealiness incidence (below 10% w/w). B) Percentage of juice in contrasting

684

phenotypes for juiciness. C) Relative expression of polygalacturonase PG normalized to RPII

685

determined in mesocarp tissue of peach fruit showing juicy or mealy phenotypes (white and black

686

bars, respectively). Data represent the mean of three biological replicates by condition (panels B

687

and C), corresponding to the representative trees of the most contrasting phenotypes (5% juiciest

688

and 5% very mealy) of a population segregating for mealiness in two seasons. Asterisks indicate

689

significant differences between juicy and mealy peaches (Mann-Whitney U-test, p < 0.05).

690 691

Figure 2. MapMan overview of cold storage-mediated gene expression changes involved in

692

different metabolic processes. The images were obtained using MapMan, showing different

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functional metabolic categories in peach fruit after CS for 21 days at 4 °C plus three days at 20 ºC.

694

Log2 ratios of average microarray expression in mealy and juicy fruit tissues were calculated and

695

the resulting file was loaded on the MapMan platform to generate the overview (Table S3).

696

Positive log2 values represented by red color indicate up-regulation and signify that those

697

transcripts are induced in juicy fruit, while negative values shown by blue color denote down-

698

regulation of the transcripts in juicy fruit. In both cases, color saturates at 1.5-fold change.

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Figure 3. Differentially expressed genes (up- and down-regulated) grouped by functional

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categories. Functional categories: 1: PS, 2: major CHO metabolism, 3: minor CHO metabolism, 4:

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glycolysis, 5: fermentation, 7: OPP, 8: TCA / org transformation, 9: mitochondrial electron

703

transport / ATP synthesis, 10: cell wall, 11: lipid metabolism, 13: amino acid metabolism, 15:

704

metal handling, 16: secondary metabolism, 17: hormone metabolism, 18: Co-factor and vitamin

705

metabolism, 20: stress, 21: redox, 23: nucleotide metabolism, 26: miscellaneous, 27: RNA, 28:

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DNA, 29: protein, 30: signaling, 31: cell, 33: development, 34: transport, 35: not assigned (total

707

data in Table S3). Asterisks indicate statistically enriched classes (hypergeometric distribution, p

Comparative transcriptome profiling in a segregating peach

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