Molecular regulation of apple and grape ripening: exploring common and distinct transcriptional aspects of representative climacteric and non-climacteric fruits.

Fleshy fruits of angiosperms are organs specialized for promoting seed dispersal by attracting herbivores and enticing them to consume the organ and the seeds it contains. Ripening can be broadly defined as the processes serving as a plant strategy to make the fleshy fruit appealing to animals, consisting of a coordinated series of changes in color, texture, aroma, and flavor that result from an intricate interplay of genetically and epigenetically programmed events. The ripening of fruits can be categorized into two types: climacteric, which is characterized by a rapid increase in respiration rate typically accompanied by a burst of ethylene production, and non-climacteric, in which this pronounced peak in respiration is absent. Here we review current knowledge of transcriptomic changes taking place in apple (Malus × domestica, climacteric) and grapevine (Vitis vinifera, non-climacteric) fruit during ripening, with the aim of highlighting specific and common hormonal and molecular events governing the process in the two species. With this perspective, we found that specific NAC transcription factor members participate in ripening initiation in grape and are involved in restoring normal physiological ripening progression in impaired fruit ripening in apple. These elements suggest the existence of a common regulatory mechanism operated by NAC transcription factors and auxin in the two species.

Heterogeneous networks integration for disease-gene prioritization with node kernels.

MOTIVATION: The identification of disease-gene associations is a task of fundamental importance in human health research. A typical approach consists in first encoding large gene/protein relational datasets as networks due to the natural and intuitive property of graphs for representing objects' relationships and then utilizing graph-based techniques to prioritize genes for successive low-throughput validation assays. Since different types of interactions between genes yield distinct gene networks, there is the need to integrate different heterogeneous sources to improve the reliability of prioritization systems. RESULTS: We propose an approach based on three phases: first, we merge all sources in a single network, then we partition the integrated network according to edge density introducing a notion of edge type to distinguish the parts and finally, we employ a novel node kernel suitable for graphs with typed edges. We show how the node kernel can generate a large number of discriminative features that can be efficiently processed by linear regularized machine learning classifiers. We report state-of-the-art results on 12 disease-gene associations and on a time-stamped benchmark containing 42 newly discovered associations. AVAILABILITY AND IMPLEMENTATION: Source code: https://github.com/dinhinfotech/DiGI.git. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Transcriptomic Insights on the Preventive Action of Apple (cv Granny Smith) Skin Wounding on Superficial Scald Development.

Superficial scald is a post-harvest chilling storage injury leading to browning of the surface of the susceptible cv Granny Smith apples. Wounding of skins has been reported to play a preventive role on scald development however its underlying molecular factors are unknown. We have artificially wounded the epidermal and sub-epidermal layers of apple skins consistently obtaining the prevention of superficial scald in the surroundings of the wounds during two independent vintages. Time course RNA-Seq analyses of the transcriptional changes in wounded versus unwounded skins revealed that two transcriptional waves occurred. An early wave included genes up-regulated by wounding already after 6 h, highlighting a specific transcriptional rearrangement of genes connected to the biosynthesis and signalling of JA, ethylene and ABA. A later transcriptional wave, occurring after three months of cold storage, included genes up-regulated exclusively in unwounded skins and was prevented from its occurrence in wounded skins. A significant portion of these genes was related to decay of tissues and to the senescence hormones ABA, JA and ethylene. Such changes suggest a wound-inducible reversed hormonal balance during post-harvest storage which may explain the local inhibition of scald in wounded tissues, an aspect that will need further studies for its mechanistic explanation.

ShaKer: RNA SHAPE prediction using graph kernel.

SUMMARY: SHAPE experiments are used to probe the structure of RNA molecules. We present ShaKer to predict SHAPE data for RNA using a graph-kernel-based machine learning approach that is trained on experimental SHAPE information. While other available methods require a manually curated reference structure, ShaKer predicts reactivity data based on sequence input only and by sampling the ensemble of possible structures. Thus, ShaKer is well placed to enable experiment-driven, transcriptome-wide SHAPE data prediction to enable the study of RNA structuredness and to improve RNA structure and RNA-RNA interaction prediction. For performance evaluation, we use accuracy and accessibility comparing to experimental SHAPE data and competing methods. We can show that Shaker outperforms its competitors and is able to predict high quality SHAPE annotations even when no reference structure is provided. AVAILABILITY AND IMPLEMENTATION: ShaKer is freely available at https://github.com/BackofenLab/ShaKer.

Freiburg RNA tools: a central online resource for RNA-focused research and teaching.

The Freiburg RNA tools webserver is a well established online resource for RNA-focused research. It provides a unified user interface and comprehensive result visualization for efficient command line tools. The webserver includes RNA-RNA interaction prediction (IntaRNA, CopraRNA, metaMIR), sRNA homology search (GLASSgo), sequence-structure alignments (LocARNA, MARNA, CARNA, ExpaRNA), CRISPR repeat classification (CRISPRmap), sequence design (antaRNA, INFO-RNA, SECISDesign), structure aberration evaluation of point mutations (RaSE), and RNA/protein-family models visualization (CMV), and other methods. Open education resources offer interactive visualizations of RNA structure and RNA-RNA interaction prediction as well as basic and advanced sequence alignment algorithms. The services are freely available at http://rna.informatik.uni-freiburg.de.

Apple fruit superficial scald resistance mediated by ethylene inhibition is associated with diverse metabolic processes.

Fruits stored at low temperature can exhibit different types of chilling injury. In apple, one of the most serious physiological disorders is superficial scald, which is characterized by discoloration and brown necrotic patches on the fruit exocarp. Although this phenomenon is widely ascribed to the oxidation of α-farnesene, its physiology is not yet fully understood. To elucidate the mechanism of superficial scald development and possible means of prevention, we performed an integrated metabolite screen, including an analysis of volatiles, phenols and lipids, together with a large-scale transcriptome study. We also determined that prevention of superficial scald, through the use of an ethylene action inhibitor, is associated with the triggering of cold acclimation-related processes. Specifically, the inhibition of ethylene perception stimulated the production of antioxidant compounds to scavenge reactive oxygen species, the synthesis of fatty acids to stabilize plastid and vacuole membranes against cold temperature, and the accumulation of the sorbitol, which can act as a cryoprotectant. The pattern of sorbitol accumulation was consistent with the expression profile of a sorbitol 6-phosphate dehydrogenase, MdS6PDH, the overexpression of which in transgenic Arabidopsis thaliana plants confirmed its involvement in the cold acclimation and freezing tolerance.

MYB107 and MYB9 Homologs Regulate Suberin Deposition in Angiosperms.

Suberin, a polymer composed of both aliphatic and aromatic domains, is deposited as a rough matrix upon plant surface damage and during normal growth in the root endodermis, bark, specialized organs (e.g., potato [Solanum tuberosum] tubers), and seed coats. To identify genes associated with the developmental control of suberin deposition, we investigated the chemical composition and transcriptomes of suberized tomato (Solanum lycopersicum) and russet apple (Malus x domestica) fruit surfaces. Consequently, a gene expression signature for suberin polymer assembly was revealed that is highly conserved in angiosperms. Seed permeability assays of knockout mutants corresponding to signature genes revealed regulatory proteins (i.e., AtMYB9 and AtMYB107) required for suberin assembly in the Arabidopsis thaliana seed coat. Seeds of myb107 and myb9 Arabidopsis mutants displayed a significant reduction in suberin monomers and altered levels of other seed coat-associated metabolites. They also exhibited increased permeability, and lower germination capacities under osmotic and salt stress. AtMYB9 and AtMYB107 appear to synchronize the transcriptional induction of aliphatic and aromatic monomer biosynthesis and transport and suberin polymerization in the seed outer integument layer. Collectively, our findings establish a regulatory system controlling developmentally deposited suberin, which likely differs from the one of stress-induced polymer assembly recognized to date.

An efficient graph kernel method for non-coding RNA functional prediction.

MOTIVATION: The importance of RNA protein-coding gene regulation is by now well appreciated. Non-coding RNAs (ncRNAs) are known to regulate gene expression at practically every stage, ranging from chromatin packaging to mRNA translation. However the functional characterization of specific instances remains a challenging task in genome scale settings. For this reason, automatic annotation approaches are of interest. Existing computational methods are either efficient but non-accurate or they offer increased precision, but present scalability problems. RESULTS: In this article, we present a predictive system based on kernel methods, a type of machine learning algorithm grounded in statistical learning theory. We employ a flexible graph encoding to preserve multiple structural hypotheses and exploit recent advances in representation and model induction to scale to large data volumes. Experimental results on tens of thousands of ncRNA sequences available from the Rfam database indicate that we can not only improve upon state-of-the-art predictors, but also achieve speedups of several orders of magnitude. AVAILABILITY AND IMPLEMENTATION: The code is available from http://www.bioinf.uni-freiburg.de/~costa/EDeN.tgz . CONTACT: f.costa@exeter.ac.uk.

RNAscClust: clustering RNA sequences using structure conservation and graph based motifs.

MOTIVATION: Clustering RNA sequences with common secondary structure is an essential step towards studying RNA function. Whereas structural RNA alignment strategies typically identify common structure for orthologous structured RNAs, clustering seeks to group paralogous RNAs based on structural similarities. However, existing approaches for clustering paralogous RNAs, do not take the compensatory base pair changes obtained from structure conservation in orthologous sequences into account. RESULTS: Here, we present RNAscClust , the implementation of a new algorithm to cluster a set of structured RNAs taking their respective structural conservation into account. For a set of multiple structural alignments of RNA sequences, each containing a paralog sequence included in a structural alignment of its orthologs, RNAscClust computes minimum free-energy structures for each sequence using conserved base pairs as prior information for the folding. The paralogs are then clustered using a graph kernel-based strategy, which identifies common structural features. We show that the clustering accuracy clearly benefits from an increasing degree of compensatory base pair changes in the alignments. AVAILABILITY AND IMPLEMENTATION: RNAscClust is available at http://www.bioinf.uni-freiburg.de/Software/RNAscClust . CONTACT: gorodkin@rth.dk or backofen@informatik.uni-freiburg.de. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Formalin-Fixed, Paraffin-Embedded Tissues (FFPE) as a Robust Source for the Profiling of Native and Protease-Generated Protein Amino Termini.

Dysregulated proteolysis represents a hallmark of numerous diseases. In recent years, increasing number of studies has begun looking at the protein termini in hope to unveil the physiological and pathological functions of proteases in clinical research. However, the availability of cryopreserved tissue specimens is often limited. Alternatively, formalin-fixed, paraffin-embedded (FFPE) tissues offer an invaluable resource for clinical research. Pathologically relevant tissues are often stored as FFPE, which represent the most abundant resource of archived human specimens. In this study, we established a robust workflow to investigate native and protease-generated protein N termini from FFPE specimens. We demonstrate comparable N-terminomes of cryopreserved and formalin-fixed tissue, thereby showing that formalin fixation/paraffin embedment does not proteolytically damage proteins. Accordingly, FFPE specimens are fully amenable to N-terminal analysis. Moreover, we demonstrate feasibility of FFPE-degradomics in a quantitative N-terminomic study of FFPE liver specimens from cathepsin L deficient or wild-type mice. Using a machine learning approach in combination with the previously determined cathepsin L specificity, we successfully identify a number of potential cathepsin L cleavage sites. Our study establishes FFPE specimens as a valuable alternative to cryopreserved tissues for degradomic studies.

Interference with ethylene perception at receptor level sheds light on auxin and transcriptional circuits associated with the climacteric ripening of apple fruit (Malus x domestica Borkh.).

Apple (Malus x domestica Borkh.) is a model species for studying the metabolic changes that occur at the onset of ripening in fruit crops, and the physiological mechanisms that are governed by the hormone ethylene. In this study, to dissect the climacteric interplay in apple, a multidisciplinary approach was employed. To this end, a comprehensive analysis of gene expression together with the investigation of several physiological entities (texture, volatilome and content of polyphenolic compounds) was performed throughout fruit development and ripening. The transcriptomic profiling was conducted with two microarray platforms: a dedicated custom array (iRIPE) and a whole genome array specifically enriched with ripening-related genes for apple (WGAA). The transcriptomic and phenotypic changes following the application of 1-methylcyclopropene (1-MCP), an ethylene inhibitor leading to important modifications in overall fruit physiology, were also highlighted. The integrative comparative network analysis showed both negative and positive correlations between ripening-related transcripts and the accumulation of specific metabolites or texture components. The ripening distortion caused by the inhibition of ethylene perception, in addition to affecting the ethylene pathway, stimulated the de-repression of auxin-related genes, transcription factors and photosynthetic genes. Overall, the comprehensive repertoire of results obtained here advances the elucidation of the multi-layered climacteric mechanism of fruit ripening, thus suggesting a possible transcriptional circuit governed by hormones and transcription factors.

What makes for sound science?

The inclusive threshold policy for publication in BMC journals including BMC Plant Biology means that editorial decisions are largely based on the soundness of the research presented rather than the novelty or potential impact of the work. Here we discuss what is required to ensure that research meets the requirement of scientific soundness. BMC Plant Biology and the other BCM-series journals ( https://www.biomedcentral.com/p/the-bmc-series-journals ) differ in policy from many other journals as they aim to provide a home for all publishable research. The inclusive threshold policy for publication means that editorial decisions are largely based on the soundness of the research presented rather than the novelty or potential impact of the work. The emphasis on scientific soundness ( http://blogs.biomedcentral.com/bmcseriesblog/2016/12/05/vital-importance-inclusive/ ) rather than novelty or impact is important because it means that manuscripts that may be judged to be of low impact due to the nature of the study as well as those reporting negative results or that largely replicate earlier studies, all of which can be difficult to publish elsewhere, are available to the research community. Here we discuss the importance of the soundness of research and provide some basic guidelines to assist authors to determine whether their research is appropriate for submission to BMC Plant Biology.Prior to a research article being sent out for review, the handling editor will first determine whether the research presented is scientifically valid. To be valid the research must address a question of biological significance using suitable methods and analyses, and must follow community-agreed standards relevant to the research field.

RNAcommender: genome-wide recommendation of RNA-protein interactions.

MOTIVATION: Information about RNA-protein interactions is a vital pre-requisite to tackle the dissection of RNA regulatory processes. Despite the recent advances of the experimental techniques, the currently available RNA interactome involves a small portion of the known RNA binding proteins. The importance of determining RNA-protein interactions, coupled with the scarcity of the available information, calls for in silico prediction of such interactions. RESULTS: We present RNAcommender, a recommender system capable of suggesting RNA targets to unexplored RNA binding proteins, by propagating the available interaction information taking into account the protein domain composition and the RNA predicted secondary structure. Our results show that RNAcommender is able to successfully suggest RNA interactors for RNA binding proteins using little or no interaction evidence. RNAcommender was tested on a large dataset of human RBP-RNA interactions, showing a good ranking performance (average AUC ROC of 0.75) and significant enrichment of correct recommendations for 75% of the tested RBPs. RNAcommender can be a valid tool to assist researchers in identifying potential interacting candidates for the majority of RBPs with uncharacterized binding preferences. AVAILABILITY AND IMPLEMENTATION: The software is freely available at http://rnacommender.disi.unitn.it CONTACT: gianluca.corrado@unitn.it or andrea.passerini@unitn.itSupplementary information: Supplementary data are available at Bioinformatics online.

Characterizing leader sequences of CRISPR loci.

MOTIVATION: The CRISPR-Cas system is an adaptive immune system in many archaea and bacteria, which provides resistance against invading genetic elements. The first phase of CRISPR-Cas immunity is called adaptation, in which small DNA fragments are excised from genetic elements and are inserted into a CRISPR array generally adjacent to its so called leader sequence at one end of the array. It has been shown that transcription initiation and adaptation signals of the CRISPR array are located within the leader. However, apart from promoters, there is very little knowledge of sequence or structural motifs or their possible functions. Leader properties have mainly been characterized through transcriptional initiation data from single organisms but large-scale characterization of leaders has remained challenging due to their low level of sequence conservation. RESULTS: We developed a method to successfully detect leader sequences by focusing on the consensus repeat of the adjacent CRISPR array and weak upstream conservation signals. We applied our tool to the analysis of a comprehensive genomic database and identified several characteristic properties of leader sequences specific to archaea and bacteria, ranging from distinctive sizes to preferential indel localization. CRISPRleader provides a full annotation of the CRISPR array, its strand orientation as well as conserved core leader boundaries that can be uploaded to any genome browser. In addition, it outputs reader-friendly HTML pages for conserved leader clusters from our database. AVAILABILITY AND IMPLEMENTATION: CRISPRleader and multiple sequence alignments for all 195 leader clusters are available at http://www.bioinf.uni-freiburg.de/Software/CRISPRleader/ CONTACT: costa@informatik.uni-freiburg.de or backofen@informatik.uni-freiburg.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genome-wide association study unravels the genetic control of the apple volatilome and its interplay with fruit texture.

Fruit quality represents a fundamental factor guiding consumers' preferences. Among apple quality traits, volatile organic compounds and texture features play a major role. Proton Transfer Reaction-Time of Flight-Mass Spectrometry (PTR-ToF-MS), coupled with an artificial chewing device, was used to profile the entire apple volatilome of 162 apple accessions, while the fruit texture was dissected with a TAXT-AED texture analyzer. The array of volatile compounds was classed into seven major groups and used in a genome-wide association analysis carried out with 9142 single nucleotide polymorphisms (SNPs). Marker-trait associations were identified on seven chromosomes co-locating with important candidate genes for aroma, such as MdAAT1 and MdIGS. The integration of volatilome and fruit texture data conducted with a multiple factor analysis unraveled contrasting behavior, underlying opposite regulation of the two fruit quality aspects. The association analysis using the first two principal components identified two QTLs located on chromosomes 10 and 2, respectively. The distinction of the apple accessions on the basis of the allelic configuration of two functional markers, MdPG1 and MdACO1, shed light on the type of interplay existing between fruit texture and the production of volatile organic compounds.

Deciphering the genetic control of fruit texture in apple by multiple family-based analysis and genome-wide association.

Fruit texture is a complex feature composed of mechanical and acoustic properties relying on the modifications occurring in the cell wall throughout fruit development and ripening. Apple is characterized by a large variation in fruit texture behavior that directly impacts both the consumer's appreciation and post-harvest performance. To decipher the genetic control of fruit texture comprehensively, two complementing quantitative trait locus (QTL) mapping approaches were employed. The first was represented by a pedigree-based analysis (PBA) carried out on six full-sib pedigreed families, while the second was a genome-wide association study (GWAS) performed on a collection of 233 apple accessions. Both plant materials were genotyped with a 20K single nucleotide polymorphism (SNP) array and phenotyped with a sophisticated high-resolution texture analyzer. The overall QTL results indicated the fundamental role of chromosome 10 in controlling the mechanical properties, while chromosomes 2 and 14 were more associated with the acoustic response. The latter QTL, moreover, showed a consistent relationship between the QTL-estimated genotypes and the acoustic performance assessed among seedlings. The in silico annotation of these intervals revealed interesting candidate genes potentially involved in fruit texture regulation, as suggested by the gene expression profile. The joint integration of these approaches sheds light on the specific control of fruit texture, enabling important genetic information to assist in the selection of valuable fruit quality apple varieties.

SnoReport 2.0: new features and a refined Support Vector Machine to improve snoRNA identification.

BACKGROUND: snoReport uses RNA secondary structure prediction combined with machine learning as the basis to identify the two main classes of small nucleolar RNAs, the box H/ACA snoRNAs and the box C/D snoRNAs. Here, we present snoReport 2.0, which substantially improves and extends in the original method by: extracting new features for both box C/D and H/ACA box snoRNAs; developing a more sophisticated technique in the SVM training phase with recent data from vertebrate organisms and a careful choice of the SVM parameters C and γ; and using updated versions of tools and databases used for the construction of the original version of snoReport. To validate the new version and to demonstrate its improved performance, we tested snoReport 2.0 in different organisms. RESULTS: Results of the training and test phases of boxes H/ACA and C/D snoRNAs, in both versions of snoReport, are discussed. Validation on real data was performed to evaluate the predictions of snoReport 2.0. Our program was applied to a set of previously annotated sequences, some of them experimentally confirmed, of humans, nematodes, drosophilids, platypus, chickens and leishmania. We significantly improved the predictions for vertebrates, since the training phase used information of these organisms, but H/ACA box snoRNAs identification was improved for the other ones. CONCLUSION: We presented snoReport 2.0, to predict H/ACA box and C/D box snoRNAs, an efficient method to find true positives and avoid false positives in vertebrate organisms. H/ACA box snoRNA classifier showed an F-score of 93 % (an improvement of 10 % regarding the previous version), while C/D box snoRNA classifier, an F-Score of 94 % (improvement of 14 %). Besides, both classifiers exhibited performance measures above 90 %. These results show that snoReport 2.0 avoid false positives and false negatives, allowing to predict snoRNAs with high quality. In the validation phase, snoReport 2.0 predicted 67.43 % of vertebrate organisms for both classes. For Nematodes and Drosophilids, 69 % and 76.67 %, for H/ACA box snoRNAs were predicted, respectively, showing that snoReport 2.0 is good to identify snoRNAs in vertebrates and also H/ACA box snoRNAs in invertebrates organisms.

ASSIsT: an automatic SNP scoring tool for in- and outbreeding species.

UNLABELLED: ASSIsT (Automatic SNP ScorIng Tool) is a user-friendly customized pipeline for efficient calling and filtering of SNPs from Illumina Infinium arrays, specifically devised for custom genotyping arrays. Illumina has developed an integrated software for SNP data visualization and inspection called GenomeStudio (GS). ASSIsT builds on GS-derived data and identifies those markers that follow a bi-allelic genetic model and show reliable genotype calls. Moreover, ASSIsT re-edits SNP calls with null alleles or additional SNPs in the probe annealing site. ASSIsT can be employed in the analysis of different population types such as full-sib families and mating schemes used in the plant kingdom (backcross, F1, F2), and unrelated individuals. The final result can be directly exported in the format required by the most common software for genetic mapping and marker-trait association analysis. ASSIsT is developed in Python and runs in Windows and Linux. AVAILABILITY AND IMPLEMENTATION: The software, example data sets and tutorials are freely available at http://compbiotoolbox.fmach.it/assist/. CONTACT: eric.vandeweg@wur.nl.

The Tomato MIXTA-Like Transcription Factor Coordinates Fruit Epidermis Conical Cell Development and Cuticular Lipid Biosynthesis and Assembly.

The epidermis of aerial plant organs is the primary source of building blocks forming the outer surface cuticular layer. To examine the relationship between epidermal cell development and cuticle assembly in the context of fruit surface, we investigated the tomato (Solanum lycopersicum) MIXTA-like gene. MIXTA/MIXTA-like proteins, initially described in snapdragon (Antirrhinum majus) petals, are known regulators of epidermal cell differentiation. Fruit of transgenically silenced SlMIXTA-like tomato plants displayed defects in patterning of conical epidermal cells. They also showed altered postharvest water loss and resistance to pathogens. Transcriptome and cuticular lipids profiling coupled with comprehensive microscopy revealed significant modifications to cuticle assembly and suggested SlMIXTA-like to regulate cutin biosynthesis. Candidate genes likely acting downstream of SlMIXTA-like included cytochrome P450s (CYPs) of the CYP77A and CYP86A subfamilies, LONG-CHAIN ACYL-COA SYNTHETASE2, GLYCEROL-3-PHOSPHATE SN-2-ACYLTRANSFERASE4, and the ATP-BINDING CASSETTE11 cuticular lipids transporter. As part of a larger regulatory network of epidermal cell patterning and L1-layer identity, we found that SlMIXTA-like acts downstream of SlSHINE3 and possibly cooperates with homeodomain Leu zipper IV transcription factors. Hence, SlMIXTA-like is a positive regulator of both cuticle and conical epidermal cell formation in tomato fruit, acting as a mediator of the tight association between fruit cutin polymer formation, cuticle assembly, and epidermal cell patterning.