Sylvain Gaillard

The phytopathogenic bacterium Xylella fastidiosa was thought to be restricted to the Americas where it infects and kills numerous hosts. Its detection worldwide has been blooming since 2013 in Europe and Asia. Genetically diverse, this species is divided into six subspecies but genetic traits governing this classification are poorly understood. SkIf (Specific k-mers Identification) was designed and exploited for comparative genomics on a dataset of 46 X. fastidiosa genomes, including seven newly sequenced individuals. It was helpful to quickly check the synonymy between strains from different collections. SkIf identified specific SNPs within 16S rRNA sequences that can be employed for predicting the distribution of Xylella through data mining. Applied to inter- and intra-subspecies analyses, it identified specific k-mers in genes affiliated to differential gene ontologies. Chemotaxis-related genes more prevalently possess specific k-mers in genomes from subspecies fastidiosa, morus and sandyi taken as a whole group. In the subspecies pauca increased abundance of specific k-mers was found in genes associated with the bacterial cell wall/envelope/plasma membrane. Most often, the k-mer specificity occurred in core genes with non-synonymous SNPs in their sequences in genomes of the other subspecies, suggesting putative impact in the protein functions. The presence of two integrative and conjugative elements (ICEs) was identified, one chromosomic and an entire plasmid in a single strain of X. fastidiosa subsp. pauca. Finally, a revised taxonomy of X. fastidiosa into three major clades defined by the subspecies pauca (clade I), multiplex (clade II) and the combination of fastidiosa, morus and sandyi (clade III) was strongly supported by k-mers specifically associated with these subspecies. SkIf is a robust and rapid software, freely available, that can be dedicated to the comparison of sequence datasets and is applicable to any field of research. Applied to X. fastidiosa, an emerging pathogen in Europe, it provided an important resource to mine for identifying genetic markers of subspecies to optimize the strategies attempted to limit the pathogen dissemination in novel areas.

Using the latest sequencing and optical mapping technologies, we have produced a high-quality de novo assembly of the apple (Malus domestica Borkh.) genome. Repeat sequences, which represented over half of the assembly, provided an unprecedented opportunity to investigate the uncharacterized regions of a tree genome; we identified a new hyper-repetitive retrotransposon sequence that was over-represented in heterochromatic regions and estimated that a major burst of different transposable elements (TEs) occurred 21 million years ago. Notably, the timing of this TE burst coincided with the uplift of the Tian Shan mountains, which is thought to be the center of the location where the apple originated, suggesting that TEs and associated processes may have contributed to the diversification of the apple ancestor and possibly to its divergence from pear. Finally, genome-wide DNA methylation data suggest that epigenetic marks may contribute to agronomically relevant aspects, such as apple fruit development.

Hybridization with introduced genetic resources is commonly practiced in ornamental plant breeding to introgress desired traits. The 19th century was a golden age for rose breeding in France. The objective here was to study the evolution of rose genetic diversity over this period, which included the introduction of Asian genotypes into Europe. A large sample of 1228 garden roses encompassing the conserved diversity cultivated during the 18th and 19th centuries was genotyped with 32 microsatellite primer pairs. Its genetic diversity and structure were clarified. Wide diversity structured in 16 genetic groups was observed. Genetic differentiation was detected between ancient European and Asian accessions, and a temporal shift from a European to an Asian genetic background was observed in cultivated European hybrids during the 19th century. Frequent crosses with Asian roses throughout the 19th century and/or selection for Asiatic traits may have induced this shift. In addition, the consistency of the results with respect to a horticultural classification is discussed. Some horticultural groups, defined according to phenotype and/or knowledge of their pedigree, seem to be genetically more consistent than others, highlighting the difficulty of classifying cultivated plants. Therefore, the horticultural classification is probably more appropriate for commercial purposes rather than genetic relatedness, especially to define preservation and breeding strategies.

Image analysis is increasingly used in plant phenotyping. Among the various imaging techniques that can be used in plant phenotyping, chlorophyll fluorescence imaging allows imaging of the impact of biotic or abiotic stresses on leaves. Numerous chlorophyll fluorescence parameters may be measured or calculated, but only a few can produce a contrast in a given condition. Therefore, automated procedures that help screening chlorophyll fluorescence image datasets are needed, especially in the perspective of high-throughput plant phenotyping. We developed an automatic procedure aiming at facilitating the identification of chlorophyll fluorescence parameters impacted on leaves by a stress. First, for each chlorophyll fluorescence parameter, the procedure provides an overview of the data by automatically creating contact sheets of images and/or histograms. Such contact sheets enable a fast comparison of the impact on leaves of various treatments, or of the contrast dynamics during the experiments. Second, based on the global intensity of each chlorophyll fluorescence parameter, the procedure automatically produces radial plots and box plots allowing the user to identify chlorophyll fluorescence parameters that discriminate between treatments. Moreover, basic statistical analysis is automatically generated. Third, for each chlorophyll fluorescence parameter the procedure automatically performs a clustering analysis based on the histograms. This analysis clusters images of plants according to their health status. We applied this procedure to monitor the impact of the inoculation of the root parasitic plant Phelipanche ramosa on Arabidopsis thaliana ecotypes Col-0 and Ler. Using this automatic procedure, we identified eight chlorophyll fluorescence parameters discriminating between the two ecotypes of A. thaliana, and five impacted by the infection of Arabidopsis thaliana by P. ramosa. More generally, this procedure may help to identify chlorophyll fluorescence parameters impacted by various types of stresses. We implemented this procedure at http://www.phenoplant.org freely accessible to users of the plant phenotyping community.

Polyphenols have favorable antioxidant potential on human health suggesting that their high content is responsible for the beneficial effects of apple consumption. They control the quality of ciders as they predominantly account for astringency, bitterness, color and aroma. In this study, we identified QTLs controlling phenolic compound concentrations and the average polymerization degree of flavanols in a cider apple progeny. Thirty-two compounds belonging to five groups of phenolic compounds were identified and quantified by reversed phase liquid chromatography on both fruit extract and juice, over three years. The average polymerization degree of flavanols was estimated in fruit by phloroglucinolysis coupled to HPLC. Parental maps were built using SSR and SNP markers and used for the QTL analysis. Sixty-nine and 72 QTLs were detected on 14 and 11 linkage groups of the female and male maps, respectively. A majority of the QTLs identified in this study are specific to this population, while others are consistent with previous studies. This study presents for the first time in apple, QTLs for the mean polymerization degree of procyanidins, for which the mechanisms involved remains unknown to this day. Identification of candidate genes underlying major QTLs was then performed in silico and permitted the identification of 18 enzymes of the polyphenol pathway and six transcription factors involved in the apple anthocyanin regulation. New markers were designed from sequences of the most interesting candidate genes in order to confirm their co-localization with underlying QTLs by genetic mapping. Finally, the potential use of these QTLs in breeding programs is discussed.

Summary: Characterizing the transcriptome of eukaryotic organisms is essential for studying gene regulation and its impact on phenotype. The realization that anti‐sense (AS) and noncoding RNA transcription is pervasive in many genomes has emphasized our limited understanding of gene transcription and post‐transcriptional regulation. Numerous mechanisms including convergent transcription, anti‐correlated expression of sense and AS transcripts, and RNAi remain ill‐defined. Here, we have combined microarray analysis and high‐throughput sequencing of small RNAs (sRNAs) to unravel the complexity of transcriptional and potential post‐transcriptional regulation in eight organs of apple (Malus × domestica). The percentage of AS transcript expression is higher than that identified in annual plants such as rice and Arabidopsis thaliana. Furthermore, we show that a majority of AS transcripts are transcribed beyond 3′UTR regions, and may cover a significant portion of the predicted sense transcripts. Finally we demonstrate at a genome‐wide scale that anti‐sense transcript expression is correlated with the presence of both short (21–23 nt) and long (> 30 nt) siRNAs, and that the sRNA coverage depth varies with the level of AS transcript expression. Our study provides a new insight on the functional role of anti‐sense transcripts at the genome‐wide level, and a new basis for the understanding of sRNA biogenesis in plants.

Sequence alignments are the starting point for most evolutionary and comparative analyses. Full genome sequences can be compared to study patterns of within and between species variation. Genome sequence alignments are complex structures containing information such as coordinates, quality scores and synteny structure, which are stored in Multiple Alignment Format (MAF) files. Processing these alignments therefore involves parsing and manipulating typically large MAF files in an efficient way.

Efficient algorithms and programs for the analysis of the ever-growing amount of biological sequence data are strongly needed in the genomics era. The pace at which new data and methodologies are generated calls for the use of pre-existing, optimized—yet extensible—code, typically distributed as libraries or packages. This motivated the Bio++ project, aiming at developing a set of C++ libraries for sequence analysis, phylogenetics, population genetics, and molecular evolution. The main attractiveness of Bio++ is the extensibility and reusability of its components through its object-oriented design, without compromising the computer-efficiency of the underlying methods. We present here the second major release of the libraries, which provides an extended set of classes and methods. These extensions notably provide built-in access to sequence databases and new data structures for handling and manipulating sequences from the omics era, such as multiple genome alignments and sequencing reads libraries. More complex models of sequence evolution, such as mixture models and generic n-tuples alphabets, are also included.