Section: New Results

Bioinformatics Analysis

Metagenomic analysis of pea aphid symbiotic communities

Participants : Cervin Guyomar, Fabrice Legeai, Claire Lemaitre.

We worked on a methodological framework adapted to the study of genomic diversity and evolutionary dynamics of the pea aphid symbiotic community from an extensive set of metagenomics datasets. The framework is based on mapping to reference genomes and whole genome SNP-calling. We explored the genotypic diversity associated to the different symbionts of the pea aphid at several scales : across host biotypes, amongst individuals of the same biotype, and within individual aphids. Thorough phylogenomic analyses highlighted that the evolutionary dynamics of symbiotic associations strongly varied depending on the symbiont, reflecting different evolutionary histories and possible constraints [14].

Analysis of pea aphid genomic polymorphism

Participants : Fabrice Legeai, Claire Lemaitre.

We participated in the analyses of a large re-sequencing dataset of pea aphid individuals and populations. We performed the data cleaning, mapping to the reference genome and variant calling steps. The resulting polymorphism data shed light on two novel findings regarding the pea aphid genome evolution.

First, we showed that relaxed selection is likely to be the greatest contributor to the faster evolution of the X chromosome compared to autosomes [15]. Secondly, we looked for genomic bases of adaptation to novel environments, and identified 392 genomic hotspot regions of differentiation spanning 47.3 Mb and 2,484 genes. Interestingly, these hotspots were significantly enriched for candidate gene categories that are related to host–plant selection and use. These genes represent promising candidates for the genetic basis of host–plant specialization and ecological isolation in the pea aphid complex [21].

A de novo approach to disentangle partner identity and function in holobiont systems

Participants : Camille Marchet, Pierre Peterlongo.

Study of meta-transcriptomic datasets involving non-model organisms represents bioinformatic challenges that affect the study of holobiont meta-transcriptomes. Hence, we proposed an innovative bioinformatic approach and tested it on marine models as a proof of concept.

We considered three holobiont models, of which two transcriptomes were previously published and a yet unpublished transcriptome, to analyze and sort their raw reads using Short Read Connector (see section 7.1.1). Before assembly, we thus defined four distinct categories for each holobiont meta-transcriptome: host reads, symbiont reads, shared reads, and unassigned reads. Afterwards, we observed that independent de novo assemblies for each category led to a diminution of the number of chimeras compared to classical assembly methods. Moreover, the separation of each partner’s transcriptome offered the independent and comparative exploration of their functional diversity in the holobiont. Finally, our strategy allowed to propose new functional annotations for two well-studied holobionts (a Cnidaria-Dinophyta, a Porifera-Bacteria) and a first meta-transcriptome from a planktonic Radiolaria-Dinophyta system forming widespread symbiotic association for which our knowledge is considerably limited [19].

Whole genome detection of micro-satellites

Participant : Dominique Lavenier.

This study has been done in cooperation with the federal university of de São João del-Rei, Brazil. The objective was to locate tens of thousands of micro-satellite loci for an endangered piracema (i.e. migratory) South American fish, Brycon orbignyanus. Together with the Brazil group we designed a specific pipeline that first assembles short paired-end reads into contigs and then performs micro-satellite oriented scaffolding processing [23].

Analysis of the genes and genomes involved in plant and insects interactions

Participant : Fabrice Legeai.

These study has been done in cooperation with various laboratories. In particular, we characterized the effectors (secreted proteins suppressing plant defense) of the pea aphid fed on different plants, by firstly identifying these genes in the pea aphid genome, then studying and comparing their expression between different conditions, and then finally by observing their evolution among a broad set of phytophagous insects [10]. We also identified microRNAs from smallRNA datasets from Spodoptera frugiperda strains fed on different host-plants [20]. Finally, we predicted the transposable elements in the genome of Cephus cinctus, an important insect pest [22].

Analysis of the expression and identification of the targets of mir202 during the medaka oogenesis

Participant : Fabrice Legeai.

This study has been done in cooperation with the INRA LPGP laboratory (Rennes). Its goal was to identify the role of small non-coding RNAs in the regulation of the reproduction of the fish model Oryzias latipes (medaka). We predicted the putative targets of the microRNA miR202, already observed as being specifically expressed in gonads. In the second part of the work, we identified important genes and functions targeted by miR202 and differentially expressed in the gonads when the microRNA was artificially repressed [13].