Rhizocarpon geographicum Lichen Discloses a Highly Diversified Microbiota Carrying Antibiotic Resistance and Persistent Organic Pollutant Tolerance.

As rock inhabitants, lichens are exposed to extreme and fluctuating abiotic conditions associated with poor sources of nutriments. These extreme conditions confer to lichens the unique ability to develop protective mechanisms. Consequently, lichen-associated microbes disclose highly versatile lifestyles and ecological plasticity, enabling them to withstand extreme environments. Because of their ability to grow in poor and extreme habitats, bacteria associated with lichens can tolerate a wide range of pollutants, and they are known to produce antimicrobial compounds. In addition, lichen-associated bacteria have been described to harbor ecological functions crucial for the evolution of the lichen holobiont. Nevertheless, the ecological features of lichen-associated microbes are still underestimated. To explore the untapped ecological diversity of lichen-associated bacteria, we adopted a novel culturomic approach on the crustose lichen Rhizocarpon geographicum. We sampled R. geographicum in French habitats exposed to oil spills, and we combined nine culturing methods with 16S rRNA sequencing to capture the greatest bacterial diversity. A deep functional analysis of the lichen-associated bacterial collection showed the presence of a set of bacterial strains resistant to a wide range of antibiotics and displaying tolerance to Persistent Organic Pollutants (POPs). Our study is a starting point to explore the ecological features of the lichen microbiota.

Comparative transcriptome analysis at the onset of speciation in a mimetic butterfly-The Ithomiini Melinaea marsaeus.

Ecological speciation entails divergent selection on specific traits and ultimately on the developmental pathways responsible for these traits. Selection can act on gene sequences but also on regulatory regions responsible for gene expression. Mimetic butterflies are a relevant system for speciation studies because wing colour pattern (WCP) often diverges between closely related taxa and is thought to drive speciation through assortative mating and increased predation on hybrids. Here, we generate the first transcriptomic resources for a mimetic butterfly of the tribe Ithomiini, Melinaea marsaeus, to examine patterns of differential expression between two subspecies and between tissues that express traits that likely drive reproductive isolation; WCP and chemosensory genes. We sequenced whole transcriptomes of three life stages to cover a large catalogue of transcripts, and we investigated differential expression between subspecies in pupal wing discs and antennae. Eighteen known WCP genes were expressed in wing discs and 115 chemosensory genes were expressed in antennae, with a remarkable diversity of chemosensory protein genes. Many transcripts were differentially expressed between subspecies, including two WCP genes and one odorant receptor. Our results suggest that in M. marsaeus the same genes as in other mimetic butterflies are involved in traits causing reproductive isolation, and point at possible candidates for the differences in those traits between subspecies. Differential expression analyses of other developmental stages and body organs and functional studies are needed to confirm and expand these results. Our work provides key resources for comparative genomics in mimetic butterflies, and more generally in Lepidoptera.

De novo construction of a "Gene-space" for diploid plant genome rich in repetitive sequences by an iterative Process of Extraction and Assembly of NGS reads (iPEA protocol) with limited computing resources.

BACKGROUND: The continuing increase in size and quality of the "short reads" raw data is a significant help for the quality of the assembly obtained through various bioinformatics tools. However, building a reference genome sequence for most plant species remains a significant challenge due to the large number of repeated sequences which are problematic for a whole-genome quality de novo assembly. Furthermore, for most SNP identification approaches in plant genetics and breeding, only the "Gene-space" regions including the promoter, exon and intron sequences are considered. RESULTS: We developed the iPea protocol to produce a de novo Gene-space assembly by reconstructing, in an iterative way, the non-coding sequence flanking the Unigene cDNA sequence through addition of next-generation DNA-seq data. The approach was elaborated with the large diploid genome of pea (Pisum sativum L.), rich in repetitive sequences. The final Gene-space assembly included 35,400 contigs (97 Mb), covering 88 % of the 40,227 contigs (53.1 Mb) of the PsCam_low-copy Unigen set. Its accuracy was validated by the results of the built GenoPea 13.2 K SNP Array. CONCLUSION: The iPEA protocol allows the reconstruction of a Gene-space based from RNA-Seq and DNA-seq data with limited computing resources.

Colib'read on galaxy: a tools suite dedicated to biological information extraction from raw NGS reads.

BACKGROUND: With next-generation sequencing (NGS) technologies, the life sciences face a deluge of raw data. Classical analysis processes for such data often begin with an assembly step, needing large amounts of computing resources, and potentially removing or modifying parts of the biological information contained in the data. Our approach proposes to focus directly on biological questions, by considering raw unassembled NGS data, through a suite of six command-line tools. FINDINGS: Dedicated to 'whole-genome assembly-free' treatments, the Colib'read tools suite uses optimized algorithms for various analyses of NGS datasets, such as variant calling or read set comparisons. Based on the use of a de Bruijn graph and bloom filter, such analyses can be performed in a few hours, using small amounts of memory. Applications using real data demonstrate the good accuracy of these tools compared to classical approaches. To facilitate data analysis and tools dissemination, we developed Galaxy tools and tool shed repositories. CONCLUSIONS: With the Colib'read Galaxy tools suite, we enable a broad range of life scientists to analyze raw NGS data. More importantly, our approach allows the maximum biological information to be retained in the data, and uses a very low memory footprint.

SNP discovery and genetic mapping using genotyping by sequencing of whole genome genomic DNA from a pea RIL population.

BACKGROUND: Progress in genetics and breeding in pea still suffers from the limited availability of molecular resources. SNP markers that can be identified through affordable sequencing processes, without the need for prior genome reduction or a reference genome to assemble sequencing data would allow the discovery and genetic mapping of thousands of molecular markers. Such an approach could significantly speed up genetic studies and marker assisted breeding for non-model species. RESULTS: A total of 419,024 SNPs were discovered using HiSeq whole genome sequencing of four pea lines, followed by direct identification of SNP markers without assembly using the discoSnp tool. Subsequent filtering led to the identification of 131,850 highly designable SNPs, polymorphic between at least two of the four pea lines. A subset of 64,754 SNPs was called and genotyped by short read sequencing on a subpopulation of 48 RILs from the cross 'Baccara' x 'PI180693'. This data was used to construct a WGGBS-derived pea genetic map comprising 64,263 markers. This map is collinear with previous pea consensus maps and therefore with the Medicago truncatula genome. Sequencing of four additional pea lines showed that 33 % to 64 % of the mapped SNPs, depending on the pairs of lines considered, are polymorphic and can therefore be useful in other crosses. The subsequent genotyping of a subset of 1000 SNPs, chosen for their mapping positions using a KASP™ assay, showed that almost all generated SNPs are highly designable and that most (95 %) deliver highly qualitative genotyping results. Using rather low sequencing coverages in SNP discovery and in SNP inferring did not hinder the identification of hundreds of thousands of high quality SNPs. CONCLUSIONS: The development and optimization of appropriate tools in SNP discovery and genetic mapping have allowed us to make available a massive new genomic resource in pea. It will be useful for both fine mapping within chosen QTL confidence intervals and marker assisted breeding for important traits in pea improvement.

Full-length de novo assembly of RNA-seq data in pea (Pisum sativum L.) provides a gene expression atlas and gives insights into root nodulation in this species.

Next-generation sequencing technologies allow an almost exhaustive survey of the transcriptome, even in species with no available genome sequence. To produce a Unigene set representing most of the expressed genes of pea, 20 cDNA libraries produced from various plant tissues harvested at various developmental stages from plants grown under contrasting nitrogen conditions were sequenced. Around one billion reads and 100 Gb of sequence were de novo assembled. Following several steps of redundancy reduction, 46 099 contigs with N50 length of 1667 nt were identified. These constitute the 'Caméor' Unigene set. The high depth of sequencing allowed identification of rare transcripts and detected expression for approximately 80% of contigs in each library. The Unigene set is now available online (http://bios.dijon.inra.fr/FATAL/cgi/pscam.cgi), allowing (i) searches for pea orthologs of candidate genes based on gene sequences from other species, or based on annotation, (ii) determination of transcript expression patterns using various metrics, (iii) identification of uncharacterized genes with interesting patterns of expression, and (iv) comparison of gene ontology pathways between tissues. This resource has allowed identification of the pea orthologs of major nodulation genes characterized in recent years in model species, as a major step towards deciphering unresolved pea nodulation phenotypes. In addition to a remarkable conservation of the early transcriptome nodulation apparatus between pea and Medicago truncatula, some specific features were highlighted. The resource provides a reference for the pea exome, and will facilitate transcriptome and proteome approaches as well as SNP discovery in pea.