De novo genome and transcriptome resources of the Adzuki bean borer Ostrinia scapulalis (Lepidoptera: Crambidae).

We present a draft genome assembly with a de novo prediction and automated functional annotation of coding genes, and a reference transcriptome of the Adzuki bean borer, Ostrinia scapulalis, based on RNA sequencing of various tissues and developmental stages. The genome assembly spans 419 Mb, has a GC content of 37.4% and includes 26,120 predicted coding genes. The reference transcriptome holds 33,080 unigenes and contains a high proportion of a set of genes conserved in eukaryotes and arthropods, used as quality assessment of the reconstructed transcripts. The new genomic and transcriptomic data presented here significantly enrich the public sequence databases for the Crambidae and Lepidoptera, and represent useful resources for future researches related to the evolution and the adaptation of phytophagous moths. The genome and transcriptome assemblies have been deposited and made accessible via a NCBI BioProject (id PRJNA390510) and the LepidoDB database (http://bipaa.genouest.org/sp/ostrinia_scapulalis/).

Draft genome and reference transcriptomic resources for the urticating pine defoliator Thaumetopoea pityocampa (Lepidoptera: Notodontidae).

The pine processionary moth Thaumetopoea pityocampa (Lepidoptera: Notodontidae) is the main pine defoliator in the Mediterranean region. Its urticating larvae cause severe human and animal health concerns in the invaded areas. This species shows a high phenotypic variability for various traits, such as phenology, fecundity and tolerance to extreme temperatures. This study presents the construction and analysis of extensive genomic and transcriptomic resources, which are an obligate prerequisite to understand their underlying genetic architecture. Using a well-studied population from Portugal with peculiar phenological characteristics, the karyotype was first determined and a first draft genome of 537 Mb total length was assembled into 68,292 scaffolds (N50 = 164 kb). From this genome assembly, 29,415 coding genes were predicted. To circumvent some limitations for fine-scale physical mapping of genomic regions of interest, a 3X coverage BAC library was also developed. In particular, 11 BACs from this library were individually sequenced to assess the assembly quality. Additionally, de novo transcriptomic resources were generated from various developmental stages sequenced with HiSeq and MiSeq Illumina technologies. The reads were de novo assembled into 62,376 and 63,175 transcripts, respectively. Then, a robust subset of the genome-predicted coding genes, the de novo transcriptome assemblies and previously published 454/Sanger data were clustered to obtain a high-quality and comprehensive reference transcriptome consisting of 29,701 bona fide unigenes. These sequences covered 99% of the cegma and 88% of the busco highly conserved eukaryotic genes and 84% of the busco arthropod gene set. Moreover, 90% of these transcripts could be localized on the draft genome. The described information is available via a genome annotation portal (http://bipaa.genouest.org/sp/thaumetopoea_pityocampa/).

Genome scans on experimentally evolved populations reveal candidate regions for adaptation to plant resistance in the potato cyst nematode Globodera pallida.

Improving resistance durability involves to be able to predict the adaptation speed of pathogen populations. Identifying the genetic bases of pathogen adaptation to plant resistances is a useful step to better understand and anticipate this phenomenon. Globodera pallida is a major pest of potato crop for which a resistance QTL, GpaVvrn , has been identified in Solanum vernei. However, its durability is threatened as G. pallida populations are able to adapt to the resistance in few generations. The aim of this study was to investigate the genomic regions involved in the resistance breakdown by coupling experimental evolution and high-density genome scan. We performed a whole-genome resequencing of pools of individuals (Pool-Seq) belonging to G. pallida lineages derived from two independent populations having experimentally evolved on susceptible and resistant potato cultivars. About 1.6 million SNPs were used to perform the genome scan using a recent model testing for adaptive differentiation and association to population-specific covariables. We identified 275 outliers and 31 of them, which also showed a significant reduction in diversity in adapted lineages, were investigated for their genic environment. Some candidate genomic regions contained genes putatively encoding effectors and were enriched in SPRYSECs, known in cyst nematodes to be involved in pathogenicity and in (a)virulence. Validated candidate SNPs will provide a useful molecular tool to follow frequencies of virulence alleles in natural G. pallida populations and define efficient strategies of use of potato resistances maximizing their durability.

AnnotQTL: a new tool to gather functional and comparative information on a genomic region.

AnnotQTL is a web tool designed to aggregate functional annotations from different prominent web sites by minimizing the redundancy of information. Although thousands of QTL regions have been identified in livestock species, most of them are large and contain many genes. This tool was therefore designed to assist the characterization of genes in a QTL interval region as a step towards selecting the best candidate genes. It localizes the gene to a specific region (using NCBI and Ensembl data) and adds the functional annotations available from other databases (Gene Ontology, Mammalian Phenotype, HGNC and Pubmed). Both human genome and mouse genome can be aligned with the studied region to detect synteny and segment conservation, which is useful for running inter-species comparisons of QTL locations. Finally, custom marker lists can be included in the results display to select the genes that are closest to your most significant markers. We use examples to demonstrate that in just a couple of hours, AnnotQTL is able to identify all the genes located in regions identified by a full genome scan, with some highlighted based on both location and function, thus considerably increasing the chances of finding good candidate genes. AnnotQTL is available at http://annotqtl.genouest.org.