De novo annotation of the transcriptome of the Northern Wheatear (Oenanthe oenanthe)

对北鹟(Oenanthe oenanthe)转录组进行从头注释

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Abstract

We have sequenced a partial transcriptome of the Northern Wheatear (Oenanthe oenanthe), a species with one of the longest migrations on Earth. The transcriptome was constructed de novo using RNA-Seq sequence data from the pooled mRNA of six different tissues: brain, muscle, intestine, liver, adipose tissue and skin. The samples came from nine captive-bred wheatears collected at three different stages of the endogenous autumn migratory period: (1) lean birds prior the onset of migration, (2) during the fattening stage and (3) individuals at their migratory body mass plateau, when they have almost doubled their lean body mass. The sample structure used to build up the transcriptome of the Northern Wheatears concerning tissue composition and time guarantees the future survey of the regulatory genes involved in the development of the migratory phenotype. Through the pre-migratory period, birds accomplish outstanding physical and behavioural changes that involve all organ systems. Nevertheless, the molecular mechanisms through which birds synchronize and control hyperphagia, fattening, restlessness increase, immunity boosting and tuning the muscles for such endurance flight are still largely unknown. The use of RNA-Seq has emerged as a powerful tool to analyse complex traits on a broad scale, and we believe it can help to characterize the migratory phenotype of wheatears at an unprecedented level. The primary challenge to conduct quantitative transcriptomic studies in non-model species is the availability of a reference transcriptome, which we have constructed and described in this paper. The cDNA was sequenced by pyrosequencing using the Genome Sequencer Roche GS FLX System; with single paired-end reads of about 400 bp. We estimate the total number of genes at 15,640, of which  67% could be annotated using Turkey and Zebra Finch genomes, or protein sequence information from SwissProt and NCBI databases. With our study, we have made a first step towards understanding the migratory phenotype regarding gene expression of a species that has become a model to study birds long-distance migrations.

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