Sebastian Bartschat

The duck genome and transcriptome provide insight into an avian influenza virus reservoir species

The duck (Anas platyrhynchos) is one of the principal natural hosts of influenza A viruses. We present the duck genome sequence and perform deep transcriptome analyses to investigate immune-related genes. Our data indicate that the duck possesses a contractive immune gene repertoire, as in chicken and zebra finch, and this repertoire has been shaped through lineage-specific duplications. We identify genes that are responsive to influenza A viruses using the lung transcriptomes of control ducks and ones that were infected with either a highly pathogenic (A/duck/Hubei/49/05) or a weakly pathogenic (A/goose/Hubei/65/05) H5N1 virus. Further, we show how the ducks defense mechanisms against influenza infection have been optimized through the diversification of its β-defensin and butyrophilin-like repertoires. These analyses, in combination with the genomic and transcriptomic data, provide a resource for characterizing the interaction between host and influenza viruses.

Evolution of the let-7 microRNA family.

The increase of bodyplan complexity in early bilaterian evolution is correlates with the advent and diversification of microRNAs. These small RNAs guide animal development by regulating temporal transitions in gene expression involved in cell fate choices and transitions between pluripotency and differentiation. One of the two known microRNAs whose origins date back before the bilaterian ancestor is mir-100. In Bilateria, it appears stably associated in polycistronic transcripts with let-7 and mir-125, two key regulators of development. In vertebrates, these three microRNA families have expanded to form a complex system of developmental regulators. In this contribution, we disentangle the evolutionary history of the let-7 locus, which was restructured independently in nematodes, platyhelminths, and deuterostomes. The foundation of a second let-7 locus in the common ancestor of vertebrates and urochordates predates the vertebrate-specific genome duplications, which then caused a rapid expansion of the let-7 family.

U12 type introns were lost at multiple occasions during evolution

BackgroundTwo categories of introns are known, a common U2 type and a rare U12 type. These two types of introns are removed by distinct spliceosomes. The phylogenetic distribution of spliceosomal RNAs that are characteristic of the U12 spliceosome, i.e. the U11, U12, U4atac and U6atac RNAs, suggest that U12 spliceosomes were lost in many phylogenetic groups. We have now examined the distribution of U2 and U12 introns in many of these groups.ResultsU2 and U12 introns were predicted by making use of available EST and genomic sequences. The results show that in species or branches where U12 spliceosomal components are missing, also U12 type of introns are lacking. Examples are the choanoflagellate Monosiga brevicollis, Entamoeba histolytica, green algae, diatoms, and the fungal lineage Basidiomycota. Furthermore, whereas U12 splicing does not occur in Caenorhabditis elegans, U12 introns as well as U12 snRNAs are present in Trichinella spiralis, which is deeply branching in the nematode tree. A comparison of homologous genes in T. spiralis and C. elegans revealed different mechanisms whereby U12 introns were lost.ConclusionsThe phylogenetic distribution of U12 introns and spliceosomal RNAs give further support to an early origin of U12 dependent splicing. In addition, this distribution identifies a large number of instances during eukaryotic evolution where such splicing was lost.

Animal snoRNAs and scaRNAs with exceptional structures

The overwhelming majority of small nucleolar RNAs (snoRNAs) fall into two clearly defined classes characterized by distinctive secondary structures and sequence motifs. A small group of diverse ncRNAs, however, shares the hallmarks of one or both classes of snoRNAs but differs substantially from the norm in some respects. Here, we compile the available information on these exceptional cases, conduct a thorough homology search throughout the available metazoan genomes, provide improved and expanded alignments, and investigate the evolutionary histories of these ncRNA families as well as their mutual relationships.

snoStrip: a snoRNA annotation pipeline

MOTIVATION Although small nucleolar RNAs form an important class of non-coding RNAs, no comprehensive annotation efforts have been undertaken, presumably because the task is complicated by both the large number of distinct small nucleolar RNA families and their relatively rapid pace of sequence evolution. RESULTS With snoStrip we present an automatic annotation pipeline developed specifically for comparative genomics of small nucleolar RNAs. It makes use of sequence conservation, canonical box motifs as well as secondary structure and predicts putative targets. AVAILABILITY AND IMPLEMENTATION The snoStrip web service and the download version is available at http://snostrip.bioinf.uni-leipzig.de/

Matching of Soulmates: Coevolution of snoRNAs and Their Targets

Ribosomal and small nuclear RNAs (snRNAs) comprise numerous modified nucleotides. The modification patterns are retained during evolution, making it even possible to project them from yeast onto human. The stringent conservation of modification sites and the slow evolution of rRNAs and snRNAs contradicts the rapid evolution of small nucleolar RNA (snoRNA) sequences. To explain this discrepancy, we investigated the coevolution of snoRNAs and their targeted sites throughout vertebrates. To measure and evaluate the conservation of RNA-RNA interactions, we defined the interaction conservation index (ICI). It combines the quality of individual interaction with the scope of its conservation in a set of species and serves as an efficient measure to evaluate the conservation of the interaction of snoRNA and target. We show that functions of homologous snoRNAs are evolutionarily stable, thus, members of the same snoRNA family guide equivalent modifications. The conservation of snoRNA sequences is high at target binding regions while the remaining sequence varies significantly. In addition to elucidating principles of correlated evolution, we were able, with the help of the ICI measure, to assign functions to previously orphan snoRNAs and to associate snoRNAs as partners to known chemical modifications unassigned to a given snoRNA. Furthermore, we used predictions of snoRNA functions in conjunction with sequence conservation to identify distant homologies. Because of the high overall entropy of snoRNA sequences, such relationships are hard to detect by means of sequence homology search methods alone.

Structured RNAs and synteny regions in the pig genome

BackgroundAnnotating mammalian genomes for noncoding RNAs (ncRNAs) is nontrivial since far from all ncRNAs are known and the computational models are resource demanding. Currently, the human genome holds the best mammalian ncRNA annotation, a result of numerous efforts by several groups. However, a more direct strategy is desired for the increasing number of sequenced mammalian genomes of which some, such as the pig, are relevant as disease models and production animals.ResultsWe present a comprehensive annotation of structured RNAs in the pig genome. Combining sequence and structure similarity search as well as class specific methods, we obtained a conservative set with a total of 3,391 structured RNA loci of which 1,011 and 2,314, respectively, hold strong sequence and structure similarity to structured RNAs in existing databases. The RNA loci cover 139 cis-regulatory element loci, 58 lncRNA loci, 11 conflicts of annotation, and 3,183 ncRNA genes. The ncRNA genes comprise 359 miRNAs, 8 ribozymes, 185 rRNAs, 638 snoRNAs, 1,030 snRNAs, 810 tRNAs and 153 ncRNA genes not belonging to the here fore mentioned classes. When running the pipeline on a local shuffled version of the genome, we obtained no matches at the highest confidence level. Additional analysis of RNA-seq data from a pooled library from 10 different pig tissues added another 165 miRNA loci, yielding an overall annotation of 3,556 structured RNA loci. This annotation represents our best effort at making an automated annotation. To further enhance the reliability, 571 of the 3,556 structured RNAs were manually curated by methods depending on the RNA class while 1,581 were declared as pseudogenes. We further created a multiple alignment of pig against 20 representative vertebrates, from which RNAz predicted 83,859 de novo RNA loci with conserved RNA structures. 528 of the RNAz predictions overlapped with the homology based annotation or novel miRNAs. We further present a substantial synteny analysis which includes 1,004 lineage specific de novo RNA loci and 4 ncRNA loci in the known annotation specific for Laurasiatheria (pig, cow, dolphin, horse, cat, dog, hedgehog).ConclusionsWe have obtained one of the most comprehensive annotations for structured ncRNAs of a mammalian genome, which is likely to play central roles in both health modelling and production. The core annotation is available in Ensembl 70 and the complete annotation is available at http://rth.dk/resources/rnannotator/susscr102/version1.02.

MicroRNA or not MicroRNA

The avalanche of next generation sequencing data has led to a rapid increase of annotated microRNAs in the last few years. Many of them are specific to individual species or rather narrow clades. A closer inspection of the current version of miRBase shows that dozens of entries conflict with other ncRNAs, in particular snoRNAs.With few exceptions, these cases show little similarities to canonical microRNAs, however, and thus they should be considered as mis-annotations.

Genome-Wide Identification of Non-coding RNAs in Komagatella pastoris str. GS115

The methylotrophic yeast Komagatella pastoris is a relevant bioengineering platform for protein synthesis. Even though non-coding RNAs are well known to be key players in the control of gene expression no comprehensive annotation of non-coding RNAs has been reported for this species. We combine here published RNA-seq data with a wide array of homology based annotation tools and de novo gene predictions to compile the non-coding RNAs in K. pastoris.