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Abstract Background MicroRNAs (miRNAs) are a class of small regulatory RNAs that target sequences in messenger RNAs (mRNAs) to inhibit their protein output. Dissecting the complexities of miRNA function continues to prove challenging as miRNAs are predicted to have thousands of targets, and mRNAs can be targeted by dozens of miRNAs. Results To systematically address biological function of miRNAs, we constructed and validated a lentiviral miRNA expression library containing 660 currently annotated and 422 candidate human miRNA precursors. The miRNAs are expressed from their native genomic backbone, ensuring physiological processing. The arrayed layout of the library renders it ideal for high-throughput screens, but also allows pooled screening and hit picking. We demonstrate its functionality in both short- and long-term assays, and are able to corroborate previously described results of well-studied miRNAs. Conclusions With the miRNA expression library we provide a versatile tool for the systematic elucidation of miRNA function.

Abstract Background Phenotype-driven forward genetic experiments are powerful approaches for linking phenotypes to genomic elements but they still involve a laborious positional cloning process. Although sequencing of complete genomes now becomes available, discriminating causal mutations from the enormous amounts of background variation remains a major challenge. Method To improve this, we developed a universal two-step approach, named 'fast forward genetics', which combines traditional bulk segregant techniques with targeted genomic enrichment and next-generation sequencing technology Results As a proof of principle we successfully applied this approach to two Arabidopsis mutants and identified a novel factor required for stem cell activity. Conclusion We demonstrated that the 'fast forward genetics' procedure efficiently identifies a small number of testable candidate mutations. As the approach is independent of genome size, it can be applied to any model system of interest. Furthermore, we show that experiments can be multiplexed and easily scaled for the identification of multiple individual mutants in a single sequencing run.

Abstract Background Genetic variation in the regulatory region of the human serotonin transporter gene (SLC6A4) has been shown to affect brain functionality and personality. However, large heterogeneity in its biological effects is observed, which is at least partially due to genetic modifiers. To gain insight into serotonin transporter (SERT)-specific genetic modifiers, we studied an intercross between the Wistar SERT-/- rat and the behaviorally and genetically divergent Brown Norway rat, and performed a QTL analysis. Results In a cohort of >150 intercross SERT-/- and control (SERT+/+) rats we characterized 12 traits that were previously associated with SERT deficiency, including activity, exploratory pattern, cocaine-induced locomotor activity, and abdominal and subcutaneous fat. Using 325 genetic markers, 10 SERT-/--specific quantitative trait loci (QTLs) for parameters related to activity and exploratory pattern (Chr.1,9,11,14), and cocaine-induced anxiety and locomotor activity (Chr.5,8) were identified. No significant QTLs were found for fat parameters. Using in silico approaches we explored potential causal genes within modifier QTL regions and found interesting candidates, amongst others, the 5-HT1D receptor (Chr. 5), dopamine D2 receptor (Chr. 8), cannabinoid receptor 2 (Chr. 5), and genes involved in fetal development and plasticity (across chromosomes). Conclusions We anticipate that the SERT-/--specific QTLs may lead to the identification of new modulators of serotonergic signaling, which may be targets for pharmacogenetic and therapeutic approaches.

Abstract Background Digital gene expression (DGE) profiling has become an established tool to study RNA expression. Here, we provide an in-depth analysis of small RNA DGE profiles from two different rat strains (BN-Lx and SHR) from six different rat tissues (spleen, liver, brain, testis, heart, kidney). We describe the expression patterns of known and novel micro (mi)RNAs and piwi-interacting (pi)RNAs. Results We confirmed the expression of 588 known miRNAs (54 in antisense orientation) and identified 56 miRNAs homologous to known human or mouse miRNAs, as well as 45 new rat miRNAs. Furthermore, we confirmed specific A to I editing in brain for mir-376a/b/c and identified mir-377 as a novel editing target. In accordance with earlier findings, we observed a highly tissue-specific expression pattern for all tissues analyzed. The brain was found to express the highest number of tissue-specific miRNAs, followed by testis. Notably, our experiments also revealed robust strain-specific differential miRNA expression in the liver that is caused by genetic variation between the strains. Finally, we identified two types of germline-specific piRNAs in testis, mapping either to transposons or in strand-specific clusters. Conclusions Taken together, the small RNA compendium described here advances the annotation of small RNAs in the rat genome. Strain and tissue-specific expression patterns furthermore provide a strong basis for studying the role of small RNAs in regulatory networks as well as biological process like physiology and neurobiology that are extensively studied in this model system.

Abstract Background The laboratory rat (Rattus norvegicus) is one of the preferred model organisms in physiological and pharmacological research, although the availability of specific genetic models, especially gene knockouts, is limited. N-ethyl-N-nitrosourea (ENU)-driven target-selected mutagenesis is currently the most successful method in rats, although it is still very laborious and expensive. Results As ENU-induced DNA damage is normally recognized by the mismatch repair (MMR) system, we hypothesized that the effectiveness of the target-selected mutagenesis approach could be improved by using a MMR-deficient genetic background. Indeed, Msh6 knockout rats were found to be more sensitive to ENU treatment and the germ line mutation rate was boosted more than two-fold to 1 mutation per 585 kb. In addition, the molecular mutation spectrum was found to be changed in favor of generating knockout-type alleles by ~20%, resulting in an overall increase in efficiency of ~2.5 fold. The improved effectiveness was demonstrated by high throughput mutation discovery in 70 Mb of sequence in a set of only 310 mutant F1 rats. This resulted in the identification of 89 mutations of which four introduced a premature stopcodon and 64 resulted in amino acid changes. Conclusion Taken together, we show that the use of a MMR-deficient background considerably improves ENU-driven target-selected mutagenesis in the rat, thereby reducing animal use as well as screening costs. The use of a mismatch repair-deficient genetic background for improving mutagenesis and target-selected knockout efficiency is in principle applicable to any organism of interest.

Abstract Background The laboratory rat (Rattus norvegicus) is an important model for human disease, and is extensively used for studying complex traits for example in the physiological and pharmacological fields. To facilitate genetic studies like QTL mapping, genetic makers that can be easily typed, like SNPs, are essential. Results A genome-wide set of 820 SNP assays was designed for the KASPar genotyping platform, which uses a technique based on allele specific oligo extension and energy transfer-based detection. SNPs were chosen to be equally spread along all chromosomes except Y and to be polymorphic between Brown Norway and SS or Wistar rat strains based on data from the rat HapMap EU project. This panel was tested on 38 rats of 34 different strains and 3 wild rats to determine the level of polymorphism and to generate a phylogenetic network to show their genetic relationships. As a proof of principle we used this panel to map an obesity trait in Zucker rats and confirmed significant linkage (LOD 122) to chromosome 5: 119–129 Mb, where the leptin receptor gene (Lepr) is located (chr5: 122 Mb). Conclusion We provide a fast and cost-effective platform for genome-wide SNP typing, which can be used for first-pass genetic mapping and association studies in a wide variety of rat strains.

Abstract Background The laboratory rat (Rattus norvegicus) is an important model for studying many aspects of human health and disease. Detailed knowledge on genetic variation between strains is important from a biomedical, particularly pharmacogenetic point of view and useful for marker selection for genetic cloning and association studies. Results We show that Single Nucleotide Polymorphisms (SNPs) in commonly used rat strains are surprisingly well represented in wild rat isolates. Shotgun sequencing of 814 Kbp in one wild rat resulted in the identification of 485 SNPs as compared with the Brown Norway genome sequence. Genotyping 36 commonly used inbred rat strains showed that 84% of these alleles are also polymorphic in a representative set of laboratory rat strains. Conclusion We postulate that shotgun sequencing in a wild rat sample and subsequent genotyping in multiple laboratory or domesticated strains rather than direct shotgun sequencing of multiple strains, could be the most efficient SNP discovery approach. For the rat, laboratory strains still harbor a large portion of the haplotypes present in wild isolates, suggesting a relatively recent common origin and supporting the idea that rat inbred strains, in contrast to mouse inbred strains, originate from a single species, R. norvegicus.

Abstract Background With the recent progress made in large-scale genome sequencing projects a vast amount of novel data is becoming available. A comparative sequence analysis, exploiting sequence information from various resources, can be used to uncover hidden information, such as genetic variation. Although there are enormous amounts of SNPs for a wide variety of organisms submitted to NCBI dbSNP and annotated in most genome assembly viewers like Ensembl and the UCSC Genome Browser, these platforms do not easily allow for extensive annotation and incorporation of experimental data supporting the polymorphism. However, such information is very important for selecting the most promising and useful candidate polymorphisms for use in experimental setups. Description The CASCAD database is designed for presentation and query of candidate SNPs that are retrieved by in silico mining of high-throughput sequencing data. Currently, the database provides collections of laboratory rat (Rattus norvegicus) and zebrafish (Danio rerio) candidate SNPs. The database stores detailed information about raw data supporting the candidate, extensive annotation and links to external databases (e.g. GenBank, Ensembl, UniGene, and LocusLink), verification information, and predictions of a potential effect for non-synonymous polymorphisms in coding regions. The CASCAD website allows search based on an arbitrary combination of 27 different parameters related to characteristics like candidate SNP quality, genomic localization, and sequence data source or strain. In addition, the database can be queried with any custom nucleotide sequences of interest. The interface is crosslinked to other public databases and tightly coupled with primer design and local genome assembly interfaces in order to facilitate experimental verification of candidates. Conclusions The CASCAD database discloses detailed information on rat and zebrafish candidate SNPs, including the raw data underlying its discovery. An advanced web-based search interface http://cascad.niob.knaw.nl allows universal access to the database content and allows various queries supporting many types of research utilizing single nucleotide polymorphisms.

In cancer, the primary tumour's organ of origin and histopathology are the strongest determinants of its clinical behaviour, but in 3% of cases a patient presents with a metastatic tumour and no obvious primary. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we train a deep learning classifier to predict cancer type based on patterns of somatic passenger mutations detected in whole genome sequencing (WGS) of 2606 tumours representing 24 common cancer types produced by the PCAWG Consortium. Our classifier achieves an accuracy of 91% on held-out tumor samples and 88% and 83% respectively on independent primary and metastatic samples, roughly double the accuracy of trained pathologists when presented with a metastatic tumour without knowledge of the primary. Surprisingly, adding information on driver mutations reduced accuracy. Our results have clinical applicability, underscore how patterns of somatic passenger mutations encode the state of the cell of origin, and can inform future strategies to detect the source of circulating tumour DNA.

Metastatic castration-resistant prostate cancer (mCRPC) has a highly complex genomic landscape. With the recent development of novel treatments, accurate stratification strategies are needed. Here we present the whole-genome sequencing (WGS) analysis of fresh-frozen metastatic biopsies from 197 mCRPC patients. Using unsupervised clustering based on genomic features, we define eight distinct genomic clusters. We observe potentially clinically relevant genotypes, including microsatellite instability (MSI), homologous recombination deficiency (HRD) enriched with genomic deletions and BRCA2 aberrations, a tandem duplication genotype associated with CDK12-/- and a chromothripsis-enriched subgroup. Our data suggests that stratification on WGS characteristics may improve identification of MSI, CDK12-/- and HRD patients. From WGS and ChIP-seq data, we show the potential relevance of recurrent alterations in non-coding regions identified with WGS and highlight the central role of AR signaling in tumor progression. These data underline the potential value of using WGS to accurately stratify mCRPC patients into clinically actionable subgroups.