Deletion of Fibroblast growth factor 9 globally and in skeletal muscle results in enlarged tuberosities at sites of deltoid tendon attachments.

BACKGROUND: The growth of most bony tuberosities, like the deltoid tuberosity (DT), rely on the transmission of muscle forces at the tendon-bone attachment during skeletal growth. Tuberosities distribute muscle forces and provide mechanical leverage at attachment sites for joint stability and mobility. The genetic factors that regulate tuberosity growth remain largely unknown. In mouse embryos with global deletion of fibroblast growth factor 9 (Fgf9), the DT size is notably enlarged. In this study, we explored the tissue-specific regulation of DT size using both global and targeted deletion of Fgf9. RESULTS: We showed that cell hypertrophy and mineralization dynamics of the DT, as well as transcriptional signatures from skeletal muscle but not bone, were influenced by the global loss of Fgf9. Loss of Fgf9 during embryonic growth led to increased chondrocyte hypertrophy and reduced cell proliferation at the DT attachment site. This endured hypertrophy and limited proliferation may explain the abnormal mineralization patterns and locally dysregulated expression of markers of endochondral development in Fgf9null attachments. We then showed that targeted deletion of Fgf9 in skeletal muscle leads to postnatal enlargement of the DT. CONCLUSION: Taken together, we discovered that Fgf9 may play an influential role in muscle-bone cross-talk during embryonic and postnatal development.

CRISPR Spacers Indicate Preferential Matching of Specific Virioplankton Genes.

Viral infection exerts selection pressure on marine microbes, as virus-induced cell lysis causes 20 to 50% of cell mortality, resulting in fluxes of biomass into oceanic dissolved organic matter. Archaeal and bacterial populations can defend against viral infection using the clustered regularly interspaced short palindromic repeat (CRISPR)-associated (Cas) system, which relies on specific matching between a spacer sequence and a viral gene. If a CRISPR spacer match to any gene within a viral genome is equally effective in preventing lysis, no viral genes should be preferentially matched by CRISPR spacers. However, if there are differences in effectiveness, certain viral genes may demonstrate a greater frequency of CRISPR spacer matches. Indeed, homology search analyses of bacterioplankton CRISPR spacer sequences against virioplankton sequences revealed preferential matching of replication proteins, nucleic acid binding proteins, and viral structural proteins. Positive selection pressure for effective viral defense is one parsimonious explanation for these observations. CRISPR spacers from virioplankton metagenomes preferentially matched methyltransferase and phage integrase genes within virioplankton sequences. These virioplankton CRISPR spacers may assist infected host cells in defending against competing phage. Analyses also revealed that half of the spacer-matched viral genes were unknown, some genes matched several spacers, and some spacers matched multiple genes, a many-to-many relationship. Thus, CRISPR spacer matching may be an evolutionary algorithm, agnostically identifying those genes under stringent selection pressure for sustaining viral infection and lysis. Investigating this subset of viral genes could reveal those genetic mechanisms essential to virus-host interactions and provide new technologies for optimizing CRISPR defense in beneficial microbes.IMPORTANCE The CRISPR-Cas system is one means by which bacterial and archaeal populations defend against viral infection which causes 20 to 50% of cell mortality in the ocean. We tested the hypothesis that certain viral genes are preferentially targeted for the initial attack of the CRISPR-Cas system on a viral genome. Using CASC, a pipeline for CRISPR spacer discovery, and metagenome data from oceanic microbes and viruses, we found a clear subset of viral genes with high match frequencies to CRISPR spacers. Moreover, we observed a many-to-many relationship of spacers and viral genes. These high-match viral genes were involved in nucleotide metabolism, DNA methylation, and viral structure. It is possible that CRISPR spacer matching is an evolutionary algorithm pointing to those viral genes most important to sustaining infection and lysis. Studying these genes may advance the understanding of virus-host interactions in nature and provide new technologies for leveraging CRISPR-Cas systems in beneficial microbes.

MAP-RSeq: Mayo Analysis Pipeline for RNA sequencing.

BACKGROUND: Although the costs of next generation sequencing technology have decreased over the past years, there is still a lack of simple-to-use applications, for a comprehensive analysis of RNA sequencing data. There is no one-stop shop for transcriptomic genomics. We have developed MAP-RSeq, a comprehensive computational workflow that can be used for obtaining genomic features from transcriptomic sequencing data, for any genome. RESULTS: For optimization of tools and parameters, MAP-RSeq was validated using both simulated and real datasets. MAP-RSeq workflow consists of six major modules such as alignment of reads, quality assessment of reads, gene expression assessment and exon read counting, identification of expressed single nucleotide variants (SNVs), detection of fusion transcripts, summarization of transcriptomics data and final report. This workflow is available for Human transcriptome analysis and can be easily adapted and used for other genomes. Several clinical and research projects at the Mayo Clinic have applied the MAP-RSeq workflow for RNA-Seq studies. The results from MAP-RSeq have thus far enabled clinicians and researchers to understand the transcriptomic landscape of diseases for better diagnosis and treatment of patients. CONCLUSIONS: Our software provides gene counts, exon counts, fusion candidates, expressed single nucleotide variants, mapping statistics, visualizations, and a detailed research data report for RNA-Seq. The workflow can be executed on a standalone virtual machine or on a parallel Sun Grid Engine cluster. The software can be downloaded from http://bioinformaticstools.mayo.edu/research/maprseq/.

Integrated genomic characterization reveals novel, therapeutically relevant drug targets in FGFR and EGFR pathways in sporadic intrahepatic cholangiocarcinoma.

Advanced cholangiocarcinoma continues to harbor a difficult prognosis and therapeutic options have been limited. During the course of a clinical trial of whole genomic sequencing seeking druggable targets, we examined six patients with advanced cholangiocarcinoma. Integrated genome-wide and whole transcriptome sequence analyses were performed on tumors from six patients with advanced, sporadic intrahepatic cholangiocarcinoma (SIC) to identify potential therapeutically actionable events. Among the somatic events captured in our analysis, we uncovered two novel therapeutically relevant genomic contexts that when acted upon, resulted in preliminary evidence of anti-tumor activity. Genome-wide structural analysis of sequence data revealed recurrent translocation events involving the FGFR2 locus in three of six assessed patients. These observations and supporting evidence triggered the use of FGFR inhibitors in these patients. In one example, preliminary anti-tumor activity of pazopanib (in vitro FGFR2 IC50≈350 nM) was noted in a patient with an FGFR2-TACC3 fusion. After progression on pazopanib, the same patient also had stable disease on ponatinib, a pan-FGFR inhibitor (in vitro, FGFR2 IC50≈8 nM). In an independent non-FGFR2 translocation patient, exome and transcriptome analysis revealed an allele specific somatic nonsense mutation (E384X) in ERRFI1, a direct negative regulator of EGFR activation. Rapid and robust disease regression was noted in this ERRFI1 inactivated tumor when treated with erlotinib, an EGFR kinase inhibitor. FGFR2 fusions and ERRFI mutations may represent novel targets in sporadic intrahepatic cholangiocarcinoma and trials should be characterized in larger cohorts of patients with these aberrations.

SoftSearch: integration of multiple sequence features to identify breakpoints of structural variations.

BACKGROUND: Structural variation (SV) represents a significant, yet poorly understood contribution to an individual's genetic makeup. Advanced next-generation sequencing technologies are widely used to discover such variations, but there is no single detection tool that is considered a community standard. In an attempt to fulfil this need, we developed an algorithm, SoftSearch, for discovering structural variant breakpoints in Illumina paired-end next-generation sequencing data. SoftSearch combines multiple strategies for detecting SV including split-read, discordant read-pair, and unmated pairs. Co-localized split-reads and discordant read pairs are used to refine the breakpoints. RESULTS: We developed and validated SoftSearch using real and synthetic datasets. SoftSearch's key features are 1) not requiring secondary (or exhaustive primary) alignment, 2) portability into established sequencing workflows, and 3) is applicable to any DNA-sequencing experiment (e.g. whole genome, exome, custom capture, etc.). SoftSearch identifies breakpoints from a small number of soft-clipped bases from split reads and a few discordant read-pairs which on their own would not be sufficient to make an SV call. CONCLUSIONS: We show that SoftSearch can identify more true SVs by combining multiple sequence features. SoftSearch was able to call clinically relevant SVs in the BRCA2 gene not reported by other tools while offering significantly improved overall performance.