The whole-genome duplication 80 million years ago of the common ancestor of salmonids (salmonid-specific fourth vertebrate whole-genome duplication, Ss4R) provides unique opportunities to learn about the evolutionary fate of a duplicated vertebrate genome in 70 extant lineages. Here we present a high-quality genome assembly for Atlantic salmon (Salmo salar), and show that large genomic reorganizations, coinciding with bursts of transposon-mediated repeat expansions, were crucial for the post-Ss4R rediploidization process. Comparisons of duplicate gene expression patterns across a wide range of tissues with orthologous genes from a pre-Ss4R outgroup unexpectedly demonstrate far more instances of neofunctionalization than subfunctionalization. Surprisingly, we find that genes that were retained as duplicates after the teleost-specific whole-genome duplication 320 million years ago were not more likely to be retained after the Ss4R, and that the duplicate retention was not influenced to a great extent by the nature of the predicted protein interactions of the gene products. Finally, we demonstrate that the Atlantic salmon assembly can serve as a reference sequence for the study of other salmonids for a range of purposes.

Monozygotic (MZ) twins do not show complete concordance for many complex diseases; for example, discordance rates for autoimmune diseases are 20%–80%. MZ discordance indicates a role for epigenetic or environmental factors in disease. We used MZ twins discordant for psoriasis to search for genome-wide differences in DNA methylation and gene expression in CD4⁺ and CD8⁺ cells using Illumina's HumanMethylation27 and HT-12 expression assays, respectively. Analysis of these data revealed no differentially methylated or expressed genes between co-twins when analyzed separately, although we observed a substantial amount of small differences. However, combined analysis of DNA methylation and gene expression identified genes where differences in DNA methylation between unaffected and affected twins were correlated with differences in gene expression. Several of the top-ranked genes according to significance of the correlation in CD4⁺ cells are known to be associated with psoriasis. Further, gene ontology (GO) analysis revealed enrichment of biological processes associated with the immune response and clustering of genes in a biological pathway comprising cytokines and chemokines. These data suggest that DNA methylation is involved in an epigenetic dysregulation of biological pathways involved in the pathogenesis of psoriasis. This is the first study based on data from MZ twins discordant for psoriasis to detect epigenetic alterations that potentially contribute to development of the disease. Psoriasis is a common chronic inflammatory disease, which affects mainly the skin, but also the joints. It is considered a T cell–mediated autoimmune disease. Autoimmune diseases are in general due to a dysregulation of the immune system, and identification of genes involved in alterations of lymphocyte function is therefore essential. Although there is convincing evidence of a genetic basis underlying psoriasis, there is also evidence for the involvement of environmental and/or epigenetic factors. Here we use MZ twins discordant for psoriasis to search for disease-causing epigenetic and transcriptomic alterations in isolated lymphocyte subpopulations. We identified many genes involved in the immune response where changes in DNA methylation between unaffected and affected twins correlated with changes in gene expression. In addition, several of these genes had previously been identified in GWAS and linkage studies of psoriasis. These findings suggest that psoriasis involves an epigenetic dysregulation of immune-system genes.

Background Four patients from three Norwegian families presented with a common skin phenotype of warts, molluscum contagiosum, and dermatitis since early childhood, and various other immunological features. Warts are a common manifestation of human papilloma virus (HPV), but when they are overwhelming, disseminated and/or persistent, and presenting together with other immunological features, a primary immunodeficiency disease (PIDD) may be suspected. Methods and results The four patients were exome sequenced as part of a larger study for detecting genetic causes of primary immunodeficiencies. No disease‐causing variants were identified in known primary immunodeficiency genes or in other disease‐related OMIM genes. However, the same homozygous missense variant in CARMIL2 (also known as RLTPR) was identified in all four patients. In each family, the variant was located within a narrow region of homozygosity, representing a potential region of autozygosity. CARMIL2 is a protein of undetermined function. A role in T‐cell activation has been suggested and the mouse protein homolog (Rltpr) is essential for costimulation of T‐cell activation via CD28, and for the development of regulatory T cells. Immunophenotyping demonstrated reduced regulatory, CD4+ memory, and CD4+ follicular T cells in all four patients. In addition, they all seem to have a deficiency in IFNγ ‐synthesis in CD4+ T cells and NK cells. Conclusions We report a novel primary immunodeficiency, and a differential molecular diagnosis to CXCR4‐, DOCK8‐, GATA2‐, MAGT1‐, MCM4‐, STK4‐, RHOH‐, TMC6‐, and TMC8‐related diseases. The specific variant may represent a Norwegian founder variant segregating on a population‐specific haplotype.

PUF60 encodes a nucleic acid-binding protein, a component of multimeric complexes regulating RNA splicing and transcription. In 2013, patients with microdeletions of chromosome 8q24.3 including PUF60 were found to have developmental delay, microcephaly, craniofacial, renal and cardiac defects. Very similar phenotypes have been described in six patients with variants in PUF60, suggesting that it underlies the syndrome. We report 12 additional patients with PUF60 variants who were ascertained using exome sequencing: six through the Deciphering Developmental Disorders Study and six through similar projects. Detailed phenotypic analysis of all patients was undertaken. All 12 patients had de novo heterozygous PUF60 variants on exome analysis, each confirmed by Sanger sequencing: four frameshift variants resulting in premature stop codons, three missense variants that clustered within the RNA recognition motif of PUF60 and five essential splice-site (ESS) variant. Analysis of cDNA from a fibroblast cell line derived from one of the patients with an ESS variants revealed aberrant splicing. The consistent feature was developmental delay and most patients had short stature. The phenotypic variability was striking; however, we observed similarities including spinal segmentation anomalies, congenital heart disease, ocular colobomata, hand anomalies and (in two patients) unilateral renal agenesis/horseshoe kidney. Characteristic facial features included micrognathia, a thin upper lip and long philtrum, narrow almond-shaped palpebral fissures, synophrys, flared eyebrows and facial hypertrichosis. Heterozygote loss-of-function variants in PUF60 cause a phenotype comprising growth/developmental delay and craniofacial, cardiac, renal, ocular and spinal anomalies, adding to disorders of human development resulting from aberrant RNA processing/spliceosomal function.

Summary: FILTUS is a stand-alone tool for working with annotated variant files, e.g. when searching for variants causing Mendelian disease. Very flexible in terms of input file formats, FILTUS offers efficient filtering and a range of downstream utilities, including statistical analysis of gene sharing patterns, detection of de novo mutations in trios, quality control plots and autozygosity mapping. The autozygosity mapping is based on a hidden Markov model and enables accurate detection of autozygous regions directly from exome-scale variant files. Availability and implementation: FILTUS is written in Python and runs on Windows, Mac and Linux. Binaries and source code are freely available at http://folk.uio.no/magnusv/filtus.html and on GitHub: https://github.com/magnusdv/filtus. Automatic installation is available via PyPI (e.g. pip install filtus). Contact:magnusdv@medisin.uio.no Supplementary information: Supplementary data are available at Bioinformatics online.