Well differentiated papillary mesothelioma of the peritoneum (WDPMP) is a rare variant of epithelial mesothelioma of low malignancy potential, usually found in women with no history of asbestos exposure. In this study, we perform the first exome sequencing of WDPMP.

Accurate and individualized prediction of response to therapies is central to precision medicine. However, because of the generally complex and multifaceted nature of clinical drug response, realizing this vision is highly challenging, requiring integrating different data types from the same individual into one prediction model. We used the anti-epileptic drug brivaracetam as a case study and combine a hybrid data/knowledge-driven feature extraction with machine learning to systematically integrate clinical and genetic data from a clinical discovery dataset (n = 235 patients). We constructed a model that successfully predicts clinical drug response [area under the curve (AUC) = 0.76] and show that even with limited sample size, integrating high-dimensional genetics data with clinical data can inform drug response prediction. After further validation on data collected from an independently conducted clinical study (AUC = 0.75), we extensively explore our model to gain insights into the determinants of drug response, and identify various clinical and genetic characteristics predisposing to poor response. Finally, we assess the potential impact of our model on clinical trial design and demonstrate that, by enriching for probable responders, significant reductions in clinical study sizes may be achieved. To our knowledge, our model represents the first retrospectively validated machine learning model linking drug mechanism of action and the genetic, clinical and demographic background in epilepsy patients to clinical drug response. Hence, it provides a blueprint for how machine learning-based multimodal data integration can act as a driver in achieving the goals of precision medicine in fields such as neurology.

Next generation sequencing technology has revolutionized the study of cancers. Through matched normal-tumor pairs, it is now possible to identify genome-wide germline and somatic mutations. The generation and analysis of the data requires rigorous quality checks and filtering, and the current analytical pipeline is constantly undergoing improvements. We noted however that in analyzing matched pairs, there is an implicit assumption that the sequenced data are matched, without any quality check such as those implemented in association studies. There are serious implications in this assumption as identification of germline and rare somatic variants depend on the normal sample being the matched pair. Using a genetics concept on measuring relatedness between individuals, we demonstrate that the matchedness of tumor pairs can be quantified and should be included as part of a quality protocol in analysis of sequenced data. Despite the mutation changes in cancer samples, matched tumor-normal pairs are still relatively similar in sequence compared to non-matched pairs. We demonstrate that the approach can be used to assess the mutation landscape between individuals.

Prokaryotes are in general believed to possess small, compactly organized genomes, with repetitive sequences forming only a small part of them. Nonetheless, many prokaryotic genomes in fact contain species-specific repeats (>85 bp long genomic sequences with less than 60% identity to other species) as we have previously demonstrated. However, it is not known at present how frequent such species-specific repeats are and what their functional roles in bacterial genomes may be. Therefore, we have conducted a comprehensive survey of prokaryotic species-specific repeats and characterized them to examine as to whether there are functional classes among different repeats or not and how they are mutually related to each other. Of the 613 distinct prokaryotic species analyzed, 97% were found to contain at least one species-specific repeats. It seems interesting to note that the species-specific repeats thus identified appear to be functionally variable in different genomes: in some genomes, they are mostly associated with duplicated protein-coding genes, whereas in some other genomes with rRNA and tRNA genes. Contrary to what may be expected, only one-fourth of the species-specific repeats were found to be associated with mobile genetic elements.

Polymerase chain reaction (PCR) is a basic molecular biology technique with a multiplicity of uses, including deoxyribonucleic acid cloning and sequencing, functional analysis of genes, diagnosis of diseases, genotyping and discovery of genetic variants. Reliable primer design is crucial for successful PCR, and for over a decade, the open-source Primer3 software has been widely used for primer design, often in high-throughput genomics applications. It has also been incorporated into numerous publicly available software packages and web services. During this period, we have greatly expanded Primer3's functionality. In this article, we describe Primer3's current capabilities, emphasizing recent improvements. The most notable enhancements incorporate more accurate thermodynamic models in the primer design process, both to improve melting temperature prediction and to reduce the likelihood that primers will form hairpins or dimers. Additional enhancements include more precise control of primer placement-a change motivated partly by opportunities to use whole-genome sequences to improve primer specificity. We also added features to increase ease of use, including the ability to save and re-use parameter settings and the ability to require that individual primers not be used in more than one primer pair. We have made the core code more modular and provided cleaner programming interfaces to further ease integration with other software. These improvements position Primer3 for continued use with genome-scale data in the decade ahead.

Choosing appropriate primers is probably the single most important factor affecting the polymerase chain reaction (PCR). Specific amplification of the intended target requires that primers do not have matches to other targets in certain orientations and within certain distances that allow undesired amplification. The process of designing specific primers typically involves two stages. First, the primers flanking regions of interest are generated either manually or using software tools; then they are searched against an appropriate nucleotide sequence database using tools such as BLAST to examine the potential targets. However, the latter is not an easy process as one needs to examine many details between primers and targets, such as the number and the positions of matched bases, the primer orientations and distance between forward and reverse primers. The complexity of such analysis usually makes this a time-consuming and very difficult task for users, especially when the primers have a large number of hits. Furthermore, although the BLAST program has been widely used for primer target detection, it is in fact not an ideal tool for this purpose as BLAST is a local alignment algorithm and does not necessarily return complete match information over the entire primer range.

Autism spectrum disorder (ASD) represents a group of neurodevelopmental phenotypes with a strong genetic component. An excess of likely gene-disruptive (LGD) mutations in GIGYF1 was implicated in ASD. Here, we report that GIGYF1 is the second-most mutated gene among known ASD high-confidence risk genes. We investigated the inheritance of 46 GIGYF1 LGD variants, including the highly recurrent mutation c.333del:p.L111Rfs*234. Inherited GIGYF1 heterozygous LGD variants were 1.8 times more common than de novo mutations. Among individuals with ASD, cognitive impairments were less likely in those with GIGYF1 LGD variants relative to those with other high-confidence gene mutations. Using a Gigyf1 conditional KO mouse model, we showed that haploinsufficiency in the developing brain led to social impairments without significant cognitive impairments. In contrast, homozygous mice showed more severe social disability as well as cognitive impairments. Gigyf1 deficiency in mice led to a reduction in the number of upper-layer cortical neurons, accompanied by a decrease in proliferation and increase in differentiation of neural progenitor cells. We showed that GIGYF1 regulated the recycling of IGF-1R to the cell surface. KO of GIGYF1 led to a decreased level of IGF-1R on the cell surface, disrupting the IGF-1R/ERK signaling pathway. In summary, our findings show that GIGYF1 is a regulator of IGF-1R recycling. Haploinsufficiency of GIGYF1 was associated with autistic behavior, likely through interference with IGF-1R/ERK signaling pathway.

The concentration of pathogen DNA in biological samples is often very low. Therefore, the sensitivity of diagnostic tests is always a critical factor.

Carcinoma of the oral tongue (OTSCC) is the most common malignancy of the oral cavity, characterized by frequent recurrence and poor survival. The last three decades has witnessed a change in the OTSCC epidemiological profile, with increasing incidence in younger patients, females and never-smokers. Here, we sought to characterize the OTSCC genomic landscape and to determine factors that may delineate the genetic basis of this disease, inform prognosis and identify targets for therapeutic intervention.

Microsatellite instability (MSI) is a form of hypermutation that occurs in some tumors due to defects in cellular DNA mismatch repair. MSI is characterized by frequent somatic mutations (i.e., cancer-specific mutations) that change the length of simple repeats (e.g., AAAAA…., GATAGATAGATA...). Clinical MSI tests evaluate the lengths of a handful of simple repeat sites, while next-generation sequencing can assay many more sites and offers a much more complete view of their somatic mutation frequencies. Using somatic mutation data from the exomes of a 361-tumor training set, we developed classifiers to determine MSI status based on four machine-learning frameworks. All frameworks had high accuracy, and after choosing one we determined that it had >98% concordance with clinical tests in a separate 163-tumor test set. Furthermore, this classifier retained high concordance even when classifying tumors based on subsets of whole-exome data. We have released a CRAN R package, MSIseq, based on this classifier. MSIseq is faster and simpler to use than software that requires large files of aligned sequenced reads. MSIseq will be useful for genomic studies in which clinical MSI test results are unavailable and for detecting possible misclassifications by clinical tests.

The X-chromosome gene USP9X encodes a deubiquitylating enzyme that has been associated with neurodevelopmental disorders primarily in female subjects. USP9X escapes X inactivation, and in female subjects de novo heterozygous copy number loss or truncating mutations cause haploinsufficiency culminating in a recognizable syndrome with intellectual disability and signature brain and congenital abnormalities. In contrast, the involvement of USP9X in male neurodevelopmental disorders remains tentative.

Gastric cancer, a leading cause of cancer death worldwide, has been little studied compared with other cancers that impose similar health burdens. Our goal is to assess genomic copy-number loss and the possible functional consequences and therapeutic implications thereof across a large series of gastric adenocarcinomas.

Autoimmunity can occur when a checkpoint of self-tolerance fails. The study of familial autoimmune diseases can reveal pathophysiological mechanisms involved in more common autoimmune diseases. Here, by whole-exome/genome sequencing we identify heterozygous, autosomal-dominant, germline loss-of-function mutations in the SOCS1 gene in ten patients from five unrelated families with early onset autoimmune manifestations. The intracellular protein SOCS1 is known to downregulate cytokine signaling by inhibiting the JAK-STAT pathway. Accordingly, patient-derived lymphocytes exhibit increased STAT activation in vitro in response to interferon-γ, IL-2 and IL-4 that is reverted by the JAK1/JAK2 inhibitor ruxolitinib. This effect is associated with a series of in vitro and in vivo immune abnormalities consistent with lymphocyte hyperactivity. Hence, SOCS1 haploinsufficiency causes a dominantly inherited predisposition to early onset autoimmune diseases related to cytokine hypersensitivity of immune cells.

Gastric cancer is the second highest cause of global cancer mortality. To explore the complete repertoire of somatic alterations in gastric cancer, we combined massively parallel short read and DNA paired-end tag sequencing to present the first whole-genome analysis of two gastric adenocarcinomas, one with chromosomal instability and the other with microsatellite instability.

SLITRK2 is a single-pass transmembrane protein expressed at postsynaptic neurons that regulates neurite outgrowth and excitatory synapse maintenance. In the present study, we report on rare variants (one nonsense and six missense variants) in SLITRK2 on the X chromosome identified by exome sequencing in individuals with neurodevelopmental disorders. Functional studies showed that some variants displayed impaired membrane transport and impaired excitatory synapse-promoting effects. Strikingly, these variations abolished the ability of SLITRK2 wild-type to reduce the levels of the receptor tyrosine kinase TrkB in neurons. Moreover, Slitrk2 conditional knockout mice exhibited impaired long-term memory and abnormal gait, recapitulating a subset of clinical features of patients with SLITRK2 variants. Furthermore, impaired excitatory synapse maintenance induced by hippocampal CA1-specific cKO of Slitrk2 caused abnormalities in spatial reference memory. Collectively, these data suggest that SLITRK2 is involved in X-linked neurodevelopmental disorders that are caused by perturbation of diverse facets of SLITRK2 function.