smCounter2: an accurate low-frequency variant caller for targeted sequencing data with unique molecular identifiers.

MOTIVATION: Low-frequency DNA mutations are often confounded with technical artifacts from sample preparation and sequencing. With unique molecular identifiers (UMIs), most of the sequencing errors can be corrected. However, errors before UMI tagging, such as DNA polymerase errors during end repair and the first PCR cycle, cannot be corrected with single-strand UMIs and impose fundamental limits to UMI-based variant calling. RESULTS: We developed smCounter2, a UMI-based variant caller for targeted sequencing data and an upgrade from the current version of smCounter. Compared to smCounter, smCounter2 features lower detection limit that decreases from 1 to 0.5%, better overall accuracy (particularly in non-coding regions), a consistent threshold that can be applied to both deep and shallow sequencing runs, and easier use via a Docker image and code for read pre-processing. We benchmarked smCounter2 against several state-of-the-art UMI-based variant calling methods using multiple datasets and demonstrated smCounter2's superior performance in detecting somatic variants. At the core of smCounter2 is a statistical test to determine whether the allele frequency of the putative variant is significantly above the background error rate, which was carefully modeled using an independent dataset. The improved accuracy in non-coding regions was mainly achieved using novel repetitive region filters that were specifically designed for UMI data. AVAILABILITY AND IMPLEMENTATION: The entire pipeline is available at https://github.com/qiaseq/qiaseq-dna under MIT license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A case-control collapsing analysis identifies epilepsy genes implicated in trio sequencing studies focused on de novo mutations.

Trio exome sequencing has been successful in identifying genes with de novo mutations (DNMs) causing epileptic encephalopathy (EE) and other neurodevelopmental disorders. Here, we evaluate how well a case-control collapsing analysis recovers genes causing dominant forms of EE originally implicated by DNM analysis. We performed a genome-wide search for an enrichment of "qualifying variants" in protein-coding genes in 488 unrelated cases compared to 12,151 unrelated controls. These "qualifying variants" were selected to be extremely rare variants predicted to functionally impact the protein to enrich for likely pathogenic variants. Despite modest sample size, three known EE genes (KCNT1, SCN2A, and STXBP1) achieved genome-wide significance (p<2.68×10-6). In addition, six of the 10 most significantly associated genes are known EE genes, and the majority of the known EE genes (17 out of 25) originally implicated in trio sequencing are nominally significant (p<0.05), a proportion significantly higher than the expected (Fisher's exact p = 2.33×10-17). Our results indicate that a case-control collapsing analysis can identify several of the EE genes originally implicated in trio sequencing studies, and clearly show that additional genes would be implicated with larger sample sizes. The case-control analysis not only makes discovery easier and more economical in early onset disorders, particularly when large cohorts are available, but also supports the use of this approach to identify genes in diseases that present later in life when parents are not readily available.

Modeling of a negative feedback mechanism explains antagonistic pleiotropy in reproduction in domesticated Caenorhabditis elegans strains.

Most biological traits and common diseases have a strong but complex genetic basis, controlled by large numbers of genetic variants with small contributions to a trait or disease risk. The effect-size of most genetic variants is not absolute and is instead dependent upon multiple factors such as the age and genetic background of an organism. In order to understand the mechanistic basis of these changes, we characterized heritable trait differences between two domesticated strains of C. elegans. We previously identified a major effect locus, caused in part by a mutation in a component of the NURF chromatin remodeling complex, that regulates reproductive output in an age-dependent manner. The effect-size of this locus changes from positive to negative over the course of an animal's reproductive lifespan. Here, we use a previously published macroscale model of the egg-laying rate in C. elegans to show that time-dependent effect-size is explained by an unequal use of sperm combined with negative feedback between sperm and ovulation rate. We validate key predictions of this model with controlled mating experiments and quantification of oogenesis and sperm use. Incorporation of this model into QTL mapping allows us to identify and partition new QTLs into specific aspects of the egg-laying process. Finally, we show how epistasis between two genetic variants is predicted by this modeling as a consequence of the unequal use of sperm. This work demonstrates how modeling of multicellular communication systems can improve our ability to predict and understand the role of genetic variation on a complex phenotype. Negative autoregulatory feedback loops, common in transcriptional regulation, could play an important role in modifying genetic architecture in other traits.

Characterization of a variant of t(14;18) negative nodal diffuse follicular lymphoma with CD23 expression, 1p36/TNFRSF14 abnormalities, and STAT6 mutations.

A predominantly diffuse growth pattern and CD23 co-expression are uncommon findings in nodal follicular lymphoma and can create diagnostic challenges. A single case series in 2009 (Katzenberger et al) proposed a unique morphologic variant of nodal follicular lymphoma, characterized by a predominantly diffuse architecture, lack of the t(14;18) IGH/BCL2 translocation, presence of 1p36 deletion, frequent inguinal lymph node involvement, CD23 co-expression, and low clinical stage. Other studies on CD23+ follicular lymphoma, while associating inguinal location, have not specifically described this architecture. In addition, no follow-up studies have correlated the histopathologic and cytogenetic/molecular features of these cases, and they remain a diagnostic problem. We identified 11 cases of diffuse, CD23+ follicular lymphoma with histopathologic features similar to those described by Katzenberger et al. Along with pertinent clinical information, we detail their histopathology, IGH/BCL2 translocation status, lymphoma-associated chromosomal gains/losses, and assessment of mutations in 220 lymphoma-associated genes by massively parallel sequencing. All cases showed a diffuse growth pattern around well- to ill-defined residual germinal centers, uniform CD23 expression, mixed centrocytic/centroblastic cytology, and expression of at least one germinal center marker. Ten of 11 involved inguinal lymph nodes, 5 solely. By fluorescence in situ hybridization analysis, the vast majority lacked IGH/BCL2 translocation (9/11). Deletion of 1p36 was observed in five cases and included TNFRSF14. Of the six cases lacking 1p36 deletion, TNFRSF14 mutations were identified in three, highlighting the strong association of 1p36/TNFRSF14 abnormalities with this follicular lymphoma variant. In addition, 9 of the 11 cases tested (82%) had STAT6 mutations and nuclear P-STAT6 expression was detectable in the mutated cases by immunohistochemistry. The proportion of STAT6 mutations is higher than recently reported in conventional follicular lymphoma (11%). These findings lend support for a clinicopathologic variant of t(14;18) negative nodal follicular lymphoma and suggests importance of the interleukin (IL)-4/JAK/STAT6 pathway in this variant.