The precisionFDA Truth Challenge V2 aimed to assess the state of the art of variant calling in challenging genomic regions. Starting with FASTQs, 20 challenge participants applied their variant-calling pipelines and submitted 64 variant call sets for one or more sequencing technologies (Illumina, PacBio HiFi, and Oxford Nanopore Technologies). Submissions were evaluated following best practices for benchmarking small variants with updated Genome in a Bottle benchmark sets and genome stratifications. Challenge submissions included numerous innovative methods, with graph-based and machine learning methods scoring best for short-read and long-read datasets, respectively. With machine learning approaches, combining multiple sequencing technologies performed particularly well. Recent developments in sequencing and variant calling have enabled benchmarking variants in challenging genomic regions, paving the way for the identification of previously unknown clinically relevant variants.

Modern horses represent heterogeneous populations specifically selected for appearance and performance. Genomic regions under high selective pressure show characteristic runs of homozygosity (ROH) which represent a low genetic diversity. This study aims at detecting the number and functional distribution of ROHs in different horse populations using next generation sequencing data. Next generation sequencing was performed for two Sorraia, one Dülmen Horse, one Arabian, one Saxon-Thuringian Heavy Warmblood, one Thoroughbred and four Hanoverian. After quality control reads were mapped to the reference genome EquCab2.70. ROH detection was performed using PLINK, version 1.07 for a trimmed dataset with 11,325,777 SNPs and a mean read depth of 12. Stretches with homozygous genotypes of >40 kb as well as >400 kb were defined as ROHs. SNPs within consensus ROHs were tested for neutrality. Functional classification was done for genes annotated within ROHs using PANTHER gene list analysis and functional variants were tested for their distribution among breed or non-breed groups. ROH detection was performed using whole genome sequences of ten horses of six populations representing various breed types and non-breed horses. In total, an average number of 3492 ROHs were detected in windows of a minimum of 50 consecutive homozygous SNPs and an average number of 292 ROHs in windows of 500 consecutive homozygous SNPs. Functional analyses of private ROHs in each horse revealed a high frequency of genes affecting cellular, metabolic, developmental, immune system and reproduction processes. In non-breed horses, 198 ROHs in 50-SNP windows and seven ROHs in 500-SNP windows showed an enrichment of genes involved in reproduction, embryonic development, energy metabolism, muscle and cardiac development whereas all seven breed horses revealed only three common ROHs in 50-SNP windows harboring the fertility-related gene YES1. In the Hanoverian, a total of 18 private ROHs could be shown to be located in the region of genes potentially involved in neurologic control, signaling, glycogen balance and reproduction. Comparative analysis of homozygous stretches common in all ten horses displayed three ROHs which were all located in the region of KITLG, the ligand of KIT known to be involved in melanogenesis, haematopoiesis and gametogenesis. The results of this study give a comprehensive insight into the frequency and number of ROHs in various horses and their potential influence on population diversity and selection pressures. Comparisons of breed and non-breed horses suggest a significant artificial as well as natural selection pressure on reproduction performance in all types of horse populations.

Objective To describe a new spinocerebellar ataxia (SCA48) characterized by early cerebellar cognitive-affective syndrome (CCAS) and late-onset SCA. Methods This is a descriptive study of a family that has been followed for more than a decade with periodic neurologic and neuropsychological examinations, MRI, brain SPECT perfusion, and genetic analysis. Whole exome sequencing was performed in 3 affected and 1 unaffected family member and subsequently validated by linkage analysis of chromosome 16p13.3. Results Six patients fully developed cognitive-affective and complete motor cerebellar syndrome associated with vermian and hemispheric cerebellar atrophy, suggesting a continuum from a dysexecutive syndrome slowly evolving to a complete and severe CCAS with late truncal ataxia. Three presymptomatic patients showed focal cerebellar atrophy in the vermian, paravermian, and the medial part of cerebellar lobes VI and VII, suggesting that cerebellar atrophy preceded the ataxia, and that the neurodegeneration begins in cerebellar areas related to cognition and emotion, spreading later to the whole cerebellum. Among the candidate variants, only the frameshift heterozygous c.823_824delCT STUB1 (p.L275Dfs*16) pathogenic variant cosegregated with the disease. The p.L275Dfs*16 heterozygous STUB1 pathogenic variant leads to neurodegeneration and atrophy in cognition- and emotion-related cerebellar areas and reinforces the importance of STUB1 in maintaining cognitive cerebellar function. Conclusions We report a heterozygous STUB1 pathogenic genetic variant causing dominant cerebellar ataxia. Since recessive mutations in STUB1 gene have been previously associated with SCAR16, these findings suggest a previously undescribed SCA locus (SCA48; MIM# 618093).

Objective—Stimulation of monocytes with P-selectin induces the synthesis of an array of mediators of inflammation, as well as the expression of tissue factor (TF), the main initiator of coagulation. Because the membrane-bound reactions of coagulation are profoundly influenced by the presence of phosphatidylserine on the membranes of cells, factors that increase its expression may have an impact on coagulation.Methods and Results—Using flow cytometry, we studied the effect of P-selectin on phosphatidylserine expression in blood monocytes and in the monocytic cells, THP-1. Soluble P-selectin at biologically relevant concentrations (0.31 to 2.5 μg/mL) induced a time-dependent increase in phosphatidylserine expression, an effect that could be inhibited with an anti–PSGL-1 blocking antibody, and by genistein, a tyrosine kinase inhibitor. Binding of activated platelets to THP-1 cells also resulted in a significant increase in phosphatidylserine expression that was dependent on PSGL-1. Consistent with the role of phosphatidylserine on surface-dependent reactions of coagulation, treatment of monocytic cells with soluble P-selectin led to increased thrombin generation. We excluded P-selectin induced apoptosis of monocyte as a mechanism for the increased phosphatidylserine exposure.Conclusion—In summary, we show that P-selectin, either soluble or in its membrane-bound form, induces phosphatidylserine exposure in monocytes through a mechanism dependent on PSGL-1.

Rare disease patients are more likely to receive a rapid molecular diagnosis nowadays thanks to the wide adoption of next generation sequencing. However, many cases remain undiagnosed even after exome or genome analysis, because the methods used missed the molecular cause in a known gene, or a novel causative gene could not be identified and/or confirmed. To address these challenges, the RD-Connect Genome-Phenome Analysis Platform (GPAP) facilitates the collation, discovery, sharing and analysis of standardised genome-phenome data within a collaborative environment. Authorised clinicians and researchers submit pseudonymised phenotypic profiles encoded using the Human Phenotype Ontology, and raw genomic data which is processed through a standardised pipeline. After an optional embargo period, the data is shared with other platform users, with the objective that similar cases in the system and queries from peers may help diagnose the case. Additionally, the platform enables bidirectional discovery of similar cases in other databases from the Matchmaker Exchange network. To facilitate genome-phenome analysis and interpretation by clinical researchers, the RD-Connect GPAP provides a powerful user-friendly interface and leverages tens of information sources. As a result, the resource has already helped diagnose hundreds of rare disease patients and discover new disease causing genes.