Biology subjects

Koboldt, D. C.

Publications and source records attributed to Koboldt, D. C..

5 recordsLinked to original sources

bioRxiv2026

Disrupted O-GalNAc glycosylation as a mechanism and biomarker of SLC35A2-associated epilepsy

Rare germline and somatic variants in SLC35A2 cause a spectrum of severe glycosylation disorders that commonly present with epilepsy. SLC35A2 encodes the Golgi transporter for UDP-galactose, but how its deficiency leads to severe neurodevelopmental disorders is unknown. Using a mouse model deficient for Slc35a2 in the forebrain, we identified a specific defect in O-GalNAc glycan synthesis, while other galactose-containing glycoconjugates remained intact. O-GalNAc glycans were absent from their normal location within neuronal tracts of the corpus callosum, and truncated precursors accumulated in the cortex on critical extracellular matrix molecules. Cultured primary neurons lacking Slc35a2 showed impaired development, hyperexcitability, and impaired O-GalNAc glycosylation. Finally, human brain tissue from cases of SLC35A2-associated intractable epilepsy displayed a strong correlation between variant burden and truncated O-GalNAc glycans. These findings provide a mechanistic link between genetic causes of SLC35A2-associated epilepsy and protein O-glycosylation that can be targeted for biomarker and therapeutic development.

neuroscience↗

bioRxiv2025

Lipid transport is necessary for neocortical lamination

We previously described the Alkuraya-Ku[c]inskas syndrome, a disorder associated with biallelic variants in BLTP1 (bridge-like lipid transfer protein), a.k.a. KIAA1109. The majority of probands die perinatally with corpus callosum agenesis, ventriculomegaly and arthrogryposis. Homozygous ablation of mouse Bltp1 resulted in similar preweaning lethality. Here, we describe ten novel patients expanding the characterization of this syndrome at the mild end of the phenotypic spectrum. To model this syndrome, we engineered Emx1-Cre-mediated conditional knockouts (cKO) in which Bltp1 expression is only removed in cortical and hippocampal neurons. This restricted ablation of Bltp1 recapitulated the preweaning lethality observed in the constitutional knockouts, suggesting that lack of BLTP1 expression in neurons is sufficient to cause death. Homozygous cKO presented a complete agenesis of the corpus callosum, a smaller anterior commissure, a malformed hippocampus and a reduced thickness of the cortical plate with a complete lack of defined structural layers and absence of radial glial and intermediate neural progenitors and mature neurons. As BLTP1 was shown to be a barrel-shaped tube containing lipids, we compared the amount of lipid species in the cKO and their control littermates cortexes. We observed significant depletions of ether-linked phosphatidylethanolamines and triglycerides and accumulations of sphingomyelins and hexosylceramides in cKOs. Our results are consistent with the recent description of BLTP1 as a tubular protein that transports phospholipids between the endoplasmic reticulum and the plasma membrane. They suggest that non-vesicular lipid transport is essential for neocortical and cerebellar lamination. Consistent with a BLTP1 role in cortex development we show that heterozygous carriers of a BLTP1 truncation variant presented a decrease in peripheral cortical grey matter suggesting an autosomal dominant inheritance pattern beside the already described autosomal recessive.

genetics↗

bioRxiv2021

Discovery of Clinically Relevant Fusions in Pediatric Cancer

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSPediatric cancers typically have a distinct genomic landscape when compared to adult cancers and frequently carry somatic gene fusion events that alter gene expression and drive tumorigenesis. Sensitive and specific detection of gene fusions through the analysis of next-generation-based RNA sequencing (RNA-Seq) data is computationally challenging and may be confounded by low tumor cellularity or underlying genomic complexity. Furthermore, numerous computational tools are available to identify fusions from supporting RNA-Seq reads, yet each algorithm demonstrates unique variability in sensitivity and precision, and no clearly superior approach currently exists. To overcome these challenges, we have developed an ensemble fusion calling approach to increase the accuracy of identifying fusions. ResultsOur ensemble fusion detection approach utilizes seven fusion calling algorithms: Arriba, CICERO, FusionMap, FusionCatcher, JAFFA, MapSplice, and STAR-Fusion, which are packaged as a fully automated pipeline using Docker and AWS serverless technology. This method uses paired end RNA-Seq sequence reads as input, and the output from each algorithm is examined to identify fusions detected by a consensus of at least three algorithms. These consensus fusion results are filtered by comparison to an internal database to remove likely artifactual fusions occurring at high frequencies in our internal cohort, while a "known fusion list" prevents failure to report known pathogenic events. We have employed the ensemble fusion-calling pipeline on RNA-Seq data from 229 patients with pediatric cancer or blood disorders studied under an IRB-approved protocol. The samples consist of 138 central nervous system tumors, 73 solid tumors, and 18 hematologic malignancies or disorders. The combination of an ensemble fusion-calling pipeline and a knowledge-based filtering strategy identified 67 clinically relevant fusions among our cohort (diagnostic yield of 29.3%), including RBPMS-MET, BCAN-NTRK1, and TRIM22-BRAF fusions. Following clinical confirmation and reporting in the patients medical record, both known and novel fusions provided medically meaningful information. ConclusionsOur ensemble fusion detection pipeline offers a streamlined approach to discover fusions in cancer, at higher levels of sensitivity and accuracy than single algorithm methods. Furthermore, this method accurately identifies driver fusions in pediatric cancer, providing clinical impact by contributing evidence to diagnosis and, when appropriate, indicating targeted therapies.

genomics↗

bioRxiv2018

Exome sequencing identifies high impact trait-associated alleles enriched in Finns

As yet undiscovered rare variants are hypothesized to substantially influence an individuals risk for common diseases and traits, but sequencing studies aiming to identify such variants have generally been underpowered. In isolated populations that have expanded rapidly after a population bottleneck, deleterious alleles that passed through the bottleneck may be maintained at much higher frequencies than in other populations. In an exome sequencing study of nearly 20,000 cohort participants from northern and eastern Finnish populations that exemplify this phenomenon, most novel trait-associated deleterious variants displayed frequencies 10-173 times higher than in other European populations. These enriched alleles underlie 30 novel associations with 20 disease-related quantitative traits and demonstrate a geographical clustering equivalent to that of Mendelian disease mutations characteristic of the Finnish population. Sequencing studies in populations without this unique history would require hundreds of thousands to millions of participants for comparable power.

genomics↗

bioRxiv2018

Quality Control and Integration of Genotypes from Two Calling Pipelines for Whole Genome Sequence Data in the Alzheimer’s Disease Sequencing Project

The Alzheimers Disease Sequencing Project (ADSP) performed whole genome sequencing (WGS) of 584 subjects from 111 multiplex families at three sequencing centers. Genotype calling of single nucleotide variants (SNVs) and insertion-deletion variants (indels) was performed centrally using GATK-HaplotypeCaller and Atlas V2. The ADSP Quality Control (QC) Working Group applied QC protocols to project-level variant call format files (VCFs) from each pipeline, and developed and implemented a novel protocol, termed \"consensus calling,\" to combine genotype calls from both pipelines into a single high-quality set. QC was applied to autosomal bi-allelic SNVs and indels, and included pipeline-recommended QC filters, variant-level QC, and sample-level QC. Low-quality variants or genotypes were excluded, and sample outliers were noted. Quality was assessed by examining Mendelian inconsistencies (MIs) among 67 parent-offspring pairs, and MIs were used to establish additional genotype-specific filters for GATK calls. After QC, 578 subjects remained. Pipeline-specific QC excluded ~12.0% of GATK and 14.5% of Atlas SNVs. Between pipelines, ~91% of SNV genotypes across all QCed variants were concordant; 4.23% and 4.56% of genotypes were exclusive to Atlas or GATK, respectively; the remaining ~0.01% of discordant genotypes were excluded. For indels, variant-level QC excluded ~36.8% of GATK and 35.3% of Atlas indels. Between pipelines, ~55.6% of indel genotypes were concordant; while 10.3% and 28.3% were exclusive to Atlas or GATK, respectively; and ~0.29% of discordant genotypes were. The final WGS consensus dataset contains 27,896,774 SNVs and 3,133,926 indels and is publicly available.\n\nAbbreviationsAD, Alzheimers disease; QC, Quality Control; LSSAC, Large-Scale Sequencing and Analysis Center; Broad, Broad Institute Genomics Service; Baylor, Baylor College of Medicine Human Genome Sequencing Center; WashU, Washington University-St. Louis McDonnell Genome Institute; WGS, whole genome sequencing; WES, whole exome sequencing; indel, insertion-deletion variants; VCF, variant control format; MI, Mendelian inconsistency; MC, Mendelian consistency; GWAS, genome-wide association study; VR, referent allele read depth; DP, overall read depth; MS, mapping score; GQ, genotype quality score; Ti/Tv, Transition/Transversion; CS, concordance code

genetics↗