Tychele N. Turner

The paper analyzes de novo variants in 41,367 parent-child trios to explore sex differences in autism risk, identifying gene-specific and promoter-level associations.

The paper develops MoDIFI, a Bayesian framework to prioritize cell lines and regulatory regions for testing noncoding variants associated with neurodevelopmental disorders.

The paper identifies PSMC5 variants causing neurodevelopmental disorders and shows their impact on neuronal function and immune signaling, suggesting therapeutic targets.

This study uses whole-genome sequencing to analyze 9p deletion and duplication syndromes, identifying key genes and structural variants, and introduces a machine learning model for syndrome prediction.

The paper generates a mouse model with a deletion in an enhancer of EBF3, showing reduced Ebf3 expression and sex-specific behavioral and phenotypic differences.

The paper identifies human-specific gene expansions linked to brain evolution by analyzing genome sequences and functional models in zebrafish.

The paper assesses clustering of missense variants in neurodevelopmental disorders and cancer, identifying proteins with significant variation patterns in each condition.

HAT is a workflow for detecting de novo variants from short-read and long-read sequencing data using parent-child trio alignments.

The paper tests the PacBio Revio sequencer by generating high-coverage long-read sequencing data for a mouse neuronal cell line and evaluates its performance in variant detection and genome assembly.

The paper introduces the R package acorn for analyzing de novo variants, providing tools to subset data, calculate variant features, and assess parental age effects.

The paper identifies 60 new moderate risk genes for autism by integrating de novo and inherited variants across 42,607 cases and 236,000 controls.

This study shows that adjusting for ancestry improves genome-wide estimates of regional intolerance by incorporating demographic history, leading to better variant classification.

The paper identifies a de novo missense variant in KCNC2 in two affected siblings with autism and epilepsy using long-read sequencing, showing its potential clinical relevance.

The paper develops a Bayesian method to detect balancing selection across different sequencing technologies and identifies novel genes under selection in complex genomic regions.

The paper investigates family-specific contributions to de novo mutations and finds that stochasticity explains most of the variation.

This study uses iPSC models to show that a 15q13.3 duplication causes distinct neurodevelopmental and functional anomalies in an affected individual but not their unaffected mother, while both share increased cholinergic activity.

Whole-genome sequencing in thousands of families reveals variants relevant to simplex autism in a brain enhancer of the well-established neurodevelopmental disorder gene EBF3.

ACES is a computational workflow that queries specific sequences against multiple reference genomes to analyze conservation, generating alignment and phylogenetic data.

The paper identifies de novo variants in the 1000 Genomes Project using a GPU-based workflow, revealing cell line artifacts and cancer-related mutation profiles.

The paper investigates the correlation between 45S and 5S rDNA copy numbers in humans and finds no meaningful correlation, challenging previous claims of concerted variation.

The paper identifies ultra-rare inherited mutations that are younger and preferentially transmitted to autism probands, revealing novel candidate genes and functional networks.

The paper maps chromatin accessibility in developing human brain and organoids using scATAC-seq, revealing cell type-specific regulatory elements and their role in neurodevelopment.

The paper reports exome sequencing of 457 ASD families, identifying 10.4% with known ASD genes and 3.4% with possibly associated variants, and provides statistical support for 34 ASD risk genes using the TADA framework.