Biology subjects

Levy, S. E.

Publications and source records attributed to Levy, S. E..

7 recordsLinked to original sources

bioRxiv2024

A familial, telomere-to-telomere reference for human de novo mutation and recombination from a four-generation pedigree

Using five complementary short- and long-read sequencing technologies, we phased and assembled >95% of each diploid human genome in a four-generation, 28-member family (CEPH 1463) allowing us to systematically assess de novo mutations (DNMs) and recombination. From this family, we estimate an average of 192 DNMs per generation, including 75.5 de novo single-nucleotide variants (SNVs), 7.4 non-tandem repeat indels, 79.6 de novo indels or structural variants (SVs) originating from tandem repeats, 7.7 centromeric de novo SVs and SNVs, and 12.4 de novo Y chromosome events per generation. STRs and VNTRs are the most mutable with 32 loci exhibiting recurrent mutation through the generations. We accurately assemble 288 centromeres and six Y chromosomes across the generations, documenting de novo SVs, and demonstrate that the DNM rate varies by an order of magnitude depending on repeat content, length, and sequence identity. We show a strong paternal bias (75-81%) for all forms of germline DNM, yet we estimate that 17% of de novo SNVs are postzygotic in origin with no paternal bias. We place all this variation in the context of a high-resolution recombination map ([~]3.5 kbp breakpoint resolution). We observe a strong maternal recombination bias (1.36 maternal:paternal ratio) with a consistent reduction in the number of crossovers with increasing paternal (r=0.85) and maternal (r=0.65) age. However, we observe no correlation between meiotic crossover locations and de novo SVs, arguing against non-allelic homologous recombination as a predominant mechanism. The use of multiple orthogonal technologies, near-telomere-to-telomere phased genome assemblies, and a multi-generation family to assess transmission has created the most comprehensive, publicly available "truth set" of all classes of genomic variants. The resource can be used to test and benchmark new algorithms and technologies to understand the most fundamental processes underlying human genetic variation.

genomics↗

bioRxiv2024

Characterizing and addressing error modes to improve sequencing accuracy

The accuracy of a sequencing platform has traditionally been measured by the %Q30, or percentage of data exceeding a basecall accuracy of 99.9%. Improvements to accuracy beyond Q30 may be beneficial for certain applications such as the identification of low frequency alleles or the improvement of reference genomes. Here we demonstrate how we achieved over 70% Q50 (99.999% accuracy) data on the AVITI sequencer. This level of accuracy required us to not only improve sequencing quality but also to mitigate library preparation errors and analysis artifacts.

genomics↗

bioRxiv2023

Accurate human genome analysis with Element Avidity sequencing

We investigate the new sequencing technology Avidity from Element Biosciences. We show that Element whole genome sequencing achieves higher mapping and variant calling accuracy compared to Illumina sequencing at the same coverage, with larger differences at lower coverages (20x-30x). We quantify base error rates of Element reads, finding lower error rates, especially in homopolymer and tandem repeat regions. We use Elements ability to generate paired end sequencing with longer insert sizes than typical short-read sequencing. We show that longer insert sizes result in even higher accuracy, with long insert Element sequencing giving noticeably more accurate genome analyses at all coverages.

bioinformatics↗

bioRxiv2023

Utility of long-read sequencing for All of Us

The All of Us (AoU) initiative aims to sequence the genomes of over one million Americans from diverse ethnic backgrounds to improve personalized medical care. In a recent technical pilot, we compared the performance of traditional short-read sequencing with long-read sequencing in a small cohort of samples from the HapMap project and two AoU control samples representing eight datasets. Our analysis revealed substantial differences in the ability of these technologies to accurately sequence complex medically relevant genes, particularly in terms of gene coverage and pathogenic variant identification. We also considered the advantages and challenges of using low coverage sequencing to increase sample numbers in large cohort analysis. Our results show that HiFi reads produced the most accurate results for both small and large variants. Further, we present a cloud-based pipeline to optimize SNV, indel and SV calling at scale for long-reads analysis. These results will lead to widespread improvements across AoU.

bioinformatics↗

bioRxiv2021

Combinatorial transcription factor profiles predict mature and functional human islet α and β cells

Islet-enriched transcription factors (TFs) exert broad control over cellular processes in pancreatic and {beta} cells and changes in their expression are associated with developmental state and diabetes. However, the implications of heterogeneity in TF expression across islet cell populations are not well understood. To define this TF heterogeneity and its consequences for cellular function, we profiled >40,000 cells from normal human islets by scRNA-seq and stratified and {beta} cells based on combinatorial TF expression. Subpopulations of islet cells co-expressing ARX/MAFB ( cells) and MAFA/MAFB ({beta} cells) exhibited greater expression of key genes related to glucose sensing and hormone secretion relative to subpopulations expressing only one or neither TF. Moreover, all subpopulations were identified in native pancreatic tissue from multiple donors. By Patch-seq, MAFA/MAFB co-expressing {beta} cells showed enhanced electrophysiological activity. Thus, these results indicate combinatorial TF expression in islet and {beta} cells predicts highly functional, mature subpopulations.

genomics↗

bioRxiv2019

Single-Cell, Human Sperm Transcriptomes and Variants from Fathers of Autistic and Healthy Children

The human sperm is one of the smallest cells in the body, but also one of the most important, as it serves as the entire paternal genetic contribution to a child. This is especially relevant for diseases such as Autism Spectrum Disorders (ASD), which have been correlated with advance paternal age. Historically, most studies of sperm have focused on the assessment of a bulk sperm, wherein millions of individual sperm are present and only high-frequency variants can be detected. Using 10X Chromium single cell sequencing technology, we have assessed the RNA from >65,000 single sperm cells across 6 donors (scsperm-RNA-seq), including two of whom have autistic children and four that do not. Using multiple RNA-seq methods for differential expression and variant analysis, we found clusters of sperm mutations in each donor that are indicative of the sperm being produced by different stem cell pools. Moreover, by comparing the two groups, we have found expression changes that can separate out the two sets of donors. Finally, through our novel variant calling from single-cell RNA-seq methods, we have shown that we can detect mutation rates in sperm from ASD donors that is distinct from the controls, highlighting this method as a new means to characterize ASD risk.

genomics↗

bioRxiv2017

Genomic sequencing identifies secondary findings in a cohort of parent study participants

PURPOSEClinically relevant secondary variants were identified in parents enrolled with a child with developmental delay and intellectual disability.\n\nMETHODSExome/genome sequencing and analysis of 789 unaffected parents was performed.\n\nRESULTSPathogenic/likely pathogenic variants were identified in 21 genes within 25 individuals (3.2%), with 11 (1.4%) participants harboring variation in a gene defined as clinically actionable by the ACMG. Of the 25 individuals, five carried a variant consistent with a previous clinical diagnosis, thirteen were not previously diagnosed but had symptoms or family history with probable association with the detected variant, and seven reported no symptoms or family history of disease. A limited carrier screen was performed yielding 15 variants in 48 (6.1%) parents. Parents were also analyzed as mate-pairs to identify cases in which both parents were carriers for the same recessive disease; this led to one finding in ATP7B. Four participants had two findings (one carrier and one non-carrier variant). In total, 71 of the 789 enrolled parents (9.0%) received secondary findings.\n\nCONCLUSIONWe provide an overview of the rates and types of clinically relevant secondary findings, which may be useful in the design, and implementation of research and clinical sequencing efforts to identify such findings.

genomics↗