Biology subjects

McDaniel, J.

Publications and source records attributed to McDaniel, J..

11 recordsLinked to original sources

bioRxiv2026

Long-read genome sequencing reveals complex variability in lentiviral provirus insertions in deeply characterized Clonal CD19 CAR-T vector copy number reference cell lines

Chimeric antigen receptor (CAR)-T cell therapy is an important therapy involving provirus insertions in the genome. Characterizing these insertions is important for understanding the safety and efficacy of cell products, but the sequence of these insertions is not fully characterized. We generate clonal CD19 CAR-T cell lines with one to five copies of the lentiviral provirus insertions. Vector copy number (VCN) was determined by droplet digital PCR (ddPCR), which revealed that most of the elements (LTR, Psi, RRE, CD19, and WPRE) were 1 to 5 or 6 copies per cell. DdPCR data also revealed that there was an additional copy of eGFP gene in VCN4 and VCN5 cell lines. To fully characterize the sequences and locations of these insertions, we use short- and long-read whole genome sequencing as well as digital PCR and flow cytometry. Long-reads enable full resolution of each insertion, and we find that of 10 insertion events, 3 have the expected insertion sequence, 2 differ from the expected only in small variants, 3 have structural abnormalities, and 2 are small partial insertions missed by most other approaches. One particularly important structural abnormality resolved only by long-reads is a 724 bp deletion of the EF1 promoter disrupting expression of the CD19 CAR. Standard short-read and ddPCR approaches miss this deletion due to this commonly used promoter being in the unengineered human genome. These results demonstrated that these cell lines are suitable VCN reference standards for 1 to 5 or 6 copies and highlight the utility of long-read sequencing in characterizing both quantity and quality of insertions in lentiviral-engineered cells.

genomics↗

bioRxiv2026

A complete human pancreatic cancer genome

Cancer genome sequencing is essential for understanding tumor evolution and advancing precision medicine.1 However, reference gaps and germline variants obscure detection of small and large somatic variants and methylation in repetitive regions.1-3 It is common for tumor cells to gain or lose chromosome arms due to somatic structural changes that occur inside highly repetitive satellite DNA sequences in the centromeres.4 To identify the full spectrum of somatic variants, including complex rearrangements, we construct and curate near-complete, haplotype-resolved assemblies of the most recent common ancestor of an early-passage broadly-consented hypodiploid pancreatic cancer cell line and matched normal tissues. The tumor assembly completely recapitulates all 35 tumor chromosomes observed with karyotyping, with multiple translocation-induced hybrid chromosomes. The hybrid chromosomes contain putative functional dicentric and fused centromeres, nested foldback inversions causing 14 breakpoints with a haplotype switch in a single event, and centromeric satellite tandem duplications up to 136 kbp. Direct comparison of tumor and normal assembly haplotypes uncovers >7,000 variants altering >1 Mbp of sequence in repetitive regions that have been hidden by reference gaps and germline variants. 44 % of somatic small variants change representation because they alter germline variants on GRCh38, impacting mutational signatures and kataegis/omikli clusters. Most somatic LINE insertions originate from two hypomethylated non-reference germline LINE insertions, highlighting their impact on insertion mutation burden. These assemblies demonstrate that centromeric, acrocentric, and telomeric regions conventionally excluded from analysis harbor extensive somatic and epigenetic changes. Resolving complete tumor genomes enables a deeper understanding of cancer structural plasticity and the endpoints of breakage-fusion-bridge cycles. These assembled, curated paired normal-tumor benchmarks will serve as a critical foundation for developing future algorithms to characterize the most intractable regions of cancer genomes.

genomics↗

bioRxiv2026

Inter-hemispheric connections modulate splitting in a computational model of the bilateral SCN

The phenomenon of splitting was originally observed in hamsters which, after prolonged exposure to constant light, exhibit two rest/wake cycles within a subjective day. Splitting is a consequence of the left and right suprachiasmatic nuclei (SCN) falling out of synchrony. While it is known that split activity is characterized by an antiphase relationship between the left and right SCN and between the core and shell within each hemisphere, the role of the commissural projections that connect the right and left SCN is not known. In the present study, we investigate the impact of the inter-hemispheric connections on the split and unsplit dynamics of a computational model of the bilateral SCN. Our model has 4 nodes corresponding to each right and left core and shell. We simulated our bilateral model under different lighting conditions and measured its period and the phase relationships among the 4 nodes. To further characterize the dynamics of the system, we performed a bifurcation analysis. We found that the bilateral model automatically splits unless entrained by bright light/dark cycles, or unless it has excitatory inter-hemispheric connections. This suggests that excitatory cross-connections may be important for freerunning behavior. We found that constant light of varying intensities transitions the model between split and unsplit activity only in very limited conditions, but the strength and polarity of the contralateral connections play a much greater role in this dynamical transition. These findings suggest that splitting may involve plasticity of the inter-hemispheric connections of the SCN.

neuroscience↗

bioRxiv2023

Small variant benchmark from a complete assembly of X and Y chromosomes

The sex chromosomes contain complex, important genes impacting medical phenotypes, but differ from the autosomes in their ploidy and large repetitive regions. To evaluate variant detection on chromosomes X and Y, we created an 111,725 variant benchmark for the Genome in a Bottle HG002 reference material. We show how complete assemblies can expand benchmarks to difficult regions, but highlight remaining challenges benchmarking complex gene conversions, copy number variable gene arrays, and human satellites.

genomics↗

bioRxiv2023

The GIAB genomic stratifications resource for human reference genomes

Stratification of the genome into different genomic contexts is useful when developing bioinformatics software like variant callers, to assess performance in difficult regions in the human genome. Here we describe a set of genomic stratifications for the human reference genomes GRCh37, GRCh38, and T2T-CHM13v2.0. Generating stratifications for the new complete CHM13 reference genome is critical to understanding improvements in variant caller performance when using this new complete reference. The GIAB stratifications can be used when benchmarking variant calls to analyze difficult regions of the human genome in a standardized way. Here we present stratifications in the CHM13 genome in comparison to GRCh37 and GRCh38, highlighting expansions in hard-to-map and GC-rich stratifications which provide useful insight for accuracy of variants in these newly-added regions. To evaluate the reliability and utility of the new stratifications, we used the stratifications of the three references to assess accuracy of variant calls in diverse, challenging genomic regions. The means to generate these stratifications are available as a snakemake pipeline at https://github.com/ndwarshuis/giab-stratifications.

genomics↗

bioRxiv2022

THE MAJOR ROLE OF JUNCTIONAL DIVERSITY IN THE HORSE ANTIBODY REPERTOIRE

The sequencing of the antibody repertoire (Rep-seq) revolutionized the diversity of antigen B cell receptor studies, allowing deep and quantitative analysis to decipher the role of adaptive immunity in health and disease. Particularly, horse (Equus caballus) polyclonal antibodies have been produced and used since the century XIX to treat and prophylaxis of diphtheria, tuberculosis, tetanus, pneumonia, and, more recently, COVID-19. However, our knowledge about the horse B cell receptors repertories is minimal. We present a deep horse antibody heavy chain repertoire (IGH) characterization of non-immunized horses using HTS technology. In this study, we obtained a mean of 248,169 unique IgM clones and 66,141 unique IgG clones from four domestic adult horses. Rarefaction analysis showed sequence coverage was between 52 and 82% in IgM and IgG isotypes. We observed that besides horses antibody can use all of the functional IGHV genes, around 80% of their antibodies use only three IGHV gene segments, and around 55% use only one IGHJ gene segment. This limited VJ diversity seems to be compensated by the junctional diversity of these antibodies. We observed that the junctional diversity in horses antibodies is highly frequent, present in more than 90% of horse antibodies. Besides this, the length of this region seems to be higher in horse antibodies than in other species. N1 and N2 nucleotides addition range from 0 to 111 nucleotides. In addition, around 45% of the antibody clones have more than ten nucleotides in both N1 and N2 junction regions. This diversity mechanism may be one of the most important in providing variability to the equine antibody repertoire. This study provides new insights regarding horse antibody composition, diversity generation, and particularities compared to other species, such as the frequency and length of N nucleotide addition. This study also points out the urgent need to better characterize TdT in horses and in other species to better understand antibody repertoire characteristics.

immunology↗

bioRxiv2022

Automated assembly of high-quality diploid human reference genomes

The current human reference genome, GRCh38, represents over 20 years of effort to generate a high-quality assembly, which has greatly benefited society1, 2. However, it still has many gaps and errors, and does not represent a biological human genome since it is a blend of multiple individuals3, 4. Recently, a high-quality telomere-to-telomere reference genome, CHM13, was generated with the latest long-read technologies, but it was derived from a hydatidiform mole cell line with a duplicate genome, and is thus nearly homozygous5. To address these limitations, the Human Pangenome Reference Consortium (HPRC) recently formed with the goal of creating a collection of high-quality, cost-effective, diploid genome assemblies for a pangenome reference that represents human genetic diversity6. Here, in our first scientific report, we determined which combination of current genome sequencing and automated assembly approaches yields the most complete, accurate, and cost-effective diploid genome assemblies with minimal manual curation. Approaches that used highly accurate long reads and parent-child data to sort haplotypes during assembly outperformed those that did not. Developing a combination of all the top performing methods, we generated our first high- quality diploid reference assembly, containing only [~]4 gaps (range 0-12) per chromosome, most within + 1% of CHM13s length. Nearly 1/4th of protein coding genes have synonymous amino acid changes between haplotypes, and centromeric regions showed the highest density of variation. Our findings serve as a foundation for assembling near-complete diploid human genomes at the scale required for constructing a human pangenome reference that captures all genetic variation from single nucleotides to large structural rearrangements.

genomics↗

bioRxiv2021

A complete reference genome improves analysis of human genetic variation

Compared to its predecessors, the Telomere-to-Telomere CHM13 genome adds nearly 200 Mbp of sequence, corrects thousands of structural errors, and unlocks the most complex regions of the human genome to clinical and functional study. Here we demonstrate how the new reference universally improves read mapping and variant calling for 3,202 and 17 globally diverse samples sequenced with short and long reads, respectively. We identify hundreds of thousands of novel variants per sample--a new frontier for evolutionary and biomedical discovery. Simultaneously, the new reference eliminates tens of thousands of spurious variants per sample, including up to 12-fold reduction of false positives in 269 medically relevant genes. The vast improvement in variant discovery coupled with population and functional genomic resources position T2T-CHM13 to replace GRCh38 as the prevailing reference for human genetics. One Sentence SummaryThe T2T-CHM13 reference genome universally improves the analysis of human genetic variation.

genomics↗

bioRxiv2021

Towards a Comprehensive Variation Benchmark for Challenging Medically-Relevant Autosomal Genes

The repetitive nature and complexity of multiple medically important genes make them intractable to accurate analysis, despite the maturity of short-read sequencing, resulting in a gap in clinical applications of genome sequencing. The Genome in a Bottle Consortium has provided benchmark variant sets, but these excluded some medically relevant genes due to their repetitiveness or polymorphic complexity. In this study, we characterize 273 of these 395 challenging autosomal genes that have multiple implications for medical sequencing. This extended, curated benchmark reports over 17,000 SNVs, 3,600 INDELs, and 200 SVs each for GRCh37 and GRCh38 across HG002. We show that false duplications in either GRCh37 or GRCh38 result in reference-specific, missed variants for short- and long-read technologies in medically important genes including CBS, CRYAA, and KCNE1. Our proposed solution improves variant recall in these genes from 8% to 100%. This benchmark will significantly improve the comprehensive characterization of these medically relevant genes and guide new method development.

genomics↗

bioRxiv2020

precisionFDA Truth Challenge V2: Calling variants from short- and long-reads in difficult-to-map regions

The precisionFDA Truth Challenge V2 aimed to assess the state-of-the-art of variant calling in difficult-to-map regions and the Major Histocompatibility Complex (MHC). Starting with FASTQ files, 20 challenge participants applied their variant calling pipelines and submitted 64 variant callsets for one or more sequencing technologies (~35X Illumina, ~35X PacBio HiFi, and ~50X Oxford Nanopore Technologies). Submissions were evaluated following best practices for benchmarking small variants with the new GIAB benchmark sets and genome stratifications. Challenge submissions included a number of innovative methods for all three technologies, with graph-based and machine-learning methods scoring best for short-read and long-read datasets, respectively. New methods out-performed the 2016 Truth Challenge winners, and new 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.

bioinformatics↗

bioRxiv2018

Reproducible integration of multiple sequencing datasets to form high-confidence SNP, indel, and reference calls for five human genome reference materials

Benchmark small variant calls from the Genome in a Bottle Consortium (GIAB) for the CEPH/HapMap genome NA12878 (HG001) have been used extensively for developing, optimizing, and demonstrating performance of sequencing and bioinformatics methods. Here, we develop a reproducible, cloud-based pipeline to integrate multiple sequencing datasets and form benchmark calls, enabling application to arbitrary human genomes. We use these reproducible methods to form high-confidence calls with respect to GRCh37 and GRCh38 for HG001 and 4 additional broadly-consented genomes from the Personal Genome Project that are available as NIST Reference Materials. These new genomes broad, open consent with few restrictions on availability of samples and data is enabling a uniquely diverse array of applications. Our new methods produce 17% more high-confidence SNPs, 176% more indels, and 12% larger regions than our previously published calls. To demonstrate that these calls can be used for accurate benchmarking, we compare other high-quality callsets to ours (e.g., Illumina Platinum Genomes), and we demonstrate that the majority of discordant calls are errors in the other callsets, We also highlight challenges in interpreting performance metrics when benchmarking against imperfect high-confidence calls. We show that benchmarking tools from the Global Alliance for Genomics and Health can be used with our calls to stratify performance metrics by variant type and genome context and elucidate strengths and weaknesses of a method.

genomics↗