Biological Phenomena, Cell Phenomena, and Immunity Commons^™

Genomic Reporting Practices Across 5 Molecular Disciplines: A Study From The College Of American Pathologists, Larissa V Furtado, Annette S Kim, Ann M Moyer, Joel T Moncur, Rena R Xian, Angshumoy Roy, Avni B Santani, Yassmine Akkari, Karl V Voelkerding, Rhona J Souers, Jaimie Halley, Glenn E Palomaki

Faculty, Staff and Students Publications

Context.—: Genomic reports are primarily organized in a narrative and unstructured format with variations in content and format. Regulatory requirements and professional guidelines for genetic test reporting exist but provide little guidance for effective communication of information.

Objective.—: To assess clinical genomic reporting practices across 5 disciplines within molecular diagnostics, including germline, somatic solid tumors, somatic hematologic malignancies, pharmacogenomics, and prenatal cell-free DNA screening.

Design.—: Reporting practices were assessed by using a structured review of clinical genomic reports from multiple laboratories in 5 molecular disciplines spanning different practice settings. Report content was reviewed by the presence/absence of from 27 to …

Small Variant Benchmark From A Complete Assembly Of X And Y Chromosomes, Justin Wagner, Nathan D Olson, Jennifer Mcdaniel, Lindsay Harris, Brendan J Pinto, David Jáspez, Adrián Muñoz-Barrera, Luis A Rubio-Rodríguez, José M Lorenzo-Salazar, Carlos Flores, Sayed Mohammad Ebrahim Sahraeian, Giuseppe Narzisi, Marta Byrska-Bishop, Uday S Evani, Chunlin Xiao, Juniper A Lake, Peter Fontana, Craig Greenberg, Donald Freed, Mohammed Faizal Eeman Mootor, Paul C Boutros, Lisa Murray, Kishwar Shafin, Andrew Carroll, Fritz J Sedlazeck, Melissa Wilson, Justin M Zook

Faculty, Staff and Students Publications

The sex chromosomes contain complex, important genes impacting medical phenotypes, but differ from the autosomes in their ploidy and large repetitive regions. To enable technology developers along with research and clinical laboratories to evaluate variant detection on male sex chromosomes X and Y, we create a small variant benchmark set with 111,725 variants for the Genome in a Bottle HG002 reference material. We develop an active evaluation approach to demonstrate the benchmark set reliably identifies errors in challenging genomic regions and across short and long read callsets. We show how complete assemblies can expand benchmarks to difficult regions, but highlight …

Development And Evaluation Of A Training Curriculum To Engage Researchers On Accessing And Analyzing The All Of Us Data, Julie R Coleman, Jasmine N Baker, Shamika Ketkar, Ashley M Butler, Laterrica Williams, Latanya Hammonds-Odie, Elizabeth G Atkinson, Debra D Murray, Brendan Lee, Kim C Worley

Faculty, Staff and Students Publications

OBJECTIVE: The All of Us Evenings with Genetics (EwG) Research Program at Baylor College of Medicine (BCM), funded to engage research scholars to work with the All of Us data, developed a training curriculum for the Researcher Workbench, the platform to access and analyze All of Us data. All of Us EwG developed the curriculum so that it could teach scholars regardless of their skills and background in programming languages and cloud computing. All of Us EwG delivered this curriculum at the first annual All of Us EwG Faculty Summit in May 2022. The curriculum was evaluated both during and …

Large-Scale Application Of Clingen-Insight Apc-Specific Acmg/Amp Variant Classification Criteria Leads To Substantial Reduction In Vus, Xiaoyu Yin, Marcy Richardson, Andreas Laner, Xuemei Shi, Elisabet Ognedal, Valeria Vasta, Thomas V O Hansen, Marta Pineda, Deborah Ritter, Johan De Dunnen, Emadeldin Hassanin, Wencong Lyman Lin, Ester Borras, Karl Krahn, Margareta Nordling, Alexandra Martins, Khalid Mahmood, Emily Nadeau, Victoria Beshay, Carli Tops, Maurizio Genuardi, Tina Pesaran, Ian M Frayling, Gabriel Capellá, Andrew Latchford, Sean V Tavtigian, Carlo Maj, Sharon E Plon, Marc S Greenblatt, Finlay A Macrae, Isabel Spier, Stefan Aretz

Faculty, Staff and Students Publications

Pathogenic constitutional APC variants underlie familial adenomatous polyposis, the most common hereditary gastrointestinal polyposis syndrome. To improve variant classification and resolve the interpretative challenges of variants of uncertain significance (VUSs), APC-specific variant classification criteria were developed by the ClinGen-InSiGHT Hereditary Colorectal Cancer/Polyposis Variant Curation Expert Panel (VCEP) based on the criteria of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP). A streamlined algorithm using the APC-specific criteria was developed and applied to assess all APC variants in ClinVar and the International Society for Gastrointestinal Hereditary Tumours (InSiGHT) international reference APC Leiden Open Variation …

The Giab Genomic Stratifications Resource For Human Reference Genomes, Nathan Dwarshuis, Divya Kalra, Jennifer Mcdaniel, Philippe Sanio, Pilar Alvarez Jerez, Bharati Jadhav, Wenyu Eddy Huang, Rajarshi Mondal, Ben Busby, Nathan D Olson, Fritz J Sedlazeck, Justin Wagner, Sina Majidian, Justin M Zook

Faculty, Staff and Students Publications

Despite the growing variety of sequencing and variant-calling tools, no workflow performs equally well across the entire human genome. Understanding context-dependent performance is critical for enabling researchers, clinicians, and developers to make informed tradeoffs when selecting sequencing hardware and software. Here we describe a set of “stratifications,” which are BED files that define distinct contexts throughout the genome. We define these for GRCh37/38 as well as the new T2T-CHM13 reference, adding many new hard-to-sequence regions which are critical for understanding performance as the field progresses. Specifically, we highlight the increase in hard-to-map and GC-rich stratifications in CHM13 relative to the …

When Less Is More: Sketching With Minimizers In Genomics, Malick Ndiaye, Silvia Prieto-Baños, Lucy M Fitzgerald, Ali Yazdizadeh Kharrazi, Sergey Oreshkov, Christophe Dessimoz, Fritz J Sedlazeck, Natasha Glover, Sina Majidian

Faculty, Staff and Students Publications

The exponential increase in sequencing data calls for conceptual and computational advances to extract useful biological insights. One such advance, minimizers, allows for reducing the quantity of data handled while maintaining some of its key properties. We provide a basic introduction to minimizers, cover recent methodological developments, and review the diverse applications of minimizers to analyze genomic data, including de novo genome assembly, metagenomics, read alignment, read correction, and pangenomes. We also touch on alternative data sketching techniques including universal hitting sets, syncmers, or strobemers. Minimizers and their alternatives have rapidly become indispensable tools for handling vast amounts of data.

Stratomod: Predicting Sequencing And Variant Calling Errors With Interpretable Machine Learning, Nathan Dwarshuis, Peter Tonner, Nathan D Olson, Fritz J Sedlazeck, Justin Wagner, Justin M Zook

Faculty, Staff and Students Publications

Despite the variety in sequencing platforms, mappers, and variant callers, no single pipeline is optimal across the entire human genome. Therefore, developers, clinicians, and researchers need to make tradeoffs when designing pipelines for their application. Currently, assessing such tradeoffs relies on intuition about how a certain pipeline will perform in a given genomic context. We present StratoMod, which addresses this problem using an interpretable machine-learning classifier to predict germline variant calling errors in a data-driven manner. We show StratoMod can precisely predict recall using Hifi or Illumina and leverage StratoMod's interpretability to measure contributions from difficult-to-map and homopolymer regions for …

Mates: A Deep Learning-Based Model For Locus-Specific Quantification Of Transposable Elements In Single Cell, Ruohan Wang, Yumin Zheng, Zijian Zhang, Kailu Song, Erxi Wu, Xiaopeng Zhu, Tao P Wu, Jun Ding

Faculty, Staff and Students Publications

Transposable elements (TEs) are crucial for genetic diversity and gene regulation. Current single-cell quantification methods often align multi-mapping reads to either 'best-mapped' or 'random-mapped' locations and categorize them at the subfamily levels, overlooking the biological necessity for accurate, locus-specific TE quantification. Moreover, these existing methods are primarily designed for and focused on transcriptomics data, which restricts their adaptability to single-cell data of other modalities. To address these challenges, here we introduce MATES, a deep-learning approach that accurately allocates multi-mapping reads to specific loci of TEs, utilizing context from adjacent read alignments flanking the TE locus. When applied to diverse single-cell …

Single-Cell Somatic Copy Number Variants In Brain Using Different Amplification Methods And Reference Genomes, Ester Kalef-Ezra, Zeliha Gozde Turan, Diego Perez-Rodriguez, Ida Bomann, Sairam Behera, Caoimhe Morley, Sonja W Scholz, Zane Jaunmuktane, Jonas Demeulemeester, Fritz J Sedlazeck, Christos Proukakis

Faculty, Staff and Students Publications

The presence of somatic mutations, including copy number variants (CNVs), in the brain is well recognized. Comprehensive study requires single-cell whole genome amplification, with several methods available, prior to sequencing. Here we compare PicoPLEX with two recent adaptations of multiple displacement amplification (MDA): primary template-directed amplification (PTA) and droplet MDA, across 93 human brain cortical nuclei. We demonstrate different properties for each, with PTA providing the broadest amplification, PicoPLEX the most even, and distinct chimeric profiles. Furthermore, we perform CNV calling on two brains with multiple system atrophy and one control brain using different reference genomes. We find that 20.6% …

Impact And Characterization Of Serial Structural Variations Across Humans And Great Apes, Wolfram Höps, Tobias Rausch, Michael Jendrusch, Jan O Korbel, Fritz J Sedlazeck

Faculty, Staff and Students Publications

Modern sequencing technology enables the systematic detection of complex structural variation (SV) across genomes. However, extensive DNA rearrangements arising through a series of mutations, a phenomenon we refer to as serial SV (sSV), remain underexplored, posing a challenge for SV discovery. Here, we present NAHRwhals ( https://github.com/WHops/NAHRwhals ), a method to infer repeat-mediated series of SVs in long-read genomic assemblies. Applying NAHRwhals to haplotype-resolved human genomes from 28 individuals reveals 37 sSV loci of various length and complexity. These sSVs explain otherwise cryptic variation in medically relevant regions such as the TPSAB1 gene, 8p23.1, 22q11 and Sotos syndrome regions. Comparisons …

Project Give: Using A Virtual Genetics Service Platform To Reduce Health Inequities And Improve Access To Genomic Care In An Underserved Region Of Texas, Blake Vuocolo, Roberta Sierra, Daniel Brooks, Christopher Holder, Lauren Urbanski, Keila Rodriguez, Jose David Gamez, Surya Narayan Mulukutla, Ana Hernandez, Alberto Allegre, Humberto Hidalgo, Sarah Rodriguez, Sandy Magallan, Jeremy Gibson, Juan Carlos Bernini, Melanie Watson, Robert Nelson, Lizbeth Mellin-Sanchez, Nancy Garcia, Lori Berry, Hongzheng Dai, Claudia Soler-Alfonso, Kent Carter, Brendan Lee, Seema R Lalani

Faculty, Staff and Students Publications

BACKGROUND: The utilization of genomic information to improve health outcomes is progressively becoming more common in clinical practice. Nonetheless, disparities persist in accessing genetic services among ethnic minorities, individuals with low socioeconomic status, and other vulnerable populations. The Rio Grande Valley (RGV) at the Texas-Mexico border is predominantly Hispanic/Latino with a high poverty rate and very limited access to genetic services. Funded by the National Center for Advancing Translational Sciences, Project GIVE (Genetic Inclusion by Virtual Evaluation) was launched in 2022 to reduce the time to diagnosis and increase provider knowledge of genomics in this region, with the goal of …

Characterizing A Complex Ct-Rich Haplotype In Intron 4 Of Snca Using Large-Scale Targeted Amplicon Long-Read Sequencing, Pilar Alvarez Jerez, Kensuke Daida, Francis P Grenn, Laksh Malik, Abigail Miano-Burkhardt, Mary B Makarious, Jinhui Ding, J Raphael Gibbs, Anni Moore, Xylena Reed, Mike A Nalls, Syed Shah, Medhat Mahmoud, Fritz J Sedlazeck, Egor Dolzhenko, Morgan Park, Hirotaka Iwaki, Bradford Casey, Mina Ryten, Cornelis Blauwendraat, Andrew B Singleton, Kimberley J Billingsley

Faculty, Staff and Students Publications

Parkinson's disease (PD) is a common neurodegenerative disorder with a significant risk proportion driven by genetics. While much progress has been made, most of the heritability remains unknown. This is in-part because previous genetic studies have focused on the contribution of single nucleotide variants. More complex forms of variation, such as structural variants and tandem repeats, are already associated with several synucleinopathies. However, because more sophisticated sequencing methods are usually required to detect these regions, little is understood regarding their contribution to PD. One example is a polymorphic CT-rich region in intron 4 of the SNCA gene. This haplotype has …

Webgestalt 2024: Faster Gene Set Analysis And New Support For Metabolomics And Multi-Omics, John M Elizarraras, Yuxing Liao, Zhiao Shi, Qian Zhu, Alexander R Pico, Bing Zhang

Faculty, Staff and Students Publications

Enrichment analysis, crucial for interpreting genomic, transcriptomic, and proteomic data, is expanding into metabolomics. Furthermore, there is a rising demand for integrated enrichment analysis that combines data from different studies and omics platforms, as seen in meta-analysis and multi-omics research. To address these growing needs, we have updated WebGestalt to include enrichment analysis capabilities for both metabolites and multiple input lists of analytes. We have also significantly increased analysis speed, revamped the user interface, and introduced new pathway visualizations to accommodate these updates. Notably, the adoption of a Rust backend reduced gene set enrichment analysis time by 95% from 270.64 …

A Pan-Cancer Patient-Derived Xenograft Histology Image Repository With Genomic And Pathologic Annotations Enables Deep Learning Analysis, Brian S White, Xing Yi Woo, Soner Koc, Todd Sheridan, Steven B Neuhauser, Shidan Wang, Yvonne A Evrard, Li Chen, Ali Foroughi Pour, John D Landua, R Jay Mashl, Sherri R Davies, Bingliang Fang, Maria Gabriela Raso, Kurt W Evans, Matthew H Bailey, Yeqing Chen, Min Xiao, Jill C Rubinstein, Brian J Sanderson, Michael W Lloyd, Sergii Domanskyi, Lacey E Dobrolecki, Maihi Fujita, Junya Fujimoto, Guanghua Xiao, Ryan C Fields, Jacqueline L Mudd, Xiaowei Xu, Melinda G Hollingshead, Shahanawaz Jiwani, Saul Acevedo, Pdxnet Consortium, Brandi N Davis-Dusenbery, Peter N Robinson, Jeffrey A Moscow, James H Doroshow, Nicholas Mitsiades, Salma Kaochar, Chong-Xian Pan, Luis G Carvajal-Carmona, Alana L Welm, Bryan E Welm, Ramaswamy Govindan, Shunqiang Li, Michael A Davies, Jack A Roth, Funda Meric-Bernstam, Yang Xie, Meenhard Herlyn, Li Ding, Michael T Lewis, Carol J Bult, Dennis A Dean, Jeffrey H Chuang

Faculty, Staff and Students Publications

Patient-derived xenografts (PDX) model human intra- and intertumoral heterogeneity in the context of the intact tissue of immunocompromised mice. Histologic imaging via hematoxylin and eosin (H&E) staining is routinely performed on PDX samples, which could be harnessed for computational analysis. Prior studies of large clinical H&E image repositories have shown that deep learning analysis can identify intercellular and morphologic signals correlated with disease phenotype and therapeutic response. In this study, we developed an extensive, pan-cancer repository of >1,000 PDX and paired parental tumor H&E images. These images, curated from the PDX Development and Trial Centers Research Network Consortium, had a …

A Harmonized Public Resource Of Deeply Sequenced Diverse Human Genomes, Zan Koenig, Mary T Yohannes, Lethukuthula L Nkambule, Xuefang Zhao, Julia K Goodrich, Heesu Ally Kim, Michael W Wilson, Grace Tiao, Stephanie P Hao, Nareh Sahakian, Katherine R Chao, Mark A Walker, Yunfei Lyu, Heidi L Rehm, Benjamin M Neale, Michael E Talkowski, Mark J Daly, Harrison Brand, Konrad J Karczewski, Elizabeth G Atkinson, Alicia R Martin

Faculty, Staff and Students Publications

Underrepresented populations are often excluded from genomic studies owing in part to a lack of resources supporting their analyses. The 1000 Genomes Project (1kGP) and Human Genome Diversity Project (HGDP), which have recently been sequenced to high coverage, are valuable genomic resources because of the global diversity they capture and their open data sharing policies. Here, we harmonized a high-quality set of 4094 whole genomes from 80 populations in the HGDP and 1kGP with data from the Genome Aggregation Database (gnomAD) and identified over 153 million high-quality SNVs, indels, and SVs. We performed a detailed ancestry analysis of this cohort, …

Phenome-Wide Identification Of Therapeutic Genetic Targets, Leveraging Knowledge Graphs, Graph Neural Networks, And Uk Biobank Data, Lawrence Middleton, Ioannis Melas, Chirag Vasavda, Arwa Raies, Benedek Rozemberczki, Ryan S Dhindsa, Justin S Dhindsa, Blake Weido, Quanli Wang, Andrew R Harper, Gavin Edwards, Slavé Petrovski, Dimitrios Vitsios

Faculty, Staff and Students Publications

The ongoing expansion of human genomic datasets propels therapeutic target identification; however, extracting gene-disease associations from gene annotations remains challenging. Here, we introduce Mantis-ML 2.0, a framework integrating AstraZeneca's Biological Insights Knowledge Graph and numerous tabular datasets, to assess gene-disease probabilities throughout the phenome. We use graph neural networks, capturing the graph's holistic structure, and train them on hundreds of balanced datasets via a robust semi-supervised learning framework to provide gene-disease probabilities across the human exome. Mantis-ML 2.0 incorporates natural language processing to automate disease-relevant feature selection for thousands of diseases. The enhanced models demonstrate a 6.9% average classification power …

De Novo Genome Assembly For The Coppery Titi Monkey (Plecturocebus Cupreus): An Emerging Nonhuman Primate Model For Behavioral Research, Susanne P Pfeifer, Alexander Baxter, Logan E Savidge, Fritz J Sedlazeck, Karen L Bales

Faculty, Staff and Students Publications

The coppery titi monkey (Plecturocebus cupreus) is an emerging nonhuman primate model system for behavioral and neurobiological research. At the same time, the almost entire absence of genomic resources for the species has hampered insights into the genetic underpinnings of the phenotypic traits of interest. To facilitate future genotype-to-phenotype studies, we here present a high-quality, fully annotated de novo genome assembly for the species with chromosome-length scaffolds spanning the autosomes and chromosome X (scaffold N50 = 130.8 Mb), constructed using data obtained from several orthologous short- and long-read sequencing and scaffolding techniques. With a base-level accuracy of ∼99.99% in chromosome-length …

Analytical Challenges In Omics Research On Asthma And Allergy: A National Institute Of Allergy And Infectious Diseases Workshop, Supinda Bunyavanich, Patrice M Becker, Matthew C Altman, Jessica Lasky-Su, Carole Ober, Karsten Zengler, Evgeny Berdyshev, Richard Bonneau, Talal Chatila, Nilanjan Chatterjee, Kian Fan Chung, Colleen Cutcliffe, Wendy Davidson, Gang Dong, Gang Fang, Patricia Fulkerson, Blanca E Himes, Liming Liang, Rasika A Mathias, Shuji Ogino, Joseph Petrosino, Nathan D Price, Eric Schadt, James Schofield, Max A Seibold, Hanno Steen, Lisa Wheatley, Hongmei Zhang, Alkis Togias, Kohei Hasegawa

Center for Medical Ethics and Health Policy Staff Publications

Studies of asthma and allergy are generating increasing volumes of omics data for analysis and interpretation. The National Institute of Allergy and Infectious Diseases (NIAID) assembled a workshop comprising investigators studying asthma and allergic diseases using omics approaches, omics investigators from outside the field, and NIAID medical and scientific officers to discuss the following areas in asthma and allergy research: genomics, epigenomics, transcriptomics, microbiomics, metabolomics, proteomics, lipidomics, integrative omics, systems biology, and causal inference. Current states of the art, present challenges, novel and emerging strategies, and priorities for progress were presented and discussed for each area. This workshop report summarizes …

Matrin3 Mediates Differentiation Through Stabilizing Chromatin Loop-Domain Interactions And Yy1 Mediated Enhancer-Promoter Interactions, Tianxin Liu, Qian Zhu, Yan Kai, Trevor Bingham, Stacy Wang, Hye Ji Cha, Stuti Mehta, Thorsten M Schlaeger, Guo-Cheng Yuan, Stuart H Orkin

Faculty, Staff and Students Publications

Although emerging evidence indicates that alterations in proteins within nuclear compartments elicit changes in chromosomal architecture and differentiation, the underlying mechanisms are not well understood. Here we investigate the direct role of the abundant nuclear complex protein Matrin3 (Matr3) in chromatin architecture and development in the context of myogenesis. Using an acute targeted protein degradation platform (dTAG-Matr3), we reveal the dynamics of development-related chromatin reorganization. High-throughput chromosome conformation capture (Hi-C) experiments revealed substantial chromatin loop rearrangements soon after Matr3 depletion. Notably, YY1 binding was detected, accompanied by the emergence of novel YY1-mediated enhancer-promoter loops, which occurred concurrently with changes in …

Integrative Genomic Analyses Reveal Putative Cell Type-Specific Targets Of The Drosophila Ets Transcription Factor Pointed, Komal Kumar Bollepogu Raja, Kelvin Yeung, Yoon-Kyung Shim, Graeme Mardon

Faculty, Staff and Students Publications

The Ets domain transcription factors direct diverse biological processes throughout all metazoans and are implicated in development as well as in tumor initiation, progression and metastasis. The Drosophila Ets transcription factor Pointed (Pnt) is the downstream effector of the Epidermal growth factor receptor (Egfr) pathway and is required for cell cycle progression, specification, and differentiation of most cell types in the larval eye disc. Despite its critical role in development, very few targets of Pnt have been reported previously. Here, we employed an integrated approach by combining genome-wide single cell and bulk data to identify putative cell type-specific Pnt targets. …

Inference Of Phylogenetic Trees Directly From Raw Sequencing Reads Using Read2tree, David Dylus, Adrian Altenhoff, Sina Majidian, Fritz J Sedlazeck, Christophe Dessimoz

Faculty, Staff and Students Publications

Current methods for inference of phylogenetic trees require running complex pipelines at substantial computational and labor costs, with additional constraints in sequencing coverage, assembly and annotation quality, especially for large datasets. To overcome these challenges, we present Read2Tree, which directly processes raw sequencing reads into groups of corresponding genes and bypasses traditional steps in phylogeny inference, such as genome assembly, annotation and all-versus-all sequence comparisons, while retaining accuracy. In a benchmark encompassing a broad variety of datasets, Read2Tree is 10-100 times faster than assembly-based approaches and in most cases more accurate-the exception being when sequencing coverage is high and reference …

Rapid Gene Fusion Testing Using The Nanostring Ncounter Platform To Improve Pediatric Leukemia Diagnoses In Sub-Saharan Africa, Julie M Gastier-Foster, Fredrick Lutwama, Olive Mbabazi, Steven Mlenga, Kennedy Ulaya, Ruth Namazzi, E Faith Hollingsworth, Dolores Lopez-Terrada, Kevin E Fisher, Angshumoy Roy, Carl E Allen, David G Poplack, Rizine Mzikamanda, Nmazuo Ozuah, Peter Wasswa

Faculty, Staff and Students Publications

Risk stratification and molecular targeting have been key to increasing cure rates for pediatric cancers in high-income countries. In contrast, precise diagnosis in low-resource settings is hindered by insufficient pathology infrastructure. The Global HOPE program aims to improve outcomes for pediatric cancer in Sub-Saharan Africa (SSA) by building local clinical care and diagnostic capacity. This study aimed to assess the feasibility of implementing molecular assays to improve leukemia diagnoses in SSA. Custom NanoString nCounter gene fusion assays, previously validated in the US, were used to test samples from suspected leukemia patients. The NanoString platform was chosen due to relatively low …

Improved Sequence Mapping Using A Complete Reference Genome And Lift-Over, Nae-Chyun Chen, Luis F Paulin, Fritz J Sedlazeck, Sergey Koren, Adam M Phillippy, Ben Langmead

Faculty, Staff and Students Publications

Complete, telomere-to-telomere genome assemblies promise improved analyses and the discovery of new variants, but many essential genomic resources remain associated with older reference genomes. Thus, there is a need to translate genomic features and read alignments between references. Here we describe a new method called levioSAM2 that accounts for reference changes and performs fast and accurate lift-over between assemblies using a whole-genome map. In addition to enabling the use of multiple references, we demonstrate that aligning reads to a high-quality reference (e.g. T2T-CHM13) and lifting to an older reference (e.g. GRCh38) actually improves the accuracy of the resulting variant calls …

Whole Genome Analysis Of Snv And Indel Polymorphism In Common Marmosets (Callithrix Jacchus), R Alan Harris, Muthuswamy Raveendran, Wes Warren, Hillier W Ladeana, Chad Tomlinson, Tina Graves-Lindsay, Richard E Green, Jenna K Schmidt, Julia C Colwell, Allison T Makulec, Shelley A Cole, Ian H Cheeseman, Corinna N Ross, Saverio Capuano, Evan E Eichler, Jon E Levine, Jeffrey Rogers

Faculty, Staff and Students Publications

The common marmoset (Callithrix jacchus) is one of the most widely used nonhuman primate models of human disease. Owing to limitations in sequencing technology, early genome assemblies of this species using short-read sequencing suffered from gaps. In addition, the genetic diversity of the species has not yet been adequately explored. Using long-read genome sequencing and expert annotation, we generated a high-quality genome resource creating a 2.898 Gb marmoset genome in which most of the euchromatin portion is assembled contiguously (contig N50 = 25.23 Mbp, scaffold N50 = 98.2 Mbp). We then performed whole genome sequencing on 84 marmosets …

Complex Evolutionary History With Extensive Ancestral Gene Flow In An African Primate Radiation, Axel Jensen, Frances Swift, Dorien De Vries, Robin M D Beck, Lukas F K Kuderna, Sascha Knauf, Idrissa S Chuma, Julius D Keyyu, Andrew C Kitchener, Kyle Farh, Jeffrey Rogers, Tomas Marques-Bonet, Kate M Detwiler, Christian Roos, Katerina Guschanski

Faculty, Staff and Students Publications

Understanding the drivers of speciation is fundamental in evolutionary biology, and recent studies highlight hybridization as an important evolutionary force. Using whole-genome sequencing data from 22 species of guenons (tribe Cercopithecini), one of the world's largest primate radiations, we show that rampant gene flow characterizes their evolutionary history and identify ancient hybridization across deeply divergent lineages that differ in ecology, morphology, and karyotypes. Some hybridization events resulted in mitochondrial introgression between distant lineages, likely facilitated by cointrogression of coadapted nuclear variants. Although the genomic landscapes of introgression were largely lineage specific, we found that genes with immune functions were overrepresented …

A Single Cell Genomics Atlas Of The Drosophila Larval Eye Reveals Distinct Photoreceptor Developmental Timelines, Komal Kumar Bollepogu Raja, Kelvin Yeung, Yoon-Kyung Shim, Yumei Li, Rui Chen, Graeme Mardon

Faculty, Staff and Students Publications

The Drosophila eye is a powerful model system to study the dynamics of cell differentiation, cell state transitions, cell maturation, and pattern formation. However, a high-resolution single cell genomics resource that accurately profiles all major cell types of the larval eye disc and their spatiotemporal relationships is lacking. Here, we report transcriptomic and chromatin accessibility data for all known cell types in the developing eye. Photoreceptors appear as strands of cells that represent their dynamic developmental timelines. As photoreceptor subtypes mature, they appear to assume a common transcriptomic profile that is dominated by genes involved in axon function. We identify …

Genomic Variant Benchmark: If You Cannot Measure It, You Cannot Improve It, Sina Majidian, Daniel Paiva Agustinho, Chen-Shan Chin, Fritz J Sedlazeck, Medhat Mahmoud

Faculty, Staff and Students Publications

Genomic benchmark datasets are essential to driving the field of genomics and bioinformatics. They provide a snapshot of the performances of sequencing technologies and analytical methods and highlight future challenges. However, they depend on sequencing technology, reference genome, and available benchmarking methods. Thus, creating a genomic benchmark dataset is laborious and highly challenging, often involving multiple sequencing technologies, different variant calling tools, and laborious manual curation. In this review, we discuss the available benchmark datasets and their utility. Additionally, we focus on the most recent benchmark of genes with medical relevance and challenging genomic complexity.

Views Of Adolescents And Young Adults With Cancer And Their Oncologists Toward Patients' Participation In Genomic Research, Amanda M Gutierrez, Jill O Robinson, Robin Raesz-Martinez, Isabel Canfield, Mary A Majumder, Sarah Scollon, Lauren R Desrosiers, Rebecca L Hsu, Wendy Allen-Rhoades, D Williams Parsons, Sharon E Plon, Amy L Mcguire, Janet Malek

Faculty, Staff and Students Publications

Purpose:

With increased use of genomic testing in cancer research and clinical care, it is important to understand the perspectives and decision-making preferences of adolescents and young adults (AYAs) with cancer and their treating oncologists.

Methods:

We conducted an interview substudy of the BASIC3 Study, which enrolled newly diagnosed cancer patients <18 years of age with assent. Of 32 young adults (YAs) with cancer who reached the age of majority (AOM; 18 years) while on study, 12 were successfully approached and all consented to study continuation at AOM. Of those, seven completed an interview. Patients' oncologists, who enrolled and participated in return of clinical genomic results, were also interviewed (n = 12). Interviews were transcribed, deidentified, and analyzed using thematic analysis.

Results:

YAs cited the possibility of helping others and advancing science as major reasons for their assent to initial study enrollment and their willingness to consent at AOM. YAs thought obtaining informed consent from research participants for …

A Proteogenomics Data-Driven Knowledge Base Of Human Cancer, Yuxing Liao, Sara R Savage, Yongchao Dou, Zhiao Shi, Xinpei Yi, Wen Jiang, Jonathan T Lei, Bing Zhang

Faculty, Staff and Students Publications

By combining mass-spectrometry-based proteomics and phosphoproteomics with genomics, epi-genomics, and transcriptomics, proteogenomics provides comprehensive molecular characterization of cancer. Using this approach, the Clinical Proteomic Tumor Analysis Consortium (CPTAC) has characterized over 1,000 primary tumors spanning 10 cancer types, many with matched normal tissues. Here, we present LinkedOmicsKB, a proteogenomics data-driven knowledge base that makes consistently processed and systematically precomputed CPTAC pan-cancer proteogenomics data available to the public through ∼40,000 gene-, protein-, mutation-, and phenotype-centric web pages. Visualization techniques facilitate efficient exploration and reasoning of complex, interconnected data. Using three case studies, we illustrate the practical utility of LinkedOmicsKB in providing …

A Multicenter Analysis Of Abnormal Chromosomal Microarray Findings In Congenital Heart Disease, Benjamin J Landis, Lindsey R Helvaty, Gabrielle C Geddes, Jiuann-Huey Ivy Lin, Svetlana A Yatsenko, Cecilia W Lo, William L Border, Stephanie Burns Wechsler, Chaya N Murali, Mahshid S Azamian, Seema R Lalani, Robert B Hinton, Vidu Garg, Kim L Mcbride, Jennelle C Hodge, Stephanie M Ware

Faculty, Staff and Students Publications

Background

Chromosomal microarray analysis (CMA) provides an opportunity to understand genetic causes of congenital heart disease (CHD). The methods for describing cardiac phenotypes in patients with CMA abnormalities have been inconsistent, which may complicate clinical interpretation of abnormal testing results and hinder a more complete understanding of genotype–phenotype relationships.

Methods and Results

Patients with CHD and abnormal clinical CMA were accrued from 9 pediatric cardiac centers. Highly detailed cardiac phenotypes were systematically classified and analyzed for their association with CMA abnormality. Hierarchical classification of each patient into 1 CHD category facilitated broad analyses. Inclusive classification allowing multiple CHD types per …