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Background <p>Previous genomic efforts on chromosome 9p deletion and duplication syndromes have utilized low-resolution strategies (i.e., karyotypes, chromosome microarrays). These studies have provided important initial insights into these syndromes. This current study is the first large-scale whole-genome sequencing (WGS) study of 100 individuals from families with chromosome 9p syndromes.</p> Methods <p>Through the newly formed 9P-ARCH (Advanced Research in Chromosomal Health: Genomic, Phenotypic, and Functional Aspects of 9p-Related syndromes) research network, we assembled a cohort of individuals from families with chromosome 9p syndromes. WGS was applied to 100 individuals, and other genomic technologies were applied to a subset of individuals. To prioritize genes on 9p, we utilized two independent approaches: statistical analyses of genomic data and spatial transcriptomic profiling of embryonic mouse tissue. To assess the enrichment of DNVs within genomic regions, we developed a computational tool, DiamondsDenovo (<a href="https://github.com/TNTurnerLab/DiamondsDenovo">https://github.com/TNTurnerLab/DiamondsDenovo</a>).</p> Results <p>Unlike previous low-resolution studies, we analyzed the genomic architecture of chromosome 9p syndromes, highlighting fundamental features and their commonalities and differences across individuals. A machine-learning model was developed to predict 9p deletion syndrome based on gene copy number estimates using WGS data. We identified two late-replicating regions containing most structural variant breakpoints in 9p deletion syndrome, pointing to replication-based issues as a potential cause of structural variant formation in most individuals and structural rearrangements in some individuals. Genes on 9p were prioritized based on statistical assessment of human genomic variation and through spatial transcriptomics, with 24 genes (<i>AK3</i>, <i>BRD10</i>, <i>CD274</i>, <i>CDC37L1</i>, <i>DMRT1</i>, <i>DMRT2</i>, <i>DMRT3</i>, <i>DOCK8</i>, <i>GLIS3</i>, <i>JAK2</i>, <i>KANK1</i>, <i>KDM4C</i>, <i>PLPP6</i>, <i>PTPRD</i>, <i>PUM3</i>, <i>RANBP6</i>, <i>RCL1</i>, <i>RFX3</i>, <i>RIC1</i>, <i>SLC1A1</i>, <i>SMARCA2</i>, <i>UHRF2</i>, <i>VLDLR</i>, and <i>ZNG1A</i>) identified as important for the majority (83%) of individuals with 9p deletion syndrome. Testing of the mitochondrial genome revealed excess copy number in individuals with 9p deletion syndrome.</p> Conclusions <p>This study introduces the 9P-ARCH research network that is actively pursuing genomic, phenotypic, and functional aspects of 9p-related syndromes. We advanced the study of 9p-related syndromes both at the individual level and across the cohort through the largest, most comprehensive genomic analysis of 9p-related syndromes to date.</p>

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Whole-genome sequencing reveals individual and cohort level insights into chromosome 9p syndromes

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月24日

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  • Yingxi Wang,
  • Eleanor I. Sams,
  • Rachel Slaugh,
  • Sandra Crocker,
  • Emily Cordova Hurtado,
  • Sophia Tracy,
  • Ying-Chen Claire Hou,
  • Christopher Markovic,
  • Kostandin Valle,
  • Victoria Tate,
  • Khadija Belhassan,
  • Elizabeth Appelbaum,
  • Titilope Akinwe,
  • Rodrigo T. Starosta,
  • Yang Cao,
  • Amber Neilson,
  • Yu Liu,
  • Nathaniel Jensen,
  • Reza Ghasemi,
  • Tina Lindsay,
  • Juana Manuel,
  • Sophia Couteranis,
  • Milinn Kremitzki,
  • Jack Ustanik,
  • Thomas Antonacci,
  • Jeffrey K. Ng,
  • Andrew Emory,
  • Laura Metz,
  • Tracie DeLuca,
  • Katherine N. Lyons,
  • Toni Sinnwell,
  • Brianne Thomeczek,
  • Kymme Wang,
  • Nick Sisneros,
  • Megha Muraleedharan,
  • Anantha Kethireddy,
  • Marco Corbo,
  • Harsha Gowda,
  • Katherine A. King,
  • Christina A. Gurnett,
  • Susan K. Dutcher,
  • Catherine Gooch,
  • Yang E. Li,
  • Matthew W. Mitchell,
  • Kevin A. Peterson,
  • Amjad Horani,
  • Jill A. Rosenfeld,
  • Weimin Bi,
  • Pawel Stankiewicz,
  • Hsiao-Tuan Chao,
  • Jennifer E. Posey,
  • Christopher M. Grochowski,
  • Zain Dardas,
  • Erik G. Puffenberger,
  • Christopher E. Pearson,
  • Frank Kooy,
  • Dale Annear,
  • A. Micheil Innes,
  • Michael Heinz,
  • Richard Head,
  • Robert Fulton,
  • Stephan Toutain,
  • Lucinda Antonacci-Fulton,
  • Xiaoxia Cui,
  • Robi D. Mitra,
  • F. Sessions Cole,
  • Julie Neidich,
  • Patricia I. Dickson,
  • Jeffrey Milbrandt,
  • Tychele N. Turner

摘要

Background

Previous genomic efforts on chromosome 9p deletion and duplication syndromes have utilized low-resolution strategies (i.e., karyotypes, chromosome microarrays). These studies have provided important initial insights into these syndromes. This current study is the first large-scale whole-genome sequencing (WGS) study of 100 individuals from families with chromosome 9p syndromes.

Methods

Through the newly formed 9P-ARCH (Advanced Research in Chromosomal Health: Genomic, Phenotypic, and Functional Aspects of 9p-Related syndromes) research network, we assembled a cohort of individuals from families with chromosome 9p syndromes. WGS was applied to 100 individuals, and other genomic technologies were applied to a subset of individuals. To prioritize genes on 9p, we utilized two independent approaches: statistical analyses of genomic data and spatial transcriptomic profiling of embryonic mouse tissue. To assess the enrichment of DNVs within genomic regions, we developed a computational tool, DiamondsDenovo (https://github.com/TNTurnerLab/DiamondsDenovo).

Results

Unlike previous low-resolution studies, we analyzed the genomic architecture of chromosome 9p syndromes, highlighting fundamental features and their commonalities and differences across individuals. A machine-learning model was developed to predict 9p deletion syndrome based on gene copy number estimates using WGS data. We identified two late-replicating regions containing most structural variant breakpoints in 9p deletion syndrome, pointing to replication-based issues as a potential cause of structural variant formation in most individuals and structural rearrangements in some individuals. Genes on 9p were prioritized based on statistical assessment of human genomic variation and through spatial transcriptomics, with 24 genes (AK3, BRD10, CD274, CDC37L1, DMRT1, DMRT2, DMRT3, DOCK8, GLIS3, JAK2, KANK1, KDM4C, PLPP6, PTPRD, PUM3, RANBP6, RCL1, RFX3, RIC1, SLC1A1, SMARCA2, UHRF2, VLDLR, and ZNG1A) identified as important for the majority (83%) of individuals with 9p deletion syndrome. Testing of the mitochondrial genome revealed excess copy number in individuals with 9p deletion syndrome.

Conclusions

This study introduces the 9P-ARCH research network that is actively pursuing genomic, phenotypic, and functional aspects of 9p-related syndromes. We advanced the study of 9p-related syndromes both at the individual level and across the cohort through the largest, most comprehensive genomic analysis of 9p-related syndromes to date.