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APR 20, 2021 7:30 AM PDT
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Keynote Presentation: A structural variation map of 499 Han Chinese individuals using long-read sequencing data

C.E. Credits: CEU P.A.C.E. CE Florida CE
Speaker
  • Human Genome Sequencing Centre, Baylor College of Medicine
    Biography

      Dr. Fritz Sedlazeck completed his PhD in 2012 in the group of Dr. Arndt von Haeseler at the Max F. Perutz Laboratory in Vienna. After a two year postdoc, he transitioned to the lab of Dr. Michael Schatz at Cold Spring Harbor Laboratory and later to Johns Hopkins University. Since 2017 he leads his own group at the Human Genome Sequencing Centre at Baylor College of Medicine. His research focuses on developing computational methods to detect and analyze genomic variations with a focus on Structural Variations. Structural Variations are genomic events that manipulate multiple positions in a genome, which impact evolution, genomic disorders, regulation as well as play an important role in explaining multiple phenotypes. Dr. Sedlazeck groups focuses on the mechanisms of the formation of SV across multiple species and to improve our understanding how these complex alleles evolve and impact phenotypes. Over the past years, Dr. Sedlazeck lead multiple efforts from large scale short reads (e.g. Topmed, CCDG) to long reads to study SV (CARD, All of US) occurrence and mechanism of SV. In addition, he is a key member of multiple consortia leading research into the impact of SV.


    Abstract

    Structural variants (SVs) are essential in human evolution and genetic disease but remain understudied. This is especially the case for non-Caucasian ethnicities. We report, for the first time, a comprehensive study of SVs across the genomes of 499 Han Chinese, the largest ethnicity group, using ~15x Oxford Nanopore technology. We identify a total of 81,752 SVs, of which 46.86% are novel when compared to the SV calls in the dbVar and many can be successfully genotyped in short read data. Using these we were able to identify and compare Han Chinese specific SV hotspots across the genome and identified novel sequences that can be place in the human genome.  We found that SV hotspots not only affected the well-known amylase locus, but also seven carbohydrate metabolic processes in the Han Chinese genomes. Further, we uncovered 355 unreported natural knockout genes in the Han Chinese genomes. These data provide the first sequence map of structural variation map of Han Chinese and are a valuable resource for both the population genetics and medical communities.

    Learning Objectives:

    1. Attendees will learn about variability and complexity of SV across the Han Chinese population and its implication on phenotypes

    2. Attendees will learn about what we are missing on GRCH38/37 and why ethnicity specific reference/ pan genomes are necessary

    3. We will review approaches and sequencing technologies to scale up the study of hundreds to thousands of long read genomes


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