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1.
Genome Biol ; 23(1): 255, 2022 12 13.
Article in English | MEDLINE | ID: mdl-36514120

ABSTRACT

BACKGROUND: The cancer genome is commonly altered with thousands of structural rearrangements including insertions, deletions, translocation, inversions, duplications, and copy number variations. Thus, structural variant (SV) characterization plays a paramount role in cancer target identification, oncology diagnostics, and personalized medicine. As part of the SEQC2 Consortium effort, the present study established and evaluated a consensus SV call set using a breast cancer reference cell line and matched normal control derived from the same donor, which were used in our companion benchmarking studies as reference samples. RESULTS: We systematically investigated somatic SVs in the reference cancer cell line by comparing to a matched normal cell line using multiple NGS platforms including Illumina short-read, 10X Genomics linked reads, PacBio long reads, Oxford Nanopore long reads, and high-throughput chromosome conformation capture (Hi-C). We established a consensus SV call set of a total of 1788 SVs including 717 deletions, 230 duplications, 551 insertions, 133 inversions, 146 translocations, and 11 breakends for the reference cancer cell line. To independently evaluate and cross-validate the accuracy of our consensus SV call set, we used orthogonal methods including PCR-based validation, Affymetrix arrays, Bionano optical mapping, and identification of fusion genes detected from RNA-seq. We evaluated the strengths and weaknesses of each NGS technology for SV determination, and our findings provide an actionable guide to improve cancer genome SV detection sensitivity and accuracy. CONCLUSIONS: A high-confidence consensus SV call set was established for the reference cancer cell line. A large subset of the variants identified was validated by multiple orthogonal methods.


Subject(s)
DNA Copy Number Variations , Neoplasms , Humans , Sequence Analysis, DNA/methods , Genomic Structural Variation , Technology , Cell Line , High-Throughput Nucleotide Sequencing , Genome, Human , Neoplasms/genetics
2.
Nature ; 611(7936): 519-531, 2022 Nov.
Article in English | MEDLINE | ID: mdl-36261518

ABSTRACT

The current human reference genome, GRCh38, represents over 20 years of effort to generate a high-quality assembly, which has benefitted society1,2. However, it still has many gaps and errors, and does not represent a biological genome as it is a blend of multiple individuals3,4. Recently, a high-quality telomere-to-telomere reference, CHM13, was generated with the latest long-read technologies, but it was derived from a hydatidiform mole cell line with a nearly homozygous genome5. To address these limitations, the Human Pangenome Reference Consortium formed with the goal of creating 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 assembly approaches yield the most complete and accurate diploid genome assembly with minimal manual curation. Approaches that used highly accurate long reads and parent-child data with graph-based haplotype phasing during assembly outperformed those that did not. Developing a combination of the top-performing methods, we generated our first high-quality diploid reference assembly, containing only approximately four gaps per chromosome on average, with most chromosomes within ±1% of the length of CHM13. Nearly 48% of protein-coding genes have non-synonymous amino acid changes between haplotypes, and centromeric regions showed the highest diversity. Our findings serve as a foundation for assembling near-complete diploid human genomes at scale for a pangenome reference to capture global genetic variation from single nucleotides to structural rearrangements.


Subject(s)
Chromosome Mapping , Diploidy , Genome, Human , Genomics , Humans , Chromosome Mapping/standards , Genome, Human/genetics , Haplotypes/genetics , High-Throughput Nucleotide Sequencing/methods , High-Throughput Nucleotide Sequencing/standards , Sequence Analysis, DNA/methods , Sequence Analysis, DNA/standards , Reference Standards , Genomics/methods , Genomics/standards , Chromosomes, Human/genetics , Genetic Variation/genetics
3.
FEMS Microbiol Lett ; 285(2): 257-62, 2008 Aug.
Article in English | MEDLINE | ID: mdl-18616595

ABSTRACT

Escherichia coli hemolysin, also termed alpha-hemolysin, is a virulence factor for extraintestinal E. coli. Hemolysin operon (hlyCABD) transcription is inhibited by the nucleoid-associated protein, H-NS. This inhibition is stronger at lower growth temperature. This study investigated transcription of the homologous EHEC hemolysin (enterohemolysin) operon (ehxCABD) in EHEC O157:H7 strain EDL933. We examined the influence of H-NS, the sigma factor RpoS, and the small RNA DsrA, which is known to inhibit H-NS function and to stimulate RpoS synthesis. During growth at 30 degrees C, DsrA overexpression increased ehxA transcription in the wild type but not in an hns deletion mutant. During growth at 37 degrees C, DsrA overexpression increased ehxA transcription independent of hns genotype. This indicates that DsrA influences ehxCABD operon transcription by two different routes, one (at lower temperature) at least partially dependent on H-NS, and one (at higher temperature) independent of H-NS. An rpoS deletion mutant expressed nondetectable levels of ehxA mRNA regardless of growth temperature or DsrA overexpression, indicating that the RpoS sigma factor is essential for ehxCABD operon expression.


Subject(s)
Bacterial Proteins/physiology , DNA-Binding Proteins/physiology , Escherichia coli O157/metabolism , Gene Expression Regulation, Bacterial , Hemolysin Proteins/biosynthesis , RNA, Untranslated/physiology , Sigma Factor/physiology , Bacterial Proteins/genetics , DNA-Binding Proteins/genetics , Escherichia coli O157/genetics , Gene Deletion , Operon , RNA, Bacterial/biosynthesis , RNA, Messenger/biosynthesis , RNA, Small Untranslated , Sigma Factor/genetics , Temperature , Transcription, Genetic
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