Emergence and rapid transmission of SARS-CoV-2 B.1.1.7 in the United States.

The highly transmissible B.1.1.7 variant of SARS-CoV-2, first identified in the United Kingdom, has gained a foothold across the world. Using S gene target failure (SGTF) and SARS-CoV-2 genomic sequencing, we investigated the prevalence and dynamics of this variant in the United States (US), tracking it back to its early emergence. We found that, while the fraction of B.1.1.7 varied by state, the variant increased at a logistic rate with a roughly weekly doubling rate and an increased transmission of 40%-50%. We revealed several independent introductions of B.1.1.7 into the US as early as late November 2020, with community transmission spreading it to most states within months. We show that the US is on a similar trajectory as other countries where B.1.1.7 became dominant, requiring immediate and decisive action to minimize COVID-19 morbidity and mortality.

SARS-CoV-2 variant Delta rapidly displaced variant Alpha in the United States and led to higher viral loads.

We report on the sequencing of 74,348 SARS-CoV-2 positive samples collected across the United States and show that the Delta variant, first detected in the United States in March 2021, made up the majority of SARS-CoV-2 infections by July 1, 2021 and accounted for >99.9% of the infections by September 2021. Not only did Delta displace variant Alpha, which was the dominant variant at the time, it also displaced the Gamma, Iota, and Mu variants. Through an analysis of quantification cycle (Cq) values, we demonstrate that Delta infections tend to have a 1.7× higher viral load compared to Alpha infections (a decrease of 0.8 Cq) on average. Our results are consistent with the hypothesis that the increased transmissibility of the Delta variant could be due to the ability of the Delta variant to establish a higher viral load earlier in the infection as compared to the Alpha variant.

Evidence for SARS-CoV-2 Delta and Omicron co-infections and recombination.

BACKGROUND: Between November 2021 and February 2022, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta and Omicron variants co-circulated in the United States, allowing for co-infections and possible recombination events. METHODS: We sequenced 29,719 positive samples during this period and analyzed the presence and fraction of reads supporting mutations specific to either the Delta or Omicron variant. FINDINGS: We identified 18 co-infections, one of which displayed evidence of a low Delta-Omicron recombinant viral population. We also identified two independent cases of infection by a Delta-Omicron recombinant virus, where 100% of the viral RNA came from one clonal recombinant. In the three cases, the 5' end of the viral genome was from the Delta genome and the 3' end from Omicron, including the majority of the spike protein gene, though the breakpoints were different. CONCLUSIONS: Delta-Omicron recombinant viruses were rare, and there is currently no evidence that Delta-Omicron recombinant viruses are more transmissible between hosts compared with the circulating Omicron lineages. FUNDING: This research was supported by the NIH RADx initiative and by the Centers for Disease Control Contract 75D30121C12730 (Helix).

Genomic epidemiology identifies emergence and rapid transmission of SARS-CoV-2 B.1.1.7 in the United States.

As of January of 2021, the highly transmissible B.1.1.7 variant of SARS-CoV-2, which was first identified in the United Kingdom (U.K.), has gained a strong foothold across the world. Because of the sudden and rapid rise of B.1.1.7, we investigated the prevalence and growth dynamics of this variant in the United States (U.S.), tracking it back to its early emergence and onward local transmission. We found that the RT-qPCR testing anomaly of S gene target failure (SGTF), first observed in the U.K., was a reliable proxy for B.1.1.7 detection. We sequenced 212 B.1.1.7 SARS-CoV-2 genomes collected from testing facilities in the U.S. from December 2020 to January 2021. We found that while the fraction of B.1.1.7 among SGTF samples varied by state, detection of the variant increased at a logistic rate similar to those observed elsewhere, with a doubling rate of a little over a week and an increased transmission rate of 35-45%. By performing time-aware Bayesian phylodynamic analyses, we revealed several independent introductions of B.1.1.7 into the U.S. as early as late November 2020, with onward community transmission enabling the variant to spread to at least 30 states as of January 2021. Our study shows that the U.S. is on a similar trajectory as other countries where B.1.1.7 rapidly became the dominant SARS-CoV-2 variant, requiring immediate and decisive action to minimize COVID-19 morbidity and mortality.

Genome-wide, high-resolution detection of copy number, loss of heterozygosity, and genotypes from formalin-fixed, paraffin-embedded tumor tissue using microarrays.

Formalin-fixed, paraffin-embedded (FFPE) material tends to yield degraded DNA and is thus suboptimal for use in many downstream applications. We describe an integrated analysis of genotype, loss of heterozygosity (LOH), and copy number for DNA derived from FFPE tissues using oligonucleotide microarrays containing over 500K single nucleotide polymorphisms. A prequalifying PCR test predicted the performance of FFPE DNA on the microarrays better than age of FFPE sample. Although genotyping efficiency and reliability were reduced for FFPE DNA when compared with fresh samples, closer examination revealed methods to improve performance at the expense of variable reduction in resolution. Important steps were also identified that enable equivalent copy number and LOH profiles from paired FFPE and fresh frozen tumor samples. In conclusion, we have shown that the Mapping 500K arrays can be used with FFPE-derived samples to produce genotype, copy number, and LOH predictions, and we provide guidelines and suggestions for application of these samples to this integrated system.

High-resolution single nucleotide polymorphism array analysis of epithelial ovarian cancer reveals numerous microdeletions and amplifications.

PURPOSE: Genetic changes in sporadic ovarian cancer are relatively poorly characterized compared with other tumor types. We have evaluated the use of high-resolution whole genome arrays for the genetic profiling of epithelial ovarian cancer. EXPERIMENTAL DESIGN: We have evaluated 31 primary ovarian cancers and matched normal DNA for loss of heterozygosity and copy number alterations using 500 K single nucleotide polymorphism arrays. RESULTS: In addition to identifying the expected large-scale genomic copy number changes, >380 small regions of copy number gain or loss (<500 kb) were identified among the 31 tumors, including 33 regions of high-level gain (>5 copies) and 27 homozygous deletions. The existence of such a high frequency of small regions exhibiting copy number alterations had not been previously suspected because earlier genomic array platforms lacked comparable resolution. Interestingly, many of these regions harbor known cancer genes. For example, one tumor harbored a 350-kb high-level amplification centered on FGFR1 and three tumors showed regions of homozygous loss 109 to 216 kb in size involving the RB1 tumor suppressor gene only. CONCLUSIONS: These data suggest that novel cancer genes may be located within the other identified small regions of copy number alteration. Analysis of the number of copy number breakpoints and the distribution of the small regions of copy number change indicate high levels of structural chromosomal genetic instability in ovarian cancer.

A forward-backward fragment assembling algorithm for the identification of genomic amplification and deletion breakpoints using high-density single nucleotide polymorphism (SNP) array.

BACKGROUND: DNA copy number aberration (CNA) is one of the key characteristics of cancer cells. Recent studies demonstrated the feasibility of utilizing high density single nucleotide polymorphism (SNP) genotyping arrays to detect CNA. Compared with the two-color array-based comparative genomic hybridization (array-CGH), the SNP arrays offer much higher probe density and lower signal-to-noise ratio at the single SNP level. To accurately identify small segments of CNA from SNP array data, segmentation methods that are sensitive to CNA while resistant to noise are required. RESULTS: We have developed a highly sensitive algorithm for the edge detection of copy number data which is especially suitable for the SNP array-based copy number data. The method consists of an over-sensitive edge-detection step and a test-based forward-backward edge selection step. CONCLUSION: Using simulations constructed from real experimental data, the method shows high sensitivity and specificity in detecting small copy number changes in focused regions. The method is implemented in an R package FASeg, which includes data processing and visualization utilities, as well as libraries for processing Affymetrix SNP array data.

Sample processing considerations for detecting copy number changes in formalin-fixed, paraffin-embedded tissues.

The Whole Genome Sampling Analysis (WGSA) assay in combination with Affymetrix GeneChip Mapping Arrays is used for copy number analysis of high-quality DNA samples (i.e., samples that have been collected from blood, fresh or frozen tissue, or cell lines). Formalin-fixed, paraffin-embedded (FFPE) samples, however, represent the most prevalent form of archived clinical samples, but they provide additional challenges for molecular assays. FFPE processing usually results in the degradation of FFPE DNA and in the contamination and chemical modification of these DNA samples. Because of these issues, FFPE DNA is not suitable for all molecular assays designed for high-quality DNA samples. Strategies recommended for processing FFPE DNA samples through WGSA and to the Mapping arrays are described here.

Data analysis considerations for detecting copy number changes in formalin-fixed, paraffin-embedded tissues.

The Whole Genome Sampling Analysis (WGSA) assay in combination with Affymetrix GeneChip Mapping Arrays is used for copy number analysis of high-quality DNA samples (i.e., samples that have been collected from blood, fresh or frozen tissue, or cell lines). Formalin-fixed, paraffin-embedded (FFPE) samples, however, represent the most prevalent form of archived clinical samples, but they provide additional challenges for molecular assays. FFPE processing usually results in the degradation of FFPE DNA and in the contamination and chemical modification of these DNA samples. In this article, we describe the steps needed to obtain reliable copy number predictions from degraded and contaminated FFPE samples.

Retinoic acid is required early during adult neurogenesis in the dentate gyrus.

Retinoic acid (RA) is commonly used in vitro to differentiate stem cell populations including adult neural stem cells into neurons; however, the in vivo function of RA during adult neurogenesis remains largely unexplored. We found that depletion of RA in adult mice leads to significantly decreased neuronal differentiation within the granular cell layer of the dentate gyrus. RA contribution to neurogenesis occurs early, for RA deficiency also results in a decrease in newborn cells expressing an immature neuronal marker. Furthermore, although proliferation is unaffected during RA absence, cell survival is significantly reduced. Finally, a screen for retinoid-induced genes identifies metabolic targets including the lipid transporters, CD-36 and ABCA-1, the lipogenic master regulator SREBP1c as well as components of the Wnt signaling pathway. Our results reveal RA as a crucial contributor to early stages of adult neurogenesis and survival in vivo.