Whole-genome functional characterization of RE1 silencers using a modified massively parallel reporter assay.

Both upregulation and downregulation by cis-regulatory elements help modulate precise gene expression. However, our understanding of repressive elements is far more limited than activating elements. To address this gap, we characterized RE1, a group of transcriptional silencers bound by REST, at genome-wide scale using a modified massively parallel reporter assay (MPRAduo). MPRAduo empirically defined a minimal binding strength of REST (REST motif-intrinsic value [m-value]), above which cofactors colocalize and silence transcription. We identified 1,500 human variants that alter RE1 silencing and found that their effect sizes are predictable when they overlap with REST-binding sites above the m-value. Additionally, we demonstrate that non-canonical REST-binding motifs exhibit silencer function only if they precisely align half sites with specific spacer lengths. Our results show mechanistic insights into RE1, which allow us to predict its activity and effect of variants on RE1, providing a paradigm for performing genome-wide functional characterization of transcription-factor-binding sites.

Comparative transmissibility of SARS-CoV-2 variants Delta and Alpha in New England, USA.

The SARS-CoV-2 Delta variant rose to dominance in mid-2021, likely propelled by an estimated 40%-80% increased transmissibility over Alpha. To investigate if this ostensible difference in transmissibility is uniform across populations, we partner with public health programs from all six states in New England in the United States. We compare logistic growth rates during each variant's respective emergence period, finding that Delta emerged 1.37-2.63 times faster than Alpha (range across states). We compute variant-specific effective reproductive numbers, estimating that Delta is 63%-167% more transmissible than Alpha (range across states). Finally, we estimate that Delta infections generate on average 6.2 (95% CI 3.1-10.9) times more viral RNA copies per milliliter than Alpha infections during their respective emergence. Overall, our evidence suggests that Delta's enhanced transmissibility can be attributed to its innate ability to increase infectiousness, but its epidemiological dynamics may vary depending on underlying population attributes and sequencing data availability.

Synthetic DNA spike-ins (SDSIs) enable sample tracking and detection of inter-sample contamination in SARS-CoV-2 sequencing workflows.

The global spread and continued evolution of SARS-CoV-2 has driven an unprecedented surge in viral genomic surveillance. Amplicon-based sequencing methods provide a sensitive, low-cost and rapid approach but suffer a high potential for contamination, which can undermine laboratory processes and results. This challenge will increase with the expanding global production of sequences across a variety of laboratories for epidemiological and clinical interpretation, as well as for genomic surveillance of emerging diseases in future outbreaks. We present SDSI + AmpSeq, an approach that uses 96 synthetic DNA spike-ins (SDSIs) to track samples and detect inter-sample contamination throughout the sequencing workflow. We apply SDSIs to the ARTIC Consortium's amplicon design, demonstrate their utility and efficiency in a real-time investigation of a suspected hospital cluster of SARS-CoV-2 cases and validate them across 6,676 diagnostic samples at multiple laboratories. We establish that SDSI + AmpSeq provides increased confidence in genomic data by detecting and correcting for relatively common, yet previously unobserved modes of error, including spillover and sample swaps, without impacting genome recovery.