Article Methods Cell lines Cell lines were purchased from ATCC and were not formally authenticated, but confirmation of expected gene expression patterns were performed for RNA-seq and eCLIP experiments. Cell lines were routinely tested for mycoplasma contamination (MycoAlert, Lonza).

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 (U.S.), 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 U.S. as early as late November 2020, with community transmission spreading it to most states within months. We show that the U.S. 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.

As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing and/or sequencing capacity, which can also introduce biases1–3. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing4,5. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We developed and deployed improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detected emerging variants of concern up to 14 days earlier in wastewater samples, and identified multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.

Direct RNA sequencing holds great promise for the de novo identification of RNA modifications at single-coordinate resolution; however, interpretation of raw sequencing output to discover modified bases remains a challenge. Using Oxford Nanopore's direct RNA sequencing technology, we developed a random forest classifier trained using experimentally detected N 6-methyladenosine (m 6 A) sites within DRACH motifs. Our software MINES (m 6 A Identification using Nanopore Sequencing) assigned m 6 A methylation status to more than 13,000 previously unannotated DRACH sites in endogenous HEK293T transcripts and identified more than 40,000 sites with isoform-level resolution in a human mammary epithelial cell line. These sites displayed sensitivity to the m 6 A writer, METTL3, and eraser, ALKBH5, respectively. MINES (https:// github.com/YeoLab/MINES.git) enables m 6 A annotation at single coordinate-level resolution from direct RNA nanopore sequencing.

The N6-methyladenosine (m6A) modification is the most prevalent post-transcriptional mRNA modification, regulating mRNA decay and splicing. It plays a major role during normal development, differentiation, and disease progression. The modification is regulated by a set of writer, eraser, and reader proteins. The YTH domain family of proteins consists of three homologous m6A-binding proteins, Ythdf1, Ythdf2, and Ythdf3, which were suggested to have different cellular functions. However, their sequence similarity and their tendency to bind the same targets suggest that they may have overlapping roles. We systematically knocked out (KO) the Mettl3 writer, each of the Ythdf readers, and the three readers together (triple-KO). We then estimated the effect in vivo in mouse gametogenesis, postnatal viability, and in vitro in mouse embryonic stem cells (mESCs). In gametogenesis, Mettl3-KO severity is increased as the deletion occurs earlier in the process, and Ythdf2 has a dominant role that cannot be compensated by Ythdf1 or Ythdf3, due to differences in readers’ expression pattern across different cell types, both in quantity and in spatial location. Knocking out the three readers together and systematically testing viable offspring genotypes revealed a redundancy in the readers’ role during early development that is Ythdf1/2/3 gene dosage-dependent. Finally, in mESCs there is compensation between the three Ythdf reader proteins, since the resistance to differentiate and the significant effect on mRNA decay occur only in the triple-KO cells and not in the single KOs. Thus, we suggest a new model for the Ythdf readers function, in which there is profound dosage-dependent redundancy when all three readers are equivalently coexpressed in the same cell types.