A 2.91-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method. The 14.8-billion bp DNA sequence was generated over 9 months from 27,271,853 high-quality sequence reads (5.11-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals. Two assembly strategies—a whole-genome assembly and a regional chromosome assembly—were used, each combining sequence data from Celera and the publicly funded genome effort. The public data were shredded into 550-bp segments to create a 2.9-fold coverage of those genome regions that had been sequenced, without including biases inherent in the cloning and assembly procedure used by the publicly funded group. This brought the effective coverage in the assemblies to eightfold, reducing the number and size of gaps in the final assembly over what would be obtained with 5.11-fold coverage. The two assembly strategies yielded very similar results that largely agree with independent mapping data. The assemblies effectively cover the euchromatic regions of the human chromosomes. More than 90% of the genome is in scaffold assemblies of 100,000 bp or more, and 25% of the genome is in scaffolds of 10 million bp or larger. Analysis of the genome sequence revealed 26,588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ∼12,000 computationally derived genes with mouse matches or other weak supporting evidence. Although gene-dense clusters are obvious, almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence. Only 1.1% of the genome is spanned by exons, whereas 24% is in introns, with 75% of the genome being intergenic DNA. Duplications of segmental blocks, ranging in size up to chromosomal lengths, are abundant throughout the genome and reveal a complex evolutionary history. Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function, with tissue-specific developmental regulation, and with the hemostasis and immune systems. DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 2.1 million single-nucleotide polymorphisms (SNPs). A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average, but there was marked heterogeneity in the level of polymorphism across the genome. Less than 1% of all SNPs resulted in variation in proteins, but the task of determining which SNPs have functional consequences remains an open challenge.

In the genomic era, one of the fundamental goals is to characterize the function of proteins on a large scale. We describe a method, PANTHER, for relating protein sequence relationships to function relationships in a robust and accurate way. PANTHER is composed of two main components: the PANTHER library (PANTHER/LIB) and the PANTHER index (PANTHER/X). PANTHER/LIB is a collection of “books,” each representing a protein family as a multiple sequence alignment, a Hidden Markov Model (HMM), and a family tree. Functional divergence within the family is represented by dividing the tree into subtrees based on shared function, and by subtree HMMs. PANTHER/X is an abbreviated ontology for summarizing and navigating molecular functions and biological processes associated with the families and subfamilies. We apply PANTHER to three areas of active research. First, we report the size and sequence diversity of the families and subfamilies, characterizing the relationship between sequence divergence and functional divergence across a wide range of protein families. Second, we use the PANTHER/X ontology to give a high-level representation of gene function across the human and mouse genomes. Third, we use the family HMMs to rank missense single nucleotide polymorphisms (SNPs), on a database-wide scale, according to their likelihood of affecting protein function.

Progression through the eukaryotic cell cycle is known to be both regulated and accompanied by periodic fluctuation in the expression levels of numerous genes. We report here the genome-wide characterization of mRNA transcript levels during the cell cycle of the budding yeast S. cerevisiae. Cell cycle-dependent periodicity was found for 416 of the 6220 monitored transcripts. More than 25% of the 416 genes were found directly adjacent to other genes in the genome that displayed induction in the same cell cycle phase, suggesting a mechanism for local chromosomal organization in global mRNA regulation. More than 60% of the characterized genes that displayed mRNA fluctuation have already been implicated in cell cycle period-specific biological roles. Because more than 20% of human proteins display significant homology to yeast proteins, these results also link a range of human genes to cell cycle period-specific biological functions.

Technologies to measure whole-genome mRNA abundances and methods to organize and display such data are emerging as valuable tools for systems-level exploration of transcriptional regulatory networks. For instance, it has been shown that mRNA data from 118 genes, measured at several time points in the developing hindbrain of mice, can be hierarchically clustered into various patterns (or 'waves') whose members tend to participate in common processes. We have previously shown that hierarchical clustering can group together genes whose cis-regulatory elements are bound by the same proteins in vivo. Hierarchical clustering has also been used to organize genes into hierarchical dendograms on the basis of their expression across multiple growth conditions. The application of Fourier analysis to synchronized yeast mRNA expression data has identified cell-cycle periodic genes, many of which have expected cis-regulatory elements. Here we apply a systematic set of statistical algorithms, based on whole-genome mRNA data, partitional clustering and motif discovery, to identify transcriptional regulatory sub-networks in yeast-without any a priori knowledge of their structure or any assumptions about their dynamics. This approach uncovered new regulons (sets of co-regulated genes) and their putative cis-regulatory elements. We used statistical characterization of known regulons and motifs to derive criteria by which we infer the biological significance of newly discovered regulons and motifs. Our approach holds promise for the rapid elucidation of genetic network architecture in sequenced organisms in which little biology is known.

The vast amount of protein sequence data now available, together with accumulating experimental knowledge of protein function, enables modeling of protein sequence and function evolution. The PANTHER database was designed to model evolutionary sequence–function relationships on a large scale. There are a number of applications for these data, and we have implemented web services that address three of them. The first is a protein classification service. Proteins can be classified, using only their amino acid sequences, to evolutionary groups at both the family and subfamily levels. Specific subfamilies, and often families, are further classified when possible according to their functions, including molecular function and the biological processes and pathways they participate in. The second application, then, is an expression data analysis service, where functional classification information can help find biological patterns in the data obtained from genome-wide experiments. The third application is a coding single-nucleotide polymorphism scoring service. In this case, information about evolutionarily related proteins is used to assess the likelihood of a deleterious effect on protein function arising from a single substitution at a specific amino acid position in the protein. All three web services are available at .

IMPORTANCEVaccination against COVID-19 provides clear public health benefits, but vaccination also carries potential risks. The risks and outcomes of myocarditis after COVID-19 vaccination are unclear.OBJECTIVE To describe reports of myocarditis and the reporting rates after mRNA-based COVID-19 vaccination in the US. DESIGN, SETTING, AND PARTICIPANTS Descriptive study of reports of myocarditis to the Vaccine Adverse Event Reporting System (VAERS) that occurred after mRNA-based COVID-19 vaccine administration between December 2020 and August 2021 in 192 405 448 individuals older than 12 years of age in the US; data were processed by VAERS as of September 30, 2021. EXPOSURES Vaccination with BNT162b2 (Pfizer-BioNTech) or mRNA-1273 (Moderna).MAIN OUTCOMES AND MEASURES Reports of myocarditis to VAERS were adjudicated and summarized for all age groups. Crude reporting rates were calculated across age and sex strata. Expected rates of myocarditis by age and sex were calculated using 2017-2019 claims data. For persons younger than 30 years of age, medical record reviews and clinician interviews were conducted to describe clinical presentation, diagnostic test results, treatment, and early outcomes. RESULTS Among 192 405 448 persons receiving a total of 354 100 845 mRNA-based COVID-19 vaccines during the study period, there were 1991 reports of myocarditis to VAERS and 1626 of these reports met the case definition of myocarditis. Of those with myocarditis, the median age was 21 years (IQR, 16-31 years) and the median time to symptom onset was 2 days (IQR, 1-3 days). Males comprised 82% of the myocarditis cases for whom sex was reported. The crude reporting rates for cases of myocarditis within 7 days after COVID-19 vaccination exceeded the expected rates of myocarditis across multiple age and sex strata. The rates of myocarditis were highest after the second vaccination dose in adolescent males aged 12 to 15 years (70.7 per million doses of the BNT162b2 vaccine), in adolescent males aged 16 to 17 years (105.9 per million doses of the BNT162b2 vaccine), and in young men aged 18 to 24 years (52.4 and 56.3 per million doses of the BNT162b2 vaccine and the mRNA-1273 vaccine, respectively). There were 826 cases of myocarditis among those younger than 30 years of age who had detailed clinical information available; of these cases, 792 of 809 (98%) had elevated troponin levels, 569 of 794 (72%) had abnormal electrocardiogram results, and 223 of 312 (72%) had abnormal cardiac magnetic resonance imaging results. Approximately 96% of persons (784/813) were hospitalized and 87% (577/661) of these had resolution of presenting symptoms by hospital discharge. The most common treatment was nonsteroidal anti-inflammatory drugs (589/676; 87%). CONCLUSIONS AND RELEVANCEBased on passive surveillance reporting in the US, the risk of myocarditis after receiving mRNA-based COVID-19 vaccines was increased across multiple age and sex strata and was highest after the second vaccination dose in adolescent males and young men. This risk should be ...

We report here the transcriptional profiling of the cell cycle on a genome-wide scale in human fibroblasts. We identified approximately 700 genes that display transcriptional fluctuation with a periodicity consistent with that of the cell cycle. Systematic analysis of these genes revealed functional organization within groups of coregulated transcripts. A diverse set of cytoskeletal reorganization genes exhibit cell-cycle-dependent regulation, indicating that biological pathways are redirected for the execution of cell division. Many genes involved in cell motility and remodeling of the extracellular matrix are expressed predominantly in M phase, indicating a mechanism for balancing proliferative and invasive cellular behavior. Transcripts upregulated during S phase displayed extensive overlap with genes induced by DNA damage; cell-cycle-regulated transcripts may therefore constitute coherent programs used in response to external stimuli. Our data also provide clues to biological function for hundreds of previously uncharacterized human genes.

Statins are cholesterol-lowering drugs with pleiotropic activities including inhibition of isoprenylation reactions and reduction of signals driving cell proliferation and survival responses. The objectives of this study were to examine the effects of statins on breast cancer cells, both in vitro and in vivo, and to begin to determine their mechanism of action. We evaluated the effects of statins on breast cancer cell growth, phosphoprotein signaling intermediates, survival/apoptosis regulators, cell cycle regulators, and activated transcription factors. We also examined the in vivo effect of statin administration in a mouse ErbB2 + breast cancer model. Only lipophilic statins had direct anticancer activity in vitro. Breast cancer cells with activated Ras or ErbB2 pathways seemed to be more sensitive than those overexpressing estrogen receptor, and this correlated with endogenous levels of activated nuclear factor KB (NF-KB). Key intermediates regulating cell survival by NF-KB activation, as well as cell proliferation by the mitogen activated protein kinase cascade, were among the earliest phosphoproteins influenced by statin treatment. These early effects were followed by declines in activator protein-1 and NF-KB activation and concordant changes in other mediators of proliferation and apoptosis. In vivo results showed that oral dosing of statins significantly inhibited the growth of a mouse mammary carcinoma. Lipophilic statins can exert direct anticancer activity in vitro by reducing proliferation and survival signals in susceptible breast cancer phenotypes. Tumor growth inhibition in vivo using a clinically relevant statin dose also seems to be associated with reduced tumor cell proliferation and survival. These findings provide supporting rationale for future statin trials in breast cancer patients.