Extended Data Fig. 2 | Addition of two perfectly correlated errors significantly reduces UShER accuracy. As in Fig. 2, the Robinson-Foulds distances, proportion of sister nodes identical to the reference tree, distance from true placement and equally parsimonious placements, respecitvely, are shown for UShER experiments in placing 10 lineages, with two perfectly correlated errors added to 1, 2 … 10 of the lineages to be placed. To the far right in the left-most panel, labeled 'Null', the distribution of scores across 100 replicates in which 10 lineages were added randomly to the phylogeny is shown as a null model for comparison. N = 100 independent replicates for each experiment. The whiskers in the boxplot on the left are centered on the median of the data and extend to the first and third quartiles. In the error bars panel (second from the left), the data points are centered on the mean of the data and extend to the bounds of the 95% confidence interval, calculated by 1,000 iterations of bootstrapping. NATURE GENETICS | www.nature.com/naturegeneticsArticles NATURE GENETICS Extended Data Fig. 3 | UShER can output multiple trees to accommodate phylogenetic uncertainty. (A): Composite of 239 trees with 424 samples, representing all possible parsimony-optimal placements of two samples on a starting tree having 422 samples, computed using DensiTree 52 and plotted using the phangorn package (https://cran.r-project.org/web/packages/phangorn). All trees were scaled to be the same height. (B): Two of the trees from (A) compared in a tanglegram, colored according to COG-UK lineage assignments, with linker lines shown only for the two placed samples whose placements differ between topologies. As in Fig. 4, both trees in this tanglegram are ultrametric and branch lengths are arbitrary.Extended Data Fig. 6 | A demonstration of our distance metric for placements. To evaluate the accuracy of each placement in a new phylogeny, we compute the distance for each newly placed sample in the UShER tree (Tree 1) with the reference tree (Tree 2). The clade sets in the two trees are shown for each N1 and N2 value, representing the number of generations from the Sample D in Tree 1 and Tree 2, respectively. We compute the values of N1+N2-2 such that the descendant clades for both trees are identical. In case of newly placed Sample D, clades are identical when N1=2 and N2=2 and when N1=3 and N2=3, which are highlighted in bold. Hence the distance (smallest N1+N2-2) from the true placement is equal to 2.

The SARS-CoV-2 pandemic has led to unprecedented, nearly real-time genetic tracing due to the rapid community sequencing response. Researchers immediately leveraged these data to infer the evolutionary relationships among viral samples and to study key biological questions, including whether host viral genome editing and recombination are features of SARS-CoV-2 evolution. This global sequencing effort is inherently decentralized and must rely on data collected by many labs using a wide variety of molecular and bioinformatic techniques. There is thus a strong possibility that systematic errors associated with lab—or protocol—specific practices affect some sequences in the repositories. We find that some recurrent mutations in reported SARS-CoV-2 genome sequences have been observed predominantly or exclusively by single labs, co-localize with commonly used primer binding sites and are more likely to affect the protein-coding sequences than other similarly recurrent mutations. We show that their inclusion can affect phylogenetic inference on scales relevant to local lineage tracing, and make it appear as though there has been an excess of recurrent mutation or recombination among viral lineages. We suggest how samples can be screened and problematic variants removed, and we plan to regularly inform the scientific community with our updated results as more SARS-CoV-2 genome sequences are shared (https://virological.org/t/issues-with-sars-cov-2-sequencing-data/473 and https://virological.org/t/masking-strategies-for-sars-cov-2-alignments/480). We also develop tools for comparing and visualizing differences among very large phylogenies and we show that consistent clade- and tree-based comparisons can be made between phylogenies produced by different groups. These will facilitate evolutionary inferences and comparisons among phylogenies produced for a wide array of purposes. Building on the SARS-CoV-2 Genome Browser at UCSC, we present a toolkit to compare, analyze and combine SARS-CoV-2 phylogenies, find and remove potential sequencing errors and establish a widely shared, stable clade structure for a more accurate scientific inference and discourse.

The SARS-CoV-2 pandemic has led to unprecedented, nearly real-time genetic tracing due to the rapid community sequencing response. Researchers immediately leveraged these data to infer the evolutionary relationships among viral samples and to study key biological questions, including whether host viral genome editing and recombination are features of SARS-CoV-2 evolution. This global sequencing effort is inherently decentralized and must rely on data collected by many labs using a wide variety of molecular and bioinformatic techniques. There is thus a strong possibility that systematic errors associated with lab-specific practices affect some sequences in the repositories. We find that some recurrent mutations in reported SARS-CoV-2 genome sequences have been observed predominantly or exclusively by single labs, co-localize with commonly used primer binding sites and are more likely to affect the protein coding sequences than other similarly recurrent mutations. We show that their inclusion can affect phylogenetic inference on scales relevant to local lineage tracing, and make it appear as though there has been an excess of recurrent mutation and/or recombination among viral lineages. We suggest how samples can be screened and problematic mutations removed. We also develop tools for comparing and visualizing differences among phylogenies and we show that consistent clade-and tree-based comparisons can be made between phylogenies produced by different groups. These will facilitate evolutionary inferences and comparisons among phylogenies produced for a wide array of purposes. Building on the SARS-CoV-2 Genome Browser at UCSC, we present a toolkit to compare, analyze and combine SARS-CoV-2 phylogenies, find and remove potential sequencing errors and establish a widely shared, stable clade structure for a more accurate scientific inference and discourse.Foreword:

As the SARS-CoV-2 virus spreads through human populations, the unprecedented accumulation of viral genome sequences is ushering a new era of “genomic contact tracing” – that is, using viral genome sequences to trace local transmission dynamics. However, because the viral phylogeny is already so large – and will undoubtedly grow many fold – placing new sequences onto the tree has emerged as a barrier to real-time genomic contact tracing. Here, we resolve this challenge by building an efficient, tree-based data structure encoding the inferred evolutionary history of the virus. We demonstrate that our approach improves the speed of phylogenetic placement of new samples and data visualization by orders of magnitude, making it possible to complete the placements under real-time constraints. Our method also provides the key ingredient for maintaining a fully-updated reference phylogeny. We make these tools available to the research community through the UCSC SARS-CoV-2 Genome Browser to enable rapid cross-referencing of information in new virus sequences with an ever-expanding array of molecular and structural biology data. The methods described here will empower research and genomic contact tracing for laboratories worldwide.Software AvailabilityUSHER is available to users through the UCSC Genome Browser at https://genome.ucsc.edu/cgi-bin/hgPhyloPlace. The source code and detailed instructions on how to compile and run UShER are available from https://github.com/yatisht/usher.

There is massive variation in intron numbers across eukaryotic genomes, yet the major drivers of intron content during evolution remain elusive. Rapid intron loss and gain in some lineages contrast with long-term evolutionary stasis in others. Episodic intron gain could be explained by recently discovered specialized transposons called Introners, but so far Introners are only known from a handful of species. Here, we performed a systematic search across 3,325 eukaryotic genomes and identified 27,563 Introner-derived introns in 175 genomes (5.2%). Species with Introners span remarkable phylogenetic diversity, from animals to basal protists, representing lineages whose last common ancestor dates to over 1.7 billion years ago. Aquatic organisms were 6.5 times more likely to contain Introners than terrestrial organisms. Introners exhibit mechanistic diversity but most are consistent with DNA transposition, indicating that Introners have evolved convergently hundreds of times from nonautonomous transposable elements. Transposable elements and aquatic taxa are associated with high rates of horizontal gene transfer, suggesting that this combination of factors may explain the punctuated and biased diversity of species containing Introners. More generally, our data suggest that Introners may explain the episodic nature of intron gain across the eukaryotic tree of life. These results illuminate the major source of ongoing intron creation in eukaryotic genomes.

The mammalian sex chromosome system (XX female/XY male) is ancient and highly conserved. The sex chromosome karyotype of the creeping vole (Microtus oregoni) represents a long-standing anomaly, with an X chromosome that is unpaired in females (X0) and exclusively maternally transmitted. We produced a highly contiguous male genome assembly, together with short-read genomes and transcriptomes for both sexes. We show that M. oregoni has lost an independently segregating Y chromosome and that the male-specific sex chromosome is a second X chromosome that is largely homologous to the maternally transmitted X. Both maternally inherited and male-specific sex chromosomes carry fragments of the ancestral Y chromosome. Consequences of this recently transformed sex chromosome system include Y-like degeneration and gene amplification on the male-specific X, expression of ancestral Y-linked genes in females, and X inactivation of the male-specific chromosome in male somatic cells. The genome of M. oregoni elucidates the processes that shape the gene content and dosage of mammalian sex chromosomes and exemplifies a rare case of plasticity in an ancient sex chromosome system.

Objective The SARS-CoV-2 pandemic has prompted one of the most extensive and expeditious genomic sequencing efforts in history. Each viral genome is accompanied by a set of metadata which supplies important information such as the geographic origin of the sample, age of the host, and the lab at which the sample was sequenced, and is integral to epidemiological efforts and public health direction. Here, we interrogate some shortcomings of metadata within the GISAID database to raise awareness of common errors and inconsistencies that may affect data-driven analyses and provide possible avenues for resolutions. Results Our analysis reveals a startling prevalence of spelling errors and inconsistent naming conventions, which together occur in an estimated ~ 9.8% and ~ 11.6% of “originating lab” and “submitting lab” GISAID metadata entries respectively. We also find numerous ambiguous entries which provide very little information about the actual source of a sample and could easily associate with multiple sources worldwide. Importantly, all of these issues can impair the ability and accuracy of association studies by deceptively causing a group of samples to identify with multiple sources when they truly all identify with one source, or vice versa.

Spliceosomal introns, which interrupt nuclear genes and are removed from RNA transcripts by machinery termed spliceosomes, are ubiquitous features of eukaryotic nuclear genes [1]. Patterns of spliceosomal intron evolution are complex, with some lineages exhibiting virtually no intron creation while others experience thousands of intron gains [2-5]. One possibility is that this punctate phylogenetic distribution is explained by intron creation by Introner-Like Elements (ILEs), transposable elements capable of creating introns, with only those lineages harboring ILEs undergoing massive intron gain [6-10]. However, ILEs have been reported in only four lineages. Here we study intron evolution in dinoflagellates. The remarkable fragmentation of nuclear genes by spliceosomal introns reaches its apex in dinoflagellates, which have some twenty introns per gene [11,12]. Despite this, almost nothing is known about the molecular and evolutionary mechanisms governing dinoflagellate intron evolution. We reconstructed intron evolution in five dinoflagellate genomes, revealing a dynamic history of intron loss and gain. ILEs are found in 4/5 studied species. In one species, Polarella glacialis, we find an unprecedented diversity of ILEs, with ILE insertion leading to creation of some 12,253 introns, and with 15 separate families of ILEs accounting for at least 100 introns each. These ILE families range in mobilization mechanism, mechanism of intron creation, and flexibility of mechanism of intron creation. Comparison within and between ILE families provides evidence that biases in so-called intron phase, the distribution of introns relative to codon periodicity, are driven by ILE insertion site requirements [9,13,14]. Finally, we find evidence for multiple additional transformations of the spliceosomal system in dinoflagellates, including widespread loss of ancestral introns, and alterations in required, tolerated and favored splice motifs. These results reveal unappreciated intron creating elements diversity and spliceosomal evolutionary capacity, and suggest complex evolutionary dependencies shaping genome structures.