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The genomic landscape of transposable elements (TEs) varies dramatically across species, with some TEs demonstrating greater success in colonizing particular lineages than others. In mammals, long interspersed nuclear element (LINE) retrotransposons are typically more common than any other TE. Here, we report an unusual genomic landscape of TEs in the deer mouse, Peromyscus maniculatus. In contrast to other previously examined mammals, long terminal repeat elements occupy more of the deer mouse genome than LINEs (11% and 10%, respectively). This pattern reflects a combination of relatively low LINE activity and a massive invasion of lineage-specific endogenous retroviruses (ERVs). Deer mouse ERVs exhibit diverse origins spanning the retroviral phylogeny suggesting they have been host to a wide range of exogenous retroviruses. Notably, we trace the origin of one ERV lineage, which arose ∼5–18 million years ago, to a close relative of feline leukemia virus, revealing inter-ordinal horizontal transmission. Several lineage-specific ERV subfamilies have very high copy numbers, with the top five most abundant accounting for ∼2% of the genome. We also observe a massive amplification of Kruppel-associated box domain-containing zinc finger genes, which likely control ERV activity and whose expansion may have been facilitated by ectopic recombination between ERVs. Finally, we find evidence that ERVs directly impacted the evolutionary trajectory of LINEs by outcompeting them for genomic sites and frequently disrupting autonomous LINE copies. Together, our results illuminate the genomic ecology that shaped the unique deer mouse TE landscape, shedding light on the evolutionary processes that give rise to variation in mammalian genome structure.

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 contrasts 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. Marine organisms were 6.5 times more likely to contain Introners than their terrestrial counterparts. Introners exhibit mechanistic diversity but most are consistent with DNA transposition, indicating that Introners have evolved convergently hundreds of times from autonomous transposable elements. Transposable elements and marine 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.

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.

Reproductive proteins, including those expressed in the testes, are among the fastest evolving proteins across the tree of life. Sexual selection on traits involved in sperm competition is thought to be a primary driver of testes gene evolution and is expected to differ between promiscuous and monogamous species due to intense competition between males to fertilize females in promiscuous lineages and lack thereof in monogamous ones. Here, we employ the rodent genus Peromyscus as a model to explore differences in evolutionary rates between testes-expressed genes in monogamous and promiscuous species. We find candidate genes that may be associated with increased sperm production in promiscuous species and gene ontology categories that show patterns of molecular convergence associated with phenotypic convergence in independently evolved monogamous species. Overall, our results highlight the possible molecular consequences of differences in mating system, likely due to differences in selective pressures.

Metadata is integral to data-driven association studies relevant to epidemiology, viral population dynamics and public health response. However, SARS-CoV-2 metadata quality remains inadequate. Here I exemplify this through a brief analysis of two metadata categories in the GISAID SARS-CoV-2 genomic database: “originating lab” and “submitting lab”. My 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 labs” and “submitting labs” respectively. In addition, I find numerous ambiguous lab names, such as “Biology Dpt” and “Hospital” which provide very little information with regard to 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. GISAID’s “originating lab” and “submitting lab” categories are specifically relevant to identifying problematic sites in SARS-CoV-2 genomic data through lab association. Thus, I advocate that both data submitters and maintainers strive for a higher metadata quality standard now and in the future.

Funder: Alfred P. Sloan Foundation; funder-id: http://dx.doi.org/10.13039/100000879, Funder: European Molecular Biology Laboratory (EMBL), 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.

SummarySpliceosomal 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.

Spliceosomal introns, which interrupt nuclear genes, are ubiquitous features of eukaryotic nuclear genes.

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.ForewordWe wish to thank all groups that responded rapidly by producing these invaluable and essential sequence data. Their contributions have enabled an unprecedented, lightning-fast process of scientific discovery---truly an incredible benefit for humanity and for the scientific community. We emphasize that most lab groups with whom we associate specific suspicious alleles are also those who have produced the most sequence data at a time when it was urgently needed. We commend their efforts. We have already contacted each group and many have updated their sequences. Our goal with this work is not to highlight potential errors, but to understand the impacts of these and other kinds of highly recurrent mutations so as to identify commonalities among the suspicious examples that can improve sequence quality and analysis going forward.