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The divergence of chimpanzee and bonobo provides one of the few examples of recent hominid speciation1,2. Here we describe a fully annotated, high-quality bonobo genome assembly, which was constructed without guidance from reference genomes by applying a multiplatform genomics approach. We generate a bonobo genome assembly in which more than 98% of genes are completely annotated and 99% of the gaps are closed, including the resolution of about half of the segmental duplications and almost all of the full-length mobile elements. We compare the bonobo genome to those of other great apes1,3–5 and identify more than 5,569 fixed structural variants that specifically distinguish the bonobo and chimpanzee lineages. We focus on genes that have been lost, changed in structure or expanded in the last few million years of bonobo evolution. We produce a high-resolution map of incomplete lineage sorting and estimate that around 5.1% of the human genome is genetically closer to chimpanzee or bonobo and that more than 36.5% of the genome shows incomplete lineage sorting if we consider a deeper phylogeny including gorilla and orangutan. We also show that 26% of the segments of incomplete lineage sorting between human and chimpanzee or human and bonobo are non-randomly distributed and that genes within these clustered segments show significant excess of amino acid replacement compared to the rest of the genome., A high-quality bonobo genome assembly provides insights into incomplete lineage sorting in hominids and its relevance to gene evolution and the genetic relationship among living hominids.

Background Nearly half the human genome consists of repeat elements, most of which are retrotransposons, and many of which play important biological roles. However repeat elements pose several unique challenges to current bioinformatic analyses and visualization tools, as short repeat sequences can map to multiple genomic loci resulting in their misclassification and misinterpretation. In fact, sequence data mapping to repeat elements are often discarded from analysis pipelines. Therefore, there is a continued need for standardized tools and techniques to interpret genomic data of repeats. Results We present the UCSC Repeat Browser, which consists of a complete set of human repeat reference sequences derived from annotations made by the commonly used program RepeatMasker. The UCSC Repeat Browser also provides an alignment from the human genome to these references, uses it to map the standard human genome annotation tracks, and presents all of them as a comprehensive interface to facilitate work with repetitive elements. It also provides processed tracks of multiple publicly available datasets of particular interest to the repeat community, including ChIP-seq datasets for KRAB Zinc Finger Proteins (KZNFs) – a family of proteins known to bind and repress certain classes of repeats. We used the UCSC Repeat Browser in combination with these datasets, as well as RepeatMasker annotations in several non-human primates, to trace the independent trajectories of species-specific evolutionary battles between LINE 1 retroelements and their repressors. Furthermore, we document at https://repeatbrowser.ucsc.edu how researchers can map their own human genome annotations to these reference repeat sequences. Conclusions The UCSC Repeat Browser allows easy and intuitive visualization of genomic data on consensus repeat elements, circumventing the problem of multi-mapping, in which sequencing reads of repeat elements map to multiple locations on the human genome. By developing a reference consensus, multiple datasets and annotation tracks can easily be overlaid to reveal complex evolutionary histories of repeats in a single interactive window. Specifically, we use this approach to retrace the history of several primate specific LINE-1 families across apes, and discover several species-specific routes of evolution that correlate with the emergence and binding of KZNFs.

For more than two decades, the UCSC Genome Browser database (https://genome.ucsc.edu) has provided high-quality genomics data visualization and genome annotations to the research community. As the field of genomics grows and more data become available, new modes of display are required to accommodate new technologies. New features released this past year include a Hi-C heatmap display, a phased family trio display for VCF files, and various track visualization improvements. Striving to keep data up-to-date, new updates to gene annotations include GENCODE Genes, NCBI RefSeq Genes, and Ensembl Genes. New data tracks added for human and mouse genomes include the ENCODE registry of candidate cis-regulatory elements, promoters from the Eukaryotic Promoter Database, and NCBI RefSeq Select and Matched Annotation from NCBI and EMBL-EBI (MANE). Within weeks of learning about the outbreak of coronavirus, UCSC released a genome browser, with detailed annotation tracks, for the SARS-CoV-2 RNA reference assembly.

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.

BackgroundResearchers are generating molecular data pertaining to the SARS-CoV-2 RNA genome and its proteins at an unprecedented rate during the COVID-19 pandemic. As a result, there is a critical need for rapid and continuously updated access to the latest molecular data in a format in which all data can be quickly cross-referenced and compared. We adapted our genome browser visualization tool to the viral genome for this purpose. Molecular data, curated from published studies or from database submissions, are mapped to the viral genome and grouped together into “annotation tracks” where they can be visualized along the linear map of the viral genome sequence and programmatically downloaded in standard format for analysis.ResultsThe UCSC Genome Browser for SARS-CoV-2 (https://genome.ucsc.edu/covid19.html) provides continuously updated access to the mutations in the many thousands of SARS-CoV-2 genomes deposited in GISAID and the international nucleotide sequencing databases, displayed alongside phylogenetic trees. These data are augmented with alignments of bat, pangolin, and other animal and human coronavirus genomes, including per-base evolutionary rate analysis. All available annotations are cross-referenced on the virus genome, including those from major databases (PDB, RFAM, IEDB, UniProt) as well as up-to-date individual results from preprints. Annotated data include predicted and validated immune epitopes, promising antibodies, RT-PCR and sequencing primers, CRISPR guides (from research, diagnostics, vaccines, and therapies), and points of interaction between human and viral genes. As a community resource, any user can add manual annotations which are quality checked and shared publicly on the browser the next day.ConclusionsWe invite all investigators to contribute additional data and annotations to this resource to accelerate research and development activities globally. Contact us atgenome-www@soe.ucsc.eduwith data suggestions or requests for support for adding data. Rapid sharing of data will accelerate SARS-CoV-2 research, especially when researchers take time to integrate their data with those from other labs on a widely-used community browser platform with standardized machine-readable data formats, such as the SARS-CoV-2 Genome Browser.

Applying for a faculty position is a critical phase of many postdoctoral careers, but most postdoctoral researchers in STEM fields enter the academic job market with little knowledge of the process and expectations. A lack of data has made it difficult for applicants to assess their qualifications relative to the general applicant pool and for institutions to develop effective hiring policies. We analyzed responses to a survey of faculty job applicants between May 2018 and May 2019. We establish various background scholarly metrics for a typical faculty applicant and present an analysis of the interplay between those metrics and hiring outcomes. Traditional benchmarks of a positive research track record above a certain threshold of qualifications were unable to completely differentiate applicants with and without offers. Our findings suggest that there is no single clear path to a faculty job offer and that metrics such as career transition awards and publications in high impact factor journals were neither necessary nor sufficient for landing a faculty position. The applicants perceived the process as unnecessarily stressful, time-consuming, and largely lacking in feedback, irrespective of a successful outcome. Our findings emphasize the need to improve the transparency of the faculty job application process. In addition, we hope these and future data will help empower trainees to enter the academic job market with clearer expectations and improved confidence.

BackgroundNearly half the human genome consists of repeat elements, most of which are retrotransposons, and many of these sequences play important biological roles. However repeat elements pose several unique challenges to current bioinformatic analyses and visualization tools, as short repeat sequences can map to multiple genomic loci resulting in their misclassification and misinterpretation. In fact, sequence data mapping to repeat elements are often discarded from analysis pipelines. Therefore, there is a continued need for standardized tools and techniques to interpret genomic data of repeats.ResultsWe present the UCSC Repeat Browser, which consists of a complete set of human repeat reference sequences derived from the gold standard repeat database RepeatMasker. The UCSC Repeat Browser contains mapped annotations from the human genome to these references, and presents all of them as a comprehensive interface to facilitate work with repetitive elements. Furthermore, it provides processed tracks of multiple publicly available datasets of biological interest to the repeat community, including ChIP-SEQ datasets for KRAB Zinc Finger Proteins (KZNFs) – a family of proteins known to bind and repress certain classes of repeats. Here we show how the UCSC Repeat Browser in combination with these datasets, as well as RepeatMasker annotations in several non-human primates, can be used to trace the independent trajectories of species-specific evolutionary conflicts.ConclusionsThe UCSC Repeat Browser allows easy and intuitive visualization of genomic data on consensus repeat elements, circumventing the problem of multi-mapping, in which sequencing reads of repeat elements map to multiple locations on the human genome. By developing a reference consensus, multiple datasets and annotation tracks can easily be overlaid to reveal complex evolutionary histories of repeats in a single interactive window. Specifically, we use this approach to retrace the history of several primate specific LINE-1 families across apes, and discover several species-specific routes of evolution that correlate with the emergence and binding of KZNFs.

The HIV-1 protein Rev is an essential viral regulatory protein that facilitates the nuclear export of intron-containing viral mRNAs. Its sequence is organized into short, structured, functionally well-characterized motifs joined by less understood linker regions. We recently carried out a competitive deep mutational scanning study, which determined the relative fitness of every amino acid at every position of Rev in replicating viruses. This study confirmed many known constraints in Rev’s established interaction motifs, but also identified positions of mutational plasticity within these regions as well as in surrounding linker regions. Here, we probe the mutational limits of these linkers by designing and testing the activities of multiple truncation and mass substitution mutations. We find that these regions possess previously unknown structural, functional or regulatory roles, not apparent from systematic point mutational approaches. Specifically, the N- and C-termini of Rev contribute to protein stability; mutations in a turn that connects the two main helices of Rev have different effects in nuclear export assays and viral replication assays; and a linker region which connects the second helix of Rev to its nuclear export sequence has structural requirements for function. Thus, we find that Rev function extends beyond its characterized motifs, and is in fact further tuned by determinants within seemingly plastic portions of its sequence. At the same time, Rev’s ability to tolerate many of these massive truncations and substitutions illustrates the overall mutational and functional robustness inherent in this viral protein.Author Summary (non-technical summary)HIV-1 Rev is an essential viral protein that controls a critical step in the HIV life cycle. It is responsible for transporting viral mRNA messages from the nucleus to the cytoplasm where they can contribute to the formation new virus particles. In order to understand how different regions of the Rev protein sequence are involved in its function, we introduced truncations and mass substitution mutations in the protein sequence and tested their effect on protein function. Through this study, we not only confirmed previous work highlighting known functionally important regions in Rev, but also found that a large portion of Rev, with little known functional roles influence Rev function and stability. We also show that although protein sequence is critical to its function, Rev can tolerate large variations to its sequence without disrupting its function significantly.

We have analyzed host cell genes linked to HIV replication that were identified in nine genome-wide studies, including three independent siRNA screens. Overlaps among the siRNA screens were very modest (