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The period of protection from repeat infection following symptomatic influenza is not well established due to limited availability of longitudinal data. Using data from a pediatric cohort in Managua, Nicaragua, we examine the effects of natural influenza virus infection on subsequent infection with the same influenza virus subtype/lineage across multiple seasons, totaling 2,170 RT-PCR-confirmed symptomatic influenza infections. Logistic regression models assessed whether infection in the prior influenza season protected against homologous reinfection. We sequenced viruses from 2011–2019 identifying dominant clades and measuring antigenic distances between hemagglutinin clades. We observe homotypic protection from repeat infection in children infected with influenza A/H1N1pdm (OR 0.12, CI 0.02–0.88), A/H3N2 (OR 0.41, CI 0.24–0.73), and B/Victoria (OR 0.00, CI 0.00–0.14), but not with B/Yamagata viruses (OR 0.60, CI 0.09–2.10). Overall, protection wanes as time or antigenic distance increases. Individuals infected with one subtype or lineage of influenza virus have significantly lower odds of homologous reinfection for the following one to two years; after two years this protection wanes. This protection is demonstrated across multiple seasons, subtypes, and lineages among children.

Seasonal influenza viruses repeatedly infect humans in part because they rapidly change their antigenic properties and evade host immune responses, necessitating frequent updates of the vaccine composition. Accurate predictions of strains circulating in the future could therefore improve the vaccine match. Here, we studied the predictability of frequency dynamics and fixation of amino acid substitutions. Current frequency was the strongest predictor of eventual fixation, as expected in neutral evolution. Other properties, such as occurrence in previously characterized epitopes or high Local Branching Index (LBI) had little predictive power. Parallel evolution was found to be moderately predictive of fixation. Although the LBI had little power to predict frequency dynamics, it was still successful at picking strains representative of future populations. The latter is due to a tendency of the LBI to be high for consensus-like sequences that are closer to the future than the average sequence. Simulations of models of adapting populations, in contrast, show clear signals of predictability. This indicates that the evolution of influenza HA and NA, while driven by strong selection pressure to change, is poorly described by common models of directional selection such as traveling fitness waves.

Summary and statement of need The analysis of human pathogens requires a diverse collection of bioinformatics tools. These tools include standard genomic and phylogenetic software and custom software developed to handle the relatively numerous and short genomes of viruses and bacteria. Researchers increasingly depend on the outputs of these tools to infer transmission dynamics of human diseases and make actionable recommendations to public health officials (Black et al., 2020; Gardy et al., 2015). In order to enable real-time analyses of pathogen evolution, bioinformatics tools must scale rapidly with the number of samples and be flexible enough to adapt to a variety of questions and organisms. To meet these needs, we developed Augur, a bioinformatics toolkit designed for phylogenetic analyses of human pathogens.

Antibodies targeting the SARS-CoV-2 spike receptor-binding domain (RBD) are being developed as therapeutics and are a major contributor to neutralizing antibody responses elicited by infection. Here, we describe a deep mutational scanning method to map how all amino-acid mutations in the RBD affect antibody binding and apply this method to 10 human monoclonal antibodies. The escape mutations cluster on several surfaces of the RBD that broadly correspond to structurally defined antibody epitopes. However, even antibodies targeting the same surface often have distinct escape mutations. The complete escape maps predict which mutations are selected during viral growth in the presence of single antibodies. They further enable the design of escape-resistant antibody cocktails—including cocktails of antibodies that compete for binding to the same RBD surface but have different escape mutations. Therefore, complete escape-mutation maps enable rational design of antibody therapeutics and assessment of the antigenic consequences of viral evolution., Graphical Abstract, Highlights • Develop system to map all SARS-CoV-2 RBD mutations that escape antibody binding • Escape maps predict which mutations emerge when virus grown in presence of antibody • Escape maps inform surveillance for possible antigenic evolution, Greaney et al. develop a method to map all mutations to the SARS-CoV-2 RBD that escape antibody binding and apply this method to 10 antibodies. The resulting escape maps predict which mutations arise when virus is grown in the presence of antibody and can inform the design of antibody therapeutics.

Despite the appearance of variant SARS-CoV-2 viruses with altered receptorbinding or antigenic phenotypes, traditional methods for detecting adaptive evolution from sequence data do not pick up strong signals of positive selection. Here, we present a new method for identifying adaptive evolution on short evolutionary time scales with densely-sampled populations. We apply this method to SARS-CoV-2 to perform a comprehensive analysis of adaptively-evolving regions of the genome. We find that spike S1 is a focal point of adaptive evolution, but also identify positivelyselected mutations in other genes that are sculpting the evolutionary trajectory of SARS-CoV-2. Protein-coding mutations in S1 are temporally-clustered and, in 2021, the ratio of nonsynonymous to synonymous divergence in S1 is more than 4 times greater than in the equivalent influenza HA1 subunit. Funding: This work was supported by NIH R35 GM119774. KEK was supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE-1762114. Declaration of Interests: None to declare.

Seasonal influenza virus A/H3N2 is a major cause of death globally. Vaccination remains the most effective preventative. Rapid mutation of hemagglutinin allows viruses to escape adaptive immunity. This antigenic drift necessitates regular vaccine updates. Effective vaccine strains need to represent H3N2 populations circulating one year after strain selection. Experts select strains based on experimental measurements of antigenic drift and predictions made by models from hemagglutinin sequences. We developed a novel influenza forecasting framework that integrates phenotypic measures of antigenic drift and functional constraint with previously published sequence-only fitness estimates. Forecasts informed by phenotypic measures of antigenic drift consistently outperformed previous sequence-only estimates, while sequence-only estimates of functional constraint surpassed more comprehensive experimentally-informed estimates. Importantly, the best models integrated estimates of both functional constraint and either antigenic drift phenotypes or recent population growth., eLife digest Vaccination is the best protection against seasonal flu. It teaches the immune system what the flu virus looks like, preparing it to fight off an infection. But the flu virus changes its molecular appearance every year, escaping the immune defences learnt the year before. So, every year, the vaccine needs updating. Since it takes almost a year to design and make a new flu vaccine, researchers need to be able to predict what flu viruses will look like in the future. Currently, this prediction relies on experiments that assess the molecular appearance of flu viruses, a complex and slow approach. One alternative is to examine the virus's genetic code. Mathematical models try to predict which genetic changes might alter the appearance of a flu virus, saving the cost of performing specialised experiments. Recent research has shown that these models can make good predictions, but including experimental measures of the virus’ appearance could improve them even further. This could help the model to work out which genetic changes are likely to be beneficial to the virus, and which are not. To find out whether experimental data improves model predictions, Huddleston et al. designed a new forecasting tool which used 25 years of historical data from past flu seasons. Each forecast predicted what the virus population might look like the next year using the previous year's genetic code, experimental data, or both. Huddleston et al. then compared the predictions with the historical data to find the most useful data types. This showed that the best predictions combined changes from the virus's genetic code with experimental measures of its appearance. This new forecasting tool is open source, allowing teams across the world to start using it to improve their predictions straight away. Seasonal flu infects between 5 and 15% of the world's population every year, causing between quarter of a million and half a million deaths. Better predictions could lead to better flu vaccines and fewer illnesses and deaths.

Background The complex interspersed pattern of segmental duplications in humans is responsible for rearrangements associated with neurodevelopmental disease, including the emergence of novel genes important in human brain evolution. We investigate the evolution of LCR16a, a putative driver of this phenomenon that encodes one of the most rapidly evolving human–ape gene families, nuclear pore interacting protein (NPIP). Results Comparative analysis shows that LCR16a has independently expanded in five primate lineages over the last 35 million years of primate evolution. The expansions are associated with independent lineage-specific segmental duplications flanking LCR16a leading to the emergence of large interspersed duplication blocks at non-orthologous chromosomal locations in each primate lineage. The intron-exon structure of the NPIP gene family has changed dramatically throughout primate evolution with different branches showing characteristic gene models yet maintaining an open reading frame. In the African ape lineage, we detect signatures of positive selection that occurred after a transition to more ubiquitous expression among great ape tissues when compared to Old World and New World monkeys. Mouse transgenic experiments from baboon and human genomic loci confirm these expression differences and suggest that the broader ape expression pattern arose due to mutational changes that emerged in cis. Conclusions LCR16a promotes serial interspersed duplications and creates hotspots of genomic instability that appear to be an ancient property of primate genomes. Dramatic changes to NPIP gene structure and altered tissue expression preceded major bouts of positive selection in the African ape lineage, suggestive of a gene undergoing strong adaptive evolution.

Seasonal influenza viruses repeatedly infect humans in part because they rapidly change their antigenic properties and evade host immune responses, necessitating frequent updates of the vaccine composition. Accurate predictions of strains circulating in the future could therefore improve the vaccine match. Here, we studied the predictability of frequency dynamics and fixation of amino acid substitutions. Current frequency was the strongest predictor of eventual fixation, as expected in neutral evolution. Other properties, such as occurrence in previously characterized epitopes or high Local Branching Index (LBI) had little predictive power. Parallel evolution was found to be moderately predictive of fixation. While the LBI had little power to predict frequency dynamics, it was still successful at picking strains representative of future populations. The latter is due to a tendency of the LBI to be high for consensus-like sequences that are closer to the future than the average sequence. Simulations of models of adapting populations, in contrast, show clear signals of predictability. This indicates that the evolution of influenza HA and NA, while driven by strong selection pressure to change, is poorly described by common models of directional selection such as travelling fitness waves.

Summary and PurposeThe high-throughput technique of deep mutational scanning (DMS) has recently made it possible to experimentally measure the effects of all amino-acid mutations to a protein (Fowler and Fields 2014). Over the past five years, this technique has been used to study dozens of different proteins (Esposito et al. 2019) and answer a variety of research questions. For example, DMS has been used for protein engineering (Wrenbeck, Faber, and Whitehead 2017), understanding the human immune response to viruses (Lee et al. 2019), and interpreting human variation in a clinical setting (Starita et al. 2017; Gelman et al. 2019). Accompanying this proliferation of DMS studies has been the development of software tools (Bloom 2015; Rubin et al. 2017) and databases (Esposito et al. 2019) for data analysis and sharing. However, for many purposes it is important to also integrate and visualize the DMS data in the context of other information, such as the 3-D protein structure or natural sequence-variation data.Here we describe dms-view (https://dms-view.github.io/), a flexible, web-based, interactive visualization tool for DMS data. dms-view is written in JavaScript and D3, and links site-level and mutation-level DMS data to a 3-D protein structure. The user can interactively select sites of interest to examine the DMS measurements in the context of the protein structure. dms-view tracks the input data and user selections in the URL, making it possible to save specific views of interactively generated visualizations to share with collaborators or to support a published study. Importantly, dms-view takes a flexible input data file so users can easily visualize their own DMS data in the context of protein structures of their choosing, and also incorporate additional information such amino-acid frequencies in natural alignments.

A series of unfortunate events The history of how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread around the planet has been far from clear. Several narratives have been propagated by social media and, in some cases, national policies were forged in response. Now that many thousands of virus sequences are available, two studies analyzed some of the key early events in the spread of SARS-CoV-2. Bedford et al. found that the virus arrived in Washington state in late January or early February. The viral genome from the first case detected had mutations similar to those found in Chinese samples and rapidly spread and dominated subsequent undetected community transmission. The other viruses detected had origins in Europe. Worobey et al. found that early introductions into Germany and the west coast of the United States were extinguished by vigorous public health efforts, but these successes were largely unrecognized. Unfortunately, several major travel events occurred in February, including repatriations from China, with lax public health follow-up. Serial, independent introductions triggered the major outbreaks in the United States and Europe that still hold us in the grip of control measures. Science, this issue p. 571, p. 564, The first case of SARS-CoV-2 in Washington state occurred at the end of January and, by going undetected, sparked community transmission., After its emergence in Wuhan, China, in late November or early December 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus rapidly spread globally. Genome sequencing of SARS-CoV-2 allows the reconstruction of its transmission history, although this is contingent on sampling. We analyzed 453 SARS-CoV-2 genomes collected between 20 February and 15 March 2020 from infected patients in Washington state in the United States. We find that most SARS-CoV-2 infections sampled during this time derive from a single introduction in late January or early February 2020, which subsequently spread locally before active community surveillance was implemented.

In an effort to more fully understand the full spectrum of human genetic variation, we generated deep single-molecule, real-time (SMRT) sequencing data from two haploid human genomes. By using an assembly-based approach (SMRT-SV), we systematically assessed each genome independently for structural variants (SVs) and indels resolving the sequence structure of 461,553 genetic variants from 2 bp to 28 kbp in length. We find that >89% of these variants have been missed as part of analysis of the 1000 Genomes Project even after adjusting for more common variants (MAF > 1%). We estimate that this theoretical human diploid differs by as much as ∼16 Mbp with respect to the human reference, with long-read sequencing data providing a fivefold increase in sensitivity for genetic variants ranging in size from 7 bp to 1 kbp compared with short-read sequence data. Although a large fraction of genetic variants were not detected by short-read approaches, once the alternate allele is sequence-resolved, we show that 61% of SVs can be genotyped in short-read sequence data sets with high accuracy. Uncoupling discovery from genotyping thus allows for the majority of this missed common variation to be genotyped in the human population. Interestingly, when we repeat SV detection on a pseudodiploid genome constructed in silico by merging the two haploids, we find that ∼59% of the heterozygous SVs are no longer detected by SMRT-SV. These results indicate that haploid resolution of long-read sequencing data will significantly increase sensitivity of SV detection.

Summary Understanding the spread and evolution of pathogens is important for effective public health measures and surveillance. Nextstrain consists of a database of viral genomes, a bioinformatics pipeline for phylodynamics analysis, and an interactive visualization platform. Together these present a real-time view into the evolution and spread of a range of viral pathogens of high public health importance. The visualization integrates sequence data with other data types such as geographic information, serology, or host species. Nextstrain compiles our current understanding into a single accessible location, open to health professionals, epidemiologists, virologists and the public alike. Availability and implementation All code (predominantly JavaScript and Python) is freely available from github.com/nextstrain and the web-application is available at nextstrain.org.

The 2017–2018 North American influenza season caused more hospitalizations and deaths than any year since the 2009 H1N1 pandemic. The majority of recorded influenza infections were caused by A(H3N2) viruses, with most of the virus’s North American diversity falling into the A2 clade. Within A2, we observe a subclade which we call A2/re that rose to comprise almost 70 per cent of A(H3N2) viruses circulating in North America by early 2018. Unlike most fast-growing clades, however, A2/re contains no amino acid substitutions in the hemagglutinin (HA) segment. Moreover, hemagglutination inhibition assays did not suggest substantial antigenic differences between A2/re viruses and viruses sampled during the 2016–2017 season. Rather, we observe that the A2/re clade was the result of a reassortment event that occurred in late 2016 or early 2017 and involved the combination of the HA and PB1 segments of an A2 virus with neuraminidase (NA) and other segments a virus from the clade A1b. The success of this clade shows the need for antigenic analysis that targets NA in addition to HA. Our results illustrate the potential for non-HA drivers of viral success and necessitate the need for more thorough tracking of full viral genomes to better understand the dynamics of influenza epidemics.

Whole-exome and whole-genome sequencing have facilitated the large-scale discovery of de novo variants in human disease. To date, most de novo discovery through next-generation sequencing focused on congenital heart disease and neurodevelopmental disorders (NDDs). Currently, de novo variants are one of the most significant risk factors for NDDs with a substantial overlap of genes involved in more than one NDD. To facilitate better usage of published data, provide standardization of annotation, and improve accessibility, we created denovo-db (http://denovo-db.gs.washington.edu), a database for human de novo variants. As of July 2016, denovo-db contained 40 different studies and 32,991 de novo variants from 23,098 trios. Database features include basic variant information (chromosome location, change, type); detailed annotation at the transcript and protein levels; severity scores; frequency; validation status; and, most importantly, the phenotype of the individual with the variant. We included a feature on our browsable website to download any query result, including a downloadable file of the full database with additional variant details. denovo-db provides necessary information for researchers to compare their data to other individuals with the same phenotype and also to controls allowing for a better understanding of the biology of de novo variants and their contribution to disease.

Genetic differences that specify unique aspects of human evolution have typically been identified by comparative analyses between the genomes of humans and closely related primates, including more recently the genomes of archaic hominins. Not all regions of the genome, however, are equally amenable to such study. Recurrent copy number variation (CNV) at chromosome 16p11.2 accounts for approximately 1% of cases of autism and is mediated by a complex set of segmental duplications, many of which arose recently during human evolution. Here we reconstruct the evolutionary history of the locus and identify bolA family member 2 (BOLA2) as a gene duplicated exclusively in Homo sapiens. We estimate that a 95-kilobase-pair segment containing BOLA2 duplicated across the critical region approximately 282 thousand years ago (ka), one of the latest among a series of genomic changes that dramatically restructured the locus during hominid evolution. All humans examined carried one or more copies of the duplication, which nearly fixed early in the human lineage—a pattern unlikely to have arisen so rapidly in the absence of selection (P, Paul G. Allen Family Foundation (11631), Simons Foundation Autism Research Initiative (303241), Simons Foundation Autism Research Initiative (274424), United States. National Institutes of Health (2R01HG002385), United States. National Institutes of Health (TR01 MH095741), G. Harold and Leila Y. Mathers Foundation, JPB Foundation, Leona M. and Harry B. Helmsley Charitable Trust, National Science Foundation (U.S.) (DGE-1256082), National Institute of Mental Health (U.S.) (1F30MH105055-01)

Skeletal atavism in Shetland ponies is a heritable disorder characterized by abnormal growth of the ulna and fibula that extend the carpal and tarsal joints, respectively. This causes abnormal skeletal structure and impaired movements, and affected foals are usually killed. In order to identify the causal mutation we subjected six confirmed Swedish cases and a DNA pool consisting of 21 control individuals to whole genome resequencing. We screened for polymorphisms where the cases and the control pool were fixed for opposite alleles and observed this signature for only 25 SNPs, most of which were scattered on genome assembly unassigned scaffolds. Read depth analysis at these loci revealed homozygosity or compound heterozygosity for two partially overlapping large deletions in the pseudoautosomal region (PAR) of chromosome X/Y in cases but not in the control pool. One of these deletions removes the entire coding region of the SHOX gene and both deletions remove parts of the CRLF2 gene located downstream of SHOX. The horse reference assembly of the PAR is highly fragmented, and in order to characterize this region we sequenced bacterial artificial chromosome (BAC) clones by single-molecule real-time (SMRT) sequencing technology. This considerably improved the assembly and enabled size estimations of the two deletions to 160−180 kb and 60−80 kb, respectively. Complete association between the presence of these deletions and disease status was verified in eight other affected horses. The result of the present study is consistent with previous studies in humans showing crucial importance of SHOX for normal skeletal development.

The high-throughput technique of deep mutational scanning (DMS) has recently made it possible to experimentally measure the effects of all amino-acid mutations to a protein. Over the past five years, this technique has been used to study dozens of different proteins and answer a variety of research questions. For example, DMS has been used for protein engineering, understanding the human immune response to viruses, and interpreting human variation in a clinical setting. Accompanying this proliferation of DMS studies has been the development of software tools and databases for data analysis and sharing. However, for many purposes it is important to also integrate and visualize the DMS data in the context of other information, such as the 3-D protein structure or natural sequence-variation data. Here we describe dms-view (https://dms-view.github.io/), a flexible, web-based, interactive visualization tool for DMS data. dms-view is written in JavaScript and D3, and links site-level and mutation-level DMS data to a 3-D protein structure. The user can interactively select sites of interest to examine the DMS measurements in the context of the protein structure. dms-view tracks the input data and user selections in the URL, making it possible to save specific views of interactively generated visualizations to share with collaborators or to support a published study. Importantly, dms-view takes a flexible input data file so users can easily visualize their own DMS data in the context of protein structures of their choosing, and also incorporate additional information such amino-acid frequencies in natural alignments.

In many repeat diseases, such as Huntington's disease (HD), ongoing repeat expansions in affected tissues contribute to disease onset, progression and severity. Inducing contractions of expanded repeats by exogenous agents is not yet possible. Traditional approaches would target proteins driving repeat mutations. Here we report a compound, naphthyridine-azaquinolone (NA), that specifically binds slipped-CAG DNA intermediates of expansion mutations, a previously unsuspected target. NA efficiently induces repeat contractions in HD patient cells as well as en masse contractions in medium spiny neurons of HD mouse striatum. Contractions are specific for the expanded allele, independently of DNA replication, require transcription across the coding CTG strand and arise by blocking repair of CAG slip-outs. NA-induced contractions depend on active expansions driven by MutSβ. NA injections in HD mouse striatum reduce mutant HTT protein aggregates, a biomarker of HD pathogenesis and severity. Repeat-structure-specific DNA ligands are a novel avenue to contract expanded repeats.

Structural variation and single-nucleotide variation of the complement factor H (CFH) gene family underlie several complex genetic diseases, including age-related macular degeneration (AMD) and atypical hemolytic uremic syndrome (AHUS). To understand its diversity and evolution, we performed high-quality sequencing of this ∼360-kbp locus in six primate lineages, including multiple human haplotypes. Comparative sequence analyses reveal two distinct periods of gene duplication leading to the emergence of four CFH-related (CFHR) gene paralogs (CFHR2 and CFHR4 ∼25-35 Mya and CFHR1 and CFHR3 ∼7-13 Mya). Remarkably, all evolutionary breakpoints share a common ∼4.8-kbp segment corresponding to an ancestral CFHR gene promoter that has expanded independently throughout primate evolution. This segment is recurrently reused and juxtaposed with a donor duplication containing exons 8 and 9 from ancestral CFH, creating four CFHR fusion genes that include lineage-specific members of the gene family. Combined analysis of >5,000 AMD cases and controls identifies a significant burden of a rare missense mutation that clusters at the N terminus of CFH [P = 5.81 × 10-8, odds ratio (OR) = 9.8 (3.67-Infinity)]. A bipolar clustering pattern of rare nonsynonymous mutations in patients with AMD (P 2,400 individuals reveals five recurrent rearrangement breakpoints that show variable frequency among AMD cases and controls. These data suggest a dynamic and recurrent pattern of mutation critical to the emergence of new CFHR genes but also in the predisposition to complex human genetic disease phenotypes.

Significance A key goal in the study of influenza virus evolution is to forecast which viral strains will persist and which ones will die out. Here we experimentally measure the effects of all amino acid mutations to the hemagglutinin protein from a human H3N2 influenza strain on viral growth in cell culture. We show that these measurements have utility for distinguishing among viral strains that do and do not succeed in nature. Overall, our work suggests that new high-throughput experimental approaches may be useful for understanding virus evolution in nature., Human influenza virus rapidly accumulates mutations in its major surface protein hemagglutinin (HA). The evolutionary success of influenza virus lineages depends on how these mutations affect HA’s functionality and antigenicity. Here we experimentally measure the effects on viral growth in cell culture of all single amino acid mutations to the HA from a recent human H3N2 influenza virus strain. We show that mutations that are measured to be more favorable for viral growth are enriched in evolutionarily successful H3N2 viral lineages relative to mutations that are measured to be less favorable for viral growth. Therefore, despite the well-known caveats about cell-culture measurements of viral fitness, such measurements can still be informative for understanding evolution in nature. We also compare our measurements for H3 HA to similar data previously generated for a distantly related H1 HA and find substantial differences in which amino acids are preferred at many sites. For instance, the H3 HA has less disparity in mutational tolerance between the head and stalk domains than the H1 HA. Overall, our work suggests that experimental measurements of mutational effects can be leveraged to help understand the evolutionary fates of viral lineages in nature—but only when the measurements are made on a viral strain similar to the ones being studied in nature.

The production of a reference sequence assembly for the human genome was a milestone in biology and clearly has impacted many areas of biomedical research (McPherson et al. 2001; International Human Genome Sequencing 2004). The availability of this resource allows us to investigate genomic structure and variation at a depth previously unavailable (Kidd et al. 2008; The 1000 Genomes Project Consortium 2012). These studies have helped make clear the shortcomings of our initial assembly models and the difficulty of comprehensive genome analysis. While the current human reference assembly is of extremely high quality and is still the benchmark by which all other human assemblies must be compared, it is far from perfect. Technical and biological complexity lead to both missing sequences as well as misassembled sequence in the current reference, GRCh38 (Robledo et al. 2002; Eichler et al. 2004; International Human Genome Sequencing 2004; Church et al. 2011; Genovese et al. 2013). The two most vexing biological problems affecting assembly are (1) complex genomic architecture seen in large regions with highly homologous duplicated sequences and (2) excess allelic diversity (Bailey et al. 2001; Mills et al. 2006; Korbel et al. 2007; Kidd et al. 2008; Zody et al. 2008). Assembling these regions is further complicated due to the fact that regions of segmental duplication (SD) are often correlated with copy-number variants (CNVs) (Sharp et al. 2005). Regions harboring large CNV SDs have been misrepresented in the reference assembly because assembly algorithms aim to produce a haploid consensus. Highly identical paralogous and structurally polymorphic regions frequently lead to nonallelic sequences being collapsed into a single contig or allelic sequences being improperly represented as duplicates. Because of this complexity, a single, haploid reference is insufficient to fully represent human diversity (Church et al. 2011). The availability of at least one accurate allelic representation at loci with complex genomic architecture facilitates the understanding of the genomic architecture and diversity in these regions (Watson et al. 2013). To enable the assembly of these regions, we have developed a suite of resources from CHM1, a DNA source containing a single human haplotype (Taillon-Miller et al. 1997; Fan et al. 2002). A complete hydatidiform mole (CHM) is an abnormal product of conception in which there is a very early fetal demise and overgrowth of the placental tissue. Most CHMs are androgenetic and contain only paternally derived autosomes and sex chromosomes resulting either from dispermy or duplication of a single sperm genome. The phenotype is thought to be a result of abnormal parental contribution leading to aberrant genomic imprinting (Hoffner and Surti 2012). The absence of allelic variation in monospermic CHM makes it an ideal candidate for producing a single haplotype representation of the human genome. There are a number of existing resources associated with the “CHM1” sample, including a BAC library with end sequences generated with Sanger sequencing using ABI 3730 technology (https://bacpac.chori.org/), an optical map (Teague et al. 2010), and a BioNano genomic map (see Data access), some of which have previously been used to improve regions of the reference human genome assembly. BAC clones have historically been used to resolve difficult genomic regions and identify structural variants (Barbouti et al. 2004; Carvalho and Lupski 2008). A BAC library constructed from CHM1 DNA (CHORI-17, CH17) has also been utilized to resolve several very difficult genomic regions, including human-specific duplications at the SRGAP2 gene family on Chromosome 1 (Dennis et al. 2012). Additionally, the CHM1 BAC clones were used to generate single haplotype assemblies of regions that were previously misrepresented because of haplotype mixing (Watson et al. 2013). Both of these efforts contributed to the improvement of the GRCh38 reference human genome assembly, adding hundreds of kilobases of sequence missing in GRCh37, in addition to providing an accurate single haplotype representation of complex genome regions. Because of the previously established utility of sequence data derived from the CHM1 resource, we wished to develop a complete assembly of a single human haplotype. To this end, we produced a short read-based (Illumina) reference-guided assembly of CHM1 with integrated high-quality finished fully sequenced BAC clones to further improve the assembly. This assembly has been annotated using the NCBI annotation process and has been aligned to other human assemblies in GenBank, including both GRCh37 and GRCh38. Here we present evidence that the CHM1 genome assembly is a high-quality draft with respect to gene and repetitive element content as well as by comparison to other individual genome assemblies. We will also discuss current plans for developing a fully finished genome assembly based on this resource.

© 2017 Macmillan Publishers Limited, part of Springer Nature. Segmental duplications contribute to human evolution, adaptation and genomic instability but are often poorly characterized. We investigate the evolution, genetic variation and coding potential of human-specific segmental duplications (HSDs). We identify 218 HSDs based on analysis of 322 deeply sequenced archaic and contemporary hominid genomes. We sequence 550 human and nonhuman primate genomic clones to reconstruct the evolution of the largest, most complex regions with protein-coding potential (N = 80 genes from 33 gene families). We show that HSDs are non-randomly organized, associate preferentially with ancestral ape duplications termed 'core duplicons' and evolved primarily in an interspersed inverted orientation. In addition to Homo sapiens-specific gene expansions (such as TCAF1/TCAF2), we highlight ten gene families (for example, ARHGAP11B and SRGAP2C) where copy number never returns to the ancestral state, there is evidence of mRNA splicing and no common gene-disruptive mutations are observed in the general population. Such duplicates are candidates for the evolution of human-specific adaptive traits.

Most evolutionary new centromeres (ENC) are composed of large arrays of satellite DNA and surrounded by segmental duplications. However, the hypothesis is that ENCs are seeded in an anonymous sequence and only over time have acquired the complexity of “normal” centromeres. Up to now evidence to test this hypothesis was lacking. We recently discovered that the well-known polymorphism of orangutan chromosome 12 was due to the presence of an ENC. We sequenced the genome of an orangutan homozygous for the ENC, and we focused our analysis on the comparison of the ENC domain with respect to its wild type counterpart. No significant variations were found. This finding is the first clear evidence that ENC seedings are epigenetic in nature. The compaction of the ENC domain was found significantly higher than the corresponding WT region and, interestingly, the expression of the only gene embedded in the region was significantly repressed.

Obtaining high-quality sequence continuity of complex regions of recent segmental duplication remains one of the major challenges of finishing genome assemblies. In the human and mouse genomes, this was achieved by targeting large-insert clones using costly and laborious capillary-based sequencing approaches. Sanger shotgun sequencing of clone inserts, however, has now been largely abandoned, leaving most of these regions unresolved in newer genome assemblies generated primarily by next-generation sequencing hybrid approaches. Here we show that it is possible to resolve regions that are complex in a genome-wide context but simple in isolation for a fraction of the time and cost of traditional methods using long-read single molecule, real-time (SMRT) sequencing and assembly technology from Pacific Biosciences (PacBio). We sequenced and assembled BAC clones corresponding to a 1.3-Mbp complex region of chromosome 17q21.31, demonstrating 99.994% identity to Sanger assemblies of the same clones. We targeted 44 differences using Illumina sequencing and find that PacBio and Sanger assemblies share a comparable number of validated variants, albeit with different sequence context biases. Finally, we targeted a poorly assembled 766-kbp duplicated region of the chimpanzee genome and resolved the structure and organization for a fraction of the cost and time of traditional finishing approaches. Our data suggest a straightforward path for upgrading genomes to a higher quality finished state. © 2014 Huddleston et al.

Human chromosomes 14 and 15 were generated by fission of an ancestral chromosome composed of chromosome 14 attached, head-to-tail, to chromosome 15 around 25 million years ago (Ventura et al. 2003). The rearrangement occurred in the hominoid ancestor and involved a cluster of olfactory receptor (OR) genes (Rudd et al. 2009). At the point of fission, the 15q telomere and the neocentromere of chromosome 14 were seeded (Ventura et al. 2003). The 15q subtelomeric region experienced numerous structural rearrangements, including interstitial deletions and transfers of material to and from other subtelomeric regions (Rudd et al. 2009). Low-copy repeats (LCR), also named segmental duplications (SDs) (Bailey et al. 2001; Cheung et al. 2001), mediate chromosomal rearrangements through non-allelic homologous recombination (NAHR) events (Hastings et al. 2009) and are enriched at pericentromeric and subterminal regions of the human genome (Bailey and Eichler 2006). LCR15 (low-copy repeats on human chromosome 15) loci have been widely studied (Pujana et al. 2001; Zody et al. 2006); those of primary focus are on 15q11–q13 because of their involvement in the Prader-Willi and Angelman syndromes (Pujana et al. 2002). In this work, we provide insights into and highlight the role of LCR in the evolution of human chromosomes 14 and 15. We assembled a 1.6-Mb contig of macaque BAC clones encompassing the 14/15 boundary and tracked evolutionary changes initiated by the fission in the human lineage. We detected duplications from the newly seeded subtelomeric region on chromosome 15 and pericentromeric region on chromosome 14 to other existing subtelomeric and pericentromeric regions, respectively. Further, we traced the dynamics of the formation of the chromosome 14 neocentromere and demonstrated the recruitment of new pericentromeric sequences mainly from the pericentromeric regions of ancestral chromosomes orthologous to human 2q14–qter and 10. We found a correlation between clusters of LCR15 and evolutionary “hotspot” regions. (Note: For simplicity, we used the orthologous numbering of great ape and human chromosomes as proposed for great ape genome sequencing projects [Supplemental Fig. S1; McConkey 2004].)

The immunoglobulin heavy-chain locus (IGH) encodes variable (IGHV), diversity (IGHD), joining (IGHJ), and constant (IGHC) genes and is responsible for antibody heavy-chain biosynthesis, which is vital to the adaptive immune response. Programmed V-(D)-J somatic rearrangement and the complex duplicated nature of the locus have impeded attempts to reconcile its genomic organization based on traditional B-lymphocyte derived genetic material. As a result, sequence descriptions of germline variation within IGHV are lacking, haplotype inference using traditional linkage disequilibrium methods has been difficult, and the human genome reference assembly is missing several expressed IGHV genes. By using a hydatidiform mole BAC clone resource, we present the most complete haplotype of IGHV, IGHD, and IGHJ gene regions derived from a single chromosome, representing an alternate assembly of ∼1 Mbp of high-quality finished sequence. From this we add 101 kbp of previously uncharacterized sequence, including functional IGHV genes, and characterize four large germline copy-number variants (CNVs). In addition to this germline reference, we identify and characterize eight CNV-containing haplotypes from a panel of nine diploid genomes of diverse ethnic origin, discovering previously unmapped IGHV genes and an additional 121 kbp of insertion sequence. We genotype four of these CNVs by using PCR in 425 individuals from nine human populations. We find that all four are highly polymorphic and show considerable evidence of stratification (Fst = 0.3–0.5), with the greatest differences observed between African and Asian populations. These CNVs exhibit weak linkage disequilibrium with SNPs from two commercial arrays in most of the populations tested.

Background Gene innovation by duplication is a fundamental evolutionary process but is difficult to study in humans due to the large size, high sequence identity, and mosaic nature of segmental duplication blocks. The human-specific gene hydrocephalus-inducing 2, HYDIN2, was generated by a 364 kbp duplication of 79 internal exons of the large ciliary gene HYDIN from chromosome 16q22.2 to chromosome 1q21.1. Because the HYDIN2 locus lacks the ancestral promoter and seven terminal exons of the progenitor gene, we sought to characterize transcription at this locus by coupling reverse transcription polymerase chain reaction and long-read sequencing. Results 5' RACE indicates a transcription start site for HYDIN2 outside of the duplication and we observe fusion transcripts spanning both the 5' and 3' breakpoints. We observe extensive splicing diversity leading to the formation of altered open reading frames (ORFs) that appear to be under relaxed selection. We show that HYDIN2 adopted a new promoter that drives an altered pattern of expression, with highest levels in neural tissues. We estimate that the HYDIN duplication occurred ~3.2 million years ago and find that it is nearly fixed (99.9%) for diploid copy number in contemporary humans. Examination of 73 chromosome 1q21 rearrangement patients reveals that HYDIN2 is deleted or duplicated in most cases. Conclusions Together, these data support a model of rapid gene innovation by fusion of incomplete segmental duplications, altered tissue expression, and potential subfunctionalization or neofunctionalization of HYDIN2 early in the evolution of the Homo lineage. Electronic supplementary material The online version of this article (doi:10.1186/s13059-017-1163-9) contains supplementary material, which is available to authorized users.

De novo assembly of human genomes is now a tractable effort due in part to advances in sequencing and mapping technologies. We use PacBio single-molecule, real-time (SMRT) sequencing and BioNano genomic maps to construct the first de novo assembly of NA19240, a Yoruban individual from Africa. This chromosome-scaffolded assembly of 3.08 Gb with a contig N50 of 7.25 Mb and a scaffold N50 of 78.6 Mb represents one of the most contiguous high-quality human genomes. We utilize a BAC library derived from NA19240 DNA and novel haplotype-resolving sequencing technologies and algorithms to characterize regions of complex genomic architecture that are normally lost due to compression to a linear haploid assembly. Our results demonstrate that multiple technologies are still necessary for complete genomic representation, particularly in regions of highly identical segmental duplications. Additionally, we show that diploid assembly has utility in improving the quality of de novo human genome assemblies.

Short-read sequencing has enabled the de novo assembly of several individual human genomes, but with inherent limitations in characterizing repeat elements. Here we sequence a Chinese individual HX1 by single-molecule real-time (SMRT) long-read sequencing, construct a physical map by NanoChannel arrays and generate a de novo assembly of 2.93 Gb (contig N50: 8.3 Mb, scaffold N50: 22.0 Mb, including 39.3 Mb N-bases), together with 206 Mb of alternative haplotypes. The assembly fully or partially fills 274 (28.4%) N-gaps in the reference genome GRCh38. Comparison to GRCh38 reveals 12.8 Mb of HX1-specific sequences, including 4.1 Mb that are not present in previously reported Asian genomes. Furthermore, long-read sequencing of the transcriptome reveals novel spliced genes that are not annotated in GENCODE and are missed by short-read RNA-Seq. Our results imply that improved characterization of genome functional variation may require the use of a range of genomic technologies on diverse human populations., Short-read sequencing has inherent limitations in the characterisation of long repeat elements. Shi and Guo et al. combine single-molecule real-time sequencing and IrysChip to construct a Chinese reference genome that fills many gaps in the reference genome, and identify novel spliced genes.

Recurrent rearrangements of Chromosome 8p23.1 are associated with congenital heart defects and developmental delay. The complexity of this region has led to inconsistencies in the current reference assembly, confounding studies of genetic variation. Using comparative sequence-based approaches, we generated a high-quality 6.3-Mbp alternate reference assembly of an inverted Chromosome 8p23.1 haplotype. Comparison with nonhuman primates reveals a 746-kbp duplicative transposition and two separate inversion events that arose in the last million years of human evolution. The breakpoints associated with these rearrangements map to an ape-specific interchromosomal core duplicon that clusters at sites of evolutionary inversion (P = 7.8 × 10−5). Refinement of microdeletion breakpoints identifies a subgroup of patients that map to the same interchromosomal core involved in the evolutionary formation of the duplication blocks. Our results define a higher-order genomic instability element that has shaped the structure of specific chromosomes during primate evolution contributing to rearrangements associated with inversion and disease.

Deciphering the genetic basis of human disease requires a comprehensive knowledge of genetic variants irrespective of their class or frequency. Although an impressive number of human genetic variants have been catalogued, a large fraction of the genetic difference that distinguishes two human genomes is still not understood at the base-pair level. This is because the emphasis has been on single-nucleotide variation as opposed to less tractable and more complex genetic variants, including indels and structural variants. The latter, we propose, will have a large impact on human phenotypes but require a more systematic assessment of genomes at deeper coverage and alternate sequencing and mapping technologies.

Accurate sequence and assembly of genomes is a critical first step for studies of genetic variation. We generated a high-quality assembly of the gorilla genome using single-molecule, real-time sequence technology and a string graph de novo assembly algorithm. The new assembly improves contiguity by two to three orders of magnitude with respect to previously released assemblies, recovering 87% of missing reference exons and incomplete gene models. Although regions of large, high-identity segmental duplications remain largely unresolved, this comprehensive assembly provides new biological insight into genetic diversity, structural variation, gene loss, and representation of repeat structures within the gorilla genome. The approach provides a path forward for the routine assembly of mammalian genomes at a level approaching that of the current quality of the human genome.

In an effort to more fully understand the full spectrum of human genetic variation, we generated deep single-molecule, real-time (SMRT) sequencing data from two haploid human genomes. By using an assembly-based approach (SMRT-SV), we systematically assessed each genome independently for structural variants (SVs) and indels resolving the sequence structure of 461,553 genetic variants from 2 bp to 28 kbp in length. We find that >89% of these variants have been missed as part of analysis of the 1000 Genomes Project even after adjusting for more common variants (MAF > 1%). We estimate that this theoretical human diploid differs by as much as ∼16 Mbp with respect to the human reference, with long-read sequencing data providing a fivefold increase in sensitivity for genetic variants ranging in size from 7 bp to 1 kbp compared with short-read sequence data. Although a large fraction of genetic variants were not detected by short-read approaches, once the alternate allele is sequence-resolved, we show that 61% of SVs can be genotyped in short-read sequence data sets with high accuracy. Uncoupling discovery from genotyping thus allows for the majority of this missed common variation to be genotyped in the human population. Interestingly, when we repeat SV detection on a pseudodiploid genome constructed in silico by merging the two haploids, we find that ∼59% of the heterozygous SVs are no longer detected by SMRT-SV. These results indicate that haploid resolution of long-read sequencing data will significantly increase sensitivity of SV detection.

Sudmant, Peter H. et al., In order to explore the diversity and selective signatures of duplication and deletion human copy-number variants (CNVs), we sequenced 236 individuals from 125 distinct human populations. We observed that duplications exhibit fundamentally different population genetic and selective signatures than deletions and are more likely to be stratified between human populations. Through reconstruction of the ancestral human genome, we identify megabases of DNA lost in different human lineages and pinpoint large duplications that introgressed from the extinct Denisova lineage now found at high frequency exclusively in Oceanic populations. We find that the proportion of CNV base pairs to single-nucleotide–variant base pairs is greater among non-Africans than it is among African populations, but we conclude that this difference is likely due to unique aspects of non-African population history as opposed to differences in CNV load., This project has been funded in part with federal funds from the National Cancer Institute, NIH, under contract HHSN26120080001E. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does the mention of trade names, commercial products, or organizations imply endorsement by the U.S. government. This research was supported in part by the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research. This work was also partly supported by NIH grant 2R01HG002385 and a grant (11631) from the Paul G. Allen Family Foundation to E.E.E. The sequencing for this study was supported by a grant from the Simons Foundation to D.R. (SFARI 280376) and by a HOMINID grant from the NSF to D.R. (BCS-1032255). T.K. is supported by a European Research Council Starting Investigator grant (FP7 - 26213). R.S. and S.D. received support from the Ministry of Education and Science, Russian Federation (14.Z50.31.0010). H.S., E.M., R.V., and M.M. are supported by Institutional Research Funding from the Estonian Research Council IUT24-1 and by the European Regional Development Fund (European Union) through the Centre of Excellence in Genomics to Estonian Biocentre and University of Tartu. S.A.T. is supported by NIH grants 5DP1ES022577 05, 1R01DK104339-01, and 1R01GM113657-01. C.T.-S. is supported by Wellcome Trust grant 098051. C.M.B. is supported by the NSF (award numbers 0924726 and 1153911). E.E.E. and D.R. are investigators of the Howard Hughes Medical Institute. Data are deposited into ENA (PRJEB9586 or ERP010710), and variant calls are deposited in dbVar (PRJNA285786). E.E.E. is on the scientific advisory board of DNAnexus, Incorporated, and is a consultant for Kunming University of Science and Technology (KUST) as part of the 1000 China Talent Program.

We performed whole-genome sequencing (WGS) of 208 genomes from 53 families affected by simplex autism. For the majority of these families, no copy-number variant (CNV) or candidate de novo gene-disruptive single-nucleotide variant (SNV) had been detected by microarray or whole-exome sequencing (WES). We integrated multiple CNV and SNV analyses and extensive experimental validation to identify additional candidate mutations in eight families. We report that compared to control individuals, probands showed a significant (p = 0.03) enrichment of de novo and private disruptive mutations within fetal CNS DNase I hypersensitive sites (i.e., putative regulatory regions). This effect was only observed within 50 kb of genes that have been previously associated with autism risk, including genes where dosage sensitivity has already been established by recurrent disruptive de novo protein-coding mutations (ARID1B, SCN2A, NR3C2, PRKCA, and DSCAM). In addition, we provide evidence of gene-disruptive CNVs (in DISC1, WNT7A, RBFOX1, and MBD5), as well as smaller de novo CNVs and exon-specific SNVs missed by exome sequencing in neurodevelopmental genes (e.g., CANX, SAE1, and PIK3CA). Our results suggest that the detection of smaller, often multiple CNVs affecting putative regulatory elements might help explain additional risk of simplex autism.

Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association.