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The Javan gibbon, Hylobates moloch, is an endangered gibbon species restricted to the forest remnants of western and central Java, Indonesia, and one of the rarest of the Hylobatidae family. Hylobatids consist of 4 genera (Holoock, Hylobates, Symphalangus, and Nomascus) that are characterized by different numbers of chromosomes, ranging from 38 to 52. The underlying cause of this karyotype plasticity is not entirely understood, at least in part, due to the limited availability of genomic data. Here we present the first scaffold-level assembly for H. moloch using a combination of whole-genome Illumina short reads, 10X Chromium linked reads, PacBio, and Oxford Nanopore long reads and proximity-ligation data. This Hylobates genome represents a valuable new resource for comparative genomics studies in primates.

This paper evaluates the pros and cons of including private equity fund investments in defined contribution plans. Potential benefits include higher returns and improved diversification as well as a relatively safe method for accessing investments previously only available to institutions and the very wealthy. Despite these enticing benefits, they need to be weighed against potential challenges and costs that may arise from creating this broader access to private funds. The complicated structure and uncertainty around the mechanism to provide required liquidity backstops may bring increased fees or even disrupt the private fund model.

The conventional wisdom for investors in private equity funds is to invest in partnerships that have performed well in the past. This is based on the belief that performance in private equity persists across funds of the same partnership. We present new evidence on the persistence of U.S. private equity (buyout and venture capital) funds using a research-quality dataset from Burgiss, sourced from over 200 institutional investors. Relying on detailed cash-flow data for funds, we study the persistence of buyout and venture capital fund performance of the same general partners across different funds. We pay particular attention to persistence pre- and post-2000. Previous research, studying largely pre-2000 data, has found strong persistence for both buyout and venture capital firms. We confirm the previous findings on persistence in pre-2000 funds. There is persistence for buyout funds and, particularly, for venture funds. Post-2000, we find little evidence of persistence for buyout funds, except at the lower end of the performance distribution. When funds are sorted by the quartile of performance of their previous funds, performance of the current fund is statistically indistinguishable regardless of quartile. Performance for partnerships in all previous fund quartiles exceeds those of public markets as measured by the S&P 500. Regression results confirm the absence of persistence post-2000 except for funds in the lower end of the performance distribution. Post-2000, we find that performance in venture capital funds remains as persistent as pre-2000. Partnerships whose previous venture capital funds are below the median for their vintage year subsequently tend to be below median and have returns below those of the public markets (S&P 500). Partnerships in the top two quartiles tend to stay above the median and their returns exceed those of the public markets.

BackgroundThe blue whale, Balaenoptera musculus , is the largest animal known to have ever existed. Body size is tightly coupled to cell metabolism and environmental adaptations. A high-quality genome assembly of this magnificent animal will aid our understanding of body size regulation and related biological processes.ResultsWe report a reference-quality, long read based assembly of the blue whale genome. We sequenced genomic DNA using PacBio long-read, Illumina short-read, and 10X Genomics synthetic long-read technologies. We also obtained long-range mapping information using Bionano optical mapping and Dovetail Hi-C. Additionally, we sequenced the transcriptome of blue whale fibroblasts using Illumina RNA-seq and PacBio Iso-seq technologies. We also measured genome size using a flow cytometry technique. We report on: (1) comparison of alternative long-read and short-read-based assemblies; (2) segmental duplications within the blue whale genome, which have resulted in dramatic amplifications of several genes; (3) sites in IGF1 gene correlated to body size in cetaceans; and (4) heterozygosity and historical demography of Pacific and Atlantic blue whale populations.ConclusionsThis is one of the first high-quality reference genomes of a cetacean and the first baleen whale sequenced using a long-read technology. A high quality, annotated blue whale genome will serve as an important resource for biology, evolution, and conservation research.

High-quality and complete reference genome assemblies are fundamental for the application of genomics to biology, disease, and biodiversity conservation. However, such assemblies are available for only a few non-microbial species1,2,3,4. To address this issue, the international Genome 10K (G10K) consortium5,6 has worked over a five-year period to evaluate and develop cost-effective methods for assembling highly accurate and nearly complete reference genomes. Here we present lessons learned from generating assemblies for 16 species that represent six major vertebrate lineages. We confirm that long-read sequencing technologies are essential for maximizing genome quality, and that unresolved complex repeats and haplotype heterozygosity are major sources of assembly error when not handled correctly. Our assemblies correct substantial errors, add missing sequence in some of the best historical reference genomes, and reveal biological discoveries. These include the identification of many false gene duplications, increases in gene sizes, chromosome rearrangements that are specific to lineages, a repeated independent chromosome breakpoint in bat genomes, and a canonical GC-rich pattern in protein-coding genes and their regulatory regions. Adopting these lessons, we have embarked on the Vertebrate Genomes Project (VGP), an international effort to generate high-quality, complete reference genomes for all of the roughly 70,000 extant vertebrate species and to help to enable a new era of discovery across the life sciences., We thank them for their permission to publish. A.R., S.K., B.P.W. and A.M.P. were supported by the Intramural Research Program of the NHGRI, NIH (1ZIAHG200398). A.R. was also supported by the Korea Health Technology R&D Project through KHIDI, funded by the Ministry of Health & Welfare, Republic of Korea (HI17C2098). S.A.M., I.B. and R.D. were supported by Wellcome Trust grant WT207492; W.C., M. Smith, Z.N., Y.S., J.C., S. Pelan, J.T., A.T., J.W. and Kerstin Howe by WT206194; L.H., F.M., Kevin Howe and P. Flicek by WT108749/Z/15/Z, WT218328/B/19/Z and the European Molecular Biology Laboratory. O.F. and E.D.J. were supported by Howard Hughes Medical Institute and Rockefeller University start-up funds for this project. J.D. and H.A.L. were supported by the Robert and Rosabel Osborne Endowment. M.U.-S. received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement (750747). F.T.-N., J. Hoffman, P. Masterson and K.C. were supported by the Intramural Research Program of the NLM, NIH. C.L., B.J.K., J. Kim and H.K. were supported by the Marine Biotechnology Program of KIMST, funded by the Ministry of Ocean and Fisheries, Republic of Korea (20180430). M.C. was supported by Sloan Research Fellowship (FG-2020-12932). S.C.V. was funded by a Max Planck Research Group award from the Max Planck Society, and a Human Frontiers Science Program (HFSP) Research grant (RGP0058/2016). T.M.L., W.E.J. and the Canada lynx genome were funded by the Maine Department of Inland Fisheries & Wildlife (F11AF01099), including when W.E.J. held a National Research Council Research Associateship Award at the Walter Reed Army Institute of Research (WRAIR). C.B. was supported by the NSF (1457541 and 1456612). D.B. was funded by The University of Queensland (HFSP - RGP0030/2015). D.I. was supported by Science Exchange Inc. (Palo Alto, CA). H.W.D. was supported by NSF grants (OPP-0132032 ICEFISH 2004 Cruise, PLR-1444167 and OPP-1955368) and the Marine Science Center at Northeastern University (416). G.J.P.N. and the thorny skate genome were funded by Lenfest Ocean Program (30884). M.P. was funded by the German Federal Ministry of Education and Research (01IS18026C). M. Malinsky was supported by an EMBO fellowship (ALTF 456-2016). The following authors’ contributions were supported by the NIH: S. Selvaraj (R44HG008118); C.V.M., S.R.F., P.V.L. (R21 DC014432/DC/NIDCD); K.D.M. (R01GM130691); H.C. (5U41HG002371-19); M.D. (U41HG007234); and B.P. (R01HG010485). D.G. was supported by the National Key Research and Development Program of China (2017YFC1201201, 2018YFC0910504 and 2017YFC0907503). F.O.A. was supported by Al-Gannas Qatari Society and The Cultural Village Foundation-Katara, Doha, State of Qatar and Monash University Malaysia. C.T. was supported by The Rockefeller University. M. Hiller was supported by the LOEWE-Centre for Translational Biodiversity Genomics (TBG) funded by the Hessen State Ministry of Higher Education, Research and the Arts (HMWK). H.C. was supported by the NHGRI (5U41HG002371-19). R.H.S.K. was funded by the Max Planck Society with computational resources at the bwUniCluster and BinAC funded by the Ministry of Science, Research and the Arts Baden-Württemberg and the Universities of the State of Baden-Württemberg, Germany (bwHPC-C5). B.V. was supported by the Biomedical Research Council of A*STAR, Singapore. T.M.-B. was funded by the European Research Council under the European Union’s Horizon 2020 research and innovation programme (864203), MINECO/FEDER, UE (BFU2017-86471-P), Unidad de Excelencia María de Maeztu, AEI (CEX2018-000792-M), a Howard Hughes International Early Career award, Obra Social “La Caixa” and Secretaria d’Universitats i Recerca and CERCA Programme del Departament d’Economia i Coneixement de la Generalitat de Catalunya (GRC 2017 SGR 880). E.C.T. was supported by the European Research Council (ERC-2012-StG311000) and an Irish Research Council Laureate Award. M.T.P.G. was supported by an ERC Consolidator Award 681396-Extinction Genomics, and a Danish National Research Foundation Center Grant (DNRF143). T.W. was supported by the NSF (1458652). J. M. Graves was supported by the Australian Research Council (CEO561477). E.W.M. was partially supported by the German Federal Ministry of Education and Research (01IS18026C). Complementary sequencing support for the Anna’s hummingbird and several genomes was provided by Pacific Biosciences, Bionano Genomics, Dovetail Genomics, Arima Genomics, Phase Genomics, 10X Genomics, NRGene, Oxford Nanopore Technologies, Illumina, and DNAnexus. All other sequencing and assembly were conducted at the Rockefeller University, Sanger Institute, and Max Planck Institute Dresden genome labs. Part of this work used the computational resources of the NIH HPC Biowulf cluster (https://hpc.nih.gov). We acknowledge funding from the Wellcome Trust (108749/Z/15/Z) and the European Molecular Biology Laboratory., With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2018-000792-M).

Private equity performance, both for buyouts and venture capital, has been highly cyclical: periods of high fundraising have been followed by periods of low performance. Despite this seemingly predictable variation, we find modest gains, at best, to pursuing realistic, investable strategies that time capital commitments to private equity. This occurs, in part, because investors can only time their commitments to funds; they cannot time when commitments are called or when investments are exited. There is a high degree of time-series correlation in net cash flows even across commitment strategies that allocate capital in a very different manner over time.

Approximately 13% of the human genome can fold into non-canonical (non-B) DNA structures (e.g. G-quadruplexes, Z-DNA, etc.), which have been implicated in vital cellular processes. Non-B DNA also hinders replication, increasing errors and facilitating mutagenesis, yet its contribution to genome-wide variation in mutation rates remains unexplored. Here, we conducted a comprehensive analysis of nucleotide substitution frequencies at non-B DNA loci within noncoding, non-repetitive genome regions, their ±2 kb flanking regions, and 1-Megabase windows, using human-orangutan divergence and human single-nucleotide polymorphisms. Functional data analysis at single-base resolution demonstrated that substitution frequencies are usually elevated at non-B DNA, with patterns specific to each non-B DNA type. Mirror, direct and inverted repeats have higher substitution frequencies in spacers than in repeat arms, whereas G-quadruplexes, particularly stable ones, have higher substitution frequencies in loops than in stems. Several non-B DNA types also affect substitution frequencies in their flanking regions. Finally, non-B DNA explains more variation than any other predictor in multiple regression models for diversity or divergence at 1-Megabase scale. Thus, non-B DNA substantially contributes to variation in substitution frequencies at small and large scales. Our results highlight the role of non-B DNA in germline mutagenesis with implications to evolution and genetic diseases., Graphical Abstract Graphical AbstractGuiblet et al. show that loci capable of forming non-canonical (non-B) DNA structures are a major driver of variation in nucleotide substitution levels across the genome. Image credit: Wilfried Guiblet.

Motivation Sketching is now widely used in bioinformatics to reduce data size and increase data processing speed. Sketching approaches entice with improved scalability but also carry the danger of decreased accuracy and added bias. In this article, we investigate the minimizer sketch and its use to estimate the Jaccard similarity between two sequences. Results We show that the minimizer Jaccard estimator is biased and inconsistent, which means that the expected difference (i.e. the bias) between the estimator and the true value is not zero, even in the limit as the lengths of the sequences grow. We derive an analytical formula for the bias as a function of how the shared k-mers are laid out along the sequences. We show both theoretically and empirically that there are families of sequences where the bias can be substantial (e.g. the true Jaccard can be more than double the estimate). Finally, we demonstrate that this bias affects the accuracy of the widely used mashmap read mapping tool. Availability and implementation Scripts to reproduce our experiments are available at https://github.com/medvedevgroup/minimizer-jaccard-estimator/tree/main/reproduce. Supplementary information Supplementary data are available at Bioinformatics online.

Modern sequencing technologies are not error-free, and might have elevated error rates at some locations of the genome. A potential cause for such elevated error rates is the formation of alternative DNA structures (non-B DNA), such as G-quadruplexes (G4s), Z-DNA, or cruciform structures, during sequencing. Approximately 13% of the human genome has the potential to form such structures, which have been previously shown to affect the activity of DNA polymerases and helicases. Here we tested whether motifs with the potential to form non-B DNA (non-B motifs) influence the sequencing success of three major sequencing technologies—Illumina, Pacific Biosciences (PacBio) HiFi, and Oxford Nanopore Technologies (ONT). We estimated sequencing success by computing the rates of single-nucleotide, insertion, and deletion errors, as well as by evaluating mean read depth and mean base quality. Overall, all technologies exhibited altered sequencing success for most non-B motif types. Single-nucleotide error rates were generally increased for G-quadruplexes (G4s) and Z-DNA motifs in all three technologies. Illumina and PacBio HiFi deletion error rates were also increased for all non-B types except for Z-DNA motifs, while in ONT they were increased substantially only for G4 motifs. Insertion error rates for non-B motifs were highly elevated in Illumina, moderately elevated in PacBio HiFi, and only slightly elevated in ONT. Using Poisson regression modeling, we evaluated how non-B DNA motifs and other factors influence sequencing error profiles. Using the error rates at non-B motifs, we developed a probabilistic approach to determine the number of false-positive single-nucleotide variants (SNVs) in different sample size and variant frequency cutoff scenarios, as well as in previously generated sequencing data sets (1000Genomes, Simons Genome Diversity Project, and gnomAD). Overall, the effect of non-B DNA on sequencing should be considered in downstream analyses, particularly in studies with limited read depth—e.g., single-cell and ancient DNA sequencing, as well as sequencing of pooled population samples—and when scoring variants with low frequency (e.g., singletons). Because each sequencing technology analyzed has a unique error profile at non-B motifs, a combination of different technologies should be considered in future sequencing studies of such motifs, to maximize accuracy.

Significance The male-specific Y chromosome harbors genes important for sperm production. Because Y is repetitive, its DNA sequence was deciphered for only a few species, and its evolution remains elusive. Here we compared the Y chromosomes of great apes (human, chimpanzee, bonobo, gorilla, and orangutan) and found that many of their repetitive sequences and multicopy genes were likely already present in their common ancestor. Y repeats had increased intrachromosomal contacts, which might facilitate preservation of genes and gene regulatory elements. Chimpanzee and bonobo, experiencing high sperm competition, underwent many DNA changes and gene losses on the Y. Our research is significant for understanding the role of the Y chromosome in reproduction of nonhuman great apes, all of which are endangered., The mammalian male-specific Y chromosome plays a critical role in sex determination and male fertility. However, because of its repetitive and haploid nature, it is frequently absent from genome assemblies and remains enigmatic. The Y chromosomes of great apes represent a particular puzzle: their gene content is more similar between human and gorilla than between human and chimpanzee, even though human and chimpanzee share a more recent common ancestor. To solve this puzzle, here we constructed a dataset including Ys from all extant great ape genera. We generated assemblies of bonobo and orangutan Ys from short and long sequencing reads and aligned them with the publicly available human, chimpanzee, and gorilla Y assemblies. Analyzing this dataset, we found that the genus Pan, which includes chimpanzee and bonobo, experienced accelerated substitution rates. Pan also exhibited elevated gene death rates. These observations are consistent with high levels of sperm competition in Pan. Furthermore, we inferred that the great ape common ancestor already possessed multicopy sequences homologous to most human and chimpanzee palindromes. Nonetheless, each species also acquired distinct ampliconic sequences. We also detected increased chromatin contacts between and within palindromes (from Hi-C data), likely facilitating gene conversion and structural rearrangements. Our results highlight the dynamic mode of Y chromosome evolution and open avenues for studies of male-specific dispersal in endangered great ape species.

Satellite repeats are a structural component of centromeres and telomeres, and in some instances their divergence is known to drive speciation. Due to their highly repetitive nature, satellite sequences have been understudied and underrepresented in genome assemblies. To investigate their turnover in great apes, we studied satellite repeats of unit sizes up to 50 bp in human, chimpanzee, bonobo, gorilla, and Sumatran and Bornean orangutans, using unassembled short and long sequencing reads. The density of satellite repeats, as identified from accurate short reads (Illumina), varied greatly among great ape genomes. These were dominated by a handful of abundant repeated motifs, frequently shared among species, which formed two groups: (1) the (AATGG)nrepeat (critical for heat shock response) and its derivatives; and (2) subtelomeric 32-mers involved in telomeric metabolism. Using the densities of abundant repeats, individuals could be classified into species. However clustering did not reproduce the accepted species phylogeny, suggesting rapid repeat evolution. Several abundant repeats were enriched in males vs. females; using Y chromosome assemblies or FIuorescent In Situ Hybridization, we validated their location on the Y. Finally, applying a novel computational tool, we identified many satellite repeats completely embedded within long Oxford Nanopore and Pacific Biosciences reads. Such repeats were up to 59 kb in length and consisted of perfect repeats interspersed with other similar sequences. Our results based on sequencing reads generated with three different technologies provide the first detailed characterization of great ape satellite repeats, and open new avenues for exploring their functions.

New genome assemblies have been arriving at a rapidly increasing pace, thanks to decreases in sequencing costs and improvements in third-generation sequencing technologies1–3. For example, the number of vertebrate genome assemblies currently in the NCBI (National Center for Biotechnology Information) database4 increased by more than 50% to 1,485 assemblies in the year from July 2018 to July 2019. In addition to this influx of assemblies from different species, new human de novo assemblies5 are being produced, which enable the analysis of not only small polymorphisms, but also complex, large-scale structural differences between human individuals and haplotypes. This coming era and its unprecedented amount of data offer the opportunity to uncover many insights into genome evolution but also present challenges in how to adapt current analysis methods to meet the increased scale. Cactus6, a reference-free multiple genome alignment program, has been shown to be highly accurate, but the existing implementation scales poorly with increasing numbers of genomes, and struggles in regions of highly duplicated sequences. Here we describe progressive extensions to Cactus to create Progressive Cactus, which enables the reference-free alignment of tens to thousands of large vertebrate genomes while maintaining high alignment quality. We describe results from an alignment of more than 600 amniote genomes, which is to our knowledge the largest multiple vertebrate genome alignment created so far., The Progressive Cactus program can create reference-free alignments of hundreds of large vertebrate genomes efficiently, and is used for the alignment of more than 600 amniote genomes.

High-quality and complete reference genome assemblies are fundamental for the application of genomics to biology, disease, and biodiversity conservation. However, such assemblies are only available for a few non-microbial species1–4. To address this issue, the international Genome 10K (G10K) consortium5,6 has worked over a five-year period to evaluate and develop cost-effective methods for assembling the most accurate and complete reference genomes to date. Here we summarize these developments, introduce a set of quality standards, and present lessons learned from sequencing and assembling 16 species representing major vertebrate lineages (mammals, birds, reptiles, amphibians, teleost fishes and cartilaginous fishes). We confirm that long-read sequencing technologies are essential for maximizing genome quality and that unresolved complex repeats and haplotype heterozygosity are major sources of error in assemblies. Our new assemblies identify and correct substantial errors in some of the best historical reference genomes. Adopting these lessons, we have embarked on the Vertebrate Genomes Project (VGP), an effort to generate high-quality, complete reference genomes for all ~70,000 extant vertebrate species and help enable a new era of discovery across the life sciences.

This paper evaluates the pros and cons of including private equity fund investments in defined contribution plans. Potential benefits include higher returns and improved diversification as well as a relatively safe method for accessing investments previously only available to institutions and the very wealthy. Despite these enticing benefits, they need to be weighed against potential challenges and costs that may arise from creating this broader access to private funds. The complicated structure and uncertainty around the mechanism to provide required liquidity backstops may bring increased fees or even disrupt the private fund model. Consequently, whether access to private investments provide a net benefit for DC plan participants will depend both on how private fund investments perform in the future as well as how institutional features around plan participation evolve.

This paper provides a first look at newly available data on the holdings of private equity (PE) funds. Because research has been hampered by the lack of comprehensive, high-quality data on portfolio companies, this new source offers the potential for a wide range of research. Provided by Burgiss, a global provider of data and analytics to investors in PE funds (limited partner investors or LPs), the data are gathered from the financial reports of general partners (GPs) to LPs who are Burgiss clients. The sample covers over 45,000 investments in funds’ portfolio companies (in buyout and venture capital); moreover, the coverage is expected to grow through a phased release process. The paper describes preliminary findings on sample characteristics and offers a high-level view on aspects of performance in hopes of inspiring additional research. Returns to investments in portfolio companies are highly variable and skewed. This is particularly true of venture capital where many investments turn out worthless and average performance is boosted by a few spectacular successes that create the bulk of fund value. Performance is related to a number of factors (including investment size, duration of the investment and levels of fund raising), with patterns differing for buyout and venture capital investments.

This case features an entrepreneur who must decide whether to sell his small distribution company. The case explores several issues for class discussion: (1) valuation of a private company, (2) assessing the entrepreneur's perspective and alternatives, (3) deal structuring (including earnouts), (4) risks and their effect on value, and (5) advice from a banker's perspective.

This technical note compares two methods of treating debt usage in discounted-cash-flow valuation of investment projects or companies. The note demonstrates that the approach using weighted average cost of capital (WACC) and the approach using equity residual (ER) yield equivalent results if consistent assumptions are used. General features are illustrated with specific examples, including a spreadsheet.

This case is a relatively straightforward exercise in valuing a potential acquisition target. The case affords students an opportunity to use both discounted cash flow and multiples in their analyses. In addition, at the instructor's discretion, students can do a simple valuation of an option contract and analyze currency choice in a debt issue. The latter two objectives arise if the case is used as an examination. Case Exhibit 1 poses the relevant questions for student preparation.

Motivation Algorithmic solutions to index and search biological databases are a fundamental part of bioinformatics, providing underlying components to many end-user tools. Inexpensive next generation sequencing has filled publicly available databases such as the Sequence Read Archive beyond the capacity of traditional indexing methods. Recently, the Sequence Bloom Tree (SBT) and its derivatives were proposed as a way to efficiently index such data for queries about transcript presence. Results We build on the SBT framework to construct the HowDe-SBT data structure, which uses a novel partitioning of information to reduce the construction and query time as well as the size of the index. Compared to previous SBT methods, on real RNA-seq data, HowDe-SBT can construct the index in less than 36% of the time and with 39% less space and can answer small-batch queries at least five times faster. We also develop a theoretical framework in which we can analyze and bound the space and query performance of HowDe-SBT compared to other SBT methods. Availability and implementation HowDe-SBT is available as a free open source program on https://github.com/medvedevgroup/HowDeSBT. Supplementary information Supplementary data are available at Bioinformatics online.

BackgroundLarge granular lymphocyte (LGL) leukemia is an uncommon cancer characterized by a sustained clonal proliferation of LGL cells. Antibodies reactive to retroviruses have been documented in the serum of patients with LGL leukemia. Culture or molecular approaches have to date not been successful in identifying a retrovirus.MethodsBecause a retrovirus must integrate into the genome of an infected cell, we focused our efforts on detecting a novel retrovirus integration site in the clonally expanded LGL cells. We present a new computational tool that uses long-insert mate pair sequence data to search the genome of LGL leukemia cells for retrovirus integration sites. We also utilize recently published methods to interrogate the status of polymorphic human endogenous retrovirus type K (HERV-K) provirus in patient genomes.ResultsWhile our analysis did not reveal any new retrovirus insertions in LGL genomes from LGL leukemia patients, we did identify four HERV-K provirus integration sites that are polymorphic in the human population and absent from the human reference genome, hg19. To determine if the prevalence of these or other polymorphic proviral HERV-Ks differed between LGL leukemia patients and the general population, we applied a recently developed approach that reports all sites in the human genome occupied by a proviral HERV-K. Using the 1000 genomes project (KGP) data as a reference database for HERV-K proviral prevalence at each polymorphic site, we show that there are significant differences in the number of polymorphic HERV-Ks in the genomes of LGL leukemia patients of European origin compared to individuals with European ancestry in the KGP data.ConclusionsOur study confirms that the integration of a new infectious or endogenous retrovirus does not cause the clonal expansion of LGL cells in LGL leukemia, although we do not rule out that these cells could be responding to retroviral antigens produced in other cell types. However, it is of interest that the burden of polymorphic proviral HERV-K is elevated in LGL leukemia patient genomes. Our research emphasizes the merits of comprehensive genomic assessment of HERV-K in cancer samples and suggests that further analyses to determine contributions of HERV-K to LGL leukemia are warranted.

This paper examines the compensation of Chief Investment Officers (CIOs) of nonprofit endowments, which have different economic models and monitoring arrangements than those of other institutional investors. We find that compensation reflects the demands of the job, abilities and experience that individuals bring to the job and how well the endowment performs. Pay relies heavily on bonuses and is positively linked to the CIO's education and professional experience. Large endowments hire CIOs with stronger backgrounds, pay them more and structure pay significantly linked to endowment performance. Even controlling for size, compensation depends on an endowment’s governance and location. The results are consistent with the increased investment skills needed to manage large pools of capital often involving alternative assets, and with differences in labor market and monitoring arrangements across endowments. For large endowments the sensitivity of pay to performance is greater than often reported for mutual fund managers.

DNA conformation may deviate from the classical B-form in ~13% of the human genome. Non-B DNA regulates many cellular processes; however, its effects on DNA polymerization speed and accuracy have not been investigated genome-wide. Such an inquiry is critical for understanding neurological diseases and cancer genome instability. Here we present the first simultaneous examination of DNA polymerization kinetics and errors in the human genome sequenced with Single-Molecule-Real-Time technology. We show that polymerization speed differs between non-B and B-DNA: it decelerates at G-quadruplexes and fluctuates periodically at disease-causing tandem repeats. Analyzing polymerization kinetics profiles, we predict and validate experimentally non-B DNA formation for a novel motif. We demonstrate that several non-B motifs affect sequencing errors (e.g., G-quadruplexes increase error rates) and that sequencing errors are positively associated with polymerase slowdown. Finally, we show that highly divergent G4 motifs have pronounced polymerization slowdown and high sequencing error rates, suggesting similar mechanisms for sequencing errors and germline mutations.

Summary Tandem DNA repeats can be sequenced with long-read technologies, but cannot be accurately deciphered due to the lack of computational tools taking high error rates of these technologies into account. Here we introduce Noise-Cancelling Repeat Finder (NCRF) to uncover putative tandem repeats of specified motifs in noisy long reads produced by Pacific Biosciences and Oxford Nanopore sequencers. Using simulations, we validated the use of NCRF to locate tandem repeats with motifs of various lengths and demonstrated its superior performance as compared to two alternative tools. Using real human whole-genome sequencing data, NCRF identified long arrays of the (AATGG)n repeat involved in heat shock stress response. Availability and implementation NCRF is implemented in C, supported by several python scripts, and is available in bioconda and at https://github.com/makovalab-psu/NoiseCancellingRepeatFinder. Supplementary information Supplementary data are available at Bioinformatics online.

We examine the links between human capital and endowment investing. Harnessing detailed information on university endowments, we find that higher asset allocations to alternative assets accompany higher levels of human capital in the endowment’s investment process. Moreover, high levels of human capital are linked to larger returns, even on a risk-adjusted basis. The improved investment outcomes arise because endowments capture higher returns that can accompany alternative assets, select or have access to high performing managers, and minimize fees by accessing funds directly rather than through funds of funds. Our measures of human capital include expertise in alternatives on governing bodies, the presence of a chief investment officer and the size of the investment staff. We also find that a university board’s professional networks are linked to higher allocations to private equity. Finally, we conduct a novel survey of endowments and confirm that human capital is central in facilitating alternative investments.

Private equity performance, both for buyouts and venture capital, has been highly cyclical: periods of high fundraising have been followed by periods of low performance. Despite this seemingly predictable variation, we find modest gains, at best, to pursuing realistic, investable strategies that time capital commitments to private equity. This occurs, in part, because investors can only time their commitments to funds; they cannot time when commitments are called or when investments are exited. There is a high degree of time-series correlation in net cash flows even across commitment strategies that allocate capital in a very different manner over time.

Motivation The haploid mammalian Y chromosome is usually under-represented in genome assemblies due to high repeat content and low depth due to its haploid nature. One strategy to ameliorate the low coverage of Y sequences is to experimentally enrich Y-specific material before assembly. As the enrichment process is imperfect, algorithms are needed to identify putative Y-specific reads prior to downstream assembly. A strategy that uses k-mer abundances to identify such reads was used to assemble the gorilla Y. However, the strategy required the manual setting of key parameters, a time-consuming process leading to sub-optimal assemblies. Results We develop a method, RecoverY, that selects Y-specific reads by automatically choosing the abundance level at which a k-mer is deemed to originate from the Y. This algorithm uses prior knowledge about the Y chromosome of a related species or known Y transcript sequences. We evaluate RecoverY on both simulated and real data, for human and gorilla, and investigate its robustness to important parameters. We show that RecoverY leads to a vastly superior assembly compared to alternate strategies of filtering the reads or contigs. Compared to the preliminary strategy used by Tomaszkiewicz et al., we achieve a 33% improvement in assembly size and a 20% improvement in the NG50, demonstrating the power of automatic parameter selection. Availability and implementation Our tool RecoverY is freely available at https://github.com/makovalab-psu/RecoverY. Supplementary information Supplementary data are available at Bioinformatics online.

MotivationThe haploid mammalian Y chromosome is usually under-represented in genome assemblies due to high repeat content and low depth due to its haploid nature. One strategy to ameliorate the low coverage of Y sequences is to experimentally enrich Y-specific material before assembly. Since the enrichment process is imperfect, algorithms are needed to identify putative Y-specific reads prior to downstream assembly. A strategy that uses k-mer abundances to identify such reads was used to assemble the gorilla Y (Tomaszkiewicz et al 2016). However, the strategy required the manual setting of key parameters, a time-consuming process leading to sub-optimal assemblies.ResultsWe develop a method, RecoverY, that selects Y-specific reads by automatically choosing the abundance level at which a k-mer is deemed to originate from the Y. This algorithm uses prior knowledge about the Y chromosome of a related species or known Y transcript sequences. We evaluate RecoverY on both simulated and real data, for human and gorilla, and investigate its robustness to important parameters. We show that RecoverY leads to a vastly superior assembly compared to alternate strategies of filtering the reads or contigs. Compared to the preliminary strategy used in Tomaszkiewicz et al (2016), we achieve a 33% improvement in assembly size and a 20% improvement in the NG50, demonstrating the power of automatic parameter selection.AvailabilityOur tool RecoverY is freely available at https://github.com/makovalab-psu/RecoverYContactkmakova@bx.psu.edu, pashadag@cse.psu.eduSupplementary informationAttached as an additional file.

The ubiquity of next generation sequencing has transformed the size and nature of many databases, pushing the boundaries of current indexing and searching methods. One particular example is a database of 2,652 human RNA-seq experiments uploaded to the Sequence Read Archive. Recently, Solomon and Kingsford proposed the Sequence Bloom Tree data structure and demonstrated how it can be used to accurately identify SRA samples that have a transcript of interest potentially expressed. In this paper, we propose an improvement called the AllSome Sequence Bloom Tree. Results show that our new data structure significantly improves performance, reducing the tree construction time by 52.7% and query time by 39 - 85%, with a price of up to 3x memory consumption during queries. Notably, it can query a batch of 198,074 queries in under 8 hours (compared to around two days previously) and a whole set of k-mers from a sequencing experiment (about 27 mil k-mers) in under 11 minutes.