Search

SummaryWe describe a compression scheme for BUS files and an implementation of the algorithm in the bustools software. Our compression algorithm yields smaller file sizes than gzip, at significantly faster compression and decompression speeds. We evaluated our algorithm on 533 BUS files from scRNA-seq experiments with a total size of 1Tb. Our compression is more than 2x faster than the fastest gzip option and results in 1.5x smaller files than the best gzip compression. This amounts to an 8.3x reduction in the file size, resulting in a compressed size of 122Gb for the dataset.Availability and ImplementationA complete description of the format is available athttps://github.com/BUStools/BUSZ-formatand an implementation athttps://github.com/BUStools/bustoolsContactpmelsted@hi.isonline.

The Rock Ptarmigan (Lagopus muta) is a cold-adapted, largely sedentary, game bird with a Holarctic distribution. The species represents an important example of an organism likely to be affected by ongoing climatic shifts across a disparate range. We provide here a high-quality reference genome and mitogenome for the Rock Ptarmigan assembled from PacBio HiFi and Hi-C sequencing of a female bird from Iceland. The total size of the genome is 1.03 Gb with a scaffold N50 of 71.23 Mb and a contig N50 of 17.91 Mb. The final scaffolds represent all 40 predicted chromosomes, and the mitochondria with a BUSCO score of 98.6%. Gene annotation resulted in 16,078 protein-coding genes out of a total 19,831 predicted (81.08% excluding pseudogenes). The genome included 21.07% repeat sequences, and the average length of genes, exons, and introns were, 33605, 394, and 4265 bp respectively. The availability of a new reference-quality genome will contribute to understanding the Rock Ptarmigan’s unique evolutionary history, vulnerability to climate change, and demographic trajectories around the globe and serve as a reference genome for the species in the family Tetraonidae (order Galliformes).

We present a novel method for associating phenotypes with RNA expression, that can identify expression associations resulting from a wide variety of underlying transcriptional and post-transcriptional events, without relying on annotations of these events. We show that we can reliably detect,de novo, phenotypically relevant transcriptional structures

The presence of both nascent and mature mRNA molecules in single-cell RNA-seq data leads to ambiguity in the notion of a “count matrix”. Underlying this ambiguity, is the challenging problem of separately quantifying nascent and mature mRNAs. We address this problem by relatingk-mer assignment to read assignment in the context of different classes of molecules, and describe a unified approach to quantifying both single-cell and single-nucleus RNA-seq.

Age-related hearing impairment (ARHI) is the most common sensory disorder in older adults. We conducted a genome-wide association meta-analysis of 121,934 ARHI cases and 591,699 controls from Iceland and the UK. We identified 21 novel sequence variants, of which 13 are rare, under either additive or recessive models. Of special interest are a missense variant in LOXHD1 (MAF = 1.96%) and a tandem duplication in FBF1 covering 4 exons (MAF = 0.22%) associating with ARHI (OR = 3.7 for homozygotes, P = 1.7 × 10−22 and OR = 4.2 for heterozygotes, P = 5.7 × 10−27, respectively). We constructed an ARHI genetic risk score (GRS) using common variants and showed that a common variant GRS can identify individuals at risk comparable to carriers of rare high penetrance variants. Furthermore, we found that ARHI and tinnitus share genetic causes. This study sheds a new light on the genetic architecture of ARHI, through several rare variants in both Mendelian deafness genes and genes not previously linked to hearing., Erna Ivarsdottir et al. report a genome-wide association meta-analysis for age-related hearing loss in the Icelandic and UK populations. They identify 21 novel variants, 13 of which are rare, and reveal a genetic correlation between age-related hearing loss and tinnitus.

The success of genome-wide association studies (GWAS) in identifying common, low-penetrance variant-cancer associations for the past decade is undisputed. However, discovering additional high-penetrance cancer mutations in unknown cancer predisposing genes requires detection of variant-cancer association of ultra-rare coding variants. Consequently, large-scale next-generation sequence data with associated phenotype information are needed. Here, we used genotype data on 166,281 Icelanders, of which, 49,708 were whole-genome sequenced and 408,595 individuals from the UK Biobank, of which, 41,147 were whole-exome sequenced, to test for association between loss-of-function burden in autosomal genes and basal cell carcinoma (BCC), the most common cancer in Caucasians. A total of 25,205 BCC cases and 683,058 controls were tested. Rare germline loss-of-function variants in PTPN14 conferred substantial risks of BCC (OR, 8.0; P = 1.9 × 10−12), with a quarter of carriers getting BCC before age 70 and over half in their lifetime. Furthermore, common variants at the PTPN14 locus were associated with BCC, suggesting PTPN14 as a new, high-impact BCC predisposition gene. A follow-up investigation of 24 cancers and three benign tumor types showed that PTPN14 loss-of-function variants are associated with high risk of cervical cancer (OR, 12.7, P = 1.6 × 10−4) and low age at diagnosis. Our findings, using power-increasing methods with high-quality rare variant genotypes, highlight future prospects for new discoveries on carcinogenesis. Significance: This study identifies the tumor-suppressor gene PTPN14 as a high-impact BCC predisposition gene and indicates that inactivation of PTPN14 by germline sequence variants may also lead to increased risk of cervical cancer.

A set of Fortran subroutines for reverse mode algorithmic (or automatic) differentiation of the basic linear algebra subprograms (BLAS) is presented. This is preceded by a description of the mathematical tools used to obtain the formulae of these derivatives, with emphasis on special matrices supported by the BLAS: triangular, symmetric, and band. All single and double precision BLAS derivatives have been implemented, together with the Cholesky factorization from Linear Algebra Package (LAPACK). The subroutines are written in Fortran 2003 with a Fortran 77 interface to allow use from C and C++, as well as dynamic languages such as R, Python, Matlab, and Octave. The subroutines are all implemented by calling BLAS, thereby attaining fast runtime. Timing results show derivative runtimes that are about twice those of the corresponding BLAS, in line with theory. The emphasis is on reverse mode because it is more important for the main application that we have in mind, numerical optimization. Two examples are presented, one dealing with the least squares modeling of groundwater, and the other dealing with the maximum likelihood estimation of the parameters of a vector autoregressive time series. The article contains comprehensive tables of formulae for the BLAS derivatives as well as for several non-BLAS matrix operations commonly used in optimization.

We describe the analysis of whole genome sequences (WGS) of 150,119 individuals from the UK biobank (UKB). This constitutes a set of high quality variants, including 585,040,410 SNPs, representing 7.0% of all possible human SNPs, and 58,707,036 indels. The large set of variants allows us to characterize selection based on sequence variation within a population through a Depletion Rank (DR) score for windows along the genome. DR analysis shows that coding exons represent a small fraction of regions in the genome subject to strong sequence conservation. We define three cohorts within the UKB, a large British Irish cohort (XBI) and smaller African (XAF) and South Asian (XSA) cohorts. A haplotype reference panel is provided that allows reliable imputation of most variants carried by three or more sequenced individuals. We identified 895,055 structural variants and 2,536,688 microsatellites, groups of variants typically excluded from large scale WGS studies. Using this formidable new resource, we provide several examples of trait associations for rare variants with large effects not found previously through studies based on exome sequencing and/or imputation.

The spread of SARS-CoV-2 is dependent on several factors, both biological and behavioral. The effectiveness of various non-pharmaceutical interventions can largely be attributed to changes in human behavior, but quantifying this effect remains challenging. Reconstructing the transmission tree of the third wave of SARS-CoV-2 infections in Iceland using contact tracing and viral sequence data from 2522 cases enables us to compare the infectiousness of distinct groups of persons directly. We find that people diagnosed outside of quarantine are 89% more infectious than those diagnosed while in quarantine, and infectiousness decreases as a function of the time spent in quarantine. Furthermore, we find that people of working age, 16-66 years old, are 47% more infectious than those outside that age range. Lastly, the transmission tree enables us to model the effect that given population prevalence of vaccination would have had on the third wave had they been administered before that time using several different strategies. We find that vaccinating in order of ascending age or uniformly at random would have prevented more infections per vaccination than vaccinating in order of descending age.

A pressing concern in the SARS-CoV-2 epidemic and other viral outbreaks, is the extent to which the containment measures are halting the viral spread. A straightforward way to assess this is to tally the active cases and the recovered ones throughout the epidemic. Here, we show how epidemic control can be assessed with molecular information during a well characterized epidemic in Iceland. We demonstrate how the viral concentration decreased in those newly diagnosed as the epidemic transitioned from exponential growth phase to containment phase. The viral concentration in the cases identified in population screening decreased faster than in those symptomatic and considered at high risk and that were targeted by the healthcare system. The viral concentration persists in recovering individuals as we found that half of the cases are still positive after two weeks. We demonstrate that accumulation of mutations in SARS-CoV-2 genome can be exploited to track the rate of new viral generations throughout the different phases of the epidemic, where the accumulation of mutations decreases as the transmission rate decreases in the containment phase. Overall, the molecular signatures of SARS-CoV-2 infections contain valuable epidemiological information that can be used to assess the effectiveness of containment measures., The concentration of SARS-CoV-2 changes during an individual’s infection, and mutations accumulate as viruses are transmitted between people. Here, the authors use data from Iceland to demonstrate how this information can be exploited at the population-level to determine the phase of the epidemic.

Publisher's version (útgefin grein)., Analysis of sequence diversity in the human genome is fundamental for genetic studies. Structural variants (SVs) are frequently omitted in sequence analysis studies, although each has a relatively large impact on the genome. Here, we present GraphTyper2, which uses pangenome graphs to genotype SVs and small variants using short-reads. Comparison to the syndip benchmark dataset shows that our SV genotyping is sensitive and variant segregation in families demonstrates the accuracy of our approach. We demonstrate that incorporating public assembly data into our pipeline greatly improves sensitivity, particularly for large insertions. We validate 6,812 SVs on average per genome using long-read data of 41 Icelanders. We show that GraphTyper2 can simultaneously genotype tens of thousands of whole-genomes by characterizing 60 million small variants and half a million SVs in 49,962 Icelanders, including 80 thousand SVs with high-confidence., We are grateful to our colleagues from deCODE genetics / Amgen Inc. for their contributions. We also wish to thank all research participants who provided a biological sample to deCODE genetics.

The plasma proteome can help bridge the gap between the genome and diseases. Here we describe genome-wide association studies (GWASs) of plasma protein levels measured with 4,907 aptamers in 35,559 Icelanders. We found 18,084 associations between sequence variants and levels of proteins in plasma (protein quantitative trait loci; pQTL), of which 19% were with rare variants (minor allele frequency (MAF)

Background: Loss-of-function mutations in the LDL (low-density lipoprotein) receptor gene ( LDLR ) cause elevated levels of LDL cholesterol and premature cardiovascular disease. To date, a gain-of-function mutation in LDLR with a large effect on LDL cholesterol levels has not been described. Here, we searched for sequence variants in LDLR that have a large effect on LDL cholesterol levels. Methods: We analyzed whole-genome sequencing data from 43 202 Icelanders. Single-nucleotide polymorphisms and structural variants including deletions, insertions, and duplications were genotyped using whole-genome sequencing-based data. LDL cholesterol associations were carried out in a sample of >100 000 Icelanders with genetic information (imputed or whole-genome sequencing). Molecular analyses were performed using RNA sequencing and protein expression assays in Epstein-Barr virus-transformed lymphocytes. Results: We discovered a 2.5-kb deletion (del2.5) overlapping the 3′ untranslated region of LDLR in 7 heterozygous carriers from a single family. Mean level of LDL cholesterol was 74% lower in del2.5 carriers than in 101 851 noncarriers, a difference of 2.48 mmol/L (96 mg/dL; P =8.4×10 − 8 ). Del2.5 results in production of an alternative mRNA isoform with a truncated 3′ untranslated region. The truncation leads to a loss of target sites for microRNAs known to repress translation of LDLR . In Epstein-Barr virus-transformed lymphocytes derived from del2.5 carriers, expression of alternative mRNA isoform was 1.84-fold higher than the wild-type isoform ( P =0.0013), and there was 1.79-fold higher surface expression of the LDL receptor than in noncarriers ( P =0.0086). We did not find a highly penetrant detrimental impact of lifelong very low levels of LDL cholesterol due to del2.5 on health of the carriers. Conclusions: Del2.5 is the first reported gain-of-function mutation in LDLR causing a large reduction in LDL cholesterol. These data point to a role for alternative polyadenylation of LDLR mRNA as a potent regulator of LDL receptor expression in humans.

Platelets play an important role in hemostasis and other aspects of vascular biology. We conducted a meta-analysis of platelet count GWAS using data on 536,974 Europeans and identified 577 independent associations. To search for mechanisms through which these variants affect platelets, we applied cis-expression quantitative trait locus, DEPICT and IPA analyses and assessed genetic sharing between platelet count and various traits using polygenic risk scoring. We found genetic sharing between platelet count and counts of other blood cells (except red blood cells), in addition to several other quantitative traits, including markers of cardiovascular, liver and kidney functions, height, and weight. Platelet count polygenic risk score was predictive of myeloproliferative neoplasms, rheumatoid arthritis, ankylosing spondylitis, hypertension, and benign prostate hyperplasia. Taken together, these results advance understanding of diverse aspects of platelet biology and how they affect biological processes in health and disease., Evgenia Mikaelsdottir et al. report a study of variants associated with platelet count among European individuals where they identify 577 associations. They also report a genetic overlap between platelet count and human diseases, including myeloproliferative neoplasms, rheumatoid arthritis, and hypertension, as well as a genetic overlap between platelet count and various physiological markers.

Background Little is known about the nature and durability of the humoral immune response to infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Methods We measured antibodies in serum samples from 30,576 persons in Iceland, using six assays (including two pan-immunoglobulin [pan-Ig] assays), and we determined that the appropriate measure of seropositivity was a positive result with both pan-Ig assays. We tested 2102 samples collected from 1237 persons up to 4 months after diagnosis by a quantitative polymerase-chain-reaction (qPCR) assay. We measured antibodies in 4222 quarantined persons who had been exposed to SARS-CoV-2 and in 23,452 persons not known to have been exposed. Results Of the 1797 persons who had recovered from SARS-CoV-2 infection, 1107 of the 1215 who were tested (91.1%) were seropositive; antiviral antibody titers assayed by two pan-Ig assays increased during 2 months after diagnosis by qPCR and remained on a plateau for the remainder of the study. Of quarantined persons, 2.3% were seropositive; of those with unknown exposure, 0.3% were positive. We estimate that 0.9% of Icelanders were infected with SARS-CoV-2 and that the infection was fatal in 0.3%. We also estimate that 56% of all SARS-CoV-2 infections in Iceland had been diagnosed with qPCR, 14% had occurred in quarantined persons who had not been tested with qPCR (or who had not received a positive result, if tested), and 30% had occurred in persons outside quarantine and not tested with qPCR. Conclusions Our results indicate that antiviral antibodies against SARS-CoV-2 did not decline within 4 months after diagnosis. We estimate that the risk of death from infection was 0.3% and that 44% of persons infected with SARS-CoV-2 in Iceland were not diagnosed by qPCR.

Background During the current worldwide pandemic, coronavirus disease 2019 (Covid-19) was first diagnosed in Iceland at the end of February. However, data are limited on how SARS-CoV-2, the virus that causes Covid-19, enters and spreads in a population. Methods We targeted testing to persons living in Iceland who were at high risk for infection (mainly those who were symptomatic, had recently traveled to high-risk countries, or had contact with infected persons). We also carried out population screening using two strategies: issuing an open invitation to 10,797 persons and sending random invitations to 2283 persons. We sequenced SARS-CoV-2 from 643 samples. Results As of April 4, a total of 1221 of 9199 persons (13.3%) who were recruited for targeted testing had positive results for infection with SARS-CoV-2. Of those tested in the general population, 87 (0.8%) in the open-invitation screening and 13 (0.6%) in the random-population screening tested positive for the virus. In total, 6% of the population was screened. Most persons in the targeted-testing group who received positive tests early in the study had recently traveled internationally, in contrast to those who tested positive later in the study. Children under 10 years of age were less likely to receive a positive result than were persons 10 years of age or older, with percentages of 6.7% and 13.7%, respectively, for targeted testing; in the population screening, no child under 10 years of age had a positive result, as compared with 0.8% of those 10 years of age or older. Fewer females than males received positive results both in targeted testing (11.0% vs. 16.7%) and in population screening (0.6% vs. 0.9%). The haplotypes of the sequenced SARS-CoV-2 viruses were diverse and changed over time. The percentage of infected participants that was determined through population screening remained stable for the 20-day duration of screening. Conclusions In a population-based study in Iceland, children under 10 years of age and females had a lower incidence of SARS-CoV-2 infection than adolescents or adults and males. The proportion of infected persons identified through population screening did not change substantially during the screening period, which was consistent with a beneficial effect of containment efforts. (Funded by deCODE Genetics–Amgen.)

BACKGROUNDLimited data exist on how SARS-CoV-2 enters and spreads in the general population.METHODSWe used two strategies for SARS-CoV-2 testing: targeted testing of high-risk individuals (n=4,551) and a population screening (n=5,502). We sequenced SARS-CoV-2 from 340 individuals.RESULTSOn March 22 2020, 528 had tested positive for SARS-CoV-2 in the targeted testing (11.6%) and 50 in the population screening (0.9%); approximately 0.2% of the Icelandic population. Large fractions of positives had travelled outside Iceland (38.4% and 34.0%). Fewer under 10 years old were positive than those older: 2.8% vs. 12.3% for targeted testing (P=1.6e-9) and 0.0% vs. 1.0% for population screening (P=0.031). Fewer females were positive in the targeted testing than males (9.5% vs. 14.6%, P=6.8e-9). SARS-CoV-2 came from eight clades, seven A clades and one B clade. The clade composition differed between the testing groups and changed with time. In the early targeted testing, 65.0% of clades were A2a1 and A2a2 derived from Italian and Austrian skiing areas, but in the later targeted testing went down to 30.6% and were overtaken by A1a and A2a, the most common clades in the population screening.CONCLUSIONSARS-CoV-2 has spread widely in Iceland outside of the high-risk groups. Several strains cause these infections and their relative contribution changed rapidly. Children and females are less vulnerable than adults and males. To contain the pandemic we must increase the scope of the testing.

Publisher's version (útgefin grein), Pelvic organ prolapse (POP) is a downward descent of one or more of the pelvic organs, resulting in a protrusion of the vaginal wall and/or uterus. We performed a genome-wide association study of POP using data from Iceland and the UK Biobank, a total of 15,010 cases with hospital-based diagnosis code and 340,734 female controls, and found eight sequence variants at seven loci associating with POP (P 5%) and one with minor allele frequency of 4.87%. Some of the variants associating with POP also associated with traits of similar pathophysiology. Of these, rs3820282, which may alter the estrogen-based regulation of WNT4, also associates with leiomyoma of uterus, gestational duration and endometriosis. Rs3791675 at EFEMP1, a gene involved in connective tissue homeostasis, also associates with hernias and carpal tunnel syndrome. Our results highlight the role of connective tissue metabolism and estrogen exposure in the etiology of POP., This research has been conducted using the UK Biobank Resource under Application Number 24898 and 24711. We thank the individuals who participated in the study and whose contribution made this work possible. Folkert Asselbergs is supported by UCL Hospitals NIHR Biomedical Research Centre.

Autoimmune thyroid disease is the most common autoimmune disease and is highly heritable1. Here, by using a genome-wide association study of 30,234 cases and 725,172 controls from Iceland and the UK Biobank, we find 99 sequence variants at 93 loci, of which 84 variants are previously unreported2–7. A low-frequency (1.36%) intronic variant in FLT3 (rs76428106-C) has the largest effect on risk of autoimmune thyroid disease (odds ratio (OR) = 1.46, P = 2.37 × 10−24). rs76428106-C is also associated with systemic lupus erythematosus (OR = 1.90, P = 6.46 × 10−4), rheumatoid factor and/or anti-CCP-positive rheumatoid arthritis (OR = 1.41, P = 4.31 × 10−4) and coeliac disease (OR = 1.62, P = 1.20 × 10−4). FLT3 encodes fms-related tyrosine kinase 3, a receptor that regulates haematopoietic progenitor and dendritic cells. RNA sequencing revealed that rs76428106-C generates a cryptic splice site, which introduces a stop codon in 30% of transcripts that are predicted to encode a truncated protein, which lacks its tyrosine kinase domains. Each copy of rs76428106-C doubles the plasma levels of the FTL3 ligand. Activating somatic mutations in FLT3 are associated with acute myeloid leukaemia8 with a poor prognosis and rs76428106-C also predisposes individuals to acute myeloid leukaemia (OR = 1.90, P = 5.40 × 10−3). Thus, a predicted loss-of-function germline mutation in FLT3 causes a reduction in full-length FLT3, with a compensatory increase in the levels of its ligand and an increased disease risk, similar to that of a gain-of-function mutation. A predicted loss-of-function germline mutation in FLT3 causes a reduction in full-length FLT3, with a compensatory increase in the levels of FLT3 ligand, leading to increased risk of autoimmune thyroid disease.

Most sequence variants identified hitherto in genome-wide association studies (GWAS) of atrial fibrillation are common, non-coding variants associated with risk through unknown mechanisms. We performed a meta-analysis of GWAS of atrial fibrillation among 29,502 cases and 767,760 controls from Iceland and the UK Biobank with follow-up in samples from Norway and the US, focusing on low-frequency coding and splice variants aiming to identify causal genes. We observe associations with one missense (OR = 1.20) and one splice-donor variant (OR = 1.50) in RPL3L, the first ribosomal gene implicated in atrial fibrillation to our knowledge. Analysis of 167 RNA samples from the right atrium reveals that the splice-donor variant in RPL3L results in exon skipping. We also observe an association with a missense variant in MYZAP (OR = 1.38), encoding a component of the intercalated discs of cardiomyocytes. Both discoveries emphasize the close relationship between the mechanical and electrical function of the heart.

A fundamental requirement for genetic studies is an accurate determination of sequence variation. While human genome sequence diversity is increasingly well characterized, there is a need for efficient ways to use this knowledge in sequence analysis. Here we present Graphtyper, a publicly available novel algorithm and software for discovering and genotyping sequence variants. Graphtyper realigns short-read sequence data to a pangenome, a variation-aware graph structure that encodes sequence variation within a population by representing possible haplotypes as graph paths. Our results show that Graphtyper is fast, highly scalable, and provides sensitive and accurate genotype calls. Graphtyper genotyped 89.4 million sequence variants in the whole genomes of 28,075 Icelanders using less than 100,000 CPU days, including detailed genotyping of six human leukocyte antigen (HLA) genes. We show that Graphtyper is a valuable tool in characterizing sequence variation in both small and population-scale sequencing studies.

Imprinting is the preferential expression of one parental allele over the other. It is controlled primarily through differential methylation of cytosine at CpG dinucleotides. Here we combine 285 methylomes and 11,617 transcriptomes from peripheral blood samples with parent-of-origin phased haplotypes, to produce a new map of imprinted methylation and gene expression patterns across the human genome. We demonstrate how imprinted methylation is a continuous rather than a binary characteristic. We describe at high resolution the parent-of-origin methylation pattern at the 15q11.2 Prader-Willi/Angelman syndrome locus, with nearly confluent stochastic paternal methylation punctuated by 'spikes' of maternal methylation. We find examples of polymorphic imprinted methylation unrelated (at VTRNA2-1 and PARD6G) or related (at CHRNE) to nearby SNP genotypes. We observe RNA isoform-specific imprinted expression patterns suggestive of a methylation-sensitive transcriptional elongation block. Finally, we gain new insights into parent-of-origin-specific effects on phenotypes at the DLK1/MEG3 and GNAS loci.

We describe a workflow for preprocessing of single-cell RNA-sequencing data that balances efficiency and accuracy. Our workflow is based on the kallisto and bustools programs, and is near optimal in speed with a constant memory requirement providing scalability for arbitrarily large datasets. The workflow is modular, and we demonstrate its flexibility by showing how it can be used for RNA velocity analyses.

Analysis of single-cell RNA-seq data begins with pre-processing of sequencing reads to generate count matrices. We investigate algorithm choices for the challenges of pre-processing, and describe a workflow that balances efficiency and accuracy. Our workflow is based on the kallisto (https://pachterlab.github.io/kallisto/) and bustools (https://bustools.github.io/) programs, and is near-optimal in speed and memory. The workflow is modular, and we demonstrate its flexibility by showing how it can be used for RNA velocity analyses. Documentation and tutorials for using the kallisto | bus workflow are available at https://www.kallistobus.tools/.

Single-cell RNA-seq makes it possible to characterize the transcriptomes of cell types across different conditions and to identify their transcriptional signatures via differential analysis. Our method detects changes in transcript dynamics and in overall gene abundance in large numbers of cells to determine differential expression. When applied to transcript compatibility counts obtained via pseudoalignment, our approach provides a quantification-free analysis of 3' single-cell RNA-seq that can identify previously undetectable marker genes.

Tracking past population fluctuations can give insight into current levels of genetic variation present within species. Analysing population dynamics over larger timescales can be aligned to known climatic changes to determine the response of species to varying environments. Here, we applied the Pairwise Sequentially Markovian Coalescent (psmc) model to infer past population dynamics of three widespread grouse species; black grouse, willow grouse and rock ptarmigan. This allowed the tracking of the effective population size (Ne ) of all three species beyond 1 Mya, revealing that (i) early Pleistocene cooling (~2.5 Mya) caused an increase in the willow grouse and rock ptarmigan populations, (ii) the mid-Brunhes event (~430 kya) and following climatic oscillations decreased the Ne of willow grouse and rock ptarmigan, but increased the Ne of black grouse and (iii) all three species reacted differently to the last glacial maximum (LGM) - black grouse increased prior to it, rock ptarmigan experienced a severe bottleneck and willow grouse was maintained at large population size. We postulate that the varying psmc signal throughout the LGM depicts only the local history of the species. Nevertheless, the large population fluctuations in willow grouse and rock ptarmigan indicate that both species are opportunistic breeders while black grouse tracks the climatic changes more slowly and is maintained at lower Ne . Our results highlight the usefulness of the psmc approach in investigating species' reaction to climate change in the deep past, but also that caution should be taken in drawing general conclusions about the recent past.

MotivationGenome alignment of reads is the first step of most genome analysis workflows. In the case of RNA-Seq, transcriptome pseudoalignment of reads is a fast alternative to genome alignment, but the different “coordinate systems” of the genome and transcriptome have made it difficult to perform direct comparisons between the approaches.ResultsWe have developed tools for converting genome alignments to transcriptome pseudoalignments, and conversely, for projecting transcriptome pseudoalignments to genome alignments. Using these tools, we performed a direct comparison of genome alignment with transcriptome pseudoalignment. We find that both approaches produce similar quantifications. This means that for many applications genome alignment and transcriptome pseudoalignment are interchangeable.Availability and Implementationbam2tcc is a C++14 software for converting alignments in SAM/BAM format to transcript compatibility counts (TCCs) and is available at https://github.com/pachterlab/bam2tcc. kallisto genomebam is a user option of kallisto that outputs a sorted BAM file in genome coordinates as part of transcriptome pseudoalignment. The feature has been released with kallisto v0.44.0, and is available at https://pachterlab.github.io/kallisto/.Supplementary MaterialN/AContactLior Pachter (lpachter@caltech.edu)

Single-cell RNA-Seq makes it possible to characterize the transcriptomes of cell types and identify their transcriptional signatures via differential analysis. We present a fast and accurate method for discriminating cell types that takes advantage of the large numbers of cells that are assayed. When applied to transcript compatibility counts obtained via pseudoalignment, our approach provides a quantification-free analysis of 3’ single-cell RNA-Seq that can identify previously undetectable marker genes.

We performed a meta-analysis of genome-wide association studies on atrial fibrillation (AF) among 14,710 cases and 373,897 controls from Iceland and 14,792 cases and 393,863 controls from the UK Biobank, focusing on low frequency coding and splice mutations, with follow-up in samples from Norway and the US. We observed associations with two missense (OR=1.19 for both) and one splice-donor mutation (OR=1.52) in RPL3L, encoding a ribosomal protein primarily expressed in skeletal muscle and heart. Analysis of 167 RNA samples from the right atrium revealed that the splice donor mutation in RPL3L results in exon skipping. AF is the first disease associated with RPL3L and RPL3L is the first ribosomal gene implicated in AF. This finding is consistent with tissue specialization of ribosomal function. We also found an association with a missense variant in MYZAP (OR=1.37), encoding a component of the intercalated discs of cardiomyocytes, the organelle harbouring most of the mutated proteins involved in arrhythmogenic right ventricular cardiomyopathy. Both discoveries emphasize the close relationship between the mechanical and electrical function of the heart.

RNA sequencing in cancer cells is a powerful technique to detect chromosomal rearrangements, allowing for de novo discovery of actively expressed fusion genes. Here we focus on the problem of detecting gene fusions from raw sequencing data, assembling the reads to define fusion transcripts and their associated breakpoints, and quantifying their abundances. Building on the pseudoalignment idea that simplifies and accelerates transcript quantification, we introduce a novel approach to fusion detection based on inspecting paired reads that cannot be pseudoaligned due to conflicting matches. The method and software, called pizzly, filters false positives, assembles new transcripts from the fusion reads, and reports candidate fusions. With pizzly, fusion detection from raw RNA-Seq reads can be performed in a matter of minutes, making the program suitable for the analysis of large cancer gene expression databases and for clinical use. pizzly is available at https://github.com/pmelsted/pizzly

A fundamental requisite for genetic studies is an accurate determination of sequence variation. While human genome sequence diversity is increasingly well characterized, there is a need for efficient ways to utilize this knowledge in sequence analysis. Here we present Graphtyper, a publicly available novel algorithm and software for discovering and genotyping sequence variants. Graphtyper realigns short-read sequence data to a pangenome, a variation-aware graph structure that encodes sequence variation within a population by representing possible haplotypes as graph paths. Our results show that Graphtyper is fast, highly scalable, and provides sensitive and accurate genotype calls. Graphtyper genotyped 89.4 million sequence variants in whole-genomes of 28,075 Icelanders using less than 100,000 CPU days, including detailed genotyping of six human leukocyte antigen (HLA) genes. We show that Graphtyper is a valuable tool in characterizing sequence variation in population-scale sequencing studies.

Increased emphasis on reproducibility of published research in the last few years has led to the large-scale archiving of sequencing data. While this data can, in theory, be used to reproduce results in papers, it is difficult to use in practice. We introduce a series of tools for processing and analyzing RNA-Seq data in the Sequence Read Archive, that together have allowed us to build an easily extendable resource for analysis of data underlying published papers. Our system makes the exploration of data easily accessible and usable without technical expertise. Our database and associated tools can be accessed at The Lair: http://pachterlab.github.io/lair., National Institutes of Health grants R01 HG006129, R01 DK094699 and R01 HG008164.

We explore connections between metagenomic read assignment and the quantification of transcripts from RNA-Seq data. In particular, we show that the recent idea of pseudoalignment introduced in the RNA-Seq context is suitable in the metagenomics setting. When coupled with the Expectation-Maximization (EM) algorithm, reads can be assigned far more accurately and quickly than is currently possible with state of the art software., Replaced accidentally duplicated figure with correct version; fixed some issues with figure generation and labeling; fixed problem with some missing genomes from database; added link to GitHub repo containing analysis code; included assessment of aggregate sensitivity and precision; clarified assessment metrics used

Genomes usually contain some non-repetitive sequences that are missing from the reference genome and occur only in a population subset. Such non-repetitive, non-reference (NRNR) sequences have remained largely unexplored in terms of their characterization and downstream analyses. Here we describe 3,791 breakpoint-resolved NRNR sequence variants called using PopIns from whole-genome sequence data of 15,219 Icelanders. We found that over 95% of the 244 NRNR sequences that are 200 bp or longer are present in chimpanzees, indicating that they are ancestral. Furthermore, 149 variant loci are in linkage disequilibrium (r2 > 0.8) with a genome-wide association study (GWAS) catalog marker, suggesting disease relevance. Additionally, we report an association (P = 3.8 × 10-8, odds ratio (OR) = 0.92) with myocardial infarction (23,360 cases, 300,771 controls) for a 766-bp NRNR sequence variant. Our results underline the importance of including variation of all complexity levels when searching for variants that associate with disease.

Nat. Biotechnol. 34, 525–527 (2016); published online 4 April 2016; corrected after print 27 July 2016 In the version of this article initially published, in the HTML version only, the equation “αtN > 0.01” was written as “αtN > 0.01.” In addition, in the Figure 1 legend, the formatting of thenodes was incorrect (v_1, etc.

We describe sleuth (http://pachterlab.github.io/sleuth), a method for the differential analysis of gene expression data that utilizes bootstrapping in conjunction with response error linear modeling to decouple biological variance from inferential variance. sleuth is implemented in an interactive shiny app that utilizes kallisto quantifications and bootstraps for fast and accurate analysis of data from RNA-seq experiments.

We present kallisto, an RNA-seq quantification program that is two orders of magnitude faster than previous approaches and achieves similar accuracy. Kallisto pseudoaligns reads to a reference, producing a list of transcripts that are compatible with each read while avoiding alignment of individual bases. We use kallisto to analyze 30 million unaligned paired-end RNA-seq reads in

We study the the following question in Random Graphs. We are given two disjoint sets L,R with |L| = n and |R| = m. We construct a random graph G by allowing each x∈L to choose d random neighbours in R. The question discussed is as to the size μ(G) of the largest matching in G. When considered in the context of Cuckoo Hashing, one key question is as to when is μ(G) = n whp? We answer this question exactly when d is at least three. © 2012 Wiley Periodicals, Inc. Random Struct. Alg., 2012 © 2012 Wiley Periodicals, Inc.

Given a massive collection of sequences, it is infeasible to perform pairwise alignment for basic tasks like sequence clustering and search. To address this problem, we demonstrate that the MinHash technique, first applied to clustering web pages, can be applied to biological sequences with similar effect, and extend this idea to include biologically relevant distance and significance measures. Our new tool, Mash, uses MinHash locality-sensitive hashing to reduce large sequences to a representative sketch and rapidly estimate pairwise distances between genomes or metagenomes. Using Mash, we explored several use cases, including a 5,000-fold size reduction and clustering of all ~55,000 NCBI RefSeq genomes in 46 CPU hours. The resulting 93 MB sketch database includes all RefSeq genomes, effectively delineates known species boundaries, reconstructs approximate phylogenies, and can be searched in seconds using assembled genomes or raw sequencing runs from Illumina, Pacific Biosciences, and Oxford Nanopore. For metagenomics, Mash scales to thousands of samples and can replicate Human Microbiome Project and Global Ocean Survey results in a fraction of the time. Other potential applications include any problem where an approximate, global sequence distance is acceptable, e.g. to triage and cluster sequence data, assign species labels to unknown genomes, quickly identify mis-tracked samples, and search massive genomic databases. In addition, the Mash distance metric is based on simple set intersections, which are compatible with homomorphic encryption schemes. To facilitate integration with other software, Mash is implemented as a lightweight C++ toolkit and freely released under a BSD license at https://github.com/marbl/mash.