Search

Long-read sequencing (LRS) promises to improve the characterization of structural variants (SVs). We generated LRS data from 3,622 Icelanders and identified a median of 22,636 SVs per individual (a median of 13,353 insertions and 9,474 deletions). We discovered a set of 133,886 reliably genotyped SV alleles and imputed them into 166,281 individuals to explore their effects on diseases and other traits. We discovered an association of a rare deletion in PCSK9 with lower low-density lipoprotein (LDL) cholesterol levels, compared to the population average. We also discovered an association of a multiallelic SV in ACAN with height; we found 11 alleles that differed in the number of a 57-bp-motif repeat and observed a linear relationship between the number of repeats carried and height. These results show that SVs can be accurately characterized at the population scale using LRS data in a genome-wide non-targeted approach and demonstrate how SVs impact phenotypes.

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.

Thousands of genomic structural variants (SVs) segregate in the human population and can impact phenotypic traits and diseases. Their identification in whole-genome sequence data of large cohorts is a major computational challenge. Most current approaches identify SVs in single genomes and afterwards merge the identified variants into a joint call set across many genomes. We describe the approach PopDel, which directly identifies deletions of about 500 to at least 10,000 bp in length in data of many genomes jointly, eliminating the need for subsequent variant merging. PopDel scales to tens of thousands of genomes as we demonstrate in evaluations on up to 49,962 genomes. We show that PopDel reliably reports common, rare and de novo deletions. On genomes with available high-confidence reference call sets PopDel shows excellent recall and precision. Genotype inheritance patterns in up to 6794 trios indicate that genotypes predicted by PopDel are more reliable than those of previous SV callers. Furthermore, PopDel’s running time is competitive with the fastest tested previous tools. The demonstrated scalability and accuracy of PopDel enables routine scans for deletions in large-scale sequencing studies., Identifying structural variants (SVs) from whole genome sequence data has been a significant bioinformatic challenge. Here, the authors describe PopDel, which uses a joint SV detection approach to reliably and efficiently identify 500-10,000 bp deletions across large population cohorts.

Despite the important role that monozygotic twins have played in genetics research, little is known about their genomic differences. Here we show that monozygotic twins differ on average by 5.2 early developmental mutations and that approximately 15% of monozygotic twins have a substantial number of these early developmental mutations specific to one of them. Using the parents and offspring of twins, we identified pre-twinning mutations. We observed instances where a twin was formed from a single cell lineage in the pre-twinning cell mass and instances where a twin was formed from several cell lineages. CpG>TpG mutations increased in frequency with embryonic development, coinciding with an increase in DNA methylation. Our results indicate that allocations of cells during development shapes genomic differences between monozygotic twins.

Human evolutionary history is rich with the interbreeding of divergent populations. Most humans outside of Africa trace about 2% of their genomes to admixture from Neanderthals, which occurred 50–60 thousand years ago1. Here we examine the effect of this event using 14.4 million putative archaic chromosome fragments that were detected in fully phased whole-genome sequences from 27,566 Icelanders, corresponding to a range of 56,388–112,709 unique archaic fragments that cover 38.0–48.2% of the callable genome. On the basis of the similarity with known archaic genomes, we assign 84.5% of fragments to an Altai or Vindija Neanderthal origin and 3.3% to Denisovan origin; 12.2% of fragments are of unknown origin. We find that Icelanders have more Denisovan-like fragments than expected through incomplete lineage sorting. This is best explained by Denisovan gene flow, either into ancestors of the introgressing Neanderthals or directly into humans. A within-individual, paired comparison of archaic fragments with syntenic non-archaic fragments revealed that, although the overall rate of mutation was similar in humans and Neanderthals during the 500 thousand years that their lineages were separate, there were differences in the relative frequencies of mutation types—perhaps due to different generation intervals for males and females. Finally, we assessed 271 phenotypes, report 5 associations driven by variants in archaic fragments and show that the majority of previously reported associations are better explained by non-archaic variants. Analysis of Icelandic genomes reveals chromosome fragments of Neanderthal and Denisovan origin, the latter of which occurred through Denisovan gene flow either into ancestors of the Neanderthals or directly into humans.

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.

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)., Bone area is one measure of bone size that is easily derived from dual-energy X-ray absorptiometry (DXA) scans. In a GWA study of DXA bone area of the hip and lumbar spine (N ≥ 28,954), we find thirteen independent association signals at twelve loci that replicate in samples of European and East Asian descent (N = 13,608 – 21,277). Eight DXA area loci associate with osteoarthritis, including rs143384 in GDF5 and a missense variant in COL11A1 (rs3753841). The strongest DXA area association is with rs11614913[T] in the microRNA MIR196A2 gene that associates with lumbar spine area (P = 2.3 × 10−42, β = −0.090) and confers risk of hip fracture (P = 1.0 × 10−8, OR = 1.11). We demonstrate that the risk allele is less efficient in repressing miR-196a-5p target genes. We also show that the DXA area measure contributes to the risk of hip fracture independent of bone density., We thank all the study subjects for their valuable participation, the staff from all studies and the participating physicians. A part of this research has been conducted using the UK Biobank Resource under Application Number 23359. arcOGEN (http://www.arcogen.org.uk/) was funded by a special purpose grant from Arthritis Research UK (grant 18030).

De novo mutations (DNMs) cause a large proportion of severe rare diseases of childhood. DNMs that occur early may result in mosaicism of both somatic and germ cells. Such early mutations can cause recurrence of disease. We scanned 1,007 sibling pairs from 251 families and identified 878 DNMs shared by siblings (ssDNMs) at 448 genomic sites. We estimated DNM recurrence probability based on parental mosaicism, sharing of DNMs among siblings, parent-of-origin, mutation type and genomic position. We detected 57.2% of ssDNMs in the parental blood. The recurrence probability of a DNM decreases by 2.27% per year for paternal DNMs and 1.78% per year for maternal DNMs. Maternal ssDNMs are more likely to be T>C mutations than paternal ssDNMs, and less likely to be C>T mutations. Depending on the properties of the DNM, the recurrence probability ranges from 0.011% to 28.5%. We have launched an online calculator to allow estimation of DNM recurrence probability for research purposes.

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.

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.)

A genome is a mosaic of chromosome fragments from ancestors who existed some arbitrary number of generations earlier. Here, we reconstruct the genome of Hans Jonatan (HJ), born in the Caribbean in 1784 to an enslaved African mother and European father. HJ migrated to Iceland in 1802, married and had two children. We genotyped 182 of his 788 descendants using single-nucleotide polymorphism (SNP) chips and whole-genome sequenced (WGS) 20 of them. Using these data, we reconstructed 38% of HJ's maternal genome and inferred that his mother was from the region spanned by Benin, Nigeria and Cameroon.

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.

The characterization of mutational processes that generate sequence diversity in the human genome is of paramount importance both to medical genetics and to evolutionary studies. To understand how the age and sex of transmitting parents affect de novo mutations, here we sequence 1,548 Icelanders, their parents, and, for a subset of 225, at least one child, to 35× genome-wide coverage. We find 108,778 de novo mutations, both single nucleotide polymorphisms and indels, and determine the parent of origin of 42,961. The number of de novo mutations from mothers increases by 0.37 per year of age (95% CI 0.32-0.43), a quarter of the 1.51 per year from fathers (95% CI 1.45-1.57). The number of clustered mutations increases faster with the mother's age than with the father's, and the genomic span of maternal de novo mutation clusters is greater than that of paternal ones. The types of de novo mutation from mothers change substantially with age, with a 0.26% (95% CI 0.19-0.33%) decrease in cytosine-phosphate-guanine to thymine-phosphate-guanine (CpG>TpG) de novo mutations and a 0.33% (95% CI 0.28-0.38%) increase in C>G de novo mutations per year, respectively. Remarkably, these age-related changes are not distributed uniformly across the genome. A striking example is a 20 megabase region on chromosome 8p, with a maternal C>G mutation rate that is up to 50-fold greater than the rest of the genome. The age-related accumulation of maternal non-crossover gene conversions also mostly occurs within these regions. Increased sequence diversity and linkage disequilibrium of C>G variants within regions affected by excess maternal mutations indicate that the underlying mutational process has persisted in humans for thousands of years. Moreover, the regional excess of C>G variation in humans is largely shared by chimpanzees, less by gorillas, and is almost absent from orangutans. This demonstrates that sequence diversity in humans results from evolving interactions between age, sex, mutation type, and genomic location.

Searching for novel sequence variants associated with cholesterol levels is of particular interest due to the causative role of non-HDL cholesterol levels in cardiovascular disease. Through whole-genome sequencing of 15,220 Icelanders and imputation of the variants identified, we discovered a rare missense variant in NR1H4 (R436H) associating with lower levels of total cholesterol (effect = −0.47 standard deviations or −0.55 mmol L−1, p = 4.21 × 10−10, N = 150,211). Importantly, NR1H4 R436H also associates with lower levels of non-HDL cholesterol and, consistent with this, protects against coronary artery disease. NR1H4 encodes FXR that regulates bile acid homeostasis, however, we do not detect a significant association between R436H and biological markers of liver function. Transcriptional profiling of hepatocytes carrying R436H shows that it is not a loss-of-function variant. Rather, we observe changes in gene expression compatible with effects on lipids. These findings highlight the role of FXR in regulation of cholesterol levels in humans. Aimee Deaton et al. identify a rare missense variant in the bile acid receptor gene NR1H4, which is associated with lower levels of total cholesterol in the Icelandic population. Hepatocytes expressing the missense variant showed altered expression of a small number of genes, with enrichment in lipid-related pathways.

Founder effects in modern populations The genomes of ancient humans can reveal patterns of early human migration (see the Perspective by Achilli et al. ). Iceland has a genetically distinct population, despite relatively recent settlement (∼1100 years ago). Ebenesersdóttir et al. examined the genomes of ancient Icelandic people, dating to near the colonization of Iceland, and compared them with modernday Icelandic populations. The ancient DNA revealed that the founders had Gaelic and Norse origins. Genetic drift since the initial settlement has left modern Icelanders with allele frequencies that are distinctive, although still skewed toward those of their Norse founders. Scheib et al. sequenced ancient genomes from the Channel Islands of California, USA, and Ontario, Canada. The ancient Ontario population was similar to other ancient North Americans, as well as to modern Algonquian-speaking Native Americans. In contrast, the California individuals were more like groups that now live in Mexico and South America. It appears that a genetic split and population isolation likely occurred during the Ice Age, but the peoples remixed at a later date. Science , this issue p. 1028 , p. 1024 ; see also p. 964

The original HTML version of this Article was updated shortly after publication to add links to the Peer Review file.In addition, affiliations 16 and 17 incorrectly read ‘School of Medicine Sydney, University of Notre Dame Australia, Sydney, WA, 6160, Australia’ and ‘St Vincent’s Clinical School, University of New South Wales Medicine, University of New South Wales, Sydney, NSW, 2052, Australia.’ This has now been corrected in both the PDF and HTML versions of the Article.

Background: Rare missense mutations in the gene encoding coatomer subunit alpha (COPA) have recently been shown to cause autoimmune interstitial lung, joint and kidney disease, also known as COPA syndrome, under a dominant mode of inheritance. Case presentation: Here we describe an Icelandic family with three affected individuals over two generations with a rare clinical presentation of lung and joint disease and a histological diagnosis of follicular bronchiolitis. We performed whole-genome sequencing (WGS) of the three affected as well as three unaffected members of the family, and searched for rare genotypes associated with disease using 30,067 sequenced Icelanders as a reference population. We assessed all coding and splicing variants, prioritizing variants in genes known to cause interstitial lung disease. We detected a heterozygous missense mutation, p.Glu241Lys, in the COPA gene, private to the affected family members. The mutation occurred de novo in the paternal germline of the index case and was absent from 30,067 Icelandic genomes and 141,353 individuals from the genome Aggregation Database (gnomAD). The mutation occurs within the conserved and functionally important WD40 domain of the COPA protein. Conclusions: This is the second report of the p.Glu241Lys mutation in COPA, indicating the recurrent nature of the mutation. The mutation was reported to co-segregate with COPA syndrome in a large family from the USA with five affected members, and classified as pathogenic. The two separate occurrences of the p.Glu241Lys mutation in cases and its absence from a large number of sequenced genomes confirms its role in the pathogenesis of the COPA syndrome. Keywords: COPA syndrome, Lung disease, Arthritis, Immune dysregulation, Case report

Motivation: Large-scale genotype datasets can help track the dispersal patterns of epidemiological outbreaks and predict the geographic origins of individuals. Such genetically-based geographic assignments also show a range of possible applications in forensics for profiling both victims and criminals, and in wildlife management, where poaching hotspot areas can be located. They, however, require fast and accurate statistical methods to handle the growing amount of genetic information made available from genotype arrays and next-generation sequencing technologies. Results: We introduce a novel statistical method for geopositioning individuals of unknown origin from genotypes. Our method is based on a geostatistical model trained with a dataset of georeferenced genotypes. Statistical inference under this model can be implemented within the theoretical framework of Integrated Nested Laplace Approximation, which represents one of the major recent breakthroughs in statistics, as it does not require Monte Carlo simulations. We compare the performance of our method and an alternative method for geospatial inference, SPA in a simulation framework. We highlight the accuracy and limits of continuous spatial assignment methods at various scales by analyzing genotype datasets from a diversity of species, including Florida Scrub-jay birds Aphelocoma coerulescens, Arabidopsis thaliana and humans, representing 41–197,146 SNPs. Our method appears to be best suited for the analysis of medium-sized datasets (a few tens of thousands of loci), such as reduced-representation sequencing data that become increasingly available in ecology. Availability and implementation: http://www2.imm.dtu.dk/∼gigu/Spasiba/ Contact: gilles.b.guillot@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.

Understanding of sequence diversity is the cornerstone of analysis of genetic disorders, population genetics, and evolutionary biology. Here, we present an update of our sequencing set to 15,220 Icelanders who we sequenced to an average genome-wide coverage of 34X. We identified 39,020,168 autosomal variants passing GATK filters: 31,079,378 SNPs and 7,940,790 indels. Calling de novo mutations (DNMs) is a formidable challenge given the high false positive rate in sequencing datasets relative to the mutation rate. Here we addressed this issue by using segregation of alleles in three-generation families. Using this transmission assay, we controlled the false positive rate and identified 108,778 high quality DNMs. Furthermore, we used our extended family structure and read pair tracing of DNMs to a panel of phased SNPs, to determine the parent of origin of 42,961 DNMs.

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.

OBJECTIVES: The genetic aetiology of osteoarthritis has not yet been elucidated. To enable a well-powered genome-wide association study (GWAS) for osteoarthritis, the authors have formed the arcOGEN Consortium, a UK-wide collaborative effort aiming to scan genome-wide over 7500 osteoarthritis cases in a two-stage genome-wide association scan. Here the authors report the findings of the stage 1 interim analysis. METHODS: The authors have performed a genome-wide association scan for knee and hip osteoarthritis in 3177 cases and 4894 population-based controls from the UK. Replication of promising signals was carried out in silico in five further scans (44,449 individuals), and de novo in 14 534 independent samples, all of European descent. RESULTS: None of the association signals the authors identified reach genome-wide levels of statistical significance, therefore stressing the need for corroboration in sample sets of a larger size. Application of analytical approaches to examine the allelic architecture of disease to the stage 1 genome-wide association scan data suggests that osteoarthritis is a highly polygenic disease with multiple risk variants conferring small effects. CONCLUSIONS: Identifying loci conferring susceptibility to osteoarthritis will require large-scale sample sizes and well-defined phenotypes to minimise heterogeneity. Ann Rheum Dis

Osteoarthritis (OA) is a prevalent, heritable degenerative joint disease with a substantial public health impact. We used a 1000-Genomes-Project-based imputation in a genome-wide association scan for osteoarthritis (3177 OA cases and 4894 controls) to detect a previously unidentified risk locus. We discovered a small disease-associated set of variants on chromosome 13. Through large-scale replication, we establish a robust association with SNPs in MCF2L (rs11842874, combined odds ratio [95% confidence interval] 1.17 [1.11-1.23], p = 2.1 x 10(-8)) across a total of 19,041 OA cases and 24,504 controls of European descent. This risk locus represents the third established signal for OA overall. MCF2L regulates a nerve growth factor (NGF), and treatment with a humanized monoclonal antibody against NGF is associated with reduction in pain and improvement in function for knee OA patients.

Schubert, Michael et al., The domestication of the horse ∼5.5 kya and the emergence of mounted riding, chariotry, and cavalry dramatically transformed human civilization. However, the genetics underlying horse domestication are difficult to reconstruct, given the near extinction of wild horses. We therefore sequenced two ancient horse genomes from Taymyr, Russia (at 7.4- and 24.3-fold coverage), both predating the earliest archeological evidence of domestication. We compared these genomes with genomes of domesticated horses and the wild Przewalski's horse and found genetic structure within Eurasia in the Late Pleistocene, with the ancient population contributing significantly to the genetic variation of domesticated breeds. We furthermore identified a conservative set of 125 potential domestication targets using four complementary scans for genes that have undergone positive selection. One group of genes is involved in muscular and limb development, articular junctions, and the cardiac system, and may represent physiological adaptations to human utilization. A second group consists of genes with cognitive functions, including social behavior, learning capabilities, fear response, and agreeableness, which may have been key for taming horses. We also found that domestication is associated with inbreeding and an excess of deleterious mutations. This genetic load is in line with the "cost of domestication" hypothesis also reported for rice, tomatoes, and dogs, and it is generally attributed to the relaxation of purifying selection resulting from the strong demographic bottlenecks accompanying domestication. Our work demonstrates the power of ancient genomes to reconstruct the complex genetic changes that transformed wild animals into their domesticated forms, and the population context in which this process took place. © 2014, National Academy of Sciences. All rights reserved., This work was supported by the Danish Council for Independent Research, Natural Sciences (FNU); the Danish National Research Foundation (DNFR94); a Marie-Curie Career Integration Grant (FP7 CIG-293845); and the International Research Group Program (IRG14-08), Deanship of Scientific Research (King Saud University, Saudi Arabia). H.J. was supported by a Marie-Curie Initial Training Network Grant (EUROTAST; FP7 ITN-290344); A.G. and L. Ermini were supported by Marie-Curie Intra-European Fellowships (FP7 IEF-299176 and FP7 IEF-302617); M.S. was supported by a Lundbeck Foundation Grant (R52-A5062); I.D., A.F., and L. Excoffier were supported by a Swiss National Science Foundation Grant (31003A-143393); M.H. was supported by a European Research Council (ERC) Consolidator Grant (310763); T.M.-B. was supported by an ERC Starting Grant (260372) and by a Ministerio de Ciencia e Innovación (MICINN) Grant (BFU2011-28549); B.S. was supported by the Packard Foundation; and D.C. was supported by start-up funds to B.S. from the University of California, Santa Cruz.

Next-generation sequencing technologies have revolutionized the field of paleogenomics, allowing the reconstruction of complete ancient genomes and their comparison with modern references. However, this requires the processing of vast amounts of data and involves a large number of steps that use a variety of computational tools. Here we present PALEOMIX (http://geogenetics.ku.dk/publications/paleomix), a flexible and user-friendly pipeline applicable to both modern and ancient genomes, which largely automates the in silico analyses behind whole-genome resequencing. Starting with next-generation sequencing reads, PALEOMIX carries out adapter removal, mapping against reference genomes, PCR duplicate removal, characterization of and compensation for postmortem damage, SNP calling and maximum-likelihood phylogenomic inference, and it profiles the metagenomic contents of the samples. As such, PALEOMIX allows for a series of potential applications in paleogenomics, comparative genomics and metagenomics. Applying the PALEOMIX pipeline to the three ancient and seven modern Phytophthora infestans genomes as described here takes 5 d using a 16-core server.

Motivation: Ancient DNA (aDNA) molecules in fossilized bones and teeth, coprolites, sediments, mummified specimens and museum collections represent fantastic sources of information for evolutionary biologists, revealing the agents of past epidemics and the dynamics of past populations. However, the analysis of aDNA generally faces two major issues. Firstly, sequences consist of a mixture of endogenous and various exogenous backgrounds, mostly microbial. Secondly, high nucleotide misincorporation rates can be observed as a result of severe post-mortem DNA damage. Such misincorporation patterns are instrumental to authenticate ancient sequences versus modern contaminants. We recently developed the user-friendly mapDamage package that identifies such patterns from next-generation sequencing (NGS) sequence datasets. The absence of formal statistical modeling of the DNA damage process, however, precluded rigorous quantitative comparisons across samples. Results: Here, we describe mapDamage 2.0 that extends the original features of mapDamage by incorporating a statistical model of DNA damage. Assuming that damage events depend only on sequencing position and post-mortem deamination, our Bayesian statistical framework provides estimates of four key features of aDNA molecules: the average length of overhangs (λ), nick frequency (ν) and cytosine deamination rates in both double-stranded regions () and overhangs (). Our model enables rescaling base quality scores according to their probability of being damaged. mapDamage 2.0 handles NGS datasets with ease and is compatible with a wide range of DNA library protocols. Availability: mapDamage 2.0 is available at ginolhac.github.io/mapDamage/ as a Python package and documentation is maintained at the Centre for GeoGenetics Web site (geogenetics.ku.dk/publications/mapdamage2.0/). Contact: jonsson.hakon@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.