Graphtyper enables population-scale genotyping using pangenome graphs

Are we there yet? Driving the road to evolutionary graph-pangenomics

With increase in the number of sequenced genomes, it is now recognized that graph-based pangenomes can provide a comprehensive platform to study diversity in a population or species, from point mutations to large chromosomal rearrangements. By incorporating concepts from graph theory, a graph-pangenome can be studied directly to identify genomic regions and genes that underlie important evolutionary processes and traits. Here, I discuss how basic concepts in graph theory can be implemented to address questions in evolutionary genomics and guide future breeding efforts. Despite its compelling versatility, a graph-pangenome assembly is still challenging especially in species with large complex genomes. As technology is rapidly improving, the graph-pangenome is expected to become a central platform in genomics studies and applications. Thus, development of tools and methods that exploit the graph structure are urged to pave the route to evolutionary graph-pangenomics.

Pangenome-based genome inference allows efficient and accurate genotyping across a wide spectrum of variant classes

Typical genotyping workflows map reads to a reference genome before identifying genetic variants. Generating such alignments introduces reference biases and comes with substantial computational burden. Furthermore, short-read lengths limit the ability to characterize repetitive genomic regions, which are particularly challenging for fast k-mer-based genotypers. In the present study, we propose a new algorithm, PanGenie, that leverages a haplotype-resolved pangenome reference together with k-mer counts from short-read sequencing data to genotype a wide spectrum of genetic variation-a process we refer to as genome inference. Compared with mapping-based approaches, PanGenie is more than 4 times faster at 30-fold coverage and achieves better genotype concordances for almost all variant types and coverages tested. Improvements are especially pronounced for large insertions (≥50 bp) and variants in repetitive regions, enabling the inclusion of these classes of variants in genome-wide association studies. PanGenie efficiently leverages the increasing amount of haplotype-resolved assemblies to unravel the functional impact of previously inaccessible variants while being faster compared with alignment-based workflows.

A genome-wide meta-analysis identifies 50 genetic loci associated with carpal tunnel syndrome

Carpal tunnel syndrome (CTS) is the most common entrapment neuropathy and has a largely unknown underlying biology. In a genome-wide association study of CTS (48,843 cases and 1,190,837 controls), we found 53 sequence variants at 50 loci associated with the syndrome. The most significant association is with a missense variant (p.Glu366Lys) in SERPINA1 that protects against CTS (P = 2.9 × 10^-24, OR = 0.76). Through various functional analyses, we conclude that at least 22 genes mediate CTS risk and highlight the role of 19 CTS variants in the biology of the extracellular matrix. We show that the genetic component to the risk is higher in bilateral/recurrent/persistent cases than nonrecurrent/nonpersistent cases. Anthropometric traits including height and BMI are genetically correlated with CTS, in addition to early hormonal-replacement therapy, osteoarthritis, and restlessness. Our findings suggest that the components of the extracellular matrix play a key role in the pathogenesis of CTS.

Pangenomics in crop improvement-from coding structural variations to finding regulatory variants with pangenome graphs

Since the first reported crop pangenome in 2014, advances in high-throughput and cost-effective DNA sequencing technologies facilitated multiple such studies including the pangenomes of oilseed rape (Brassica napus L.), soybean [Glycine max (L.) Merr.], rice (Oryza sativa L.), wheat (Triticum aestivum L.), and barley (Hordeum vulgare L.). Compared with single-reference genomes, pangenomes provide a more accurate representation of the genetic variation present in a species. By combining the genomic data of multiple accessions, pangenomes allow for the detection and annotation of complex DNA polymorphisms such as structural variations (SVs), one of the major determinants of genetic diversity within a species. In this review we summarize the current literature on crop pangenomics, focusing on their application to find candidate SVs involved in traits of agronomic interest. We then highlight the potential of pangenomes in the discovery and functional characterization of noncoding regulatory sequences and their variations. We conclude with a summary and outlook on innovative data structures representing the complete content of plant pangenomes including annotations of coding and noncoding elements and outcomes of transcriptomic and epigenomic experiments.

Evaluation of four methods to identify the homozygotic sex chromosome in small populations

BACKGROUND

Whole genomes are commonly assembled into a collection of scaffolds and often lack annotations of autosomes, sex chromosomes, and organelle genomes (i.e., mitochondrial and chloroplast). As these chromosome types differ in effective population size and can have highly disparate evolutionary histories, it is imperative to take this information into account when analysing genomic variation. Here we assessed the accuracy of four methods for identifying the homogametic sex chromosome in a small population using two whole genome sequences (WGS) and 133 RAD sequences of white-tailed eagles (Haliaeetus albicilla): i) difference in read depth per scaffold in a male and a female, ii) heterozygosity per scaffold in a male and a female, iii) mapping to the reference genome of a related species (chicken) with annotated sex chromosomes, and iv) analysis of SNP-loadings from a principal components analysis (PCA), based on the low-depth RADseq data.

RESULTS

The best performing approach was the reference mapping (method iii), which identified 98.12% of the expected homogametic sex chromosome (Z). Read depth per scaffold (method i) identified 86.41% of the homogametic sex chromosome with few false positives. SNP-loading scores (method iv) identified 78.6% of the Z-chromosome and had a false positive discovery rate of more than 10%. Heterozygosity per scaffold (method ii) did not provide clear results due to a lack of diversity in both the Z and autosomal chromosomes, and potential interference from the heterogametic sex chromosome (W). The evaluation of these methods also revealed 10 Mb of putative PAR and gametologous regions.

CONCLUSION

Identification of the homogametic sex chromosome in a small population is best accomplished by reference mapping or examining differences in read depth between sexes.

Haplotype-resolved de novo assembly of a Tujia genome suggests the necessity for high-quality population-specific genome references

Even though the human reference genome assembly is continually being improved, it remains debatable whether a population-specific reference is necessary for every ethnic group. Here, we de novo assembled an individual genome (TJ1) from the Tujia population, an ethnic minority group most closely related to the Han Chinese. TJ1 provided a high-quality haplotype-resolved assembly of chromosome-scale with a scaffold N50 size >78 Mb. Compared with GRCh38 and other de novo assemblies, TJ1 improved short-read mapping, enhanced calling precision for structural variants, and detected rare and low-frequency variants. This revealed fine-scale differences between the closely related Han and Tujia populations, such as population-stratified variants of LCT and UBXN8, and improved screening for ancestry informative markers. We demonstrated that TJ1 could reduce false positives in clinical diagnosis and analyzed the PRSS1-PRSS2 locus as a test case. Our results suggest that population-specific assemblies are necessary for genetic and medical analysis, especially when closely related populations are studied. A record of this paper's transparent peer review process is included in the supplemental information.

Rare SLC13A1 variants associate with intervertebral disc disorder highlighting role of sulfate in disc pathology

Back pain is a common and debilitating disorder with largely unknown underlying biology. Here we report a genome-wide association study of back pain using diagnoses assigned in clinical practice; dorsalgia (119,100 cases, 909,847 controls) and intervertebral disc disorder (IDD) (58,854 cases, 922,958 controls). We identify 41 variants at 33 loci. The most significant association (OR_IDD = 0.92, P = 1.6 × 10⁻³⁹; OR_dorsalgia = 0.92, P = 7.2 × 10⁻¹⁵) is with a 3’UTR variant (rs1871452-T) in CHST3, encoding a sulfotransferase enzyme expressed in intervertebral discs. The largest effects on IDD are conferred by rare (MAF = 0.07 − 0.32%) loss-of-function (LoF) variants in SLC13A1, encoding a sodium-sulfate co-transporter (LoF burden OR = 1.44, P = 3.1 × 10⁻¹¹); variants that also associate with reduced serum sulfate. Genes implicated by this study are involved in cartilage and bone biology, as well as neurological and inflammatory processes.

Little is known about the biology of back pain, a leading cause of disability. Here the authors report 30 new back pain loci, implicating genes involved in cartilage/bone biology, as well as neurological and inflammatory processes.

Adaptation to a Commercial Quaternary Ammonium Compound Sanitizer Leads to Cross-Resistance to Select Antibiotics in Listeria monocytogenes Isolated From Fresh Produce Environments

The effective elimination of Listeria monocytogenes through cleaning and sanitation is of great importance to the food processing industry. Specifically in fresh produce operations, the lack of a kill step requires effective cleaning and sanitation to mitigate the risk of cross-contamination from the environment. As facilities rely on sanitizers to control L. monocytogenes, reports of the development of tolerance to sanitizers and other antimicrobials through cross-resistance is of particular concern. We investigated the potential for six L. monocytogenes isolates from fresh produce handling and processing facilities and packinghouses to develop cross-resistance between a commercial sanitizer and antibiotics. Experimental adaptation of isolates belonging to hypervirulent clonal complexes (CC2, CC4, and CC6) to a commercial quaternary ammonium compound sanitizer (cQAC) resulted in elevated minimum inhibitory concentrations (2–3 ppm) and minimum bactericidal concentrations (3–4 ppm). Susceptibility to cQAC was restored for all adapted (qAD) isolates in the presence of reserpine, a known efflux pump inhibitor. Reduced sensitivity to 7/17 tested antibiotics (chloramphenicol, ciprofloxacin, clindamycin, kanamycin, novobiocin, penicillin, and streptomycin) was observed in all tested isolates. qAD isolates remained susceptible to antibiotics commonly used in the treatment of listeriosis (i.e., ampicillin and gentamicin). The whole genome sequencing of qAD strains, followed by comparative genomic analysis, revealed several mutations in fepR, the regulator for FepA fluoroquinolone efflux pump. The results suggest that mutations in fepR play a role in the reduction in antibiotic susceptibility following low level adaptation to cQAC. Further investigation into the cross-resistance mechanisms and pressures leading to the development of this phenomenon among L. monocytogenes isolates recovered from different sources is needed to better understand the likelihood of cross-resistance development in food chain isolates and the implications for the food industry.

Identifying Balanced Chromosomal Translocations in Human Embryos by Oxford Nanopore Sequencing and Breakpoints Region Analysis

Background: Balanced chromosomal aberrations, especially balanced translocations, can cause infertility, recurrent miscarriage or having chromosomally defective offspring. Preimplantation genetic testing for structural rearrangement (PGT-SR) has been widely implemented to improve the clinical outcomes by selecting euploid embryos for transfer, whereas embryos with balanced translocation karyotype were difficult to be distinguished by routine genetic techniques from those with a normal karyotype.

Method: In this present study, we developed a clinically applicable method for reciprocal translocation carriers to reduce the risk of pregnancy loss. In the preclinical phase, we identified reciprocal translocation breakpoints in blood of translocation carriers by long-read Oxford Nanopore sequencing, followed by junction-spanning polymerase chain reaction (PCR) and Sanger sequencing. In the clinical phase of embryo diagnosis, aneuploidies and unbalanced translocations were screened by comprehensive chromosomal screening (CCS) with single nucleotide polymorphism (SNP) microarray, carrier embryos were diagnosed by junction-spanning PCR and family haplotype linkage analysis of the breakpoints region. Amniocentesis and cytogenetic analysis of fetuses in the second trimester were performed after embryo transfer to conform the results diagnosed by the presented method.

Results: All the accurate reciprocal translocation breakpoints were effectively identified by Nanopore sequencing and confirmed by Sanger sequencing. Twelve embryos were biopsied and detected, the results of junction-spanning PCR and haplotype linkage analysis were consistent. In total, 12 biopsied blastocysts diagnosed to be euploid, in which 6 were aneuploid or unbalanced, three blastocysts were identified to be balanced translocation carriers and three to be normal karyotypes. Two euploid embryos were subsequently transferred back to patients and late prenatal karyotype analysis of amniotic fluid cells was performed. The outcomes diagnosed by the current approach were totally consistent with the fetal karyotypes.

Conclusions: In summary, these investigations in our study illustrated that chromosomal reciprocal translocations in embryos can be accurately diagnosed. Long-read Nanopore sequencing and breakpoint analysis contributes to precisely evaluate the genetic risk of disrupted genes, and provides a way of selecting embryos with normal karyotype, especially for couples those without a reference.

The mutationathon highlights the importance of reaching standardization in estimates of pedigree-based germline mutation rates

In the past decade, several studies have estimated the human per-generation germline mutation rate using large pedigrees. More recently, estimates for various nonhuman species have been published. However, methodological differences among studies in detecting germline mutations and estimating mutation rates make direct comparisons difficult. Here, we describe the many different steps involved in estimating pedigree-based mutation rates, including sampling, sequencing, mapping, variant calling, filtering, and appropriately accounting for false-positive and false-negative rates. For each step, we review the different methods and parameter choices that have been used in the recent literature. Additionally, we present the results from a ‘Mutationathon,’ a competition organized among five research labs to compare germline mutation rate estimates for a single pedigree of rhesus macaques. We report almost a twofold variation in the final estimated rate among groups using different post-alignment processing, calling, and filtering criteria, and provide details into the sources of variation across studies. Though the difference among estimates is not statistically significant, this discrepancy emphasizes the need for standardized methods in mutation rate estimations and the difficulty in comparing rates from different studies. Finally, this work aims to provide guidelines for computational and statistical benchmarks for future studies interested in identifying germline mutations from pedigrees.

Alignment-Free Genotyping of Known Variations with MALVA

The discovery and characterization of sequence variations in human populations are crucial in genetic studies. Standard methods for addressing this problem are computationally expensive and highly time consuming, thus impractical for clinical applications, where time is often an issue. When the task is to genotype variations that have been previously annotated, alignment-free methods come to the aid. Here, we describe MALVA, an alignment-free approach for genotyping a set of known variations. MALVA is the first mapping-free tool which is able to genotype multi-allelic SNPs and indels, even in high-density genomic regions, and to effectively handle a huge number of variations.

Infliximab-induced liver injury: Clinical phenotypes, autoimmunity and the role of corticosteroid treatment

BACKGROUND & AIMS

Infliximab has been associated with drug-induced liver injury (DILI), particularly drug-induced autoimmune hepatitis (DIAIH). DIAIH is commonly treated with corticosteroids, but there is limited data on the efficacy of corticosteroids in infliximab-induced DILI.

METHODS

Patients were included for assessment if they had been treated with infliximab between 2009-2020 in Iceland and had developed elevated liver tests. Other specific etiologies of liver enzyme elevations were excluded. Patients treated with corticosteroids were compared to patients not receiving corticosteroids.

RESULTS

A total of 36 patients with infliximab-induced DILI were identified: median age was 46 years (IQR 32-54) and 28 (78%) were female. Type of liver injury was predominantly hepatocellular (64%). Median peak liver enzymes were: alanine aminotransferase (ALT) 393 (328-695) U/L, aspartate aminotransferase 283 (158-564) U/L, alkaline phosphatase 116 (83-205) U/L, and bilirubin (10-20) 13 μmol/L. A total of 25 (69%) were positive for anti-nuclear antibody and/or had elevated IgG. Corticosteroids were initiated in 17 (47%). Median time from onset of liver injury to peak ALT value was longer in patients treated with corticosteroids, 22 (12-59) vs. 0 (0-3) days (p = 0.001). Time from peak ALT to normalization of liver enzymes was 45 days in the corticosteroid group vs. 77 days in others (p = 0.062). Corticosteroids were tapered in all patients, with no cases of relapse during the follow-up period of 1,245 (820-2,698) days. Overall 75% received another biologic, mostly adalimumab, without evidence of liver injury.

CONCLUSION

Approximately half of patients with infliximab-induced liver injury had slow improvement in ALT despite cessation of therapy and were treated with corticosteroids. Treatment response was good with prompt resolution of liver test abnormalities. Relapse of liver injury was not observed after tapering of corticosteroids despite prolonged follow-up and no patients developed DILI due to a second biologic.

LAY SUMMARY

A rare side effect of infliximab, a biologic medicine used to treat multiple inflammatory diseases, is liver injury and liver inflammation. Steroid treatment has been used in some patients with liver injury caused by infliximab, but there have been few studies supporting this treatment. In this study of 36 patients with infliximab-induced liver injury, approximately half of patients were treated with steroids and the results suggest that patients receiving steroids recover more quickly.

deGSM: Memory Scalable Construction Of Large Scale de Bruijn Graph

The de Bruijn graph, a fundamental data structure to represent and organize genome sequence, plays important roles in various kinds of sequence analysis tasks. With the rapid development of HTS data and ever-increasing number of assembled genomes, there is a high demand to construct the very large de Bruijn graph for sequences up to Tera-base-pair level. Current approaches may have unaffordable memory footprints to handle such a large de Bruijn graph. We propose a lightweight parallel de Bruijn graph construction approach: de Bruijn Graph Constructor in Scalable Memory (deGSM). The main idea of deGSM is to efficiently construct the Burrows-Wheeler Transformation (BWT) of the unipaths of the de Bruijn graph in constant RAM space and transform the BWT into the original unitigs. The experimental results demonstrate that, just with a commonly available machine, deGSM is able to handle very large genome sequence(s), e.g., the contigs (305 Gbp) and scaffolds (1.1 Tbp) recorded in GenBank database and Picea abies HTS dataset (9.7 Tbp). Moreover, deGSM also has faster or comparable construction speed compared with state-of-the-art approaches. With its high scalability and efficiency, deGSM has enormous potential in many large scale genomics studies. The deGSM is publicly available at: https://github.com/hitbc/deGSM.

Application of Whole Genome Sequencing to Understand Diversity and Presence of Genes Associated with Sanitizer Tolerance in Listeria monocytogenes from Produce Handling Sources

Recent listeriosis outbreaks linked to fresh produce suggest the need to better understand and mitigate L. monocytogenes contamination in packing and processing environments. Using whole genome sequencing (WGS) and phenotype screening assays for sanitizer tolerance, we characterized 48 L. monocytogenes isolates previously recovered from environmental samples in five produce handling facilities. Within the studied population there were 10 sequence types (STs) and 16 cgMLST types (CTs). Pairwise single nucleotide polymorphisms (SNPs) ranged from 0 to 3047 SNPs within a CT, revealing closely and distantly related isolates indicative of both sporadic and continuous contamination events within the facility. Within Facility 1, we identified a closely related cluster (0-2 SNPs) of isolates belonging to clonal complex 37 (CC37; CT9492), with isolates recovered during sampling events 1-year apart and in various locations inside and outside the facility. The accessory genome of these CC37 isolates varied from 94 to 210 genes. Notable genetic elements and mutations amongst the isolates included the bcrABC cassette (2/48), associated with QAC tolerance; mutations in the actA gene on the Listeria pathogenicity island (LIPI) 1 (20/48); presence of LIPI-3 (21/48) and LIPI-4 (23/48). This work highlights the potential use of WGS in tracing the pathogen within a facility and understanding properties of L. monocytogenes in produce settings.

A genome-wide meta-analysis uncovers six sequence variants conferring risk of vertigo

Vertigo is the leading symptom of vestibular disorders and a major risk factor for falls. In a genome-wide association study of vertigo (Ncases = 48,072, Ncontrols = 894,541), we uncovered an association with six common sequence variants in individuals of European ancestry, including missense variants in ZNF91, OTOG, OTOGL, and TECTA, and a cis-eQTL for ARMC9. The association of variants in ZNF91, OTOGL, and OTOP1 was driven by an association with benign paroxysmal positional vertigo. Using previous reports of sequence variants associating with age-related hearing impairment and motion sickness, we found eight additional variants that associate with vertigo. Although disorders of the auditory and the vestibular system may co-occur, none of the six genome-wide significant vertigo variants were associated with hearing loss and only one was associated with age-related hearing impairment. Our results uncovered sequence variants associating with vertigo in a genome-wide association study and implicated genes with known roles in inner ear development, maintenance, and disease.

Large-Scale Screening for Monogenic and Clinically Defined Familial Hypercholesterolemia in Iceland

Objective: Familial hypercholesterolemia (FH) is traditionally defined as a monogenic disease characterized by severely elevated LDL-C (low-density lipoprotein cholesterol) levels. In practice, FH is commonly a clinical diagnosis without confirmation of a causative mutation. In this study, we sought to characterize and compare monogenic and clinically defined FH in a large sample of Icelanders. Approach and Results: We whole-genome sequenced 49 962 Icelanders and imputed the identified variants into an overall sample of 166 281 chip-genotyped Icelanders. We identified 20 FH mutations in LDLR, APOB, and PCSK9 with combined prevalence of 1 in 836. Monogenic FH was associated with severely elevated LDL-C levels and increased risk of premature coronary disease, aortic valve stenosis, and high burden of coronary atherosclerosis. We used a modified version of the Dutch Lipid Clinic Network criteria to screen for the clinical FH phenotype among living adult participants (N=79 058). Clinical FH was found in 2.2% of participants, of whom only 5.2% had monogenic FH. Mutation-negative clinical FH has a strong polygenic basis. Both individuals with monogenic FH and individuals with mutation-negative clinical FH were markedly undertreated with cholesterol-lowering medications and only a minority attained an LDL-C target of <2.6 mmol/L (<100 mg/dL; 11.0% and 24.9%, respectively) or <1.8 mmol/L (<70 mg/dL; 0.0% and 5.2%, respectively), as recommended for primary prevention by European Society of Cardiology/European Atherosclerosis Society cholesterol guidelines. Conclusions: Clinically defined FH is a relatively common phenotype that is explained by monogenic FH in only a minority of cases. Both monogenic and clinical FH confer high cardiovascular risk but are markedly undertreated.

Pandora: nucleotide-resolution bacterial pan-genomics with reference graphs

We present pandora, a novel pan-genome graph structure and algorithms for identifying variants across the full bacterial pan-genome. As much bacterial adaptability hinges on the accessory genome, methods which analyze SNPs in just the core genome have unsatisfactory limitations. Pandora approximates a sequenced genome as a recombinant of references, detects novel variation and pan-genotypes multiple samples. Using a reference graph of 578 Escherichia coli genomes, we compare 20 diverse isolates. Pandora recovers more rare SNPs than single-reference-based tools, is significantly better than picking the closest RefSeq reference, and provides a stable framework for analyzing diverse samples without reference bias.

Gramtools enables multiscale variation analysis with genome graphs

Genome graphs allow very general representations of genetic variation; depending on the model and implementation, variation at different length-scales (single nucleotide polymorphisms (SNPs), structural variants) and on different sequence backgrounds can be incorporated with different levels of transparency. We implement a model which handles this multiscale variation and develop a JSON extension of VCF (jVCF) allowing for variant calls on multiple references, both implemented in our software gramtools. We find gramtools outperforms existing methods for genotyping SNPs overlapping large deletions in M. tuberculosis and is able to genotype on multiple alternate backgrounds in P. falciparum, revealing previously hidden recombination.

Genomic Approaches to Plant-Pathogen Epidemiology and Diagnostics

Diseases have a significant cost to agriculture. Findings from analyses of whole-genome sequences show great promise for informing strategies to mitigate risks from diseases caused by phytopathogens. Genomic approaches can be used to dramatically shorten response times to outbreaks and inform disease management in novel ways. However, the use of these approaches requires expertise in working with big, complex data sets and an understanding of their pitfalls and limitations to infer well-supported conclusions. We suggest using an evolutionary framework to guide the use of genomic approaches in epidemiology and diagnostics of plant pathogens. We also describe steps that are necessary for realizing these as standard approaches in disease surveillance.

Methods and Developments in Graphical Pangenomics

Pangenomes are organized collections of the genomic information from related individuals or groups. Graphical pangenomics is the study of these pangenomes using graphical methods to identify and analyze genes, regions, and mutations of interest to an array of biological questions. This field has seen significant progress in recent years including the development of graph based models that better resolve biological phenomena, and an explosion of new tools for mapping reads, creating graphical genomes, and performing pangenome analysis. In this review, we discuss recent developments in models, algorithms associated with graphical genomes, and comparisons between similar tools. In addition we briefly discuss what these developments may mean for the future of genomics.

Expanding the conservation genomics toolbox: Incorporating structural variants to enhance genomic studies for species of conservation concern

Structural variants (SVs) are large rearrangements (>50 bp) within the genome that impact gene function and the content and structure of chromosomes. As a result, SVs are a significant source of functional genomic variation, that is, variation at genomic regions underpinning phenotype differences, that can have large effects on individual and population fitness. While there are increasing opportunities to investigate functional genomic variation in threatened species via single nucleotide polymorphism (SNP) data sets, SVs remain understudied despite their potential influence on fitness traits of conservation interest. In this future-focused Opinion, we contend that characterizing SVs offers the conservation genomics community an exciting opportunity to complement SNP-based approaches to enhance species recovery. We also leverage the existing literature-predominantly in human health, agriculture and ecoevolutionary biology-to identify approaches for readily characterizing SVs and consider how integrating these into the conservation genomics toolbox may transform the way we manage some of the world's most threatened species.

VariantStore: an index for large-scale genomic variant search

Efficiently scaling genomic variant search indexes to thousands of samples is computationally challenging due to the presence of multiple coordinate systems to avoid reference biases. We present VariantStore, a system that indexes genomic variants from multiple samples using a variation graph and enables variant queries across any sample-specific coordinate system. We show the scalability of VariantStore by indexing genomic variants from the TCGA project in 4 h and the 1000 Genomes project in 3 h. Querying for variants in a gene takes between 0.002 and 3 seconds using memory only 10% of the size of the full representation.

read_haps: using read haplotypes to detect same species contamination in DNA sequences

MOTIVATION

Data analysis is requisite on reliable data. In genetics this includes verifying that the sample is not contaminated with another, a problem ubiquitous in biology.

RESULTS

In human, and other diploid species, DNA contamination from the same species can be found by the presence of three haplotypes between polymorphic SNPs. read_haps is a tool that detects sample contamination from short read whole genome sequencing data.

AVAILABILITYAND IMPLEMENTATION

github.com/DecodeGenetics/read_haps.

The genomic history of the Middle East

The Middle East region is important to understand human evolution and migrations but is underrepresented in genomic studies. Here, we generated 137 high-coverage physically phased genome sequences from eight Middle Eastern populations using linked-read sequencing. We found no genetic traces of early expansions out-of-Africa in present-day populations but found Arabians have elevated Basal Eurasian ancestry that dilutes their Neanderthal ancestry. Population sizes within the region started diverging 15–20 kya, when Levantines expanded while Arabians maintained smaller populations that derived ancestry from local hunter-gatherers. Arabians suffered a population bottleneck around the aridification of Arabia 6 kya, while Levantines had a distinct bottleneck overlapping the 4.2 kya aridification event. We found an association between movement and admixture of populations in the region and the spread of Semitic languages. Finally, we identify variants that show evidence of selection, including polygenic selection. Our results provide detailed insights into the genomic and selective histories of the Middle East.

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Middle Easterners do not have ancestry from an early out-of-Africa expansion

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Basal Eurasian and African ancestry in Arabians deplete their Neanderthal ancestry

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Populations experienced bottlenecks overlapping aridification events

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Identification of recent single and polygenic signals of selection in Arabia

A variant selection framework for genome graphs

MOTIVATION

Variation graph representations are projected to either replace or supplement conventional single genome references due to their ability to capture population genetic diversity and reduce reference bias. Vast catalogues of genetic variants for many species now exist, and it is natural to ask which among these are crucial to circumvent reference bias during read mapping.

RESULTS

In this work, we propose a novel mathematical framework for variant selection, by casting it in terms of minimizing variation graph size subject to preserving paths of length α with at most δ differences. This framework leads to a rich set of problems based on the types of variants [e.g. single nucleotide polymorphisms (SNPs), indels or structural variants (SVs)], and whether the goal is to minimize the number of positions at which variants are listed or to minimize the total number of variants listed. We classify the computational complexity of these problems and provide efficient algorithms along with their software implementation when feasible. We empirically evaluate the magnitude of graph reduction achieved in human chromosome variation graphs using multiple α and δ parameter values corresponding to short and long-read resequencing characteristics. When our algorithm is run with parameter settings amenable to long-read mapping (α = 10 kbp, δ = 1000), 99.99% SNPs and 73% SVs can be safely excluded from human chromosome 1 variation graph. The graph size reduction can benefit downstream pan-genome analysis.

AVAILABILITY AND IMPLEMENTATION

: https://github.com/AT-CG/VF.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Founder Reconstruction Enables Scalable and Seamless Pangenomic Analysis

Motivation

Variant calling workflows that utilize a single reference sequence are the de facto standard elementary genomic analysis routine for resequencing projects. Various ways to enhance the reference with pangenomic information have been proposed, but scalability combined with seamless integration to existing workflows remains a challenge.

Results

We present PanVC with founder sequences, a scalable and accurate variant calling workflow based on a multiple alignment of reference sequences. Scalability is achieved by removing duplicate parts up to a limit into a founder multiple alignment, that is then indexed using a hybrid scheme that exploits general purpose read aligners. Our implemented workflow uses GATK or BCFtools for variant calling, but the various steps of our workflow (e.g. vcf2multialign tool, founder reconstruction) can be of independent interest as a basis for creating novel pangenome analysis workflows beyond variant calling.

Availability and implementation

Our open access tools and instructions how to reproduce our experiments are available at the following address: https://github.com/algbio/panvc-founders.

Supplementary information

Supplementary data are available at Bioinformatics online.

Building pan-genome infrastructures for crop plants and their use in association genetics

Pan-genomic studies aim at representing the entire sequence diversity within a species to provide useful resources for evolutionary studies, functional genomics and breeding of cultivated plants. Cost reductions in high-throughput sequencing and advances in sequence assembly algorithms have made it possible to create multiple reference genomes along with a catalogue of all forms of genetic variations in plant species with large and complex or polyploid genomes. In this review, we summarize the current approaches to building pan-genomes as an in silico representation of plant sequence diversity and outline relevant methods for their effective utilization in linking structural with phenotypic variation. We propose as future research avenues (i) transcriptomic and epigenomic studies across multiple reference genomes and (ii) the development of user-friendly and feature-rich pan-genome browsers.

Molecular benchmarks of a SARS-CoV-2 epidemic

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.

The genetic architecture of age-related hearing impairment revealed by genome-wide association analysis

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.

Eleven genomic loci affect plasma levels of chronic inflammation marker soluble urokinase-type plasminogen activator receptor

Soluble urokinase-type plasminogen activator receptor (suPAR) is a chronic inflammation marker associated with the development of a range of diseases, including cancer and cardiovascular disease. The genetics of suPAR remain unexplored but may shed light on the biology of the marker and its connection to outcomes. We report a heritability estimate of 60% for the variation in suPAR and performed a genome-wide association meta-analysis on suPAR levels measured in Iceland (N = 35,559) and in Denmark (N = 12,177). We identified 13 independently genome-wide significant sequence variants associated with suPAR across 11 distinct loci. Associated variants were found in and around genes encoding uPAR (PLAUR), its ligand uPA (PLAU), the kidney-disease-associated gene PLA2R1 as well as genes with relations to glycosylation, glycoprotein biosynthesis, and the immune response. These findings provide new insight into the causes of variation in suPAR plasma levels, which may clarify suPAR's potential role in associated diseases, as well as the underlying mechanisms that give suPAR its prognostic value as a unique marker of chronic inflammation.

Impacts of allopolyploidization and structural variation on intraspecific diversification in Brassica rapa

BACKGROUND

Despite the prevalence and recurrence of polyploidization in the speciation of flowering plants, its impacts on crop intraspecific genome diversification are largely unknown. Brassica rapa is a mesopolyploid species that is domesticated into many subspecies with distinctive morphotypes.

RESULTS

Herein, we report the consequences of the whole-genome triplication (WGT) on intraspecific diversification using a pan-genome analysis of 16 de novo assembled and two reported genomes. Among the genes that derive from WGT, 13.42% of polyploidy-derived genes accumulate more transposable elements and non-synonymous mutations than other genes during individual genome evolution. We denote such genes as being "flexible." We construct the Brassica rapa ancestral genome and observe the continuing influence of the dominant subgenome on intraspecific diversification in B. rapa. The gene flexibility is biased to the more fractionated subgenomes (MFs), in contrast to the more intact gene content of the dominant LF (least fractionated) subgenome. Furthermore, polyploidy-derived flexible syntenic genes are implicated in the response to stimulus and the phytohormone auxin; this may reflect adaptation to the environment. Using an integrated graph-based genome, we investigate the structural variation (SV) landscapes in 524 B. rapa genomes. We observe that SVs track morphotype domestication. Four out of 266 candidate genes for Chinese cabbage domestication are speculated to be involved in the leafy head formation.

CONCLUSIONS

This pan-genome uncovers the possible contributions of allopolyploidization on intraspecific diversification and the possible and underexplored role of SVs in favorable trait domestication. Collectively, our work serves as a rich resource for genome-based B. rapa improvement.

Integrated Analysis of Whole Genome and Epigenome Data Using Machine Learning Technology: Toward the Establishment of Precision Oncology

With the completion of the International Human Genome Project, we have entered what is known as the post-genome era, and efforts to apply genomic information to medicine have become more active. In particular, with the announcement of the Precision Medicine Initiative by U.S. President Barack Obama in his State of the Union address at the beginning of 2015, "precision medicine," which aims to divide patients and potential patients into subgroups with respect to disease susceptibility, has become the focus of worldwide attention. The field of oncology is also actively adopting the precision oncology approach, which is based on molecular profiling, such as genomic information, to select the appropriate treatment. However, the current precision oncology is dominated by a method called targeted-gene panel (TGP), which uses next-generation sequencing (NGS) to analyze a limited number of specific cancer-related genes and suggest optimal treatments, but this method causes the problem that the number of patients who benefit from it is limited. In order to steadily develop precision oncology, it is necessary to integrate and analyze more detailed omics data, such as whole genome data and epigenome data. On the other hand, with the advancement of analysis technologies such as NGS, the amount of data obtained by omics analysis has become enormous, and artificial intelligence (AI) technologies, mainly machine learning (ML) technologies, are being actively used to make more efficient and accurate predictions. In this review, we will focus on whole genome sequencing (WGS) analysis and epigenome analysis, introduce the latest results of omics analysis using ML technologies for the development of precision oncology, and discuss the future prospects.

Long-read sequencing of 3,622 Icelanders provides insight into the role of structural variants in human diseases and other traits

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.

Novel functional sequences uncovered through a bovine multiassembly graph

Many genomic analyses start by aligning sequencing reads to a linear reference genome. However, linear reference genomes are imperfect, lacking millions of bases of unknown relevance and are unable to reflect the genetic diversity of populations. This makes reference-guided methods susceptible to reference-allele bias. To overcome such limitations, we build a pangenome from six reference-quality assemblies from taurine and indicine cattle as well as yak. The pangenome contains an additional 70,329,827 bases compared to the Bos taurus reference genome. Our multiassembly approach reveals 30 and 10.1 million bases private to yak and indicine cattle, respectively, and between 3.3 and 4.4 million bases unique to each taurine assembly. Utilizing transcriptomes from 56 cattle, we show that these nonreference sequences encode transcripts that hitherto remained undetected from the B. taurus reference genome. We uncover genes, primarily encoding proteins contributing to immune response and pathogen-mediated immunomodulation, differentially expressed between Mycobacterium bovis-infected and noninfected cattle that are also undetectable in the B. taurus reference genome. Using whole-genome sequencing data of cattle from five breeds, we show that reads which were previously misaligned against the Bos taurus reference genome now align accurately to the pangenome sequences. This enables us to discover 83,250 polymorphic sites that segregate within and between breeds of cattle and capture genetic differentiation across breeds. Our work makes a so-far unused source of variation amenable to genetic investigations and provides methods and a framework for establishing and exploiting a more diverse reference genome.

Germline variants at SOHLH2 influence multiple myeloma risk

Multiple myeloma (MM) is caused by the uncontrolled, clonal expansion of plasma cells. While there is epidemiological evidence for inherited susceptibility, the molecular basis remains incompletely understood. We report a genome-wide association study totalling 5,320 cases and 422,289 controls from four Nordic populations, and find a novel MM risk variant at SOHLH2 at 13q13.3 (risk allele frequency = 3.5%; odds ratio = 1.38; P = 2.2 × 10-14). This gene encodes a transcription factor involved in gametogenesis that is normally only weakly expressed in plasma cells. The association is represented by 14 variants in linkage disequilibrium. Among these, rs75712673 maps to a genomic region with open chromatin in plasma cells, and upregulates SOHLH2 in this cell type. Moreover, rs75712673 influences transcriptional activity in luciferase assays, and shows a chromatin looping interaction with the SOHLH2 promoter. Our work provides novel insight into MM susceptibility.

StellarPGx: A Nextflow Pipeline for Calling Star Alleles in Cytochrome P450 Genes

Bioinformatics pipelines for calling star alleles (haplotypes) in cytochrome P450 (CYP) genes are important for the implementation of precision medicine. Genotyping CYP genes using high throughput sequencing data is complicated, e.g., by being highly polymorphic, not to mention the structural variations especially in CYP2D6, CYP2A6, and CYP2B6. Genome graph-based variant detection approaches have been shown to be reliable for genotyping HLA alleles. However, their application to enhancing star allele calling in CYP genes has not been extensively explored. We present StellarPGx, a Nextflow pipeline for accurately genotyping CYP genes by combining genome graph-based variant detection, read coverage information from the original reference-based alignments, and combinatorial diplotype assignments. The implementation of StellarPGx using Nextflow facilitates its portability, reproducibility, and scalability on various user platforms. StellarPGx is currently able to genotype 12 important pharmacogenes belonging to the CYP1, 2, and 3 families. For purposes of validation, we use CYP2D6 as a model gene owing to its high degree of polymorphisms (over 130 star alleles defined to date, including complex structural variants) and clinical importance. We applied StellarPGx and three existing callers to 109 whole genome sequenced samples for which the Genetic Testing Reference Material Coordination Program (GeT-RM) has recently provided consensus truth CYP2D6 diplotypes. StellarPGx had the highest CYP2D6 diplotype concordance (99%) with GeT-RM compared with Cyrius (98%), Aldy (82%), and Stargazer (84%). This exemplifies the high accuracy of StellarPGx and highlights its importance for both research and clinical pharmacogenomics applications. The StellarPGx pipeline is open-source and available from https://github.com/SBIMB/StellarPGx.

Loss-of-Function Variants in the Tumor-Suppressor Gene PTPN14 Confer Increased Cancer Risk

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 meta-analysis uncovers the first sequence variant conferring risk of Bell's palsy

Bell's palsy is the most common cause of unilateral facial paralysis and is defined as an idiopathic and acute inability to control movements of the facial muscles on the affected side. While the pathogenesis remains unknown, previous studies have implicated post-viral inflammation and resulting compression of the facial nerve. Reported heritability estimates of 4-14% suggest a genetic component in the etiology and an autosomal dominant inheritance has been proposed. Here, we report findings from a meta-analysis of genome-wide association studies uncovering the first unequivocal association with Bell's palsy (rs9357446-A; P = 6.79 × 10^-23, OR = 1.23; N_cases = 4714, N_controls = 1,011,520). The variant also confers risk of intervertebral disc disorders (P = 2.99 × 10^-11, OR = 1.04) suggesting a common pathogenesis in part or a true pleiotropy.

A genome-wide meta-analysis yields 46 new loci associating with biomarkers of iron homeostasis

Iron is essential for many biological functions and iron deficiency and overload have major health implications. We performed a meta-analysis of three genome-wide association studies from Iceland, the UK and Denmark of blood levels of ferritin (N = 246,139), total iron binding capacity (N = 135,430), iron (N = 163,511) and transferrin saturation (N = 131,471). We found 62 independent sequence variants associating with iron homeostasis parameters at 56 loci, including 46 novel loci. Variants at DUOX2, F5, SLC11A2 and TMPRSS6 associate with iron deficiency anemia, while variants at TF, HFE, TFR2 and TMPRSS6 associate with iron overload. A HBS1L-MYB intergenic region variant associates both with increased risk of iron overload and reduced risk of iron deficiency anemia. The DUOX2 missense variant is present in 14% of the population, associates with all iron homeostasis biomarkers, and increases the risk of iron deficiency anemia by 29%. The associations implicate proteins contributing to the main physiological processes involved in iron homeostasis: iron sensing and storage, inflammation, absorption of iron from the gut, iron recycling, erythropoiesis and bleeding/menstruation.

PopDel identifies medium-size deletions simultaneously in tens of thousands of genomes

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.

State-of-the-art genome inference in the human MHC

The Major Histocompatibility Complex (MHC) on the short arm of chromosome 6 is associated with more diseases than any other region of the genome; it encodes the antigen-presenting Human Leukocyte Antigen (HLA) proteins and is one of the key immunogenetic regions of the genome. Accurate genome inference and interpretation of MHC association signals have traditionally been hampered by the region's uniquely complex features, such as high levels of polymorphism; inter-gene sequence homologies; structural variation; and long-range haplotype structures. Recent algorithmic and technological advances have, however, significantly increased the accessibility of genetic variation in the MHC; these developments include (i) accurate SNP-based HLA type imputation; (ii) genome graph approaches for variation-aware genome inference from next-generation sequencing data; (iii) long-read-based diploid de novo assembly of the MHC; (iv) cost-effective targeted MHC sequencing methods. Applied to hundreds of thousands of samples over the last years, these technologies have already enabled significant biological discoveries, for example in the field of autoimmune disease genetics. Remaining challenges concern the development of integrated methods that leverage haplotype-resolved de novo assembly of the MHC for the development of improved MHC genotyping methods for short reads and the construction of improved reference panels for SNP-based imputation. Improved genome inference in the MHC can crucially contribute to an improved genetic and functional understanding of many immune-related phenotypes and diseases.

Differences between germline genomes of monozygotic twins

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.

Estimating Pangenomes with Roary

A description of the genetic makeup of a species based on a single genome is often insufficient because it ignores the variability in gene repertoire among multiple strains. The estimation of the pangenome of a species is a solution to this issue as it provides an overview of genes that are shared by all strains and genes that are present in only some of the genomes. These different sets of genes can then be analyzed functionally to explore correlations with unique phenotypes and adaptations. This protocol presents the usage of Roary, a Linux-native pangenome application. Roary is a straightforward software that provides 1) an overview about core and accessory genes for those interested in general trends and, also, 2) detailed information on gene presence/absence in each genome for in-depth analyses. Results are provided both in text and graphic format.

The design and construction of reference pangenome graphs with minigraph

The recent advances in sequencing technologies enable the assembly of individual genomes to the quality of the reference genome. How to integrate multiple genomes from the same species and make the integrated representation accessible to biologists remains an open challenge. Here, we propose a graph-based data model and associated formats to represent multiple genomes while preserving the coordinate of the linear reference genome. We implement our ideas in the minigraph toolkit and demonstrate that we can efficiently construct a pangenome graph and compactly encode tens of thousands of structural variants missing from the current reference genome.

Sequence Variants in TAAR5 and Other Loci Affect Human Odor Perception and Naming

Olfactory receptor (OR) genes in humans form a special class characterized by unusually high DNA sequence diversity, which should give rise to differences in perception and behavior. In the largest genome-wide association study to date based on olfactory testing, we investigated odor perception and naming with smell tasks performed by 9,122 Icelanders, with replication in a separate sample of 2,204 individuals. We discovered an association between a low-frequency missense variant in TAAR5 and reduced intensity rating of fish odor containing trimethylamine (p.Ser95Pro, p_combined = 5.6 × 10^-15). We demonstrate that TAAR5 genotype affects aversion to fish odor, reflected by linguistic descriptions of the odor and pleasantness ratings. We also discovered common sequence variants in two canonical olfactory receptor loci that associate with increased intensity and naming of licorice odor (trans-anethole: lead variant p.Lys233Asn in OR6C70, p_combined = 8.8 × 10^-16 and p_combined = 1.4 × 10^-9) and enhanced naming of cinnamon (trans-cinnamaldehyde; intergenic variant rs317787-T, p_combined = 5.0 × 10^-17). Together, our results show that TAAR5 genotype variation influences human odor responses and highlight that sequence diversity in canonical OR genes can lead to enhanced olfactory ability, in contrast to the view that greater tolerance for mutations in the human OR repertoire leads to diminished function.

Bovine breed-specific augmented reference graphs facilitate accurate sequence read mapping and unbiased variant discovery

BACKGROUND

The current bovine genomic reference sequence was assembled from a Hereford cow. The resulting linear assembly lacks diversity because it does not contain allelic variation, a drawback of linear references that causes reference allele bias. High nucleotide diversity and the separation of individuals by hundreds of breeds make cattle ideally suited to investigate the optimal composition of variation-aware references.

RESULTS

We augment the bovine linear reference sequence (ARS-UCD1.2) with variants filtered for allele frequency in dairy (Brown Swiss, Holstein) and dual-purpose (Fleckvieh, Original Braunvieh) cattle breeds to construct either breed-specific or pan-genome reference graphs using the vg toolkit. We find that read mapping is more accurate to variation-aware than linear references if pre-selected variants are used to construct the genome graphs. Graphs that contain random variants do not improve read mapping over the linear reference sequence. Breed-specific augmented and pan-genome graphs enable almost similar mapping accuracy improvements over the linear reference. We construct a whole-genome graph that contains the Hereford-based reference sequence and 14 million alleles that have alternate allele frequency greater than 0.03 in the Brown Swiss cattle breed. Our novel variation-aware reference facilitates accurate read mapping and unbiased sequence variant genotyping for SNPs and Indels.

CONCLUSIONS

We develop the first variation-aware reference graph for an agricultural animal ( https://doi.org/10.5281/zenodo.3759712 ). Our novel reference structure improves sequence read mapping and variant genotyping over the linear reference. Our work is a first step towards the transition from linear to variation-aware reference structures in species with high genetic diversity and many sub-populations.

Bovine breed-specific augmented reference graphs facilitate accurate sequence read mapping and unbiased variant discovery

BACKGROUND

The current bovine genomic reference sequence was assembled from a Hereford cow. The resulting linear assembly lacks diversity because it does not contain allelic variation, a drawback of linear references that causes reference allele bias. High nucleotide diversity and the separation of individuals by hundreds of breeds make cattle ideally suited to investigate the optimal composition of variation-aware references.

RESULTS

We augment the bovine linear reference sequence (ARS-UCD1.2) with variants filtered for allele frequency in dairy (Brown Swiss, Holstein) and dual-purpose (Fleckvieh, Original Braunvieh) cattle breeds to construct either breed-specific or pan-genome reference graphs using the vg toolkit. We find that read mapping is more accurate to variation-aware than linear references if pre-selected variants are used to construct the genome graphs. Graphs that contain random variants do not improve read mapping over the linear reference sequence. Breed-specific augmented and pan-genome graphs enable almost similar mapping accuracy improvements over the linear reference. We construct a whole-genome graph that contains the Hereford-based reference sequence and 14 million alleles that have alternate allele frequency greater than 0.03 in the Brown Swiss cattle breed. Our novel variation-aware reference facilitates accurate read mapping and unbiased sequence variant genotyping for SNPs and Indels.

CONCLUSIONS

We develop the first variation-aware reference graph for an agricultural animal ( https://doi.org/10.5281/zenodo.3759712 ). Our novel reference structure improves sequence read mapping and variant genotyping over the linear reference. Our work is a first step towards the transition from linear to variation-aware reference structures in species with high genetic diversity and many sub-populations.

Global Role of Crop Genomics in the Face of Climate Change

The development of climate change resilient crops is necessary if we are to meet the challenge of feeding the growing world's population. We must be able to increase food production despite the projected decrease in arable land and unpredictable environmental conditions. This review summarizes the technological and conceptual advances that have the potential to transform plant breeding, help overcome the challenges of climate change, and initiate the next plant breeding revolution. Recent developments in genomics in combination with high-throughput and precision phenotyping facilitate the identification of genes controlling critical agronomic traits. The discovery of these genes can now be paired with genome editing techniques to rapidly develop climate change resilient crops, including plants with better biotic and abiotic stress tolerance and enhanced nutritional value. Utilizing the genetic potential of crop wild relatives (CWRs) enables the domestication of new species and the generation of synthetic polyploids. The high-quality crop plant genome assemblies and annotations provide new, exciting research targets, including long non-coding RNAs (lncRNAs) and cis-regulatory regions. Metagenomic studies give insights into plant-microbiome interactions and guide selection of optimal soils for plant cultivation. Together, all these advances will allow breeders to produce improved, resilient crops in relatively short timeframes meeting the demands of the growing population and changing climate.

Unexpected conservation and global transmission of agrobacterial virulence plasmids

The accelerated evolution and spread of pathogens are threats to host species. Agrobacteria require an oncogenic Ti or Ri plasmid to transfer genes into plants and cause disease. We developed a strategy to characterize virulence plasmids and applied it to analyze hundreds of strains collected between 1927 and 2017, on six continents and from more than 50 host species. In consideration of prior evidence for prolific recombination, it was surprising that oncogenic plasmids are descended from a few conserved lineages. Characterization of a hierarchy of features that promote or constrain plasticity allowed inference of the evolutionary history across the plasmid lineages. We uncovered epidemiological patterns that highlight the importance of plasmid transmission in pathogen diversification as well as in long-term persistence and the global spread of disease.