Pangenome graph construction from genome alignments with Minigraph-Cactus.

Pangenome references address biases of reference genomes by storing a representative set of diverse haplotypes and their alignment, usually as a graph. Alternate alleles determined by variant callers can be used to construct pangenome graphs, but advances in long-read sequencing are leading to widely available, high-quality phased assemblies. Constructing a pangenome graph directly from assemblies, as opposed to variant calls, leverages the graph's ability to represent variation at different scales. Here we present the Minigraph-Cactus pangenome pipeline, which creates pangenomes directly from whole-genome alignments, and demonstrate its ability to scale to 90 human haplotypes from the Human Pangenome Reference Consortium. The method builds graphs containing all forms of genetic variation while allowing use of current mapping and genotyping tools. We measure the effect of the quality and completeness of reference genomes used for analysis within the pangenomes and show that using the CHM13 reference from the Telomere-to-Telomere Consortium improves the accuracy of our methods. We also demonstrate construction of a Drosophila melanogaster pangenome.

Color Doppler ultrasound versus CT angiography for DIEP flap planning: A randomized controlled trial.

BACKGROUND: Identifying relevant perforators is crucial in planning a deep inferior epigastric perforator (DIEP) flap. Color Doppler ultrasonography (CDU) has gained popularity for localizing perforators; however, current evidence on its efficiency is still inconclusive. This study aimed to compare the efficiency of CDU with that of computed tomography angiography (CTA) in localizing and selecting the relevant perforators. METHODS: In this randomized controlled trial, 60 patients undergoing DIEP flap breast reconstruction (uni- or bilateral) were randomly assigned to the CDU group (i.e., CDU was performed to map and select the relevant perforators preoperatively) or the CTA+CDU group (i.e., mapping was based on CTA and supplemented by CDU). CDU was performed by the same surgeon with a well-defined sonography experience from our previous study. The reference XY coordinates of the dissected perforators were measured intraoperatively, and deviations from preoperatively deducted coordinates were calculated (ΔCDU or ΔCTA+CDU). The flaps were categorized according to the number of dissected perforators, and adherence to the preoperative strategy was evaluated. RESULTS: Overall, 22 patients (30 flaps) in the CTA+CDU group and 27 (39 flaps) patients in the CDU group were evaluated. The average ΔCDU (0.6 cm) was significantly lower than the average ΔCTA+CDU (1.0 cm) (p < 0.001). Adherence to the mapping-based dissection strategy was higher in the CDU group; however, the difference was insignificant (p = 0.092). CONCLUSION: CDU is not inferior to CTA + CDU in localizing and selecting relevant DIEA perforators. Therefore, CDU mapping is a possible complementary or substitute modality for CTA mapping.

A draft human pangenome reference.

Here the Human Pangenome Reference Consortium presents a first draft of the human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals1. These assemblies cover more than 99% of the expected sequence in each genome and are more than 99% accurate at the structural and base pair levels. Based on alignments of the assemblies, we generate a draft pangenome that captures known variants and haplotypes and reveals new alleles at structurally complex loci. We also add 119 million base pairs of euchromatic polymorphic sequences and 1,115 gene duplications relative to the existing reference GRCh38. Roughly 90 million of the additional base pairs are derived from structural variation. Using our draft pangenome to analyse short-read data reduced small variant discovery errors by 34% and increased the number of structural variants detected per haplotype by 104% compared with GRCh38-based workflows, which enabled the typing of the vast majority of structural variant alleles per sample.

Haplotype-aware pantranscriptome analyses using spliced pangenome graphs.

Pangenomics is emerging as a powerful computational paradigm in bioinformatics. This field uses population-level genome reference structures, typically consisting of a sequence graph, to mitigate reference bias and facilitate analyses that were challenging with previous reference-based methods. In this work, we extend these methods into transcriptomics to analyze sequencing data using the pantranscriptome: a population-level transcriptomic reference. Our toolchain, which consists of additions to the VG toolkit and a standalone tool, RPVG, can construct spliced pangenome graphs, map RNA sequencing data to these graphs, and perform haplotype-aware expression quantification of transcripts in a pantranscriptome. We show that this workflow improves accuracy over state-of-the-art RNA sequencing mapping methods, and that it can efficiently quantify haplotype-specific transcript expression without needing to characterize the haplotypes of a sample beforehand.

Surgeon-conducted color Doppler ultrasound deep inferior epigastric artery perforator mapping: A cohort study and learning curve assessment.

BACKGROUND: Perforator mapping using diagnostic methods facilitates deep inferior epigastric perforator (DIEP) flap planning. Computed tomographic angiography (CTA) is a well-proven tool for perforator mapping. However, the benefits of color Doppler ultrasonography (CDU) are as follows: 1) CDU involves dynamic real-time examination and 2) does not use radiation. Comparing the accuracies of both methods in a cohort of patients, this study aimed to evaluate the learning curve of surgeon-conducted CDU perforator mapping. METHODS: Twenty patients undergoing DIEP flap breast reconstruction were enrolled in a cohort study. All patients underwent CTA perforator mapping preoperatively. XY coordinates of significant perforators were subtracted by a radiologist. A single surgeon (sonographer) with minimal experience with CDU performed CDU perforator mapping, including XY coordinates subtraction. The sonographer was blinded to the CTA data. The reference coordinates of dissected perforators were measured during surgery. Deviations from reference coordinates for both methods were compared, and CDU mapping learning curve was assessed using Joinpoint Regression. RESULTS: We included 20 women (32 DIEP flaps and 59 dissected perforators). The mean deviation between mapped and reference coordinates was 1.00 (0.50-1.12) cm for CDU and 0.71 (0.50-1.12) cm for CTA. The learning curve of CDU mapping showed the breaking point after the seventh patient (≈ 21 localized perforators). After the breaking point, no significant differences between the deviations of both methods were found (p = 0.980). CONCLUSION: A limited number of examinations were needed for the surgeon to learn CDU DIEA perforator mapping with accuracy similar to that of CTA mapping.

Personalized Pangenome References.

Pangenomes, by including genetic diversity, should reduce reference bias by better representing new samples compared to them. Yet when comparing a new sample to a pangenome, variants in the pangenome that are not part of the sample can be misleading, for example, causing false read mappings. These irrelevant variants are generally rarer in terms of allele frequency, and have previously been dealt with using allele frequency filters. However, this is a blunt heuristic that both fails to remove some irrelevant variants and removes many relevant variants. We propose a new approach, inspired by local ancestry inference methods, that imputes a personalized pangenome subgraph based on sampling local haplotypes according to k-mer counts in the reads. Our approach is tailored for the Giraffe short read aligner, as the indexes it needs for read mapping can be built quickly. We compare the accuracy of our approach to state-of-the-art methods using graphs from the Human Pangenome Reference Consortium. The resulting personalized pangenome pipelines provide faster pangenome read mapping than comparable pipelines that use a linear reference, reduce small variant genotyping errors by 4x relative to the Genome Analysis Toolkit (GATK) best-practice pipeline, and for the first time make short-read structural variant genotyping competitive with long-read discovery methods.

The Human Pangenome Project: a global resource to map genomic diversity.

The human reference genome is the most widely used resource in human genetics and is due for a major update. Its current structure is a linear composite of merged haplotypes from more than 20 people, with a single individual comprising most of the sequence. It contains biases and errors within a framework that does not represent global human genomic variation. A high-quality reference with global representation of common variants, including single-nucleotide variants, structural variants and functional elements, is needed. The Human Pangenome Reference Consortium aims to create a more sophisticated and complete human reference genome with a graph-based, telomere-to-telomere representation of global genomic diversity. Here we leverage innovations in technology, study design and global partnerships with the goal of constructing the highest-possible quality human pangenome reference. Our goal is to improve data representation and streamline analyses to enable routine assembly of complete diploid genomes. With attention to ethical frameworks, the human pangenome reference will contain a more accurate and diverse representation of global genomic variation, improve gene-disease association studies across populations, expand the scope of genomics research to the most repetitive and polymorphic regions of the genome, and serve as the ultimate genetic resource for future biomedical research and precision medicine.

Oil-Based Mud Waste as a Filler Material in LDPE Composites: Evaluation of Mechanical Properties.

Traditionally, the drilling waste generated in oil and gas exploration operations, including spent drilling fluid, is disposed of or treated by several methods, including burial pits, landfill sites and various thermal treatments. This study investigates drilling waste valorisation and its use as filler in polymer composites. The effect of the poor particle/polymer interfacial adhesion bonding of the suspended clay in oil-based mud (OBM) slurry and the LDPE matrix is believed to be the main reason behind the poor thermo-mechanical and mechanical properties of low-density polyethylene (LDPE)/OBM slurry nanocomposites. The thermo-mechanical and mechanical performances of LDPE)/OBM slurry nanocomposites without the clay surface treatment and without using compatibilizer are evaluated and discussed. In our previous studies, it has been observed that adding thermally treated reclaimed clay from OBM waste in powder form improves both the thermal and mechanical properties of LDPE nanocomposites. However, incorporating OBM clay in slurry form in the LDPE matrix can decrease the thermal stability remarkably, which was reported recently, and thereby has increased the interest to identify the mechanical response of the composite material after adding this filler. The results show the severe deterioration of the tensile and flexural properties of the LDPE/OBM slurry composites compared to those properties of the LDPE/MMT nanocomposites in this study. It is hypothesised, based on the observation of the different test results in this study, that this deterioration in the mechanical properties of the materials was associated with the poor Van der Waals force between the polymer molecules/clay platelets and the applied force. The decohesion between the matrix and OBM slurry nanoparticles under stress conditions generated stress concentration through the void area between the matrix and nanoparticles, resulting in sample failure. Interfacial adhesion bonding appears to be a key factor influencing the mechanical properties of the manufactured nanocomposite materials.

Pangenomics enables genotyping of known structural variants in 5202 diverse genomes.

We introduce Giraffe, a pangenome short-read mapper that can efficiently map to a collection of haplotypes threaded through a sequence graph. Giraffe maps sequencing reads to thousands of human genomes at a speed comparable to that of standard methods mapping to a single reference genome. The increased mapping accuracy enables downstream improvements in genome-wide genotyping pipelines for both small variants and larger structural variants. We used Giraffe to genotype 167,000 structural variants, discovered in long-read studies, in 5202 diverse human genomes that were sequenced using short reads. We conclude that pangenomics facilitates a more comprehensive characterization of variation and, as a result, has the potential to improve many genomic analyses.

Signaling through Syk or CARD9 Mediates Species-Specific Anti-Candida Protection in Bone Marrow Chimeric Mice.

The spleen tyrosine kinase (Syk) and the downstream adaptor protein CARD9 are crucial signaling molecules in antimicrobial immunity. Candida parapsilosis is an emerging fungal pathogen with a high incidence in neonates, while Candida albicans is the most common agent of candidiasis. While signaling through Syk/CARD9 promotes protective host mechanisms in response to C. albicans, its function in immunity against C. parapsilosis remains unclear. Here, we generated Syk-/- and CARD9-/- bone marrow chimeric mice to study the role of Syk/CARD9 signaling in immune responses to C. parapsilosis compared to C. albicans. We demonstrate various functions of this pathway (e.g., phagocytosis, phagosome acidification, and killing) in Candida-challenged, bone marrow-derived macrophages with differential involvement of Syk and CARD9 along with species-specific differences in cytokine production. We report that Syk-/- or CARD9-/- chimeras rapidly display high susceptibility to C. albicans, while C. parapsilosis infection exacerbates over a prolonged period in these animals. Thus, our results establish that Syk and CARD9 contribute to systemic resistance to C. parapsilosis and C. albicans differently. Additionally, we confirm prior studies but also detail new insights into the fundamental roles of both proteins in immunity against C. albicans. Our data further suggest that Syk has a more prominent influence on anti-Candida immunity than CARD9. Therefore, this study reinforces the Syk/CARD9 pathway as a potential target for anti-Candida immune therapy. IMPORTANCE While C. albicans remains the most clinically significant Candida species, C. parapsilosis is an emerging pathogen with increased affinity to neonates. Syk/CARD9 signaling is crucial in immunity to C. albicans, but its role in in vivo responses to other pathogenic Candida species is largely unexplored. We used mice with hematopoietic systems deficient in Syk or CARD9 to comparatively study the function of these proteins in anti-Candida immunity. We demonstrate that Syk/CARD9 signaling has a protective role against C. parapsilosis differently than against C. albicans. Thus, this study is the first to reveal that Syk can exert immune responses during systemic Candida infections species specifically. Additionally, Syk-dependent immunity to a nonalbicans Candida species in an in vivo murine model has not been reported previously. We highlight that the contribution of Syk and CARD9 to fungal infections are not identical and underline this pathway as a promising immune-therapeutic target to fight Candida infections.

Efficient dynamic variation graphs.

MOTIVATION: Pangenomics is a growing field within computational genomics. Many pangenomic analyses use bidirected sequence graphs as their core data model. However, implementing and correctly using this data model can be difficult, and the scale of pangenomic datasets can be challenging to work at. These challenges have impeded progress in this field. RESULTS: Here, we present a stack of two C++ libraries, libbdsg and libhandlegraph, which use a simple, field-proven interface, designed to expose elementary features of these graphs while preventing common graph manipulation mistakes. The libraries also provide a Python binding. Using a diverse collection of pangenome graphs, we demonstrate that these tools allow for efficient construction and manipulation of large genome graphs with dense variation. For instance, the speed and memory usage are up to an order of magnitude better than the prior graph implementation in the VG toolkit, which has now transitioned to using libbdsg's implementations. AVAILABILITY AND IMPLEMENTATION: libhandlegraph and libbdsg are available under an MIT License from https://github.com/vgteam/libhandlegraph and https://github.com/vgteam/libbdsg.

Progressive Cactus is a multiple-genome aligner for the thousand-genome era.

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

Distance indexing and seed clustering in sequence graphs.

MOTIVATION: Graph representations of genomes are capable of expressing more genetic variation and can therefore better represent a population than standard linear genomes. However, due to the greater complexity of genome graphs relative to linear genomes, some functions that are trivial on linear genomes become much more difficult in genome graphs. Calculating distance is one such function that is simple in a linear genome but complicated in a graph context. In read mapping algorithms such distance calculations are fundamental to determining if seed alignments could belong to the same mapping. RESULTS: We have developed an algorithm for quickly calculating the minimum distance between positions on a sequence graph using a minimum distance index. We have also developed an algorithm that uses the distance index to cluster seeds on a graph. We demonstrate that our implementations of these algorithms are efficient and practical to use for a new generation of mapping algorithms based upon genome graphs. AVAILABILITY AND IMPLEMENTATION: Our algorithms have been implemented as part of the vg toolkit and are available at https://github.com/vgteam/vg.

Pangenome Graphs.

Low-cost whole-genome assembly has enabled the collection of haplotype-resolved pangenomes for numerous organisms. In turn, this technological change is encouraging the development of methods that can precisely address the sequence and variation described in large collections of related genomes. These approaches often use graphical models of the pangenome to support algorithms for sequence alignment, visualization, functional genomics, and association studies. The additional information provided to these methods by the pangenome allows them to achieve superior performance on a variety of bioinformatic tasks, including read alignment, variant calling, and genotyping. Pangenome graphs stand to become a ubiquitous tool in genomics. Although it is unclear whether they will replace linearreference genomes, their ability to harmoniously relate multiple sequence and coordinate systems will make them useful irrespective of which pangenomic models become most common in the future.

Genotyping structural variants in pangenome graphs using the vg toolkit.

Structural variants (SVs) remain challenging to represent and study relative to point mutations despite their demonstrated importance. We show that variation graphs, as implemented in the vg toolkit, provide an effective means for leveraging SV catalogs for short-read SV genotyping experiments. We benchmark vg against state-of-the-art SV genotypers using three sequence-resolved SV catalogs generated by recent long-read sequencing studies. In addition, we use assemblies from 12 yeast strains to show that graphs constructed directly from aligned de novo assemblies improve genotyping compared to graphs built from intermediate SV catalogs in the VCF format.

Haplotype-aware graph indexes.

MOTIVATION: The variation graph toolkit (VG) represents genetic variation as a graph. Although each path in the graph is a potential haplotype, most paths are non-biological, unlikely recombinations of true haplotypes. RESULTS: We augment the VG model with haplotype information to identify which paths are more likely to exist in nature. For this purpose, we develop a scalable implementation of the graph extension of the positional Burrows-Wheeler transform. We demonstrate the scalability of the new implementation by building a whole-genome index of the 5008 haplotypes of the 1000 Genomes Project, and an index of all 108 070 Trans-Omics for Precision Medicine Freeze 5 chromosome 17 haplotypes. We also develop an algorithm for simplifying variation graphs for k-mer indexing without losing any k-mers in the haplotypes. AVAILABILITY AND IMPLEMENTATION: Our software is available at https://github.com/vgteam/vg, https://github.com/jltsiren/gbwt and https://github.com/jltsiren/gcsa2. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Role of Protein Mannosylation in the Candida tropicalis-Host Interaction.

Mannans are components of the fungal wall attached to proteins via N- or O-linkages. In Candida albicans, Och1 is an α1,6-mannosyltransferase that adds the first mannose unit to the N-linked mannan outer chain; whereas Pmr1 is an ion pump that imports Mn2+ into the Golgi lumen. This cation is the cofactor of Golgi-resident mannosyltransferases, and thus Pmr1 is involved in the synthesis of both N- and O-linked mannans. Since we currently have limited information about the genetic network behind the Candida tropicalis protein mannosylation machinery, we disrupted OCH1 and PMR1 in this organism. The C. tropicalis pmr1Δ and och1Δ mutants showed increased doubling times, aberrant colony and cellular morphology, reduction in the wall mannan content, and increased susceptibility to wall perturbing agents. These changes were accompanied by increased exposure of both ß1,3-glucan and chitin at the wall surface of both mutant strains. Our results showed that O-linked mannans are dispensable for cytokine production by human mononuclear cells, but N-linked mannans and ß1,3-glucan are key ligands to trigger cytokine production in a co-stimulatory pathway involving dectin-1 and mannose receptor. Moreover, we found that the N-linked mannan core found on the surface of C. tropicalis och1Δ null mutant was capable of inducing cytokine production; and that a mannan-independent pathway for IL-10 production is present in the C. tropicalis-mononuclear cell interaction. Both mutant strains showed virulence attenuation in the Galleria mellonella and the mouse model of systemic candidiasis. Therefore, mannans are relevant for cell wall composition and organization, and for the C. tropicalis-host interaction.

Sequence tube maps: making graph genomes intuitive to commuters.

MOTIVATION: Compared to traditional haploid reference genomes, graph genomes are an efficient and compact data structure for storing multiple genomic sequences, for storing polymorphisms or for mapping sequencing reads with greater sensitivity. Further, graphs are well-studied computer science objects that can be efficiently analyzed. However, their adoption in genomic research is slow, in part because of the cognitive difficulty in interpreting graphs. RESULTS: We present an intuitive graphical representation for graph genomes that re-uses well-honed techniques developed to display public transport networks, and demonstrate it as a web tool. AVAILABILITY AND IMPLEMENTATION: Code: https://github.com/vgteam/sequenceTubeMap. DEMONSTRATION: https://vgteam.github.io/sequenceTubeMap/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Improving safety through speaking up: An ethical and financial imperative.

BACKGROUND: Fostering a culture that empowers staff to speak up when concerned about the quality or safety of patient care is both an ethically1 and economically2 responsible endeavor. The Michigan Health & Hospital Association (MHA) Keystone Center has implemented the Speak-Up! Award program that acknowledges frontline health care staff for voicing their concerns and making care safer. The objective of this effort was to advance patient safety in Keystone Center member organizations through widespread, measurable culture improvement. After extensive data collection and analysis, there was a discernable improvement in culture survey results across a 2-year period coinciding with the launch and sustainment of the award program. Furthermore, in an effort to demonstrate the power of speaking up among staff, the Keystone Center applied a cost-savings framework to the types of harm avoided. Results from the cost-savings analysis suggest that each instance of speaking up by staff saves patients, families, and health care organizations an average of more than $13,000. METHODS: Keystone Center Speak-Up! Award nominations were submitted through an electronic form that collects open, closed, and Likert-type question responses, producing a data array on type and severity of harm prevented, as well as the difficulty and magnitude of the decision to speak up. All data were then coded by harm type and subsequently applied to a tailored version of the cost-savings estimation framework used in the Great Lakes Partnership for Patients Hospital Improvement and Innovation Network. Safety culture was measured through the use of a survey instrument called the Safety, Communication, Operational Reliability, and Engagement (SCORE) instrument. RESULTS: The Keystone Center Speak-Up! Award program received 416 nominations across the 2-year study period, of which 62% (n = 258) were coded as a specific harm type. Adverse drug events (n = 153), imaging errors (n = 42), and specimen errors (n = 27) were the most common harm types prevented by speaking up. After applying the cost-savings framework to these data, it is estimated that for every instance of speaking up, approximately $13,000 in total expenses were avoided, which is in line with the findings from a report on the economic impact of medical errors sponsored by the Society of Actuaries.3 Furthermore, culture survey results improved by 6% between 2015 and 2017, coinciding with the Keystone Center Speak-Up! Award program. CONCLUSIONS: The Keystone Center Speak-Up! Award has proven to be a valuable tool in recognizing staff awareness and willingness to raise concerns about quality and safety in health care. Data analysis from this program presents evidence that fostering a psychologically safe culture of speaking up yields fiscal and humanistic returns, both of which are crucial to sustainable, meaningful progress in safety and quality. However, further research is required to adequately gauge the degree to which safety culture improvement is proportional to cost savings.

A strategy for building and using a human reference pangenome.

In March 2019, 45 scientists and software engineers from around the world converged at the University of California, Santa Cruz for the first pangenomics codeathon. The purpose of the meeting was to propose technical specifications and standards for a usable human pangenome as well as to build relevant tools for genome graph infrastructures. During the meeting, the group held several intense and productive discussions covering a diverse set of topics, including advantages of graph genomes over a linear reference representation, design of new methods that can leverage graph-based data structures, and novel visualization and annotation approaches for pangenomes. Additionally, the participants self-organized themselves into teams that worked intensely over a three-day period to build a set of pipelines and tools for specific pangenomic applications. A summary of the questions raised and the tools developed are reported in this manuscript.