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The variation graph toolkit (VG) represents genetic variation as a graph. Each path in the graph is a potential haplotype, though most paths are unlikely recombinations of true haplotypes. We augment the VG model with haplotype information to identify which paths are more likely to be correct. 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 indexing the 1000 Genomes Project haplotypes. We also develop an algorithm for simplifying variation graphs for k-mer indexing without losing any k-mers in the haplotypes.

Abstract Background During the most recent decade many Bayesian statistical models and software for answering questions related to the genetic structure underlying population samples have appeared in the scientific literature. Most of these methods utilize molecular markers for the inferences, while some are also capable of handling DNA sequence data. In a number of earlier works, we have introduced an array of statistical methods for population genetic inference that are implemented in the software BAPS. However, the complexity of biological problems related to genetic structure analysis keeps increasing such that in many cases the current methods may provide either inappropriate or insufficient solutions. Results We discuss the necessity of enhancing the statistical approaches to face the challenges posed by the ever-increasing amounts of molecular data generated by scientists over a wide range of research areas and introduce an array of new statistical tools implemented in the most recent version of BAPS. With these methods it is possible, e.g., to fit genetic mixture models using user-specified numbers of clusters and to estimate levels of admixture under a genetic linkage model. Also, alleles representing a different ancestry compared to the average observed genomic positions can be tracked for the sampled individuals, and a priori specified hypotheses about genetic population structure can be directly compared using Bayes' theorem. In general, we have improved further the computational characteristics of the algorithms behind the methods implemented in BAPS facilitating the analyses of large and complex datasets. In particular, analysis of a single dataset can now be spread over multiple computers using a script interface to the software. Conclusion The Bayesian modelling methods introduced in this article represent an array of enhanced tools for learning the genetic structure of populations. Their implementations in the BAPS software are designed to meet the increasing need for analyzing large-scale population genetics data. The software is freely downloadable for Windows, Linux and Mac OS X systems at http://web.abo.fi/fak/mnf//mate/jc/software/baps.html.

Pangenomes reduce reference bias by representing genetic diversity better than a single reference sequence. Yet when comparing a 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 by filtering rare variants. However, this blunt heuristic both fails to remove some irrelevant variants and removes many relevant variants. We propose a new approach that imputes a personalized pangenome subgraph by sampling local haplotypes according to k-mer counts in the reads. We implement the approach in the vg toolkit ( https://github.com/vgteam/vg ) for the Giraffe short-read aligner and compare its accuracy to state-of-the-art methods using human pangenome graphs from the Human Pangenome Reference Consortium. This reduces small variant genotyping errors by four times relative to the Genome Analysis Toolkit and makes short-read structural variant genotyping of known variants competitive with long-read variant discovery methods., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

The timing of dental development in ethnic Finns and Somalis, who were born and living in Finland, was compared, with efforts to minimize environmental bias. The developmental status of seven lower left permanent teeth were staged according to Demirjian et al., using panoramic radiographs from 2,100 Finnish and 808 Somali females and males, aged 2 to 23 years. For each tooth, a continuation-ratio model was constructed to analyze the allocated stages as a function of sex and ethnic origin. Several statistically significant differences in mean age of certain tooth developmental stage transitions were revealed. While Somalis generally displayed stage transitions at younger age, none of the seven teeth consistently showed earlier stage transitions in Somalis compared to Finns. Within each tooth, the lowest (or highest) mean age of stage transition varied without any discernible pattern between the two ethnic groups. Overall, the observed differences in mean age of stage transition between the groups was minimal, suggesting a low impact on clinical and forensic age assessment practice. In conclusion, the studied ethnic Finn and Somali groups with equal nutritional and /or environmental conditions exhibit similar timing in the development of all lower left permanent teeth., (© 2024. The Author(s).)

Aligning DNA sequences retrieved from fossils or other paleontological artifacts, referred to as ancient DNA, is particularly challenging due to the short sequence length and chemical damage which creates a specific pattern of substitution (C→T and G→A) in addition to the heightened divergence between the sample and the reference genome thus exacerbating reference bias. This bias can be mitigated by aligning to pangenome graphs to incorporate documented organismic variation, but this approach still suffers from substitution patterns due to chemical damage. We introduce a novel methodology introducing the RYmer index, a variant of the commonly-used minimizer index which represents purines (A,G) and pyrimidines (C,T) as R and Y respectively. This creates an indexing scheme robust to the aforementioned chemical damage. We implemented SAFARI, an ancient DNA damage-aware version of the pangenome aligner vg giraffe which uses RYmers to rescue alignments containing deaminated seeds. We show that our approach produces more correct alignments from ancient DNA sequences than current approaches while maintaining a tolerable rate of spurious alignments. In addition, we demonstrate that our algorithm improves the estimate of the rate of ancient DNA damage, especially for highly damaged samples. Crucially, we show that this improved alignment can directly translate into better insights gained from the data by showcasing its integration with a number of extant pangenome tools.

Background: Antitumoral immune response has a crucial role in constraining cancer. However, previous studies on cholangiocarcinoma (CCA), a rare and aggressive cancer, have reported contradictory findings on the prognostic impact of tumor-infiltrating T-lymphocytes. We aimed to clarify the effect of tumor-infiltrating CD3+ and CD8+ lymphocytes and PD-1/PD-L1 expression on CCA prognosis., Methods: CD3+, CD8+, and PD-1+ lymphocyte densities, as well as PD-L1 expression rate were analyzed from stained tissue microarray samples from the tumor center and invasive margin of 47 cholangiocarcinomas. The association of CD3+ and CD8+ based Immune cell score (ICS) and its components with overall survival was evaluated, adjusting for age, sex, TNM stage, radicality of surgery, tumor location, and PD-L1 expression on immune cells., Results: Low ICS was a strong independent prognostic factor for worse overall survival (Hazard ratio 9.27, 95% confidence interval 2.72-31.64, P<0.001). Among the ICS components, high CD8+ lymphocyte infiltration at the tumor center had the most evident impact on patient outcome. PD-1 and PD-L1 expression on immune cells did not have a significant impact on overall survival alone; however, PD-L1 positivity seemed to impair survival for ICS low subgroup., Conclusion: Identifying patient subgroups that could benefit from immunotherapy with PD-1/PD-L1 pathway blockade may help improve treatment strategies for this aggressive cancer. Our findings highlight the importance of evaluating the immune contexture in cholangiocarcinoma, as ICS serves as a strong independent prognostic and selective factor for patients who might benefit from immunotherapy., Competing Interests: TS reports a consultation fee from Amgen Finland, and being a co-owner and CEO of Healthfund Finland Ltd, and the Clinical Advisory Board of LS Cancer Diag Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Wirta, Szeto, Koppatz, Nordin, Mäkisalo, Arola, Sirén, Ahtiainen, Böhm, Mecklin, Sallinen and Seppälä.)

Background: The aim of this study was to assess the incidence of bacterobilia at the time of a pancreaticoduodenectomy (PD) and the association of resistant bacteria in bile to surgical site infections (SSI)., Methods: This was a retrospective cohort study including patients undergoing PD in a single center between May 2016 and October 2020. Data of preoperative biliary drainage (PBD), intraoperative biliary cultures (IBC) and postoperative complications were analysed to assess the risk factors for resistant bacteria in IBC and SSIs., Results: Of 361 patients included, 254 (70%) had undergone PBD. Second-generation cephalosporin resistant bacteria were found in IBC of 183 (64%) of all the patients. PBD was the only risk factor for second-generation cephalosporin resistance. The risk for second-generation cephalosporin resistance was more than 20-fold in patients with PBD [n = 170/254 (67%) (OR 22.58 (95% CI, 9.61-53.01), p < 0.001)] compared to patients who did not have PBD (n = 13/107 (12%)). Also, if the time between PBD and surgery was 2 months or more the second-generation cephalosporin resistance in IBC increased the risk for SSIs (OR 4.14 (95% CI, 1.18-14.51), p = 0.027)., Conclusion: The second-generation cephalosporin resistance in IBC is common in patients who have undergone PBD. Broad-spectrum antibiotics in prophylaxis may be beneficial for these patients., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Objective: Indication-specific optimum field-of-views (FOVs) have been assessed for CBCT scans of impacted maxillary canines and mandibular third molars, as 40∅ × 35 mm and 35∅ × 35 mm, respectively. The objective was to investigate possible changes in absorbed organs and effective doses, for these two imaging indications, performing CBCT examinations with optimum FOV sizes instead of commonly used FOVs. Additionally, radiation exposure-induced cancer risk was calculated for both imaging indications with optimum FOVs., Methods: An adult female head phantom (ATOM 702-D, CIRS, Norfolk, VA, USA) was scanned using Planmeca Viso G7 CBCT-device (Planmeca, Helsinki, Finland). Scanning factors, different FOV sizes, dose-area product (DAP) values and anatomical FOV locations were used for Monte Carlo PCXMC-simulation and ImpactMC software. In the PCXMC- simulation, 10-year-old child and 30-year-old adult phantoms were used to estimating effective and absorbed organ doses., Results: The effective dose varied from 58 µSv to 284 µSv for impacted maxillary canines, and from 38 µSv to 122 µSv for mandibular third molars, the lowest dose value for each corresponding to optimum FOV. Effective dose reduction between the optimum FOV and the smallest common FOV of 50∅ × 50 mm, maintaining other scanning factors constant, was 33% for impacted maxillary canines, and 45% for mandibular third molars. At all examinations, the highest absorbed organ doses were in salivary glands or in oral mucosa., Conclusions: Optimum FOVs, 40∅ × 35 mm for impacted maxillary canine and 35∅ × 35 mm for mandibular third molar, could decrease effective doses received by young patients, and improve radiation safety in these common CBCT imaging procedures.

Objectives: The aim was to analyse the costs and duration of orthodontic-surgical treatment with mandibular advancement in the public health care sector in Finland., Materials: The study was conducted as a retrospective registry study in a public district hospital on all nonsyndromic patients that were ethnic Finns and treated with full fixed appliances and mandibular advancement surgery in 2016-2020., Results: The mean treatment duration of the included 45 patients was 28.1 months, including 18.9 months pre and 9.2 months postoperative orthodontics. The median number of visits was 27, including 17 visits before and 9 visits after surgery. The mean total treatment time was 14.5 h. The mean total direct costs per course of treatment were 7574 € to the municipality and 947 € to the patient. The costs positively correlated with the duration of the treatment (rho = 0.71, P = .000), but were not associated to gender or age of patient. The mean surgery time was 78 minutes, and significantly less with an experienced surgeon (P = .002). It was calculated that the mean minimum treatment costs would be 45% of the present total, achievable with a patient with optimum dental arches at the start of treatment., Limitations: The major limitation of the study is the relatively small number of study subjects., Conclusion: A 55% share of the costs is influenced by case- and operator-dependent factors. This indicates that the complexity and performance of the orthodontic phases of treatment are important determinants in the cost structure., (© The Author(s) 2023. Published by Oxford University Press on behalf of the European Orthodontic Society.)

Viral diversity has been discovered across scales from host individuals to populations. However, the drivers of viral community assembly are still largely unknown. Within-host viral communities are formed through co-infections, where the interval between the arrival times of viruses may vary. Priority effects describe the timing and order in which species arrive in an environment, and how early colonizers impact subsequent community assembly. To study the effect of the first-arriving virus on subsequent infection patterns of five focal viruses, we set up a field experiment using naïve Plantago lanceolata plants as sentinels during a seasonal virus epidemic. Using joint species distribution modelling, we find both positive and negative effects of early season viral infection on late season viral colonization patterns. The direction of the effect depends on both the host genotype and which virus colonized the host early in the season. It is well established that co-occurring viruses may change the virulence and transmission of viral infections. However, our results show that priority effects may also play an important, previously unquantified role in viral community assembly. The assessment of these temporal dynamics within a community ecological framework will improve our ability to understand and predict viral diversity in natural systems.

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 individuals 1 . 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., (© 2023. The Author(s).)

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., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)