Correction: PPanGGOLiN: Depicting microbial diversity via a partitioned pangenome graph.
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ABSTRACT:
SUBMITTER: Gautreau G
PROVIDER: S-EPMC8664182 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The use of comparative genomics for functional, evolutionary, and epidemiological studies requires methods to classify gene families in terms of occurrence in a given species. These methods usually lack multivariate statistical models to infer the partitions and the optimal number of classes and don't account for genome organization. We introduce a graph structure to model pangenomes in which nodes represent gene families and edges represent genomic neighborhood. Our method, named PPanGGOLiN, partitions nodes using an Expectation-Maximization algorithm based on multivariate Bernoulli Mixture Model coupled with a Markov Random Field. This approach takes into account the topology of the graph and the presence/absence of genes in pangenomes to classify gene families into persistent, cloud, and one or several shell partitions. By analyzing the partitioned pangenome graphs of isolate genomes from 439 species and metagenome-assembled genomes from 78 species, we demonstrate that our method is effective in estimating the persistent genome. Interestingly, it shows that the shell genome is a key element to understand genome dynamics, presumably because it reflects how genes present at intermediate frequencies drive adaptation of species, and its proportion in genomes is independent of genome size. The graph-based approach proposed by PPanGGOLiN is useful to depict the overall genomic diversity of thousands of strains in a compact structure and provides an effective basis for very large scale comparative genomics. The software is freely available at https://github.com/labgem/PPanGGOLiN.
| S-EPMC7108747 | biostudies-literature
Project description:MotivationThe increasing availability of complete genomes demands for models to study genomic variability within entire populations. Pangenome graphs capture the full genomic similarity and diversity between multiple genomes. In order to understand them, we need to see them. For visualization, we need a human readable graph layout: A graph embedding in low (e.g. two) dimensional depictions. Due to a pangenome graph's potential excessive size, this is a significant challenge.ResultsIn response, we introduce a novel graph layout algorithm: the Path-Guided Stochastic Gradient Descent (PG-SGD). PG-SGD uses the genomes, represented in the pangenome graph as paths, as an embedded positional system to sample genomic distances between pairs of nodes. This avoids the quadratic cost seen in previous versions of graph drawing by Stochastic Gradient Descent (SGD). We show that our implementation efficiently computes the low dimensional layouts of gigabase-scale pangenome graphs, unveiling their biological features.AvailabilityWe integrated PG-SGD in ODGI which is released as free software under the MIT open source license. Source code is available at https://github.com/pangenome/odgi.
| S-EPMC10542513 | biostudies-literature
Project description:Missing heritability in genome-wide association studies defines a major problem in genetic analyses of complex biological traits1,2. The solution to this problem is to identify all causal genetic variants and to measure their individual contributions3,4. Here we report a graph pangenome of tomato constructed by precisely cataloguing more than 19 million variants from 838 genomes, including 32 new reference-level genome assemblies. This graph pangenome was used for genome-wide association study analyses and heritability estimation of 20,323 gene-expression and metabolite traits. The average estimated trait heritability is 0.41 compared with 0.33 when using the single linear reference genome. This 24% increase in estimated heritability is largely due to resolving incomplete linkage disequilibrium through the inclusion of additional causal structural variants identified using the graph pangenome. Moreover, by resolving allelic and locus heterogeneity, structural variants improve the power to identify genetic factors underlying agronomically important traits leading to, for example, the identification of two new genes potentially contributing to soluble solid content. The newly identified structural variants will facilitate genetic improvement of tomato through both marker-assisted selection and genomic selection. Our study advances the understanding of the heritability of complex traits and demonstrates the power of the graph pangenome in crop breeding.
| S-EPMC9200638 | biostudies-literature
Project description:BackgroundThe reliance on a solitary linear reference genome has imposed a significant constraint on our comprehensive understanding of genetic variation in animals. This constraint is particularly pronounced for non-reference sequences (NRSs), which have not been extensively studied.ResultsIn this study, we constructed a pig pangenome graph using 21 pig assemblies and identified 23,831 NRSs with a total length of 105 Mb. Our findings revealed that NRSs were more prevalent in breeds exhibiting greater genetic divergence from the reference genome. Furthermore, we observed that NRSs were rarely found within coding sequences, while NRS insertions were enriched in immune-related Gene Ontology terms. Notably, our investigation also unveiled a close association between novel genes and the immune capacity of pigs. We observed substantial differences in terms of frequencies of NRSs between Eastern and Western pigs, and the heat-resistant pigs exhibited a substantial number of NRS insertions in an 11.6 Mb interval on chromosome X. Additionally, we discovered a 665 bp insertion in the fourth intron of the TNFRSF19 gene that may be associated with the ability of heat tolerance in Southern Chinese pigs.ConclusionsOur findings demonstrate the potential of a graph genome approach to reveal important functional features of NRSs in pig populations.
| S-EPMC10882747 | biostudies-literature
Project description:BackgroundA revolutionary diversion from classical vaccinology to reverse vaccinology approach has been observed in the last decade. The ever-increasing genomic and proteomic data has greatly facilitated the vaccine designing and development process. Reverse vaccinology is considered as a cost-effective and proficient approach to screen the entire pathogen genome. To look for broad-spectrum immunogenic targets and analysis of closely-related bacterial species, the assimilation of pangenome concept into reverse vaccinology approach is essential. The categories of species pangenome such as core, accessory, and unique genes sets can be analyzed for the identification of vaccine candidates through reverse vaccinology.ResultsWe have designed an integrative computational pipeline term as "PanRV" that employs both the pangenome and reverse vaccinology approaches. PanRV comprises of four functional modules including i) Pangenome Estimation Module (PGM) ii) Reverse Vaccinology Module (RVM) iii) Functional Annotation Module (FAM) and iv) Antibiotic Resistance Association Module (ARM). The pipeline is tested by using genomic data from 301 genomes of Staphylococcus aureus and the results are verified by experimentally known antigenic data.ConclusionThe proposed pipeline has proved to be the first comprehensive automated pipeline that can precisely identify putative vaccine candidates exploiting the microbial pangenome. PanRV is a Linux based package developed in JAVA language. An executable installer is provided for ease of installation along with a user manual at https://sourceforge.net/projects/panrv2/ .
| S-EPMC6419457 | biostudies-literature
Project description:Summary:Genome-wide association studies (GWAS) in microbes have different challenges to GWAS in eukaryotes. These have been addressed by a number of different methods. pyseer brings these techniques together in one package tailored to microbial GWAS, allows greater flexibility of the input data used, and adds new methods to interpret the association results. Availability and implementation:pyseer is written in python and is freely available at https://github.com/mgalardini/pyseer, or can be installed through pip. Documentation and a tutorial are available at http://pyseer.readthedocs.io. Supplementary information:Supplementary data are available at Bioinformatics online.
| S-EPMC6289128 | biostudies-literature
Project description:The arms race between bacteria and phages led to the development of sophisticated antiphage defense systems, including CRISPR-Cas and restriction-modification systems. Evidence suggests that known and unknown defense systems are located in "defense islands" in microbial genomes. Here, we comprehensively characterized the bacterial defensive arsenal by examining gene families that are clustered next to known defense genes in prokaryotic genomes. Candidate defense systems were systematically engineered and validated in model bacteria for their antiphage activities. We report nine previously unknown antiphage systems and one antiplasmid system that are widespread in microbes and strongly protect against foreign invaders. These include systems that adopted components of the bacterial flagella and condensin complexes. Our data also suggest a common, ancient ancestry of innate immunity components shared between animals, plants, and bacteria.
| S-EPMC6387622 | biostudies-literature
Project description:This study presents the first chromosome-level genome assembly of Hanwoo, an indigenous Korean breed of Bos taurus taurus. This is the first genome assembly of Asian taurus breed. Also, we constructed a pangenome graph of 14 B. taurus genome assemblies. The contig N50 was over 55 Mb, the scaffold N50 was over 89 Mb and a genome completeness of 95.8%, as estimated by BUSCO using the mammalian set, indicated a high-quality assembly. 48.7% of the genome comprised various repetitive elements, including DNAs, tandem repeats, long interspersed nuclear elements, and simple repeats. A total of 27,314 protein-coding genes were identified, including 25,302 proteins with inferred gene names and 2,012 unknown proteins. The pangenome graph of 14 B. taurus autosomes revealed 528.47 Mb non-reference regions in total and 61.87 Mb Hanwoo-specific regions. Our Hanwoo assembly and pangenome graph provide valuable resources for studying B. taurus populations.
| S-EPMC10447506 | biostudies-literature
Project description:BackgroundThe red junglefowl, the wild outgroup of domestic chickens, has historically served as a reference for genomic studies of domestic chickens. These studies have provided insight into the etiology of traits of commercial importance. However, the use of a single reference genome does not capture diversity present among modern breeds, many of which have accumulated molecular changes due to drift and selection. While reference-based resequencing is well-suited to cataloging simple variants such as single-nucleotide changes and short insertions and deletions, it is mostly inadequate to discover more complex structural variation in the genome.MethodsWe present a pangenome for the domestic chicken consisting of thirty assemblies of chickens from different breeds and research lines.ResultsWe demonstrate how this pangenome can be used to catalog structural variants present in modern breeds and untangle complex nested variation. We show that alignment of short reads from 100 diverse wild and domestic chickens to this pangenome reduces reference bias by 38%, which affects downstream genotyping results. This approach also allows for the accurate genotyping of a large and complex pair of structural variants at the K feathering locus using short reads, which would not be possible using a linear reference.ConclusionsWe expect that this new paradigm of genomic reference will allow better pinpointing of exact mutations responsible for specific phenotypes, which will in turn be necessary for breeding chickens that meet new sustainability criteria and are resilient to quickly evolving pathogen threats.
| S-EPMC10664547 | biostudies-literature
Project description:MotivationA pangenome represents many diverse genome sequences of the same species. In order to cope with small variations as well as structural variations, recent research focused on the development of graph based models of pangenomes. Mapping is the process of finding the original location of a DNA read in a reference sequence, typically a genome. Using a pangenome instead of a (linear) reference genome can e.g. reduce mapping bias, the tendency to incorrectly map sequences that differ from the reference genome. Mapping reads to a graph, however, is more complex and needs more resources than mapping to a reference genome. Reducing the complexity of the graph by encoding simple variations like SNPs in a simple way can accelerate read mapping and reduce the memory requirements at the same time.ResultsWe introduce graphs based on elastic-degenerate strings (ED strings, EDS) and the linearised form of these EDS graphs as a new representation for pangenomes. In this representation, small variations are encoded directly in the sequence. Structural variations are encoded in a graph structure. This reduces the size of the representation in comparison to sequence graphs. In the linearised form, mapping techniques that are known from ordinary strings can be applied with appropriate adjustments. Since most variations are expressed directly in the sequence, the mapping process rarely has to take edges of the EDS graph into account. We developed a prototypical software tool GED-MAP that uses this representation together with a minimizer index to map short reads to the pangenome. Our experiments show that the new method works on a whole human genome scale, taking structural variants properly into account. The advantage of GED-MAP, compared with other pangenomic short read mappers, is that the new representation allows for a simple indexing method. This makes GED-MAP fast and memory efficient.AvailabilitySources are available at: https://github.com/thomas-buechler-ulm/gedmap.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC10232250 | biostudies-literature