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Vieira Mourato B, Tsers I, Denker S, Klötzl F, Haubold B. Marker discovery in the large. BIOINFORMATICS ADVANCES 2024; 4:vbae113. [PMID: 39132289 PMCID: PMC11310107 DOI: 10.1093/bioadv/vbae113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/16/2024] [Revised: 07/06/2024] [Accepted: 07/26/2024] [Indexed: 08/13/2024]
Abstract
Motivation Markers for diagnostic polymerase chain reactions are routinely constructed by taking regions common to the genomes of a target organism and subtracting the regions found in the targets' closest relatives, their neighbors. This approach is implemented in the published package Fur, which originally required memory proportional to the number of nucleotides in the neighborhood. This does not scale well. Results Here, we describe a new version of Fur that only requires memory proportional to the longest neighbor. In spite of its greater memory efficiency, the new Fur remains fast and is accurate. We demonstrate this by applying it to simulated sequences and comparing it to an efficient alternative. Then we use the new Fur to extract markers from 120 reference bacteria. To make this feasible, we also introduce software for automatically finding target and neighbor genomes and for assessing markers. We pick the best primers from the 10 most sequenced reference bacteria and show their excellent in silico sensitivity and specificity. Availability and implementation Fur is available from github.com/evolbioinf/fur, in the Docker image hub.docker.com/r/beatrizvm/mapro, and in the Code Ocean capsule 10.24433/CO.7955947.v1.
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Affiliation(s)
- Beatriz Vieira Mourato
- Research Group Bioinformatics, Max-Planck-Institute for Evolutionary Biology, 24306 Plön, Schleswig-Holstein, Germany
| | - Ivan Tsers
- Research Group Bioinformatics, Max-Planck-Institute for Evolutionary Biology, 24306 Plön, Schleswig-Holstein, Germany
| | - Svenja Denker
- Research Group Bioinformatics, Max-Planck-Institute for Evolutionary Biology, 24306 Plön, Schleswig-Holstein, Germany
- Universität zu Lübeck, Lübeck, Schleswig-Holstein, Germany
| | | | - Bernhard Haubold
- Research Group Bioinformatics, Max-Planck-Institute for Evolutionary Biology, 24306 Plön, Schleswig-Holstein, Germany
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Kadibalban AS, Landan G, Dagan T. The extent and characteristics of DNA transfer between plasmids and chromosomes. Curr Biol 2024; 34:3189-3200.e5. [PMID: 38964320 DOI: 10.1016/j.cub.2024.06.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 03/29/2024] [Accepted: 06/10/2024] [Indexed: 07/06/2024]
Abstract
Plasmids are extrachromosomal genetic elements that reside in prokaryotes. The acquisition of plasmids encoding beneficial traits can facilitate short-term survival in harsh environmental conditions or long-term adaptation of new ecological niches. Due to their ability to transfer between cells, plasmids are considered agents of gene transfer. Nonetheless, the frequency of DNA transfer between plasmids and chromosomes remains understudied. Using a novel approach for detection of homologous loci between genome pairs, we uncover gene sharing with the chromosome in 1,974 (66%) plasmids residing in 1,016 (78%) taxonomically diverse isolates. The majority of homologous loci correspond to mobile elements, which may be duplicated in the host chromosomes in tens of copies. Neighboring shared genes often encode similar functional categories, indicating the transfer of multigene functional units. Rare transfer events of antibiotics resistance genes are observed mainly with mobile elements. The frequent erosion of sequence similarity in homologous regions indicates that the transferred DNA is often devoid of function. DNA transfer between plasmids and chromosomes thus generates genetic variation that is akin to workings of endosymbiotic gene transfer in eukaryotic evolution. Our findings imply that plasmid contribution to gene transfer most often corresponds to transfer of the plasmid entity rather than transfer of protein-coding genes between plasmids and chromosomes.
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Affiliation(s)
- A Samer Kadibalban
- Institute of General Microbiology, Kiel University, Am Botanischen Garten 11, Kiel 24118, Germany
| | - Giddy Landan
- Institute of General Microbiology, Kiel University, Am Botanischen Garten 11, Kiel 24118, Germany
| | - Tal Dagan
- Institute of General Microbiology, Kiel University, Am Botanischen Garten 11, Kiel 24118, Germany.
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Khan J, Rubel T, Molloy E, Dhulipala L, Patro R. Fast, parallel, and cache-friendly suffix array construction. Algorithms Mol Biol 2024; 19:16. [PMID: 38679714 PMCID: PMC11056320 DOI: 10.1186/s13015-024-00263-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 03/21/2024] [Indexed: 05/01/2024] Open
Abstract
PURPOSE String indexes such as the suffix array (SA) and the closely related longest common prefix (LCP) array are fundamental objects in bioinformatics and have a wide variety of applications. Despite their importance in practice, few scalable parallel algorithms for constructing these are known, and the existing algorithms can be highly non-trivial to implement and parallelize. METHODS In this paper we present CAPS-SA, a simple and scalable parallel algorithm for constructing these string indexes inspired by samplesort and utilizing an LCP-informed mergesort. Due to its design, CAPS-SA has excellent memory-locality and thus incurs fewer cache misses and achieves strong performance on modern multicore systems with deep cache hierarchies. RESULTS We show that despite its simple design, CAPS-SA outperforms existing state-of-the-art parallel SA and LCP-array construction algorithms on modern hardware. Finally, motivated by applications in modern aligners where the query strings have bounded lengths, we introduce the notion of a bounded-context SA and show that CAPS-SA can easily be extended to exploit this structure to obtain further speedups. We make our code publicly available at https://github.com/jamshed/CaPS-SA .
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Affiliation(s)
- Jamshed Khan
- Department of Computer Science, University of Maryland, College Park, MD, 20742, USA.
| | - Tobias Rubel
- Department of Computer Science, University of Maryland, College Park, MD, 20742, USA
| | - Erin Molloy
- Department of Computer Science, University of Maryland, College Park, MD, 20742, USA
| | - Laxman Dhulipala
- Department of Computer Science, University of Maryland, College Park, MD, 20742, USA
| | - Rob Patro
- Department of Computer Science, University of Maryland, College Park, MD, 20742, USA.
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Bascón-Cardozo K, Bours A, Manthey G, Durieux G, Dutheil JY, Pruisscher P, Odenthal-Hesse L, Liedvogel M. Fine-Scale Map Reveals Highly Variable Recombination Rates Associated with Genomic Features in the Eurasian Blackcap. Genome Biol Evol 2024; 16:evad233. [PMID: 38198800 PMCID: PMC10781513 DOI: 10.1093/gbe/evad233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/12/2023] [Indexed: 01/12/2024] Open
Abstract
Recombination is responsible for breaking up haplotypes, influencing genetic variability, and the efficacy of selection. Bird genomes lack the protein PR domain-containing protein 9, a key determinant of recombination dynamics in most metazoans. Historical recombination maps in birds show an apparent stasis in positioning recombination events. This highly conserved recombination pattern over long timescales may constrain the evolution of recombination in birds. At the same time, extensive variation in recombination rate is observed across the genome and between different species of birds. Here, we characterize the fine-scale historical recombination map of an iconic migratory songbird, the Eurasian blackcap (Sylvia atricapilla), using a linkage disequilibrium-based approach that accounts for population demography. Our results reveal variable recombination rates among and within chromosomes, which associate positively with nucleotide diversity and GC content and negatively with chromosome size. Recombination rates increased significantly at regulatory regions but not necessarily at gene bodies. CpG islands are associated strongly with recombination rates, though their specific position and local DNA methylation patterns likely influence this relationship. The association with retrotransposons varied according to specific family and location. Our results also provide evidence of heterogeneous intrachromosomal conservation of recombination maps between the blackcap and its closest sister taxon, the garden warbler. These findings highlight the considerable variability of recombination rates at different scales and the role of specific genomic features in shaping this variation. This study opens the possibility of further investigating the impact of recombination on specific population-genomic features.
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Affiliation(s)
- Karen Bascón-Cardozo
- MPRG Behavioural Genomics, Max Planck Institute for Evolutionary Biology, Plön 24306, Germany
| | - Andrea Bours
- MPRG Behavioural Genomics, Max Planck Institute for Evolutionary Biology, Plön 24306, Germany
| | - Georg Manthey
- Institute of Avian Research “Vogelwarte Helgoland”, Wilhelmshaven 26386, Germany
| | - Gillian Durieux
- MPRG Behavioural Genomics, Max Planck Institute for Evolutionary Biology, Plön 24306, Germany
| | - Julien Y Dutheil
- Department for Theoretical Biology, Max Planck Institute for Evolutionary Biology, Plön 24306, Germany
| | - Peter Pruisscher
- MPRG Behavioural Genomics, Max Planck Institute for Evolutionary Biology, Plön 24306, Germany
- Department of Zoology, Stockholm University, Stockholm SE-106 91, Sweden
| | - Linda Odenthal-Hesse
- Department Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Plön 24306, Germany
| | - Miriam Liedvogel
- MPRG Behavioural Genomics, Max Planck Institute for Evolutionary Biology, Plön 24306, Germany
- Institute of Avian Research “Vogelwarte Helgoland”, Wilhelmshaven 26386, Germany
- Department of Biology and Environmental Sciences, Carl von Ossietzky University of Oldenburg, Oldenburg 26129, Germany
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Orlov YL, Orlova NG. Bioinformatics tools for the sequence complexity estimates. Biophys Rev 2023; 15:1367-1378. [PMID: 37974990 PMCID: PMC10643780 DOI: 10.1007/s12551-023-01140-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 09/01/2023] [Indexed: 11/19/2023] Open
Abstract
We review current methods and bioinformatics tools for the text complexity estimates (information and entropy measures). The search DNA regions with extreme statistical characteristics such as low complexity regions are important for biophysical models of chromosome function and gene transcription regulation in genome scale. We discuss the complexity profiling for segmentation and delineation of genome sequences, search for genome repeats and transposable elements, and applications to next-generation sequencing reads. We review the complexity methods and new applications fields: analysis of mutation hotspots loci, analysis of short sequencing reads with quality control, and alignment-free genome comparisons. The algorithms implementing various numerical measures of text complexity estimates including combinatorial and linguistic measures have been developed before genome sequencing era. The series of tools to estimate sequence complexity use compression approaches, mainly by modification of Lempel-Ziv compression. Most of the tools are available online providing large-scale service for whole genome analysis. Novel machine learning applications for classification of complete genome sequences also include sequence compression and complexity algorithms. We present comparison of the complexity methods on the different sequence sets, the applications for gene transcription regulatory regions analysis. Furthermore, we discuss approaches and application of sequence complexity for proteins. The complexity measures for amino acid sequences could be calculated by the same entropy and compression-based algorithms. But the functional and evolutionary roles of low complexity regions in protein have specific features differing from DNA. The tools for protein sequence complexity aimed for protein structural constraints. It was shown that low complexity regions in protein sequences are conservative in evolution and have important biological and structural functions. Finally, we summarize recent findings in large scale genome complexity comparison and applications for coronavirus genome analysis.
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Affiliation(s)
- Yuriy L. Orlov
- The Digital Health Institute, I.M. Sechenov First Moscow State Medical University of the Russian Ministry of Health (Sechenov University), Moscow, 119991 Russia
- Institute of Cytology and Genetics SB RAS, 630090 Novosibirsk, Russia
- Agrarian and Technological Institute, Peoples’ Friendship University of Russia, 117198 Moscow, Russia
| | - Nina G. Orlova
- Department of Mathematics, Financial University under the Government of the Russian Federation, Moscow, 125167 Russia
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Haubold B, Klötzl F, Hellberg L, Thompson D, Cavalar M. Fur: Find Unique Genomic Regions for Diagnostic PCR. Bioinformatics 2021; 37:2081-2087. [PMID: 33515232 PMCID: PMC8352509 DOI: 10.1093/bioinformatics/btab059] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 12/04/2020] [Accepted: 01/26/2021] [Indexed: 11/12/2022] Open
Abstract
Motivation Unique marker sequences are highly sought after in molecular diagnostics. Nevertheless, there are only few programs available to search for marker sequences, compared to the many programs for similarity search. We therefore wrote the program Fur for Finding Unique genomic Regions. Results Fur takes as input a sample of target sequences and a sample of closely related neighbors. It returns the regions present in all targets and absent from all neighbors. The recently published program genmap can also be used for this purpose and we compared it to fur. When analyzing a sample of 33 genomes representing the major phylogroups of E.coli, fur was 40 times faster than genmap but used three times more memory. On the other hand, genmap yielded three times more markers, but they were less accurate when tested in silico on a sample of 237 E.coli genomes. We also designed phylogroup-specific PCR primers based on the markers proposed by genmap and fur, and tested them by analyzing their virtual amplicons in GenBank. Finally, we used fur to design primers specific to a Lactobacillus species, and found excellent sensitivity and specificity in vitro. Availability and implementation Fur sources and documentation are available from https://github.com/evolbioinf/fur. The compiled software is posted as a docker container at https://hub.docker.com/r/haubold/fox. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Bernhard Haubold
- Department of Evolutionary Genetics, Max-Planck-Institute for Evolutionary Biology, Pl öon, Germany
| | - Fabian Klötzl
- Department of Evolutionary Genetics, Max-Planck-Institute for Evolutionary Biology, Pl öon, Germany
| | - Lars Hellberg
- Molecular Infection Diagnostics, Euroimmun Medizinische Labordiagnostika, Lüubeck, Germany
| | - Daniel Thompson
- Molecular Infection Diagnostics, Euroimmun Medizinische Labordiagnostika, Lüubeck, Germany
| | - Markus Cavalar
- Molecular Infection Diagnostics, Euroimmun Medizinische Labordiagnostika, Lüubeck, Germany
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