Phylogeny Reconstruction with Alignment-Free Method That Corrects for Horizontal Gene Transfer

A survey of k-mer methods and applications in bioinformatics

The rapid progression of genomics and proteomics has been driven by the advent of advanced sequencing technologies, large, diverse, and readily available omics datasets, and the evolution of computational data processing capabilities. The vast amount of data generated by these advancements necessitates efficient algorithms to extract meaningful information. K-mers serve as a valuable tool when working with large sequencing datasets, offering several advantages in computational speed and memory efficiency and carrying the potential for intrinsic biological functionality. This review provides an overview of the methods, applications, and significance of k-mers in genomic and proteomic data analyses, as well as the utility of absent sequences, including nullomers and nullpeptides, in disease detection, vaccine development, therapeutics, and forensic science. Therefore, the review highlights the pivotal role of k-mers in addressing current genomic and proteomic problems and underscores their potential for future breakthroughs in research.

An alignment- and reference-free strategy using k-mer present pattern for population genomic analyses

Pangenomes are replacing single reference genomes to capture all variants within a species or clade, but their analysis predominantly leverages graph-based methods that require multiple high-quality genomes and computationally intensive multiple-genome alignments. K-mer decomposition is an alternative to graph-based pangenomes. However, how to directly use k-mers for the population genetic analyses is unknown. Here, we developed a novel strategy that uses the variants of k-mer count in the genome for population analyses. To test the effectivity of this method, we compared it directly to the SNP-based method on the analysis of population structure and genetic diversity of 267 Saccharomyces cerevisiae strains within two simulated datasets and a real sequence dataset. The population structure identified with k-mers recapitulates that obtained using SNPs, indicating the effectiveness of k-mer-based approach, and higher genetic diversity within real dataset supported k-mers contained more genetic variants. Based on k-mer frequency, we found not only SNP but also some insertion/deletion and horizontal gene transfer (HGT) fragments related to the adaptive evolution of S. cerevisiae. Our study creates a framework for the alignment- and reference-free (ARF) method in population genetic analyses, which will be more pronounced in the species with no complete genome or highly diverged species.

KINN: An alignment-free accurate phylogeny reconstruction method based on inner distance distributions of k-mer pairs in biological sequences

Alignment-based methods have faced disadvantages in sequence comparison and phylogeny reconstruction due to their high computational complexity. Alignment-free methods for sequence comparison and phylogeny inference have attracted a great deal of attention in recent years. Here, we explore an alignment-free approach that uses inner distance distributions of k-mer pairs in biological sequences for phylogeny inference. For every sequence in a dataset, our method transforms the sequence into a numeric feature vector consisting of features each representing a specific k-mer pair's contribution to the characterization of the sequentiality uniqueness of the sequence. This newly defined k-mer pair's contribution is an integration of the reverse Kullback-Leibler divergence, pseudo mode and the classic entropy of an inner distance distribution of the k-mer pair in the sequence. Our method has been tested on datasets of complete genome sequences, complete protein sequences, and gene sequences of rRNA of various lengths. Our method achieves the best performance in comparison with state-of-the-art alignment-free methods as measured by the Robinson-Foulds distance between the reference and the constructed phylogeny trees.

Taxonomic proposal for a deep branching bacterial phylogenetic lineage: transfer of the family Thermodesulfobiaceae to Thermodesulfobiales ord. nov., Thermodesulfobiia classis nov. and Thermodesulfobiota phyl. nov

The family Thermodesulfobiaceae, comprising one genus Thermodesulfobium with two validly published species, is currently assigned to order Thermoanaerobacterales within the class Clostridia of the phylum Bacillota. At the same time, the very first 16S rRNA gene sequence-based phylogenetic studies of representatives of the genus pointed out great differences between Thermodesulfobium and other members of the phylum Bacillota. Subsequent studies of new Thermodesulfobium representatives supported deep phylogenetic branching of this lineage within bacterial tree, implying that it represents a novel phylum. The results of the phylogenomic analysis performed in the frames of the present work confirm previous findings and suggest that Thermodesulfobium represents a distinct phylum-level lineage. Thus, we propose the transfer of the family Thermodesulfobiaceae to the new order Thermodesulfobiales within the new class Thermodesulfobiia and the new phylum Thermodesulfobiota.

In-depth investigation of the point mutation pattern of HIV-1

Mutations may produce highly transmissible and damaging HIV variants, which increase the genetic diversity, and pose a challenge to develop vaccines. Therefore, it is of great significance to understand how mutations drive the virulence of HIV. Based on the 11897 reliable genomes of HIV-1 retrieved from HIV sequence Database, we analyze the 12 types of point mutation (A>C, A>G, A>T, C>A, C>G, C>T, G>A, G>C, G>T, T>A, T>C, T>G) from multiple statistical perspectives for the first time. The global/geographical location/subtype/k-mer analysis results report that A>G, G>A, C>T and T>C account for nearly 64% among all SNPs, which suggest that APOBEC-editing and ADAR-editing may play an important role in HIV-1 infectivity. Time analysis shows that most genomes with abnormal mutation numbers comes from African countries. Finally, we use natural vector method to check the k-mer distribution changing patterns in the genome, and find that there is an important substitution pattern between nucleotides A and G, and 2-mer CG may have a significant impact on viral infectivity. This paper provides an insight into the single mutation of HIV-1 by using the latest data in the HIV sequence Database.

Interpreting alignment-free sequence comparison: what makes a score a good score?

Alignment-free methods are alternatives to alignment-based methods when searching sequence data sets. The output from an alignment-free sequence comparison is a similarity score, the interpretation of which is not straightforward. We propose objective functions to interpret and calibrate outputs from alignment-free searches, noting that different objective functions are necessary for different biological contexts. This leads to advantages: visualising and comparing score distributions, including those from true positives, may be a relatively simple method to gain insight into the performance of different metrics. Using an empirical approach with both DNA and protein sequences, we characterise different similarity score distributions generated under different parameters. In particular, we demonstrate how sequence length can affect the scores. We show that scores of true positive sequence pairs may correlate significantly with their mean length; and even if the correlation is weak, the relative difference in length of the sequence pair may significantly reduce the effectiveness of alignment-free metrics. Importantly, we show how objective functions can be used with test data to accurately estimate the probability of true positives. This can significantly increase the utility of alignment-free approaches. Finally, we have developed a general-purpose software tool called KAST for use in high-throughput workflows on Linux clusters.

High-Throughput Genotyping Technologies in Plant Taxonomy

Molecular markers provide researchers with a powerful tool for variation analysis between plant genomes. They are heritable and widely distributed across the genome and for this reason have many applications in plant taxonomy and genotyping. Over the last decade, molecular marker technology has developed rapidly and is now a crucial component for genetic linkage analysis, trait mapping, diversity analysis, and association studies. This chapter focuses on molecular marker discovery, its application, and future perspectives for plant genotyping through pangenome assemblies. Included are descriptions of automated methods for genome and sequence distance estimation, genome contaminant analysis in sequence reads, genome structural variation, and SNP discovery methods.

'Multi-SpaM': a maximum-likelihood approach to phylogeny reconstruction using multiple spaced-word matches and quartet trees

Word-based or 'alignment-free' methods for phylogeny inference have become popular in recent years. These methods are much faster than traditional, alignment-based approaches, but they are generally less accurate. Most alignment-free methods calculate 'pairwise' distances between nucleic-acid or protein sequences; these distance values can then be used as input for tree-reconstruction programs such as neighbor-joining. In this paper, we propose the first word-based phylogeny approach that is based on 'multiple' sequence comparison and 'maximum likelihood'. Our algorithm first samples small, gap-free alignments involving four taxa each. For each of these alignments, it then calculates a quartet tree and, finally, the program 'Quartet MaxCut' is used to infer a super tree for the full set of input taxa from the calculated quartet trees. Experimental results show that trees produced with our approach are of high quality.

The number of k-mer matches between two DNA sequences as a function of k and applications to estimate phylogenetic distances

We study the number Nk of length-k word matches between pairs of evolutionarily related DNA sequences, as a function of k. We show that the Jukes-Cantor distance between two genome sequences-i.e. the number of substitutions per site that occurred since they evolved from their last common ancestor-can be estimated from the slope of a function F that depends on Nk and that is affine-linear within a certain range of k. Integers kmin and kmax can be calculated depending on the length of the input sequences, such that the slope of F in the relevant range can be estimated from the values F(kmin) and F(kmax). This approach can be generalized to so-called Spaced-word Matches (SpaM), where mismatches are allowed at positions specified by a user-defined binary pattern. Based on these theoretical results, we implemented a prototype software program for alignment-free sequence comparison called Slope-SpaM. Test runs on real and simulated sequence data show that Slope-SpaM can accurately estimate phylogenetic distances for distances up to around 0.5 substitutions per position. The statistical stability of our results is improved if spaced words are used instead of contiguous words. Unlike previous alignment-free methods that are based on the number of (spaced) word matches, Slope-SpaM produces accurate results, even if sequences share only local homologies.

Stratified reconstruction of ancestral Escherichia coli diversification

Background

Phylogenetic analyses of the bacterial genomes based on the simple classification in core- genes and accessory genes pools could offer an incomplete view of the evolutionary processes, of which some are still unresolved. A combined strategy based on stratified phylogeny and ancient molecular polymorphisms is proposed to infer detailed evolutionary reconstructions by using a large number of whole genomes. This strategy, based on the highest number of genomes available in public databases, was evaluated for improving knowledge of the ancient diversification of E. coli. This staggered evolutionary scenario was also used to investigate whether the diversification of the ancient E. coli lineages could be associated with particular lifestyles and adaptive strategies.

Results

Phylogenetic reconstructions, exploiting 6220 available genomes in Genbank, established the E. coli core genome in 1023 genes, representing about 20% of the complete genome. The combined strategy using stratified phylogeny plus molecular polymorphisms inferred three ancient lineages (D, EB1A and FGB2). Lineage D was the closest to E. coli root. A staggered diversification could also be proposed in EB1A and FGB2 lineages and the phylogroups into these lineages. Several molecular markers suggest that each lineage had different adaptive trajectories. The analysis of gained and lost genes in the main lineages showed that functions of carbohydrates utilization (uptake of and metabolism) were gained principally in EB1A lineage, whereas loss of environmental-adaptive functions in FGB2 lineage were observed, but this lineage showed higher accumulated mutations and ancient recombination events. The population structure of E. coli was re-evaluated including up to 7561 new sequenced genomes, showing a more complex population structure of E. coli, as a new phylogroup, phylogroup I, was proposed.

Conclusions

A staggered reconstruction of E. coli phylogeny is proposed, indicating evolution from three ancestral lineages to reach all main known phylogroups. New phylogroups were confirmed, suggesting an increasingly complex population structure of E. coli. However these new phylogroups represent < 1% of the global E. coli population. A few key evolutionary forces have driven the diversification of the two main E. coli lineages, metabolic flexibility in one of them and colonization-virulence in the other.

Alignment-free inference of hierarchical and reticulate phylogenomic relationships

We are amidst an ongoing flood of sequence data arising from the application of high-throughput technologies, and a concomitant fundamental revision in our understanding of how genomes evolve individually and within the biosphere. Workflows for phylogenomic inference must accommodate data that are not only much larger than before, but often more error prone and perhaps misassembled, or not assembled in the first place. Moreover, genomes of microbes, viruses and plasmids evolve not only by tree-like descent with modification but also by incorporating stretches of exogenous DNA. Thus, next-generation phylogenomics must address computational scalability while rethinking the nature of orthogroups, the alignment of multiple sequences and the inference and comparison of trees. New phylogenomic workflows have begun to take shape based on so-called alignment-free (AF) approaches. Here, we review the conceptual foundations of AF phylogenetics for the hierarchical (vertical) and reticulate (lateral) components of genome evolution, focusing on methods based on k-mers. We reflect on what seems to be successful, and on where further development is needed.

The statistical power of k-mer based aggregative statistics for alignment-free detection of horizontal gene transfer

Alignment-based database search and sequence comparison are commonly used to detect horizontal gene transfer (HGT). However, with the rapid increase of sequencing depth, hundreds of thousands of contigs are routinely assembled from metagenomics studies, which challenges alignment-based HGT analysis by overwhelming the known reference sequences. Detecting HGT by k-mer statistics thus becomes an attractive alternative. These alignment-free statistics have been demonstrated in high performance and efficiency in whole-genome and transcriptome comparisons. To adapt k-mer statistics for HGT detection, we developed two aggregative statistics TsumS and Tsum*, which subsample metagenome contigs by their representative regions, and summarize the regional D2S and D2* metrics by their upper bounds. We systematically studied the aggregative statistics’ power at different k-mer size using simulations. Our analysis showed that, in general, the power of TsumS and Tsum* increases with sequencing coverage, and reaches a maximum power >80% at k = 6, with 5% Type-I error and the coverage ratio >0.2x. The statistical power of TsumS and Tsum* was evaluated with realistic simulations of HGT mechanism, sequencing depth, read length, and base error. We expect these statistics to be useful distance metrics for identifying HGT in metagenomic studies.

AnnoTree: visualization and exploration of a functionally annotated microbial tree of life

Bacterial genomics has revolutionized our understanding of the microbial tree of life; however, mapping and visualizing the distribution of functional traits across bacteria remains a challenge. Here, we introduce AnnoTree-an interactive, functionally annotated bacterial tree of life that integrates taxonomic, phylogenetic and functional annotation data from over 27 000 bacterial and 1500 archaeal genomes. AnnoTree enables visualization of millions of precomputed genome annotations across the bacterial and archaeal phylogenies, thereby allowing users to explore gene distributions as well as patterns of gene gain and loss in prokaryotes. Using AnnoTree, we examined the phylogenomic distributions of 28 311 gene/protein families, and measured their phylogenetic conservation, patchiness, and lineage-specificity within bacteria. Our analyses revealed widespread phylogenetic patchiness among bacterial gene families, reflecting the dynamic evolution of prokaryotic genomes. Genes involved in phage infection/defense, mobile elements, and antibiotic resistance dominated the list of most patchy traits, as well as numerous intriguing metabolic enzymes that appear to have undergone frequent horizontal transfer. We anticipate that AnnoTree will be a valuable resource for exploring prokaryotic gene histories, and will act as a catalyst for biological and evolutionary hypothesis generation. AnnoTree is freely available at http://annotree.uwaterloo.ca.

Alignment-free method for DNA sequence clustering using Fuzzy integral similarity

A larger amount of sequence data in private and public databases produced by next-generation sequencing put new challenges due to limitation associated with the alignment-based method for sequence comparison. So, there is a high need for faster sequence analysis algorithms. In this study, we developed an alignment-free algorithm for faster sequence analysis. The novelty of our approach is the inclusion of fuzzy integral with Markov chain for sequence analysis in the alignment-free model. The method estimate the parameters of a Markov chain by considering the frequencies of occurrence of all possible nucleotide pairs from each DNA sequence. These estimated Markov chain parameters were used to calculate similarity among all pairwise combinations of DNA sequences based on a fuzzy integral algorithm. This matrix is used as an input for the neighbor program in the PHYLIP package for phylogenetic tree construction. Our method was tested on eight benchmark datasets and on in-house generated datasets (18 s rDNA sequences from 11 arbuscular mycorrhizal fungi (AMF) and 16 s rDNA sequences of 40 bacterial isolates from plant interior). The results indicate that the fuzzy integral algorithm is an efficient and feasible alignment-free method for sequence analysis on the genomic scale.

Cyanobacterial phylogenetic analysis based on phylogenomics approaches render evolutionary diversification and adaptation: an overview of representative orders

Phylogenetic studies based on a definite set of marker genes usually reconstruct evolutionary relationships among the prokaryotic species. Based on specific target sequences, such studies represent variations and allow identification of similarities or dissimilarities in organisms. With the advent of completely sequenced genomes and accumulation of information on whole prokaryotic genomes, phylogenetic reconstructions should be considered more reliable if they are ideally based on entire genomes to resolve phylogenetic interest. We applied phylogenomics approaches taking into account completely sequenced cyanobacterial genomes to reconstruct underlying species that represented major taxonomic classes and belonged to distinctly different habitats (freshwater, marine, soils, and rocks). We did not rely on describing phylogeny of all representative class of cyanobacterial species on the basis of only ribosomal gene, 16S rDNA gene. In contrast, we analyzed combined molecular marker and phylogenomics approaches (genome alignment, gene content and gene order, composition vector and protein domain content) for accurately inferring phylogenetic relationship of species. We have shown that this approach reflects the impact of evolution on the organisms and considers connects with the ecological adaptation in cyanobacteria in different habitats. Analysis revealed that the members from marine habitat occupy different profile than those from freshwater. Impact of GC content and genomic repetitiveness over the diversification of cyanobacterial species and their possible role in adaptation was also reflected. Members occupying similar habitats cover more evolutionary distance together and also evolve various strategies for adaptation and survival either through genomic repetitiveness or preferences for genes of particular functions or modified GC content. Genomes undergo different changes for their adaptation in diverse habitats.

A Dual-H-NOX Signaling System in Saccharophagus degradans

Nitric oxide (NO) is a critical signaling molecule involved in the regulation of a wide variety of physiological processes across every domain of life. In most aerobic and facultative anaerobic bacteria, heme-nitric oxide/oxygen binding (H-NOX) proteins selectively sense NO and inhibit the activity of a histidine kinase (HK) located on the same operon. This NO-dependent inhibition of the cognate HK alters the phosphorylation of the downstream response regulators. In the marine bacterium Saccharophagus degradans ( Sde), in addition to a typical H-NOX ( Sde 3804)/HK ( Sde 3803) pair, an orphan H-NOX ( Sde 3557) with no associated signaling protein has been identified distant from the H-NOX/HK pair in the genome. The characterization reported here elucidates the function of both H-NOX proteins. Sde 3557 exhibits a weaker binding affinity with the kinase, yet both Sde 3804 and Sde 3557 are functional H-NOXs with proper gas binding properties and kinase inhibition activity. Additionally, Sde 3557 has an NO dissociation rate that is significantly slower than that of Sde 3804, which may confer prolonged kinase inhibition in vivo. While it is still unclear whether Sde 3557 has another signaling partner or shares the histidine kinase with Sde 3804, Sde 3557 is the only orphan H-NOX characterized to date. S. degradans is likely using a dual-H-NOX system to fine-tune the downstream response of NO signaling.

SSAW: A new sequence similarity analysis method based on the stationary discrete wavelet transform

BACKGROUND

Alignment-free sequence similarity analysis methods often lead to significant savings in computational time over alignment-based counterparts.

RESULTS

A new alignment-free sequence similarity analysis method, called SSAW is proposed. SSAW stands for Sequence Similarity Analysis using the Stationary Discrete Wavelet Transform (SDWT). It extracts k-mers from a sequence, then maps each k-mer to a complex number field. Then, the series of complex numbers formed are transformed into feature vectors using the stationary discrete wavelet transform. After these steps, the original sequence is turned into a feature vector with numeric values, which can then be used for clustering and/or classification.

CONCLUSIONS

Using two different types of applications, namely, clustering and classification, we compared SSAW against the the-state-of-the-art alignment free sequence analysis methods. SSAW demonstrates competitive or superior performance in terms of standard indicators, such as accuracy, F-score, precision, and recall. The running time was significantly better in most cases. These make SSAW a suitable method for sequence analysis, especially, given the rapidly increasing volumes of sequence data required by most modern applications.

Proposal for a new classification of a deep branching bacterial phylogenetic lineage: transfer of Coprothermobacter proteolyticus and Coprothermobacter platensis to Coprothermobacteraceae fam. nov., within Coprothermobacterales ord. nov., Coprothermobacteria classis nov. and Coprothermobacterota phyl. nov. and emended description of the family Thermodesulfobiaceae

The genus Coprothermobacter (initially named Thermobacteroides) is currently placed within the phylum Firmicutes. Early 16S rRNA gene based phylogenetic studies pointed out the great differences between Coprothermobacter and other members of the Firmicutes, revealing that it constitutes a new deep branching lineage. Over the years, several studies based on 16S rRNA gene and whole genome sequences have indicated that Coprothermobacter is very distant phylogenetically to all other bacteria, supporting its placement in a distinct deeply rooted novel phylum. In view of this, we propose its allocation to the new family Coprothermobacteraceae within the novel order Coprothermobacterales, the new class Coprothermobacteria, and the new phylum Coprothermobacterota, and an emended description of the family Thermodesulfobiaceae.

Alignment-free sequence comparison: benefits, applications, and tools

Alignment-free sequence analyses have been applied to problems ranging from whole-genome phylogeny to the classification of protein families, identification of horizontally transferred genes, and detection of recombined sequences. The strength of these methods makes them particularly useful for next-generation sequencing data processing and analysis. However, many researchers are unclear about how these methods work, how they compare to alignment-based methods, and what their potential is for use for their research. We address these questions and provide a guide to the currently available alignment-free sequence analysis tools.

Reshaping Darwin's Tree: Impact of the Symbiome

Much of the undescribed biodiversity on Earth is microbial, often in mutualistic or pathogenic associations. Physically associated and coevolving life forms comprise a symbiome. We propose that systematics research can accelerate progress in science by introducing a new framework for phylogenetic analysis of symbiomes, here termed SYMPHY (symbiome phylogenetics).

Fast and accurate phylogeny reconstruction using filtered spaced-word matches

Motivation

Word-based or ‘alignment-free’ algorithms are increasingly used for phylogeny reconstruction and genome comparison, since they are much faster than traditional approaches that are based on full sequence alignments. Existing alignment-free programs, however, are less accurate than alignment-based methods.

Results

We propose Filtered Spaced Word Matches (FSWM), a fast alignment-free approach to estimate phylogenetic distances between large genomic sequences. For a pre-defined binary pattern of match and don’t-care positions, FSWM rapidly identifies spaced word-matches between input sequences, i.e. gap-free local alignments with matching nucleotides at the match positions and with mismatches allowed at the don’t-care positions. We then estimate the number of nucleotide substitutions per site by considering the nucleotides aligned at the don’t-care positions of the identified spaced-word matches. To reduce the noise from spurious random matches, we use a filtering procedure where we discard all spaced-word matches for which the overall similarity between the aligned segments is below a threshold. We show that our approach can accurately estimate substitution frequencies even for distantly related sequences that cannot be analyzed with existing alignment-free methods; phylogenetic trees constructed with FSWM distances are of high quality. A program run on a pair of eukaryotic genomes of a few hundred Mb each takes a few minutes.

Availability and Implementation

The program source code for FSWM including a documentation, as well as the software that we used to generate artificial genome sequences are freely available at http://fswm.gobics.de/

Supplementary information

Supplementary data are available at Bioinformatics online.