Please Mind the Gap: Indel-Aware Parsimony for Fast and Accurate Ancestral Sequence Reconstruction and Multiple Sequence Alignment including Long Indels

Iglhaut, Clara; Pečerska, Jūlija; Gil, Manuel; Anisimova, Maria

doi:10.1101/2024.03.27.586611

Cited by 3 publications

(1 citation statement)

References 57 publications

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“…We demonstrate PanMAN representative capabilities using the example of SARS-CoV-2 and show that PanMANs provide a more detailed and accurate representation of the pathogen's evolutionary and mutational histories. Notably, PanMAN represents indels and recombination events that are often ignored in bioinformatic analyses 33,37 . We also demonstrate that PanMANs are compatible with any phylogenetic and ancestral state reconstruction algorithms.…”

Section: Introductionmentioning

confidence: 99%

Compressive Pangenomics Using Mutation-Annotated Networks

Walia,

Motwani,

Smith

et al. 2024

Preprint

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Pangenomics is an emerging field that uses a collection of genomes of a species instead of a single reference genome to overcome reference bias and study the within-species genetic diversity. Future pangenomics applications will require analyzing large and ever-growing collections of genomes. Therefore, the choice of data representation is a key determinant of the scope, as well as the computational and memory performance of pangenomic analyses. Current pangenome formats, while capable of storing genetic variations across multiple genomes, fail to capture the shared evolutionary and mutational histories among them, thereby limiting their applications. They are also inefficient for storage, and therefore face significant scaling challenges. In this manuscript, we propose PanMAN, a novel data structure that is information-wise richer than all existing pangenome formats – in addition to representing the alignment and genetic variation in a collection of genomes, PanMAN represents the shared mutational and evolutionary histories inferred between those genomes. By using “evolutionary compression”, PanMAN achieves 5.2 to 680-fold compression over other variation-preserving pangenomic formats. PanMAN’s relative performance generally improves with larger datasets and it is compatible with any method for inferring phylogenies and ancestral nucleotide states. Using SARS-CoV-2 as a case study, we show that PanMAN offers a detailed and accurate portrayal of the pathogen’s evolutionary and mutational history, facilitating the discovery of new biological insights. We also presentpanmanUtils, a software toolkit that supports common pangenomic analyses and makes PanMANs interoperable with existing tools and formats. PanMANs are poised to enhance the scale, speed, resolution, and overall scope of pangenomic analyses and data sharing.

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Section: Introductionmentioning

confidence: 99%

Compressive Pangenomics Using Mutation-Annotated Networks

Walia,

Motwani,

Smith

et al. 2024

Preprint

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Kudoagenomes from contaminated hosts reveal extensive gene order conservation and rapid sequence evolution

Weber,

Paulini,

Blaxter

2024

Preprint

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Myxozoans are obligate endoparasites that belong to the phylum Cnidaria. Compared to their closest free-living relatives, they have evolved highly simplified body plans and reduced genomes. Kudoa iwatai, for example, has lost upwards of two thirds of genes thought to have been present in its ancestors. However, little is known about myxozoan genome architecture because of a lack of sufficiently contiguous genome assemblies. This work presents two new, near-chromosomal Kudoa genomes, built entirely from low-coverage long reads from infected fish samples. The results illustrate the potential of using unsupervised learning methods to disentangle sequences from different sources, and facilitate producing genomes from undersampled taxa. Extracting distinct components of chromatin interaction networks allows scaffolds from mixed samples to be assigned to their source genomes. Meanwhile, low-dimensional embeddings of read composition permit targeted assembly of potential parasite reads. Despite drastic changes in genome architecture in the lineage leading to Kudoa and considerable sequence divergence between the two genomes, gene order is highly conserved. Although parasitic cnidarians show rapid protein evolution compared to their free-living relatives, there is limited evidence of less efficient selection. While deleterious substitutions may become fixed at a higher rate, large evolutionary distances between species make robustly analysing patterns of molecular evolution challenging. These observations highlight the importance of filling in taxonomic gaps, to allow a comprehensive assessment of the impacts of parasitism on genome evolution.

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Single-character insertion–deletion model preserves long indels in ancestral sequence reconstruction

Jowkar,

Pečerska,

Gil

et al. 2024

BMC Bioinformatics

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Insertions and deletions (indels) play a significant role in genome evolution across species. Realistic modelling of indel evolution is challenging and is still an open research question. Several attempts have been made to explicitly model multi-character (long) indels, such as TKF92, by relaxing the site independence assumption and introducing fragments. However, these methods are computationally expensive. On the other hand, the Poisson Indel Process (PIP) assumes site independence but allows one to infer single-character indels on the phylogenetic tree, distinguishing insertions from deletions. PIP’s marginal likelihood computation has linear time complexity, enabling ancestral sequence reconstruction (ASR) with indels in linear time. Recently, we developed ARPIP, an ASR method using PIP, capable of inferring indel events with explicit evolutionary interpretations. Here, we investigate the effect of the single-character indel assumption on reconstructed ancestral sequences on mammalian protein orthologs and on simulated data. We show that ARPIP’s ancestral estimates preserve the gap length distribution observed in the input alignment. In mammalian proteins the lengths of inserted segments appear to be substantially longer compared to deleted segments. Further, we confirm the well-established deletion bias observed in real data. To date, ARPIP is the only ancestral reconstruction method that explicitly models insertion and deletion events over time. Given a good quality input alignment, it can capture ancestral long indel events on the phylogeny.

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Please Mind the Gap: Indel-Aware Parsimony for Fast and Accurate Ancestral Sequence Reconstruction and Multiple Sequence Alignment including Long Indels

Cited by 3 publications

References 57 publications

Compressive Pangenomics Using Mutation-Annotated Networks

Compressive Pangenomics Using Mutation-Annotated Networks

Kudoagenomes from contaminated hosts reveal extensive gene order conservation and rapid sequence evolution

Single-character insertion–deletion model preserves long indels in ancestral sequence reconstruction

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