A Probabilistic Model for Indel Evolution: Differentiating Insertions from Deletions.
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ABSTRACT:
SUBMITTER: Loewenthal G
PROVIDER: S-EPMC8662616 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:A fundamental task in sequence analysis is to calculate the probability of a multiple alignment given a phylogenetic tree relating the sequences and an evolutionary model describing how sequences change over time. However, the most widely used phylogenetic models only account for residue substitution events. We describe a probabilistic model of a multiple sequence alignment that accounts for insertion and deletion events in addition to substitutions, given a phylogenetic tree, using a rate matrix augmented by the gap character. Starting from a continuous Markov process, we construct a non-reversible generative (birth-death) evolutionary model for insertions and deletions. The model assumes that insertion and deletion events occur one residue at a time. We apply this model to phylogenetic tree inference by extending the program dnaml in phylip. Using standard benchmarking methods on simulated data and a new "concordance test" benchmark on real ribosomal RNA alignments, we show that the extended program dnamlepsilon improves accuracy relative to the usual approach of ignoring gaps, while retaining the computational efficiency of the Felsenstein peeling algorithm.
| S-EPMC2527138 | biostudies-literature
Project description:Modern phylogenetic methods allow inference of ancestral molecular sequences given an alignment and phylogeny relating present-day sequences. This provides insight into the evolutionary history of molecules, helping to understand gene function and to study biological processes such as adaptation and convergent evolution across a variety of applications. Here, we propose a dynamic programming algorithm for fast joint likelihood-based reconstruction of ancestral sequences under the Poisson Indel Process (PIP). Unlike previous approaches, our method, named ARPIP, enables the reconstruction with insertions and deletions based on an explicit indel model. Consequently, inferred indel events have an explicit biological interpretation. Likelihood computation is achieved in linear time with respect to the number of sequences. Our method consists of two steps, namely finding the most probable indel points and reconstructing ancestral sequences. First, we find the most likely indel points and prune the phylogeny to reflect the insertion and deletion events per site. Second, we infer the ancestral states on the pruned subtree in a manner similar to FastML. We applied ARPIP (Ancestral Reconstruction under PIP) on simulated data sets and on real data from the Betacoronavirus genus. ARPIP reconstructs both the indel events and substitutions with a high degree of accuracy. Our method fares well when compared to established state-of-the-art methods such as FastML and PAML. Moreover, the method can be extended to explore both optimal and suboptimal reconstructions, include rate heterogeneity through time and more. We believe it will expand the range of novel applications of ancestral sequence reconstruction. [Ancestral sequences; dynamic programming; evolutionary stochastic process; indel; joint ancestral sequence reconstruction; maximum likelihood; Poisson Indel Process; phylogeny; SARS-CoV.].
| S-EPMC10275563 | biostudies-literature
Project description:Indels in the coding regions of a gene can either cause frameshifts or amino acid insertions/deletions. Frameshifting indels are indels that have a length that is not divisible by 3 and subsequently cause frameshifts. Indels that have a length divisible by 3 cause amino acid insertions/deletions or block substitutions; we call these 3n indels. The new amino acid changes resulting from 3n indels could potentially affect protein function. Therefore, we construct a SIFT Indel prediction algorithm for 3n indels which achieves 82% accuracy, 81% sensitivity, 82% specificity, 82% precision, 0.63 MCC, and 0.87 AUC by 10-fold cross-validation. We have previously published a prediction algorithm for frameshifting indels. The rules for the prediction of 3n indels are different from the rules for the prediction of frameshifting indels and reflect the biological differences of these two different types of variations. SIFT Indel was applied to human 3n indels from the 1000 Genomes Project and the Exome Sequencing Project. We found that common variants are less likely to be deleterious than rare variants. The SIFT indel prediction algorithm for 3n indels is available at http://sift-dna.org/
| S-EPMC3806772 | biostudies-literature
Project description:MotivationSmall insertion and deletion (sindel) of human genome has an important implication for human disease. One important mechanism for non-coding sindel (nc-sindel) to have an impact on human diseases and phenotypes is through the regulation of gene expression. Nevertheless, current sequencing experiments may lack statistical power and resolution to pinpoint the functional sindel due to lower minor allele frequency or small effect size. As an alternative strategy, a supervised machine learning method can identify the otherwise masked functional sindels by predicting their regulatory potential directly. However, computational methods for annotating and predicting the regulatory sindels, especially in the non-coding regions, are underdeveloped.ResultsBy leveraging labeled nc-sindels identified by cis-expression quantitative trait loci analyses across 44 tissues in Genotype-Tissue Expression (GTEx), and a compilation of both generic functional annotations and large-scale epigenomic profiles, we develop TIssue-specific Variant Annotation for Non-coding indel (TIVAN-indel), which is a supervised computational framework for predicting non-coding regulatory sindels. As a result, we demonstrate that TIVAN-indel achieves the best prediction performance in both with-tissue prediction and cross-tissue prediction. As an independent evaluation, we train TIVAN-indel from the 'Whole Blood' tissue in GTEx and test the model using 15 immune cell types from an independent study named Database of Immune Cell Expression. Lastly, we perform an enrichment analysis for both true and predicted sindels in key regulatory regions such as chromatin interactions, open chromatin regions and histone modification sites, and find biologically meaningful enrichment patterns.Availability and implementationhttps://github.com/lichen-lab/TIVAN-indel.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC9900211 | biostudies-literature
Project description:Amino acid insertions and deletions (indels) are an abundant class of genetic variants. However, compared to substitutions, the effects of indels are not well understood and poorly predicted. Here we address this shortcoming by performing deep indel mutagenesis (DIM) of structurally diverse proteins. Indel tolerance is strikingly different to substitution tolerance and varies extensively both between different proteins and within different regions of the same protein. Although state of the art variant effect predictors perform poorly on indels, we show that both experimentally-measured and computationally-predicted substitution scores can be repurposed as good indel variant effect predictors by incorporating information on protein secondary structures. Quantifying the effects of indels on protein-protein interactions reveals that insertions can be an important class of gain-of-function variants. Our results provide an overview of the impact of indels on proteins and a method to predict their effects genome-wide.
2023-09-28 | GSE244096 | GEO
Project description:BackgroundInsertions and deletions (indels) represent a common type of sequence variations, which are less studied and pose many important biological questions. Recent research has shown that the presence of sizable indels in protein sequences may be indicative of protein essentiality and their role in protein interaction networks. Examples of utilization of indels for structure-based drug design have also been recently demonstrated. Nonetheless many structural and functional characteristics of indels remain less researched or unknown.DescriptionWe have created a web-based resource, Indel PDB, representing a structural database of insertions/deletions identified from the sequence alignments of highly similar proteins found in the Protein Data Bank (PDB). Indel PDB utilized large amounts of available structural information to characterize 1-, 2- and 3-dimensional features of indel sites. Indel PDB contains 117,266 non-redundant indel sites extracted from 11,294 indel-containing proteins. Unlike loop databases, Indel PDB features more indel sequences with secondary structures including alpha-helices and beta-sheets in addition to loops. The insertion fragments have been characterized by their sequences, lengths, locations, secondary structure composition, solvent accessibility, protein domain association and three dimensional structures.ConclusionBy utilizing the data available in Indel PDB, we have studied and presented here several sequence and structural features of indels. We anticipate that Indel PDB will not only enable future functional studies of indels, but will also assist protein modeling efforts and identification of indel-directed drug binding sites.
| S-EPMC2459192 | biostudies-literature
Project description:The life cycle of Yersinia pestis has changed a lot to adapt to flea-borne transmission since it evolved from an enteric pathogen, Yersinia pseudotuberculosis. Small insertions and deletions (indels), especially frameshift mutations, can have major effects on phenotypes and contribute to virulence and host adaptation through gene disruption and inactivation. Here, we analyzed 365 Y. pestis genomes and identified 2,092 genome-wide indels on the core genome. As recently reported in Mycobacterium tuberculosis, we also detected "indel pockets" in Y. pestis, with average complexity scores declining around indel positions, which we speculate might also exist in other prokaryotes. Phylogenic analysis showed that indel-based phylogenic tree could basically reflect the phylogenetic relationships of major phylogroups in Y. pestis, except some inconsistency around the Big Bang polytomy. We observed 83 indels arising in the trunk of the phylogeny, which played a role in accumulation of pseudogenes related to key metabolism and putatively pathogenicity. We also discovered 32 homoplasies at the level of phylogroups and 7 frameshift scars (i.e., disrupted reading frame being rescued by a second frameshift). Additionally, our analysis showed evidence of parallel evolution at the level of genes, with sspA, rpoS, rnd, and YPO0624, having enriched mutations in Brazilian isolates, which might be advantageous for Y. pestis to cope with fluctuating environments. The diversified selection signals observed here demonstrates that indels are important contributors to the adaptive evolution of Y. pestis. Meanwhile, we provide potential targets for further exploration, as some genes/pseudogenes with indels we focus on remain uncharacterized. IMPORTANCE Yersinia pestis, the causative agent of plague, is a highly pathogenic clone of Yersinia pseudotuberculosis. Previous genome-wide SNP analysis provided few adaptive signatures during its evolution. Here by investigating 365 public genomes of Y. pestis, we give a comprehensive overview of general features of genome-wide indels on the core genome and their roles in Y. pestis evolution. Detection of "indel pockets," with average complexity scores declining around indel positions, in both Mycobacterium tuberculosis and Y. pestis, gives us a clue that this phenomenon might appear in other bacterial genomes. Importantly, the identification of four different forms of selection signals in indels would improve our understanding on adaptive evolution of Y. pestis, and provide targets for further physiological mechanism researches of this pathogen. As evolutionary research based on genome-wide indels is still rare in bacteria, our study would be a helpful reference in deciphering the role of indels in other species.
| S-EPMC9248902 | biostudies-literature
Project description:Evolution of indels in a MTBC lineage 2 MDR-outbreak
| PRJEB36040 | ENA
Project description:Gene targeting is a powerful technique for manipulating the human genome, but few studies have directly compared the targeting frequencies of various types of vector constructs. Here we show that similar targeting constructs are able to insert nucleotides at the homologous chromosomal target locus more efficiently than they can delete nucleotides, and combination insertion/deletion vectors appear to target at intermediate frequencies. This holds true for deletions ranging from 1 to 334 bp and insertions ranging from 1 to 1332 bp. In addition, vectors designed to inactivate the human hypoxanthine phosphoribosyltransferase gene (HPRT) by deleting nucleotides often produced rearrangements at the target locus that in many cases were due to insertions of multimerized vector constructs, effectively converting a deletion vector into an insertion vector. These findings were obtained when adeno-associated virus vectors were used to efficiently deliver single-stranded DNA targeting constructs, but the same phenomenon was also observed when transfecting linearized double-stranded plasmids. Thus human cells distinguish between deletion and insertion vectors and process their recombination intermediates differently, presumably at the heteroduplex stage, with implications for the design of gene-targeting vectors and the evolution of human genomes.
| S-EPMC2940567 | biostudies-literature
Project description:Small insertions and deletions occur in humans at a lower rate compared to nucleotide changes, but evolve under more constraint than nucleotide changes. While the evolution of insertions and deletions have been investigated using ape outgroups, the now available genome of a Neandertal can shed light on the evolution of indels in more recent times.We used the Neandertal genome together with several primate outgroup genomes to differentiate between human insertion/deletion changes that likely occurred before the split from Neandertals and those that likely arose later. Changes that pre-date the split from Neandertals show a smaller proportion of deletions than those that occurred later. The presence of a Neandertal-shared allele in Europeans or Asians but the absence in Africans was used to detect putatively introgressed indels in Europeans and Asians. A larger proportion of these variants reside in intergenic regions compared to other modern human variants, and some variants are linked to SNPs that have been associated with traits in modern humans.Our results are in agreement with earlier results that suggested that deletions evolve under more constraint than insertions. When considering Neandertal introgressed variants, we find some evidence that negative selection affected these variants more than other variants segregating in modern humans. Among introgressed variants we also identify indels that may influence the phenotype of their carriers. In particular an introgressed deletion associated with a decrease in the time to menarche may constitute an example of a former Neandertal-specific trait contributing to modern human phenotypic diversity.
| S-EPMC5543596 | biostudies-literature