Biology subjects

Morgenstern, B.

Publications and source records attributed to Morgenstern, B..

10 recordsLinked to original sources

bioRxiv2021

Insertions and deletions as phylogenetic signal in alignment-free sequence comparison

Most methods for phylogenetic tree reconstruction are based on sequence alignments; they infer phylogenies from substitutions that may have occurred at the aligned sequence positions. Gaps in alignments are usually not employed as phylogenetic signal. In this paper, we explore an alignment-free approach that uses insertions and deletions (indels) as an additional source of information for phylogeny inference. For a set of four or more input sequences, we generate so-called quartet blocks of four putative homologous segments each. For pairs of such quartet blocks involving the same four sequences, we compare the distances between the two blocks in these sequences, to obtain hints about indels that may have happened between the blocks since the respective four sequences have evolved from their last common ancestor. A prototype implementation is presented to infer phylogenetic trees from these data, using a quartet-tree approach or, alternatively, under the maximum-parsimony paradigm. This approach should not be regarded as an alternative to established methods, but rather as a complementary source of phylogenetic information. Interestingly, however, our software is able to produce phylogenetic trees from putative indels alone that are comparable to trees obtained with existing alignment-free methods.

bioinformatics↗

bioRxiv2020

Phylogenetic placement of short reads without sequence alignment

Phylogenetic placement is the task of placing a query sequence of unknown taxonomic origin into a given phylogenetic tree of a set of reference sequences. Several approaches to phylogenetic placement have been proposed in recent years. The most accurate of them need a multiple alignment of the reference sequences as input. Most of them also need alignments of the query sequences to the multiple alignment of the reference sequences. A major field of application of phylogenetic placement is taxonomic read assignment in metagenomics. Herein, we propose App-SpaM, an efficient alignment-free algorithm for phylogenetic placement of short sequencing reads on a tree of a set of reference genomes. App-SpaM is based on the Filtered Spaced Word Matches approach that we previously developed. Unlike other methods, our approach neither requires a multiple alignment of the reference genomes, nor alignments of the queries to the reference sequences. Moreover, App-SpaM works not only on assembled reference genomes, but can also take reference taxa as input for which only unassembled read sequences are available. The quality of the results achieved with App-SpaM is comparable to the best available approaches to phylogenetic placement. However, since App-SpaM is not based on sequence alignment, it is between one and two orders of magnitude faster than those existing methods.

bioinformatics↗

bioRxiv2020

V. longisporum elicits media-dependent secretome responses with a further capacity to distinguish between plant-related environments

Verticillia cause a vascular wilt disease affecting a broad range of economically valuable crops. The fungus enters its host plants through the roots and colonizes the vascular system. It requires extracellular proteins for a successful plant colonization. The exoproteome of the allodiploid Verticillium longisporum was analyzed upon cultivation in different media. Secreted fungal proteins were identified by label free LC-MS/MS screening. V. longisporum induced two main secretion patterns. One response pattern was elicited in various non-plant related environments. The second pattern includes the exoprotein responses to the plant-related media, pectin-rich simulated xylem medium and pure xylem sap, which exhibited similar but additional distinct features. These exoproteomes include a shared core set of 223 secreted and similarly enriched fungal proteins. The pectin-rich medium significantly induced the secretion of 144 proteins including a number of pectin degrading enzymes, whereas xylem sap triggered a smaller but unique fungal exoproteome pattern with 32 enriched proteins. The latter pattern included proteins with domains of known effectors, metallopeptidases and carbohydrate-active enzymes. The most abundant and uniquely enriched proteins of these different groups are the necrosis and ethylene inducing-like proteins Nlp2 and Nlp3, the cerato-platanin proteins Cp1 and Cp2, the metallopeptidases Mep1 and Mep2 and the CAZys Gla1, Amy1 and Cbd1. Deletion of the majority of the corresponding genes caused no phenotypic changes during ex planta growth or invasion and colonization of tomato plants. However, we discovered that the NLP2 and NLP3 deletion strains were compromised in plant infections. Overall, our exoproteome approach revealed that the fungus induces specific secretion responses in different environments. The fungus has a general response to non-plant related media whereas it is able to fine-tune its exoproteome in the presence of plant material. Importantly, the xylem sap-specific exoproteome pinpointed Nlp2 and Nlp3 as single effectors required for successful V. dahliae colonization. Author SummaryVerticillium spp. infect hundreds of different plants world-wide leading to enormous economic losses. Verticillium wilt is a disease of the vasculature. The fungus colonizes the xylem of its host plant where it exploits the vascular system to colonize the whole plant. Therefore, the fungus spends part of its lifetime in this nutrient-low and imbalanced environment where it is inaccessible for disease control treatments. This lifestyle as well requires the fungus to react to plant defense responses by secreting specific effector molecules to establish a successful infection. We addressed the differences in media-dependent secretion responses of Verticillium longisporum. We identified a broad response pattern induced by several media, and a similar response (but with some distinct differences) for the plant-related environments: the pectin-rich medium SXM and xylem sap from the host rapeseed. Importantly, we show that the necrosis and ethylene inducing-like proteins Nlp2 and Nlp3 are xylem sap-specific proteins that are required for full V. dahliae pathogenicity on tomato. These factors play a role during the colonization phase and represent potential targets for new control strategies for Verticillium wilt.

genetics↗

bioRxiv2019

Smash++: an alignment-free and memory-efficient tool to find genomic rearrangements

BackgroundThe development of high-throughput sequencing technologies and, as its result, the production of huge volumes of genomic data, has accelerated biological and medical research and discovery. Study on genomic rearrangements is crucial due to their role in chromosomal evolution, genetic disorders and cancer; ResultsWe present Smash++, an alignment-free and memory-efficient tool to find and visualize small- and large-scale genomic rearrangements between two DNA sequences. This computational solution extracts information contents of the two sequences, exploiting a data compression technique, in order for finding rearrangements. We also present Smash++ visualizer, a tool that allows the visualization of the detected rearrangements along with their self- and relative complexity, by generating an SVG (Scalable Vector Graphics) image; ConclusionsTested on several synthetic and real DNA sequences from bacteria, fungi, Aves and mammalia, the proposed tool was able to accurately find genomic rearrangements. The detected regions complied with previous studies which took alignment-based approaches or performed FISH (Fluorescence in situ hybridization) analysis. The maximum peak memory usage among all experiments was ~1 GB, which makes Smash++ feasible to run on present-day standard computers.

bioinformatics↗

bioRxiv2019

Sequence Comparison without Alignment: The SpaM approaches

Sequence alignment is at the heart of DNA and protein sequence analysis. For the data volumes that are nowadays produced by massively parallel sequencing technologies, however, pairwise and multiple alignment methods have become too slow for many data-analysis tasks. Therefore, fast alignment-free approaches to sequence comparison have become popular in recent years. Most of these approaches are based on word frequencies, for words of a fixed length, or on word-matching statistics. Other approaches are based on the length of maximal word matches. While these methods are very fast, most of them are based on ad-hoc measures of sequences similarity or dissimilarity that are often hard to interpret. In this review article, I describe a number of alignment-free methods that we developed in recent years. Our approaches are based on spaced word matches ( SpaM), i.e. on inexact word matches, that are allowed to contain mismatches at certain pre-defined positions. Unlike most previous alignment-free approaches, our approaches are able to accurately estimate phylogenetic distances between DNA or protein sequences based on stochastic models of molecular evolution.

bioinformatics↗

bioRxiv2019

S-conLSH: Alignment-free gapped mapping of noisy long reads

MotivationThe advancement of SMRT technology has unfolded new opportunities of genome analysis with its longer read length and low GC bias. Alignment of the reads to their appropriate positions in the respective reference genome is the first but costliest step of any analysis pipeline based on SMRT sequencing. However, the state-of-the-art aligners often fail to identify distant homologies due to lack of conserved regions, caused by frequent genetic duplication and recombination. Therefore, we developed a novel alignment-free method of sequence mapping that is fast and accurate. ResultsWe present a new mapper called S-conLSH that uses Spaced context based Locality Sensitive Hashing. With multiple spaced patterns, S-conLSH facilitates a gapped mapping of noisy long reads to the corresponding target locations of a reference genome. We have examined the performance of the proposed method on 5 different real and simulated datasets. S-conLSH is at least 2 times faster than the state-of-the-art alignment-based methods. It achieves a sensitivity of 99%, without using any traditional base-to-base alignment, on human simulated sequence data. By default, S-conLSH provides an alignment-free mapping in PAF format. However, it has an option of generating aligned output as SAM-file, if it is required for any downstream processing. AvailabilityThe source code of our software is freely available at https://github.com/anganachakraborty/S-conLSH

bioinformatics↗

bioRxiv2019

Benchmarking of alignment-free sequence comparison methods

Alignment-free (AF) sequence comparison is attracting persistent interest driven by data-intensive applications. Hence, many AF procedures have been proposed in recent years, but a lack of a clearly defined benchmarking consensus hampers their performance assessment. Here, we present a community resource (http://afproject.org) to establish standards for comparing alignment-free approaches across different areas of sequence-based research. We characterize 74 AF methods available in 24 software tools for five research applications, namely, protein sequence classification, gene tree inference, regulatory element detection, genome-based phylogenetic inference and reconstruction of species trees under horizontal gene transfer and recombination events. The interactive web service allows researchers to explore the performance of alignment-free tools relevant to their data types and analytical goals. It also allows method developers to assess their own algorithms and compare them with current state-of-the-art tools, accelerating the development of new, more accurate AF solutions.

bioinformatics↗

bioRxiv2019

Read-SpaM: assembly-free and alignment-free comparison of bacterial genomes with low sequencing coverage

In many fields of biomedical research, it is important to estimate phylogenetic distances between taxa based on low-coverage sequencing reads. Major applications are, for example, phylogeny reconstruction, species identification from small sequencing samples, or bacterial strain typing in medical diagnostics. Herein, we adapt our previously developed software program Filtered Spaced-Word Matches (FSWM) for alignment-free phylogeny reconstruction to work on unassembled reads; we call this implementation Read-SpaM. Test runs on simulated reads from bacterial genomes show that our approach can estimate phylogenetic distances with high accuracy, even for large evolutionary distances and for very low sequencing coverage. Contact: bmorgen@gwdg.de

bioinformatics↗

bioRxiv2019

The number of spaced-word matches between two DNA sequences as a function of the underlying pattern weight

We study the number Nk of (spaced) word matches between pairs of evolutionarily related DNA sequences depending on the word length or pattern weight k, respectively. We show that, under the Jukes-Cantor model, the number of substitutions per site that occurred since two sequences evolved from their last common ancestor, can be esti-mated from the slope of a certain function of Nk. Based on these considerations, we implemented a software program for alignment-free sequence comparison called Slope-SpaM. Test runs on simulated sequence data show that Slope-SpaM can estimate phylogenetic dis-tances with high accuracy for up to around 0.5 substitutions per po-sitions. The statistical stability of our results is improved if spaced words are used instead of contiguous k-mers. Unlike previous methods that are based on the number of (spaced) word matches, our approach can deal with sequences that share only local homologies.

bioinformatics↗

bioRxiv2018

Prot-SpaM: Fast alignment-free phylogeny reconstruction based on whole-proteome sequences

Word-based or alignment-free sequence comparison has become an active area of research in bioinformatics. While previous word-frequency approaches calculated rough measures of sequence similarity or dissimilarity, some new alignment-free methods are able to accurately estimate phylogenetic distances between genomic sequences. One of these approaches is Filtered Spaced Word Matches. Herein, we extend this approach to estimate evolutionary distances between complete or incomplete proteomes; our implementation of this approach is called Prot-SpaM. We compare the performance of Prot-SpaM to other alignment-free methods on simulated sequences and on various groups of eukaryotic and prokaryotic taxa. Prot-SpaM can be used to calculate high-quality phylogenetic trees from whole-proteome sequences in a matter of seconds or minutes and often outperforms other alignment-free approaches. The source code of our software is available through Github:\n\nhttps://github.com/jschellh/ProtSpaM

bioinformatics↗