Spaced Seeds Research Articles

Rasbhari: Optimizing Spaced Seeds for Database Searching, Read Mapping and Alignment-Free Sequence Comparison.

Many algorithms for sequence analysis rely on word matching or word statistics. Often, these approaches can be improved if binary patterns representing match and don’t-care positions are used as a filter, such that only those positions of words are considered that correspond to the match positions of the patterns. The performance of these approaches, however, depends on the underlying patterns. Herein, we show that the overlap complexity of a pattern set that was introduced by Ilie and Ilie is closely related to the variance of the number of matches between two evolutionarily related sequences with respect to this pattern set. We propose a modified hill-climbing algorithm to optimize pattern sets for database searching, read mapping and alignment-free sequence comparison of nucleic-acid sequences; our implementation of this algorithm is called rasbhari. Depending on the application at hand, rasbhari can either minimize the overlap complexity of pattern sets, maximize their sensitivity in database searching or minimize the variance of the number of pattern-based matches in alignment-free sequence comparison. We show that, for database searching, rasbhari generates pattern sets with slightly higher sensitivity than existing approaches. In our Spaced Words approach to alignment-free sequence comparison, pattern sets calculated with rasbhari led to more accurate estimates of phylogenetic distances than the randomly generated pattern sets that we previously used. Finally, we used rasbhari to generate patterns for short read classification with CLARK-S. Here too, the sensitivity of the results could be improved, compared to the default patterns of the program. We integrated rasbhari into Spaced Words; the source code of rasbhari is freely available at http://rasbhari.gobics.de/

WALT: fast and accurate read mapping for bisulfite sequencing

WALT is available under the GPL v3 license, and downloadable from https://github.com/smithlabcode/walt. andrewds@usc.edu or tingchen@usc.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Spaced seeds improve k-mer-based metagenomic classification.

Metagenomics is a powerful approach to study genetic content of environmental samples, which has been strongly promoted by next-generation sequencing technologies. To cope with massive data involved in modern metagenomic projects, recent tools rely on the analysis of k-mers shared between the read to be classified and sampled reference genomes. Within this general framework, we show that spaced seeds provide a significant improvement of classification accuracy, as opposed to traditional contiguous k-mers. We support this thesis through a series of different computational experiments, including simulations of large-scale metagenomic projects.Availability and implementation, Supplementaryinformation: Scripts and programs used in this study, as well as supplementarymaterial, are available from http://github.com/gregorykucherov/spaced-seeds-for-metagenomics. gregory.kucherov@univ-mlv.fr.

Penguin Search Optimisation Algorithm for Finding Optimal Spaced Seeds

This paper develops PeSeeD, a new metaheuristic algorithm for finding optimal spaced seed. Sequences matching is a hot topic in bio-informatics, which is used in many applications such as understanding the functional, structural, or evolutionary relationships between the sequences. The most relevant sequences matching methods are based on seeds designed to match two biological sequences. The first approach which introduced seeds was facilitated via Blastn tool, the approach builds seeds of 11 length size. However, it is clear that not all local alignments have to include an identical fragment of length 11. The spaced seeds approach is one of the methods which does not require a consecutive matching position. Dynamic programming is used to solve this kind of problem and it takes quadratic time. Several approaches have then been proposed to improve the sensitivity of searching in reasonable runtime. To reduce the complexity of such approaches, other heuristics based approaches can also be reviewed. The aim is to find spaced seeds subset which improves sensitivity without increasing the computation time. In this paper, the optimal subset spaced seeds are explored using the bio-inspired approach, penguins search optimisation algorithm (‘'PeSOA'' for short). The authors further propose an efficient heuristic for computing the overlap complexity between seeds. To evaluate the efficiency of the proposed approach, they compared the obtained results with the results of several seeds based software tools. The obtained results are very promising in terms of sensitivity and computation time for the overlap complexity.

Segmentation, Separation and Pose Estimation of Prostate Brachytherapy Seeds in CT Images.

In this paper, we address the development of an automatic approach for the computation of pose information (position + orientation) of prostate brachytherapy loose seeds from 3-D CT images. From an initial detection of a set of seed candidates in CT images using a threshold and connected component method, the orientation of each individual seed is estimated by using the principal components analysis method. The main originality of this approach is the ability to classify the detected objects based on a priori intensity and volume information and to separate groups of closely spaced seeds using three competing clustering methods: the standard and a modified k-means method and a Gaussian mixture model with an expectation-maximization algorithm. Experiments were carried out on a series of CT images of two phantoms and patients. The fourteen patients correspond to a total of 1063 implanted seeds. Detections are compared to manual segmentation and to related work in terms of detection performance and calculation time. This automatic method has proved to be accurate and fast including the ability to separate groups of seeds in a reliable way and to determine the orientation of each seed. Such a method is mandatory to be able to compute precisely the real dose delivered to the patient postoperatively instead of assuming the alignment of seeds along the theoretical insertion direction of the brachytherapy needles.

Spaced Seed Data Structures for De Novo Assembly.

De novo assembly of the genome of a species is essential in the absence of a reference genome sequence. Many scalable assembly algorithms use the de Bruijn graph (DBG) paradigm to reconstruct genomes, where a table of subsequences of a certain length is derived from the reads, and their overlaps are analyzed to assemble sequences. Despite longer subsequences unlocking longer genomic features for assembly, associated increase in compute resources limits the practicability of DBG over other assembly archetypes already designed for longer reads. Here, we revisit the DBG paradigm to adapt it to the changing sequencing technology landscape and introduce three data structure designs for spaced seeds in the form of paired subsequences. These data structures address memory and run time constraints imposed by longer reads. We observe that when a fixed distance separates seed pairs, it provides increased sequence specificity with increased gap length. Further, we note that Bloom filters would be suitable to implicitly store spaced seeds and be tolerant to sequencing errors. Building on this concept, we describe a data structure for tracking the frequencies of observed spaced seeds. These data structure designs will have applications in genome, transcriptome and metagenome assemblies, and read error correction.

A Coverage Criterion for Spaced Seeds and Its Applications to Support Vector Machine String Kernels andk-Mer Distances

Spaced seeds have been recently shown to not only detect more alignments, but also to give a more accurate measure of phylogenetic distances (Boden et al., 2013, Horwege et al., 2014, Leimeister et al., 2014), and to provide a lower misclassification rate when used with Support Vector Machines (SVMs) (On-odera and Shibuya, 2013), We confirm by independent experiments these two results, and propose in this article to use a coverage criterion (Benson and Mak, 2008, Martin, 2013, Martin and No{\'e}, 2014), to measure the seed efficiency in both cases in order to design better seed patterns. We show first how this coverage criterion can be directly measured by a full automaton-based approach. We then illustrate how this criterion performs when compared with two other criteria frequently used, namely the single-hit and multiple-hit criteria, through correlation coefficients with the correct classification/the true distance. At the end, for alignment-free distances, we propose an extension by adopting the coverage criterion, show how it performs, and indicate how it can be efficiently computed.

Improved search heuristics find 20 000 new alignments between human and mouse genomes

Sequence similarity search is a fundamental way of analyzing nucleotide sequences. Despite decades of research, this is not a solved problem because there exist many similarities that are not found by current methods. Search methods are typically based on a seed-and-extend approach, which has many variants (e.g. spaced seeds, transition seeds), and it remains unclear how to optimize this approach. This study designs and tests seeding methods for inter-mammal and inter-insect genome comparison. By considering substitution patterns of real genomes, we design sets of multiple complementary transition seeds, which have better performance (sensitivity per run time) than previous seeding strategies. Often the best seed patterns have more transition positions than those used previously. We also point out that recent computer memory sizes (e.g. 60 GB) make it feasible to use multiple (e.g. eight) seeds for whole mammal genomes. Interestingly, the most sensitive settings achieve diminishing returns for human–dog and melanogaster–pseudoobscura comparisons, but not for human–mouse, which suggests that we still miss many human–mouse alignments. Our optimized heuristics find ∼20 000 new human–mouse alignments that are missing from the standard UCSC alignments. We tabulate seed patterns and parameters that work well so they can be used in future research.

A bioinformatician's guide to the forefront of suffix array construction algorithms

The suffix array and its variants are text-indexing data structures that have become indispensable in the field of bioinformatics. With the uninitiated in mind, we provide an accessible exposition of the SA-IS algorithm, which is the state of the art in suffix array construction. We also describe DisLex, a technique that allows standard suffix array construction algorithms to create modified suffix arrays designed to enable a simple form of inexact matching needed to support ‘spaced seeds’ and ‘subset seeds’ used in many biological applications.

Spaced Seed Design Using Perfect Rulers

A widely used class of approximate pattern matching algorithms work in two stages, the first being a filtering stage that uses spaced seeds to quickly discards regions where a match is not likely to occur. The design of effective spaced seeds is known to be a hard problem. In this setting, we propose a family of lossless spaced seeds for matching with up to two errors based on mathematical objects known as perfect rulers. We analyze these seeds with respect to the tradeoff they offer between seed weight and the minimum length of the pattern to be matched. We identify a specific property of rulers, namely their skewness, which is closely related to the minimum pattern length of the derived seeds. In this context, we study in depth the specific case of Wichmann rulers and investigate the generalization of our approach to the larger class of unrestricted rulers. Although our analysis is mainly of theoretical interest, we show that for pattern lengths of practical relevance our seeds have a larger weight, hence a better filtration efficiency, than the ones known in the literature.

Space Seeds for Asian Future

The Seeds for Asian Future (SSAF) program is one of the activities of the initiative under the Asia-Pacific Regional Space Agency Forum (APRSAF). The program intends to promote understanding, and to give regional space agencies experience in the utilization of the Japanese Experiment Module, of the International Space Station (ISS). It also aims to provide young people in the Asia-Pacific region with opportunities to learn about leading edge sciences through their participations in experiments under peculiar space conditions, including microgravity. Students from Indonesia, Malaysia, Thailand and Vietnam participated in the SSAF2010-2011 program. As part of this program seeds from each of these nations were flown to the ISS and kept in the Kibo Module. These seeds were then returned to Earth where they were germinated and compared to control seed not flown in space. This experiment involved researchers, students and the general public. In the SSAF2013 program, there are plans to cultivate seeds indigenous to Asia in the Kibo/ISS facilities. The plan is to send Azuki bean (Vigna angularis) to Kibo, and observe the growth of their seedlings under dark conditions. Members of the Kibo-ABC initiative are collaborating in the preparation of the seed germination testing procedures, following which many people, including children, students and researchers, are expected to participate in the program.

Design and analysis of periodic multiple seeds

A wide class of approximate pattern matching algorithms are based on a filtration phase in which spaced seeds are used to discard regions where a match is not likely to occur. The problem of determining the “optimal” shape of a spaced seed in a particular setting is known to be a hard one: in practice spaced seeds are chosen using heuristics or considering a restricted family of seeds with “reasonably good” performances.In this paper we consider the family of spaced seeds with a periodic structure. Such seeds have been already proven valuable both as a theoretical tool and in bioinformatics applications. We show that known combinatorial objects, namely Difference Sets and Families and Steiner Systems, naturally lead to the design of lossless periodic seeds for approximate pattern matching with k=2 and k=3 mismatches. We analyze in depth the properties of the resulting seeds obtaining insights also on seeds without a periodic structure. The results of the analysis are then used to guide an experimental evaluation of the effectiveness of periodic seeds for pattern lengths of practical interest. Our results give a complete picture of strengths and limitations of periodic seeds, and can be used by practitioners for the design of effective approximate pattern matching algorithms.

Microgravity effects on different stages of higher plant life cycle and completion of the seed‐to‐seed cycle

Human inhabitation of Space requires the efficient realisation of crop cultivation in bioregenerative life-support systems (BLSS). It is well known that plants can grow under Space conditions; however, perturbations of many biological phenomena have been highlighted due to the effect of altered gravity and its possible interactions with other factors. The mechanisms priming plant responses to Space factors, as well as the consequences of such alterations on crop productivity, have not been completely elucidated. These perturbations can occur at different stages of plant life and are potentially responsible for failure of the completion of the seed-to-seed cycle. After brief consideration of the main constraints found in the most recent experiments aiming to produce seeds in Space, we focus on two developmental phases in which the plant life cycle can be interrupted more easily than in others also on Earth. The first regards seedling development and establishment; we discuss reasons for slow development at the seedling stage that often occurs under microgravity conditions and can reduce successful establishment. The second stage comprises gametogenesis and pollination; we focus on male gamete formation, also identifying potential constraints to subsequent fertilisation. We finally highlight how similar alterations at cytological level can not only be common to different processes occurring at different life stages, but can be primed by different stress factors; such alterations can be interpreted within the model of 'stress-induced morphogenic response' (SIMR). We conclude by suggesting that a systematic analysis of all growth and reproductive phases during the plant life cycle is needed to optimise resource use in plant-based BLSS.

Amyloid-β may be released from non-junctional varicosities of axons generated from abnormal tau-containing brainstem nuclei in sporadic Alzheimer’s disease: a hypothesis

How can the relatively abruptly beginning formation of Aβ deposits be explained? That so little is known about this process is all the more remarkable when one considers that Aβ precipitations develop with such consistency during the course of the AD-associated pathological process that they belong to the hallmark lesions of AD [22, 33, 43]. Ear-lier findings could show that Aβ protein does not enter the extracellular space of the CNS from serum via the vascu-lature, via strongly vascularized ependymal organs, or by way of the choroid plexus, nor is it generated by astrocytes, oligodendrocytes, or microglia cells [ 32]. A β protein aggre-gates are the result of a sequential cleavage of an amyloid precursor protein, which is a physiological constituent of the cellular membranes of nerve cells [22, 33]. Neuronally generated soluble and diffusible Aβ is presumed to equili-brate within the interstitial fluid of the CNS and, from there, it may enter the cerebrospinal fluid that occupies the ventricles and subarachnoid space [3]. At seeds in the interstitial space, soluble oligomeric Aβ may aggregate and form insoluble plaque-like deposits [44].It is unlikely that all types of nerve cells are equally capable of generating Aβ, and, for instance, the nerve cells of the enteric as well as peripheral nervous systems are not known to do so. Nor do all neuronal types within the CNS produce Aβ, inasmuch as Aβ deposition is not ubiquitous there. Rather, Aβ deposition consistently occurs at spe-cific CNS sites according to a distinct developmental and distributional pattern [46, 47]. In general, Aβ deposits are rare in the white substance but they do tend to appear in the gray matter where the somatodendritic compartments of projection neurons are located. Even within the gray matter, regions with high densities of Aβ plaques, e.g., the All cases of sporadic Alzheimer’s disease (AD) are neu-ropathologically characterized by disease-related lesions that develop at specific sites in the human brain and gradu-ally disperse from there into hitherto uninvolved regions [5, 14, 24, 35–37, 44]. Central to this pathological process are abnormal alterations of the neuronal cytoskeleton that consist mainly of hyperphosphorylated and aggregated tau protein [17, 21, 25–27, 30, 31]. Involved nerve cells first can be seen in brainstem nuclei that diffusely project to the cerebral cortex. Among others, these include the noradren-ergic locus coeruleus, the serotonergic upper raphe nuclei, and the cholinergic magnocellular nuclei of the basal fore-brain [8]. Later on, in the pathological process, the intra-neuronal inclusions are accompanied by extracellular plaque-like deposits of a second abnormal protein, amy-loid β (Aβ) [10, 11, 42].In the present context, we are referring only to forms of both proteins that can be assessed by light microscopy, i.e., those which precipitate in aqueous solutions of formalde-hyde and can be detected in human autopsy material using immunoreactions and/or silver stains. Plaque-like deposits of aggregated Aβ are located outside of nerve cells, glial cells, or cells of the vascular wall in the interstitial space of the central nervous system (CNS) [46, 47]. Cerebral amyloid angiopathy is a frequently co-occurring lesion [19, 50].

Better spaced seeds using Quadratic Residues

Spaced seeds are used in approximate pattern matching algorithms to quickly discard regions where a match is not likely to occur. We propose a family of lossless spaced seeds based on Quadratic Residues modulo a prime number. Our seeds work with a threshold t>1 in the sense that two regions are considered similar only if the seed hits t times within the regions. We prove that, for any number of errors, our seeds have an exponentially smaller probability of producing false positive matches than any traditional seed using a threshold t=1. To establish our result we introduce a formal notion of selectivity that generalizes the concept of seed weight, and we relate it to the minimum coverage and to a new structural property defined in terms on seed rotations. This groundwork will be useful for further analysis on seeds with threshold and we use it to provide improved bounds for approximate matching with 2 or 3 errors. Our results show that the use of a single seed with a threshold t>1 should be considered as a possible alternative to single or multiple seeds with t=1.

Evaluation of the visibility of a new thinner 125I radioactive source for permanent prostate brachytherapy

PurposeThe 125I source currently used for prostate brachytherapy at St. James’s Institute of Oncology is a standard size seed (≈4.5mm in length and 0.8mm in diameter). A new, thinner seed is under evaluation. This is designed to be implanted using narrower needles, potentially reducing edema and improving the dose distribution. This study investigated the visibility of the thinner source on multimodality images and compared it with that of standard size seeds. Methods and MaterialsImages of dummy seeds of both thinner and standard size models were taken using ultrasound, fluoroscopy, computed tomography (CT), and magnetic resonance (MR) imaging. The ultrasound, fluoroscopy, and CT images were acquired with the seeds inserted into phantoms positioned in a water tank. The MR images were acquired using phantoms containing single seeds. The images were analyzed visually and quantitatively. The resolution of closely spaced seeds on CT images was investigated. ResultsThe visibility of both seeds was similar on ultrasound, fluoroscopy, and MR images. On CT images, the thinner seeds give reduced artifacts and better resolution. ConclusionsThe use of the thinner seed would have minimal effect on ultrasound and fluoroscopy imaging during treatment. However on CT images, the use of the thinner seeds may improve seed identification for post-treatment dosimetry. Further study is required into the suitability of MR images alone for post-treatment dosimetry.

Efficient computation of spaced seeds.

BackgroundThe most frequently used tools in bioinformatics are those searching for similarities, or local alignments, between biological sequences. Since the exact dynamic programming algorithm is quadratic, linear-time heuristics such as BLAST are used. Spaced seeds are much more sensitive than the consecutive seed of BLAST and using several seeds represents the current state of the art in approximate search for biological sequences. The most important aspect is computing highly sensitive seeds. Since the problem seems hard, heuristic algorithms are used. The leading software in the common Bernoulli model is the SpEED program.FindingsSpEED uses a hill climbing method based on the overlap complexity heuristic. We propose a new algorithm for this heuristic that improves its speed by over one order of magnitude. We use the new implementation to compute improved seeds for several software programs. We compute as well multiple seeds of the same weight as MegaBLAST, that greatly improve its sensitivity.ConclusionMultiple spaced seeds are being successfully used in bioinformatics software programs. Enabling researchers to compute very fast high quality seeds will help expanding the range of their applications.

A Comparison of Frugivory and Scatter-Hoarding Seed-Dispersal Syndromes

Frugivory (animals ingest all or part of fleshy-fruits and defecate or regurgitate seeds) and scatter-hoarding (animals store seeds in small caches in soil) are two important vertebrate-mediated seed dispersal syndromes. In both instances, there is an exchange of food for seed transport, but there are many important differences. For example, the seeds of frugivore-dispersed plants are often clumped in feces or under roosts and the microsite of depostion is often unsuitable for seedling establishment. However, frugivores can transport seeds long distances allowing plants to colonize new areas and promoting gene flow between populations. Scatter-hoarding animals, on the other hand, actively space seeds in microsites that often favor seedling establishment, but don’t move seeds very far. Both modes of seed dispersal can be very effective, but in different way. Some species of plants have evolved propagules that take advantage of both modes of dispersal in two separate phases (i.e., diplochory), apparently to obtain both types of benefits.

SEED: efficient clustering of next-generation sequences

Motivation: Similarity clustering of next-generation sequences (NGS) is an important computational problem to study the population sizes of DNA/RNA molecules and to reduce the redundancies in NGS data. Currently, most sequence clustering algorithms are limited by their speed and scalability, and thus cannot handle data with tens of millions of reads.Results: Here, we introduce SEED—an efficient algorithm for clustering very large NGS sets. It joins sequences into clusters that can differ by up to three mismatches and three overhanging residues from their virtual center. It is based on a modified spaced seed method, called block spaced seeds. Its clustering component operates on the hash tables by first identifying virtual center sequences and then finding all their neighboring sequences that meet the similarity parameters. SEED can cluster 100 million short read sequences in <4 h with a linear time and memory performance. When using SEED as a preprocessing tool on genome/transcriptome assembly data, it was able to reduce the time and memory requirements of the Velvet/Oasis assembler for the datasets used in this study by 60–85% and 21–41%, respectively. In addition, the assemblies contained longer contigs than non-preprocessed data as indicated by 12–27% larger N50 values. Compared with other clustering tools, SEED showed the best performance in generating clusters of NGS data similar to true cluster results with a 2- to 10-fold better time performance. While most of SEED's utilities fall into the preprocessing area of NGS data, our tests also demonstrate its efficiency as stand-alone tool for discovering clusters of small RNA sequences in NGS data from unsequenced organisms.Availability: The SEED software can be downloaded for free from this site: http://manuals.bioinformatics.ucr.edu/home/seed.Contact: thomas.girke@ucr.eduSupplementary information: Supplementary data are available at Bioinformatics online

SpEED: fast computation of sensitive spaced seeds

Multiple spaced seeds represent the current state-of-the-art for similarity search in bioinformatics, with applications in various areas such as sequence alignment, read mapping, oligonucleotide design, etc. We present SpEED, a software program that computes highly sensitive multiple spaced seeds. SpEED can be several orders of magnitude faster and computes better seeds than the existing leading software programs. The source code of SpEED is freely available at www.csd.uwo.ca/~ilie/SpEED/ CONTACT: ilie@csd.uwo.ca Supplementary data are available at Bioinformatics online.