DOCEST-fast and accurate estimator of human NGS sequencing depth and error rate.

Motivation: Accurate estimation of next-generation sequencing depth of coverage is needed for detecting the copy number of repeated elements in the human genome. The common methods for estimating sequencing depth are based on counting the number of reads mapped to the genome or subgenomic regions. Such methods are sensitive to the mapping quality. The presence of contamination or the large deviance of an individual genome from the reference may introduce bias in depth estimation. Results: Here, we present an algorithm and implementation for estimating both the sequencing depth and error rate from unmapped reads using a uniquely filtered k-mer set. On simulated reads with 20× coverage, the margin of error was less than 0.01%. At 0.01× coverage and the presence of 10-fold contamination, the precision was within 2% for depth and within 10% for error rate. Availability and implementation: DOCEST program and database can be downloaded from https://bioinfo.ut.ee/docest/. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

KATK: Fast genotyping of rare variants directly from unmapped sequencing reads.

KATK is a fast and accurate software tool for calling variants directly from raw next-generation sequencing reads. It uses predefined k-mers to retrieve only the reads of interest from the FASTQ file and calls genotypes by aligning retrieved reads locally. KATK does not use data about known polymorphisms and has NC (no call) as the default genotype. The reference or variant allele is called only if there is sufficient evidence for their presence in data. Thus it is not biased against rare variants or de-novo mutations. With simulated datasets, we achieved a false-negative rate of 0.23% (sensitivity 99.77%) and a false discovery rate of 0.19%. Calling all human exonic regions with KATK requires 1-2 h, depending on sequencing coverage.

Creating basis for introducing non-invasive prenatal testing in the Estonian public health setting.

OBJECTIVE: The study aimed to validate a whole-genome sequencing-based NIPT laboratory method and our recently developed NIPTmer aneuploidy detection software with the potential to integrate the pipeline into prenatal clinical care in Estonia. METHOD: In total, 424 maternal blood samples were included. Analysis pipeline involved cell-free DNA extraction, library preparation and massively parallel sequencing on Illumina platform. Aneuploidies were determined with NIPTmer software, which is based on counting pre-defined per-chromosome sets of unique k-mers from sequencing raw data. SeqFF was implemented to estimate cell-free fetal DNA (cffDNA) fraction. RESULTS: NIPTmer identified correctly all samples of non-mosaic trisomy 21 (T21, 15/15), T18 (9/9), T13 (4/4) and monosomy X (4/4) cases, with the 100% sensitivity. However, one mosaic T18 remained undetected. Six false-positive (FP) results were observed (FP rate of 1.5%, 6/398), including three for T18 (specificity 99.3%) and three for T13 (specificity 99.3%). The level of cffDNA of <4% was estimated in eight samples, including one sample with T13 and T18. Despite low cffDNA level, these two samples were determined as aneuploid. CONCLUSION: We believe that the developed NIPT method can successfully be used as a universal primary screening test in combination with ultrasound scan for the first trimester fetal examination.

NIPTmer: rapid k-mer-based software package for detection of fetal aneuploidies.

Non-invasive prenatal testing (NIPT) is a recent and rapidly evolving method for detecting genetic lesions, such as aneuploidies, of a fetus. However, there is a need for faster and cheaper laboratory and analysis methods to make NIPT more widely accessible. We have developed a novel software package for detection of fetal aneuploidies from next-generation low-coverage whole genome sequencing data. Our tool - NIPTmer - is based on counting pre-defined per-chromosome sets of unique k-mers from raw sequencing data, and applying linear regression model on the counts. Additionally, the filtering process used for k-mer list creation allows one to take into account the genetic variance in a specific sample, thus reducing the source of uncertainty. The processing time of one sample is less than 10 CPU-minutes on a high-end workstation. NIPTmer was validated on a cohort of 583 NIPT samples and it correctly predicted 37 non-mosaic fetal aneuploidies. NIPTmer has the potential to reduce significantly the time and complexity of NIPT post-sequencing analysis compared to mapping-based methods. For non-commercial users the software package is freely available at http://bioinfo.ut.ee/NIPTMer/ .

Primer3_masker: integrating masking of template sequence with primer design software.

Summary: Designing PCR primers for amplifying regions of eukaryotic genomes is a complicated task because the genomes contain a large number of repeat sequences and other regions unsuitable for amplification by PCR. We have developed a novel k-mer based masking method that uses a statistical model to detect and mask failure-prone regions on the DNA template prior to primer design. We implemented the software as a standalone software primer3_masker and integrated it into the primer design program Primer3. Availability and implementation: The standalone version of primer3_masker is implemented in C. The source code is freely available at https://github.com/bioinfo-ut/primer3_masker/ (standalone version for Linux and macOS) and at https://github.com/primer3-org/primer3/ (integrated version). Primer3 web application that allows masking sequences of 196 animal and plant genomes is available at http://primer3.ut.ee/. Contact: maido.remm@ut.ee. Supplementary information: Supplementary data are available at Bioinformatics online.

FastGT: an alignment-free method for calling common SNVs directly from raw sequencing reads.

We have developed a computational method that counts the frequencies of unique k-mers in FASTQ-formatted genome data and uses this information to infer the genotypes of known variants. FastGT can detect the variants in a 30x genome in less than 1 hour using ordinary low-cost server hardware. The overall concordance with the genotypes of two Illumina "Platinum" genomes is 99.96%, and the concordance with the genotypes of the Illumina HumanOmniExpress is 99.82%. Our method provides k-mer database that can be used for the simultaneous genotyping of approximately 30 million single nucleotide variants (SNVs), including >23,000 SNVs from Y chromosome. The source code of FastGT software is available at GitHub (https://github.com/bioinfo-ut/GenomeTester4/).

StrainSeeker: fast identification of bacterial strains from raw sequencing reads using user-provided guide trees.

BACKGROUND: Fast, accurate and high-throughput identification of bacterial isolates is in great demand. The present work was conducted to investigate the possibility of identifying isolates from unassembled next-generation sequencing reads using custom-made guide trees. RESULTS: A tool named StrainSeeker was developed that constructs a list of specific k-mers for each node of any given Newick-format tree and enables the identification of bacterial isolates in 1-2 min. It uses a novel algorithm, which analyses the observed and expected fractions of node-specific k-mers to test the presence of each node in the sample. This allows StrainSeeker to determine where the isolate branches off the guide tree and assign it to a clade whereas other tools assign each read to a reference genome. Using a dataset of 100 Escherichia coli isolates, we demonstrate that StrainSeeker can predict the clades of E. coli with 92% accuracy and correct tree branch assignment with 98% accuracy. Twenty-five thousand Illumina HiSeq reads are sufficient for identification of the strain. CONCLUSION: StrainSeeker is a software program that identifies bacterial isolates by assigning them to nodes or leaves of a custom-made guide tree. StrainSeeker's web interface and pre-computed guide trees are available at http://bioinfo.ut.ee/strainseeker. Source code is stored at GitHub: https://github.com/bioinfo-ut/StrainSeeker.

A novel hypothesis for histone-to-protamine transition in Bos taurus spermatozoa.

DNA compaction with protamines in sperm is essential for successful fertilization. However, a portion of sperm chromatin remains less tightly packed with histones, which genomic location and function remain unclear. We extracted and sequenced histone-associated DNA from sperm of nine ejaculates from three bulls. We found that the fraction of retained histones varied between samples, but the variance was similar between samples from the same and different individuals. The most conserved regions showed similar abundance across all samples, whereas in other regions, their presence correlated with the size of histone fraction. This may refer to gradual histone-protamine transition, where easily accessible genomic regions, followed by the less accessible regions are first substituted by protamines. Our results confirm those from previous studies that histones remain in repetitive genome elements, such as centromeres, and added new findings of histones in rRNA and SRP RNA gene clusters and indicated histone enrichment in some spermatogenesis-associated genes, but not in genes of early embryonic development. Our functional analysis revealed significant overrepresentation of cGMP-dependent protein kinase G (cGMP-PKG) pathway genes among histone-enriched genes. This pathway is known for its importance in pre-fertilization sperm events. In summary, a novel hypothesis for gradual histone-to-protamine transition in sperm maturation was proposed. We believe that histones may contribute structural information into early embryo by epigenetically modifying centromeric chromatin and other types of repetitive DNA. We also suggest that sperm histones are retained in genes needed for sperm development, maturation and fertilization, as these genes are transcriptionally active shortly prior to histone-to-protamine transition.

GenomeTester4: a toolkit for performing basic set operations - union, intersection and complement on k-mer lists.

BACKGROUND: K-mer-based methods of genome analysis have attracted great interest because they do not require genome assembly and can be performed directly on sequencing reads. Many analysis tasks require one to compare k-mer lists from different sequences to find words that are either unique to a specific sequence or common to many sequences. However, no stand-alone k-mer analysis tool currently allows one to perform these algebraic set operations. FINDINGS: We have developed the GenomeTester4 toolkit, which contains a novel tool GListCompare for performing union, intersection and complement (difference) set operations on k-mer lists. We provide examples of how these general operations can be combined to solve a variety of biological analysis tasks. CONCLUSIONS: GenomeTester4 can be used to simplify k-mer list manipulation for many biological analysis tasks.

Haplotype phasing and inheritance of copy number variants in nuclear families.

DNA copy number variants (CNVs) that alter the copy number of a particular DNA segment in the genome play an important role in human phenotypic variability and disease susceptibility. A number of CNVs overlapping with genes have been shown to confer risk to a variety of human diseases thus highlighting the relevance of addressing the variability of CNVs at a higher resolution. So far, it has not been possible to deterministically infer the allelic composition of different haplotypes present within the CNV regions. We have developed a novel computational method, called PiCNV, which enables to resolve the haplotype sequence composition within CNV regions in nuclear families based on SNP genotyping microarray data. The algorithm allows to i) phase normal and CNV-carrying haplotypes in the copy number variable regions, ii) resolve the allelic copies of rearranged DNA sequence within the haplotypes and iii) infer the heritability of identified haplotypes in trios or larger nuclear families. To our knowledge this is the first program available that can deterministically phase null, mono-, di-, tri- and tetraploid genotypes in CNV loci. We applied our method to study the composition and inheritance of haplotypes in CNV regions of 30 HapMap Yoruban trios and 34 Estonian families. For 93.6% of the CNV loci, PiCNV enabled to unambiguously phase normal and CNV-carrying haplotypes and follow their transmission in the corresponding families. Furthermore, allelic composition analysis identified the co-occurrence of alternative allelic copies within 66.7% of haplotypes carrying copy number gains. We also observed less frequent transmission of CNV-carrying haplotypes from parents to children compared to normal haplotypes and identified an emergence of several de novo deletions and duplications in the offspring.

Fast masking of repeated primer binding sites in eukaryotic genomes.

In this article we describe the working principle and a list of practical applications for GenomeMasker-a program that finds and masks all repeated DNA motifs in fully sequenced genomes. The GenomeMasker exhaustively finds and masks all repeated DNA motifs in studied genomes. The software is optimized for PCR primer design. The algorithm is designed for high-throughput work, allowing masking of large DNA regions, even entire eukaryotic genomes. Additionally, the software is able to predict all alternative PCR products from studied genomes for thousands of candidate PCR primer pairs. Practical applications of the GenomeMasker are shown for command-line version of the GenomeMasker, which can be downloaded from http://bioinfo.ut.ee/download/. Graphical Web interfaces with limited options are available at http://bioinfo.ut.ee/genometester/ and http://bioinfo.ut.ee/snpmasker/.

MultiPLX: automatic grouping and evaluation of PCR primers.

In this chapter we describe MultiPLX-a tool for automatic grouping of PCR primers for multiplexed PCR. Both generic working principle and step-by-step practical procedures with examples are presented. MultiPLX performs grouping by calculating many important interaction levels between the different primer pairs and then distributes primer pairs to groups so that the strength of unwanted interactions is kept below user-defined compatibility level. In addition it can be used to select optimal primer pairs for multiplexing from list of candidates. MultiPLX can be downloaded from http://bioinfo.ut.ee/?page_id=167. Graphical web-based interface to most functions of MultiPLX is available at http://bioinfo.ut.ee/multiplx/.

Position-specific scoring matrix and hidden Markov model complement each other for the prediction of conopeptide superfamilies.

Classified into 16 superfamilies, conopeptides are the main component of cone snail venoms that attract growing interest in pharmacology and drug discovery. The conventional approach to assigning a conopeptide to a superfamily is based on a consensus signal peptide of the precursor sequence. While this information is available at the genomic or transcriptomic levels, it is not present in amino acid sequences of mature bioactives generated by proteomic studies. As the number of conopeptide sequences is increasing exponentially with the improvement in sequencing techniques, there is a growing need for automating superfamily elucidation. To face this challenge we have defined distinct models of the signal sequence, propeptide region and mature peptides for each of the superfamilies containing more than 5 members (14 out of 16). These models rely on two robust techniques namely, Position-Specific Scoring Matrices (PSSM, also named generalized profiles) and hidden Markov models (HMM). A total of 50 PSSMs and 47 HMM profiles were generated. We confirm that propeptide and mature regions can be used to efficiently classify conopeptides lacking a signal sequence. Furthermore, the combination of all three-region models demonstrated improvement in the classification rates and results emphasise how PSSM and HMM approaches complement each other for superfamily determination. The 97 models were validated and offer a straightforward method applicable to large sequence datasets.

ConoDictor: a tool for prediction of conopeptide superfamilies.

ConoDictor is a tool that enables fast and accurate classification of conopeptides into superfamilies based on their amino acid sequence. ConoDictor combines predictions from two complementary approaches-profile hidden Markov models and generalized profiles. Results appear in a browser as tables that can be downloaded in various formats. This application is particularly valuable in view of the exponentially increasing number of conopeptides that are being identified. ConoDictor was written in Perl using the common gateway interface module with a php submission page. Sequence matching is performed with hmmsearch from HMMER 3 and ps_scan.pl from the pftools 2.3 package. ConoDictor is freely accessible at http://conco.ebc.ee.

Label-free, multiplexed detection of bacterial tmRNA using silicon photonic microring resonators.

A label-free biosensing method for the sensitive detection and identification of bacterial transfer-messenger RNA (tmRNA) is presented employing arrays of silicon photonic microring resonators. Species specific tmRNA molecules are targeted by complementary DNA capture probes that are covalently attached to the sensor surface. Specific hybridization is monitored in near real-time by observing the resonance wavelength shift of each individual microring. The sensitivity of the biosensing platform allowed for detection down to 53 fmol of Streptococcus pneumoniae tmRNA, equivalent to approximately 3.16×10(7) CFU of bacteria. The simplicity and scalability of this biosensing approach makes it a promising tool for the rapid identification of different bacteria via tmRNA profiling.

Identification and classification of conopeptides using profile Hidden Markov Models.

Conopeptides are small toxins produced by predatory marine snails of the genus Conus. They are studied with increasing intensity due to their potential in neurosciences and pharmacology. The number of existing conopeptides is estimated to be 1 million, but only about 1000 have been described to date. Thanks to new high-throughput sequencing technologies the number of known conopeptides is likely to increase exponentially in the near future. There is therefore a need for a fast and accurate computational method for identification and classification of the novel conopeptides in large data sets. 62 profile Hidden Markov Models (pHMMs) were built for prediction and classification of all described conopeptide superfamilies and families, based on the different parts of the corresponding protein sequences. These models showed very high specificity in detection of new peptides. 56 out of 62 models do not give a single false positive in a test with the entire UniProtKB/Swiss-Prot protein sequence database. Our study demonstrates the usefulness of mature peptide models for automatic classification with accuracy of 96% for the mature peptide models and 100% for the pro- and signal peptide models. Our conopeptide profile HMMs can be used for finding and annotation of new conopeptides from large datasets generated by transcriptome or genome sequencing. To our knowledge this is the first time this kind of computational method has been applied to predict all known conopeptide superfamilies and some conopeptide families.

Detection of NASBA amplified bacterial tmRNA molecules on SLICSel designed microarray probes.

BACKGROUND: We present a comprehensive technological solution for bacterial diagnostics using tmRNA as a marker molecule. A robust probe design algorithm for microbial detection microarray is implemented. The probes were evaluated for specificity and, combined with NASBA (Nucleic Acid Sequence Based Amplification) amplification, for sensitivity. RESULTS: We developed a new web-based program SLICSel for the design of hybridization probes, based on nearest-neighbor thermodynamic modeling. A SLICSel minimum binding energy difference criterion of 4 kcal/mol was sufficient to design of Streptococcus pneumoniae tmRNA specific microarray probes. With lower binding energy difference criteria, additional hybridization specificity tests on the microarray were needed to eliminate non-specific probes. Using SLICSel designed microarray probes and NASBA we were able to detect S. pneumoniae tmRNA from a series of total RNA dilutions equivalent to the RNA content of 0.1-10 CFU. CONCLUSIONS: The described technological solution and both its separate components SLICSel and NASBA-microarray technology independently are applicative for many different areas of microbial diagnostics.

Detection of tmRNA molecules on microarrays at low temperatures using helper oligonucleotides.

BACKGROUND: The hybridization of synthetic Streptococcus pneumoniae tmRNA on a detection microarray is slow at 34 degrees C resulting in low signal intensities. RESULTS: We demonstrate that adding specific DNA helper oligonucleotides (chaperones) to the hybridization buffer increases the signal strength at a given temperature and thus makes the specific detection of Streptococcus pneumoniae tmRNA more sensitive. No loss of specificity was observed at low temperatures compared to hybridization at 46 degrees C. The effect of the chaperones can be explained by disruption of the strong secondary and tertiary structure of the target RNA by the selective hybridization of helper molecules. The amplification of the hybridization signal strength by chaperones is not necessarily local; we observed increased signal intensities in both local and distant regions of the target molecule. CONCLUSIONS: The sensitivity of the detection of tmRNA at low temperature can be increased by chaperone oligonucleotides. Due to the complexity of RNA secondary and tertiary structures the effect of any individual chaperone is currently not predictable.

Fluorescent labeling of NASBA amplified tmRNA molecules for microarray applications.

BACKGROUND: Here we present a novel promising microbial diagnostic method that combines the sensitivity of Nucleic Acid Sequence Based Amplification (NASBA) with the high information content of microarray technology for the detection of bacterial tmRNA molecules. The NASBA protocol was modified to include aminoallyl-UTP (aaUTP) molecules that were incorporated into nascent RNA during the NASBA reaction. Post-amplification labeling with fluorescent dye was carried out subsequently and tmRNA hybridization signal intensities were measured using microarray technology. Significant optimization of the labeled NASBA protocol was required to maintain the required sensitivity of the reactions. RESULTS: Two different aaUTP salts were evaluated and optimum final concentrations were identified for both. The final 2 mM concentration of aaUTP Li-salt in NASBA reaction resulted in highest microarray signals overall, being twice as high as the strongest signals with 1 mM aaUTP Na-salt. CONCLUSION: We have successfully demonstrated efficient combination of NASBA amplification technology with microarray based hybridization detection. The method is applicative for many different areas of microbial diagnostics including environmental monitoring, bio threat detection, industrial process monitoring and clinical microbiology.

Fast masking of repeated primer binding sites in eukaryotic genomes.

In this article, we describe the working principle and a list of practical applications for GenomeMasker-a program that finds and masks all repeated DNA motifs in fully sequenced genomes. The GenomeMasker exhaustively finds and masks all repeated DNA motifs in studied genomes. The software is optimized for polymerase chain reaction (PCR) primer design. The algorithm is designed for high-throughput work, allowing masking of large DNA regions, even entire eukaryotic genomes. Additionally, the software is able to predict all alternative PCR products from studied genomes for thousands of candidate PCR primer pairs. Practical applications of the GenomeMasker are shown for command-line version of the GenomeMasker, which can be downloaded from http://bioinfo.ut.ee/download/. Graphical Web interfaces with limited options are available at http://bioinfo.ut.ee/genometester/ and http://bioinfo.ut.ee/snpmasker/.