South Asia harbors one of the highest levels genetic diversity in Eurasia, which could be interpreted as a result of its long-term large effective population size and of admixture during its complex demographic history. In contrast to Pakistani populations, populations of Indian origin have been underrepresented in previous genomic scans of positive selection and population structure. Here we report data for more than 600,000 SNP markers genotyped in 142 samples from 30 ethnic groups in India. Combining our results with other available genome-wide data, we show that Indian populations are characterized by two major ancestry components, one of which is spread at comparable frequency and haplotype diversity in populations of South and West Asia and the Caucasus. The second component is more restricted to South Asia and accounts for more than 50% of the ancestry in Indian populations. Haplotype diversity associated with these South Asian ancestry components is significantly higher than that of the components dominating the West Eurasian ancestry palette. Modeling of the observed haplotype diversities suggests that both Indian ancestry components are older than the purported Indo-Aryan invasion 3,500 YBP. Consistent with the results of pairwise genetic distances among world regions, Indians share more ancestry signals with West than with East Eurasians. However, compared to Pakistani populations, a higher proportion of their genes show regionally specific signals of high haplotype homozygosity. Among such candidates of positive selection in India are MSTN and DOK5, both of which have potential implications in lipid metabolism and the etiology of type 2 diabetes.

The pattern of linkage disequilibrium (LD) is critical for association studies, in which disease-causing variants are identified by allelic association with adjacent markers. The aim of this study is to compare the LD patterns in several distinct European populations. We analyzed four genomic regions (in total, 749 kb) containing candidate genes for complex traits. Individuals were genotyped for markers that are evenly distributed at an average spacing of approximately 2-4 kb in eight population-based samples from ongoing epidemiological studies across Europe. The Centre d'Etude du Polymorphisme Humain (CEPH) trios of the HapMap project were included and were used as a reference population. In general, we observed a conservation of the LD patterns across European samples. Nevertheless, shifts in the positions of the boundaries of high-LD regions can be demonstrated between populations, when assessed by a novel procedure based on bootstrapping. Transferability of LD information among populations was also tested. In two of the analyzed gene regions, sets of tagging single-nucleotide polymorphisms (tagSNPs) selected from the HapMap CEPH trios performed surprisingly well in all local European samples. However, significant variation in the other two gene regions predicts a restricted applicability of CEPH-derived tagging markers. Simulations based on our data set show the extent to which further gain in tagSNP efficiency and transferability can be achieved by increased SNP density.

This study has evaluated the correlation between different carbapenemases detection methods on carbapenem non-susceptible Klebsiella pneumoniae strains from Northern and Eastern Europe; 31 institutions in 9 countries participated in the research project, namely Finland, Estonia, Latvia, Lithuania, Russia, St. Petersburg, Poland, Belarus, Ukraine, and Georgia. During the research program, a total of 5,001 clinical K. pneumoniae isolates were screened for any carbapenem non-susceptibility by the disk diffusion method, Vitek 2 or Phoenix system following the EUCAST guideline on detection of resistance mechanisms, version 1.0. Strains isolated from outpatients and hospitalized patients from April 2015 to June 2015 were included. All types of samples (blood, pus, urine, etc.) excluding fecal screening or fecal colonization samples have been represented. In total, 171 carbapenemase screening-positive K. pneumoniae isolates (3.42%) were found and characterized. Several methods were used for detection of carbapenemases production, including Luminex assay (PCR and hybridization), whole genome sequencing, MALDI-TOF based Imipenem degradation assay, and immunochromatography testing. Minimal inhibitory concentration determination for Meropenem by agar-based gradient method was also used. Finally, 83 K. pneumoniae strains were carbapenemase negative by all confirmation methods (49.4% of all screening-positive ones), 74 - positive by three methods (44.0%), 8 - positive by two methods (4.8%) and 3 - positive by only one method (1.8%). The sensitivity of the tests was 96.3% for Whole genome sequencing and MALDI-TOF assay (both three undetected cases), and 95.1% for Luminex-Carba (4 undetected cases). The most commonly detected carbapenemases were NDM (n = 54) and OXA-48 (n = 26), followed by KPC-2, VIM-5, and OXA-72 (one case of each). Our results showed that different types of carbapenemases can be detected in the countries involved in the project. The sensitivity of our methods for carbapenemase detection (including screening as a first step and further confirmation tests) was >95%, but we would recommend using different methods to increase the sensitivity of detection and make it more precise.

Recently, alignment-free sequence analysis methods have gained popularity in the field of personal genomics. These methods are based on counting frequencies of short k-mer sequences, thus allowing faster and more robust analysis compared to traditional alignment-based methods.

In this study, we compare the genetic ancestry of individuals from two as yet genetically unstudied cultural traditions in Estonia in the context of available modern and ancient datasets: 15 from the Late Bronze Age stone-cist graves (1200-400 BC) (EstBA) and 6 from the Pre-Roman Iron Age tarand cemeteries (800/500 BC-50 AD) (EstIA). We also included 5 Pre-Roman to Roman Iron Age Ingrian (500 BC-450 AD) (IngIA) and 7 Middle Age Estonian (1200-1600 AD) (EstMA) individuals to build a dataset for studying the demographic history of the northern parts of the Eastern Baltic from the earliest layer of Mesolithic to modern times. Our findings are consistent with EstBA receiving gene flow from regions with strong Western hunter-gatherer (WHG) affinities and EstIA from populations related to modern Siberians. The latter inference is in accordance with Y chromosome (chrY) distributions in present day populations of the Eastern Baltic, as well as patterns of autosomal variation in the majority of the westernmost Uralic speakers [1-5]. This ancestry reached the coasts of the Baltic Sea no later than the mid-first millennium BC; i.e., in the same time window as the diversification of west Uralic (Finnic) languages [6]. Furthermore, phenotypic traits often associated with modern Northern Europeans, like light eyes, hair, and skin, as well as lactose tolerance, can be traced back to the Bronze Age in the Eastern Baltic. VIDEO ABSTRACT.

Fast and reliable analytical methods for the identification of plants from metagenomic samples play an important role in identifying the components of complex mixtures of processed biological materials, including food, herbal products, gut contents or environmental samples. Different PCR-based methods that are commonly used for plant identification from metagenomic samples are often inapplicable due to DNA degradation, a low level of successful amplification or a lack of detection power. We introduce a method that combines metagenomic sequencing and an alignment-free k-mer based approach for the identification of plant DNA in processed metagenomic samples. Our method identifies plant DNA directly from metagenomic sequencing reads and does not require mapping or assembly of the reads. We identified more than 31,000 Lupinus-specific 32-mers from assembled chloroplast genome sequences. We demonstrate that lupin DNA can be detected from controlled mixtures of sequences from target species (different Lupinus species) and closely related non-target species (Arachis hypogaea, Glycine max, Pisum sativum, Vicia faba, Phaseolus vulgaris, Lens culinaris, and Cicer arietinum). Moreover, these 32-mers are detectable in the following processed samples: lupin flour, conserved seeds and baked cookies containing different amounts of lupin flour. Under controlled conditions, lupin-specific components are detectable in baked cookies containing a minimum of 0.05% of lupin flour in wheat flour.

Tribbles homolog 3 (TRIB3) is pseudokinase involved in intracellular regulatory processes and has been implicated in several diseases. In this article, we report that human TRIB3 promoter contains a 33-bp variable number tandem repeat (VNTR) and characterize the heterogeneity and function of this genetic element. Analysis of human populations around the world uncovered the existence of alleles ranging from 1 to 5 copies of the repeat, with 2-, 3- and 5-copy alleles being the most common but displaying considerable geographical differences in frequency. The repeated sequence overlaps a C/EBP-ATF transcriptional regulatory element and is highly conserved, but not repeated, in various mammalian species, including great apes. The repeat is however evident in Neanderthal and Denisovan genomes. Reporter plasmid experiments in human cell culture reveal that an increased copy number of the TRIB3 promoter 33-bp repeat results in increased transcriptional activity. In line with this, analysis of whole genome sequencing and RNA-Seq data from human cohorts demonstrates that the copy number of TRIB3 promoter 33-bp repeats is positively correlated with TRIB3 mRNA expression level in many tissues throughout the body. Moreover, the copy number of the TRIB3 33-bp repeat appears to be linked to known TRIB3 eQTL SNPs as well as TRIB3 SNPs reported in genetic association studies. Taken together, the results indicate that the promoter 33-bp VNTR constitutes a causal variant for TRIB3 expression variation between individuals and could underlie the results of SNP-based genetic studies.

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.

Polymerase chain reaction (PCR) is a basic molecular biology technique with a multiplicity of uses, including deoxyribonucleic acid cloning and sequencing, functional analysis of genes, diagnosis of diseases, genotyping and discovery of genetic variants. Reliable primer design is crucial for successful PCR, and for over a decade, the open-source Primer3 software has been widely used for primer design, often in high-throughput genomics applications. It has also been incorporated into numerous publicly available software packages and web services. During this period, we have greatly expanded Primer3's functionality. In this article, we describe Primer3's current capabilities, emphasizing recent improvements. The most notable enhancements incorporate more accurate thermodynamic models in the primer design process, both to improve melting temperature prediction and to reduce the likelihood that primers will form hairpins or dimers. Additional enhancements include more precise control of primer placement-a change motivated partly by opportunities to use whole-genome sequences to improve primer specificity. We also added features to increase ease of use, including the ability to save and re-use parameter settings and the ability to require that individual primers not be used in more than one primer pair. We have made the core code more modular and provided cleaner programming interfaces to further ease integration with other software. These improvements position Primer3 for continued use with genome-scale data in the decade ahead.

Prokaryotes are in general believed to possess small, compactly organized genomes, with repetitive sequences forming only a small part of them. Nonetheless, many prokaryotic genomes in fact contain species-specific repeats (>85 bp long genomic sequences with less than 60% identity to other species) as we have previously demonstrated. However, it is not known at present how frequent such species-specific repeats are and what their functional roles in bacterial genomes may be. Therefore, we have conducted a comprehensive survey of prokaryotic species-specific repeats and characterized them to examine as to whether there are functional classes among different repeats or not and how they are mutually related to each other. Of the 613 distinct prokaryotic species analyzed, 97% were found to contain at least one species-specific repeats. It seems interesting to note that the species-specific repeats thus identified appear to be functionally variable in different genomes: in some genomes, they are mostly associated with duplicated protein-coding genes, whereas in some other genomes with rRNA and tRNA genes. Contrary to what may be expected, only one-fourth of the species-specific repeats were found to be associated with mobile genetic elements.

Endophytes are microbes and fungi that live inside plant tissues without damaging the host. Herein we examine the dynamic changes in the endophytic bacterial community in potato (Solanum tuberosum) tuber in response to pathogenic infection by Pectobacterium atrosepticum, which causes soft rot in numerous economically important crops. We quantified community changes using both cultivation and next-generation sequencing of the 16S rRNA gene and found that, despite observing significant variability in both the mass of macerated tissue and structure of the endophytic community between individual potato tubers, P. atrosepticum is always taken over by the endophytes during maceration. 16S rDNA sequencing revealed bacteria from the phyla Proteobacteria, Actinobacteria, Firmicutes, Bacteroidetes, Fusobacteria, Verrucomicrobia, Acidobacteria, TM7, and Deinococcus-Thermus. Prior to infection, Propionibacterium acnes is frequently among the dominant taxa, yet is out competed by relatively few dominant taxa as the infection proceeds. Two days post-infection, the most abundant sequences in macerated potato tissue are Gammaproteobacteria. The most dominant genera are Enterobacter and Pseudomonas. Eight days post-infection, the number of anaerobic pectolytic Clostridia increases, probably due to oxygen depletion. These results demonstrate that the pathogenesis is strictly initiated by the pathogen (sensu stricto) and proceeds with a major contribution from the endophytic community.

The design of oligonucleotides and PCR primers for studying large genomes is complicated by the redundancy of sequences. The eukaryotic genomes are particularly difficult to study due to abundant repeats. The speed of most existing primer evaluation programs is not sufficient for large-scale experiments.

New technologies have enabled genome-wide association studies to be conducted with hundreds of thousands of genotyped SNPs. Several different first-generation genome-wide panels of SNPs have been commercialized. The total amount of common genetic variation is still unknown; however, the coverage of commercial panels can be evaluated against reference population samples genotyped by the International HapMap project. Less information is available about coverage in samples from other populations.

We have developed an easy-to-use and memory-efficient method called PhenotypeSeeker that (a) identifies phenotype-specific k-mers, (b) generates a k-mer-based statistical model for predicting a given phenotype and (c) predicts the phenotype from the sequencing data of a given bacterial isolate. The method was validated on 167 Klebsiella pneumoniae isolates (virulence), 200 Pseudomonas aeruginosa isolates (ciprofloxacin resistance) and 459 Clostridium difficile isolates (azithromycin resistance). The phenotype prediction models trained from these datasets obtained the F1-measure of 0.88 on the K. pneumoniae test set, 0.88 on the P. aeruginosa test set and 0.97 on the C. difficile test set. The F1-measures were the same for assembled sequences and raw sequencing data; however, building the model from assembled genomes is significantly faster. On these datasets, the model building on a mid-range Linux server takes approximately 3 to 5 hours per phenotype if assembled genomes are used and 10 hours per phenotype if raw sequencing data are used. The phenotype prediction from assembled genomes takes less than one second per isolate. Thus, PhenotypeSeeker should be well-suited for predicting phenotypes from large sequencing datasets. PhenotypeSeeker is implemented in Python programming language, is open-source software and is available at GitHub (https://github.com/bioinfo-ut/PhenotypeSeeker/).

We aimed to identify the main spreading clones, describe the resistance mechanisms associated with carbapenem- and/or multidrug-resistant P. aeruginosa and characterize patients at risk of acquiring these strains in Estonian hospitals.

Chromosomal toxin-antitoxin (TA) systems are widespread genetic elements among bacteria, yet, despite extensive studies in the last decade, their biological importance remains ambivalent. The ability of TA-encoded toxins to affect stress tolerance when overexpressed supports the hypothesis of TA systems being associated with stress adaptation. However, the deletion of TA genes has usually no effects on stress tolerance, supporting the selfish elements hypothesis. Here, we aimed to evaluate the cost and benefits of chromosomal TA systems to Pseudomonas putida. We show that multiple TA systems do not confer fitness benefits to this bacterium as deletion of 13 TA loci does not influence stress tolerance, persistence or biofilm formation. Our results instead show that TA loci are costly and decrease the competitive fitness of P. putida. Still, the cost of multiple TA systems is low and detectable in certain conditions only. Construction of antitoxin deletion strains showed that only five TA systems code for toxic proteins, while other TA loci have evolved towards reduced toxicity and encode non-toxic or moderately potent proteins. Analysis of P. putida TA systems' homologs among fully sequenced Pseudomonads suggests that the TA loci have been subjected to purifying selection and that TA systems spread among bacteria by horizontal gene transfer.

When nutrients run out, bacteria enter a dormant metabolic state. This low or undetectable metabolic activity helps bacteria to preserve their scant reserves for the future needs, yet it also diminishes their ability to scan the environment for new growth-promoting substrates. However, neighboring microbial growth is a reliable indicator of a favorable environment and can thus serve as a cue for exiting dormancy. Here we report that for Escherichia coli and Pseudomonas aeruginosa this cue is provided by the basic peptidoglycan unit (i.e. muropeptide). We show that several forms of muropeptides from a variety of bacterial species can stimulate growth resumption of dormant cells and the sugar - peptide bond is crucial for this activity. These results, together with previous research that identifies muropeptides as a germination signal for bacterial spores, and their detection by mammalian immune cells, show that muropeptides are a universal cue for bacterial growth.

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/).

Plasmids play an important role in the dissemination of antibiotic resistance, making their detection an important task. Using whole genome sequencing (WGS), it is possible to capture both bacterial and plasmid sequence data, but short read lengths make plasmid detection a complex problem.

Genomes exhibit large regions with segmental copy number variation, many of which include entire genes and are multiallelic. We have developed a computational method GeneToCN that counts the frequencies of gene-specific k-mers in FASTQ files and uses this information to infer copy number of the gene. We validated the copy number predictions for amylase genes (AMY1, AMY2A, AMY2B) using experimental data from digital droplet PCR (ddPCR) on 39 individuals and observed a strong correlation (R = 0.99) between GeneToCN predictions and experimentally determined copy numbers. An additional validation on FCGR3 genes showed a higher concordance for FCGR3A compared to two other methods, but reduced accuracy for FCGR3B. We further tested the method on three different genomic regions (SMN, NPY4R, and LPA Kringle IV-2 domain). Predicted copy number distributions of these genes in a set of 500 individuals from the Estonian Biobank were in good agreement with the previously published studies. In addition, we investigated the possibility to use GeneToCN on sequencing data generated by different technologies by comparing copy number predictions from Illumina, PacBio, and Oxford Nanopore data of the same sample. Despite the differences in variability of k-mer frequencies, all three sequencing technologies give similar predictions with GeneToCN.