Single Nucleotide Polymorphism Calling Research Articles

CascAGS: Comparative Analysis of SNP Calling Methods for Human Genome Data in the Absence of Gold Standard.

The development of third-generation sequencing has accelerated the boom of single nucleotide polymorphism (SNP) calling methods, but evaluating accuracy remains challenging owing to the absence of the SNP gold standard. The definitions for without-gold-standard and performance metrics and their estimation are urgently needed. Additionally, the possible correlations between different SNP loci should also be further explored. To address these challenges, we first introduced the concept of a gold standard and imperfect gold standard under the consistency framework and gave the corresponding definitions of sensitivity and specificity. A latent class model (LCM) was established to estimate the sensitivity and specificity of callers. Furthermore, we incorporated different dependency structures into LCM to investigate their impact on sensitivity and specificity. The performance of LCM was illustrated by comparing the accuracy of BCFtools, DeepVariant, FreeBayes, and GATK on various datasets. Through estimations across multiple datasets, the results indicate that LCM is well-suitable for evaluating callers without the SNP gold standard, and accurate inclusion of the dependency between variations is crucial for better performance ranking. DeepVariant has a higher sum of sensitivity and specificity than other callers, followed by GATK and BCFtools. FreeBayes has low sensitivity but high specificity. Notably, appropriate sequencing coverage is another important factor for precise callers' evaluation. Most importantly, a web interface for assessing and comparing different callers was developed to simplify the evaluation process.

TigerBase: A DNA registration system to enhance enforcement and compliance testing of captive tiger facilities

The illegal trade in tigers (Panthera tigris) and their derivatives, such as bones, teeth and pelts, is a major threat to the species’ long-term persistence. As wild tiger populations have dwindled, a large proportion of trafficked tiger products now derive from captive breeding facilities found throughout Asia. Moreover, wild tigers have been poached and laundered into captive facilities, then falsely designated as captive-bred. The establishment of a DNA registration system is recognized as a key tool to monitor compliance of captive facilities, support tiger trade investigations and improve prosecution outcomes. Here, we present a standardised wildlife forensic DNA profiling system for captive tigers called TigerBase. TigerBase has been developed in four South-East Asia countries with captive tiger facilities: Malaysia, Vietnam, Thailand and Lao PDR. TigerBase DNA profile data is based on 60 single nucleotide polymorphism (SNP) markers, genotyped using two different TaqMan®-based approaches: OpenArray® chip (capable of genotyping 60 SNPs for 48 samples in a single chip), and singleplex TaqMan® assays (capable of genotyping one SNP for one sample per reaction). Of the 60 SNPs, 53 are autosomal nuclear markers, suitable for individualisation and parentage applications, two are sex-linked markers, suitable for sexing, and five are mtDNA markers, suitable for maternal subspecies identification. We conducted a series of validation experiments to investigate the reliability and limitations of these SNP genotyping platforms. We found that the OpenArray® chip platform is more appropriate for generating reference data given its greater throughput, while the singleplex TaqMan® assays are more appropriate for genotyping lower quality casework samples, given their higher sensitivity and throughput flexibility. Only 19 autosomal nuclear markers were validated as singleplex TaqMan® assays, which generally provides ample power for individualisation analysis (probability of identity among siblings was <6.9 ×10−4), but may lack power for specific parentage questions, such as determining parentage of an offspring when one of the parent’s genotypes is missing. Further, we have developed pipelines to support standardised SNP calling and decrease the chance of genotyping errors through the use of analytical workflows and synthetic positive controls. We expect the implementation of TigerBase will enhance enforcement of tiger trafficking cases and encourage compliance among captive tiger facilities, together contributing to combatting the illegal tiger trade.

Simultaneous de novo calling and phasing of genetic variants at chromosome-scale using NanoStrand-seq

The successful accomplishment of the first telomere-to-telomere human genome assembly, T2T-CHM13, marked a milestone in achieving completeness of the human reference genome. The upcoming era of genome study will focus on fully phased diploid genome assembly, with an emphasis on genetic differences between individual haplotypes. Most existing sequencing approaches only achieved localized haplotype phasing and relied on additional pedigree information for further whole-chromosome scale phasing. The short-read-based Strand-seq method is able to directly phase single nucleotide polymorphisms (SNPs) at whole-chromosome scale but falls short when it comes to phasing structural variations (SVs). To shed light on this issue, we developed a Nanopore sequencing platform-based Strand-seq approach, which we named NanoStrand-seq. This method allowed for de novo SNP calling with high precision (99.52%) and acheived a superior phasing accuracy (0.02% Hamming error rate) at whole-chromosome scale, a level of performance comparable to Strand-seq for haplotype phasing of the GM12878 genome. Importantly, we demonstrated that NanoStrand-seq can efficiently resolve the MHC locus, a highly polymorphic genomic region. Moreover, NanoStrand-seq enabled independent direct calling and phasing of deletions and insertions at whole-chromosome level; when applied to long genomic regions of SNP homozygosity, it outperformed the strategy that combined Strand-seq with bulk long-read sequencing. Finally, we showed that, like Strand-seq, NanoStrand-seq was also applicable to primary cultured cells. Together, here we provided a novel methodology that enabled interrogation of a full spectrum of haplotype-resolved SNPs and SVs at whole-chromosome scale, with broad applications for species with diploid or even potentially polypoid genomes.

Bsgenova: an accurate, robust, and fast genotype caller for bisulfite-sequencing data

BackgroundBisulfite sequencing (BS-Seq) is a fundamental technique for characterizing DNA methylation profiles. Genotype calling from bisulfite-converted BS-Seq data allows allele-specific methylation analysis and the concurrent exploration of genetic and epigenetic profiles. Despite various methods have been proposed, single nucleotide polymorphisms (SNPs) calling from BS-Seq data, particularly for SNPs on chromosome X and in the presence of contaminative data, poses ongoing challenges.ResultsWe introduce bsgenova, a novel SNP caller tailored for bisulfite sequencing data, employing a Bayesian multinomial model. The performance of bsgenova is assessed by comparing SNPs called from real-world BS-Seq data with those from corresponding whole-genome sequencing (WGS) data across three human cell lines. bsgenova is both sensitive and precise, especially for chromosome X, compared with three existing methods. Moreover, in the presence of low-quality reads, bsgenova outperforms other methods notably. In addition, bsgenova is meticulously implemented, leveraging matrix imputation and multi-process parallelization. Compared to existing methods, bsgenova stands out for its speed and efficiency in memory and disk usage. Furthermore, bsgenova integrates bsextractor, a methylation extractor, enhancing its flexibility and expanding its utility.ConclusionsWe introduce bsgenova for SNP calling from bisulfite-sequencing data. The source code is available at https://github.com/hippo-yf/bsgenova under license GPL-3.0.

Different reference genomes determine different results: Comparing SNP calling in RAD-seq of Engelhardia roxburghiana using different reference genomes

Advances in next-generation sequencing (NGS) have significantly reduced the cost and improved the efficiency of obtaining single nucleotide polymorphism (SNP) markers, particularly through restriction site-associated DNA sequencing (RAD-seq). Meanwhile, the progression in whole genome sequencing has led to the utilization of an increasing number of reference genomes in SNP calling processes. This study utilized RAD-seq data from 242 individuals of Engelhardia roxburghiana, a tropical tree of the walnut family (Juglandaceae), with SNP calling conducted using the STACKS pipeline. We aimed to compare both reference-based approaches, namely, employing a closely related species as the reference genome versus the species itself as the reference genome, to evaluate their respective merits and limitations. Our findings indicate a substantial discrepancy in the number of obtained SNPs between using a closely related species as opposed to the species itself as reference genomes, the former yielded approximately an order of magnitude fewer SNPs compared to the latter. While the missing rate of individuals and sites of the final SNPs obtained in the two scenarios showed no significant difference. The results showed that using the reference genome of the species itself tends to be prioritized in RAD-seq studies. However, if this is unavailable, considering closely related genomes is feasible due to their wide applicability and low missing rate as alternatives. This study contributes to enrich the understanding of the impact of SNP acquisition when utilizing different reference genomes.

FishSNP: a high quality cross-species SNP database of fishes

The progress of aquaculture heavily depends on the efficient utilization of diverse genetic resources to enhance production efficiency and maximize profitability. Single nucleotide polymorphisms (SNPs) have been widely used in the study of aquaculture genomics, genetics, and breeding research since they are the most prevalent molecular markers on the genome. Currently, a large number of SNP markers from cultured fish species are scattered in individual studies, making querying complicated and data reuse problematic. We compiled relevant SNP data from literature and public databases to create a fish SNP database, FishSNP (http://bioinfo.ihb.ac.cn/fishsnp), and also used a unified analysis pipeline to process raw data that the author of the literature did not perform SNP calling on to obtain SNPs with high reliability. This database presently contains 45,690,243 (45 million) nonredundant SNP data for 13 fish species, with 30,288,958 (30 million) of those being high-quality SNPs. The main function of FishSNP is to search, browse, annotate and download SNPs, which provide researchers various and comprehensive associated information.

Ex situ conservation of two rare oak species using microsatellite and SNP markers.

Plant collections held by botanic gardens and arboreta are key components of ex situ conservation. Maintaining genetic diversity in such collections allows them to be used as resources for supplementing wild populations. However, most recommended minimum sample sizes for sufficient ex situ genetic diversity are based on microsatellite markers, and it remains unknown whether these sample sizes remain valid in light of more recently developed next-generation sequencing (NGS) approaches. To address this knowledge gap, we examine how ex situ conservation status and sampling recommendations differ when derived from microsatellites and single nucleotide polymorphisms (SNPs) in garden and wild samples of two threatened oak species. For Quercus acerifolia, SNPs show lower ex situ representation of wild allelic diversity and slightly lower minimum sample size estimates than microsatellites, while results for each marker are largely similar for Q. boyntonii. The application of missing data filters tends to lead to higher ex situ representation, while the impact of different SNP calling approaches is dependent on the species being analyzed. Measures of population differentiation within species are broadly similar between markers, but larger numbers of SNP loci allow for greater resolution of population structure and clearer assignment of ex situ individuals to wild source populations. Our results offer guidance for future ex situ conservation assessments utilizing SNP data, such as the application of missing data filters and the usage of a reference genome, and illustrate that both microsatellites and SNPs remain viable options for botanic gardens and arboreta seeking to ensure the genetic diversity of their collections.

Development and Assessment of SNP Genotyping Arrays for Citrus and Its Close Relatives.

Rapid advancements in technologies provide various tools to analyze fruit crop genomes to better understand genetic diversity and relationships and aid in breeding. Genome-wide single nucleotide polymorphism (SNP) genotyping arrays offer highly multiplexed assays at a relatively low cost per data point. We report the development and validation of 1.4M SNP Axiom® Citrus HD Genotyping Array (Citrus 15AX 1 and Citrus 15AX 2) and 58K SNP Axiom® Citrus Genotyping Arrays for Citrus and close relatives. SNPs represented were chosen from a citrus variant discovery panel consisting of 41 diverse whole-genome re-sequenced accessions of Citrus and close relatives, including eight progenitor citrus species. SNPs chosen mainly target putative genic regions of the genome and are accurately called in both Citrus and its closely related genera while providing good coverage of the nuclear and chloroplast genomes. Reproducibility of the arrays was nearly 100%, with a large majority of the SNPs classified as the most stringent class of markers, "PolyHighResolution" (PHR) polymorphisms. Concordance between SNP calls in sequence data and array data average 98%. Phylogenies generated with array data were similar to those with comparable sequence data and little affected by 3 to 5% genotyping error. Both arrays are publicly available.

VariantDetective: an accurate all-in-one pipeline for detecting consensus bacterial SNPs and SVs.

Genomic variations comprise a spectrum of alterations, ranging from single nucleotide polymorphisms (SNPs) to large-scale structural variants (SVs), which play crucial roles in bacterial evolution and species diversification. Accurately identifying SNPs and SVs is beneficial for subsequent evolutionary and epidemiological studies. This study presents VariantDetective (VD), a novel, user-friendly, and all-in-one pipeline combining SNP and SV calling to generate consensus genomic variants using multiple tools. The VD pipeline accepts various file types as input to initiate SNP and/or SV calling, and benchmarking results demonstrate VD's robustness and high accuracy across multiple tested datasets when compared to existing variant calling approaches. The source code, test data, and relevant information for VD are freely accessible at https://github.com/OLF-Bioinformatics/VariantDetective under the MIT License.

Düşük Kapsamlı WGS Verileri Kullanılarak Hızlı ve Yüksek Doğruluklu Guppy Baz Çağırma Modellerinin Varyant Çağırma Üzerine Etkisinin İncelenmesi

Long-read sequencing technologies such as Oxford Nanopore Technologies (ONT) enabled researchers to sequence long reads fast and cost-effectively. ONT sequencing uses nanopores integrated into semiconductor surfaces and sequences the genomic materials using changes in current across the surface as each nucleotide passes through the nanopore. The default output of ONT sequencers is in FAST5 format. The first and one of the most important steps of ONT data analysis is the conversion of FAST5 files to FASTQ files using “base caller” tools. Generally, base caller tools pre-trained deep learning models to transform electrical signals into reads. Guppy, the most commonly used base caller, uses 2 main model types, fast and high accuracy. Since the computation duration is significantly different between these two models, the effect of models on the variant calling process has not been fully understood. This study aims to evaluate the effect of different models on performance on variant calling.&#x0D; In this study, 15 low-coverage long-read sequencing results coming from different flow cells of NA12878 (gold standard data) were used to compare the variant calling results of Guppy. &#x0D; Obtained results indicated that the number of output FASTQ files, read counts and average read lengths between fast and high accuracy models are not statistically significant while pass/fail ratios of the base called datasets are significantly higher in high accuracy models. Results also indicated that the difference in pass/fail ratios arises in a significant difference in the number of called Single Nucleotide Polymorphisms (SNPs), insertions and deletions (InDels). Interestingly the true positive rates of SNPs are not significantly different. These results show that using fast models for SNP calling does not affect the true positive rates statistically. The primary observation in this study, using fast models does not decrease the true positive rate but decreases the called variants that arise due to altered pass/fail ratios. Also, it is not advised to use fast models for InDel calling while both the number of InDels and true positive rates are significantly lower in fast models.&#x0D; This study, to the best of our knowledge, is the first study that evaluates the effect of different base calling models of Guppy, one of the most common and ONT-supported base callers, on variant calling.

2476. Universal detection of healthcare-related bacterial transmissions using de novo assembly with short-read whole genome sequencing

Abstract Background Whole genome sequencing (WGS) is the gold standard for molecular evidence of pathogen transmission. To date, most WGS investigations within healthcare settings have used low cost short-read technologies (e.g., Illumina), aligning reads to a high quality reference genome. However, this relies on either public repositories having closely-related high quality references, which is not guaranteed for arbitrary clinical isolates, or additional long-read sequencing. De novo assembly avoids reliance on references, but the utility of fragmented assemblies of short reads is not well-established in hospital outbreak investigations. Methods 24 clusters of clinical isolates were identified by automated and routine methods at 17 U.S. hospitals and underwent paired-end WGS on Illumina platforms, followed by two parallel analyses. For a reference-free analysis, de novo assembly was performed with Shovill, assemblies were clustered with Mash, core-genome alignments were created with Harvest, and finally single nucleotide polymorphism (SNP) distances were visualized using the PathoSPOT phylogenomics toolkit to highlight likely transmission events. For a reference-guided analysis, references were selected for each isolate using StrainGST, and SNPs called by read alignment were used to define phylogenomic distances. Finally, conclusions from both analyses were compared. Results 92 bacterial isolates underwent WGS, of which 86 (93%) completed de novo assembly and passed quality control, comprising 10 isolates of Acinetobacter baumanii, 4 of Klebsiella oxytoca, 46 of Klebsiella pneumoniae, and 26 of Staphylococcus aureus. Reference-free analysis with PathoSPOT identified close relatedness consistent with transmission in 13 of 24 clusters (54%), while the reference-guided analysis identified the same in 12 clusters (50%). Overall, 21 clusters (88%) showed concordance between reference-free and reference-guided methods. Cohen’s kappa indicated substantial agreement (0.75; 95% CI, 0.49–1.0). Conclusion De novo assembly of short reads is tenable for WGS investigation of hospital outbreaks, elides the need for reference genomes or long-read sequencing, and compares favorably with SNP calling via read alignment for detecting likely healthcare-related transmissions. Disclosures Laura E. McLean, M.Ed., HCA Healthcare: Stocks/Bonds Susan S. Huang, MD MPH, Medline Industries, Inc: Conducted studies whereby participating nursing homes and hospital patients received cleaning &amp; antiseptic products|Xttrium Laboratories: Conducted studies where participating nursing homes and hospital patients received antiseptic products Yonatan H. Grad, MD, PhD, Day Zero Diagnostics: Board Member|GSK: Advisor/Consultant

An Autochthonous Susceptible Candida auris Clade I Otomycosis Case in Iran.

Candida auris is a newly emerging multidrug-resistant fungal pathogen considered to be a serious global health threat. Due to diagnostic challenges, there is no precise estimate for the prevalence rate of this pathogen in Iran. Since 2019, only six culture-proven C. auris cases have been reported from Iran, of which, five belonged to clade V and one to clade I. Herein, we report a case of otomycosis due to C. auris from 2017 in a 78-year-old man with diabetes mellitus type II without an epidemiological link to other cases or travel history. Short tandem repeat genotyping and whole genome sequencing (WGS) analysis revealed that this isolate belonged to clade I of C. auris (South Asian Clade). The WGS single nucleotide polymorphism calling demonstrated that the C. auris isolate from 2017 is not related to a previously reported clade I isolate from Iran. The presence of this retrospectively recognized clade I isolate also suggests an early introduction from other regions or an autochthonous presence. Although the majority of reported C. auris isolates worldwide are resistant to fluconazole and, to a lesser extent, to echinocandins and amphotericin B, the reported clade I isolate from Iran was susceptible to all antifungal drugs.

Diversity analysis of southern African Artemisia afra using a single nucleotide polymorphism derived from diversity arrays

Artemisia afra is an aromatic shrub used as a herbal remedy in southern Africa for various disorders, including coughs, colds, influenza, and, most notably, for the prophylaxis and treatment of Plasmodium falciparum infections. Modern high-throughput genotyping by sequencing, which combines next generation sequencing and diversity array technology (DArTseq) complexity reduction methods, allows for the generation of high-quality whole-genome profiles without any previous organismal genetic information that may hamper the diversity analyses. This study investigated the feasibility of incorporating DArTseq-derived single-nucleotide polymorphisms (SNPs) and bioactive compounds into a geographic information system to predict the spatial distribution of A. afra gene diversity in selected southern African environs. DNA extraction, sequencing, and SNP calling mineral analyses (using R Studio) were performed on a total of 80 genotypes collected around Roma and Mohale’s Hoek, Lesotho, and Wepener and Hobhouse, South Africa. The unweighted pair group method with arithmetic mean (UPGMA) and neighbour-joining dendrograms revealed three clusters of variation among genotypes; however, geographic distribution did not influence A. afra genetic diversity. The mean heterozygosity among genotypes was 7.7%. Genotypes collected in Roma and Mohale’s Hoek exhibited high levels of genetic diversity. Local A. afra genetic diversity was relatively low, indicating uniformity of subspecies per locality. The diversity among genotypes indicated that A. afra SNPs may occur despite the location. Given that genetic diversity enhances crop performance, our findings can be useful in germplasm management, industries producing by-products of A. afra, and plant breeding programs. For the long-term conservation of medicinal plants in South Africa, significant sampling and regional data are required. In addition to evaluating qualitative and quantitative assessments of phytochemicals, it is necessary to evaluate foliar mineral composition, as well as the agronomic and morphological characteristics of collected specimens from studied locations.

Accurate prediction of quantitative traits with failed SNP calls in canola and maize.

In modern plant breeding, genomic selection is becoming the gold standard to select superior genotypes in large breeding populations that are only partially phenotyped. Many breeding programs commonly rely on single-nucleotide polymorphism (SNP) markers to capture genome-wide data for selection candidates. For this purpose, SNP arrays with moderate to high marker density represent a robust and cost-effective tool to generate reproducible, easy-to-handle, high-throughput genotype data from large-scale breeding populations. However, SNP arrays are prone to technical errors that lead to failed allele calls. To overcome this problem, failed calls are often imputed, based on the assumption that failed SNP calls are purely technical. However, this ignores the biological causes for failed calls-for example: deletions-and there is increasing evidence that gene presence-absence and other kinds of genome structural variants can play a role in phenotypic expression. Because deletions are frequently not in linkage disequilibrium with their flanking SNPs, permutation of missing SNP calls can potentially obscure valuable marker-trait associations. In this study, we analyze published datasets for canola and maize using four parametric and two machine learning models and demonstrate that failed allele calls in genomic prediction are highly predictive for important agronomic traits. We present two statistical pipelines, based on population structure and linkage disequilibrium, that enable the filtering of failed SNP calls that are likely caused by biological reasons. For the population and trait examined, prediction accuracy based on these filtered failed allele calls was competitive to standard SNP-based prediction, underlying the potential value of missing data in genomic prediction approaches. The combination of SNPs with all failed allele calls or the filtered allele calls did not outperform predictions with only SNP-based prediction due to redundancy in genomic relationship estimates.

Identification of sex-linked SNP markers in wild populations of monomorphic birds.

Single-nucleotide polymorphism (SNP) analysis is a powerful tool for population genetics, pedigree reconstruction and phenotypic trait mapping. However, the untapped potential of SNP markers to discriminate the sex of individuals in species with reduced sexual dimorphism or of individuals during immature stages remains a largely unexplored avenue. Here, we developed a novel protocol for molecular sexing of birds based on the detection of unique Z- and W-linked SNP markers. Our method is based on the identification of two unique loci, one in each sexual chromosome. Individuals are considered males when they show no calls for the W-linked SNP and are heterozygous or homozygous for the Z-linked SNP, while females exhibit both Z- and W-linked SNP calls. We validated the method in the Jackdaw (Corvus monedula). The reduced sexual dimorphism in this species makes it difficult to identify the sex of individuals in the wild. We assessed the reliability of the method using 36 individuals of known sex and found that their sex was correctly assigned in 100% of cases. The sex-linked markers also proved to be widely applicable for discriminating males and females from a sample of 927 genotyped individuals at different maturity stages, with an accuracy of 99.5%. Since SNP markers are increasingly used in quantitative genetic analyses of wild populations, the approach we propose has great potential to be integrated into broader genetic research programmes without the need for additional sexing techniques.

Joint analysis of phenotype-effect-generation identifies loci associated with grain quality traits in rice hybrids

Genetic improvement of grain quality is more challenging in hybrid rice than in inbred rice due to additional nonadditive effects such as dominance. Here, we describe a pipeline developed for joint analysis of phenotypes, effects, and generations (JPEG). As a demonstration, we analyze 12 grain quality traits of 113 inbred lines (male parents), five tester lines (female parents), and 565 (113×5) of their hybrids. We sequence the parents for single nucleotide polymorphisms calling and infer the genotypes of the hybrids. Genome-wide association studies with JPEG identify 128 loci associated with at least one of the 12 traits, including 44, 97, and 13 loci with additive effects, dominant effects, and both additive and dominant effects, respectively. These loci together explain more than 30% of the genetic variation in hybrid performance for each of the traits. The JEPG statistical pipeline can help to identify superior crosses for breeding rice hybrids with improved grain quality.

On the usefulness of mock genomes to define heterotic pools, testers, and hybrid predictions in orphan crops.

The advances in genomics in recent years have increased the accuracy and efficiency of breeding programs for many crops. Nevertheless, the adoption of genomic enhancement for several other crops essential in developing countries is still limited, especially for those that do not have a reference genome. These crops are more often called orphans. This is the first report to show how the results provided by different platforms, including the use of a simulated genome, called the mock genome, can generate in population structure and genetic diversity studies, especially when the intention is to use this information to support the formation of heterotic groups, choice of testers, and genomic prediction of single crosses. For that, we used a method to assemble a reference genome to perform the single-nucleotide polymorphism (SNP) calling without needing an external genome. Thus, we compared the analysis results using the mock genome with the standard approaches (array and genotyping-by-sequencing (GBS)). The results showed that the GBS-Mock presented similar results to the standard methods of genetic diversity studies, division of heterotic groups, the definition of testers, and genomic prediction. These results showed that a mock genome constructed from the population's intrinsic polymorphisms to perform the SNP calling is an effective alternative for conducting genomic studies of this nature in orphan crops, especially those that do not have a reference genome.

High‐throughput genotyping in estimating genetic resources and detecting pathogens in aquaculture

High‐throughput genotyping in estimating genetic resources and detecting pathogens in aquaculture

Transmission Dynamics of a Mycobacterium tuberculosis Complex Outbreak in an Indigenous Population in the Colombian Amazon Region.

Whole genome sequencing (WGS) has become the main tool for studying the transmission of Mycobacterium tuberculosis complex (MTBC) strains; however, the clonal expansion of one strain often limits its application in local MTBC outbreaks. The use of an alternative reference genome and the inclusion of repetitive regions in the analysis could potentially increase the resolution, but the added value has not yet been defined. Here, we leveraged short and long WGS read data of a previously reported MTBC outbreak in the Colombian Amazon Region to analyze possible transmission chains among 74 patients in the indigenous setting of Puerto Nariño (March to October 2016). In total, 90.5% (67/74) of the patients were infected with one distinct MTBC strain belonging to lineage 4.3.3. Employing a reference genome from an outbreak strain and highly confident single nucleotide polymorphisms (SNPs) in repetitive genomic regions, e.g., the proline-glutamic acid/proline-proline-glutamic-acid (PE/PPE) gene family, increased the phylogenetic resolution compared to a classical H37Rv reference mapping approach. Specifically, the number of differentiating SNPs increased from 890 to 1,094, which resulted in a more granular transmission network as judged by an increasing number of individual nodes in a maximum parsimony tree, i.e., 5 versus 9 nodes. We also found in 29.9% (20/67) of the outbreak isolates, heterogenous alleles at phylogenetically informative sites, suggesting that these patients are infected with more than one clone. In conclusion, customized SNP calling thresholds and employment of a local reference genome for a mapping approach can improve the phylogenetic resolution in highly clonal MTBC populations and help elucidate within-host MTBC diversity. IMPORTANCE The Colombian Amazon around Puerto Nariño has a high tuberculosis burden with a prevalence of 1,267/100,000 people in 2016. Recently, an outbreak of Mycobacterium tuberculosis complex (MTBC) bacteria among the indigenous populations was identified with classical MTBC genotyping methods. Here, we employed a whole-genome sequencing-based outbreak investigation in order to improve the phylogenetic resolution and gain new insights into the transmission dynamics in this remote Colombian Amazon Region. The inclusion of well-supported single nucleotide polymorphisms in repetitive regions and a de novo-assembled local reference genome provided a more granular picture of the circulating outbreak strain and revealed new transmission chains. Multiple patients from different settlements were possibly infected with at least two different clones in this high-incidence setting. Thus, our results have the potential to improve molecular surveillance studies in other high-burden settings, especially regions with few clonal multidrug-resistant (MDR) MTBC lineages/clades.

Evaluation of Different SNP Analysis Software and Optimal Mining Process in Tree Species.

Single nucleotide polymorphism (SNP) is one of the most widely used molecular markers to help researchers understand the relationship between phenotypes and genotypes. SNP calling mainly consists of two steps, including read alignment and locus identification based on statistical models, and various software have been developed and applied in this issue. Meanwhile, in our study, very low agreement (<25%) was found among the prediction results generated by different software, which was much less consistent than expected. In order to obtain the optimal protocol of SNP mining in tree species, the algorithm principles of different alignment and SNP mining software were discussed in detail. And the prediction results were further validated based on in silico and experimental methods. In addition, hundreds of validated SNPs were provided along with some practical suggestions on program selection and accuracy improvement were provided, and we wish that these results could lay the foundation for the subsequent analysis of SNP mining.