STRategy: A support system for collecting and analyzing next-generation sequencing data of short tandem repeats for forensic science.

Short tandem repeats (STRs) are short repeated sequences commonly found in the human genome and valuable in forensic science, used for human identity and relatedness markers. Next-generation sequencing (NGS) technologies, e.g., ForenSeq Signature Prep, can sequence STRs, inferring length-based alleles and single nucleotide polymorphisms (SNPs) and providing valuable insights into population and sub-population structures. Despite the potential benefits of NGS for STRs, no open-source software platform integrates the collection, management, and analysis of STR data from NGS into one place. Users must use multiple programs to process their STR data and then collect the results into a separate database or a file system folder. Moreover, analyzing repeat structures (STR repeat motifs) may require learning multiple software tools, making the process inefficient and cumbersome. To address this gap, we introduce the STRategy, a standalone web-based application supporting essential STR data management and analysis capabilities. The STRategy allows users to collect their data into its database, automatically calculates forensic parameters, and visualizes the analyzed data in various forms. Users can search the database using different options, such as by profile, loci, and genotypes, with and without a specific test kit. Moreover, users can also find the nucleotide variants of a locus among the samples. We designed the STRategy for internal use in a laboratory or an organization. Hence, our system includes role-based access control that allows users to search for or access specific data based on their responsibilities. The administrator role can customize the system, for example, configure maps according to the samples' geographic data, and manage reference STR repeat motifs. A laboratory or an organization can download and install a copy of STRategy on their local system using Docker, as described in https://github.com/cucpbioinfo/STRategy. In summary, the STRategy is an end-to-end system that provides users with a database to collect the analyzed STR data from NGS, the dynamic analyses of forensic parameters, and the variants of STR patterns according to the newly added samples, which are then explorable via various search options and visualizations. The system is helpful for both forensic investigations and forensic genetics.

The concordance of length- and sequence-based STRs used in forensic markers with guidance for practice.

Next-generation sequencing (NGS) technology has shed light on every aspect of genetic discoveries, including forensic genetics. The Miseq® FGx Forensic Genetic System (Verogen) is one of the pioneering forensic NGS that provided a complete system from library preparation to data analysis. The system has been validated by several studies and led to a more practical aspect. Short tandem repeat (STR) is a well-established marker that was designed specifically for human individualization. Since NGS provides different data from fragment analysis, a new STR nomenclature is established to make NGS backward compatible with the previous data. In this study, Thai population were used to evaluate the Miseq® FGx Forensic genetic system (Verogen) in practical aspect, including concordance study and forensic population parameters. In summary, we purposed a practical guideline for sequence-based STRs.

Unraveling the mitochondrial phylogenetic landscape of Thailand reveals complex admixture and demographic dynamics.

The evolutionary dynamics of mitochondrial DNA within the Thai population were comprehensively explored with a specific focus on the influence of South Asian admixture. A total of 166 samples were collected through randomized sampling, ensuring a diverse representation. Our findings unveil substantial genetic and haplogroup diversity within the Thai population. We have identified 164 haplotypes categorized into 97 haplogroups, with a notable inclusion of 20 novel haplogroups. The distribution of haplogroups exhibited variations across different populations and countries. The central Thai population displayed a high diversity of haplogroups from both the M and N clades. Maternal lineage affinities were discerned between several Mainland Southeast Asia (MSEA) and South Asian populations, implying ancestral genetic connections and a substantial influence of South Asian women in establishing these relationships. f4-statistics indicates the presence of a Tibeto-Burman genetic component within the Mon population from Thailand. New findings demonstrate two phases of population expansion occurring 22,000-26,000 and 2500-3800 years ago, coinciding with the Last Glacial Maximum, and Neolithic demographic transition, respectively. This research significantly enhances our understanding of the maternal genetic history of Thailand and MSEA, emphasizing the influence of South Asian admixture. Moreover, it underscores the critical role of prior information, such as mutation rates, within the Bayesian framework for accurate estimation of coalescence times and inferring demographic history.

SNPer: an R library for quantitative variant analysis on single nucleotide polymorphisms among influenza virus populations.

Influenza virus (IFV) can evolve rapidly leading to genetic drifts and shifts resulting in human and animal influenza epidemics and pandemics. The genetic shift that gave rise to the 2009 influenza A/H1N1 pandemic originated from a triple gene reassortment of avian, swine and human IFVs. More minor genetic alterations in genetic drift can lead to influenza drug resistance such as the H274Y mutation associated with oseltamivir resistance. Hence, a rapid tool to detect IFV mutations and the potential emergence of new virulent strains can better prepare us for seasonal influenza outbreaks as well as potential pandemics. Furthermore, identification of specific mutations by closely examining single nucleotide polymorphisms (SNPs) in IFV sequences is essential to classify potential genetic markers associated with potentially dangerous IFV phenotypes. In this study, we developed a novel R library called "SNPer" to analyze quantitative variants in SNPs among IFV subpopulations. The computational SNPer program was applied to three different subpopulations of published IFV genomic information. SNPer queried SNPs data and grouped the SNPs into (1) universal SNPs, (2) likely common SNPs, and (3) unique SNPs. SNPer outperformed manual visualization in terms of time and labor. SNPer took only three seconds with no errors in SNP comparison events compared with 40 hours with errors using manual visualization. The SNPer tool can accelerate the capacity to capture new and potentially dangerous IFV strains to mitigate future influenza outbreaks.