Single Nucleotide Polymorphism Profiles Research Articles

It’s all relative: A multi-generational study using ForenSeq™ Kintelligence

The successful application of Forensic Investigative Genetic Genealogy (FIGG) to the identification of unidentified human remains and perpetrators of serious crime has led to a growing interest in its use internationally, including Australia. Routinely, FIGG has relied on the generation of high-density single nucleotide polymorphism (SNP) profiles from forensic samples using whole genome array (WGA) (∼650,000 or more SNPs) or whole genome sequencing (WGS) (millions of SNPs) for DNA segment-based comparisons in commercially available genealogy databases. To date, this approach has required DNA of a quality and quantity that is often not compatible with forensic samples. Furthermore, it requires the management of large data sets that include SNPs of medical relevance. The ForenSeq™ Kintelligence kit, comprising of 10,230 SNPs including 9867 for kinship association, was designed to overcome these challenges using a targeted amplicon sequencing-based method developed for low DNA inputs, inhibited and/or degraded forensic samples. To assess the ability of the ForenSeq™ Kintelligence workflow to correctly predict biological relationships, a comparative study comprising of 12 individuals from a family (with varying degrees of relatedness from 1st to 6th degree relatives) was undertaken using ForenSeq™ Kintelligence and a WGA approach using the Illumina Global Screening Array-24 version 3.0 Beadchip. All expected 1st, 2nd, 3rd, 4th and 5th degree relationships were correctly predicted using ForenSeq™ Kintelligence, while the expected 6th degree relationships were not detected. Given the (often) limited availability of forensic samples, findings from this study will assist Australian Law enforcement and other agencies considering the use of FIGG, to determine if the ForenSeq™ Kintelligence is suitable for existing workflows and casework sample types considered for FIGG.

Nosocomial transmission of fluconazole-resistant Candida glabrata bloodstream isolates revealed by whole-genome sequencing.

The prevalence of fluconazole-resistant bloodstream infections caused by Candida glabrata is increasing globally, but the transmission of these resistant strains within hospitals has rarely been documented. Through whole-genome sequencing and epidemiological analyses, this study identified two potential clusters of C. glabrata bloodstream infections within the same hospital, revealing the transmission of clonal C. glabrata strains with different levels of fluconazole susceptibility or distinct transcription factor pleiotropic drug resistance protein 1 (Pdr1p) single-nucleotide polymorphism profiles among patients receiving antifungal therapy.

Single Nucleotide Polymorphism-based Identification of Bacterial Artificial Chromosome-mediated Homologous Recombination.

Bacterial Artificial chromosome (BAC) recombineering is a powerful genetic manipulation tool for the efficient development of recombinant genetic resources. Long homology arms of more than 150 kb composed of BAC constructs not only substantially enhance genetic recombination events, but also provide a variety of single nucleotide polymorphisms (SNPs) that are useful markers for accurately docking BAC constructs at target sites. Even if the BAC construct is homologous to the sequences of the target region, different variations may be distributed between various SNPs within the region and those within the BAC construct. Once the BAC construct carrying these variations was precisely replaced in the target region, the SNP profiles within the target genomic locus were directly replaced with those in the BAC. This alteration in SNP profiles ensured that the BAC construct accurately targeted the designated site. In this study, we introduced restriction fragment length polymorphism or single-strand conformation polymorphism analyses to validate and evaluate BAC recombination based on changes in SNP patterns. These methods provide a simple and economical solution to validation steps that can be cumbersome with large homologous sequences, facilitating access to the production of therapeutic resources or disease models based on BAC-mediated homologous recombination.

A study on factors influencing delayed sputum conversion in newly diagnosed pulmonary tuberculosis based on bacteriology and genomics

Conversion of sputum from positive to negative is one of the indicators to evaluate the efficacy of anti-tuberculosis treatment (ATT). We investigate the factors associated with delayed sputum conversion after 2 or 5 months of ATT from the perspectives of bacteriology and genomics. A retrospective study of sputum conversion in sputum positive 1782 pulmonary tuberculosis (PTB) was conducted from 2021 to 2022 in Beijing, China. We also designed a case-matched study including 24 pairs of delayed-sputum-conversion patients (DSCPs) and timely-sputum-conversion patients (TSCPs), and collect clinical isolates from DSCPs before and after ATT and initial isolates of TSCPs who successfully achieved sputum conversion to negative after 2 months of ATT. A total of 75 strains were conducted drug sensitivity testing (DST) of 13 anti-TB drugs and whole-genome sequencing (WGS) to analyze the risk factors of delayed conversion and the dynamics changes of drug resistance and genomics of Mycobacterium tuberculosis (MTB) during ATT. We found TSCPs have better treatment outcomes and whose initial isolates show lower levels of drug resistance. Clinical isolates of DSCPs showed dynamically changing of resistance phenotypes and intra-host heterogeneity. Single nucleotide polymorphism (SNP) profiles showed large differences between groups. The study provided insight into the bacteriological and genomic variation of delayed sputum conversion. It would be helpful for early indication of sputum conversion and guidance on ATT.

Single nucleotide polymorphism profiles of canine T-cell and null-cell lymphomas.

The histopathological classification of T-cell lymphoma (TCL) in humans has distinctive mutational genotyping that suggests different lymphomagenesis. A similar concept is assumed to be observed in dogs with different TCL phenotypes. This study aimed to identify the previously reported single-nucleotide polymorphisms (SNPs) in both human beings and dogs in canine TCLs and null-cell lymphomas (NCLs) and to design compatible oligonucleotides from each variant based on the multiplex polymerase chain reaction. Genomic DNA was extracted from 68 tumor specimens (62 TCLs and 6 NCLs) and 5 buffy coat samples from dogs with TCL. Four TCL subtypes and NCL were analyzed in 44 SNPs from 21 genes using the MassARRAY. The greatest incidences of SNPs observed in all TCL subtypes and NCL ware SATB1 c.1259A > C, KIT c.1275A > G, SEL1L c.2040 + 200C > G, and TP53 c.1024C > T, respectively. Some SNP locations were statistically significant associated with NCL, including MYC p.S75F (p = 0.0003), TP53 p.I149N (p = 0.030), PDCD1 p.F37LX (p = 0.012), and POT1 p.R583* (p = 0.012). Each TCL histological subtype and NCL are likely to contain distinctive mutational genetic profiles, which might play a role in lymphoma gene-risk factors and might be useful for selecting therapeutic target drugs for each canine patient.

Characterization of Turner Syndrome-associated diabetes mellitus.

Diabetes mellitus (DM) risk factors in Turner Syndrome (TS) may include autoimmunity, obesity, beta-cell dysfunction, genetic predisposition and insulin resistance (IR). Evaluate glucose tolerance and DM risk factors in adults with TS. A single centre study with two phases. To determine the prevalence of DM and to assess diabetes risk markers comparing women with TS with and without impaired glucose tolerance (IGT). Tertiary referral center, University College Hospitals. 106 Women with TS (age range 18-70 years) undergoing annual health surveillance. Participants underwent oral glucose tolerance tests (OGTT), with additional samples for autoimmunity and genetic analysis. Glucose tolerance, insulin, autoimmune and single nucleotide polymorphism (SNP) profile. OGTT screening showed that those without a previous DM diagnosis, 72.7% had normal glucose tolerance, 19.5% had IGT, and 7.6% were newly diagnosed with DM. OGTT identified more cases of DM than HbAc1 sampling alone. Women with IGT or DM were older, with higher body mass index and IR. No association was found between autoimmune markers GAD, IA-2 and ZnT8, risk karyotypes or selected SNPs and DM. In DM cases, GAD positivity was associated with requirement for insulin therapy. The median age of onset of the diagnosis of DM was 36 years (range 11-56). In the spectrum of DM subtypes, TS-associated DM lies between type 1 and type 2 DM with features of both. Key factors include weight and IR. Assessing C-peptide or GAD antibodies may aid future insulin requirement.

Single nucleotide polymorphism profile for quantitative trait nucleotide in populations with small effective size and its impact on mapping and genomic predictions.

Increasing SNP density by incorporating sequence information only marginally increases prediction accuracies of breeding values in livestock. To find out why, we used statistical models and simulations to investigate the shape of distribution of estimated SNP effects (a profile) around quantitative trait nucleotides (QTNs) in populations with a small effective population size (Ne). A QTN profile created by averaging SNP effects around each QTN was similar to the shape of expected pairwise linkage disequilibrium (PLD) based on Ne and genetic distance between SNP, with a distinct peak for the QTN. Populations with smaller Ne showed lower but wider QTN profiles. However, adding more genotyped individuals with phenotypes dragged the profile closer to the QTN. The QTN profile was higher and narrower for populations with larger compared to smaller Ne. Assuming the PLD curve for the QTN profile, 80% of the additive genetic variance explained by each QTN was contained in ± 1/Ne Morgan interval around the QTN, corresponding to 2 Mb in cattle and 5 Mb in pigs and chickens. With such large intervals, identifying QTN is difficult even if all of them are in the data and the assumed genetic architecture is simplistic. Additional complexity in QTN detection arises from confounding of QTN profiles with signals due to relationships, overlapping profiles with closely spaced QTN, and spurious signals. However, small Ne allows for accurate predictions with large data even without QTN identification because QTNs are accounted for by QTN profiles if SNP density is sufficient to saturate the segments.

Integrated sequence-based genomic, transcriptomic, and methylation characterization of the susceptibility to tuberculosis in monozygous twins

BackgroundTuberculosis (TB) is a complex disease with a spectrum of outcomes for more than six decades; however, the genomic and epigenetic mechanisms underlying the highly heritable susceptibility to TB remain unclear. MethodsIntegrated sequence-based genomic, transcriptomic, and methylation analyses were conducted to identity the genetic factors associated with susceptibility to TB in two pairs of Mongolian monozygous twins. In this study, whole-genome sequencing was employed to analyze single nucleotide polymorphisms (SNPs), insertions and deletions (InDels), and copy number variations (CNVs). Gene expression was assessed through RNA sequencing, and methylation patterns were examined using the Illumina Infinium Methylation EPIC BeadChip. The gene–gene interaction network was analyzed using differentially expressed genes. ResultsOur study revealed no significant difference in SNP and InDel profiles between participants with and without TB. Genes with CNVs were involved in human immunity (human leukocyte antigen [HLA] family and interferon [IFN] pathway) and the inflammatory response. Different DNA methylation patterns and mRNA expression profiles were observed in genes participating in immunity (HLA family) and inflammatory responses (IFNA, interleukin 10 receptor [IL-10R], IL-12B, Toll-like receptor, and IL-1B). ConclusionsThe results of this study suggested that susceptibility to TB is associated with transcriptional and epigenetic alternations of genes involved in immune and inflammatory responses. The genes in the HLA family (HLA-A, HLA-B, and HLA-DRB1) and IFN pathway (IFN-α and IFN-γ) may play major roles in susceptibility to TB.

A comparative genomics approach reveals a local genetic signature of Leishmania tropica in Morocco.

In Morocco, cutaneous leishmaniasis (CL) caused by Leishmania (L.) tropica is an important health problem. Despite the high incidence of CL in the country, the genomic heterogeneity of these parasites is still incompletely understood. In this study, we sequenced the genomes of 14 Moroccan isolates of L. tropica collected from confirmed cases of CL to investigate their genomic heterogeneity. Comparative genomics analyses were conducted by applying the recently established Genome Instability Pipeline (GIP), which allowed us to conduct phylogenomic and principal components analyses (PCA), and to assess genomic variations at the levels of the karyotype, gene copy number, single nucleotide polymorphisms (SNPs) and small insertions/deletions (INDELs) variants. Read-depth analyses revealed a mostly disomic karyotype, with the exception of the stable tetrasomy of chromosome 31. In contrast, we identified important gene copy number variations across all isolates, which affect known virulence genes and thus were probably selected in the field. SNP-based cluster analysis of the 14 isolates revealed a core group of 12 strains that formed a tight cluster and shared 45.1 % (87 751) of SNPs, as well as two strains (M3015, Ltr_16) that clustered separately from each other and the core group, suggesting the circulation of genetically highly diverse strains in Morocco. Phylogenetic analysis, which compared our 14 L. tropica isolates against 40 published genomes of L. tropica from a diverse array of locations, confirmed the genetic difference of our Moroccan isolates from all other isolates examined. In conclusion, our results indicate potential regional variations in SNP profiles that may differentiate Moroccan L. tropica from other L. tropica strains circulating in endemic countries in the Middle East. Our report paves the way for future research with a larger number of strains that will allow correlation of diverse phenotypes (resistance to treatments, virulence) and origins (geography, host species, year of isolation) to defined genomic signals such as gene copy number variations or SNP profiles that may represent interesting biomarker candidates.

Abstract LB234: Identifying cancer vulnerabilities associated with changes in chromatin accessibility by simultaneously profiling hundreds of cancer cell lines with ATAC-seq

Abstract The goal of the Cancer Dependency Map project (DepMap) is to identify the landscape of cancer vulnerabilities by systematically profiling hundreds of cell lines representing the heterogeneity of human cancer. Cancer cells are known to undergo significant alterations in the cancer genome including changes in the accessible chromatin regions (ACRs). These alterations could lead to novel cancer vulnerabilities but chromatin accessibility has not been systematically profiled in DepMap. Profiling hundreds of cell lines individually for ACRs would require large resources. Here we show that we can efficiently profile hundreds of cell lines using two single-cell approaches developed by our labs. SHARE-seq is a single-cell high-throughput combinatorial indexing method to measure both chromatin accessibility (scATAC-seq), and gene expression (scRNA-seq) in the same single cell. MIX-Seq is an approach that leverages the ability to pool hundreds of unique cancer cell lines and then apply single-cell genomics across cell populations from each cell line, resolving its identity using single nucleotide polymorphism (SNP) profiles. Here, we used a combination of MIX-seq (pooling cell lines) and SHARE-seq (scATAC-seq and RNA-seq) to simultaneously profile 500 unique cell lines covering 110 lineages within 22 cancer types at the single-cell level. Encouragingly, in a UMAP representation of the data, cancer cell lines cluster by lineage. Interestingly, we identified hundreds of thousands of peaks within cis-regulatory elements (CREs), 1/3 of which are unique to cancer cell lines and not present in normal cell types. Using published tools, we calculated an ATAC-seq gene activity prediction score per cell line. To identify cancer vulnerabilities associated with ACRs changes, we combined the ATAC-seq gene-activity predictions with RNAseq-based features to construct machine-learning models of cancer dependency scores. We found that the prediction accuracy for multiple dependencies improved with the addition of the ATAC-seq-based scores, indicating that chromatin accessibility provides information beyond gene expression. Additional analyses are underway to create other features. Overall, we have generated a large high-quality dataset to simultaneously map the chromatin accessibility in hundreds of cancer cell lines. Importantly, the chromatin accessibility adds to other omics profiling to identify biomarkers of response and understand how changes in chromatin can lead to new vulnerabilities. Citation Format: Patricia Borck, Kirsty Wienand, Fabiana Duarte, Alvin Qin, Ruochi Zhang, Juliana Babu, Simone Zhang, Samuel Maffa, Max Horlbeck, Rojesh Shrestha, Joshua Dempster, Jennifer Roth, Catarina Campbell, Jason Buenrostro, Francisca Vazquez. Identifying cancer vulnerabilities associated with changes in chromatin accessibility by simultaneously profiling hundreds of cancer cell lines with ATAC-seq [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB234.

Association of pharmacogenomic, clinical and behavioural factors with oral levothyroxine (LT-4) dose of hypothyroid patients in Sri Lanka: a matched case control study

BackgroundHypothyroidism is a common endocrine disorder that exerts a substantial influence on people all over the world. Levothyroxine (LT-4) is the drug of choice for the treatment of hypothyroidism and the starting oral dose is typically ranging from 1.5 to 1.7 µg/kg/day. The target is to achieve an optimum serum TSH level of 0.4-4.0 mIU/L; hence, the dose is titrated accordingly. Once the LT-4 dose is adjusted to obtain the target TSH level, it usually remains stable for a long period of time in most cases. However, some of the patients require frequent dose adjustments and some of them require unusually high doses. Therefore, the aim of this study is to determine the association of pharmacogenomic, clinical and behavioural factors with the oral levothyroxine (LT-4) dose requirement of hypothyroid patients in Sri Lanka.MethodThis study will be conducted as a matched case-control study and will involve primary hypothyroid patients who visit the diabetes and endocrinology clinic at the National Hospital, Kandy, Sri Lanka. We will recruit a total of 292 cases and select 292 controls from the clinic who are matched in terms of age, sex and Body Mass Index (BMI). An interviewer-administered questionnaire will be used to collect data from the participants (n = 584). Of the 584 patients, blood samples will be collected from a sub-sample (n = 150) for DNA extraction. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) will be performed for single nucleotide polymorphisms (SNP) analysis.DiscussionFrequent dose adjustments of levothyroxine cause a serious economic burden to the healthcare system. By identifying the root causes of the variations in LT-4 dosage, a more comprehensive comprehension of hypothyroidism and its management can be attained in Sri Lanka. Furthermore, upon identification of a positive association/correlation between genetic polymorphisms and the LT-4 dose, SNP profiles can be used as a possible genetic marker for dose adjustment determination in future patients.

Novel loci associated with resistance to downy and powdery mildew in grapevine.

Among the main challenges in current viticulture, there is the increasing demand for sustainability in the protection from fungal diseases, such as downy mildew (DM) and powdery mildew (PM). Breeding disease-resistant grapevine varieties is a key strategy for better managing fungicide inputs. This study explores the diversity of grapevine germplasm (cultivated and wild) from Caucasus and neighboring areas to identify genotypes resistant to DM and PM, based on 13 Simple Sequence Repeat (SSR) loci and phenotypical (artificial pathogen inoculation) analysis, and to identify loci associated with DM and PM resistance, via Genome-Wide Association Analysis (GWAS) on Single Nucleotide Polymorphism (SNP) profiles. SSR analysis revealed resistant alleles for 16 out of 88 genotypes. Phenotypic data identified seven DM and 31 PM resistant genotypes. GWAS identified two new loci associated with DM resistance, located on chromosome 15 and 16 (designated as Rpv36 and Rpv37), and two with PM resistance, located on chromosome 6 and 17 (designated as Ren14 and Ren15). The four novel loci identified genomic regions rich in genes related to biotic stress response, such as genes involved in pathogen recognition, signal transduction and resistance response. This study highlights potential candidate genes associated with resistance to DM and PM, providing valuable insights for breeding programs for resistant varieties. To optimize their utilization, further functional characterization studies are recommended.

Genetic Diversity and Population Structure of Jujube Cultivars in the United States Revealed by Single Nucleotide Polymorphism Markers

The nutritional and medicinal significance of jujube (Ziziphus jujuba) has led to persistent efforts in genomics to accelerate the utilization of its germplasm resources. However, the absence of accurate genetic identity of existing germplasm limits these studies. In the United States, different names were frequently given to the same jujube cultivars because the pedigrees of the imported germplasm are unclear. The present study selected a panel of 147 single nucleotide polymorphism (SNP) markers distributed across the jujube genome to examine genetic identity, genetic diversity, and population structure in 177 jujube cultivars sampled from different locations in the United States. SNP profile multilocus matching reported a total of 23 synonymous groups including 116 samples that were identical to at least one other sample. This led to the detection of 74 unique genotypes for subsequent diversity analysis. Model-based genetic structure analysis divided the distinctive genotypes into three major groups, with some admixtures among the groups. The genetic differentiation among these groups was further validated by analysis of molecular variance (Fst = 0.199, P value < 0.001), principal coordinate analysis, and clustering analysis. Morphological traits were studied in some of the genetically identical commercial cultivar groups, (i.e., Li, Lang, and Jinsi). Results demonstrated significant morphological differences within genetically identical cultivars in the Jinsi group, indicating phenotypic variation resulting from mutations in these clones.

Polyketide synthases mutation in tuberculosis transmission revealed by whole genomic sequence, China, 2011-2019.

Introduction: Tuberculosis (TB) is an infectious disease caused by a bacterium called Mycobacterium tuberculosis (Mtb). Previous studies have primarily focused on the transmissibility of multidrug-resistant (MDR) or extensively drug-resistant (XDR) Mtb. However, variations in virulence across Mtb lineages may also account for differences in transmissibility. In Mtb, polyketide synthase (PKS) genes encode large multifunctional proteins which have been shown to be major mycobacterial virulence factors. Therefore, this study aimed to identify the role of PKS mutations in TB transmission and assess its risk and characteristics. Methods: Whole genome sequences (WGSs) data from 3,204 Mtb isolates was collected from 2011 to 2019 in China. Whole genome single nucleotide polymorphism (SNP) profiles were used for phylogenetic tree analysis. Putative transmission clusters (≤10 SNPs) were identified. To identify the role of PKS mutations in TB transmission, we compared SNPs in the PKS gene region between "clustered isolates" and "non-clustered isolates" in different lineages. Results: Cluster-associated mutations in ppsA, pks12, and pks13 were identified among different lineage isolates. They were statistically significant among clustered strains, indicating that they may enhance the transmissibility of Mtb. Conclusion: Overall, this study provides new insights into the function of PKS and its localization in M. tuberculosis. The study found that ppsA, pks12, and pks13 may contribute to disease progression and higher transmission of certain strains. We also discussed the prospective use of mutant ppsA, pks12, and pks13 genes as drug targets.

Cracking the code: Can forensic genetics distinguish identical twins? A technical perspective

DNA fingerprinting has revolutionized the field of forensic investigation in recent times. The utility of DNA fingerprinting technology in differentiating between monozygotic twins has always been an area of academic interest for researchers. While traditional chiral fingerprinting effectively differentiates monozygotic twins, situations may arise where the absence of conventional fingerprints at a crime scene necessitates DNA analysis for conclusive identification. Although Short Tandem Repeats (STR) profiling is of not much help in that case, monozygotic twins can still be differentiated using current advancements in the field of forensic genetics. The methods that can help discriminate between identical twins are mitochondrial genome (mtGenome) analysis, Single Nucleotide Polymorphism (SNP) profiling, Epigenetic profiling (DNA methylation profiling), Copy Number Variants (CNV) profiling, and studying Single Nucleotide Variants (SNV) in the genetic material by traditional sequencing methods like sanger sequencing or advanced methods like Whole Genome Sequencing (WGS). In conclusion, these alternative methods may be able to distinguish between monozygotic twins, but they also have drawbacks that must be considered when using them in real-world crime investigations. To establish their accuracy, dependability, and application in forensic situations, more study, validation, and standardization are required. A combination strategy will strengthen the case and lessen the fallacy of individual profiling methods.

Genomic sequencing revealed recombination event between clade 1 and clade 2 occurs in circulating varicella-zoster virus in China.

Varicella-zoster virus (VZV), a member of the Alphaherpesvirinae subfamily, causes varicella in primary infections and establishing a latent stage in sensory ganglia. Upon reactivation, VZV causes herpes zoster with severe neuralgia, especially in elderly patients. The mutation rate for VZV is comparatively lower than the other members of other alpha herpesviruses. Due to geographic isolation, different genotypes of VZV are circulating on separate continents. Here, we successfully isolated a VZV from the vesicular fluid of a youth zoster patient. Based on the single-nucleotide polymorphism profiles of different open reading frames that define the genotype, this newly isolated VZV primarily represents genotype clade 2 but also has characteristics of genotype clade 1. The next-generation sequencing provided a nearly full-length sequence, and further phylogenetic analysis revealed that this VZV isolate is distinct from clades 1 and 2. The Recombination Detection Program indicates that a possible recombinant event may occur between the VZV isolate and clade 1. In summary, we found that there is a circulating VZV isolate in China that may represent a recombinant between clade 1 and clade 2, providing new concerns that need to be considered in the future VZV vaccination program.

Single-nucleotide polymorphism profiling by multimodal-targeted next-generation sequencing in methotrexate-resistant and -sensitive human osteosarcoma cell lines

Introduction: Methotrexate (MTX) is one of the most important drugs included in the first-line protocols to treat high-grade osteosarcoma (HGOS). Although several polymorphisms have been reported to be associated with drug response or MTX-related toxicity in pharmacogenetic studies, their role in the development of MTX resistance in HGOS is still unclear.Methods: Therefore, in this study, 22 single nucleotide polymorphisms (SNPs) in 4 genes of the folate metabolism, 7 MTX transporter genes, and 2 SNPs of the tumor protein p53 (TP53) gene were investigated using a custom multimodal-targeted next-generation sequencing (mmNGS) approach in 8 MTX-resistant and 12 MTX-sensitive human HGOS cell lines. The panel was validated by TaqMan genotyping assays.Results: High instability of TP53 rs1642785 was observed in all U-2OS/MTX variants. Allele changes of the solute carrier family 19 member 1/replication factor C subunit 1 (SLC19A1, previously known as RFC1) and rs1051266 were identified in all Saos-2/MTX-resistant variants in both DNA- and RNA- derived libraries compared to the parental Saos-2 cell line. Allele changes of methylenetetrahydrofolate reductase (MTHFR) rs1801133 were identified only in the RNA-derived libraries of the two U2OS variants with the highest MTX resistance level. Significantly upregulated gene expression associated with the development of MTX resistance was revealed for dihydrofolate reductase (DHFR) whereas SLC19A1 was downregulated. In addition, a fusion transcript of DHFR (ex4) and MutS Homolog 3 (MSH3) (ex9) was identified in the RNA libraries derived from the two U-2OS variants with the highest MTX resistance level.Conclusion: This innovative mmNGS approach enabled the simultaneous exploration of SNPs at DNA and RNA levels in human HGOS cell lines, providing evidence of the functional involvement of allele changes associated with the development of MTX resistance.

Detection of doping control sample substitutions via single nucleotide polymorphism-based ID typing.

The authenticity of a doping control sample is a key element of sports drug testing programmes. Doping control sample manipulation by providing another individual's urine or blood (instead of the tested athlete's sample) has been observed in the past and is an unequivocal violation of the World Anti-Doping Agency anti-doping rules. To determine attempts of manipulations by sample swapping, the utility of a single nucleotide polymorphism (SNP)-based sample authentication with a multi-target SNP panel was assessed. The panel comprises detection assays for 44 different SNPs, 3 gender markers and 5 quality control markers for DNA-profile determination. Sample analysis is based on a multiplex polymerase chain reaction step followed by a multiplex single base extension (SBE) reaction and subsequent SBE-product detection by MALDI-TOF MS. Panel performance was evaluated for urine and dried blood spot (DBS) samples. Urine (8ml) and DBS (20 μl) test samples were reliably typed and matched to whole blood reference samples, while efficient typing of urine samples correlated with sample quality and input amounts. Robust profiling of urine doping control specimens was confirmed with an assay input of 12 ml. Samples can be processed in a high-throughput format with an overall assay turnaround time of approximately 11 h. SNP-based DNA typing via MALDI-TOF MS thus represents a high throughput-capable possibility for doping control sample authentication. SNP profiling of samples could offer the opportunity to complement existing steroid profile analytics to substantiate sample manipulations and to support quality control processes in high throughput routine settings.

Operationalisation of the ForenSeq® Kintelligence Kit for Australian unidentified and missing persons casework

Single nucleotide polymorphism (SNP) genotyping technologies can generate investigative leads for human remains identification, including estimation of biological sex, biogeographical ancestry (BGA), externally visible characteristics (EVCs), identity, uniparental lineage and extended kinship. The ForenSeq® Kintelligence Kit provides forensic laboratories with the ability to apply this suite of genetic tools to forensic samples using one panel targeting 10,230 SNPs (including 56 ancestry-informative, 24 phenotype-informative, 94 identity-informative, 106 X chromosome, 85 Y chromosome and 9867 kinship-informative SNPs) sequenced on the MiSeq FGx® Sequencing System. The ForenSeq® Kintelligence Kit has been internally validated, optimised and operationalised by the Australian Federal Police National DNA Program for Unidentified and Missing Persons (AFP Program) for coronial casework. The internal validation was conducted according to the Scientific Working Group on DNA Analysis Methods guidelines (excluding mixture analysis), focussing on sample types typically encountered in human remains identification casework, such as bones, teeth, nail, blood and hair. The workflow was optimised for a high throughput library preparation and sequencing workflow, and additional analytical thresholds were developed to improve genotyping accuracy for low DNA input samples. Additionally, the genetic intelligence generated from the kit was compared to the self-declared biological sex, EVCs and BGA of the DNA donors to assess concordance. The kit was able to produce high quality SNP profiles from 1.0 ng down to 0.1 ng of DNA, with high repeatability and reproducibility, and minimal background noise. The prediction accuracy for biological sex (95%), hair colour (58%), eye colour (74%) and BGA inferences (consistent: 74%; partially consistent: 10%; inconclusive: 16%) was determined based on self-declared data. Additionally, SNP profiles from a volunteer family group of ten related individuals were uploaded to GEDmatch PRO™ to assess kinship accuracy. The kit was capable of detecting (97%) and accurately classifying (90%) genetic relationships spanning from first to fifth degree. The Kintelligence Kit provides the AFP Program with a robust and reliable genetic intelligence tool for unidentified and missing persons investigations, which has been designed to sequence multiple challenging samples in a single multiplexed assay using existing laboratory instrumentation.

A Machine Learning Based Computational Method for Prediction of Functional SNPs in Rice Genome

<p>Single nucleotide polymorphisms (SNPs) are the most prevalent and stable class of genetic diversity that exist in most organisms. Functional SNPs are the most commonly used genetic markers for diversity study and molecular breeding in plants, and their quick recognition is in urgent demand. In this work, a computational approach to identify functional SNPs in rice genome based on machine learning is presented. To characterize and prioritize variants, two different categories of features, the nucleotide-sequence based features and the allele-specific based features, are extracted. In particular, the weighted Euclidean distance is employed to measure the changes of the transcription factors (TFs) binding affinities caused by SNPs. To deal with the classification problem on unbalanced data, the support vector machine (SVM) together with an oversampling method is employed. We use mRMR to find the optimal feature set, and the result shows that our method can achieve accuracy with sensitivity of ~74.2% and specificity of ~72.3% after 10-fold cross-validation. Furthermore, the sources of data to build the proposed prediction model are mainly sequence context of SNP and TF profiles in JASPAR database, which are all easy to be acquired. So, the prediction method can be easily applied to other plant species.</p> <p> </p>