Genotyping SNPs and Indels: A method to improve the scope and sensitivity of High-Resolution melt (HRM) analysis based applications.

High-resolution melt (HRM) analysis is a closed-tube technique for detecting single nucleotide polymorphisms (SNPs). However, it has limited use in high-resolution melting devices, even those with high thermal accuracy (HTA). In addition to the cost of switching to these specialized devices, the presence of nearest neighbour neutral changes (class III, IV SNPs and small indels) made HRM-based assays a challenging task due to reduced sensitivity. This study aimed to design a common modified competitive amplification of differently melting amplicons (CADMA)-based assay to address these challenges by generating allele-specific qPCR products that are detectable on most qPCR platforms. For this study, SNPs were selected from all four classes of SNPs (class I: C/T or G/A mutation; class II: C/A or G/T mutation; class III: G/C mutation; class IV: A/T mutation). A single base pair and 19 bp indels were also chosen to simulate how CADMA primers could be designed for indels of varying lengths. The melting temperatures (Tm) were determined using IDT oligoAnalyzer. qPCR and melt data acquisition were performed on the CFX96 qPCR platform, and the melt curve data were analyzed using Precision Melt software (Bio-Rad, USA). The clusters for different genotypes were successfully identified with the aid of the control samples, and Tm predictions were carried out using the uMelt batch and Tm online tools for comparison. Using HRM-qPCR assays based on the modified CADMA method, genotyping of various SNPs was successfully carried out. For some SNPs, similarly shaped melt curves were observed for homozygotes and heterozygotes, making shape-based genotype prediction difficult. The Tm values calculated via the Blake and Delcourts (1998) method were the closest to the experimental Tm values after adjusting for the salt concentration. Since HRM assays usually depend on the ΔTm caused by mutations, they are prone to a high error rate due to nearest neighbour neutral changes. The technique developed in this study significantly reduces the failure rates in HRM-based genotyping and could be applied to any SNP or indel in any platform. It is crucial to have a deep understanding of the melt instrument, its accuracy and the nature of the target (SNP class or indel length and GC content of the flanking region). Furthermore, the availability of controls is essential for a high success rate.

A novel PCR-based genotyping method for Proteus mirabilis - Intergenic region polymorphism analysis.

Proteus mirabilis is a predominant species in cases of food poisoning associated with meat products and is also an opportunistic pathogen causing numerous infections in humans. This study aimed to differentiate P. mirabilis isolates using intergenic region polymorphism analysis (IRPA). The IRPA typing scheme was developed to amplify polymorphic fragments in intergenic regions (IGRs). The presence, absence, or size change of amplified products were identified and utilized as genetic markers for rapid differentiation of strains. A total of 75 P. mirabilis isolates were isolated from 63 fresh poultry and pork samples were subtyped using the IRPA and ERIC-PCR methods, and their antibiotic resistance profiles were tested. The majority of P. mirabilis isolates showed resistance to tetracycline (85.3%), doxycycline (93.3%), chloramphenicol (82.7%), streptomycin (92.0%), spectinomycin (80.0%), trimethoprim (97.3%); trimethoprim-sulfalleth (82.7%), and erythromycin (100.0%). In contrast, resistance rates to ceftriaxon, cefoxitin, cefepime, and cefotaxim were lower at only 17.3%, 5.3%, 6.7%, and 13.3%, respectively, among P. mirabilis isolates. Eleven loci were selected for analysis of the genetic diversity of 75 P. mirabilis isolates. A combination of 4 loci was determined as the optimal combination. The results compared to those obtained using ERIC-PCR for the same isolates. The Simpson's index of diversity was 0.999 for IRPA and 0.923 for ERIC-PCR, indicating that IRPA has a higher discriminatory power than ERIC-PCR. The concordance between IRPA and ERIC-PCR methods was low, primarily because IRPA classified isolates from the same ERIC cluster into separate clusters due to its high resolution. The IRPA method presented in this study offers a rapid, simple, reproducible, and economical approach for genotyping P. mirabilis.

Highly accurate single-color fluorogenic DNA decoding sequencing for mutational genotyping.

We proposed a single-color fluorogenic DNA decoding sequencing method designed to improve sequencing accuracy, increase read length and throughput, as well as decrease scanning time. This method involves the incorporation of a mixture of four types of 3'-O-modified nucleotide reversible terminators into each reaction. Among them, two nucleotides are labeled with the same fluorophore, while the remaining two are unlabeled. Only one nucleotide can be extended in each reaction, and an encoding that partially defines base composition can be obtained. Through cyclic interrogation of a template twice with different nucleotide combinations, two sets of encodings are sequentially obtained, enabling the determination of the sequence. We demonstrate the feasibility of this method using established sequencing chemistry, achieving a cycle efficiency of approximately 99.5 %. Notably, this strategy exhibits remarkable efficacy in the detection and correction of sequencing errors, achieving a theoretical error rate of 0.00016 % at a sequencing depth of ×2, which is lower than Sanger sequencing. This method is theoretically compatible with the existing sequencing-by-synthesis (SBS) platforms, and the instrument is simpler, which may facilitate further reductions in sequencing costs, thereby broadening its applications in biology and medicine. Moreover, we demonstrate the capability to detect known mutation sites using information from only a single sequencing run. We validate this approach by accurately identifying a mutation site in the human mitochondrial DNA.

Optimizing single-tube nested PCR for enhanced genotyping of single cells and in vitro produced bovine embryos.

Single-tube nested PCR (STnPCR) is a technique that improves nested PCR, reducing potential contamination and false-positive results, enhancing the amplification sensitivity. Despite being commonly used for the detection of microorganisms, STnPCR can be a valuable tool for bovine genotyping, encompassing essential targets as ROSA26 and TSPY, pivotal in the fields of animal reproduction, genetic improvement, and transgenic research. The objective of this study was to improve and innovate STnPCR for gene detection in cattle. We aimed to detect the ROSA26 and TSPY genes using low-concentration DNA samples, including single cells, small cell groups (one to five cells), in vitro-produced embryos, and bovine tissue samples. Moreover, we refined STnPCR for gene detection in up to single cells by conducting sensitivity testing with different concentration ratios of internal and external primers. Successful amplification of the ROSA26 and TSPY genes was achieved across all tested primer concentrations, even in single cells, with more consistent results observed at lower primer concentrations. Additionally, simultaneous gene amplification was achieved through STnPCR multiplexing, representing the first study of multiplex STnPCR in cattle. These outcomes not only confirm its effectiveness in detecting genetic markers for animal genetic improvement and transgenic elements but also pave the way for its widespread adoption in reproductive studies in bovines.

Performance evaluation of the Allplex HPV HR Detection assay in comparison with the Cobas HPV test for high-risk HPV genotyping.

Molecular testing for high-risk human papillomavirus (hrHPV) genotypes is important in screening for cervical cancer. In this study, we evaluated the performance of a newly developed Allplex HPV HR Detection assay in comparison with the Cobas HPV Test. A total of 1,275 cervical specimens obtained from a healthcare center between August 2021 and May 2022 were analyzed. The overall agreement for hrHPV detection was 98.4%, with higher agreement observed for HPV-16 (99.7%) and HPV-18 (99.8%) compared to other hrHPV genotypes (97.2%). Sequencing revealed that the majority of discrepancies was genotyped accurately by the Allplex HPV HR Detection assay with the exception of one false positive for HPV-16 and two false positives for other hrHPV genotypes. The Allplex HPV HR Detection assay showed almost perfect agreement with the Cobas HPV test, emphasizing its utility in hrHPV screening and monitoring.

Genetic diversity of Plasmodium malariae in sub-Saharan Africa: a two-marker genotyping approach for molecular epidemiological studies.

Introduction: Plasmodium malariae is the most common non-falciparum species in sub-Saharan Africa. Despite this, data on its genetic diversity is scarce. Therefore, we aimed to establish a P. malariae genotyping approach based on size polymorphic regions that can be easily applied in molecular epidemiological studies. Methods: Four potential genotyping markers, Pm02, Pm09, P. malariae thrombospondin-related anonymous protein (pmtrap), and P. malariae merozoite surface protein fragment 2 (pmmsp1 F2) were amplified via nested PCR and analysed using automated capillary gel electrophoresis. Results: We observed the highest allelic diversity for pmtrap (MOI = 1.61) and pmmsp1 F2 (He = 0.81). Further applying the two markers pmtrap and pmmsp1 F2 on a different sample set of 21 P. malariae positive individuals followed up over one week, we saw a high consistency in their performance. The results show a large complexity and high dynamics of P. malariae infections in the asymptomatic Gabonese study population. Discussion: We successfully implemented a new genotyping panel for P. malariae consisting of only two markers: pmtrap and pmmsp1 F2. It can be easily applied in other settings to investigate the genotype diversity of P. malariae populations, providing further important data on the molecular epidemiology of this parasite species.

Accurate and Automated Genotyping of the CFTR Poly-T/TG Tract with CFTR-TIPS.

Cystic fibrosis is caused by biallelic pathogenic variants in the CFTR gene, which contains a polymorphic (TG)mTn sequence (the "poly-T/TG tract") in intron 9. While T9 and T7 alleles are benign, T5 alleles with longer TG repeats, e.g., (TG)12T5 and (TG)13T5, are clinically significant. Thus, professional medical societies currently recommend reporting the TG repeat size when T5 is detected. Sanger sequencing is a cost-effective method of genotyping the (TG)mTn tract; however, its polymorphic length substantially complicates data analysis. We developed CFTR-TIPS, a freely available web-based software tool that infers the (TG)mTn genotype from Sanger sequencing data. This tool detects the (TG)mTn tract in the chromatograms, quantifies goodness of fit with expected patterns, and visualizes the results in a graphical user interface. It is broadly compatible with any Sanger chromatogram that contains the (TG)mTn tract ± 15 bp. We evaluated CFTR-TIPS using 835 clinical samples previously analyzed in a CLIA-certified, CAP-accredited laboratory. When operated fully automatically, CFTR-TIPS achieved 99.8% concordance with our clinically validated manual workflow, while generally taking less than 10 s per sample. There were two discordant samples: one due to a co-occurring heterozygous duplication that confounded the tool and the other due to incomplete (TG)mTn tract detection in the reverse chromatogram. No clinically significant misclassifications were observed. CFTR-TIPS is a free, accurate, and rapid tool for CFTR (TG)mTn tract genotyping using cost-effective Sanger sequencing. This tool is suitable both for automated use and as an aid to manual review to enhance accuracy and reduce analysis time.

High resolution HLA genotyping with third generation sequencing technology-A multicentre study.

Molecular HLA typing techniques are currently undergoing a rapid evolution. While real-time PCR is established as the standard method in tissue typing laboratories regarding allocation of solid organs, next generation sequencing (NGS) for high-resolution HLA typing is becoming indispensable but is not yet suitable for deceased donors. By contrast, high-resolution typing is essential for stem cell transplantation and is increasingly required for questions relating to various disease associations. In this multicentre clinical study, the TGS technique using nanopore sequencing is investigated applying NanoTYPE™ kit and NanoTYPER™ software (Omixon Biocomputing Ltd., Budapest, Hungary) regarding the concordance of the results with NGS and its practicability in diagnostic laboratories. The results of 381 samples show a concordance of 99.58% for 11 HLA loci, HLA-A, -B, -C, -DRB1, -DRB3, -DRB4, -DRB5, -DQA1, -DQB1, -DPA1 and -DPB1. The quality control (QC) data shows a very high quality of the sequencing performed in each laboratory, 34,926 (97.15%) QC values were returned as 'passed', 862 (2.4%) as 'inspect' and 162 (0.45%) as 'failed'. We show that an 'inspect' or 'failed' QC warning does not automatically lead to incorrect HLA typing. The advantages of nanopore sequencing are speed, flexibility, reusability of the flow cells and easy implementation in the laboratory. There are challenges, such as exon coverage and the handling of large amounts of data. Finally, nanopore sequencing presents potential for applications in basic research within the field of epigenetics and genomics and holds significance for clinical concerns.

Benchmarking pharmacogenomics genotyping tools: Performance analysis on short-read sequencing samples and depth-dependent evaluation.

Pharmacogenomics (PGx) investigates the influence of genetics on drug responses, enabling tailored treatments for personalized healthcare. This study assessed the accuracy of genotyping six genes using whole genome sequencing with four different computational tools and various sequencing depths. The effects of using different reference genomes (GRCh38 and GRCh37) and sequence aligners (BWA-MEM and Bowtie2) were also explored. The results showed generally minor variations in tool performance across most genes; however, more notable discrepancies were observed in the analysis of the complex CYP2D6 gene. Cyrius, a CYP2D6-specific tool, demonstrated the most robust performance, achieving the highest concordance rates for CYP2D6 in all instances, comparable to the consensus approach in most cases. There were rather small differences between the samples with 20× coverage depth and those with higher depth, but the decreased performance was more evident at lower depths, particularly at 5×. Additionally, variations in CYP2D6 results were observed when samples were aligned to different reference genomes using the same method, or to the same genome using different aligners, which led to reporting incorrect rare star alleles in several cases. These findings inform the selection of optimal PGx tools and methodologies as well as suggest that employing a consensus approach with two or more tools might be preferable for certain genes and tool combinations, especially at lower sequencing depths, to ensure accurate results. Additionally, we show how the upstream alignment can affect the performance of tools, an important factor to take into account.

Short Tandem Repeat Genotyping of Medically Important Fungi: A Comprehensive Review of a Powerful Tool with Extensive Future Potential.

Fungal infections pose an increasing threat to public health. New pathogens and changing epidemiology are a pronounced risk for nosocomial outbreaks. To investigate clonal transmission between patients and trace the source, genotyping is required. In the last decades, various typing assays have been developed and applied to different medically important fungal species. While these different typing methods will be briefly discussed, this review will focus on the development and application of short tandem repeat (STR) genotyping. This method relies on the amplification and comparison of highly variable STR markers between isolates. For most common fungal pathogens, STR schemes were developed and compared to other methods, like multilocus sequence typing (MLST), amplified fragment length polymorphism (AFLP) and whole genome sequencing (WGS) single nucleotide polymorphism (SNP) analysis. The pros and cons of STR typing as compared to the other methods are discussed, as well as the requirements for the development of a solid STR typing assay. The resolution of STR typing, in general, is higher than MLST and AFLP, with WGS SNP analysis being the gold standard when it comes to resolution. Although most modern laboratories are capable to perform STR typing, little progress has been made to standardize typing schemes. Allelic ladders, as developed for Aspergillus fumigatus, facilitate the comparison of STR results between laboratories and develop global typing databases. Overall, STR genotyping is an extremely powerful tool, often complimentary to whole genome sequencing. Crucial details for STR assay development, its applications and merit are discussed in this review.

Comparison of multiplex PCR capillary electrophoresis assay and PCR-reverse dot blot assay for human papillomavirus DNA genotyping detection in cervical cancer tissue specimens.

Background: The study aimed to evaluate the positivity rates and genotype distribution of the multiplex PCR capillary electrophoresis (MPCE) and PCR-Reverse Dot Blot (PCR-RDB) assays for human papillomavirus (HPV) detection in cervical cancer tissue specimens, and to explore their detection principles and applications in large-scale population screening. Methods: The MPCE and PCR-RDB assays were performed separately on 425 diagnosed cervical cancer tissue specimens. Subsequently, the results of both assays were compared based on the HPV infection positivity rates and genotype distribution. Results: The overall positive rates of HPV genotypes for the MPCE and PCR-RDB assays were 97.9% and 92.9%, respectively. A p-value < 0.001 indicated a statistically significance difference in consistency between the two assays. The kappa value was 0.390, indicating that the consistency between both assays was fair. HPV16 was the most common single-genotype infection type, with infection rates detected via MPCE and PCR-RDB assays being 75.7% and 68.3%, respectively. In the age group >50 years, the HPV multiple-type infection rate detected via MPCE assay was significantly higher than that detected by the PCR-RDB assay, with a statistically significant difference (p = 0.002). Conclusion: To reduce the false-negative rate and improve screening efficiency, the MPCE assay, which targets the oncogenic gene E6/E7 segments, can be extended to the general female population for the early detection, diagnosis, and treatment of cervical cancer.

Sequence-specific nanoparticle barcode strategy for multiplex human enterovirus typing.

Human enteroviruses (HEV) can cause a range of diseases from mild to potentially life-threatening. Identification and genotyping of HEV are crucial for disease management. Existing typing methods, however, have inherent limitations. Developing alternative methods to detect HEV with more virus types, high accuracy, and sensitivity in an accessible manner presents a technological and analytical challenge. Here, a sequence-specific nanoparticle barcode (SSNB) method is presented for simultaneous detection of 10 HEV types. This method significantly increases sensitivity, enhancing detection by 10-106 times over the traditional multiplex hybrid genotyping (MHG) method, by resolving cross-interference between the multiple primer sets. Furthermore, the SSNB method demonstrates a 100% specificity in accurately distinguishing between 10 different HEV types and other prevalent clinical viruses. In an analysis of 70 clinical throat swab samples, the SSNB method shows slightly higher detection rate for positive samples (50%) compared to the RT-PCR method (48.6%). Additionally, further assessment of the typing accuracy for samples identified as positive by SSNB using sequencing method reveals a concordance rate of 100%. The combined high sensitivity and specificity level of the methodology, together with the capability for multiple type analysis and compatibility with clinical workflow, make this approach a promising tool for clinical settings.

On leveraging self-supervised learning for accurate HCV genotyping.

Hepatitis C virus (HCV) is a major global health concern, affecting millions of individuals worldwide. While existing literature predominantly focuses on disease classification using clinical data, there exists a critical research gap concerning HCV genotyping based on genomic sequences. Accurate HCV genotyping is essential for patient management and treatment decisions. While the neural models excel at capturing complex patterns, they still face challenges, such as data scarcity, that exist a lot in computational genomics. To overcome this challenges, this paper introduces an advanced deep learning approach for HCV genotyping based on the graphical representation of nucleotide sequences that outperforms classical approaches. Notably, it is effective for both partial and complete HCV genomes and addresses challenges associated with imbalanced datasets. In this work, ten HCV genotypes: 1a, 1b, 2a, 2b, 2c, 3a, 3b, 4, 5, and 6 were used in the analysis. This study utilizes Chaos Game Representation for 2D mapping of genomic sequences, employing self-supervised learning using convolutional autoencoder for deep feature extraction, resulting in an outstanding performance for HCV genotyping compared to various machine learning and deep learning models. This baseline provides a benchmark against which the performance of the proposed approach and other models can be evaluated. The experimental results showcase a remarkable classification accuracy of over 99%, outperforming traditional deep learning models. This performance demonstrates the capability of the proposed model to accurately identify HCV genotypes in both partial and complete sequences and in dealing with data scarcity for certain genotypes. The results of the proposed model are compared to NCBI genotyping tool.

Variant calling and genotyping accuracy of ddRAD-seq: Comparison with 20X WGS in layers.

Whole Genome Sequencing (WGS) remains a costly or unsuitable method for routine genotyping of laying hens. Until now, breeding companies have been using or developing SNP chips. Nevertheless, alternatives methods based on sequencing have been developed. Among these, reduced representation sequencing approaches can offer sequencing quality and cost-effectiveness by reducing the genomic regions covered by sequencing. The aim of this study was to evaluate the ability of double digested Restriction site Associated DNA sequencing (ddRAD-seq) to identify and genotype SNPs in laying hens, by comparison with a presumed reliable WGS approach. Firstly, the sensitivity and precision of variant calling and the genotyping reliability of ddRADseq were determined. Next, the SNP Call Rate (CRSNP) and mean depth of sequencing per SNP (DPSNP) were compared between both methods. Finally, the effect of multiple combinations of thresholds for these parameters on genotyping reliability and amount of remaining SNPs in ddRAD-seq was studied. In raw form, the ddRAD-seq identified 349,497 SNPs evenly distributed on the genome with a CRSNP of 0.55, a DPSNP of 11X and a mean genotyping reliability rate per SNP of 80%. Considering genomic regions covered by expected enzymatic fragments (EFs), the sensitivity of the ddRAD-seq was estimated at 32.4% and its precision at 96.4%. The low CRSNP and DPSNP values were explained by the detection of SNPs outside the EFs theoretically generated by the ddRAD-seq protocol. Indeed, SNPs outside the EFs had significantly lower CRSNP (0.25) and DPSNP (1X) values than SNPs within the EFs (0.7 and 17X, resp.). The study demonstrated the relationship between CRSNP, DPSNP, genotyping reliability and the number of SNPs retained, to provide a decision-support tool for defining filtration thresholds. Severe quality control over ddRAD-seq data allowed to retain a minimum of 40% of the SNPs with a CcR of 98%. Then, ddRAD-seq was defined as a suitable method for variant calling and genotyping in layers.

Approach for Phased Sequence-Based Genotyping of the Critical Pharmacogene Dihydropyrimidine Dehydrogenase (DPYD).

Pre-treatment genotyping of four well-characterized toxicity risk-variants in the dihydropyrimidine dehydrogenase gene (DPYD) has been widely implemented in Europe to prevent serious adverse effects in cancer patients treated with fluoropyrimidines. Current genotyping practices are largely limited to selected commonly studied variants and are unable to determine phasing when more than one variant allele is detected. Recent evidence indicates that common DPYD variants modulate the functional impact of deleterious variants in a phase-dependent manner, where a cis- or a trans-configuration translates into different toxicity risks and dosing recommendations. DPYD is a large gene with 23 exons spanning nearly a mega-base of DNA, making it a challenging candidate for full-gene sequencing in the diagnostic setting. Herein, we present a time- and cost-efficient long-read sequencing approach for capturing the complete coding region of DPYD. We demonstrate that this method can reliably produce phased genotypes, overcoming a major limitation with current methods. This method was validated using 21 subjects, including two cancer patients, each of whom carried multiple DPYD variants. Genotype assignments showed complete concordance with conventional approaches. Furthermore, we demonstrate that the method is robust to technical challenges inherent in long-range sequencing of PCR products, including reference alignment bias and PCR chimerism.

High-fidelity, large-scale targeted profiling of microsatellites.

Microsatellites are highly mutable sequences that can serve as markers for relationships among individuals or cells within a population. The accuracy and resolution of reconstructing these relationships depends on the fidelity of microsatellite profiling and the number of microsatellites profiled. However, current methods for targeted profiling of microsatellites incur significant "stutter" artifacts that interfere with accurate genotyping, and sequencing costs preclude whole-genome microsatellite profiling of a large number of samples. We developed a novel method for accurate and cost-effective targeted profiling of a panel of more than 150,000 microsatellites per sample, along with a computational tool for designing large-scale microsatellite panels. Our method addresses the greatest challenge for microsatellite profiling-"stutter" artifacts-with a low-temperature hybridization capture that significantly reduces these artifacts. We also developed a computational tool for accurate genotyping of the resulting microsatellite sequencing data that uses an ensemble approach integrating three microsatellite genotyping tools, which we optimize by analysis of de novo microsatellite mutations in human trios. Altogether, our suite of experimental and computational tools enables high-fidelity, large-scale profiling of microsatellites, which may find utility in diverse applications such as lineage tracing, population genetics, ecology, and forensics.

Genotyping-by-sequencing targets genic regions and improves resolution of genome-wide association studies in autotetraploid potato.

KEY MESSAGE: De novo genotyping in potato using methylation-sensitive GBS discovers SNPs largely confined to genic or gene-associated regions and displays enhanced effectiveness in estimating LD decay rates, population structure and detecting GWAS associations over 'fixed' SNP genotyping platform. Study also reports the genetic architectures including robust sequence-tagged marker-trait associations for sixteen important potato traits potentially carrying higher transferability across a wider range of germplasm. This study deploys recent advancements in polyploid analytical approaches to perform complex trait analyses in cultivated tetraploid potato. The study employs a 'fixed' SNP Infinium array platform and a 'flexible and open' genome complexity reduction-based sequencing method (GBS, genotyping-by-sequencing) to perform genome-wide association studies (GWAS) for several key potato traits including the assessment of population structure and linkage disequilibrium (LD) in the studied population. GBS SNPs discovered here were largely confined (~ 90%) to genic or gene-associated regions of the genome demonstrating the utility of using a methylation-sensitive restriction enzyme (PstI) for library construction. As compared to Infinium array SNPs, GBS SNPs displayed enhanced effectiveness in estimating LD decay rates and discriminating population subgroups. GWAS using a combined set of 30,363 SNPs identified 189 unique QTL marker-trait associations (QTL-MTAs) covering all studied traits. The majority of the QTL-MTAs were from GBS SNPs potentially illustrating the effectiveness of marker-dense de novo genotyping platforms in overcoming ascertainment bias and providing a more accurate correction for different levels of relatedness in GWAS models. GWAS also detected QTL 'hotspots' for several traits at previously known as well as newly identified genomic locations. Due to the current study exploiting genome-wide genotyping and de novo SNP discovery simultaneously on a large tetraploid panel representing a greater diversity of the cultivated potato gene pool, the reported sequence-tagged MTAs are likely to have higher transferability across a wider range of potato germplasm and increased utility for expediting genomics-assisted breeding for the several complex traits studied.

Development and Optimization of Oligonucleotide Ligation Assay (OLA) Probes for Detection of HIV-1 Resistance to Dolutegravir.

The WHO currently recommends dolutegravir (DTG)-based ART for persons living with HIV infection in resource-limited-settings (RLS). To expand access to testing for HIV drug resistance (DR) to DTG in RLS, we developed probes for use in the oligonucleotide ligation assay (OLA)-Simple, a near-point of care HIV DR kit. Genotypic data from clinical trials and case reports were used to determine the mutations in HIV-1 integrase critical to identifying individuals with DTG-resistance at virologic failure of DTG-based ART. Probes to detect G118R, Q148H/K/R, N155H and R263K in HIV-1 subtypes A, B, C, D and CRF01_AE were designed using sequence alignments from the Los Alamos database and validated using 61 clinical samples of HIV-1 subtypes A, B, C, D, CRF01_AE genotyped by PacBio (n = 15) or Sanger (n = 46). Initial OLA probes failed to ligate for 16/244 (6.5%) codons (9 at G118R and 7 at Q148H/K/R). Probes revised to accommodate polymorphisms interfering with ligation at codons G118R and Q148R reduced indeterminates to 3.7% (5 at G118R and 4 at Q148H/K/R) and detected DTG-mutations with a sensitivity of 96.5% and 100% specificity. These OLA DTG resistance probes appear highly sensitive and specific across HIV-1 subtypes common in RLS with high burden of HIV infection.

Multiplex PCR-based genotyping of Salmonella Enteritidis and Salmonella Typhimurium from food sources and assessment of their antimicrobial resistance profiles in Egypt.

BACKGROUND: Salmonellosis is a widespread zoonotic disease that poses a significant threat to livestock and public health. This study aimed to serotype 20 Salmonella isolates obtained from sixty retail chicken meats, assess Salmonella contamination from eggs, and evaluate antibiotic resistance profiles. METHODS AND RESULTS: Twenty eggs were randomly collected in the new Borg El Arab market. Bacterial isolation was carried out utilizing both traditional culture, biochemical, and PCR methods. Among the twenty eggs analyzed, three (15%) tested positive for Salmonella, while the remaining seventeen (85%) were confirmed as negative. Genotyping through multiplex PCR revealed the presence of two S. Enteritidis and other serovar, with the use of three specific gene sets: a random sequence for Salmonella spp., sdfI gene for S. Enteritidis, and flagellin (fliC gene) for S. Typhimurium. Out of the 20 isolates obtained from chicken meat, five (25%) were identified as S. Typhimurium, and three (15%) were classified as S. Enteritidis. All isolates sourced from chicken meat exhibited resistance to Rifampicin and Amoxicillin, with 90% displaying sensitivity to cefotaxime, gemifloxacin, and Erythromycin. Importantly, S. Blegdam, identified via serological methods, displayed resistance to all tested antibiotics. For the three isolates obtained from eggs, 66.6% showed sensitivity to cefotaxime, erythromycin, cefuraxime, and cefaclor, while displaying complete resistance (100%) to Amoxicillin, rifampicin, clarithromycin, and cefadroxil. Notably, one serovar exhibited absolute resistance to all tested drugs. CONCLUSION: Stakeholders must implement strict control measures and rationalize antibiotic use in veterinary and human medicine due to the rise of antibiotic-resistant strains.

Phylogeography and genetic structure of Papaver bracteatum populations in Iran based on genotyping-by-sequencing (GBS).

Papaver bracteatum, known for its high thebaine content and absence of morphine, has emerged as a promising alternative to opium poppy for codeine production. In this study, our objective was to create a diverse panel representing the natural variation of this species in Iran. To achieve this, we employed genotyping-by-sequencing to obtain genome-wide distributed single-nucleotide polymorphisms (SNPs) for phylogeographic analysis, population structure assessment, and evaluation of genetic diversity within P. bracteatum populations. A total of 244 P. bracteatum individuals from 13 distinct populations formed seven genetic groups, along with one highly admixed population. We observed a clear split between the populations inhabiting the Alborz Mts. in the east and Zagros Mts. in the west. In between these mountain ranges, the population of Kachal Mangan exhibited a high degree of genetic admixture between both genetic groups. At or after the end of the last glacial maximum, when climate conditions rapidly changed, all P. bracteatum populations experienced a strong demographic bottleneck reducing the already small effective population sizes further before they increased to their recent strengths. Our results suggest that the ongoing climate change together with human pressure on the species' habitats and limited seed-dispersal ability are potential factors contributing today to rising genetic isolation of P. bracteatum populations. Our results provide genetic data that can be used for conservation measures to safeguard the species' genetic diversity as a resource for future breeding approaches in this medicinally important species.