SNP Genotyping Research Articles

Optimization of Whole-Genome Resequencing Depth for High-Throughput SNP Genotyping in Litopenaeus vannamei

The application of whole-genome resequencing in genetic research is rapidly expanding, yet the impact of sequencing depth on data quality and variant detection remains unclear, particularly in aquaculture species. This study re-sequenced 31 Litopenaeus vannamei (L. vannamei) samples at over 28× sequencing depth using the Illumina NovaSeq system and down-sampled the data to simulate depths from 0.5× to 20×. Results showed that when the sequencing depth was below 10×, the number of SNP identifications increased sharply with the rise in depth, with single nucleotide polymorphisms (SNPs) detected at 10× accounting for approximately 69.16% of those detected at 20×. The genotyping accuracy followed a similar trend to SNP detection results, being approximately 0.90 at 6×. Further analyses showed that the main cause of genotyping errors was the misidentification of heterozygous variants as homozygous variants. Therefore, considering both the quantity and quality of SNPs, a sequencing depth of 10× is recommended for whole-genome studies and genetic mapping, while a depth of 6× is more cost-effective for population structure analysis. This study underscores the importance of selecting optimal sequencing depth to ensure reliable variant detection and high data quality, providing valuable guidance for whole-genome resequencing in shrimp and other aquatic species.

Parental Reconstruction from a Half-Sib Population of Stoneless Jujube Ziziphus jujuba Mill. Based on Individual Specific SNP Markers Using Multiplex PCR

The selection of unique and individual-specific SNPs is important as compared with universal SNPs for individual identification. Therefore, the main significance of this research is the selection of specific SNPs in male parent and the identification of offspring with these specific SNPs in their genome by multiplex PCR, which is utilized for genotyping of 332 half-sib plants of Ziziphus jujuba.This cost-effective method makes as much as possible to utilize the same amount of each pair of various targeted loci primers. After PCR amplification of targeted genome parts, the mixed products can be directly used in a next-generation sequencing platform. We concomitantly amplified 10 unique SNP loci at 10 different chromosomes of male JingZao 39 plants in 332 half-sib plants and sequenced them on the Illumina Novaseq 6000 platform. Analysis of SNP genotyping accuracy of 332 half-sib plants showed that all 10 unique SNPs in all 332 plants were correctly amplified in this multiplex PCR method. Furthermore, based on Mendelian inheritance, we identified 124 full-sib plants that have 10 unique SNPs in their genomes. These results were further confirmed by whole genome resequencing of 82 randomly selected half-sib plants, and the identity-by-descent values of all full-sib plants were between 0.4399 to 0.5652. This study displayed a cost-effective multiplex PCR method and proper identification of pollen parent through specific SNPs in half-sib progenies and firstly obtained a full-sib population between ‘Wuhezao’ and ‘JingZao 39’, segregating for stone and stoneless fruit.

Extended sperm storage recorded in red-tailed phascogale (Phascogale calura) during a trial translocation to Vulkathunha-Gammon Ranges National Park, South Australia

We present a case of extended sperm storage in a female red-tailed phascogale (Phascogale calura) during a trial reintroduction in 2022. Parentage reported by single nucleotide polymorphism genotyping revealed the father of one litter had died approximately 50 days before the litter was born. The recorded gestation period for red-tailed phascogales is 28–32 days. Our record indicates sperm storage and/or diapause of up to 15–27 days, at least double the previously recorded sperm storage duration in this species.

Fluorescent primers amplification refractory mutation system qPCR (FP ARMS-qPCR) for MTHFR C677T SNP genotyping.

The currently used methods for the detection of methylene tetrahydrofolic acid reductase (MTHFR) C677T single nucleotide polymorphism (SNP) are either time-consuming or expensive. In this study, we devised an accurate, rapid and easy-to-use SNP detection system based on fluorescent primers amplification refractory mutation system qPCR, known as FP ARMS-qPCR. Fluorescent primers (FPs) modified by fluorescent dye or quencher near the 3' terminal thymine were designed. The reaction conditions were optimized and the performance was evaluated. Using commercial kits as controls, 242 samples were tested in parallel to verify the feasibility of the FP ARMS-qPCR assay. We demonstrated the good sensitivity and specificity of the FP ARMS-qPCR with optimized conditions. The assay was able to accurately distinguish between different SNP sites of MTHFR C677T in less than 2h using as low as 50 pg of template genomic DNA. Completely consistent genotyping results reveal that FP ARMS-qPCR is concordant with commercial kits. We established a specific, sensitive, and rapid FP ARMS-qPCR method for the detection of MTHFR C677T genotype. This could also serve as a potential diagnostic tool for a variety of diseases.

Tenascin-C-Matrix Metalloproteinase-3 Phenotype and the Risk of Tendinopathy in High-Performance Athletes: A Case–Control Study

Background/Objectives: Tendon structure is predominantly composed of the extracellular matrix (ECM), and genetic variants in non-collagenous ECM components may influence susceptibility to tendinopathy. We investigated the potential influence of single nucleotide polymorphisms (SNPs) in fibrillin-2 (FBN2), tenascin-C (TNC), and matrix metalloproteinase-3 (MMP3) on the tendon regeneration failure phenotype and impact on the susceptibility to tendinopathy in Brazilian high-performance athletes. Methods: This case–control study was conducted with 397 high-performance athletes from different sports modalities (197 tendinopathy cases and 200 controls), and they were analyzed by validated TaqManTM SNP genotyping assays of the SNPs FBN2 (rs331079), TNC (rs2104772), and MMP3 (rs591058). Results: Out of the 197 tendinopathy cases, 63% suffered from chronic tendon pain and 22% experienced more than three episodes of disease manifestation. The TNC-rs2104772-A allele was significantly associated with tendinopathy (OR: 1.4; 95% CI: 1.1–1.8), while athletes carrying the MMP3-rs591058-T allele were linked to an increased risk of more episodes of disease manifestation (OR: 1.7; 95% CI: 1.1–2.8). The TNC-MMP3 tendon regeneration failure phenotype (TNC-A/MMP3-T) was associated with an increased risk of tendinopathy (OR: 1.4; 95% CI: 1.1–2.0) and episodes of disease manifestation (OR: 2.0; 95% CI: 1.2–3.5). Athletes with tendinopathy who had the TNC-A/MMP3-T interaction were more prone to experiencing more than three disease exacerbations (OR: 4.3; 95% CI: 1.8–10.5) compared to TNC-A/TNC-C. Conclusions: This study suggests that rs2104772 and rs591058 SNPs could be involved in the tendon regeneration failure phenotype and may influence the molecular mechanism related to the regulation of the tendon ECM during training workload.

Genetic association of the kynurenine pathway to suicidal behavior

Suicidal behavior has been associated with dysfunctions in the kynurenine pathway, including alterations in the levels of neuroprotective and neurotoxic metabolites. Changes in the catalytic activity of enzymes within the pathway may contribute significantly. Variations in the genes encoding enzymes within the pathway can significantly affect their catalytic activity, playing a crucial role in the process. To explore this possibility, we hypothesized that these genetic variations would occur more frequently in patients with a history of suicidal behavior compared to non-suicidal individuals. Thus, we investigated the relationship between a history of suicide attempts and five single nucleotide polymorphisms (SNPs) within genes involved in the kynurenine pathway: IDO1 (rs7820268), IDO2 (rs10109853), KMO (rs1053230), KAT1 (rs10988134), and ACSMD (rs2121337). Our sample comprised 849 subjects: 325 individuals who had attempted suicide in their lifetime (SAs), 99 individuals with a history of major depression disorder but no previous suicide attempts (non-SAs), and 425 non-psychiatric controls (CTRL). We performed SNP association analyses using codominant, dominant, and recessive models. Adjustment for sex and multiple comparisons was applied. After adjustment, the analysis revealed that SAs showed a significantly higher frequency of T alleles and TT genotypes of the rs1053230 SNP compared to CTRL across nearly all models. Furthermore, in the recessive model, non-SAs displayed a higher prevalence of the TT genotype of the rs10109853 SNP compared to CTRL.The rs1053230 and rs10109853 SNPs could play a role in the previously observed metabolic dysregulation among SAs and non-SAs, respectively. To validate our findings, it is crucial to conduct functional analyses to investigate the impact of rs10109853 and rs1053230 SNPs on the expression and/or catalytic activity of the corresponding enzymes.

Host genetic regulation of specific functional groups in the rumen microbiome of dairy cows: Implications for lactation trait

IntroductionRuminants play a pivotal role in our society by transforming non-consumable substances from industrial by-products and plant fibers into valuable resources such as meat and milk. This remarkable conversion ability is primarily attributed to the rumen microbiota, which is influenced by various factors, including diet, climate, and geographical location. In recent years, increasing research has shown that host factors (breed, genetic variation, etc.) also play vital roles in shaping rumen microbial composition and function in cattle. ObjectiveThis study aims to provide a theoretical basis and an opportunity for further investigating the regulation of lactation traits in dairy cows through host genetics and the interaction with the rumen microbiota. MethodTo investigate the interactions between host genotype, rumen microbiota, and animal phenotype, we curated and analyzed the dairy herd improvement (DHI) data, single nucleotide polymorphisms (SNPs) genotypes, and 16S rumen microbiota data from 1,169 Holstein dairy cows. Heritability and microbiability estimation, along with genome-wide association studies (GWAS) were performed to identify candidate microorganisms and host genetic loci. ResultWe identified thirty-one heritable taxa, whose functions were predominantly enriched in carbohydrate metabolism and energy metabolism. The genome-wide association study revealed that nine heritable bacteria were significantly associated with forty-three SNPs. Functional genes located within or near these SNPs were primarily associated with rumen epithelial development. Additionally, these nine heritable bacteria were primarily annotated as complex polysaccharide degraders and butyrate producers, such as Fibrobacter sp900143055 and Pseudoruminococcus massiliensis, which showed significant associations with milk yield and milk fat percentage. Compared to previous studies, we newly discovered the existence of a high heritability of Olsenella umbonate, Butyrivibrio hungatei, among others.

Are SNPs Linked to Somatic Cell Score Suitable Markers for the Susceptibility to Specific Mastitis Pathogens in Holstein Cows?

Mastitis in cattle is often caused by microorganism infections in the udder. The three most common pathogens are esculin-positive streptococci (SC+), coagulase-negative staphylococci (CNS), and Escherichia coli (E. coli). In a previous study, 10 SNPs were associated with somatic cell score and mastitis in diverse Holstein populations. We tested these SNPs for their effects on individual pathogen presence. Milk and pathogen samples of 3076 Holstein cows were collected from four farms. Samples were excluded if multiple pathogens were present at the same time. Records of the same pathogen within 14 days of each other were counted as one infection. This resulted in 1129 pathogen-positive samples. Cases and controls were in ratios of 20:80 for SC+, 8:92 for CNS, and 11:89 for E. coli. The lasso, backward, and forward methods were used to narrow down SNPs associated with pathogen presence. The suitability of the SNPs to separate the samples into cases or controls for each pathogen was indicated using ROC curves. The Cochran-Armitage (CAT) and the Jonckheere-Terpstra (JTT) tests evaluated the influence of the SNPs on pathogen presence. Finally, a generalised linear mixed model (GLMM) including fixed environmental effects and a random sire effect was fitted to the binary trait of pathogen presence to test for association. In total, six out of the 10 investigated SNPs showed associations with pathogen presence based on the forward method: Two SNPs each for SC+ (rs41588957, rs41257403) and CNS (rs109934030, rs109441194), and three for E. coli (rs109934030, rs41634110, rs41636878). The CAT and GTT tests linked four SNPs (rs41588957, rs41634110, rs109441194, rs41636878) to pathogen presence, two of which were confirmed with the GLMM (rs41634110, rs109441194), with effects on CNS and E. coli. The SNPs linked to CNS and those linked to E. coli explained 13.2% and 13.8% of the variance, compared to 19% and 18.4%, respectively, of the full model with all 10 SNPs. Half of the SNP genotypes previously linked to lower SCS also decreased the probability for pathogen presence and might therefore be targets not just for lower SCS but for a better pathogen resistance. Trial Registration: Not applicable, no new data were collected for this study.

Allele-specific micro-RNA-mediated regulation of ADAM33 in childhood allergic asthma.

A disintegrin and metalloprotease 33 (ADAM33) is associated with asthma susceptibility, and its genetic variations impact susceptibility and disease severity. However, the mechanisms remain unclear. This study aimed to investigate ADAM33 single nucleotide polymorphisms (SNPs) in childhood asthma susceptibility and explore their regulatory mechanisms. Eleven selected SNPs in ADAM33 were genotyped and identified the association with asthma susceptibility. In the validation cohort, we measured plasma sADAM33 levels and compared them with disease severity among children with different SNP genotypes. Computational predictions identified miRNAs targeting the SNP, and the impact of the SNP on miRNA regulation was confirmed using a dual luciferase reporter system. Finally, we validated the regulatory role of miRNAs on ADAM33 expression using an in vitro model with upregulated ADAM33 expression. Only rs3918400 was associated with asthma susceptibility. In the validation cohort, children with allergic asthma exhibited higher plasma sADAM33 levels. Among asthmatic children, those with the rs3918400 CT/TT genotype had higher sADAM33 levels, poorer asthma control, more severe airway hyper-responsiveness, lower FEV1% and higher dust mite-specific IgE activity compared to those with the CC genotype. miR-3928-5p bound strongly to the rs3918400 C allele and effectively reduced ADAM33 protein expression in CC genotype cells. However, the binding affinity of miR-3928-5p to the T allele was weaker, resulting in diminished negative regulation of protein expression. The rs3918400 SNP affects the negative regulation of ADAM33 by miR-3928-5p, potentially participating in a complex interplay of processes related to childhood asthma susceptibility.

Revealing host genome–microbiome networks underlying feed efficiency in dairy cows

Ruminants have the ability to digest human-inedible plant materials, due to the symbiotic relationship with the rumen microbiota. Rumen microbes supply short chain fatty acids, amino acids, and vitamins to dairy cows that are used for maintenance, growth, and lactation functions. The main goal of this study was to investigate gene-microbiome networks underlying feed efficiency traits by integrating genotypic, microbial, and phenotypic data from lactating dairy cows. Data consisted of dry matter intake (DMI), net energy secreted in milk, and residual feed intake (RFI) records, SNP genotype, and 16S rRNA rumen microbial abundances from 448 mid-lactation Holstein cows. We first assessed marginal associations between genotypes and phenotypic and microbial traits through genomic scans, and then, in regions with multiple significant hits, we assessed gene-microbiome-phenotype networks using causal structural learning algorithms. We found significant regions co-localizing the rumen microbiome and feed efficiency traits. Interestingly, we found three types of network relationships: (1) the cow genome directly affects both rumen microbial abundances and feed efficiency traits; (2) the cow genome (Chr3: 116.5 Mb) indirectly affects RFI, mediated by the abundance of Syntrophococcus, Prevotella, and an unknown genus of Class Bacilli; and (3) the cow genome (Chr7: 52.8 Mb and Chr11: 6.1–6.2 Mb) affects the abundance of Rikenellaceae RC9 gut group mediated by DMI. Our findings shed light on how the host genome acts directly and indirectly on the rumen microbiome and feed efficiency traits and the potential benefits of the inclusion of specific microbes in selection indexes or as correlated traits in breeding programs. Overall, the multistep approach described here, combining whole-genome scans and causal network reconstruction, allows us to reveal the relationship between genome and microbiome underlying dairy cow feed efficiency.

SNP Genotype Imputation in Forensics—A Performance Study

Background/Objectives: Emerging forensic genetic applications, such as forensic investigative genetic genealogy (FIGG), advanced DNA phenotyping, and distant kinship inference, increasingly require dense SNP genotype datasets. However, forensic-grade DNA often contains missing genotypes due to its quality and quantity limitations, potentially hindering these applications. Genotype imputation, a method that predicts missing genotypes, is widely used in population and medical genetics, but its utility in forensic genetics has not been thoroughly explored. This study aims to assess the performance of genotype imputation in forensic contexts and determine the conditions under which it can be effectively applied. Methods: We employed a simulation-based approach to generate realistic forensic SNP genotype datasets with varying numbers, densities, and qualities of observed genotypes. Genotype imputation was performed using Beagle software, and the performance was evaluated based on the call rate and imputation accuracy across different datasets and imputation settings. Results: The results demonstrate that genotype imputation can significantly increase the number of SNP genotypes. However, imputation accuracy was dependent on factors such as the quality of the original genotype data and the characteristics of the reference population. Higher SNP density and fewer genotype errors generally resulted in improved imputation accuracy. Conclusions: This study highlights the potential of genotype imputation to enhance forensic SNP datasets but underscores the importance of optimizing imputation parameters and understanding the limitations of the original data. These findings will inform the future application of imputation in forensic genetics, supporting its integration into forensic workflows.

Genotyping single nucleotide polymorphisms in homologous regions using multiplex kb level amplicon capture sequencing.

Single nucleotide polymorphisms (SNPs) in homologous regions play a critical role in the field of genetics. However, genotyping these SNPs is challenging due to the presence of repetitive sequences within genome, which demand specific method. We introduce a new, mid-throughput method that simplifies SNP genotyping in homologous DNA sequences by utilizing a combination of multiplex kb level PCR (PCR size 2.5k-3.5kb) for capturing targeted regions and multiplex nested PCR library construction for next-generation sequencing (Multi-kb level capture-seq). First of all, we randomly selected 7 SNPs in homologous regions and successfully captured 6-plex kb level amplicons (one of segments contains 2 SNPs, while the remaining segments each have only one SNP) in a single tube. And then, the amplification products were subjected to multiplex nested PCR for library construction and sequenced on Illumina platform. We tested this strategy using 600 amplicons from 100 samples and accurately genotyped 96.8% of target SNPs with a coverage depth of ≥ 15×. For the uniformity within the samples, over 66.7% (4/6) of the amplicons had a coverage depth above 0.2-fold of average sequencing depth. To validate the accuracy of this approach, we performed Ligase detection reaction PCR for genotyping the 100 samples, and found that the genotyping data was 97.71% consistent with our NGS results. In conclusion, we have developed a highly efficient and accurate method for SNP genotyping in homologous regions, which offers researchers a new strategy to explore the complex regions of genome.

Identification of quantitative trait locus and positional candidate loci influencing chicken egg quality under tropical conditions.

Egg quality is a vital factor in the poultry industry. High-quality eggs not only meet consumer expectations for appearance, taste, and nutritional value but also have high marketability, profitability, and consumer satisfaction. Accordingly, we executed our research with the purpose of determining chromosomal regions and genetic markers associated with egg quality in an F2 cross-bred chicken population under tropical conditions; we determined these through a genome-wide association study and quantitative trait locus (QTL) mapping. This population was created by cross-breeding the L2 line of Taiwan Country chickens, which is adapted to local conditions in Taiwan, with an experimental line (R-line) of Rhode Island Red layer chickens, which was developed by the French National Research Institute for Agriculture, Food and the Environment. A 60K single nucleotide polymorphism (SNP) genotyping array for chickens was employed to execute the analysis. Our analysis revealed 40 QTLs associated with egg quality under tropical conditions, namely 20 QTLs with genome-wide statistical significance and 20 QTLs with chromosome-wide statistical significance. Furthermore, we identified 93 SNPs exerting discernible effects on egg quality, with 10 of these effects exhibiting genome-wide significance and 83 exhibiting potential significance. The majority of the detected QTL regions and SNPs agreed with those identified as having an association with egg quality or production traits in previous studies, thus supporting the interrelationships determined between the studied characteristics. The findings of this study enhance the understanding regarding the genetic regulation governing chicken egg quality, thereby serving as a valuable reference for future functional investigations.

SNPs Analysis Indicates Non-Uniform Origins of Invasive Mussels (Mytilus galloprovincialis Lamarck, 1819) on the Southern African Coast

Understanding the origins of invasive species is necessary to manage them and predict their potential for spreading. The mussel genus Mytilus forms an important component of coastal ecosystems in the northern and southern hemispheres. M. galloprovincialis is an important invasive species globally, first appearing on the South African coast in the 1970s. Studies using nuclear and mitochondrial DNA indicated that the invasion probably originated from the north-east Atlantic. We used fifty-five polymorphic SNPs to genotype mussels from sites across the coast of South Africa with reference samples from the Mediterranean, the Atlantic, and New Zealand to test for possible introgression of the northern and southern taxa. Low levels of genetic differentiation were confirmed, and all samples grouped with reference samples of the Atlantic form of M. galloprovincialis, supporting previous studies. The SNP genotyping, however, allowed the detection of some individuals with genotypes typical of the Mediterranean, indicating that introduced populations in South Africa do not have a uniform origin. The initial population introduced to South Africa may have been genetically heterogenous from the start, coming from a region influenced by both the Atlantic and Mediterranean. Alternatively, multiple introductions may have taken place, originating from different regions, specifically North Africa, southern Europe, and the Mediterranean, building up the final heterogeneity.

Genetic Diversity in the Orenburg Goat Breed Revealed by Single-Nucleotide Polymorphism (SNP) Analysis: Initial Steps in Saving a Threatened Population

Background/Objectives: Orenburg goats are renowned for their soft down that acts as a substrate for warm clothing, particularly shawls that have an international reputation. As with many local livestock breeds, however, the Orenburg is presently at risk of extinction, an issue that can be addressed by assessing population genetic diversity and, thereafter, encouraging as much outbreeding as possible. Using single-nucleotide polymorphism (SNP)-based data, therefore, we analyzed the genetic diversity and population structure of modern Orenburg goats using samples collected from an expedition to Orenburg Oblast in 2024. Methods: We applied the Goat SNP50 BeadChip (Illumina, San Diego, CA, USA) for the genotyping of Orenburg goats from modern and archived populations. SNP genotypes of three Orenburg populations sampled in 2017 and 2019, Altai Mountain, Altai White, and Soviet Mohair breeds, were added to the dataset. Results: Principal component analysis and network and admixture analyses demonstrated that the genetic background inherent to the archived group of Orenburg goats was maintained in all modern populations. Values of genetic diversity indicators in modern populations were compatible with those obtained in comparison groups. Runs of homozygosity (ROH) were found in all the Orenburg goat populations (with a mean ROH length of 72.6–108.9 Mb and mean ROH number of 28–36). Genomic inbreeding based on ROH was low in all the Orenburg populations (FROH = 0.03–0.045). Conclusions: We showed that the ancestral background is retained in present-day Orenburg goats sampled in 2024. We provide the genetic basis through which certain breeder animals may be selected and bred traditionally or ex situ through a conservation program of gamete preservation.

Using eDNA to Supplement Population Genetic Analyses for Cryptic Marine Species: Identifying Population Boundaries for Alaska Harbour Porpoises.

Isolation by distance and biogeographical boundaries define patterns of population genetic structure for harbour porpoise along the Pacific coast from California to British Columbia. Until recently, inadequate sample sizes in many regions constrained efforts to characterise population genetic structure throughout the coastal waters of Alaska. Here, tissue samples from beachcast strandings and fisheries bycatch were supplemented with targeted environmental DNA (eDNA) samples in key regions of Alaska coastal and inland waters. Using a geographically explicit, hierarchical approach, we examined the genetic structure of Alaska harbour porpoises, using both mitochondrial DNA (mtDNA) sequence data and multilocus SNP genotypes. Despite a lack of evidence of genetic differentiation from nuclear SNP loci, patterns of relatedness and genetic differentiation from mtDNA suggest natal philopatry at multiple geographic scales, with limited gene flow among sites possibly mediated by male dispersal. A priori clustering of sampled areas at an intermediate scale (eastern and western Bering Sea, Gulf of Alaska and Southeast Alaska) best explained the genetic variance (12.37%) among regions. In addition, mtDNA differentiation between the Gulf of Alaska and eastern Bering Sea, and among regions within the Gulf of Alaska, indicated significant genetic structuring of harbour porpoise populations in Southeast Alaska. The targeted collection of eDNA samples from strata within Southeast Alaska was key for elevating the statistical power of our mtDNA dataset, and findings indicate limited dispersal between neighbouring strata within coastal and inland waters. These results provide evidence supporting a population boundary within the currently recognised Southeast Alaska Stock. Together, these findings will prove useful for ongoing management efforts to reduce fisheries conflict and conserve genetic diversity in this iconic coastal species.

Single nucleotide polymorphism discrimination and genotyping based on cascade strand displacement reaction mediated label-free Cas12a system

Single nucleotide polymorphism (SNP) discrimination plays an important role in precision medicine by providing insights into an individual’s genetic information. The low abundance of the mutant target and the minimal impact caused by SNP on the whole nucleic acid sequence remain a challenge during discrimination. Herein, a cascade strand displacement reaction mediated label-free Cas12a sensing platform is established for SNP analysis. Split G-quadruplex (G4) motif is recruited as label-free signal output for Cas12a sensing system, and hence overcomes relying of fluorescence labeled substrates like conventional method. The established platform exhibits excellent single base difference discrimination ability attributing to the cascade strand displacement process, during which, single-base mismatch will affect the strand-exchange rate significantly. The limit of detection reaches 1 copy / test after integration with isothermal preamplification. The proposed method can discriminate as low as 0.1 % single base variation and perform robustly in biological matrixes. Human buccal swab samples are successfully genotyped with high accuracy.

Genotyping Error Detection and Customised Filtration for SNP Datasets.

A major challenge in analysing single-nucleotide polymorphism (SNP) genotype datasets is detecting and filtering errors that bias analyses and misinterpret ecological and evolutionary processes. Here, we present a comprehensive method to estimate and minimise genotyping error rates (deviations from the 'true' genotype) in any SNP datasets using triplicates (three repeats of the same sample) in a four-step filtration pipeline. The approach involves: (1) SNP filtering by missing data; (2) SNP filtering by error rates; (3) sample filtering by missing data and (4) detection of recaptured individuals by using estimated SNP error rates. The modular pipeline is provided in an R script that allows customised adjustments. We demonstrate the applicability of the method using non-invasive sampling from the Asiatic wild ass (Equus hemionus) population in Israel. We genotyped 756 samples using 625 SNPs, of which 255 were triplicates of 85 samples. The average SNP error rate, calculated based on the number of mismatching genotypes across triplicates before filtration, was 0.0034 and was reduced to 0.00174 following filtration. Evaluating genetic distance (GD) and relatedness (r) between triplicates before and after filtration (expected to be at the minimum and maximum respectively) showed a significant reduction in the average GD, from 58.1 to 25.3 (p = 0.0002) and a significant increase in relatedness, from r = 0.98 to r = 0.991 (p = 0.00587). We demonstrate how error rate estimation enhances recapture detection and improves genotype quality.

Genetic Diversity and Population Structure of Cacao (Theobroma cacao L.) Germplasm from Sierra Leone and Togo Based on KASP–SNP Genotyping

Cacao (Theobroma cacao L.) is a tropical tree species belonging to the Malvaceae, which originated in the lowland rainforests of the Amazon. It is a major agricultural commodity, which contributes towards the Gross Domestic Product of West African countries, where it accounts for about 70% of the world’s production. Understanding the genetic diversity of genetic resources in a country, especially for an introduced crop such as cacao, is crucial to their management and effective utilization. However, very little is known about the genetic structure of the cacao germplasm from Sierra Leone and Togo based on molecular information. We assembled cacao germplasm accessions (235 from Sierra Leone and 141 from Togo) from different seed gardens and farmers’ fields across the cacao-producing states/regions of these countries for genetic diversity and population structure studies based on single nucleotide polymorphism (SNP) markers using 20 highly informative and reproducible KASP–SNPs markers. Genetic diversity among these accessions was assessed with three complementary clustering methods, including model-based population structure, discriminant analysis of principal components (DAPC), and phylogenetic trees. STRUCTURE and DAPC exhibited some consistency in the allocation of accessions into subpopulations or groups, although some discrepancies in their groupings were noted. Hierarchical clustering analysis grouped all the individuals into two major groups, as well as several sub-clusters. We also conducted a network analysis to elucidate genetic relationships among cacao accessions from Sierra Leone and Togo. Analysis of molecular variance (AMOVA) revealed high genetic diversity (86%) within accessions. A high rate of mislabeling/duplicate genotype names was revealed in both countries, which may be attributed to errors from the sources of introduction, labeling errors, and lost labels. This preliminary study demonstrates the use of KASP–SNPs for fingerprinting that can help identify duplicate/mislabeled accessions and provide strong evidence for improving accuracy and efficiency in cacao germplasm management as well as the distribution of correct materials to farmers.

Rapid identification of the predominant azole-resistant genotype in Candida tropicalis.

Candida tropicalis is a leading cause of non-albicans candidemia in tropical/sub-tropical areas and a predominant genotype of azole-resistant C. tropicalis clinical isolates belongs to clade 4. The aim of this study was to reveal markers for rapidly identifying the predominant azole-resistant Candida tropicalis genotype. We analysed XYR1, one of the six genes used in the multilocus sequence typing analysis, and SNQ2, an ATP-binding cassette (ABC) transporter in 281 C. tropicalis, including 120 and 161 from Taiwan and global areas, respectively. Intriguingly, the first 4-mer of codon sequences ATRA of CTRG_05 978 (96/119vs. 21/162, p<0.001, at phi=0. 679) and the SNQ2 A2977G resulting in amino acid I993V alternation (105/118vs.12/163, p<0.001, at phi=0.81) was significantly associated with the clade 4 genotype. The sensitivity and specificity of the clade 4 genotype detection with a combination of SNPs of CTRG_05 978 and SNQ2 were 0.812 and 0.994, respectively, at phi=0.838. Furthermore, we successfully established a TaqMan SNP genotyping assay to identify the clade 4 genotype. Our findings suggest that to improve the management of C. tropicalis infections, rapidly identifying azole-resistant C. tropicalis by detecting SNPs of CTRG_05 978 and SNQ2 is promising.