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BACKGROUND: Anti-calcitonin gene-related peptide (CGRP) monoclonal antibodies have emerged as promising therapeutic options for the treatment of chronic migraine. However, treatment response varies considerably among individuals, suggesting a potential role for genetic factors. This study aimed to identify genetic variants affecting the efficacy of anti-CGRP monoclonal antibody therapy in chronic migraine among the Han Chinese population in Taiwan to enhance treatment precision and to understand the genetic architecture of migraine. METHODS: We conducted a quantitative trait locus (QTL) association study in patients with chronic migraines from a tertiary medical center in Taiwan using the Taiwan Precision Medicine Array Chip. The patients received fremanezumab or galcanezumab for at least 12 weeks. Treatment efficacy was assessed based on the improvement rate in monthly migraine days. Genetic variants were identified, and their associations with treatment efficacy were examined through quantitative trait loci analysis, linkage disequilibrium studies, and functional annotations using the Gene Ontology database. RESULTS: Six single nucleotide polymorphisms (SNPs) relative variants were significantly associated with anti-CGRP therapy response (p < 1 × 10- 7): rs116870564, rs75244870, rs56216870, rs12938101, rs74655790, and rs149540851. These variants are located in or near genes, including LRRC4C, ATAD2B, and OXR1, which are involved in neuronal development, DNA-dependent ATPase activity, and oxidation-reduction processes, respectively. The rs116870564 variant in LRRC4C showed the strongest association (ß = -0.551, p = 6.65 × 10- 9). The functional impact of these variants is attributed to their regulatory effects on gene expression, which are influenced by intron splicing regulation, transcription factors, and changes in chromatin structure. CONCLUSION: The identification of key genetic markers associated with response to anti-CGRP therapy emphasizes the importance of genetic variability in treatment efficacy. This could lead to more personalized chronic migraine management strategies and tailored therapeutic approaches based on individual genetic profiles. Further research in larger, diverse populations is warranted to validate these findings and refine our understanding of the role of CGRP in chronic migraine pathophysiology. TRIAL REGISTRATION: Not applicable.

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BACKGROUND: Sheep breeds native to the United Kingdom exhibit a striking diversity of different traits. Some of these traits are highly sustainable, such as seasonal wool shedding in the Wiltshire Horn, and are likely to become more important as pressures on sheep production increase in coming decades. Despite their clear importance to the future of sheep farming, the genetic diversity of native UK sheep breeds is poorly characterised. This increases the risk of losing the ability to select for breed-specific traits from native breeds that might be important to the UK sheep sector in the future. Here, we use 50 K genotyping to perform preliminary analysis of breed relationships and genetic diversity within native UK sheep breeds, as a first step towards a comprehensive characterisation. This study generates novel data for thirteen native UK breeds, including six on the UK Breeds at Risk (BAR) list, and utilises existing data from the publicly available Sheep HapMap dataset to investigate population structure, heterozygosity and admixture. RESULTS: In this study the commercial breeds exhibited high levels of admixture, weaker population structure and had higher heterozygosity compared to the other native breeds, which generally tend to be more distinct, less admixed, and have lower genetic diversity and higher kinship coefficients. Some breeds including the Wiltshire Horn, Lincoln Longwool and Ryeland showed very little admixture at all, indicating a high level of breed integrity but potentially low genetic diversity. Population structure and admixture were strongly influenced by sample size and sample provenance - highlighting the need for equal sample sizes, sufficient numbers of individuals per breed, and sampling across multiple flocks. The genetic profiles both within and between breeds were highly complex for UK sheep, reflecting the complexity in the demographic history of these breeds. CONCLUSION: Our results highlight the utility of genotyping data for investigating breed diversity and genetic structure. They also suggest that routine generation of genotyping data would be very useful in informing conservation strategies for rare and declining breeds with small population sizes. We conclude that generating genetic resources for the sheep breeds that are native to the UK will help preserve the considerable genetic diversity represented by these breeds, and safe-guard this diversity as a valuable resource for the UK sheep sector to utilise in the face of future challenges.

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Africa is home to a wide diversity of locally adapted pig breeds whose genetic architecture offers important insights into livestock adaptation to climate change. However, the majority of these inherent traits have not been fully highlighted. This review presents an overview of the current state of African pig genetic resources, providing highlights on their population and production statistics, production system, population diversity indices, and genomic evidence underlying their evolutionary potential. The study results reveal an incomplete characterization of local pig genotypes across the continent. The characterized population, however, demonstrates moderate to high levels of genetic diversity, enough to support breeding and conservation programs. Owing to low genetic differentiation and limited evidence of distinct population structures, it appears that most local pig populations are strains within larger breeds. Genomic evidence has shown a higher number of selection signatures associated with various economically important traits, thus making them potential candidates for climate change adaptation. The reportedly early evidence of hybridization with wild suid groups further suggests untapped insights into disease resistance and resilience traits that need to be illuminated using higher-density markers. Nevertheless, gene introgression from commercial breeds is prevalent across Africa; thus, efforts to realize and utilize these traits must increase before they are permanently depleted.

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OBJECTIVE: This study assesses the accuracy of the IrisPlex system, a genetic eye color prediction tool for forensic analysis, in the Kazakh population. The study compares previously published genotypes of 515 Kazakh individuals from varied geographical and ethnohistorical contexts with phenotypic data on their eye color, introduced for the first time in this research. RESULTS: The IrisPlex panel's effectiveness in predicting eye color in the Kazakh population was validated. It exhibited slightly lower accuracy than in Western European populations but was higher than in Siberian populations. The sensitivity was notably high for brown-eyed individuals (0.99), but further research is needed for blue and intermediate eye colors. This study establishes IrisPlex as a useful predictive tool in the Kazakh population and provides a basis for future investigations into the genetic basis of phenotypic variations in this diverse population.

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Current methodologies of genome-wide single-nucleotide polymorphism (SNP) genotyping produce large amounts of missing data that may affect statistical inference and bias the outcome of experiments. Genotype imputation is routinely used in well-studied species to buffer the impact in downstream analysis, and several algorithms are available to fill in missing genotypes. The lack of reference haplotype panels precludes the use of these methods in genomic studies on non-model organisms. As an alternative, machine learning algorithms are employed to explore the genotype data and to estimate the missing genotypes. Here, we propose an imputation method based on self-organizing maps (SOM), a widely used neural networks formed by spatially distributed neurons that cluster similar inputs into close neurons. The method explores genotype datasets to select SNP loci to build binary vectors from the genotypes, and initializes and trains neural networks for each query missing SNP genotype. The SOM-derived clustering is then used to impute the best genotype. To automate the imputation process, we have implemented gtImputation, an open-source application programmed in Python3 and with a user-friendly GUI to facilitate the whole process. The method performance was validated by comparing its accuracy, precision and sensitivity on several benchmark genotype datasets with other available imputation algorithms. Our approach produced highly accurate and precise genotype imputations even for SNPs with alleles at low frequency and outperformed other algorithms, especially for datasets from mixed populations with unrelated individuals.

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Deafness in vertebrates is associated with variants of hundreds of genes. Yet, many mutant genes causing rare forms of deafness remain to be discovered. A consanguineous Pakistani family segregating nonsyndromic deafness in two sibships were studied using microarrays and exome sequencing. A 1.2 Mb locus (DFNB128) on chromosome 5q11.2 encompassing six genes was identified. In one of the two sibships of this family, a novel homozygous recessive variant NM_005921.2:c.4460G>A p.(Arg1487His) in the kinase domain of MAP3K1 co-segregated with nonsyndromic deafness. There are two previously reported Map3k1-kinase-deficient mouse models that are associated with recessively inherited syndromic deafness. MAP3K1 phosphorylates serine and threonine and functions in a signaling pathway where pathogenic variants of HGF, MET, and GAB1 were previously reported to be associated with human deafness DFNB39, DFNB97, and DFNB26, respectively. Our single-cell transcriptome data of mouse cochlea mRNA show expression of Map3k1 and its signaling partners in several inner ear cell types suggesting a requirement of wild-type MAP3K1 for normal hearing. In contrast to dominant variants of MAP3K1 associated with Disorders of Sex Development 46,XY sex-reversal, our computational modeling of the recessive substitution p.(Arg1487His) predicts a subtle structural alteration in MAP3K1, consistent with the limited phenotype of nonsyndromic deafness.

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Soil-transmitted helminth (STH) infections, commonly treated with benzimidazoles, are linked to resistance through single nucleotide polymorphisms (SNPs) at position 167, 198, or 200 in the ß-tubulin isotype 1 gene. The aim of this study was to establish a novel genotyping assay characterized by its rapidity and specificity. This assay was designed to detect the presence of SNPs within the partial ß-tubulin gene of Trichuris trichiura. This was achieved through the biallelic discrimination at codons 167, 198, and 200 by employing the competitive binding of two allele-specific forward primers. The specificity and reliability of this assay were subsequently confirmed using Trichuris samples isolated from captive primates. Furthermore, a molecular study was conducted to substantiate the utility of the ß-tubulin gene as a molecular marker. The assays showed high sensitivity and specificity when applied to field samples. Nevertheless, none of the SNPs within the ß-tubulin gene were detected in any of the adult worms or eggs from the analyzed populations. All specimens consistently displayed an SS genotype. The examination of the ß-tubulin gene further validated the established close relationships between the T. trichiura clade and Trichuris suis clade. This reaffirms its utility as a marker for phylogenetic analysis.

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Heartworm disease caused by the nematode Dirofilaria immitis is one of the most important parasitoses of dogs. The treatment of the infection is long, complicated, risky and expensive. Conversely, prevention is easy, safe, and effective and it is achieved by the administration of macrocyclic lactones (MLs). In recent years, D. immitis strains resistant to MLs have been described in Southern USA, raising concerns for possible emergence, or spreading in other areas of the world. The present study describes the first case of ML-resistant D. immitis in a dog in Europe. The dog arrived in Rome, Italy, from USA in 2023. Less than 6 months after its arrival in Italy, the dog tested positive for D. immitis circulating antigen and microfilariae, despite it having received monthly the ML milbemycin oxime (plus an isoxazoline) after arrival. The microfilariae suppression test suggested a resistant strain. Microfilariae DNA was examined by droplet digital PCR-based duplex assays targeting four marker positions at single nucleotide polymorphisms (SNP1, SNP2, SNP3, SNP7) which differentiate resistant from susceptible isolates. The genetic analysis showed that microfilariae had a ML-resistant genotype at SNP1 and SNP7 positions, compatible with a resistant strain. It is unlikely that the dog acquired the infection after its arrival in Europe, while it is biologically and epidemiologically plausible that the dog was already infected when imported from USA to Europe. The present report highlights the realistic risk of ML-resistant D. immitis strains being imported and possibly transmitted in Europe and other areas of the world. Monitoring dogs travelling from one area to another, especially if they originate from regions where ML-resistance is well-documented, is imperative. Scientists, practitioners, and pet owners should be aware of the risk and remain vigilant against ML-resistance, in order to monitor and reduce the spreading of resistant D. immitis.

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Variable Fragment Length Allele-Specific Polymerase Chain Reaction (VFLASP) and Amplification Refractory Mutation System (ARMS) are reliable methods for detecting allelic variations resulting from single base changes within the genome. Due to their widespread application, allele variations caused by Single Nucleotide Polymorphisms (SNPs) can be readily detected using allele-specific primers. In the context of the current study, VFLASP was combined with ARMS method as a novel strategy to enhance the efficacy of both techniques. Clinically important base variations within SNP regions used in the study were detected by a fragment analysis method. To validate the accuracy of the developed VFLASP-ARMS method, specifically designed synthetic sequences were tested using a capillary electrophoresis system. Allele-specific primers exhibit differences solely at the 3' end based on the sequence of the SNP. Additionally, to increase the specificity of the primers, a base was intentionally added for incompatibility. Therefore, allele discrimination on fragment analysis has been made possible through the 3-6 bp differences in the amplicons. With the optimization of the system, designed synthetic sequences provided reliable and reproducible results in wild-type, heterozygous, and homozygous genotypes using the VFLASP-ARMS method. Hence, our results demonstrated that VFLASP-ARMS method, offers a novel design methodology that can be included in the content of SNP genotyping assays.

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Single Nucleotide Polymorphisms (SNPs), as the most prevalent type of variation in the human genome, play a pivotal role in influencing human traits. They are extensively utilized in diverse fields such as population genetics, forensic science, and genetic medicine. This study focuses on the 'Rita' BeadChip, a custom SNP microarray panel developed using Illumina Infinium HTS technology. Designed for high-throughput genotyping, the panel facilitates the analysis of over 4000 markers efficiently and cost-effectively. After careful clustering performed on a set of 1000 samples, an evaluation of the Rita panel was undertaken, assessing its sensitivity, repeatability, reproducibility, precision, accuracy, and resistance to contamination. The panel's performance was evaluated in various scenarios, including sex estimation and parental relationship assessment, using GenomeStudio data analysis software. Findings show that over 95 % of the custom BeadChip assay markers were successful, with better performance of transitions over other mutations, and a considerably lower success rate for Y chromosome loci. An exceptional call rate exceeding 99 % was demonstrated for control samples, even with DNA input as low as 0.781 ng. Call rates above 80 % were still obtained with DNA quantities under 0.1 ng, indicating high sensitivity and suitability for forensic applications where DNA quantity is often limited. Repeatability, reproducibility, and precision studies revealed consistency of the panel's performance across different batches and operators, with no significant deviations in call rates or genotyping results. Accuracy assessments, involving comparison with multiple available genetic databases, including the 1000 Genome Project and HapMap, denoted over 99 % concordance, establishing the Rita panel's reliability in genotyping. The contamination study revealed insights into background noise and allowed the definition of thresholds for sample quality evaluation. Multiple metrics for differentiating between negative controls and true samples were highlighted, increasing the reliability of the obtained results. The sex estimation tool in GenomeStudio proved highly effective, correctly assigning sex in all samples with autosomal loci call rates above 97 %. The parental relationship assessment of family trios highlighted the utility of GenomeStudio in identifying genotyping errors or potential Mendelian inconsistencies, promoting the application of arrays such as Rita in kinship testing. Overall, this evaluation confirms the Rita microarray as a robust, high-throughput genotyping tool, underscoring its potential in genetic research and forensic applications. With its custom content and adaptable design, it not only meets current genotyping demands but also opens avenues for further research and application expansion in the field of genetic analysis.

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Wolves are assumed to be ungulate obligates, however, a recently described pack on Pleasant Island, Alaska USA, is persisting on sea otters and other marine resources without ungulate prey, violating this long-held assumption. We address questions about these wolves regarding their origin and fate, degree of isolation, risk of inbreeding depression, and diet specialization by individual and sex. We applied DNA metabarcoding and genotyping by amplicon sequencing using 957 scats collected from 2016 to 2022, and reduced representation sequencing of tissue samples to establish a detailed understanding of Pleasant Island wolf ecology and compare them with adjacent mainland wolves. Dietary overlap was higher among individual wolves on Pleasant Island (Pianka's index mean 0.95 ± 0.03) compared to mainland wolves (0.70 ± 0.21). The individual diets of island wolves were dominated by sea otter, ranging from 40.6% to 63.2% weighted percent of occurrence (wPOO) (mean 55.5 ± 8.7). In contrast, individual mainland wolves primarily fed on ungulates (42.2 ± 21.3) or voles during a population outbreak (31.2 ± 23.2). We traced the origin of the Pleasant Island pack to a mainland pair that colonized around 2013 and produced several litters. After this breeding pair was killed, their female offspring and an immigrant male became the new breeders in 2019. We detected 20 individuals of which 8 (40%) were trapped and killed while two died of natural causes during the 6-year study. Except for the new breeding male, the pedigree analysis and genotype results showed no additional movement to or from the island, indicating limited dispersal but no evidence of inbreeding. Our findings suggest wolves exhibit more flexible foraging behavior than previously believed, and hunting strategies can substantially differ between individuals within or between packs. Nevertheless, anthropogenic and natural mortality combined with limited connectivity to the mainland may inhibit the continued persistence of Pleasant Island wolves.

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Improving the seed protein concentration (SPC) of pea (Pisum sativum L.) has turned into an important breeding objective because of the consumer demand for plant-based protein and demand from protein fractionation industries. To support the marker-assisted selection (MAS) of SPC towards accelerated breeding of improved cultivars, we have explored two diverse recombinant inbred line (RIL) populations to identify the quantitative trait loci (QTLs) associated with SPC. The two RIL populations, MP 1918 × P0540-91 (PR-30) and Ballet × Cameor (PR-31), were derived from crosses between moderate SPC × high SPC accessions. A total of 166 and 159 RILs of PR-30 and PR-31, respectively, were genotyped using an Axiom® 90K SNP array and 13.2K SNP arrays, respectively. The RILs were phenotyped in replicated trials in two and three locations of Saskatchewan, Canada in 2020 and 2021, respectively, for agronomic assessment and SPC. Using composite interval mapping, we identified three QTLs associated with SPC in PR-30 and five QTLs in PR-31, with the LOD value ranging from 3.0 to 11.0. A majority of these QTLs were unique to these populations compared to the previously known QTLs for SPC. The QTL SPC-Ps-5.1 overlapped with the earlier reported SPC associated QTL PC-QTL-3. Three QTLs, SPC-Ps-4.2, SPC-Ps-5.1, and SPC-Ps-7.2 with LOD scores of 7.2, 7.9, and 11.3, and which explained 14.5%, 11.6%, and 11.3% of the phenotypic variance, respectively, can be used for marker-assisted breeding to increase SPC in peas. Eight QTLs associated with the grain yield were identified with LOD scores ranging from 3.1 to 8.2. Two sets of QTLs, SPC-Ps-2.1 and GY-Ps-2.1, and SPC-Ps-5.1 and GY-Ps-5.3, shared the QTL/peak regions. Each set of QTLs contributed to either SPC or grain yield depending on which parent the QTL region is derived from, thus confirming that breeding for SPC should take into consideration the effects on grain yield.

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OBJECTIVE: Data from DNA genotyping via a 96-SNP panel in a study of 25,015 clinical samples were utilized for quality control and tracking of sample identity in a clinical sequencing network. The study aimed to demonstrate the value of both the precise SNP tracking and the utility of the panel for predicting the sex-by-genotype of the participants, to identify possible sample mix-ups. RESULTS: Precise SNP tracking showed no sample swap errors within the clinical testing laboratories. In contrast, when comparing predicted sex-by-genotype to the provided sex on the test requisition, we identified 110 inconsistencies from 25,015 clinical samples (0.44%), that had occurred during sample collection or accessioning. The genetic sex predictions were confirmed using additional SNP sites in the sequencing data or high-density genotyping arrays. It was determined that discrepancies resulted from clerical errors (49.09%), samples from transgender participants (3.64%) and stem cell or bone marrow transplant patients (7.27%) along with undetermined sample mix-ups (40%) for which sample swaps occurred prior to arrival at genome centers, however the exact cause of the events at the sampling sites resulting in the mix-ups were not able to be determined.

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Schizophrenia is a complex condition with entwined genetic and epigenetic risk factors, posing a challenge to disentangle the intermixed pathological and therapeutic epigenetic signatures. To resolve this, we performed 850K methylome-wide and 700K genome-wide studies on the same set of schizophrenia patients by stratifying them into responders, non-responders, and drug-naïve patients. The key genes that signified the response were followed up using real-time gene expression studies to understand the effect of antipsychotics at the gene transcription level. The study primarily implicates hypermethylation in therapeutic response and hypomethylation in the drug-non-responsive state. Several differentially methylated sites and regions colocalized with the schizophrenia genome-wide association study (GWAS) risk genes and variants, supporting the convoluted gene-environment association. Gene ontology and protein-protein interaction (PPI) network analyses revealed distinct patterns that differentiated the treatment response from drug resistance. The study highlights the strong involvement of several processes related to nervous system development, cell adhesion, and signaling in the antipsychotic response. The ability of antipsychotic medications to alter the pathology by modulating gene expression or methylation patterns is evident from the general increase in the gene expression of response markers and histone modifiers and the decrease in class II human leukocyte antigen (HLA) genes following treatment with varying concentrations of medications like clozapine, olanzapine, risperidone, and haloperidol. The study indicates a directional overlap of methylation markers between pathogenesis and therapeutic response, thereby suggesting a careful distinction of methylation markers of pathogenesis from treatment response. In addition, there is a need to understand the trade-off between genetic and epigenetic observations. It is suggested that methylomic changes brought about by drugs need careful evaluation for their positive effects on pathogenesis, course of disease progression, symptom severity, side effects, and refractoriness.

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OBJECTIVES: The collection of genotype data was conducted as an essential part of a pivotal research project with the goal of examining the genetic variability of skin, hair, and iris color among the Kazakh population. The data has practical application in the field of forensic DNA phenotyping (FDA). Due to the limited size of forensic databases from Central Asia (Kazakhstan), it is practically impossible to obtain an individual identification result based on forensic profiling of short tandem repeats (STRs). However, the pervasive use of the FDA necessitates validation of the currently employed set of genetic markers in a variety of global populations. No such data existed for the Kazakhs. The Phenotype Expert kit (DNA Research Center, LLC, Russia) was used for the first time in this study to collect data. DATA DESCRIPTION: The present study provides genotype data for a total of 60 SNP genetic markers, which were analyzed in a sample of 515 ethnic Kazakhs. The dataset comprises a total of 41 single nucleotide polymorphisms (SNPs) obtained from the HIrisPlex-S panel. Additionally, there are 4 SNPs specifically related to the AB0 gene, 1 marker associated with the AMELX/Y genes, and 14 SNPs corresponding to the primary haplogroups of the Y chromosome. The aforementioned data could prove valuable to researchers with an interest in investigating genetic variability and making predictions about phenotype based on eye color, hair color, skin color, AB0 blood group, gender, and biogeographic origin within the male lineage.

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Genetic assessment of highly incinerated and/or degraded human skeletal material is a persistent challenge in forensic DNA analysis, including identifying victims of mass disasters. Few studies have investigated the impact of thermal degradation on whole-genome single-nucleotide polymorphism (SNP) quality and quantity using next-generation sequencing (NGS). We present whole-genome SNP data obtained from the bones and teeth of 27 fire victims using two DNA extraction techniques. Extracts were converted to double-stranded DNA libraries then enriched for whole-genome SNPs using unpublished biotinylated RNA baits and sequenced on an Illumina NextSeq 550 platform. Raw reads were processed using the EAGER (Efficient Ancient Genome Reconstruction) pipeline, and the SNPs filtered and called using FreeBayes and GATK (v. 3.8). Mixed-effects modeling of the data suggest that SNP variability and preservation is predominantly determined by skeletal element and burn category, and not by extraction type. Whole-genome SNP data suggest that selecting long bones, hand and foot bones, and teeth subjected to temperatures <350°C are the most likely sources for higher genomic DNA yields. Furthermore, we observed an inverse correlation between the number of captured SNPs and the extent to which samples were burned, as well as a significant decrease in the total number of SNPs measured for samples subjected to temperatures >350°C. Our data complement previous analyses of burned human remains that compare extraction methods for downstream forensic applications and support the idea of adopting a modified Dabney extraction technique when traditional forensic methods fail to produce DNA yields sufficient for genetic identification.

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Breast cancer is a global health problem. It is an age-dependent disease, but cases of early-onset breast cancer (eBC) are gradually increasing. There are many unresolved questions regarding eBC risk factors, mechanisms of development and screening. Only 10% of eBC cases are due to mutations in the BRCA1/BRCA2 genes, and 90% have a more complex genetic background. This poses a significant challenge to timely cancer detection in young women and highlights the need for research and awareness. Therefore, identifying genetic risk factors for eBC is essential to solving these problems. This study represents an association analysis of 144 eBC cases and 163 control participants to identify genetic markers associated with eBC risks in Kazakh women. We performed a two-stage approach in association analysis to assess genetic predisposition to eBC. First-stage genome-wide association analysis revealed two risk intronic loci in the CHI3L2 gene (p = 5.2 × 10-6) and MGAT5 gene (p = 8.4 × 10-6). Second-stage exonic polymorphisms haplotype analysis showed significant risks for seven haplotypes (p < 9.4 × 10-4). These results point to the importance of studying medium- and low-penetrant genetic markers in their haplotype combinations for a detailed understanding of the role of detected genetic markers in eBC development and prediction.

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Biological samples are important resources for scientific research. These samples are stored in biobanks over years until needed, and some of them can never be retrieved if they are improperly stored, causing them to be wasted. Thus, they are priceless, and they should be used correctly and effectively. Sample quality substantially affects biomedical research results. However, sample misidentification or mix-up is common. It is necessary to establish quality standards for sample identification. In this study, we used the Advanta Sample ID genotyping panel to detect homology identification and cross-contamination. We compared the single-nucleotide polymorphism (SNP) typing results of two different samples and calculated the similarity score of homologous sample pairs and nonhomologous sample pairs. Through analysis, we obtained a similarity score cutoff point of 0.8620, which was an effective way to distinguish homology and nonhomology. Cross-contamination was detected in two sets of mixtures (STD8:STD6 and jj3:1-P) mixed at a series of special ratios. Sensitivity was dependent on the sample characteristics and mixing ratios. Finally, we assessed the effect of sample degradation degree on SNP genotyping and found that degraded samples with a minimal DNA integrity number of 1.9 had complete genotyping results. On the whole, this study shows that the Sample ID panel is reliable for homology identification and cross-contamination analysis. Moreover, this technology has promising further applications in biological sample quality control.

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Background: Sugarcane (Saccharum spp.) is an economically significant crop for both the sugar and biofuel industries. Breeding sugarcane cultivars with high-performance agronomic traits is the most effective approach for meeting the rising demand for sugar and biofuels. Molecular markers associated with relevant agronomic traits could drastically reduce the time and resources required to develop new sugarcane varieties. Previous sugarcane candidate gene association analyses have found single nucleotide polymorphism (SNP) markers associated with sugar-related traits. This study aims to validate these associated SNP markers of six genes, including Lesion simulating disease 1 (LSD), Calreticulin (CALR), Sucrose synthase 1 (SUS1), DEAD-box ATP-dependent RNA helicase (RH), KANADI1 (KAN1), and Sodium/hydrogen exchanger 7 (NHX7), in a diverse population in 2-year and two-location evaluations. Methods: After genotyping of seven targeted SNP markers was performed by PCR Allelic Competitive Extension (PACE) SNP genotyping, the association with sugar-related traits and important cane yield component traits was determined on a set of 159 sugarcane genotypes. The marker-trait relationships were validated and identified by both t-test analysis and an association analysis based on the general linear model. Results: The mSoSUS1_SNPCh10.T/C and mSoKAN1_SNPCh7.T/C markers that were designed from the SUS1 and KAN1 genes, respectively, showed significant associations with different amounts of sugar-related traits and yield components. The mSoSUS1_SNPCh10.T/C marker was found to have more significant association with sugar-related traits, including pol, CCS, brix, fiber and sugar yield, with p values of 6.08 × 10-6 to 4.35 × 10-2, as well as some cane yield component traits with p values of 1.61 × 10-4 to 3.35 × 10-2. The significant association is consistent across four environments. Conclusion: Sucrose synthase (SUS) is considered a crucial enzyme involved in sucrose metabolism. This marker is a high potential functional marker that may be used in sugarcane breeding programs to select superior sugarcane with good fiber and high sugar contents.

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Rapid and accurate identification of Anthonomus grandis subspecies is crucial for effective management and eradication. Current diagnostic methods have limitations in terms of time to diagnosis (up to seven days) and can yield ambiguous results. Here, we present the validation of a custom TaqMan SNP Genotyping Assay for the rapid and accurate identification of A. grandis grandis (boll weevil) and A. g. thurberiae (thurberia weevil) subspecies. To validate the assay, we conducted three main experiments: (1) a sensitivity test to determine the DNA concentration range at which the assay performs, (2) a non-target specificity test to ensure no amplification in non-target weevils (false positives), and (3) an accuracy test comparing the results of the new assay to previously established methods. These experiments were carried out in parallel at three independent facilities to confirm the robustness of the assay to variations in equipment and personnel. We used DNA samples from various sources, including field-collected specimens, museum specimens, and previously isolated DNA. The assay demonstrated high sensitivity (PCR success with ≥0.05 ng/µL DNA template), specificity (0.02 false positive rate), and accuracy (97.7%) in diagnosing boll weevil and thurberia weevil subspecies. The entire workflow, including DNA extraction, assay preparation, PCR run time, and data analysis, can be completed within a single workday (7-9 h) by a single technician. The deployment of this assay as a diagnostic tool could benefit boll weevil management and eradication programs by enabling same-day diagnosis of trap-captured or intercepted weevil specimens. Furthermore, it offers a more reliable method for identifying unknown specimens, contributing to the overall effectiveness of boll weevil research and control efforts.