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.

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.

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.

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.

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.

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.

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.

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.

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.

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.