A case of 46,XX/46,XX chimerism in a phenotypically normal woman.

Chimerism is the presence of two genetically different cell lines within a single organism, which is rarely observed in humans. Usually, chimerism in the human body is revealed by the finding of an abnormal phenotype during a medical examination or is unexpectedly detected in routine genetic analysis. However, the incidence or underlying mechanism of chimerism remains unclear due to the lack of information on this infrequent biological event. A phenotypically normal woman with a 46,XX karyotype and atypical short tandem repeat (STR) allelic patterns observed in DNA analysis was investigated with various genetic testing methods, including STR typing based on capillary electrophoresis and massively parallel sequencing, genome-wide SNP array, and a differentially methylated parental allele assay (DMPA). The proband's parents were not available for testing to discriminate the parental allelic contribution, but the parents' alleles were recovered from testing the proband's siblings. Based on the results consistently found in multiple analyses using STR and single nucleotide polymorphism (SNP) polymorphism markers, dispermic fertilization was suggested as the underlying mechanism. The application of various molecular genetic testing methods was used to elucidate the chimerism observed in the proband in this study. In the future, the development of novel genetic markers or techniques, such as DMPA, may have potential use in the investigation of chimerism.

Conservation priority and run of homozygosity pattern assessment of global chicken genetic resources.

The conservation of genetic resources is becoming increasingly important for the sustainable development of the poultry industry. In the present study, we systematically analyzed the population structure, conservation priority, runs of homozygosity (ROH) of chicken breeds globally, and proposed rational conservation strategies. We used a 600K Affymetrix Axiom HD genotyping SNP array dataset of 2,429 chickens from 134 populations. The chickens were divided into 5 groups based on their country of origin and sampling location: Asian chickens (AS-LOC), African chickens (AF), European local chickens (EU-LOC), Asian breeds sampled in Germany (AS-DE), and European breeds sampled in Germany (EU-DE). The results indicated that the population structure was consistent with the actual geographical distribution of the populations. AS-LOC had the highest positive contribution to the total gene (HT, 1.00%,) and allelic diversity (AT, 0.0014%), the lowest inbreeding degree and the fastest linkage disequilibrium (LD) decay rate; the lowest contribution are derived by European ex situ chicken breeds (EU-DE:HT = -0.072%, AT = -0.0014%), which showed the highest inbreeding and slowest LD decay. Breeds farmed in ex situ (AS-DE, EU-DE) conditions exhibited reduced genetic diversity and increased inbreeding due to small population size. Given limited funds, it is a better choice for government to conserve the breeds with the highest contribution to genetic diversity in each group. Therefore, we evaluated the contribution of each breed to genetic and allelic diversity in 5 groups. Among each group, KUR(AF), BANG(AS-LOC), ALxx(EU-LOC), BHwsch(AS-DE), and ARw(EU-DE) had the highest contribution to gene diversity in the order of the above grouping. Similarly, according to the allelic diversity standard (in the same order), ZIMxx, PIxx, ALxx, SHsch, and ARsch had the highest contribution. After analyzing ROH, we found a total of 144,708 fragments and 27 islands. The gene and genome regions identified by the ROH islands and QTLs indicate that chicken breeds have potential for adaptation to different production systems. Based on these findings, it is recommended to prioritize the conservation of breeds with the highest genetic diversity in each group, while paying more attention to the conservation of Asian and African breeds. Furthermore, providing a valuable reference for the conservation and utilization of chicken.

Improving CNV Detection Performance in Microarray Data Using a Machine Learning-Based Approach.

Copy number variation (CNV) is a primary source of structural variation in the human genome, leading to several disorders. Therefore, analyzing neonatal CNVs is crucial for managing CNV-related chromosomal disabilities. However, genomic waves can hinder accurate CNV analysis. To mitigate the influences of the waves, we adopted a machine learning approach and developed a new method that uses a modified log R ratio instead of the commonly used log R ratio. Validation results using samples with known CNVs demonstrated the superior performance of our method. We analyzed a total of 16,046 Korean newborn samples using the new method and identified CNVs related to 39 genetic disorders were identified in 342 cases. The most frequently detected CNV-related disorder was Joubert syndrome 4. The accuracy of our method was further confirmed by analyzing a subset of the detected results using NGS and comparing them with our results. The utilization of a genome-wide single nucleotide polymorphism array with wave offset was shown to be a powerful method for identifying CNVs in neonatal cases. The accurate screening and the ability to identify various disease susceptibilities offered by our new method could facilitate the identification of CNV-associated chromosomal disease etiologies.

Assessment of the functionality of genome-wide canine SNP arrays and implications for canine disease association studies.

Domestic dogs share a wide range of important disease conditions with humans, including cancers, diabetes and epilepsy. Many of these conditions have similar or identical underlying pathologies to their human counterparts and thus dogs represent physiologically relevant natural models of human disorders. Comparative genomic approaches whereby disease genes can be identified in dog diseases and then mapped onto the human genome are now recognized as a valid method and are increasing in popularity. The majority of dog breeds have been created over the past few hundred years and, as a consequence, the dog genome is characterized by extensive linkage disequilibrium (LD), extending usually from hundreds of kilobases to several megabases within a breed, rather than tens of kilobases observed in the human genome. Genome-wide canine SNP arrays have been developed, and increasing success of using these arrays to map disease loci in dogs is emerging. No equivalent of the human HapMap currently exists for different canine breeds, and the LD structure for such breeds is far less understood than for humans. This study is a dedicated large-scale assessment of the functionalities (LD and SNP tagging performance) of canine genome-wide SNP arrays in multiple domestic dog breeds. We have used genotype data from 18 breeds as well as wolves and coyotes genotyped by the Illumina 22K canine SNP array and Affymetrix 50K canine SNP array. As expected, high tagging performance was observed with most of the breeds using both Illumina and Affymetrix arrays when multi-marker tagging was applied. In contrast, however, large differences in population structure, LD coverage and pairwise tagging performance were found between breeds, suggesting that study designs should be carefully assessed for individual breeds before undertaking genome-wide association studies (GWAS).