Genotyping of hundreds of individuals from Kazakh population in Kazakhstan
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE199322 | GEO | 2024/10/04
REPOSITORIES: GEO
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Project description:Introduction:ABO blood group genotyping is a new technology in hematology that helps prevent adverse transfusion reactions in patients. Identification of antigens on the surface of red blood cells is based on serology; however, genotyping employs a different strategy and is aimed directly at genes that determine the surface proteins. ABO blood group genotyping by real-time PCR has several crucial advantages over other PCR-based techniques, such as high rapidity and reliability of analysis. The purpose of this study was to examine nucleotide substitutions differences by blood types using a PCR-based method on Kazakh blood donors. Methods:The study was approved by the Ethics Committee of the National Center for Biotechnology. Venous blood samples from 369 healthy Kazakh blood donors, whose blood types had been determined by serological methods, were collected after obtaining informed consent. The phenotypes of the samples included blood group A (n = 99), B (n = 93), O (n = 132), and AB (n = 45). Genomic DNA was extracted using a salting-out method. PCR products of ABO gene were sequenced on an ABI 3730xl DNA analyzer (Applied Biosystems). The resulting nucleotide sequences were compared and aligned against reference sequence NM_020469.2. Real-time PCR analysis was performed on CFX96 Touch™ Real-Time PCR Detection System (BioRad). Results:Direct sequencing of ABO gene in 369 samples revealed that the vast majority of nucleotide substitutions that change the ABO phenotype were limited to exons 6 and 7 of the ABO gene at positions 261, 467, 657, 796, 803, 930 and 1,060. However, genotyping of only three of them (261, 796 and 803) resulted in identification of major ABO genotypes in the Kazakh population. As a result, TaqMan probe based real-time PCR assay for the specific detection of genotypes 261, 796 and 803 was developed. The assay did not take into account several other mutations that may affect the determination of blood group, because they have a low occurrence rate and therefore have not been found in the population sample. Conclusion:Real-time PCR based method for fast and reliable ABO genotyping was developed. This assay may be used as a complement to classic serological blood typing.
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Project description:Estimating the relationships between individuals is one of the fundamental challenges in many fields. In particular, relationship estimation could provide valuable information for missing persons cases. The recently developed investigative genetic genealogy approach uses high-density single nucleotide polymorphisms (SNPs) to determine close and more distant relationships, in which hundreds of thousands to tens of millions of SNPs are generated either by microarray genotyping or whole-genome sequencing. The current studies usually assume the SNP profiles were generated with minimum errors. However, in the missing person cases, the DNA samples can be highly degraded, and the SNP profiles generated from these samples usually contain lots of errors. In this study, a robust machine learning approach was developed for estimating the relationships with high error SNP profiles. In this approach, a hierarchical classification strategy was employed first to classify the relationships by degree and then the relationship types within each degree separately. As for each classification, feature selection was implemented to gain better performance. Both simulated and real data sets with various genotyping error rates were utilized in evaluating this approach, and the accuracies of this approach were higher than individual measures; namely, this approach was more accurate and robust than the individual measures for SNP profiles with genotyping errors. In addition, the highest accuracy could be obtained by providing the same genotyping error rates in train and test sets, and thus estimating genotyping errors of the SNP profiles is critical to obtaining high accuracy of relationship estimation.
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Project description:ObjectivesKazakhstan is a Central Asian crossroad of European and Asian populations situated along the way of the Great Silk Way. The territory of Kazakhstan has historically been inhabited by nomadic tribes and today is the multi-ethnic country with the dominant Kazakh ethnic group. We sequenced and analyzed the whole-genomes of five ethnic healthy Kazakh individuals with high coverage using next-generation sequencing platform. This whole-genome sequence data of healthy Kazakh individuals can be a valuable reference for biomedical studies investigating disease associations and population-wide genomic studies of ethnically diverse Central Asian region.Data descriptionBlood samples have been collected from five ethnic healthy Kazakh individuals living in Kazakhstan. The genomic DNA was extracted from blood and sequenced. Sequencing was performed on Illumina HiSeq2000 next-generation sequencing platform. We sequenced and analyzed the whole-genomes of ethnic Kazakh individuals with the coverage ranging from 26 to 32X. Ranging from 98.85 to 99.58% base pairs were totally mapped and aligned on the human reference genome GRCh37 hg19. Het/Hom and Ts/Tv ratios for each whole genome ranged from 1.35 to 1.49 and from 2.07 to 2.08, respectively. Sequencing data are available in the National Center for Biotechnology Information SRA database under the accession number PRJNA374772.
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