Project description:Esophageal squamous cell carcinoma (ESCC) is characterized as a metabolic disorder characterized by lipid metabolic reprogramming. To investigate the regional characteristics of ESCC patients in Xinjiang Province, China, and lipid metabolism, in this study, we described the characteristics of the serum lipid composition in Kazakh ESCC patients by performing an integrated analysis of the transcriptome and lipidomic data. Serum samples from 30 Kazakh ESCC patients and 30 healthy individuals were subjected to targeted lipid metabolomics analysis via UPLC‒MS/MS, while 3 tumor samples and matched adjacent normal tissues from 30 ESCC patients were subjected to transcriptome analysis. Compared with those in the healthy group, we observed obvious changes in the serum lipid subclass content, chain length and unsaturation in the ESCC patients. Integrated lipidomic and transcriptomic analyses revealed that unsaturated fatty acid biosynthesis, fatty acid metabolism, lipid degradation, cholesterol metabolism and the AMPK signaling pathway were enriched in tumor tissues. In addition, RT–qPCR results demonstrated that genes closely related to these pathways were differentially expressed between the ESCC group and the healthy control group. Considering the key role of AMPK in lipid metabolism, we conducted a targeted lipid metabolomics analysis on AMPK-knockdown esophageal cancer cells by UPLC‒MS/MS. These findings suggested that AMPK might be correlated with lipid metabolism in Kazakh ESCC patients, identifying potential therapeutic targets of AMPK and other lipid metabolism-related markers against the progression of ESCC.
Project description:Investigate long non-coding RNA (lncRNA) expression characteristics in the peripheral blood lymphocytes of Xinjiang Kazakh people with essential hypertension.
Project description:Kazakhstan, the ninth-largest country in the world, is located along the Great Silk Road and connects Europe with Asia. Historically, its territory has been inhabited by nomadic tribes, and modern-day Kazakhstan is a multiethnic country with a dominant Kazakh population. We sequenced and analyzed the genomes of five ethnic Kazakhs at high coverage using the Illumina HiSeq2000 next-generation sequencing platform. The five Kazakhs yielded a total number of base pairs ranging from 87,308,581,400 to 107,526,741,301. On average, 99.06% were properly mapped. Based on the Het/Hom and Ti/Tv ratios, the quality of the genomic data ranged from 1.35 to 1.49 and from 2.07 to 2.08, respectively. Genetic variants were identified and annotated. Functional analysis of the genetic variants identified several variants that were associated with higher risks of metabolic and neurogenerative diseases. The present study showed high levels of genetic admixture of Kazakhs that were comparable to those of other Central Asians. These whole-genome sequence data of healthy Kazakhs could contribute significantly to biomedical studies of common diseases as their findings could allow better insight into the genotype-phenotype relations at the population level.
Project description:The Asian Central Steppe, consisting of current-day Kazakhstan and Russia, has acted as a highway for major migrations throughout history. Therefore, describing the genetic composition of past populations in Central Asia holds value to understanding human mobility in this pivotal region. In this study, we analyse paleogenomic data generated from five humans from Kuygenzhar, Kazakhstan. These individuals date to the early to mid-18th century, shortly after the Kazakh Khanate was founded, a union of nomadic tribes of Mongol Golden Horde and Turkic origins. Genomic analysis identifies that these individuals are admixed with varying proportions of East Asian ancestry, indicating a recent admixture event from East Asia. The high amounts of DNA from the anaerobic Gram-negative bacteria Tannerella forsythia, a periodontal pathogen, recovered from their teeth suggest they may have suffered from periodontitis disease. Genomic analysis of this bacterium identified recently evolved virulence and glycosylation genes including the presence of antibiotic resistance genes predating the antibiotic era. This study provides an integrated analysis of individuals with a diet mostly based on meat (mainly horse and lamb), milk, and dairy products and their oral microbiome.
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.
Project description:Whole-genome sequencing on PacBio of laboratory mouse strains. See http://www.sanger.ac.uk/resources/mouse/genomes/ for more details. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/