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Population admixture results in the combinations of genetic components derived from distinct ancestral populations, which may impact diversity at the genetic, transcriptomic, and phenotypic levels, as well as postadmixture adaptive evolution. Here, we systematically investigated the genomic and transcriptomic diversity in Kazaks, Uyghurs, and Huis-three admixed populations of various Eurasian ancestries living in Xinjiang, China. All three populations showed elevated genetic diversity and closer genetic distance compared with the reference populations across the Eurasian continent. However, we also observed differentiated genomic diversity and inferred different demographic histories among the three populations. Varying ancestry proportions observed in both the global and local aspects corresponded to the population-differentiated genomic diversity, with the most representative signals observed in the genes EDAR, SULT1C4, and SLC24A5. The varying local ancestry partly resulted from the postadmixture local adaptation, with the most significant signals observed in immunity- and metabolism-related pathways. Admixture-shaped genomic diversity further influenced the transcriptomic diversity in the admixed populations; in particular, population-specific regulatory effects were associated with immunity- and metabolism-involved genes such as MTHFR, FCER1G, SDHC, and BDH2. Furthermore, differentially expressed genes between the populations were identified, many of which could be explained by the population-specific regulatory properties, including genes related to health concerns (e.g., AHI1 between Kazak and Uyghurs [P < 6.92 × 10-5] and CTRC between Huis and Uyghurs [P < 2.32 × 10-4]). Our results demonstrate genetic admixture as a driving force in shaping the genomic and transcriptomic diversity of human populations.
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Genética de Población , Transcriptoma , Humanos , Genómica , Hidroxibutirato Deshidrogenasa/genética , Polimorfismo de Nucleótido SimpleRESUMEN
Transcriptomic diversity across human populations reflects differential regulatory mechanisms. Allelic-imbalanced gene expression is a genetic regulatory mechanism that contributes to human phenotypic variation. To systematically investigate genome-wide allele-specific expression (ASE), we analyzed RNA-Seq data from European and African populations provided by the Geuvadis project. We identified 11 sites in 8 genes showing ASE in both Europeans and Africans, and 9 sites in 9 genes showing population-specific ASE, including both novel and known ASE signals. Notably, the top signal of differentiated ASE between inter-continental populations was observed in DNAJC15, of which the derived allele of rs12015, a single nucleotide polymorphism (SNP), showed significantly higher expression than did the ancestral allele specifically in European individuals. We identified a unique haplotype of DNAJC15, where a few SNPs highly differentiated between European and African populations were strongly linked to sites with high ASE. Among these, SNP rs17553284 affected the binding of several transcription factors as well as the genotype-dependent expression of DNAJC15. Therefore, we speculated that rs17553284 could be a regulatory causal variant that mediates the ASE of rs12015. We found several variations in ASE between intercontinental populations. The highly differentiated ASE genes identified here may implicate in the phenotypic variations among populations that are both evolutionarily and medically important.
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Población Negra/genética , Frecuencia de los Genes , Población Blanca/genética , Regulación de la Expresión Génica , Variación Genética , Estudio de Asociación del Genoma Completo/métodos , Proteínas del Choque Térmico HSP40/genética , Haplotipos , Humanos , Polimorfismo de Nucleótido Simple , Sitios de Carácter Cuantitativo , Análisis de Secuencia de ARN/métodos , TranscriptomaRESUMEN
The Uyghur people residing in Xinjiang, a territory located in the far west of China and crossed by the Silk Road, are a key ethnic group for understanding the history of human dispersion in Eurasia. Here we assessed the genetic structure and ancestry of 951 Xinjiang's Uyghurs (XJU) representing 14 geographical subpopulations. We observed a southwest and northeast differentiation within XJU, which was likely shaped jointly by the Tianshan Mountains, which traverses from east to west as a natural barrier, and gene flow from both east and west directions. In XJU, we identified four major ancestral components that were potentially derived from two earlier admixed groups: one from the West, harboring European (25-37%) and South Asian ancestries (12-20%), and the other from the East, with Siberian (15-17%) and East Asian (29-47%) ancestries. By using a newly developed method, MultiWaver, the complex admixture history of XJU was modeled as a two-wave admixture. An ancient wave was dated back to â¼3,750 years ago (ya), which is much earlier than that estimated by previous studies, but fits within the range of dating of mummies that exhibited European features that were discovered in the Tarim basin, which is situated in southern Xinjiang (4,000-2,000 ya); a more recent wave occurred around 750 ya, which is in agreement with the estimate from a recent study using other methods. We unveiled a more complex scenario of ancestral origins and admixture history in XJU than previously reported, which further suggests Bronze Age massive migrations in Eurasia and East-West contacts across the Silk Road.
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Pueblo Asiatico/genética , Etnicidad/genética , Genética de Población/métodos , China/etnología , Flujo Génico , Geografía , Haplotipos/genética , Humanos , Filogeografía , Polimorfismo de Nucleótido Simple/genética , Población Blanca/genéticaRESUMEN
Background: Recent research has shown that lysosomes play a critical role in the onset and progression of malignancy by regulating tumor cell death through several mechanisms. Nevertheless, the involvement of lysosome-associated genes (LSAGs) in lung adenocarcinoma (LUAD) is still not well understood. Methods: LSAGs were identified in malignant lung epithelial cells, as well as biologically and functionally annotated by the comprehensive integration of single-cell and bulk RNA-sequencing data. Prognostic characterization of LSAGs was established, of which the accuracy and reliability were assessed by one-way Cox and LASSO regression. Correlations between LSAG properties and immune cell infiltration, chemotherapy, and immunotherapy were analyzed by integrated omics data. Finally, we characterized the expression of three LSAGs (KCNE1, NPC2, and SFTPD) in malignant lung epithelium and assessed their impact on tumor malignancy related phenotypes. Results: We identified 18 LSAGs associated with prognosis, of which 3 LSAGs were used to construct prognostic models. High-risk patients had worse survival and the model predicted it better than other clinical indicators. Based on the functional enrichment analyses, LSAGs were associated with binding and molecular activity functions, inhibition of DNA damage repair and tumor growth, IL7 signaling pathway, and glycolysis. M0 macrophages and M1 macrophages were substantially enriched in high-risk patients. Conversely, there was a considerable enrichment of resting dendritic cells and M2 macrophages in patients at low risk. We also found that risk scores predicted the outcome of immunotherapy. In vitro, we found that KCNE1, NPC2, and SFTPD were lowly expressed in malignant epithelial cells and patients with low expression of KCNE1, NPC2, and SFTPD had a higher percentage of M2 macrophage infiltration. Overexpression of KCNE1, NPC2, and SFTPD suppressed the proliferation and invasion of malignant cells, and M0 macrophages remarkably reduced M2 macrophage polarization and cellular secretion of pro-tumor cytokines. Conclusions: We used three LASGs-KCNE1, NPC2, and SFTPD-to develop and validate a predictive signature for LUAD patients. Furthermore, we found that low expression of KCNE1, NPC2, and SFTPD promotes lung cancer cell proliferation and invasion and M2 macrophage polarization. Our study may provide fresh perspectives for customized immunotherapy.
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Research on brain expression quantitative trait loci (eQTLs) has illuminated the genetic underpinnings of schizophrenia (SCZ). Yet, the majority of these studies have been centered on European populations, leading to a constrained understanding of population diversities and disease risks. To address this gap, we examined genotype and RNA-seq data from African Americans (AA, n=158), Europeans (EUR, n=408), and East Asians (EAS, n=217). When comparing eQTLs between EUR and non-EUR populations, we observed concordant patterns of genetic regulatory effect, particularly in terms of the effect sizes of the eQTLs. However, 343,737 cis-eQTLs (representing â¼17% of all eQTLs pairs) linked to 1,276 genes (about 10% of all eGenes) and 198,769 SNPs (approximately 16% of all eSNPs) were identified only in the non-EUR populations. Over 90% of observed population differences in eQTLs could be traced back to differences in allele frequency. Furthermore, 35% of these eQTLs were notably rare (MAF < 0.05) in the EUR population. Integrating brain eQTLs with SCZ signals from diverse populations, we observed a higher disease heritability enrichment of brain eQTLs in matched populations compared to mismatched ones. Prioritization analysis identified seven new risk genes ( SFXN2 , RP11-282018.3 , CYP17A1 , VPS37B , DENR , FTCDNL1 , and NT5DC2 ), and three potential novel regulatory variants in known risk genes ( CNNM2 , C12orf65 , and MPHOSPH9 ) that were missed in the EUR dataset. Our findings underscore that increasing genetic ancestral diversity is more efficient for power improvement than merely increasing the sample size within single-ancestry eQTLs datasets. Such a strategy will not only improve our understanding of the biological underpinnings of population structures but also pave the way for the identification of novel risk genes in SCZ.
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It remains unknown and debatable how European-Asian-differentiated alleles affect individual phenotypes. Here, we made the first effort to analyze the expression profiles of highly differentiated genes with eastern and western origins in 90 Uyghurs using whole-genome (30× to 60×) and transcriptome data. We screened 921 872 east-west highly differentiated genetic variants, of which â¼4.32% were expression quantitative trait loci (eQTLs), â¼0.12% were alternative splicing quantitative trait loci (sQTLs), and â¼0.12% showed allele-specific expression (ASE). The 8305 highly differentiated eQTLs of strong effects appear to have undergone natural selection, associated with immunity and metabolism. European-origin alleles tend to be more biasedly expressed; highly differentiated ASEs were enriched in diabetes-associated genes, likely affecting the diabetes susceptibility in the Uyghurs. We proposed an admixture-induced expression model to dissect the highly differentiated expression profiles. We provide new insights into the genetic basis of phenotypic differentiation between Western and Eastern populations, advancing our understanding of the impact of genetic admixture.
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Population admixture results in genome-wide combinations of genetic variants derived from different ancestral populations of distinct ancestry, thus providing a unique opportunity for understanding the genetic determinants of phenotypic variation in humans. Here, we used whole-genome sequencing of 92 individuals with high coverage (30-60×) to systematically investigate genomic diversity in the Uyghurs living in Xinjiang, China (XJU), an admixed population of both European-like and East-Asian-like ancestry. The XJU population shows greater genetic diversity, especially a higher proportion of rare variants, compared with their ancestral source populations, corresponding to greater phenotypic diversity of XJU. Admixture-induced functional variants in EDAR were associated with the diversity of facial morphology in XJU. Interestingly, the interaction of functional variants between SLC24A5 and OCA2 likely influences the diversity of skin pigmentation. Notably, selection has seemingly been relaxed or canceled in several genes with significantly biased ancestry, such as HERC2-OCA2. Moreover, signatures of post-admixture adaptation in XJU were identified, including genes related to metabolism (e.g. CYP2D6), digestion (e.g. COL11A1), olfactory perception (e.g. ANO2) and immunity (e.g. HLA). Our results demonstrated population admixture as a driving force, locally or globally, in shaping human genetic and phenotypic diversity as well as in adaptive evolution.
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Structural variants (SVs) may play important roles in human adaptation to extreme environments such as high altitude but have been under-investigated. Here, combining long-read sequencing with multiple scaffolding techniques, we assembled a high-quality Tibetan genome (ZF1), with a contig N50 length of 24.57 mega-base pairs (Mb) and a scaffold N50 length of 58.80 Mb. The ZF1 assembly filled 80 remaining N-gaps (0.25 Mb in total length) in the reference human genome (GRCh38). Markedly, we detected 17 900 SVs, among which the ZF1-specific SVs are enriched in GTPase activity that is required for activation of the hypoxic pathway. Further population analysis uncovered a 163-bp intronic deletion in the MKL1 gene showing large divergence between highland Tibetans and lowland Han Chinese. This deletion is significantly associated with lower systolic pulmonary arterial pressure, one of the key adaptive physiological traits in Tibetans. Moreover, with the use of the high-quality de novo assembly, we observed a much higher rate of genome-wide archaic hominid (Altai Neanderthal and Denisovan) shared non-reference sequences in ZF1 (1.32%-1.53%) compared to other East Asian genomes (0.70%-0.98%), reflecting a unique genomic composition of Tibetans. One such archaic hominid shared sequence-a 662-bp intronic insertion in the SCUBE2 gene-is enriched and associated with better lung function (the FEV1/FVC ratio) in Tibetans. Collectively, we generated the first high-resolution Tibetan reference genome, and the identified SVs may serve as valuable resources for future evolutionary and medical studies.
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Despite the tremendous growth of the DNA sequencing data in the last decade, our understanding of the human genome is still in its infancy. To understand the implications of genetic variants in the light of population genetics and molecular evolution, we developed a database, PGG.SNV ( https://www.pggsnv.org ), which gives much higher weight to previously under-investigated indigenous populations in Asia. PGG.SNV archives 265 million SNVs across 220,147 present-day genomes and 1018 ancient genomes, including 1009 newly sequenced genomes, representing 977 global populations. Moreover, estimation of population genetic diversity and evolutionary parameters is available in PGG.SNV, a unique feature compared with other databases.
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Pueblo Asiatico/genética , Bases de Datos Genéticas , Enfermedad/genética , Genoma Humano , Polimorfismo de Nucleótido Simple , Evolución Molecular , Frecuencia de los Genes , Variación Genética , Humanos , Pueblos Indígenas/genéticaRESUMEN
BACKGROUND: The genetic relationships reported by recent studies between Sherpas and Tibetans are controversial. To gain insights into the population history and the genetic basis of high-altitude adaptation of the two groups, we analyzed genome-wide data in 111 Sherpas (Tibet and Nepal) and 177 Tibetans (Tibet and Qinghai), together with available data from present-day human populations. RESULTS: Sherpas and Tibetans show considerable genetic differences and can be distinguished as two distinct groups, even though the divergence between them (~3200-11,300 years ago) is much later than that between Han Chinese and either of the two groups (~6200-16,000 years ago). Sub-population structures exist in both Sherpas and Tibetans, corresponding to geographical or linguistic groups. Differentiation of genetic variants between Sherpas and Tibetans associated with adaptation to either high-altitude or ultraviolet radiation were identified and validated by genotyping additional Sherpa and Tibetan samples. CONCLUSIONS: Our analyses indicate that both Sherpas and Tibetans are admixed populations, but the findings do not support the previous hypothesis that Tibetans derive their ancestry from Sherpas and Han Chinese. Compared to Tibetans, Sherpas show higher levels of South Asian ancestry, while Tibetans show higher levels of East Asian and Central Asian/Siberian ancestry. We propose a new model to elucidate the differentiated demographic histories and local adaptations of Sherpas and Tibetans.