Junming Xu

Bio: Junming Xu is an academic researcher from Beijing Genomics Institute. The author has contributed to research in topics: Population & Medicine. The author has an hindex of 3, co-authored 3 publications receiving 9037 citations.

A human gut microbial gene catalogue established by metagenomic sequencing

Abstract: To understand the impact of gut microbes on human health and well-being it is crucial to assess their genetic potential. Here we describe the Illumina-based metagenomic sequencing, assembly and characterization of 3.3 million non-redundant microbial genes, derived from 576.7 gigabases of sequence, from faecal samples of 124 European individuals. The gene set, ~150 times larger than the human gene complement, contains an overwhelming majority of the prevalent (more frequent) microbial genes of the cohort and probably includes a large proportion of the prevalent human intestinal microbial genes. The genes are largely shared among individuals of the cohort. Over 99% of the genes are bacterial, indicating that the entire cohort harbours between 1,000 and 1,150 prevalent bacterial species and each individual at least 160 such species, which are also largely shared. We define and describe the minimal gut metagenome and the minimal gut bacterial genome in terms of functions present in all individuals and most bacteria, respectively

Sequencing of 50 Human Exomes Reveals Adaptation to High Altitude

Abstract: Residents of the Tibetan Plateau show heritable adaptations to extreme altitude. We sequenced 50 exomes of ethnic Tibetans, encompassing coding sequences of 92% of human genes, with an average coverage of 18x per individual. Genes showing population-specific allele frequency changes, which represent strong candidates for altitude adaptation, were identified. The strongest signal of natural selection came from endothelial Per-Arnt-Sim (PAS) domain protein 1 (EPAS1), a transcription factor involved in response to hypoxia. One single-nucleotide polymorphism (SNP) at EPAS1 shows a 78% frequency difference between Tibetan and Han samples, representing the fastest allele frequency change observed at any human gene to date. This SNP's association with erythrocyte abundance supports the role of EPAS1 in adaptation to hypoxia. Thus, a population genomic survey has revealed a functionally important locus in genetic adaptation to high altitude.

Archaeology Augments Tibet's Genetic History--Response

Abstract: We thank Brantingham et al. for their interest in our study; we agree that both molecular and archaeological evidence should be used to understand the demographic history of the Tibetan people. Our Report focused not on the demographic history of the Tibetan population, but rather the selection acting on specific putatively adaptive mutations segregating in the Tibetan population. We included some limited demographic analyses because they helped illuminate our results regarding natural selection. The real demographic model is clearly likely to be more complex than the simple models of two populations diverging from each other. For example, Zhao et al. ([ 1 ][1]) used mitochondrial DNA to argue that late settlers of the Tibetan plateau may not have entirely replaced the original population but that a small proportion of them carry mitochondrial DNA lineages tracing back to Late Paleolithic inhabitants on the plateau. If this is the case, even if the EPAS1 variant was present in the early inhabitants of Tibet, strong selection would be needed to increase its frequency in the modern Tibetan gene pool. The understanding that the majority of the current population of the Tibetan plateau may trace their genetic ancestry back to quite recent immigrants into Tibet, even though humans have lived in Tibet for a much longer time—possibly with some continuity of culture—is important for understanding the difference between inferences based on archaeology and inferences based on genetics. 1. [↵][2] 1. M. Zhao 2. et al ., Proc. Natl. Acad. Sci. U.S.A. 106, 21230 (2009). [OpenUrl][3][Abstract/FREE Full Text][4] [1]: #ref-1 [2]: #xref-ref-1-1 "View reference 1 in text" [3]: {openurl}?query=rft.jtitle%253DProc.%2BNatl.%2BAcad.%2BSci.%2BU.S.A.%26rft_id%253Dinfo%253Adoi%252F10.1073%252Fpnas.0907844106%26rft_id%253Dinfo%253Apmid%252F19955425%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [4]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6NDoicG5hcyI7czo1OiJyZXNpZCI7czoxMjoiMTA2LzUwLzIxMjMwIjtzOjQ6ImF0b20iO3M6MjU6Ii9zY2kvMzI5LzU5OTgvMTQ2Ny4yLmF0b20iO31zOjg6ImZyYWdtZW50IjtzOjA6IiI7fQ==

Ratio of CA19-9 Level to Total Tumor Volume as a Prognostic Predictor of Pancreatic Carcinoma After Curative Resection

Abstract: Background: Pancreatic ductal adenocarcinoma (PDAC) is known to have a poor prognosis, early local invasion, and distant metastasis. Surgical resection is the most effective treatment, and tumor recurrence can be the key factor affecting the surgical outcome. Serum carbohydrate antigen 19-9 (CA19-9) is a tumor marker with high sensitivity to pancreatic cancer; elevated CA19-9 levels often indicate poor biological behavior. Tumor size is also a crucial factor that affects the prognosis. Therefore, we developed a program to evaluate the effect of the ratio of CA19-9 to total tumor volume (CA19-9/TTV) as a prognostic marker on tumor recurrence and long-term survival in patients with PDAC following pancreaticoduodenectomy (PD). Methods: Data from 200 patients who underwent PD for PDAC were retrospectively analyzed. CA19-9/TTV was calculated according to preoperative CA19-9 and TTV, and patients were divided into two groups according to the optimal cut-off value. Univariate and multivariate analyses were performed on the clinicopathological data to screen the risk factors affecting postoperative recurrence and long-term prognosis of patients with PDAC undergoing PD. Results: The receiver operating characteristic curve showed that the best cut-off value was 5.62 (area under curve [AUC], 0.633; 95% CI: 0.548-0.718). Multivariate analysis showed that tumor differentiation and CA19-9/TTV were independent risk factors for the long-term prognosis of PDAC (P = 0.004, P = 0.007), as well as for tumor recurrence (P = 0.008, P = 0.008). Conclusion: CA19-9/TTV is an independent risk factor for the prognosis of PDAC and may be a new marker for lower survival benefits.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

A global reference for human genetic variation.

Abstract: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.

A framework for variation discovery and genotyping using next-generation DNA sequencing data

Abstract: Recent advances in sequencing technology make it possible to comprehensively catalogue genetic variation in population samples, creating a foundation for understanding human disease, ancestry and evolution. The amounts of raw data produced are prodigious and many computational steps are required to translate this output into high-quality variant calls. We present a unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs. Our process includes (1) initial read mapping; (2) local realignment around indels; (3) base quality score recalibration; (4) SNP discovery and genotyping to find all potential variants; and (5) machine learning to separate true segregating variation from machine artifacts common to next-generation sequencing technologies. We discuss the application of these tools, instantiated in the Genome Analysis Toolkit (GATK), to deep whole-genome, whole-exome capture, and multi-sample low-pass (~4×) 1000 Genomes Project datasets.

Structure, function and diversity of the healthy human microbiome

Abstract: The Human Microbiome Project Consortium reports the first results of their analysis of microbial communities from distinct, clinically relevant body habitats in a human cohort; the insights into the microbial communities of a healthy population lay foundations for future exploration of the epidemiology, ecology and translational applications of the human microbiome.