人类微生物组测序与比较研究

人体微生物群系影响人类的健康,与人类的各种疾病,如肥胖、糖尿病、冠心病、结肠癌等的发生具有密切的关系.近年来,人类微生物组研究日益受到重视.综述人类微生物组的测序和比较研究进展.     

An Integrated Metagenome Catalog Reveals New Insights into the Murine Gut Microbiome

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Extensive Unexplored Human Microbiome Diversity Revealed by Over 150,000 Genomes from Metagenomes Spanning Age,Geography, and Lifestyle

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Spatial Ecology of the Human Tongue Dorsum Microbiome

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Insolubility of Cr2O3 in Bioaccessibility Tests Points to Requirement for a New Human Oral Reference Dose for Trivalent Chromium

Bioaccessibility measurements have the potential to improve the accuracy of risk assessments and reduce the potential costs of remediation when they reveal that the solubility of chemicals in a matrix (e.g., soil) differs markedly from that in the critical toxicity study (i.e., the key study from which a toxicological or toxicity reference value is derived). We aimed to apply this approach to a brownfield site contaminated with chromium, and found that the speciation was Cr^III, using a combination of alkaline digestion/diphenylcarbazide complexation and X-ray absorption near edge structure analysis. The bioaccessibility of Cr₂O₃, the compound on which a reference dose for Cr^III is based, was substantially lower (<0.1%) than that of the Cr^III in the soils, which was a maximum of 9%, giving relative bioaccessibility values of 13,000% in soil. This shows that the reference dose is based on essentially an insoluble compound, and thus we suggest that other compounds be considered for toxicity testing and derivation of reference dose. Two possibilities are CrCl₃·6H₂O and KCr(SO₄)₂·12H₂O, which have been used for derivation of ecological toxicity reference values and are soluble at a range of dosing levels in our bioaccessibility tests.     

Towards Precision Medicine: Advances in Computational Approaches for the Analysis of Human Variants

Variations and similarities in our individual genomes are part of our history, our heritage, and our identity. Some human genomic variants are associated with common traits such as hair and eye color, while others are associated with susceptibility to disease or response to drug treatment. Identifying the human variations producing clinically relevant phenotypic changes is critical for providing accurate and personalized diagnosis, prognosis, and treatment for diseases. Furthermore, a better understanding of the molecular underpinning of disease can lead to development of new drug targets for precision medicine. Several resources have been designed for collecting and storing human genomic variations in highly structured, easily accessible databases. Unfortunately, a vast amount of information about these genetic variants and their functional and phenotypic associations is currently buried in the literature, only accessible by manual curation or sophisticated text text-mining technology to extract the relevant information. In addition, the low cost of sequencing technologies coupled with increasing computational power has enabled the development of numerous computational methodologies to predict the pathogenicity of human variants. This review provides a detailed comparison of current human variant resources, including HGMD, OMIM, ClinVar, and UniProt/Swiss-Prot, followed by an overview of the computational methods and techniques used to leverage the available data to predict novel deleterious variants. We expect these resources and tools to become the foundation for understanding the molecular details of genomic variants leading to disease, which in turn will enable the promise of precision medicine.     

Expressed Emotion,Human Agency,and Schizophrenia: Toward a New Model for the EE-Relapse Association

Although there is a clear statistical association between expressed emotion (EE) and schizophrenic relapse, our understanding of the mechanisms underlying this relationship is underdeveloped. This study tested a theoretical model in which caregivers’ perceptions of their ill relative’s agency underlie the EE-relapse association. To evaluate this model, we completed qualitative and quantitative analyses of narratives provided by individuals caring for a relative with schizophrenia. The results indicate that high-EE caregivers perceive the expression of symptoms as stemming from their ill relative’s agency more frequently than low-EE caregivers. This was true for both high-EE-criticism and high-EE-emotional overinvolvement caregivers. High-EE and low-EE caregivers did not differ in their perceptions of the role of their ill relative’s agency with regard to the control of symptoms. The findings suggest that EE may be a proxy risk factor for caregivers’ perceptions of their ill relative’s agency.

Quality control and integration of genotypes from two calling pipelines for whole genome sequence data in the Alzheimer's disease sequencing project

The Alzheimer's Disease Sequencing Project (ADSP) performed whole genome sequencing (WGS) of 584 subjects from 111 multiplex families at three sequencing centers. Genotype calling of single nucleotide variants (SNVs) and insertion-deletion variants (indels) was performed centrally using GATK-HaplotypeCaller and Atlas V2. The ADSP Quality Control (QC) Working Group applied QC protocols to project-level variant call format files (VCFs) from each pipeline, and developed and implemented a novel protocol, termed “consensus calling,” to combine genotype calls from both pipelines into a single high-quality set. QC was applied to autosomal bi-allelic SNVs and indels, and included pipeline-recommended QC filters, variant-level QC, and sample-level QC. Low-quality variants or genotypes were excluded, and sample outliers were noted. Quality was assessed by examining Mendelian inconsistencies (MIs) among 67 parent-offspring pairs, and MIs were used to establish additional genotype-specific filters for GATK calls. After QC, 578 subjects remained. Pipeline-specific QC excluded ~12.0% of GATK and 14.5% of Atlas SNVs. Between pipelines, ~91% of SNV genotypes across all QCed variants were concordant; 4.23% and 4.56% of genotypes were exclusive to Atlas or GATK, respectively; the remaining ~0.01% of discordant genotypes were excluded. For indels, variant-level QC excluded ~36.8% of GATK and 35.3% of Atlas indels. Between pipelines, ~55.6% of indel genotypes were concordant; while 10.3% and 28.3% were exclusive to Atlas or GATK, respectively; and ~0.29% of discordant genotypes were. The final WGS consensus dataset contains 27,896,774 SNVs and 3,133,926 indels and is publicly available.