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1.  Genotypic variants at 2q33 and risk of esophageal squamous cell carcinoma in China: a meta-analysis of genome-wide association studies 
Abnet, Christian C. | Wang, Zhaoming | Song, Xin | Hu, Nan | Zhou, Fu-You | Freedman, Neal D. | Li, Xue-Min | Yu, Kai | Shu, Xiao-Ou | Yuan, Jian-Min | Zheng, Wei | Dawsey, Sanford M. | Liao, Linda M. | Lee, Maxwell P. | Ding, Ti | Qiao, You-Lin | Gao, Yu-Tang | Koh, Woon-Puay | Xiang, Yong-Bing | Tang, Ze-Zhong | Fan, Jin-Hu | Chung, Charles C. | Wang, Chaoyu | Wheeler, William | Yeager, Meredith | Yuenger, Jeff | Hutchinson, Amy | Jacobs, Kevin B. | Giffen, Carol A. | Burdett, Laurie | Fraumeni, Joseph F. | Tucker, Margaret A. | Chow, Wong-Ho | Zhao, Xue-Ke | Li, Jiang-Man | Li, Ai-Li | Sun, Liang-Dan | Wei, Wu | Li, Ji-Lin | Zhang, Peng | Li, Hong-Lei | Cui, Wen-Yan | Wang, Wei-Peng | Liu, Zhi-Cai | Yang, Xia | Fu, Wen-Jing | Cui, Ji-Li | Lin, Hong-Li | Zhu, Wen-Liang | Liu, Min | Chen, Xi | Chen, Jie | Guo, Li | Han, Jing-Jing | Zhou, Sheng-Li | Huang, Jia | Wu, Yue | Yuan, Chao | Huang, Jing | Ji, Ai-Fang | Kul, Jian-Wei | Fan, Zhong-Min | Wang, Jian-Po | Zhang, Dong-Yun | Zhang, Lian-Qun | Zhang, Wei | Chen, Yuan-Fang | Ren, Jing-Li | Li, Xiu-Min | Dong, Jin-Cheng | Xing, Guo-Lan | Guo, Zhi-Gang | Yang, Jian-Xue | Mao, Yi-Ming | Yuan, Yuan | Guo, Er-Tao | Zhang, Wei | Hou, Zhi-Chao | Liu, Jing | Li, Yan | Tang, Sa | Chang, Jia | Peng, Xiu-Qin | Han, Min | Yin, Wan-Li | Liu, Ya-Li | Hu, Yan-Long | Liu, Yu | Yang, Liu-Qin | Zhu, Fu-Guo | Yang, Xiu-Feng | Feng, Xiao-Shan | Wang, Zhou | Li, Yin | Gao, She-Gan | Liu, Hai-Lin | Yuan, Ling | Jin, Yan | Zhang, Yan-Rui | Sheyhidin, Ilyar | Li, Feng | Chen, Bao-Ping | Ren, Shu-Wei | Liu, Bin | Li, Dan | Zhang, Gao-Fu | Yue, Wen-Bin | Feng, Chang-Wei | Qige, Qirenwang | Zhao, Jian-Ting | Yang, Wen-Jun | Lei, Guang-Yan | Chen, Long-Qi | Li, En-Min | Xu, Li-Yan | Wu, Zhi-Yong | Bao, Zhi-Qin | Chen, Ji-Li | Li, Xian-Chang | Zhuang, Xiang | Zhou, Ying-Fa | Zuo, Xian-Bo | Dong, Zi-Ming | Wang, Lu-Wen | Fan, Xue-Pin | Wang, Jin | Zhou, Qi | Ma, Guo-Shun | Zhang, Qin-Xian | Liu, Hai | Jian, Xin-Ying | Lian, Sin-Yong | Wang, Jin-Sheng | Chang, Fu-Bao | Lu, Chang-Dong | Miao, Jian-Jun | Chen, Zhi-Guo | Wang, Ran | Guo, Ming | Fan, Zeng-Lin | Tao, Ping | Liu, Tai-Jing | Wei, Jin-Chang | Kong, Qing-Peng | Fan, Lei | Wang, Xian-Zeng | Gao, Fu-Sheng | Wang, Tian-Yun | Xie, Dong | Wang, Li | Chen, Shu-Qing | Yang, Wan-Cai | Hong, Jun-Yan | Wang, Liang | Qiu, Song-Liang | Goldstein, Alisa M. | Yuan, Zhi-Qing | Chanock, Stephen J. | Zhang, Xue-Jun | Taylor, Philip R. | Wang, Li-Dong
Human Molecular Genetics  2012;21(9):2132-2141.
Genome-wide association studies have identified susceptibility loci for esophageal squamous cell carcinoma (ESCC). We conducted a meta-analysis of all single-nucleotide polymorphisms (SNPs) that showed nominally significant P-values in two previously published genome-wide scans that included a total of 2961 ESCC cases and 3400 controls. The meta-analysis revealed five SNPs at 2q33 with P< 5 × 10−8, and the strongest signal was rs13016963, with a combined odds ratio (95% confidence interval) of 1.29 (1.19–1.40) and P= 7.63 × 10−10. An imputation analysis of 4304 SNPs at 2q33 suggested a single association signal, and the strongest imputed SNP associations were similar to those from the genotyped SNPs. We conducted an ancestral recombination graph analysis with 53 SNPs to identify one or more haplotypes that harbor the variants directly responsible for the detected association signal. This showed that the five SNPs exist in a single haplotype along with 45 imputed SNPs in strong linkage disequilibrium, and the strongest candidate was rs10201587, one of the genotyped SNPs. Our meta-analysis found genome-wide significant SNPs at 2q33 that map to the CASP8/ALS2CR12/TRAK2 gene region. Variants in CASP8 have been extensively studied across a spectrum of cancers with mixed results. The locus we identified appears to be distinct from the widely studied rs3834129 and rs1045485 SNPs in CASP8. Future studies of esophageal and other cancers should focus on comprehensive sequencing of this 2q33 locus and functional analysis of rs13016963 and rs10201587 and other strongly correlated variants.
doi:10.1093/hmg/dds029
PMCID: PMC3315211  PMID: 22323360
2.  The Genomes of Oryza sativa: A History of Duplications 
Yu, Jun | Wang, Jun | Lin, Wei | Li, Songgang | Li, Heng | Zhou, Jun | Ni, Peixiang | Dong, Wei | Hu, Songnian | Zeng, Changqing | Zhang, Jianguo | Zhang, Yong | Li, Ruiqiang | Xu, Zuyuan | Li, Shengting | Li, Xianran | Zheng, Hongkun | Cong, Lijuan | Lin, Liang | Yin, Jianning | Geng, Jianing | Li, Guangyuan | Shi, Jianping | Liu, Juan | Lv, Hong | Li, Jun | Wang, Jing | Deng, Yajun | Ran, Longhua | Shi, Xiaoli | Wang, Xiyin | Wu, Qingfa | Li, Changfeng | Ren, Xiaoyu | Wang, Jingqiang | Wang, Xiaoling | Li, Dawei | Liu, Dongyuan | Zhang, Xiaowei | Ji, Zhendong | Zhao, Wenming | Sun, Yongqiao | Zhang, Zhenpeng | Bao, Jingyue | Han, Yujun | Dong, Lingli | Ji, Jia | Chen, Peng | Wu, Shuming | Liu, Jinsong | Xiao, Ying | Bu, Dongbo | Tan, Jianlong | Yang, Li | Ye, Chen | Zhang, Jingfen | Xu, Jingyi | Zhou, Yan | Yu, Yingpu | Zhang, Bing | Zhuang, Shulin | Wei, Haibin | Liu, Bin | Lei, Meng | Yu, Hong | Li, Yuanzhe | Xu, Hao | Wei, Shulin | He, Ximiao | Fang, Lijun | Zhang, Zengjin | Zhang, Yunze | Huang, Xiangang | Su, Zhixi | Tong, Wei | Li, Jinhong | Tong, Zongzhong | Li, Shuangli | Ye, Jia | Wang, Lishun | Fang, Lin | Lei, Tingting | Chen, Chen | Chen, Huan | Xu, Zhao | Li, Haihong | Huang, Haiyan | Zhang, Feng | Xu, Huayong | Li, Na | Zhao, Caifeng | Li, Shuting | Dong, Lijun | Huang, Yanqing | Li, Long | Xi, Yan | Qi, Qiuhui | Li, Wenjie | Zhang, Bo | Hu, Wei | Zhang, Yanling | Tian, Xiangjun | Jiao, Yongzhi | Liang, Xiaohu | Jin, Jiao | Gao, Lei | Zheng, Weimou | Hao, Bailin | Liu, Siqi | Wang, Wen | Yuan, Longping | Cao, Mengliang | McDermott, Jason | Samudrala, Ram | Wang, Jian | Wong, Gane Ka-Shu | Yang, Huanming
PLoS Biology  2005;3(2):e38.
We report improved whole-genome shotgun sequences for the genomes of indica and japonica rice, both with multimegabase contiguity, or almost 1,000-fold improvement over the drafts of 2002. Tested against a nonredundant collection of 19,079 full-length cDNAs, 97.7% of the genes are aligned, without fragmentation, to the mapped super-scaffolds of one or the other genome. We introduce a gene identification procedure for plants that does not rely on similarity to known genes to remove erroneous predictions resulting from transposable elements. Using the available EST data to adjust for residual errors in the predictions, the estimated gene count is at least 38,000–40,000. Only 2%–3% of the genes are unique to any one subspecies, comparable to the amount of sequence that might still be missing. Despite this lack of variation in gene content, there is enormous variation in the intergenic regions. At least a quarter of the two sequences could not be aligned, and where they could be aligned, single nucleotide polymorphism (SNP) rates varied from as little as 3.0 SNP/kb in the coding regions to 27.6 SNP/kb in the transposable elements. A more inclusive new approach for analyzing duplication history is introduced here. It reveals an ancient whole-genome duplication, a recent segmental duplication on Chromosomes 11 and 12, and massive ongoing individual gene duplications. We find 18 distinct pairs of duplicated segments that cover 65.7% of the genome; 17 of these pairs date back to a common time before the divergence of the grasses. More important, ongoing individual gene duplications provide a never-ending source of raw material for gene genesis and are major contributors to the differences between members of the grass family.
Comparative genome sequencing of indica and japonica rice reveals that duplication of genes and genomic regions has played a major part in the evolution of grass genomes
doi:10.1371/journal.pbio.0030038
PMCID: PMC546038  PMID: 15685292
3.  The sequence and de novo assembly of the giant panda genome 
Li, Ruiqiang | Fan, Wei | Tian, Geng | Zhu, Hongmei | He, Lin | Cai, Jing | Huang, Quanfei | Cai, Qingle | Li, Bo | Bai, Yinqi | Zhang, Zhihe | Zhang, Yaping | Wang, Wen | Li, Jun | Wei, Fuwen | Li, Heng | Jian, Min | Li, Jianwen | Zhang, Zhaolei | Nielsen, Rasmus | Li, Dawei | Gu, Wanjun | Yang, Zhentao | Xuan, Zhaoling | Ryder, Oliver A. | Leung, Frederick Chi-Ching | Zhou, Yan | Cao, Jianjun | Sun, Xiao | Fu, Yonggui | Fang, Xiaodong | Guo, Xiaosen | Wang, Bo | Hou, Rong | Shen, Fujun | Mu, Bo | Ni, Peixiang | Lin, Runmao | Qian, Wubin | Wang, Guodong | Yu, Chang | Nie, Wenhui | Wang, Jinhuan | Wu, Zhigang | Liang, Huiqing | Min, Jiumeng | Wu, Qi | Cheng, Shifeng | Ruan, Jue | Wang, Mingwei | Shi, Zhongbin | Wen, Ming | Liu, Binghang | Ren, Xiaoli | Zheng, Huisong | Dong, Dong | Cook, Kathleen | Shan, Gao | Zhang, Hao | Kosiol, Carolin | Xie, Xueying | Lu, Zuhong | Zheng, Hancheng | Li, Yingrui | Steiner, Cynthia C. | Lam, Tommy Tsan-Yuk | Lin, Siyuan | Zhang, Qinghui | Li, Guoqing | Tian, Jing | Gong, Timing | Liu, Hongde | Zhang, Dejin | Fang, Lin | Ye, Chen | Zhang, Juanbin | Hu, Wenbo | Xu, Anlong | Ren, Yuanyuan | Zhang, Guojie | Bruford, Michael W. | Li, Qibin | Ma, Lijia | Guo, Yiran | An, Na | Hu, Yujie | Zheng, Yang | Shi, Yongyong | Li, Zhiqiang | Liu, Qing | Chen, Yanling | Zhao, Jing | Qu, Ning | Zhao, Shancen | Tian, Feng | Wang, Xiaoling | Wang, Haiyin | Xu, Lizhi | Liu, Xiao | Vinar, Tomas | Wang, Yajun | Lam, Tak-Wah | Yiu, Siu-Ming | Liu, Shiping | Zhang, Hemin | Li, Desheng | Huang, Yan | Wang, Xia | Yang, Guohua | Jiang, Zhi | Wang, Junyi | Qin, Nan | Li, Li | Li, Jingxiang | Bolund, Lars | Kristiansen, Karsten | Wong, Gane Ka-Shu | Olson, Maynard | Zhang, Xiuqing | Li, Songgang | Yang, Huanming | Wang, Jian | Wang, Jun
Nature  2009;463(7279):311-317.
Using next-generation sequencing technology alone, we have successfully generated and assembled a draft sequence of the giant panda genome. The assembled contigs (2.25 gigabases (Gb)) cover approximately 94% of the whole genome, and the remaining gaps (0.05 Gb) seem to contain carnivore-specific repeats and tandem repeats. Comparisons with the dog and human showed that the panda genome has a lower divergence rate. The assessment of panda genes potentially underlying some of its unique traits indicated that its bamboo diet might be more dependent on its gut microbiome than its own genetic composition. We also identified more than 2.7 million heterozygous single nucleotide polymorphisms in the diploid genome. Our data and analyses provide a foundation for promoting mammalian genetic research, and demonstrate the feasibility for using next-generation sequencing technologies for accurate, cost-effective and rapid de novo assembly of large eukaryotic genomes.
doi:10.1038/nature08696
PMCID: PMC3951497  PMID: 20010809
4.  The diploid genome sequence of an Asian individual 
Nature  2008;456(7218):60-65.
Here we present the first diploid genome sequence of an Asian individual. The genome was sequenced to 36-fold average coverage using massively parallel sequencing technology. We aligned the short reads onto the NCBI human reference genome to 99.97% coverage, and guided by the reference genome, we used uniquely mapped reads to assemble a high-quality consensus sequence for 92% of the Asian individual's genome. We identified approximately 3 million single-nucleotide polymorphisms (SNPs) inside this region, of which 13.6% were not in the dbSNP database. Genotyping analysis showed that SNP identification had high accuracy and consistency, indicating the high sequence quality of this assembly. We also carried out heterozygote phasing and haplotype prediction against HapMap CHB and JPT haplotypes (Chinese and Japanese, respectively), sequence comparison with the two available individual genomes (J. D. Watson and J. C. Venter), and structural variation identification. These variations were considered for their potential biological impact. Our sequence data and analyses demonstrate the potential usefulness of next-generation sequencing technologies for personal genomics.
doi:10.1038/nature07484
PMCID: PMC2716080  PMID: 18987735
5.  Genome-wide association study in Han Chinese identifies four new susceptibility loci for coronary artery disease 
Nature genetics  2012;44(8):890-894.
We performed a meta-analysis of 2 genome-wide association studies of coronary artery disease comprising 1,515 cases with coronary artery disease and 5,019 controls, followed by de novo replication studies in 15,460 cases and 11,472 controls, all of Chinese Han descent. We successfully identified four new loci for coronary artery disease reaching genome-wide significance (P < 5 × 10−8), which mapped in or near TTC32-WDR35, GUCY1A3, C6orf10-BTNL2 and ATP2B1. We also replicated four loci previously identified in European populations (PHACTR1, TCF21, CDKN2A/B and C12orf51). These findings provide new insights into biological pathways for the susceptibility of coronary artery disease in Chinese Han population.
doi:10.1038/ng.2337
PMCID: PMC3927410  PMID: 22751097
6.  Complete Resequencing of 40 Genomes Reveals Domestication Events and Genes in Silkworm (Bombyx) 
Science (New York, N.Y.)  2009;326(5951):433-436.
A single–base pair resolution silkworm genetic variation map was constructed from 40 domesticated and wild silkworms, each sequenced to approximately threefold coverage, representing 99.88% of the genome. We identified ∼16 million single-nucleotide polymorphisms, many indels, and structural variations. We find that the domesticated silkworms are clearly genetically differentiated from the wild ones, but they have maintained large levels of genetic variability, suggesting a short domestication event involving a large number of individuals. We also identified signals of selection at 354 candidate genes that may have been important during domestication, some of which have enriched expression in the silk gland, midgut, and testis. These data add to our understanding of the domestication processes and may have applications in devising pest control strategies and advancing the use of silkworms as efficient bioreactors.
doi:10.1126/science.1176620
PMCID: PMC3951477  PMID: 19713493
7.  An atlas of DNA methylomes in porcine adipose and muscle tissues 
Nature communications  2012;3:850.
It is evident that epigenetic factors, especially DNA methylation, play essential roles in obesity development. Using pig as a model, here we investigated the systematic association between DNA methylation and obesity. We sampled eight variant adipose and two distinct skeletal muscle tissues from three pig breeds living within comparable environments but displaying distinct fat level. We generated 1,381 gigabases (Gb) of sequence data from 180 methylated DNA immunoprecipitation (MeDIP) libraries, and provided a genome-wide DNA methylation map as well as a gene expression map for adipose and muscle studies. The analysis showed global similarity and difference among breeds, sexes and anatomic locations, and identified the differentially methylated regions (DMRs). The DMRs in promoters are highly associated with obesity development via expression repression of both known obesity-related genes and novel genes. This comprehensive map provides a solid basis for exploring epigenetic mechanisms of adipose deposition and muscle growth.
doi:10.1038/ncomms1854
PMCID: PMC3508711  PMID: 22617290
8.  Impact of genital warts on health related quality of life in men and women in mainland China: a multicenter hospital-based cross-sectional study 
BMC Public Health  2012;12:153.
Background
Information on the health-related quality of life (HRQoL) of patients with genital warts (GW) in populations in mainland China is still limited. The aim of the study was to use a generic instrument to measure the impact of genital warts on HRQoL in men and women in this setting.
Methods
A multi-centre hospital-based cross-sectional study across 18 centers in China was conducted to interview patients using the European quality of life-5 dimension (EQ-5D) instrument; respondents' demographic and clinical data were also collected.
Results
A total of 1,358 GW patients (612 men, 746 women) were included in the analysis, with a mean age of 32.0 ± 10.6 years. 56.4% of the patients reported some problems in the dimension of Anxiety/Depression (highest), followed by Pain/Discomfort (24.7%) and Mobility (3.5%). The overall visual analogue scale (VAS) score of the study population was found to be 65.2 ± 22.0, and the EQ-5D index score was found to be 0.843 ± 0.129 using Japanese preference weights (the Chinese preference was unavailable yet). Patients with lower VAS means and EQ-5D index scores were more often female, living in urban area, and suffering multiple GW (all p values < 0.05), but the values did not differ notably by age (p values > 0.05).
Conclusions
The HRQoL of patients with GW was substantially lower, compared to a national representative general population in China (VAS = ~80); the findings of different subgroups are informative for future GW prevention and control efforts.
doi:10.1186/1471-2458-12-153
PMCID: PMC3359232  PMID: 22381149
9.  The polycomb group protein Bmi-1 represses the tumor suppressor PTEN and induces epithelial-mesenchymal transition in human nasopharyngeal epithelial cells 
The Journal of Clinical Investigation  2009;119(12):3626-3636.
The polycomb group protein B lymphoma Mo-MLV insertion region 1 homolog (Bmi-1) is dysregulated in various cancers, and its upregulation strongly correlates with an invasive phenotype and poor prognosis in patients with nasopharyngeal carcinomas. However, the underlying mechanism of Bmi-1–mediated invasiveness remains unknown. In the current study, we found that upregulation of Bmi-1 induced epithelial-mesenchymal transition (EMT) and enhanced the motility and invasiveness of human nasopharyngeal epithelial cells, whereas silencing endogenous Bmi-1 expression reversed EMT and reduced motility. Furthermore, upregulation of Bmi-1 led to the stabilization of Snail, a transcriptional repressor associated with EMT, via modulation of PI3K/Akt/GSK-3β signaling. Chromatin immunoprecipitation assays revealed that Bmi-1 transcriptionally downregulated expression of the tumor suppressor PTEN in tumor cells through direct association with the PTEN locus. This in vitro analysis was consistent with the statistical inverse correlation detected between Bmi-1 and PTEN expression in a cohort of human nasopharyngeal carcinoma biopsies. Moreover, ablation of PTEN expression partially rescued the migratory/invasive phenotype of Bmi-1–silenced cells, indicating that PTEN might be a major mediator of Bmi-1–induced EMT. Our results provide functional and mechanistic links between the oncoprotein Bmi-1 and the tumor suppressor PTEN in the development and progression of cancer.
doi:10.1172/JCI39374
PMCID: PMC2786794  PMID: 19884659
10.  Sero-Survey of Polio Antibodies during Wild Poliovirus Outbreak in Southern Xinjiang Uygur Autonomous Region, China 
PLoS ONE  2014;9(7):e80069.
Background
After being polio free for more than 10 years, an outbreak following importation of wild poliovirus (WPV) was confirmed in Xinjiang Uygur Autonomous Region, China, in 2011.
Methods
A cross-sectional study was conducted prior to supplementary immunization activities (SIAs), immediately after the confirmation of the WPV outbreak. In selected prefectures, participants aged ≤60 years old who visited hospitals at county-level or above to have their blood drawn for reasons not related to the study, were invited to participate in our study. Antibody titers ≥8 were considered positive.
Results
Among the 2,611 participants enrolled, 2,253 (86.3%), 2,283 (87.4%), and 1,989 (76.2%) were seropositive to P1, P2 and P3 respectively, and 1744 (66.8%) participants were seropositive to all the three serotypes. Lower antibody seropositivities and geometric mean titers were observed in children <1 year of age and in adults aged 15–39 years.
Conclusion
Serosurveys to estimate population immunity in districts at high risk of polio importation might be useful to gauge underlying population immunity gaps to polio and possibly to guide preparedness and response planning. Consideration should be given to older children and adults during polio risk assessment planning and outbreak response.
doi:10.1371/journal.pone.0080069
PMCID: PMC4081020  PMID: 24991811
11.  Spleen Dynamic Contrast-Enhanced Magnetic Resonance Imaging as a New Method for Staging Liver Fibrosis in a Piglet Model 
PLoS ONE  2013;8(12):e83697.
Objective
To explore spleen hemodynamic alteration in liver fibrosis with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), and to determine how to stage liver fibrosis with spleen DCE-MRI parameters.
Materials and Methods
Sixteen piglets were prospectively used to model liver fibrosis staged by liver biopsy, and underwent spleen DCE-MRI on 0, 5th, 9th, 16th and 21st weekend after modeling this disease. DCE-MRI parameters including time to peak (TTP), positive enhancement integral (PEI), maximum slope of increase (MSI) and maximum slope of decrease (MSD) of spleen were measured, and statistically analyzed to stage this disease.
Results
Spearman's rank correlation tests showed that TTP tended to increase with increasing stages of liver fibrosis (r = 0.647, P<0.001), and that PEI tended to decrease from stage 0 to 4 (r = −0.709, P<0.001). MSD increased slightly from stage 0 to 2 (P>0.05), and decreased from stage 2 to 4 (P<0.05). MSI increased from stage 0 to 1, and decreased from stage 1 to 4 (all P>0.05). Mann-Whitney tests demonstrated that TTP and PEI could classify fibrosis between stage 0 and 1–4, between 0–1 and 2–4, between 0–2 and 3–4, or between 0–3 and 4 (all P<0.01). MSD could discriminate between 0–2 and 3–4 (P = 0.006), or between 0–3 and 4 (P = 0.012). MSI could not differentiate between any two stages. Receiver operating characteristic analysis illustrated that area under receiver operating characteristic curve (AUC) of TTP was larger than of PEI for classifying stage ≥1 and ≥2 (AUC = 0.851 and 0.783, respectively). PEI could best classify stage ≥3 and 4 (AUC = 0.903 and 0.96, respectively).
Conclusion
Spleen DCE-MRI has potential to monitor spleen hemodynamic alteration and classify liver fibrosis stages.
doi:10.1371/journal.pone.0083697
PMCID: PMC3869810  PMID: 24376732
12.  Obligate mutualism within a host drives the extreme specialization of a fig wasp genome 
Genome Biology  2013;14(12):R141.
Background
Fig pollinating wasps form obligate symbioses with their fig hosts. This mutualism arose approximately 75 million years ago. Unlike many other intimate symbioses, which involve vertical transmission of symbionts to host offspring, female fig wasps fly great distances to transfer horizontally between hosts. In contrast, male wasps are wingless and cannot disperse. Symbionts that keep intimate contact with their hosts often show genome reduction, but it is not clear if the wide dispersal of female fig wasps will counteract this general tendency. We sequenced the genome of the fig wasp Ceratosolen solmsi to address this question.
Results
The genome size of the fig wasp C. solmsi is typical of insects, but has undergone dramatic reductions of gene families involved in environmental sensing and detoxification. The streamlined chemosensory ability reflects the overwhelming importance of females finding trees of their only host species, Ficus hispida, during their fleeting adult lives. Despite long-distance dispersal, little need exists for detoxification or environmental protection because fig wasps spend nearly all of their lives inside a largely benign host. Analyses of transcriptomes in females and males at four key life stages reveal that the extreme anatomical sexual dimorphism of fig wasps may result from a strong bias in sex-differential gene expression.
Conclusions
Our comparison of the C. solmsi genome with other insects provides new insights into the evolution of obligate mutualism. The draft genome of the fig wasp, and transcriptomic comparisons between both sexes at four different life stages, provide insights into the molecular basis for the extreme anatomical sexual dimorphism of this species.
doi:10.1186/gb-2013-14-12-r141
PMCID: PMC4053974  PMID: 24359812
13.  Sequencing of Fifty Human Exomes Reveals Adaptation to High Altitude 
Science (New York, N.Y.)  2010;329(5987):75-78.
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 EPAS1, a transcription factor involved in response to hypoxia. One 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.
doi:10.1126/science.1190371
PMCID: PMC3711608  PMID: 20595611
14.  Guidelines for the use and interpretation of assays for monitoring autophagy 
Klionsky, Daniel J. | Abdalla, Fabio C. | Abeliovich, Hagai | Abraham, Robert T. | Acevedo-Arozena, Abraham | Adeli, Khosrow | Agholme, Lotta | Agnello, Maria | Agostinis, Patrizia | Aguirre-Ghiso, Julio A. | Ahn, Hyung Jun | Ait-Mohamed, Ouardia | Ait-Si-Ali, Slimane | Akematsu, Takahiko | Akira, Shizuo | Al-Younes, Hesham M. | Al-Zeer, Munir A. | Albert, Matthew L. | Albin, Roger L. | Alegre-Abarrategui, Javier | Aleo, Maria Francesca | Alirezaei, Mehrdad | Almasan, Alexandru | Almonte-Becerril, Maylin | Amano, Atsuo | Amaravadi, Ravi K. | Amarnath, Shoba | Amer, Amal O. | Andrieu-Abadie, Nathalie | Anantharam, Vellareddy | Ann, David K. | Anoopkumar-Dukie, Shailendra | Aoki, Hiroshi | Apostolova, Nadezda | Arancia, Giuseppe | Aris, John P. | Asanuma, Katsuhiko | Asare, Nana Y.O. | Ashida, Hisashi | Askanas, Valerie | Askew, David S. | Auberger, Patrick | Baba, Misuzu | Backues, Steven K. | Baehrecke, Eric H. | Bahr, Ben A. | Bai, Xue-Yuan | Bailly, Yannick | Baiocchi, Robert | Baldini, Giulia | Balduini, Walter | Ballabio, Andrea | Bamber, Bruce A. | Bampton, Edward T.W. | Juhász, Gábor | Bartholomew, Clinton R. | Bassham, Diane C. | Bast, Robert C. | Batoko, Henri | Bay, Boon-Huat | Beau, Isabelle | Béchet, Daniel M. | Begley, Thomas J. | Behl, Christian | Behrends, Christian | Bekri, Soumeya | Bellaire, Bryan | Bendall, Linda J. | Benetti, Luca | Berliocchi, Laura | Bernardi, Henri | Bernassola, Francesca | Besteiro, Sébastien | Bhatia-Kissova, Ingrid | Bi, Xiaoning | Biard-Piechaczyk, Martine | Blum, Janice S. | Boise, Lawrence H. | Bonaldo, Paolo | Boone, David L. | Bornhauser, Beat C. | Bortoluci, Karina R. | Bossis, Ioannis | Bost, Frédéric | Bourquin, Jean-Pierre | Boya, Patricia | Boyer-Guittaut, Michaël | Bozhkov, Peter V. | Brady, Nathan R | Brancolini, Claudio | Brech, Andreas | Brenman, Jay E. | Brennand, Ana | Bresnick, Emery H. | Brest, Patrick | Bridges, Dave | Bristol, Molly L. | Brookes, Paul S. | Brown, Eric J. | Brumell, John 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Xiangmei | Chen, Xiequn | Chen, Ye-Guang | Chen, Yingyu | Chen, Yongqiang | Chen, Yu-Jen | Chen, Zhixiang | Cheng, Alan | Cheng, Christopher H.K. | Cheng, Yan | Cheong, Heesun | Cheong, Jae-Ho | Cherry, Sara | Chess-Williams, Russ | Cheung, Zelda H. | Chevet, Eric | Chiang, Hui-Ling | Chiarelli, Roberto | Chiba, Tomoki | Chin, Lih-Shen | Chiou, Shih-Hwa | Chisari, Francis V. | Cho, Chi Hin | Cho, Dong-Hyung | Choi, Augustine M.K. | Choi, DooSeok | Choi, Kyeong Sook | Choi, Mary E. | Chouaib, Salem | Choubey, Divaker | Choubey, Vinay | Chu, Charleen T. | Chuang, Tsung-Hsien | Chueh, Sheau-Huei | Chun, Taehoon | Chwae, Yong-Joon | Chye, Mee-Len | Ciarcia, Roberto | Ciriolo, Maria R. | Clague, Michael J. | Clark, Robert S.B. | Clarke, Peter G.H. | Clarke, Robert | Codogno, Patrice | Coller, Hilary A. | Colombo, María I. | Comincini, Sergio | Condello, Maria | Condorelli, Fabrizio | Cookson, Mark R. | Coombs, Graham H. | Coppens, Isabelle | Corbalan, Ramon | Cossart, Pascale | Costelli, Paola | Costes, Safia | Coto-Montes, Ana | Couve, Eduardo | Coxon, Fraser P. | Cregg, James M. | Crespo, José L. | Cronjé, Marianne J. | Cuervo, Ana Maria | Cullen, Joseph J. | Czaja, Mark J. | D'Amelio, Marcello | Darfeuille-Michaud, Arlette | Davids, Lester M. | Davies, Faith E. | De Felici, Massimo | de Groot, John F. | de Haan, Cornelis A.M. | De Martino, Luisa | De Milito, Angelo | De Tata, Vincenzo | Debnath, Jayanta | Degterev, Alexei | Dehay, Benjamin | Delbridge, Lea M.D. | Demarchi, Francesca | Deng, Yi Zhen | Dengjel, Jörn | Dent, Paul | Denton, Donna | Deretic, Vojo | Desai, Shyamal D. | Devenish, Rodney J. | Di Gioacchino, Mario | Di Paolo, Gilbert | Di Pietro, Chiara | Díaz-Araya, Guillermo | Díaz-Laviada, Inés | Diaz-Meco, Maria T. | Diaz-Nido, Javier | Dikic, Ivan | Dinesh-Kumar, Savithramma P. | Ding, Wen-Xing | Distelhorst, Clark W. | Diwan, Abhinav | Djavaheri-Mergny, Mojgan | Dokudovskaya, Svetlana | Dong, Zheng | Dorsey, Frank C. | Dosenko, Victor | Dowling, James J. | Doxsey, Stephen | Dreux, Marlène | Drew, Mark E. | Duan, Qiuhong | Duchosal, Michel A. | Duff, Karen E. | Dugail, Isabelle | Durbeej, Madeleine | Duszenko, Michael | Edelstein, Charles L. | Edinger, Aimee L. | Egea, Gustavo | Eichinger, Ludwig | Eissa, N. Tony | Ekmekcioglu, Suhendan | El-Deiry, Wafik S. | Elazar, Zvulun | Elgendy, Mohamed | Ellerby, Lisa M. | Eng, Kai Er | Engelbrecht, Anna-Mart | Engelender, Simone | Erenpreisa, Jekaterina | Escalante, Ricardo | Esclatine, Audrey | Eskelinen, Eeva-Liisa | Espert, Lucile | Espina, Virginia | Fan, Huizhou | Fan, Jia | Fan, Qi-Wen | Fan, Zhen | Fang, Shengyun | Fang, Yongqi | Fanto, Manolis | Fanzani, Alessandro | Farkas, Thomas | Farre, Jean-Claude | Faure, Mathias | Fechheimer, Marcus | Feng, Carl G. | Feng, Jian | Feng, Qili | Feng, Youji | Fésüs, László | Feuer, Ralph | Figueiredo-Pereira, Maria E. | Fimia, Gian Maria | Fingar, Diane C. | Finkbeiner, Steven | Finkel, Toren | Finley, Kim D. | Fiorito, Filomena | Fisher, Edward A. | Fisher, Paul B. | Flajolet, Marc | Florez-McClure, Maria L. | Florio, Salvatore | Fon, Edward A. | Fornai, Francesco | Fortunato, Franco | Fotedar, Rati | Fowler, Daniel H. | Fox, Howard S. | Franco, Rodrigo | Frankel, Lisa B. | Fransen, Marc | Fuentes, José M. | Fueyo, Juan | Fujii, Jun | Fujisaki, Kozo | Fujita, Eriko | Fukuda, Mitsunori | Furukawa, Ruth H. | Gaestel, Matthias | Gailly, Philippe | Gajewska, Malgorzata | Galliot, Brigitte | Galy, Vincent | Ganesh, Subramaniam | Ganetzky, Barry | Ganley, Ian G. | Gao, Fen-Biao | Gao, George F. | Gao, Jinming | Garcia, Lorena | Garcia-Manero, Guillermo | Garcia-Marcos, Mikel | Garmyn, Marjan | Gartel, Andrei L. | Gatti, Evelina | Gautel, Mathias | Gawriluk, Thomas R. | Gegg, Matthew E. | Geng, Jiefei | Germain, Marc | Gestwicki, Jason E. | Gewirtz, David A. | Ghavami, Saeid | Ghosh, Pradipta | Giammarioli, Anna M. | Giatromanolaki, Alexandra N. | Gibson, Spencer B. | Gilkerson, Robert W. | Ginger, Michael L. | Ginsberg, Henry N. | Golab, Jakub | Goligorsky, Michael S. | Golstein, Pierre | Gomez-Manzano, Candelaria | Goncu, Ebru | Gongora, Céline | Gonzalez, Claudio D. | Gonzalez, Ramon | González-Estévez, Cristina | González-Polo, Rosa Ana | Gonzalez-Rey, Elena | Gorbunov, Nikolai V. | Gorski, Sharon | Goruppi, Sandro | Gottlieb, Roberta A. | Gozuacik, Devrim | Granato, Giovanna Elvira | Grant, Gary D. | Green, Kim N. | Gregorc, Ales | Gros, Frédéric | Grose, Charles | Grunt, Thomas W. | Gual, Philippe | Guan, Jun-Lin | Guan, Kun-Liang | Guichard, Sylvie M. | Gukovskaya, Anna S. | Gukovsky, Ilya | Gunst, Jan | Gustafsson, Åsa B. | Halayko, Andrew J. | Hale, Amber N. | Halonen, Sandra K. | Hamasaki, Maho | Han, Feng | Han, Ting | Hancock, Michael K. | Hansen, Malene | Harada, Hisashi | Harada, Masaru | Hardt, Stefan E. | Harper, J. Wade | Harris, Adrian L. | Harris, James | Harris, Steven D. | Hashimoto, Makoto | Haspel, Jeffrey A. | Hayashi, Shin-ichiro | Hazelhurst, Lori A. | He, Congcong | He, You-Wen | Hébert, Marie-Josée | Heidenreich, Kim A. | Helfrich, Miep H. | Helgason, Gudmundur V. | Henske, Elizabeth P. | Herman, Brian | Herman, Paul K. | Hetz, Claudio | Hilfiker, Sabine | Hill, Joseph A. | Hocking, Lynne J. | Hofman, Paul | Hofmann, Thomas G. | Höhfeld, Jörg | Holyoake, Tessa L. | Hong, Ming-Huang | Hood, David A. | Hotamisligil, Gökhan S. | Houwerzijl, Ewout J. | Høyer-Hansen, Maria | Hu, Bingren | Hu, Chien-an A. | Hu, Hong-Ming | Hua, Ya | Huang, Canhua | Huang, Ju | Huang, Shengbing | Huang, Wei-Pang | Huber, Tobias B. | Huh, Won-Ki | Hung, Tai-Ho | Hupp, Ted R. | Hur, Gang Min | Hurley, James B. | Hussain, Sabah N.A. | Hussey, Patrick J. | Hwang, Jung Jin | Hwang, Seungmin | Ichihara, Atsuhiro | Ilkhanizadeh, Shirin | Inoki, Ken | Into, Takeshi | Iovane, Valentina | Iovanna, Juan L. | Ip, Nancy Y. | Isaka, Yoshitaka | Ishida, Hiroyuki | Isidoro, Ciro | Isobe, Ken-ichi | Iwasaki, Akiko | Izquierdo, Marta | Izumi, Yotaro | Jaakkola, Panu M. | Jäättelä, Marja | Jackson, George R. | Jackson, William T. | Janji, Bassam | Jendrach, Marina | Jeon, Ju-Hong | Jeung, Eui-Bae | Jiang, Hong | Jiang, Hongchi | Jiang, Jean X. | Jiang, Ming | Jiang, Qing | Jiang, Xuejun | Jiang, Xuejun | Jiménez, Alberto | Jin, Meiyan | Jin, Shengkan V. | Joe, Cheol O. | Johansen, Terje | Johnson, Daniel E. | Johnson, Gail V.W. | Jones, Nicola L. | Joseph, Bertrand | Joseph, Suresh K. | Joubert, Annie M. | Juhász, Gábor | Juillerat-Jeanneret, Lucienne | Jung, Chang Hwa | Jung, Yong-Keun | Kaarniranta, Kai | Kaasik, Allen | Kabuta, Tomohiro | Kadowaki, Motoni | Kågedal, Katarina | Kamada, Yoshiaki | Kaminskyy, Vitaliy O. | Kampinga, Harm H. | Kanamori, Hiromitsu | Kang, Chanhee | Kang, Khong Bee | Kang, Kwang Il | Kang, Rui | Kang, Yoon-A | Kanki, Tomotake | Kanneganti, Thirumala-Devi | Kanno, Haruo | Kanthasamy, Anumantha G. | Kanthasamy, Arthi | Karantza, Vassiliki | Kaushal, Gur P. | Kaushik, Susmita | Kawazoe, Yoshinori | Ke, Po-Yuan | Kehrl, John H. | Kelekar, Ameeta | Kerkhoff, Claus | Kessel, David H. | Khalil, Hany | Kiel, Jan A.K.W. | Kiger, Amy A. | Kihara, Akio | Kim, Deok Ryong | Kim, Do-Hyung | Kim, Dong-Hou | Kim, Eun-Kyoung | Kim, Hyung-Ryong | Kim, Jae-Sung | Kim, Jeong Hun | Kim, Jin Cheon | Kim, John K. | Kim, Peter K. | Kim, Seong Who | Kim, Yong-Sun | Kim, Yonghyun | Kimchi, Adi | Kimmelman, Alec C. | King, Jason S. | Kinsella, Timothy J. | Kirkin, Vladimir | Kirshenbaum, Lorrie A. | Kitamoto, Katsuhiko | Kitazato, Kaio | Klein, Ludger | Klimecki, Walter T. | Klucken, Jochen | Knecht, Erwin | Ko, Ben C.B. | Koch, Jan C. | Koga, Hiroshi | Koh, Jae-Young | Koh, Young Ho | Koike, Masato | Komatsu, Masaaki | Kominami, Eiki | Kong, Hee Jeong | Kong, Wei-Jia | Korolchuk, Viktor I. | Kotake, Yaichiro | Koukourakis, Michael I. | Flores, Juan B. Kouri | Kovács, Attila L. | Kraft, Claudine | Krainc, Dimitri | Krämer, Helmut | Kretz-Remy, Carole | Krichevsky, Anna M. | Kroemer, Guido | Krüger, Rejko | Krut, Oleg | Ktistakis, Nicholas T. | Kuan, Chia-Yi | Kucharczyk, Roza | Kumar, Ashok | Kumar, Raj | Kumar, Sharad | Kundu, Mondira | Kung, Hsing-Jien | Kurz, Tino | Kwon, Ho Jeong | La Spada, Albert R. | Lafont, Frank | Lamark, Trond | Landry, Jacques | Lane, Jon D. | Lapaquette, Pierre | Laporte, Jocelyn F. | László, Lajos | Lavandero, Sergio | Lavoie, Josée N. | Layfield, Robert | Lazo, Pedro A. | Le, Weidong | Le Cam, Laurent | Ledbetter, Daniel J. | Lee, Alvin J.X. | Lee, Byung-Wan | Lee, Gyun Min | Lee, Jongdae | lee, Ju-hyun | Lee, Michael | Lee, Myung-Shik | Lee, Sug Hyung | Leeuwenburgh, Christiaan | Legembre, Patrick | Legouis, Renaud | Lehmann, Michael | Lei, Huan-Yao | Lei, Qun-Ying | Leib, David A. | Leiro, José | Lemasters, John J. | Lemoine, Antoinette | Lesniak, Maciej S. | Lev, Dina | Levenson, Victor V. | Levine, Beth | Levy, Efrat | Li, Faqiang | Li, Jun-Lin | Li, Lian | Li, Sheng | Li, Weijie | Li, Xue-Jun | Li, Yan-Bo | Li, Yi-Ping | Liang, Chengyu | Liang, Qiangrong | Liao, Yung-Feng | Liberski, Pawel P. | Lieberman, Andrew | Lim, Hyunjung J. | Lim, Kah-Leong | Lim, Kyu | Lin, Chiou-Feng | Lin, Fu-Cheng | Lin, Jian | Lin, Jiandie D. | Lin, Kui | Lin, Wan-Wan | Lin, Weei-Chin | Lin, Yi-Ling | Linden, Rafael | Lingor, Paul | Lippincott-Schwartz, Jennifer | Lisanti, Michael P. | Liton, Paloma B. | Liu, Bo | Liu, Chun-Feng | Liu, Kaiyu | Liu, Leyuan | Liu, Qiong A. | Liu, Wei | Liu, Young-Chau | Liu, Yule | Lockshin, Richard A. | Lok, Chun-Nam | Lonial, Sagar | Loos, Benjamin | Lopez-Berestein, Gabriel | López-Otín, Carlos | Lossi, Laura | Lotze, Michael T. | Low, Peter | Lu, Binfeng | Lu, Bingwei | Lu, Bo | Lu, Zhen | Luciano, Fréderic | Lukacs, Nicholas W. | Lund, Anders H. | Lynch-Day, Melinda A. | Ma, Yong | Macian, Fernando | MacKeigan, Jeff P. | Macleod, Kay F. | Madeo, Frank | Maiuri, Luigi | Maiuri, Maria Chiara | Malagoli, Davide | Malicdan, May Christine V. | Malorni, Walter | Man, Na | Mandelkow, Eva-Maria | Manon, Stephen | Manov, Irena | Mao, Kai | Mao, Xiang | Mao, Zixu | Marambaud, Philippe | Marazziti, Daniela | Marcel, Yves L. | Marchbank, Katie | Marchetti, Piero | Marciniak, Stefan J. | Marcondes, Mateus | Mardi, Mohsen | Marfe, Gabriella | Mariño, Guillermo | Markaki, Maria | Marten, Mark R. | Martin, Seamus J. | Martinand-Mari, Camille | Martinet, Wim | Martinez-Vicente, Marta | Masini, Matilde | Matarrese, Paola | Matsuo, Saburo | Matteoni, Raffaele | Mayer, Andreas | Mazure, Nathalie M. | McConkey, David J. | McConnell, Melanie J. | McDermott, Catherine | McDonald, Christine | McInerney, Gerald M. | McKenna, Sharon L. | McLaughlin, BethAnn | McLean, Pamela J. | McMaster, Christopher R. | McQuibban, G. Angus | Meijer, Alfred J. | Meisler, Miriam H. | Meléndez, Alicia | Melia, Thomas J. | Melino, Gerry | Mena, Maria A. | Menendez, Javier A. | Menna-Barreto, Rubem F. S. | Menon, Manoj B. | Menzies, Fiona M. | Mercer, Carol A. | Merighi, Adalberto | Merry, Diane E. | Meschini, Stefania | Meyer, Christian G. | Meyer, Thomas F. | Miao, Chao-Yu | Miao, Jun-Ying | Michels, Paul A.M. | Michiels, Carine | Mijaljica, Dalibor | Milojkovic, Ana | Minucci, Saverio | Miracco, Clelia | Miranti, Cindy K. | Mitroulis, Ioannis | Miyazawa, Keisuke | Mizushima, Noboru | Mograbi, Baharia | Mohseni, Simin | Molero, Xavier | Mollereau, Bertrand | Mollinedo, Faustino | Momoi, Takashi | Monastyrska, Iryna | Monick, Martha M. | Monteiro, Mervyn J. | Moore, Michael N. | Mora, Rodrigo | Moreau, Kevin | Moreira, Paula I. | Moriyasu, Yuji | Moscat, Jorge | Mostowy, Serge | Mottram, Jeremy C. | Motyl, Tomasz | Moussa, Charbel E.-H. | Müller, Sylke | Muller, Sylviane | Münger, Karl | Münz, Christian | Murphy, Leon O. | Murphy, Maureen E. | Musarò, Antonio | Mysorekar, Indira | Nagata, Eiichiro | Nagata, Kazuhiro | Nahimana, Aimable | Nair, Usha | Nakagawa, Toshiyuki | Nakahira, Kiichi | Nakano, Hiroyasu | Nakatogawa, Hitoshi | Nanjundan, Meera | Naqvi, Naweed I. | Narendra, Derek P. | Narita, Masashi | Navarro, Miguel | Nawrocki, Steffan T. | Nazarko, Taras Y. | Nemchenko, Andriy | Netea, Mihai G. | Neufeld, Thomas P. | Ney, Paul A. | Nezis, Ioannis P. | Nguyen, Huu Phuc | Nie, Daotai | Nishino, Ichizo | Nislow, Corey | Nixon, Ralph A. | Noda, Takeshi | Noegel, Angelika A. | Nogalska, Anna | Noguchi, Satoru | Notterpek, Lucia | Novak, Ivana | Nozaki, Tomoyoshi | Nukina, Nobuyuki | Nürnberger, Thorsten | Nyfeler, Beat | Obara, Keisuke | Oberley, Terry D. | Oddo, Salvatore | Ogawa, Michinaga | Ohashi, Toya | Okamoto, Koji | Oleinick, Nancy L. | Oliver, F. Javier | Olsen, Laura J. | Olsson, Stefan | Opota, Onya | Osborne, Timothy F. | Ostrander, Gary K. | Otsu, Kinya | Ou, Jing-hsiung James | Ouimet, Mireille | Overholtzer, Michael | Ozpolat, Bulent | Paganetti, Paolo | Pagnini, Ugo | Pallet, Nicolas | Palmer, Glen E. | Palumbo, Camilla | Pan, Tianhong | Panaretakis, Theocharis | Pandey, Udai Bhan | Papackova, Zuzana | Papassideri, Issidora | Paris, Irmgard | Park, Junsoo | Park, Ohkmae K. | Parys, Jan B. | Parzych, Katherine R. | Patschan, Susann | Patterson, Cam | Pattingre, Sophie | Pawelek, John M. | Peng, Jianxin | Perlmutter, David H. | Perrotta, Ida | Perry, George | Pervaiz, Shazib | Peter, Matthias | Peters, Godefridus J. | Petersen, Morten | Petrovski, Goran | Phang, James M. | Piacentini, Mauro | Pierre, Philippe | Pierrefite-Carle, Valérie | Pierron, Gérard | Pinkas-Kramarski, Ronit | Piras, Antonio | Piri, Natik | Platanias, Leonidas C. | Pöggeler, Stefanie | Poirot, Marc | Poletti, Angelo | Poüs, Christian | Pozuelo-Rubio, Mercedes | Prætorius-Ibba, Mette | Prasad, Anil | Prescott, Mark | Priault, Muriel | Produit-Zengaffinen, Nathalie | Progulske-Fox, Ann | Proikas-Cezanne, Tassula | Przedborski, Serge | Przyklenk, Karin | Puertollano, Rosa | Puyal, Julien | Qian, Shu-Bing | Qin, Liang | Qin, Zheng-Hong | Quaggin, Susan E. | Raben, Nina | Rabinowich, Hannah | Rabkin, Simon W. | Rahman, Irfan | Rami, Abdelhaq | Ramm, Georg | Randall, Glenn | Randow, Felix | Rao, V. Ashutosh | Rathmell, Jeffrey C. | Ravikumar, Brinda | Ray, Swapan K. | Reed, Bruce H. | Reed, John C. | Reggiori, Fulvio | Régnier-Vigouroux, Anne | Reichert, Andreas S. | Reiners, John J. | Reiter, Russel J. | Ren, Jun | Revuelta, José L. | Rhodes, Christopher J. | Ritis, Konstantinos | Rizzo, Elizete | Robbins, Jeffrey | Roberge, Michel | Roca, Hernan | Roccheri, Maria C. | Rocchi, Stephane | Rodemann, H. Peter | Rodríguez de Córdoba, Santiago | Rohrer, Bärbel | Roninson, Igor B. | Rosen, Kirill | Rost-Roszkowska, Magdalena M. | Rouis, Mustapha | Rouschop, Kasper M.A. | Rovetta, Francesca | Rubin, Brian P. | Rubinsztein, David C. | Ruckdeschel, Klaus | Rucker, Edmund B. | Rudich, Assaf | Rudolf, Emil | Ruiz-Opazo, Nelson | Russo, Rossella | Rusten, Tor Erik | Ryan, Kevin M. | Ryter, Stefan W. | Sabatini, David M. | Sadoshima, Junichi | Saha, Tapas | Saitoh, Tatsuya | Sakagami, Hiroshi | Sakai, Yasuyoshi | Salekdeh, Ghasem Hoseini | Salomoni, Paolo | Salvaterra, Paul M. | Salvesen, Guy | Salvioli, Rosa | Sanchez, Anthony M.J. | Sánchez-Alcázar, José A. | Sánchez-Prieto, Ricardo | Sandri, Marco | Sankar, Uma | Sansanwal, Poonam | Santambrogio, Laura | Saran, Shweta | Sarkar, Sovan | Sarwal, Minnie | Sasakawa, Chihiro | Sasnauskiene, Ausra | Sass, Miklós | Sato, Ken | Sato, Miyuki | Schapira, Anthony H.V. | Scharl, Michael | Schätzl, Hermann M. | Scheper, Wiep | Schiaffino, Stefano | Schneider, Claudio | Schneider, Marion E. | Schneider-Stock, Regine | Schoenlein, Patricia V. | Schorderet, Daniel F. | Schüller, Christoph | Schwartz, Gary K. | Scorrano, Luca | Sealy, Linda | Seglen, Per O. | Segura-Aguilar, Juan | Seiliez, Iban | Seleverstov, Oleksandr | Sell, Christian | Seo, Jong Bok | Separovic, Duska | Setaluri, Vijayasaradhi | Setoguchi, Takao | Settembre, Carmine | Shacka, John J. | Shanmugam, Mala | Shapiro, Irving M. | Shaulian, Eitan | Shaw, Reuben J. | Shelhamer, James H. | Shen, Han-Ming | Shen, Wei-Chiang
Autophagy  2012;8(4):445-544.
In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field.
doi:10.4161/auto.19496
PMCID: PMC3404883  PMID: 22966490
LC3; autolysosome; autophagosome; flux; lysosome; phagophore; stress; vacuole
15.  Magnetic resonance-based total liver volume and magnetic resonance-diffusion weighted imaging for staging liver fibrosis in mini-pigs 
AIM: To determine whether and how magnetic resonance imaging (MRI)-based total liver volume (TLV) and diffusion weighted imaging (DWI) could predict liver fibrosis.
METHODS: Sixteen experimental mature mini-pigs (6 males, 10 females), weighing between 20.0 and 24.0 kg were prospectively used to model liver fibrosis induced by intraperitoneal injection of 40% CCl4 dissolved in fat emulsion twice a week for 16 wk, and by feeding 40% CCl4 mixed with maize flour twice daily for the subsequent 5 wk. All the survival animals underwent percutaneous liver biopsy and DWI using b = 300, 500 and 800 s/mm2 followed by abdominal gadolinium-enhanced MRI at the 0, 5th, 9th, 16th and 21st weekend after beginning of the modeling. TLV was obtained on enhanced MRI, and apparent diffusion coefficient (ADC) was obtained on DWI. Hepatic tissue specimens were stained with hematoxylin and Masson’s trichrome staining for staging liver fibrosis. Pathological specimens were scored using the human METAVIR classification system. Statistical analyses were performed to determine whether and how the TLV and ADC could be used to predict the stage of liver fibrosis.
RESULTS: TLV increased from stage 0 to 2 and decreased from stage 3 (r = 0.211; P < 0.001). There was a difference in TLV between stage 0-1 and 2-4 (P = 0.03) whereas no difference between stage 0-2 and 3-4 (P = 0.71). TLV could predict stage ≥ 2 [area under receiver operating characteristic curve (AUC) = 0.682]. There was a decrease in ADC values with increasing stage of fibrosis for b = 300, 500 and 800 s/mm2 (r = -0.418, -0.535 and -0.622, respectively; all P < 0.001). Differences were found between stage 0-1 and 2-4 in ADC values for b = 300, 500 and 800 s/mm2, and between stage 0-2 and 3-4 for b = 500 or 800 s/mm2 (all P < 0.05). For predicting stage ≥ 2 and ≥ 3, AUC was 0.803 and 0.847 for b = 500 s/mm2, and 0.848 and 0.887 for b = 800 s/mm2, respectively.
CONCLUSION: ADC for b = 500 or 800 s/mm2 could be better than TLV and ADC for b = 300 s/mm2 to predict fibrosis stage ≥ 2 or ≥ 3.
doi:10.3748/wjg.v18.i48.7225
PMCID: PMC3544024  PMID: 23326127
Magnetic resonance imaging; Total liver volume; Liver fibrosis; Apparent diffusion coefficient; Stage
16.  Association analyses identify six new psoriasis susceptibility loci in the Chinese population 
Nature genetics  2010;42(11):1005-1009.
We extended our previous GWAS for psoriasis with a a multistage replication study including 8,312 cases and 12,919 controls from China as well as 3,293 cases, 4,188 controls from Germany and the USA, and 254 nuclear families from the USA. We identified 6 new susceptibility loci associated to psoriasis in Chinese, containing candidate genes ERAP1, PTTG1, CSMD1, GJB2, SERPINB8, ZNF816A (PCombined<5×10−8) and replicated one locus 5q33.1 (TNIP1/ANXA6) previously reported (PCombined=3.8×10−21) in European studies. Two of these loci showed evidence for association evidence in the German study, at ZNF816A and GJB2 with P=3.6×10−3 and P=7.9×10−3, respectively. ERAP1 and ZNF816A were preferentially associated with Type I (early onset) psoriasis in Chinese Han population (test for heterogeneity P=6.5×10−3 and P=1.5×10−3, respectively). Comparisons with previous GWAS of psoriasis highlight the heterogeneity of disease susceptibility between Chinese and European populations. Our study identifies new genetic susceptibility factors and suggests new biological pathways in psoriasis.
doi:10.1038/ng.690
PMCID: PMC3140436  PMID: 20953187
17.  Early B-cell factor 3 (EBF3) is a novel tumor suppressor gene with promoter hypermethylation in pediatric acute myeloid leukemia 
Background
Pediatric acute myeloid leukemia (AML) comprises up to 20% of all childhood leukemia. Recent research shows that aberrant DNA methylation patterning may play a role in leukemogenesis. The epigenetic silencing of the EBF3 locus is very frequent in glioblastoma. However, the expression profiles and molecular function of EBF3 in pediatric AML is still unclear.
Methods
Twelve human acute leukemia cell lines, 105 pediatric AML samples and 30 normal bone marrow/idiopathic thrombocytopenic purpura (NBM/ITP) control samples were analyzed. Transcriptional level of EBF3 was evaluated by semi-quantitative and real-time PCR. EBF3 methylation status was determined by methylation specific PCR (MSP) and bisulfite genomic sequencing (BGS). The molecular mechanism of EBF3 was investigated by apoptosis assays and PCR array analysis.
Results
EBF3 promoter was hypermethylated in 10/12 leukemia cell lines. Aberrant EBF3 methylation was observed in 42.9% (45/105) of the pediatric AML samples using MSP analysis, and the BGS results confirmed promoter methylation. EBF3 expression was decreased in the AML samples compared with control. Methylated samples revealed similar survival outcomes by Kaplan-Meier survival analysis. EBF3 overexpression significantly inhibited cell proliferation and increased apoptosis. Real-time PCR array analysis revealed 93 dysregulated genes possibly implicated in the apoptosis of EBF3-induced AML cells.
Conclusion
In this study, we firstly identified epigenetic inactivation of EBF3 in both AML cell lines and pediatric AML samples for the first time. Our findings also showed for the first time that transcriptional overexpression of EBF3 could inhibit proliferation and induce apoptosis in AML cells. We identified 93 dysregulated apoptosis-related genes in EBF3-overexpressing, including DCC, AIFM2 and DAPK1. Most of these genes have never been related with EBF3 over expression. These results may provide new insights into the molecular mechanism of EBF3-induced apoptosis; however, further research will be required to determine the underlying details.
Our findings suggest that EBF3 may act as a putative tumor suppressor gene in pediatric AML.
doi:10.1186/s13046-014-0118-1
PMCID: PMC4311429  PMID: 25609158
Early B-cell factor 3; Pediatric acute myeloid leukemia; Methylation; Tumor suppressor; Real-time PCR array
18.  Molecular Targeting of the Oncoprotein PLK1 in Pediatric Acute Myeloid Leukemia: RO3280, a Novel PLK1 Inhibitor, Induces Apoptosis in Leukemia Cells 
Polo-like kinase 1 (PLK1) is highly expressed in many cancers and therefore a biomarker of transformation and potential target for the development of cancer-specific small molecule drugs. RO3280 was recently identified as a novel PLK1 inhibitor; however its therapeutic effects in leukemia treatment are still unknown. We found that the PLK1 protein was highly expressed in leukemia cell lines as well as 73.3% (11/15) of pediatric acute myeloid leukemia (AML) samples. PLK1 mRNA expression was significantly higher in AML samples compared with control samples (82.95 ± 110.28 vs. 6.36 ± 6.35; p < 0.001). Kaplan-Meier survival analysis revealed that shorter survival time correlated with high tumor PLK1 expression (p = 0.002). The 50% inhibitory concentration (IC50) of RO3280 for acute leukemia cells was between 74 and 797 nM. The IC50 of RO3280 in primary acute lymphocytic leukemia (ALL) and AML cells was between 35.49 and 110.76 nM and 52.80 and 147.50 nM, respectively. RO3280 induced apoptosis and cell cycle disorder in leukemia cells. RO3280 treatment regulated several apoptosis-associated genes. The regulation of DCC, CDKN1A, BTK, and SOCS2 was verified by western blot. These results provide insights into the potential use of RO3280 for AML therapy; however, the underlying mechanisms remain to be determined.
doi:10.3390/ijms16011266
PMCID: PMC4307303  PMID: 25574601
RO3280; pediatric acute myeloid leukemia (AML); polo-like kinase 1 (PLK1); apoptosis; oncogene target
19.  Development of a general method for detection and quantification of the P35S promoter based on assessment of existing methods 
Scientific Reports  2014;4:7358.
The Cauliflower mosaic virus (CaMV) 35S promoter (P35S) is a commonly used target for detection of genetically modified organisms (GMOs). There are currently 24 reported detection methods, targeting different regions of the P35S promoter. Initial assessment revealed that due to the absence of primer binding sites in the P35S sequence, 19 of the 24 reported methods failed to detect P35S in MON88913 cotton, and the other two methods could only be applied to certain GMOs. The rest three reported methods were not suitable for measurement of P35S in some testing events, because SNPs in binding sites of the primer/probe would result in abnormal amplification plots and poor linear regression parameters. In this study, we discovered a conserved region in the P35S sequence through sequencing of P35S promoters from multiple transgenic events, and developed new qualitative and quantitative detection systems targeting this conserved region. The qualitative PCR could detect the P35S promoter in 23 unique GMO events with high specificity and sensitivity. The quantitative method was suitable for measurement of P35S promoter, exhibiting good agreement between the amount of template and Ct values for each testing event. This study provides a general P35S screening method, with greater coverage than existing methods.
doi:10.1038/srep07358
PMCID: PMC4258656  PMID: 25483893
20.  Genome-wide association analysis identifies new lung cancer susceptibility loci in never-smoking women in Asia 
Lan, Qing | Hsiung, Chao A | Matsuo, Keitaro | Hong, Yun-Chul | Seow, Adeline | Wang, Zhaoming | Hosgood, H Dean | Chen, Kexin | Wang, Jiu-Cun | Chatterjee, Nilanjan | Hu, Wei | Wong, Maria Pik | Zheng, Wei | Caporaso, Neil | Park, Jae Yong | Chen, Chien-Jen | Kim, Yeul Hong | Kim, Young Tae | Landi, Maria Teresa | Shen, Hongbing | Lawrence, Charles | Burdett, Laurie | Yeager, Meredith | Yuenger, Jeffrey | Jacobs, Kevin B | Chang, I-Shou | Mitsudomi, Tetsuya | Kim, Hee Nam | Chang, Gee-Chen | Bassig, Bryan A | Tucker, Margaret | Wei, Fusheng | Yin, Zhihua | Wu, Chen | An, She-Juan | Qian, Biyun | Lee, Victor Ho Fun | Lu, Daru | Liu, Jianjun | Jeon, Hyo-Sung | Hsiao, Chin-Fu | Sung, Jae Sook | Kim, Jin Hee | Gao, Yu-Tang | Tsai, Ying-Huang | Jung, Yoo Jin | Guo, Huan | Hu, Zhibin | Hutchinson, Amy | Wang, Wen-Chang | Klein, Robert | Chung, Charles C | Oh, In-Jae | Chen, Kuan-Yu | Berndt, Sonja I | He, Xingzhou | Wu, Wei | Chang, Jiang | Zhang, Xu-Chao | Huang, Ming-Shyan | Zheng, Hong | Wang, Junwen | Zhao, Xueying | Li, Yuqing | Choi, Jin Eun | Su, Wu-Chou | Park, Kyong Hwa | Sung, Sook Whan | Shu, Xiao-Ou | Chen, Yuh-Min | Liu, Li | Kang, Chang Hyun | Hu, Lingmin | Chen, Chung-Hsing | Pao, William | Kim, Young-Chul | Yang, Tsung-Ying | Xu, Jun | Guan, Peng | Tan, Wen | Su, Jian | Wang, Chih-Liang | Li, Haixin | Sihoe, Alan Dart Loon | Zhao, Zhenhong | Chen, Ying | Choi, Yi Young | Hung, Jen-Yu | Kim, Jun Suk | Yoon, Ho-Il | Cai, Qiuyin | Lin, Chien-Chung | Park, In Kyu | Xu, Ping | Dong, Jing | Kim, Christopher | He, Qincheng | Perng, Reury-Perng | Kohno, Takashi | Kweon, Sun-Seog | Chen, Chih-Yi | Vermeulen, Roel | Wu, Junjie | Lim, Wei-Yen | Chen, Kun-Chieh | Chow, Wong-Ho | Ji, Bu-Tian | Chan, John K C | Chu, Minjie | Li1, Yao-Jen | Yokota, Jun | Li, Jihua | Chen, Hongyan | Xiang, Yong-Bing | Yu, Chong-Jen | Kunitoh, Hideo | Wu, Guoping | Jin, Li | Lo, Yen-Li | Shiraishi, Kouya | Chen, Ying-Hsiang | Lin, Hsien-Chih | Wu, Tangchun | Wu, Yi-Long | Yang, Pan-Chyr | Zhou, Baosen | Shin, Min-Ho | Fraumeni, Joseph F | Lin, Dongxin | Chanock, Stephen J | Rothman, Nathaniel
Nature genetics  2012;44(12):1330-1335.
To identify common genetic variants that contribute to lung cancer susceptibility, we conducted a multistage genome-wide association study of lung cancer in Asian women who never smoked. We scanned 5,510 never-smoking female lung cancer cases and 4,544 controls drawn from 14 studies from mainland China, South Korea, Japan, Singapore, Taiwan, and Hong Kong. We genotyped the most promising variants (associated at P < 5 × 10-6) in an additional 1,099 cases and 2,913 controls. We identified three new susceptibility loci at 10q25.2 (rs7086803, P = 3.54 × 10-18), 6q22.2 (rs9387478, P = 4.14 × 10-10) and 6p21.32 (rs2395185, P = 9.51 × 10-9). We also confirmed associations reported for loci at 5p15.33 and 3q28 and a recently reported finding at 17q24.3. We observed no evidence of association for lung cancer at 15q25 in never-smoking women in Asia, providing strong evidence that this locus is not associated with lung cancer independent of smoking.
doi:10.1038/ng.2456
PMCID: PMC4169232  PMID: 23143601
21.  Metallothionein III (MT3) is a putative tumor suppressor gene that is frequently inactivated in pediatric acute myeloid leukemia by promoter hypermethylation 
Background
Acute myeloid leukemia (AML) is the second most common form of leukemia in children. Aberrant DNA methylation patterns are a characteristic feature in various tumors, including AML. Metallothionein III (MT3) is a tumor suppresser reported to show promoter hypermethylated in various cancers. However, the expression and molecular function of MT3 in pediatric AML is unclear.
Methods
Eleven human leukemia cell lines and 41 pediatric AML samples and 20 NBM/ITP (Norma bone marrow/Idiopathic thrombocytopenic purpura) control samples were analyzed. Transcription levels of MT3 were evaluated by semi-quantitative and real-time PCR. MT3 methylation status was determined by methylation specific PCR (MSP) and bisulfite genomic sequencing (BSG). The molecular mechanism of MT3 was investigated by apoptosis assays and PCR array analysis.
Results
The MT3 promoter was hypermethylated in leukemia cell lines. More CpG’s methylated of MT3 was observed 39.0% pediatric AML samples compared to 10.0% NBM controls. Transcription of MT3 was also significantly decreased in AML samples compared to NBM/ITP controls (P < 0.001); patients with methylated MT3 exhibited lower levels of MT3 expression compared to those with unmethylated MT3 (P = 0.049). After transfection with MT3 lentivirus, proliferation was significantly inhibited in AML cells in a dose-dependent manner (P < 0.05). Annexin V assay showed that apoptosis was significantly upregulated MT3-overexpressing AML cells compared to controls. Real-time PCR array analysis revealed 34 dysregulated genes that may be implicated in MT3 overexpression and apoptosis in AML, including FOXO1.
Conclusion
MT3 may be a putative tumor suppressor gene in pediatric AML. Epigenetic inactivation of MT3 via promoter hypermethylation was observed in both AML cell lines and pediatric AML samples. Overexpression of MT3 may inhibit proliferation and induce apoptosis in AML cells. FOXO1 was dysregulated in MT3-overexpressing cells, offering an insight into the mechanism of MT3-induced apoptosis. However, further research is required to determine the underlying molecular details.
doi:10.1186/1479-5876-12-182
PMCID: PMC4082423  PMID: 24962166
Metallothionein III; Pediatric acute myeloid leukemia; Methylation; Tumor suppressor
22.  Variations in the MHC Region Confer Risk to Esophageal Squamous Cell Carcinoma on the Subjects from High-Incidence Area in Northern China 
PLoS ONE  2014;9(3):e90438.
Background
The human major histocompatibility complex (MHC) is the most important region in vertebrate genome, and is crucial in innate immunity. Recent studies have demonstrated the possible role of polymorphisms in the MHC region to high risk for esophageal squamous cell carcinoma (ESCC). Our previous genome-wide association study (GWAS) has indicated that the MHC region may confer important risk loci for ESCC, but without further fine mapping. The aim of this study is to further identify the risk loci in the MHC region for ESCC in Chinese population.
Methods
Conditional logistic regression analysis (CLRA) was performed on 24 single nucleotide polymorphisms (SNPs) within the MHC region, which were obtained from the genetically matched 937 cases and 692 controls of Chinese Han population. The identified promising SNPs were further correlated with clinical and clinicopathology characteristics. Immunohistochemistry was performed to explore the protein expression pattern of the related genes in ESCC and neighboring normal tissues.
Results
Of the 24 promising SNPs analyzed, we identified three independent SNPs in the MHC region associated with ESCC: rs35399661 (P = 6.07E-06, OR = 1.71, 95%CI = 1.36–2.17), rs3763338 (P = 1.62E-05, OR = 0.63, 95%CI = 0.50–0.78) and rs2844695 (P = 7.60E-05, OR = 0.74, 95%CI = 0.64–0.86). These three SNPs were located at the genes of HLA-DQA1, TRIM27, and DPCR1, respectively. Further analyses showed that rs2844695 was preferentially associated with younger ESCC cases (P = 0.009). The positive immunostaining rates both for HLA-DQA1 and TRIM27 were much higher in ESCC tissues than in neighboring normal tissues (69.4% vs. 26.8% for HLA-DQA1 and 77.6% vs. 47.8% for TRIM27, P<0.001). Furthermore, the overexpression of HLA-DQA1 is correlated significantly with age (P = 0.001) and family history (P<0.001).
Conclusion
This study for the first time provides evidence that multiple genetic factors within the MHC region confer risk to ESCC on the subjects from high-risk area in northern China.
doi:10.1371/journal.pone.0090438
PMCID: PMC3942432  PMID: 24595008
23.  Associations of Educational Attainment, Occupation, Social Class and Major Depressive Disorder among Han Chinese Women 
PLoS ONE  2014;9(1):e86674.
Background
The prevalence of major depressive disorder (MDD) is higher in those with low levels of educational attainment, the unemployed and those with low social status. However the extent to which these factors cause MDD is unclear. Most of the available data comes from studies in developed countries, and these findings may not extrapolate to developing countries. Examining the relationship between MDD and socio economic status in China is likely to add to the debate because of the radical economic and social changes occurring in China over the last 30 years.
Principal findings
We report results from 3,639 Chinese women with recurrent MDD and 3,800 controls. Highly significant odds ratios (ORs) were observed between MDD and full time employment (OR = 0.36, 95% CI = 0.25–0.46, logP = 78), social status (OR = 0.83, 95% CI = 0.77–0.87, logP = 13.3) and education attainment (OR = 0.90, 95% CI = 0.86–0.90, logP = 6.8). We found a monotonic relationship between increasing age and increasing levels of educational attainment. Those with only primary school education have significantly more episodes of MDD (mean 6.5, P-value = 0.009) and have a clinically more severe disorder, while those with higher educational attainment are likely to manifest more comorbid anxiety disorders.
Conclusions
In China lower socioeconomic position is associated with increased rates of MDD, as it is elsewhere in the world. Significantly more episodes of MDD occur among those with lower educational attainment (rather than longer episodes of disease), consistent with the hypothesis that the lower socioeconomic position increases the likelihood of developing MDD. The phenomenology of MDD varies according to the degree of educational attainment: higher educational attainment not only appears to protect against MDD but alters its presentation, to a more anxious phenotype.
doi:10.1371/journal.pone.0086674
PMCID: PMC3909008  PMID: 24497966
24.  A human gut microbial gene catalog established by metagenomic sequencing 
Nature  2010;464(7285):59-65.
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 nonredundant microbial genes, derived from 576.7 Gb 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 microbial genes of the cohort and likely 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, suggesting that the entire cohort harbours between 1000 and 1150 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 encoded by the gene set.
doi:10.1038/nature08821
PMCID: PMC3779803  PMID: 20203603
25.  Molecular footprints of domestication and improvement in soybean revealed by whole genome re-sequencing 
BMC Genomics  2013;14:579.
Background
Artificial selection played an important role in the origin of modern Glycine max cultivars from the wild soybean Glycine soja. To elucidate the consequences of artificial selection accompanying the domestication and modern improvement of soybean, 25 new and 30 published whole-genome re-sequencing accessions, which represent wild, domesticated landrace, and Chinese elite soybean populations were analyzed.
Results
A total of 5,102,244 single nucleotide polymorphisms (SNPs) and 707,969 insertion/deletions were identified. Among the SNPs detected, 25.5% were not described previously. We found that artificial selection during domestication led to more pronounced reduction in the genetic diversity of soybean than the switch from landraces to elite cultivars. Only a small proportion (2.99%) of the whole genomic regions appear to be affected by artificial selection for preferred agricultural traits. The selection regions were not distributed randomly or uniformly throughout the genome. Instead, clusters of selection hotspots in certain genomic regions were observed. Moreover, a set of candidate genes (4.38% of the total annotated genes) significantly affected by selection underlying soybean domestication and genetic improvement were identified.
Conclusions
Given the uniqueness of the soybean germplasm sequenced, this study drew a clear picture of human-mediated evolution of the soybean genomes. The genomic resources and information provided by this study would also facilitate the discovery of genes/loci underlying agronomically important traits.
doi:10.1186/1471-2164-14-579
PMCID: PMC3844514  PMID: 23984715
Artificial selection; Evolution; Genetic diversity; Population genomics; Soybean

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