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BACKGROUND & AIMS Zinc-fingers and homeoboxes 2 (ZHX2) represses transcription of several genes associated with liver cancer. However, little is known about the role of ZHX2 in development of hepatocellular carcinoma (HCC). We investigated the mechanisms by which ZHX2 might affect proliferation of HCC cells. METHODS We overexpressed and knocked down ZHX2 in HCC cells and analyzed the effects on proliferation, colony formation, and the cell cycle. We also analyzed the effects of ZHX2 overexpression in growth of HepG2.2.15 tumor xenografts in nude mice. Chromatin immunoprecipitation and luciferase reporter assays were used to measure binding of ZHX2 target promoters. Levels of ZHX2 in HCC samples were evaluated by immunohistochemistry. RESULTS ZHX2 overexpression significantly reduced proliferation of HCC cells and growth of tumor xenografts in mice; it led to G1 arrest and reduced levels of cyclins A and E in HCC cell lines. ZHX2 bound to promoter regions of CCNA2 (which encodes Cyclin A) and CCNE1 (which encodes cyclin E) and inhibited their transcription. Knockdown of cyclin A or cyclin E reduced the increased proliferation mediated by ZHX2 knockdown. Nuclear localization of ZHX2 was required for it to inhibit proliferation of HCC cells in culture and in mice. Nuclear localization of ZHX2 was reduced in human HCC samples, even in small tumors (diameter<5 cm), compared to adjacent non-tumor tissues. Moreover, reduced nuclear levels of ZHX2 correlated with reduced survival times of patients, high levels of tumor microvascularization, and hepatocyte proliferation. CONCLUSIONS ZHX2 inhibits HCC cell proliferation, by preventing expression of cyclins A and E, and reduces growth of xenograft tumors in mice. Loss of nuclear ZHX2 might be an early step in the development of HCC.

BackgroundGrowth and meat production traits are significant economic traits in sheep. The aim of the study is to identify candidate genes affecting growth and meat production traits at genome level with high throughput single nucleotide polymorphisms (SNP) genotyping technologies.Methodology and ResultsUsing Illumina OvineSNP50 BeadChip, we performed a GWA study in 329 purebred sheep for 11 growth and meat production traits (birth weight, weaning weight, 6-month weight, eye muscle area, fat thickness, pre-weaning gain, post-weaning gain, daily weight gain, height at withers, chest girth, and shin circumference). After quality control, 319 sheep and 48,198 SNPs were analyzed by TASSEL program in a mixed linear model (MLM). 36 significant SNPs were identified for 7 traits, and 10 of them reached genome-wise significance level for post-weaning gain. Gene annotation was implemented with the latest sheep genome Ovis_aries_v3.1 (released October 2012). More than one-third SNPs (14 out of 36) were located within ovine genes, others were located close to ovine genes (878bp-398,165bp apart). The strongest new finding is 5 genes were thought to be the most crucial candidate genes associated with post-weaning gain: s58995.1 was located within the ovine genes MEF2B and RFXANK, OAR3_84073899.1, OAR3_115712045.1 and OAR9_91721507.1 were located within CAMKMT, TRHDE, and RIPK2 respectively. GRM1, POL, MBD5, UBR2, RPL7 and SMC2 were thought to be the important candidate genes affecting post-weaning gain too. Additionally, 25 genes at chromosome-wise significance level were also forecasted to be the promising genes that influencing sheep growth and meat production traits.ConclusionsThe results will contribute to the similar studies and facilitate the potential utilization of genes involved in growth and meat production traits in sheep in future.

Land plants in natural soil form intimate relationships with the diverse root bacterial microbiota. A growing body of evidence shows that these microbes are important for plant growth and health. Root microbiota composition has been widely studied in several model plants and crops; however, little is known about how root microbiota vary throughout the plant's life cycle under field conditions. We performed longitudinal dense sampling in field trials to track the time-series shift of the root microbiota from two representative rice cultivars in two separate locations in China. We found that the rice root microbiota varied dramatically during the vegetative stages and stabilized from the beginning of the reproductive stage, after which the root microbiota underwent relatively minor changes until rice ripening. Notably, both rice genotype and geographical location influenced the patterns of root microbiota shift that occurred during plant growth. The relative abundance of Deltaproteobacteria in roots significantly increased overtime throughout the entire life cycle of rice, while that of Betaproteobacteria, Firmicutes, and Gammaproteobacteria decreased. By a machine learning approach, we identified biomarker taxa and established a model to correlate root microbiota with rice resident time in the field (e.g., Nitrospira accumulated from 5 weeks/tillering in field-grown rice). Our work provides insights into the process of rice root microbiota establishment.

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