ABCG2: A potential marker of stem cells and novel target in stem cell and cancer therapy

ABCG2 is a member of the ATP binding cassette (ABC) transporters, which can pump a wide variety of endogenous and exogenous compounds out of cells. Widely expressed in stem cells, ABCG2 is also found to confer the side population phenotype and is recognized as a universal marker of stem cells. Although the precise physiological role of ABCG2 in stem cells is still unclear, existing data strongly suggest that ABCG2 plays an important role in promoting stem cell proliferation and the maintenance of the stem cell phenotype. In addition, ABCG2 is also found to be expressed in a number of cancer cells and appears to be a marker of cancer stem cells. Moreover, ABCG2 expression in tumors may contribute to their formation and progression. Thus, ABCG2 has potential applications in stem cell and tumor therapy.     

Improving the accuracy of genomic prediction in Chinese Holstein cattle by using one-step blending

Background

The one-step blending approach has been suggested for genomic prediction in dairy cattle. The core of this approach is to incorporate pedigree and phenotypic information of non-genotyped animals. The objective of this study was to investigate the improvement of the accuracy of genomic prediction using the one-step blending method in Chinese Holstein cattle.

Findings

Three methods, GBLUP (genomic best linear unbiased prediction), original one-step blending with a genomic relationship matrix, and adjusted one-step blending with an adjusted genomic relationship matrix, were compared with respect to the accuracy of genomic prediction for five milk production traits in Chinese Holstein. For the two one-step blending methods, de-regressed proofs of 17 509 non-genotyped cows, including 424 dams and 17 085 half-sisters of the validation cows, were incorporated in the prediction model. The results showed that, averaged over the five milk production traits, the one-step blending increased the accuracy of genomic prediction by about 0.12 compared to GBLUP. No further improvement in accuracies was obtained from the adjusted one-step blending over the original one-step blending in our situation. Improvements in accuracies obtained with both one-step blending methods were almost completely contributed by the non-genotyped dams.

Conclusions

Compared with GBLUP, the one-step blending approach can significantly improve the accuracy of genomic prediction for milk production traits in Chinese Holstein cattle. Thus, the one-step blending is a promising approach for practical genomic selection in Chinese Holstein cattle, where the reference population mainly consists of cows.     

1H-NMR and MS Based Metabolomics Study of the Intervention Effect of Curcumin on Hyperlipidemia Mice Induced by High-Fat Diet

Curcumin, a principle bioactive component of Curcuma longa L, is well known for its anti-hyperlipidemia effect. However, no holistic metabolic information of curcumin on hyperlipidemia models has been revealed, which may provide us an insight into the underlying mechanism. In the present work, NMR and MS based metabolomics was conducted to investigate the intervention effect of curcumin on hyperlipidemia mice induced by high-fat diet (HFD) feeding for 12 weeks. The HFD induced animals were orally administered with curcumin (40, 80 mg/kg) or lovastatin (30 mg/kg, positive control) once a day during the inducing period. Serum biochemistry assay of TC, TG, LDL-c, and HDL-c was conducted and proved that treatment of curcumin or lovastatin can significantly improve the lipid profiles. Subsequently, metabolomics analysis was carried out for urine samples. Orthogonal Partial Least Squares-Discriminant analysis (OPLS-DA) was employed to investigate the anti-hyperlipidemia effect of curcumin and to detect related potential biomarkers. Totally, 35 biomarkers were identified, including 31 by NMR and nine by MS (five by both). It turned out that curcumin treatment can partially recover the metabolism disorders induced by HFD, with the following metabolic pathways involved: TCA cycle, glycolysis and gluconeogenesis, synthesis of ketone bodies and cholesterol, ketogenesis of branched chain amino acid, choline metabolism, and fatty acid metabolism. Besides, NMR and MS based metabolomics proved to be powerful tools in investigating pharmacodynamics effect of natural products and underlying mechanisms.     

Genome engineering of Agrobacterium tumefaciens using the lambda Red recombination system

Agrobacterium tumefaciens has been widely used as a tool for transgenesis in plants. The availability of its genome sequence should facilitate the directed engineering of improved properties; however, the current genome engineering options are laborious. Here, we investigated whether the lambda R ed operon can be applied for recombineering of the A. tumefaciens genome. First, we built an expression plasmid for A. tumefaciens employing a tetracycline-inducible promoter to regulate the Red operon. This multicopy plasmid was then itself modified in A. tumefaciens to verify that the Red operon was functional. Then, we modified the endogenous A. tumefaciens tumor-inducing plasmid and the linear chromosome. These results extend recombineering technology to a new host and indicate a fast and convenient way to engineer the A. tumefaciens genome for functional genomics and strain improvements.     

RT-PCR heteroduplex analysis permits differentiation of transgene and host gene expression in a transgenic animal model

In transgenic animal models, the conservation of DNA sequences between the transgene and the host wild-type gene can complicate the evaluation of the expression of each gene. The potential for gene silencing may complicate matters further. Here we report the use of RT-PCR heteroduplex analysis to differentiate the expression of a transgene and its homologous wild-type, even when these genes are very similar in their respective DNA sequences. We designed RT-PCR primers to amplify identically sized 243-bp fragments within the DNA binding domain of the p53 gene from both human and mouse mRNA samples. Ten samples from human p53 (273H) transgenic mice and 10 samples from wild-type controls were tested. Heteroduplex bands were formed in all transgenic samples but were absent from all wild-type samples. In addition, RT-PCR heteroduplex analysis was able in one sample to differentiate a silenced transgene from its wild-type allele, without the assistance of sequencing or labeling. In summary, the RT-PCR heteroduplex analysis is easy to use and has the ability to screen a large number of samples in a short time. The RT-PCR heteroduplex analysis is especially useful for the detection of expression when a transgene and the host homologous endogenous allele are too conserved in sequence to design species-specific RT-PCR primers.     

云南禄丰古猿地点的松鼠类化石

记述了云南禄丰晚中新世石灰坝古猿地点发现的松鼠科化石。禄丰石灰坝动物群的松鼠动物共有 7属 7种 :地松鼠Sciurotamiaswangisp .nov .,树松鼠Tamiopssp .、Callosciurussp .、Dremomysprimitivussp .nov .和飞松鼠Miopetauristaasiaticasp .nov .、Hylopetodondianensegen .etsp.nov.、Pteromyinaegen.etsp .indet.。该动物群松鼠类动物的组成以树松鼠和飞松鼠为主 ,反映了较为湿润的热带—亚热带森林环境。在动物地理上 ,其成员几乎局限于东南亚分布 ,具有浓厚的现代东洋界色彩     

Association between variants of EXT2 and type 2 diabetes: a replication and meta-analysis

Recent publications have found an association between variants of exostosin 2 (EXT2) gene and the risk of type 2 diabetes in some population but not in others. In an attempt to address these inconsistencies, we investigated EXT2 variants in two independent cohorts, and conducted a literature-based meta-analysis. Through regression model, we assessed the relationship between the EXT2 single nucleotide polymorphisms (SNPs) (rs3740878, rs11037909 and rs1113132) and the risk of type 2 diabetes in Han Chinese population, including a total of 2,533 cases and 2,643 controls. We combined our data with that from previously published studies and performed a meta-analysis to evaluate the effect size of the gene. Consistent with some studies, we found marginal association for the rs3740878 (OR = 1.07, 95 % CI = 0.99, 1.16, p = 0.09), rs11037909 (OR = 1.07, 95 % CI = 0.99, 1.16, p = 0.08), and rs1113132 (OR = 1.08, 95 % CI = 1.00, 1.17, p = 0.06) in our 2 cohorts. Meta-analysis, comprising 9,224 type 2 diabetes and 10,484 controls, revealed that three SNPs (rs3740878, rs11037909 and rs1113132) in EXT2 were significantly associated with type 2 diabetes (ORs range from 1.06 to 1.07, p = 0.038, p = 0.008 and p = 0.005, respectively). Variation in the EXT2 locus appears to be associated with a small increase in the risk of type 2 diabetes. However, well-designed prospective studies with larger sample size and more ethnic groups are needed to further validate the results.