Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Visualization Investigation on the Marine Data with Multivariate Statistical Analysis Methods

Marine information is an important way for us to know and study more about the ocean. Marine data makes the basic of marine information. Because of the huge quantity and diversity of marine data, and at the same time marine data is polyatomic variable, we start with statistical analysis methods to search for the regularity of the marine data. On one hand, we get the aggregate variation functions of the marine data by factor analyzing in aspect of the spatiality. Then we visually describe the marine status of the studied sea area with pre variogram function and post variogram function. On the other hand, we used cluster analysis method to get the verifying rule in time and make visible graphs of the marine data. In this way, we can also supply with the suggestions in classifying the sea seawater quality. The data processing result shows that the suggested methods in this article are both operable and effective. At the same time some reasonable suggestions are given in the article

Appl. Phys. Lett.

A lack of dependence of the Raman frequency of optical vibrational modes on excitation wavelength in polar nanosemiconductors was observed. This is in contrast to the earlier observed dependence in nonpolar nanomaterials: carbon nanotubes and Si nanowires. This difference has been ascribed to the different crystallographic natures of their Raman spectra: crystalline for nonpolar and amorphous for polar nanosemiconductors. The result has been explored theoretically to the Raman spectra being insensitive to sample sizes and thus indicates that the size confinement effect, a basic effect in nanomaterials, does not exhibit in the optical vibrational modes of polar nanosemiconductors. (c) 2006 American Institute of Physics.A lack of dependence of the Raman frequency of optical vibrational modes on excitation wavelength in polar nanosemiconductors was observed. This is in contrast to the earlier observed dependence in nonpolar nanomaterials: carbon nanotubes and Si nanowires. This difference has been ascribed to the different crystallographic natures of their Raman spectra: crystalline for nonpolar and amorphous for polar nanosemiconductors. The result has been explored theoretically to the Raman spectra being insensitive to sample sizes and thus indicates that the size confinement effect, a basic effect in nanomaterials, does not exhibit in the optical vibrational modes of polar nanosemiconductors. (c) 2006 American Institute of Physics

A Genetic Variant in <em>pre-miR-27a</em> Is Associated with a Reduced Renal Cell Cancer Risk in a Chinese Population

<div><h3>Background</h3><p>MicroRNAs (miRNAs) are a class of small non-coding RNAs to regulate cell differentiation, proliferation, development, and apoptosis. The single nucleotide polymorphism (SNP) rs895819 is located at the terminal loop of <em>pre-miR-27a</em>. Here, we aimed to investigate whether SNP rs895819 was associated with the development of renal cell cancer (RCC) in a Chinese population.</p> <h3>Methods</h3><p>In this case-control study, we recruited 594 RCC patients and 600 cancer-free controls with frequency matched by age and sex. We genotyped this polymorphism using the TaqMan assay and assessed the effect of this polymorphism on RCC survival. Logistic regression model was used to assess the genetic effects on the development of RCC and interactions between rs895819 polymorphism and risk factors.</p> <h3>Results</h3><p>Compared with AA homozygote, individuals carrying AG/GG genotypes had a statistically significant reduced susceptibility to RCC (adjusted OR = 0.71, 95% CI = 0.56–0.90). Furthermore, AG/GG genotypes were associated with reduced RCC susceptibility in localized clinical stage (adjusted OR = 0.71, 95% CI = 0.55–0.91), and similar effects were observed in well differentiated and poorly differentiated RCC (adjusted OR = 0.71, 95% CI = 0.55–0.93 for well differentiated, adjusted OR = 0.51, 95% CI = 0.28–0.93 for poorly differentiated). We also observed that rs895819 had multiplicative interactions with age and hypertension. However, the polymorphism did not influence the survival of RCC.</p> <h3>Conclusion</h3><p>Our results suggest that the <em>pre-miR-27a</em> rs895819 polymorphism can predict RCC risk in a Chinese population. Larger population-based prospective studies should be used to validate our findings.</p> </div

Associations between rs895819 polymorphism and clinical characteristics of RCC.

a<p>Adjusted for age, sex, smoking, drinking status, diabetes and hypertension in logistic regression model.</p

Distribution of selected variables between the RCC cases and control subjects.

a<p>Student's t-test for age and BMI distributions between cases and controls; two-sided χ² test for other selected variables between cases and controls.</p><p>SD, standard deviation; BMI, body mass index.</p

DNA sequencing chromatograms of three different samples of PCR products confirmed rs895819 polymorphism.

<p>(A) Double peaks labeled with an arrow represented the heterozygous genotype TC (AG). (B) Single peak labeled with an arrow represented the homozygous genotype TT (AA). (C) Single peak labeled with an arrow represented the homozygous genotype CC (GG).</p

Stratification analyses between the genotypes of rs895819 polymorphism and RCC risk.

a<p>Adjusted for age, sex, smoking, drinking status, diabetes and hypertension in logistic regression model. CI, confidence interval; OR, odds ratio.</p