Conservation and implications of eukaryote transcriptional regulatory regions across multiple species

<p>Abstract</p> <p>Background</p> <p>Increasing evidence shows that whole genomes of eukaryotes are almost entirely transcribed into both protein coding genes and an enormous number of non-protein-coding RNAs (ncRNAs). Therefore, revealing the underlying regulatory mechanisms of transcripts becomes imperative. However, for a complete understanding of transcriptional regulatory mechanisms, we need to identify the regions in which they are found. We will call these transcriptional regulation regions, or TRRs, which can be considered functional regions containing a cluster of regulatory elements that cooperatively recruit transcriptional factors for binding and then regulating the expression of transcripts.</p> <p>Results</p> <p>We constructed a hierarchical stochastic language (HSL) model for the identification of core TRRs in yeast based on regulatory cooperation among TRR elements. The HSL model trained based on yeast achieved comparable accuracy in predicting TRRs in other species, e.g., fruit fly, human, and rice, thus demonstrating the conservation of TRRs across species. The HSL model was also used to identify the TRRs of genes, such as p53 or <it>OsALYL1</it>, as well as microRNAs. In addition, the ENCODE regions were examined by HSL, and TRRs were found to pervasively locate in the genomes.</p> <p>Conclusion</p> <p>Our findings indicate that 1) the HSL model can be used to accurately predict core TRRs of transcripts across species and 2) identified core TRRs by HSL are proper candidates for the further scrutiny of specific regulatory elements and mechanisms. Meanwhile, the regulatory activity taking place in the abundant numbers of ncRNAs might account for the ubiquitous presence of TRRs across the genome. In addition, we also found that the TRRs of protein coding genes and ncRNAs are similar in structure, with the latter being more conserved than the former.</p

Hybridization modeling of oligonucleotide SNP arrays for accurate DNA copy number estimation

Affymetrix SNP arrays have been widely used for single-nucleotide polymorphism (SNP) genotype calling and DNA copy number variation inference. Although numerous methods have achieved high accuracy in these fields, most studies have paid little attention to the modeling of hybridization of probes to off-target allele sequences, which can affect the accuracy greatly. In this study, we address this issue and demonstrate that hybridization with mismatch nucleotides (HWMMN) occurs in all SNP probe-sets and has a critical effect on the estimation of allelic concentrations (ACs). We study sequence binding through binding free energy and then binding affinity, and develop a probe intensity composite representation (PICR) model. The PICR model allows the estimation of ACs at a given SNP through statistical regression. Furthermore, we demonstrate with cell-line data of known true copy numbers that the PICR model can achieve reasonable accuracy in copy number estimation at a single SNP locus, by using the ratio of the estimated AC of each sample to that of the reference sample, and can reveal subtle genotype structure of SNPs at abnormal loci. We also demonstrate with HapMap data that the PICR model yields accurate SNP genotype calls consistently across samples, laboratories and even across array platforms

The prognosis of Different Types of Reciprocal ST-segment Depression (R-ST-D) on Electrocardiograms in Acute Myocardial Infarction

Summary: Background: We investigated how to define the culprit coronary artery according to different reciprocal ST-segment depression (R-ST-D) types on electrocardiograms in ST-segment elevation acute myocardial infarction (STEMI), as well as the high-risk factors. Methods: To analyze the prognosis of different R-ST-D types to define the culprit coronary artery and high-risk factors, 967 patients with STEMI were included and divided into four groups according to STEMI infarction sites and R-ST-D type: group I (type I), without R-ST-D (n = 143); group II (type II), R-ST-D less than or equal to the amplitude of ST-segment elevation (n = 664); group III (type III), R-ST-D greater than or equal to the amplitude of ST-segment elevation (n = 93); and group IV (type IV), the amplitudes of R-ST-D and ST-segment elevation were both elevated (n = 67). Results: The incidence of type II was the highest at 68.7%, followed by that of type I, which was mainly due to anterior descending branch stenosis. Type IV was mainly caused by complete occlusion of multiple vessels including the anterior descending branch and circumflex branch and/or right coronary artery. Type III was always related to a higher incidence of malignant complications, ventricular wall motion disorders, and ejection fraction index ≤50% compared with types I and II (p < 0.05 and p < 0.01, respectively). Conclusion: Different high-risk stratifications of R-ST-D in patients with STEMI, especially type III and IV, can be used as objective independent indices to predict and assess the culprit coronary artery and life-threatening prognosis. Keywords: myocardial infarction, reciprocal ST-segment, type, prognosi

Preparation and Hydrogen Storage Properties of Mg-Rich Mg-Ni Ultrafine Particles

In the present work, Mg-rich Mg-Ni ultrafine powders were prepared through an arc plasma method. The phase components, microstructure, and hydrogen storage properties of the powders were carefully investigated. It is found that Mg2Ni and MgNi2 could be obtained directly from the vapor state reactions between Mg and Ni, depending on the local vapor content in the reaction chamber. A nanostructured MgH2 + Mg2NiH4 hydrogen storage composite could be generated after hydrogenation of the Mg-Ni ultrafine powders. After dehydrogenation, MgH2 and Mg2NiH4 decomposed into nanograined Mg and Mg2Ni, respectively. Thermogravimetry/differential scanning calorimetry (TG/DSC) analyses showed that Mg2NiH4 phase may play a catalytic role in the dehydriding process of the hydrogenated Mg ultrafine particles

<i>Funneliformis mosseae</i> Inoculation Enhances <i>Cucurbita pepo</i> L. Plant Growth and Fruit Yield by Reshaping Rhizosphere Microbial Community Structure

Arbuscular mycorrhizal fungi (AMF) are essential components of the soil microbiome that can facilitate plant growth and enhance abiotic and biotic stress resistance. However, the mechanisms via which AMF inoculation influences Cucurbita pepo L. plant growth and fruit yield remain unclear. Here, we conducted pot experiments to investigate bacterial and fungal community structure in the rhizosphere of C. pepo plants inoculated with Funneliformis mosseae (Nicoll. & Gerd.) Gerd. & Trappe based on 16S ribosomal RNA and internal transcribed spacer gene sequencing. The α-diversity of bacteria increased significantly following F. mosseae inoculation, whereas the α-diversity of fungi exhibited an opposite trend (p F. mosseae inoculation led to remarkable enrichment of potentially beneficial taxa (e.g., Streptomyces, Sphingomonas, Lysobacter, and Trichoderma), in stark contrast to depletion of fungal pathogens (e.g., Botryotrichum, Acremonium, Fusarium, and Plectosphaerella). Pathways related to amino acid metabolism and antibiotic biosynthesis were upregulated by F. mosseae inoculation, whereas pathways involved in infectious diseases were downregulated. The results suggest that F. mosseae inoculation reshapes the rhizosphere microbiome, thereby augmenting C. pepo plant growth and fruit yield

Comparison of oxidative stress biomarkers in hypertensive patients with or without hyperhomocysteinemia

Hyperhomocysteinemia is an independent risk factor for cardiovascular impairment in hypertension. Oxidative stress is important in the molecular mechanisms associated with hypertension, but there are few studies focusing on the comparison of oxidative stress biomarkers in hypertensive patients with or without hyperhomocysteinemia. The study included 50 newly diagnosed hypertensive patients with hyperhomocysteinemia, 50 newly diagnosed hypertensive patients without hyperhomocysteinemia, and 50 age-matched healthy controls. Serum levels of malondialdehyde, nitric oxide, 8-isoprostane-F2ɑ, superoxide dismutase, catalase, and glutathione peroxides were compared. Levels of malondialdehyde and 8-isoprostane-F2ɑ were higher in both hypertensive groups than in the control group (8.3 ± 1.8 μmol/L vs. 6.5 ± 1.3 μmol/L vs. 4.3 ± 1.2 μmol/L, P < 0.05; 23.5 ± 12.1 pg/mL vs. 17.4 ± 10.3 pg/mL vs. 13.9 ± 7.5 pg/mL, P < 0.05), while levels of superoxide dismutase and catalase were lower in both hypertensive groups than in the control group (120.5 ± 13.7 U/mL vs. 131.3 ± 18.2 U/mL vs. 149.1 ± 14.6 U/mL, P < 0.05; 23.8 ± 7.4 U/mL vs. 24.6 ± 9.2 U/mL vs. 33.5 ± 8.2 U/mL, P < 0.05). In hypertensive subgroups, serum malondialdehyde levels were higher in the hyperhomocysteinemia group than the other group (8.3 ± 1.8 μmol/L vs. 6.5 ± 1.3 μmol/L; P < 0.05), and superoxide dismutase activities were lower in the hyperhomocysteinemia group than the other group (120.5 ± 13.7 U/mL vs. 131.3 ± 18.2 U/mL; P < 0.05). Moreover, in hypertensive patients, homocysteine levels were significantly correlated with malondialdehyde (r = 0.39, P < 0.01), 8-isoprostane-F2ɑ (r = 0.47, P < 0.05), superoxide dismutase (r = −0.51, P < 0.01), and catalase (r = −0.51, P < 0.05), respectively. Our findings demonstrated oxidative stress was more severe in hypertensive patients with hyperhomocysteinemia than those hypertensive patients without it. Besides, there were strong relationships between homocysteine activities and oxidative/antioxidative parameters, which indicated that homocysteine might aggravate the oxidative stress in hypertension to produce contributory effects on cardiovascular impairment