REPdenovo: Inferring De Novo Repeat Motifs from Short Sequence Reads.

Repeat elements are important components of eukaryotic genomes. One limitation in our understanding of repeat elements is that most analyses rely on reference genomes that are incomplete and often contain missing data in highly repetitive regions that are difficult to assemble. To overcome this problem we develop a new method, REPdenovo, which assembles repeat sequences directly from raw shotgun sequencing data. REPdenovo can construct various types of repeats that are highly repetitive and have low sequence divergence within copies. We show that REPdenovo is substantially better than existing methods both in terms of the number and the completeness of the repeat sequences that it recovers. The key advantage of REPdenovo is that it can reconstruct long repeats from sequence reads. We apply the method to human data and discover a number of potentially new repeats sequences that have been missed by previous repeat annotations. Many of these sequences are incorporated into various parasite genomes, possibly because the filtering process for host DNA involved in the sequencing of the parasite genomes failed to exclude the host derived repeat sequences. REPdenovo is a new powerful computational tool for annotating genomes and for addressing questions regarding the evolution of repeat families. The software tool, REPdenovo, is available for download at https://github.com/Reedwarbler/REPdenovo

MALT1 regulates Th2 and Th17 differentiation via NF-κB and JNK pathways, as well as correlates with disease activity and treatment outcome in rheumatoid arthritis

ObjectiveMALT1 regulates immunity and inflammation in multiple ways, while its role in rheumatoid arthritis (RA) is obscure. This study aimed to investigate the relationship of MALT1 with disease features, treatment outcome, as well as its effect on Th1/2/17 cell differentiation and underlying molecule mechanism in RA.MethodsTotally 147 RA patients were enrolled. Then their blood Th1, Th2, and Th17 cells were detected by flow cytometry. Besides, PBMC MALT1 expression was detected before treatment (baseline), at week (W) 6, W12, and W24. PBMC MALT1 in 30 osteoarthritis patients and 30 health controls were also detected. Then, blood CD4+ T cells were isolated from RA patients, followed by MALT1 overexpression or knockdown lentivirus transfection and Th1/2/17 polarization assay. In addition, IMD 0354 (NF-κB antagonist) and SP600125 (JNK antagonist) were also added to treat CD4+ T cells.ResultsMALT1 was increased in RA patients compared to osteoarthritis patients and healthy controls. Meanwhile, MALT1 positively related to CRP, ESR, DAS28 score, Th17 cells, negatively linked with Th2 cells, but did not link with other features or Th1 cells in RA patients. Notably, MALT1 decreased longitudinally during treatment, whose decrement correlated with RA treatment outcome (treatment response, low disease activity, or disease remission). In addition, MALT1 overexpression promoted Th17 differentiation, inhibited Th2 differentiation, less affected Th1 differentiation, activated NF-κB and JNK pathways in RA CD4+ T cells; while MALT1 knockdown exhibited the opposite effect. Besides, IMD 0354 and SP600125 addition attenuated MALT1’s effect on Th2 and Th17 differentiation.ConclusionMALT1 regulates Th2 and Th17 differentiation via NF-κB and JNK pathways, as well as correlates with disease activity and treatment outcome in RA

IsoDOT Detects Differential RNA-isoform Expression/Usage with respect to a Categorical or Continuous Covariate with High Sensitivity and Specificity

We have developed a statistical method named IsoDOT to assess differential isoform expression (DIE) and differential isoform usage (DIU) using RNA-seq data. Here isoform usage refers to relative isoform expression given the total expression of the corresponding gene. IsoDOT performs two tasks that cannot be accomplished by existing methods: to test DIE/DIU with respect to a continuous covariate, and to test DIE/DIU for one case versus one control. The latter task is not an uncommon situation in practice, e.g., comparing paternal and maternal allele of one individual or comparing tumor and normal sample of one cancer patient. Simulation studies demonstrate the high sensitivity and specificity of IsoDOT. We apply IsoDOT to study the effects of haloperidol treatment on mouse transcriptome and identify a group of genes whose isoform usages respond to haloperidol treatment

Genomic Takeover by Transposable Elements in the Strawberry Poison Frog

We sequenced the genome of the strawberry poison frog, Oophaga pumilio, at a depth of 127.5× using variable insert size libraries. The total genome size is estimated to be 6.76 Gb, of which 4.76 Gb are from high copy number repetitive elements with low differentiation across copies. These repeats encompass DNA transposons, RNA transposons, and LTR retrotransposons, including at least 0.4 and 1.0 Gb of Mariner/Tc1 and Gypsy elements, respectively. Expression data indicate high levels of gypsy and Mariner/Tc1 expression in ova of O. pumilio compared with Xenopus laevis. We further observe phylogenetic evidence for horizontal transfer (HT) of Mariner elements, possibly between fish and frogs. The elements affected by HT are present in high copy number and are highly expressed, suggesting ongoing proliferation after HT. Our results suggest that the large amphibian genome sizes, at least partially, can be explained by a process of repeated invasion of new transposable elements that are not yet suppressed in the germline. We also find changes in the spliceosome that we hypothesize are related to permissiveness of O. pumilio to increases in intron length due to transposon proliferation. Finally, we identify the complement of ion channels in the first genomic sequenced poison frog and discuss its relation to the evolution of autoresistance to toxins sequestered in the skin

Clinical Usefulness of Measuring Red Blood Cell Distribution Width in Patients with Hepatitis B

BACKGROUND: Red blood cell distribution width (RDW), an automated measure of red blood cell size heterogeneity (e.g., anisocytosis) that is largely overlooked, is a newly recognized risk marker in patients with cardiovascular diseases, but its role in persistent viral infection has not been well-defined. The present study was designed to investigate the association between RDW values and different disease states in hepatitis B virus (HBV)-infected patients. In addition, we analyzed whether RDW is associated with mortality in the HBV-infected patients. METHODOLOGY/PRINCIPAL FINDINGS: One hundred and twenty-three patients, including 16 with acute hepatitis B (AHB), 61 with chronic hepatitis B (CHB), and 46 with chronic severe hepatitis B (CSHB), and 48 healthy controls were enrolled. In all subjects, a blood sample was collected at admission to examine liver function, renal function, international normalized ratio and routine hematological testing. All patients were followed up for at least 4 months. A total of 10 clinical chemistry, hematology, and biochemical variables were analyzed for possible association with outcomes by using Cox proportional hazards and multiple regression models. RDW values at admission in patients with CSHB (18.30±3.11%, P<0.001), CHB (16.37±2.43%, P<0.001) and AHB (14.38±1.72%, P<0.05) were significantly higher than those in healthy controls (13.03±1.33%). Increased RDW values were clinically associated with severe liver disease and increased 3-month mortality rate. Multivariate analysis demonstrated that RDW values and the model for end-stage liver disease score were independent predictors for mortality (both P<0.001). CONCLUSION: RDW values are significantly increased in patients with hepatitis B and associated with its severity. Moreover, RDW values are an independent predicting factor for the 3-month mortality rate in patients with hepatitis B

Association of Adiponectin SNP+45 and SNP+276 with Type 2 Diabetes in Han Chinese Populations: A Meta-Analysis of 26 Case-Control Studies

Recently, many studies have reported that the SNP+45(T>G) and SNP+276(G>T) polymorphisms in the adiponectin gene are associated with type 2 diabetes (T2DM) in the Chinese Han population. However, the previous studies yielded many conflicting results. Thus, a meta-analysis of the association of the adiponectin gene with T2DM in the Chinese Han population is required. In the current study, we first determined the distribution of the adiponectin SNP+276 polymorphism in T2DM and nondiabetes (NDM) control groups. Our results suggested that the genotype and allele frequencies for SNP+276 did not differ significantly between the T2DM and NDM groups. Then, a meta-analysis of 23 case-control studies of SNP+45, with a total of 4161 T2DM patients and 3709 controls, and 11 case-control studies of SNP+276, with 2533 T2DM patients and 2212 controls, was performed. All subjects were Han Chinese. The fixed-effects model and random-effects model were applied for dichotomous outcomes to combine the results of the included studies. The results revealed a trend towards an increased risk of T2DM for the SNP+45G allele as compared with the SNP+45T allele (OR = 1.34; 95% CI, 1.11–1.62; P<0.01) in the Chinese Han population. However, there was no association between SNP+276 and T2DM (OR = 0.90; 95% CI, 0.73–1.10; P = 0.31). The results of our association study showed there was no association between the adiponectin SNP+276 polymorphism and T2DM in the Yunnan Han population. The meta-analysis results suggested that the SNP+45G allele might be a susceptibility allele for T2DM in the Chinese Han population. However, we did not observe an association between SNP+276 and T2DM

Principal variable selection to explain grain yield variation in winter wheat from features extracted from UAV imagery

Background: Automated phenotyping technologies are continually advancing the breeding process. However, collecting various secondary traits throughout the growing season and processing massive amounts of data still take great efforts and time. Selecting a minimum number of secondary traits that have the maximum predictive power has the potential to reduce phenotyping efforts. The objective of this study was to select principal features extracted from UAV imagery and critical growth stages that contributed the most in explaining winter wheat grain yield. Five dates of multispectral images and seven dates of RGB images were collected by a UAV system during the spring growing season in 2018. Two classes of features (variables), totaling to 172 variables, were extracted for each plot from the vegetation index and plant height maps, including pixel statistics and dynamic growth rates. A parametric algorithm, LASSO regression (the least angle and shrinkage selection operator), and a non-parametric algorithm, random forest, were applied for variable selection. The regression coefficients estimated by LASSO and the permutation importance scores provided by random forest were used to determine the ten most important variables influencing grain yield from each algorithm. Results: Both selection algorithms assigned the highest importance score to the variables related with plant height around the grain filling stage. Some vegetation indices related variables were also selected by the algorithms mainly at earlier to mid growth stages and during the senescence. Compared with the yield prediction using all 172 variables derived from measured phenotypes, using the selected variables performed comparable or even better. We also noticed that the prediction accuracy on the adapted NE lines (r = 0.58–0.81) was higher than the other lines (r = 0.21–0.59) included in this study with different genetic backgrounds. Conclusions: With the ultra-high resolution plot imagery obtained by the UAS-based phenotyping we are now able to derive more features, such as the variation of plant height or vegetation indices within a plot other than just an averaged number, that are potentially very useful for the breeding purpose. However, too many features or variables can be derived in this way. The promising results from this study suggests that the selected set from those variables can have comparable prediction accuracies on the grain yield prediction than the full set of them but possibly resulting in a better allocation of efforts and resources on phenotypic data collection and processing

3D ITO-nanowire networks as transparent electrode for all-terrain substrate

A 3D ITO nanowire network with high quality by using polystyrene as an assisted material has been prepared, demonstrating superior optoelectronic performances with a sheet resistance of 193 Ω/sq at 96% transmission. Both remarkable flexibility tested under bending stress and excellent adhesion applied on special terrain substrate have been achieved. This method has led to a full coverage of micro-holes at a depth of 18 µm and a bottom spacing of only 1 µm, as well as a perfect gap-free coverage for micro-tubes and pyramid array. It has been proved that this 3D ITO nanowire network can be used as a transparent conductive layer for optoelectronic devices with any topography surface. Through the application on the micro-holes, -tubes and -pyramid array, some new characteristics of the 3D ITO nanowires in solar cells, sensors, micro-lasers and flexible LEDs have been found. Such 3D ITO nanowire networks could be fabricated directly on micro-irregular substrates, which will greatly promote the application of the heterotypic devices