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Quantitative real-time polymerase chain reaction (qPT-PCR) is commonly used to analyze gene expression, however, the accuracy of the normalized results is affected by the expression stability of reference genes. Holotrichia oblita (Coleoptera: Scarabaeidae) causes serious damage to crops. Reliable reference genes in H. oblita are needed for qRT-PCR analysis. Therefore, we evaluated 13 reference genes under biotic and abiotic conditions. RefFinder provided a comprehensive stability ranking, and geNorm suggested the optimal number of reference genes for normalization. RPL13a and RPL18 were the most suitable reference genes for developmental stages, tissues, and temperature treatments; RPL13a and RPS3 were the most suitable for pesticide and photoperiod treatments; RPS18 and RPL18 were the most suitable for the two sexes. We validated the normalized results using odorant-binding protein genes as target genes in different tissues. Compared with the selected suitable reference genes, the expression of OBP1 in antennae, abdomen, and wings, and OBP2 in antennae and wings were overestimated due to the instability of ACTb. These results identified several reliable reference genes in H. oblita for normalization, and are valuable for future molecular studies.

Background Postnatal human cardiomyocyte proliferation declines rapidly with age, which has been suggested to be correlated with increases in oxidative DNA damage in mice and plays an important role in regulating cardiomyocyte proliferation. However, the relationship between oxidative DNA damage and age in humans is unclear. Methods Sixty right ventricular outflow myocardial tissue specimens were obtained from ventricular septal defect infant patients during routine congenital cardiac surgery. These specimens were divided into three groups based on age: group A (age 0–6 months), group B (age, 7–12 months), and group C (>12 months). Each tissue specimen was subjected to DNA extraction, RNA extraction, and immunofluorescence. Results Immunofluorescence and qRT-PCR analysis revealed that DNA damage markers—mitochondrial DNA copy number, oxoguanine 8, and phosphorylated ataxia telangiectasia mutated—were highest in Group B. However immunofluorescence and qRT-PCR demonstrated that two cell proliferation markers, Ki67 and cyclin D2, were decreased with age. In addition, wheat germ agglutinin-staining indicated that the average size of cardiomyocytes increased with age. Conclusions Oxidative DNA damage of cardiomyocytes was not correlated positively with age in human beings. Oxidative DNA damage is unable to fully explain the reduced proliferation of human cardiomyocytes.

Background and objectiveGenetic factors including TNF-β have been considered as important components in the aetiology of migraine. Many studies have investigated the association between TNF-β 252A>G polymorphism and migraine risk, with debatable results. This study was designed to examine whether the TNF-β 252A>G polymorphism confers genetic susceptibility to migraine in diverse populations.MethodStudies eligible for this meta-analysis were searched in the PubMed, Embase, and CNKI by using the keywords "tumor necrosis factor", "TNF", "252A>G", "rs909253", "polymorphism", "polymorphisms", "variant", "SNP", combined with "migraine" or "migraine with aura (MA)" or "migraine without aura (MO)". Pooled ORs and 95% CI were appropriately calculated using the fixed-effect model.ResultsWe finally included a total of seven studies, providing 5 557 migraineurs and 20 543 unrelated healthy controls. Meta-analysis results showed no statistical evidence of a significant association between TNF-β 252A>G polymorphism and overall migraine risk. Stratified analyses by type of migraine and gender revealed similar results. Interestingly, an OR with 95% CI representing an increased migraine risk was indicated in Asians under the recessive model (GG vs. AG + AA: OR, 1.38; 95%CI, 1.04-1.84; P for heterogeneity, 0.665).ConclusionsOur findings appear to support the hypothesis that genetic variability of 252A>G polymorphism in TNF region may modulate risk of migraine in the population of Asian ancestry.

One of the reasons for the progressive yield decline observed in cereals production is the rapid build-up of populations of the cereal cyst nematode (CCN, Heterodera avenae). These nematodes secrete so-call effectors into their host plant to suppress the plant defense responses, alter plant signaling pathways and then induce the formation of syncytium after infection. However, little is known about its molecular mechanism and parasitism during incompatible infection. To gain insight into its repertoire of parasitism genes, we investigated the transcriptome of the early parasitic second-stage (30 hours, 3 days and 9 days post infection) juveniles of the CCN as well as the CCN infected tissue of the host Aegilops variabilis by Illumina sequencing. Among all assembled unigenes, 681 putative genes of parasitic nematode were found, in which 56 putative effectors were identified, including novel pioneer genes and genes corresponding to previously reported effectors. All the 681 CCN unigenes were mapped to 229 GO terms and 200 KEGG pathways, including growth, development and several stimulus-related signaling pathways. Sixteen clusters were involved in the CCN unigene expression atlas at the early stages during infection process, and three of which were significantly gene-enriched. Besides, the protein-protein interaction network analysis revealed 35 node unigenes which may play an important role in the plant-CCN interaction. Moreover, in a comparison of differentially expressed genes between the pre-parasitic juveniles and the early parasitic juveniles, we found that hydrolase activity was up-regulated in pre J2s whereas binding activity was upregulated in infective J2s. RT-qPCR analysis on some selected genes showed detectable expression, indicating possible secretion of the proteins and putative role in infection. This study provided better insights into the incompatible interaction between H. avenae and the host plant Ae. varabilis. Moreover, RNAi targets with potential lethality were screened out and primarily validated, which provide candidates for engineering-based control of cereal cyst nematode in crops breeding.

Background Anomala corpulenta is an important insect pest and can cause enormous economic losses in agriculture, horticulture and forestry. It is widely distributed in China, and both larvae and adults can cause serious damage. It is difficult to control this pest because the larvae live underground. Any new control strategy should exploit alternatives to heavily and frequently used chemical insecticides. However, little genetic research has been carried out on A. corpulenta due to the lack of genomic resources. Genomic resources could be produced by next generation sequencing technologies with low cost and in a short time. In this study, we performed de novo sequencing, assembly and characterization of the antennal transcriptome of A. corpulenta. Results Illumina sequencing technology was used to sequence the antennal transcriptome of A. corpulenta. Approximately 76.7 million total raw reads and about 68.9 million total clean reads were obtained, and then 35,656 unigenes were assembled. Of these unigenes, 21,463 of them could be annotated in the NCBI nr database, and, among the annotated unigenes, 11,154 and 6,625 unigenes could be assigned to GO and COG, respectively. Additionally, 16,350 unigenes could be annotated in the Swiss-Prot database, and 14,499 unigenes could map onto 258 pathways in the KEGG Pathway database. We also found 24 unigenes related to OBPs, 6 to CSPs, and in total 167 unigenes related to chemodetection. We analyzed 4 OBPs and 3CSPs sequences and their RT-qPCR results agreed well with their FPKM values. Conclusion We produced the first large-scale antennal transcriptome of A. corpulenta, which is a species that has little genomic information in public databases. The identified chemodetection unigenes can promote the molecular mechanistic study of behavior in A. corpulenta. These findings provide a general sequence resource for molecular genetics research on A. corpulenta.

Four pairs of XX and XY gonads from Nile tilapia were sequenced at four developmental stages, 5, 30, 90, and 180 days after hatching (dah) using Illumina Hiseq(TM) technology. This produced 28 Gb sequences, which were mapped to 21,334 genes. Of these, 259 genes were found to be specifically expressed in XY gonads, and 69 were found to be specific to XX gonads. Totally, 187 XX- and 1,358 XY-enhanced genes were identified, and 2,978 genes were found to be co-expressed in XX and XY gonads. Almost all steroidogenic enzymes, including cyp19a1a, were up-regulated in XX gonads at 5 dah; but in XY gonads these enzymes, including cyp11b2, were significantly up-regulated at 90 dah, indicating that, at a time critical to sex determination, the XX fish produced estrogen and the XY fish did not produce androgens. The most pronounced expression of steroidogenic enzyme genes was observed at 30 and 90 dah for XX and XY gonads, corresponding to the initiation of germ cell meiosis in the female and male gonads, respectively. Both estrogen and androgen receptors were found to be expressed in XX gonads, but only estrogen receptors were expressed in XY gonads at 5 dah. This could explain why exogenous steroid treatment induced XX and XY sex reversal. The XX-enhanced expression of cyp19a1a and cyp19a1b at all stages suggests an important role for estrogen in female sex determination and maintenance of phenotypic sex. This work is the largest collection of gonadal transcriptome data in tilapia and lays the foundation for future studies into the molecular mechanisms of sex determination and maintenance of phenotypic sex in non-model teleosts.

Background As one of the most common types of co-regulatory motifs, feed-forward loops (FFLs) control many cell functions and play an important role in human cancers. Therefore, it is crucial to reconstruct and analyze cancer-related FFLs that are controlled by transcription factor (TF) and microRNA (miRNA) simultaneously, in order to find out how miRNAs and TFs cooperate with each other in cancer cells and how they contribute to carcinogenesis. Current FFL studies rely on predicted regulation information and therefore suffer the false positive issue in prediction results. More critically, FFLs generated by existing approaches cannot represent the dynamic and conditional regulation relationship under different experimental conditions. Methodology/Principal Findings In this study, we proposed a novel filter-wrapper feature selection method to accurately identify co-regulatory mechanism by incorporating prior information from predicted regulatory interactions with parallel miRNA/mRNA expression datasets. By applying this method, we reconstructed 208 and 110 TF-miRNA co-regulatory FFLs from human pan-cancer and prostate datasets, respectively. Further analysis of these cancer-related FFLs showed that the top-ranking TF STAT3 and miRNA hsa-let-7e are key regulators implicated in human cancers, which have regulated targets significantly enriched in cellular process regulations and signaling pathways that are involved in carcinogenesis. Conclusions/Significance In this study, we introduced an efficient computational approach to reconstruct co-regulatory FFLs by accurately identifying gene co-regulatory interactions. The strength of the proposed feature selection method lies in the fact it can precisely filter out false positives in predicted regulatory interactions by quantitatively modeling the complex co-regulation of target genes mediated by TFs and miRNAs simultaneously. Moreover, the proposed feature selection method can be generally applied to other gene regulation studies using parallel expression data with respect to different biological contexts.

Background It has been well established that theoretical kernel for recently surging genome-wide association study (GWAS) is statistical inference of linkage disequilibrium (LD) between a tested genetic marker and a putative locus affecting a disease trait. However, LD analysis is vulnerable to several confounding factors of which population stratification is the most prominent. Whilst many methods have been proposed to correct for the influence either through predicting the structure parameters or correcting inflation in the test statistic due to the stratification, these may not be feasible or may impose further statistical problems in practical implementation. Methodology We propose here a novel statistical method to control spurious LD in GWAS from population structure by incorporating a control marker into testing for significance of genetic association of a polymorphic marker with phenotypic variation of a complex trait. The method avoids the need of structure prediction which may be infeasible or inadequate in practice and accounts properly for a varying effect of population stratification on different regions of the genome under study. Utility and statistical properties of the new method were tested through an intensive computer simulation study and an association-based genome-wide mapping of expression quantitative trait loci in genetically divergent human populations. Results/Conclusions The analyses show that the new method confers an improved statistical power for detecting genuine genetic association in subpopulations and an effective control of spurious associations stemmed from population structure when compared with other two popularly implemented methods in the literature of GWAS.