Journal of Biological Research-Thessaloniki最新文献

Background: Elucidating the patterns of the Atlantic Bluefin tuna [ABFT, Thunnus thynnus (Linnaeus, 1758)] population structure constitutes a challenging task of great importance. Most of the unique challenges stem from its biology, as well as the attributes of the marine realm in which it disperses. Accurate information is urgently needed for stock assessment, and the identification of critical features to the persistence and adaptation of populations in order to formulate and adopt effective strategies for ABFT conservation and management. Conclusions of a great number of ABFT genetic studies on the Mediterranean Sea stock structure are rather controversial and not yet conclusive. In this study, ABFT genomic diversity was investigated in the Mediterranean Sea, which is the most important area for the species' reproduction.

Results: Analyzing genome-wide SNPs and microsatellites from ABFT samples collected throughout the Mediterranean Sea did not provide strong evidence of genetic structure, pointing towards the existence of a single panmictic unit. An alternative view would recognize a failure to reject the null hypothesis of a panmictic unit as an effect of the study's sampling design, the type of markers used, and the effectiveness/suitability of analysis methods in respect to the species biological characteristics or any combination of the above.

Conclusions: Unravelling the drivers of ABFT population diversity would require the consideration of important aspects of the species spawning behavior for the determination of the appropriate sampling design. Novel approaches and methods of analysis that will bring together experts in genetics/-omics, ecology and oceanography are deemed necessary. Analyzing ABFT genetic data under the discipline of seascape genetics could provide the analysis framework under which major abiotic and biotic forces controlling ABFT recruitment could be identified, elucidating the complicated population dynamics of the species, while multiple and continuous fisheries monitoring should in all cases be considered as a prerequisite in order to achieve efficient and long-term ABFT conservation.

Background: In vitro plant regeneration via androgenesis or somatic embryogenesis is capable of inducing (epi)mutations that may affect sexual progenies. While epimutations are associated with DNA methylation, mutations could be due to the movement of transposons. The common notion is that both processes are linked. It is being assumed that demethylation activates transposable elements (TEs). Analysis of methylation changes and their relation with TEs activation in tissue cultures requires uniquely derived donor plants (Ds), their regenerants (Rs) and respective progeny (Ps) that would allow discrimination of processes not related to changes introduced via in vitro cultures. Moreover, a set of methods (RP-HPLC, SSAP, and MSTD) is needed to study whether different TEs families are being activated during in vitro tissue culture plant regeneration and whether their activity could be linked to DNA methylation changes or alternative explanations should be considered.

Results: The in vitro tissue culture plant regeneration in barley was responsible for the induction of DNA methylation in regenerants and conservation of the methylation level in the progeny as shown by the RP-HPLC approach. No difference between andro- and embryo-derived Rs and Ps was observed. The SSAP and MSTD approach revealed that Ds and Rs were more polymorphic than Ps. Moreover, Rs individuals exhibited more polymorphisms with the MSTD than SSAP approach. The differences between Ds, Rs and Ps were also evaluated via ANOVA and AMOVA.

Conclusions: Stressful conditions during plant regeneration via in vitro tissue cultures affect regenerants and their sexual progeny leading to an increase in global DNA methylation of Rs and Ps compared to Ds in barley. The increased methylation level noted among regenerants remains unchanged in the Ps as indicated via RP-HPLC data. Marker-based experiments suggest that TEs are activated via in vitro tissue cultures and that, independently of the increased methylation, their activity in Rs is greater than in Ps. Thus, the increased methylation level may not correspond to the stabilization of TEs movement at least at the level of regenerants. The presence of TEs variation among Ds that were genetically and epigenetically uniform may suggest that at least some mobile elements may be active, and they may mask variation related to tissue cultures. Thus, tissue cultures may activate some TEs whereas the others remain intact, or their level of movement is changed. Finally, we suggest that sexual reproduction may be responsible for the stabilization of TEs.

Background: The use of stably expressed genes as normalizers has crucial role in accurate and reliable expression analysis estimated by quantitative real-time polymerase chain reaction (qPCR). Recent studies have shown that, the expression levels of common housekeeping genes are varying in different tissues and experimental conditions. The genomic DNA contamination in RNA samples is another important factor that also influence the interpretation of the data obtained from qPCR. It is estimated that the gDNA contamination in gene expression analysis lead to an overestimation of the RNA transcript level. The aim of this study was to validate the most stably expressed reference genes in two different tissues of Aeluropus littoralis-halophyte grass at salt stress and recovery condition. Also, a qPCR-based approach for monitoring contamination with gDNA was conducted.

Results: Ten candidate reference genes participating in different biological processes were analyzed in four groups of samples including root and leaf tissues, salt stress and recovery condition. To determine the most stably expressed reference genes, three statistical methods (geNorm, NormFinder and BestKeeper) were applied. According to results obtained, ten candidate reference genes were ranked based on the stability of their expression. Here, our results show that a set of four housekeeping genes (HKGs) e.g. RPS3, EF1A, GTF and RPS12 could be used as general reference genes for the all selected conditions and tissues. Also, four set of reference genes were proposed for each tissue and condition including: RPS3, EF1A and UBQ for salt stress and root samples; RPS3, EF1A, UBQ as well as GAPDH for recovery condition; U2SURP and GTF for leaf samples. Additionally, for assessing DNA contamination in RNA samples, a set of unique primers were designed based on the conserved region of ribosomal DNA (rDNA). The universality, specificity and sensitivity of these primer pairs were also evaluated in Poaceae.

Conclusions: Overall, the sets of reference genes proposed in this study are ideal normalizers for qPCR analysis in A. littoralis transcriptome. The novel reference gene e.g. RPS3 that applied this study had higher expression stability than commonly used housekeeping genes. The application of rDNA-based primers in qPCR analysis was addressed.

Mitochondrial Eve confirms the "out of Africa" theory, but the evidence also supports interbreeding between Homo sapiens and other hominins: Neanderthals, Denisovans, and Homo heidelbergensis. This article explains how interbreeding between early H. sapiens and archaic hominins occurred. The availability of edible insects in East Asia aided the spread of the unaggressive, highly cooperative Neanderthals, who interbred with H. sapiens in Asia, resulting in a higher admixture of Neanderthal DNA in East Asian populations. Geographical variation in degree of interbreeding between H. sapiens and Neanderthals likely contributed to neurological and behavioral differences in modern humans. Similarly, people with Denisovan genetic admixture were better able to dwell in mountainous regions, allowing their genetic legacy to cross the Himalayas and persist in Southeast Asian and Oceanian H. sapiens. In the Sub-Saharan region, unaffected by Denisovan or Neanderthal interbreeding, H. sapiens interbred with H. heidelbergensis, because high humidity militated against fire-making and allowed the survival of these non-fire-making hominins.

Background: Reliable prediction of protein-protein interaction sites is an important goal in the field of bioinformatics. Many computational methods have been explored for the large-scale prediction of protein-protein interaction sites based on various data types, including protein sequence, structural and genomic data. Although much progress has been achieved in recent years, the problem has not yet been satisfactorily solved.

Results: In this work, we presented an efficient approach that uses ensemble learning algorithm with weighted feature descriptor (EL-WFD) to predict protein-protein interaction sites. Moreover, weighted feature descriptor was designed to describe the distance influence of neighboring residues on interaction sites. The results on two dataset (Hetero and Homo), show that the proposed method yields a satisfactory accuracy with 83.8 % recall and 96.3 % precision on the Hetero dataset and 84.2 % recall and 96.3 % precision on the Homo dataset, respectively. In both datasets, our method tend to obtain high Mathews correlation coefficient compared with state-of-the-art technique random forest method.

Conclusions: The experimental results show that the EL-WFD method is quite effective in predicting protein-protein interaction sites. The novel weighted feature descriptor was proved to be promising in discovering interaction sites. Overall, the proposed method can be considered as a new powerful tool for predicting protein-protein interaction sites with excellence performance.

Background: Ontology development, as an increasingly practical vehicle applied in various fields, plays a significant role in knowledge management. This paper, focusing on constructing and querying a hepatitis ontology, aims to provide a framework for ontology-based medical services. The paper is devoted to the algorithm of query expansion for the hepatitis ontology, including synonym expansion, hypernym/hyponym expansion and expansion of similar words. It applies semantic similarity calculation to judge the similarity of retrieval terms.

Results: The paper proposes a new prototype system. The accuracy of query expansion is improved in both precision@40 and AP@40, which indicates that query expansion improves the accuracy of the query after using the method proposed in this paper.

Conclusions: The paper has adopted semantic similarity computing to improve retrieval performance. Experiments show that search precision of query expansion is higher based on domain concept relationship.

Background: Post-translational modifications (PTMs) occur on almost all proteins and often strongly affect the functions of modified proteins. Phosphorylation is a crucial PTM mechanism with important regulatory functions in biological systems. Identifying the potential phosphorylation sites of a target protein may increase our understanding of the molecular processes in which it takes part.

Results: In this paper, we propose PredPhos, a computational method that can accurately predict both kinase-specific and non-kinase-specific phosphorylation sites by using optimally selected properties. The optimal combination of features was selected from a set of 153 novel structural neighborhood properties by a two-step feature selection method consisting of a random forest algorithm and a sequential backward elimination method. To overcome the imbalanced problem, we adopt an ensemble method, which combines bootstrap resampling technique, support vector machine-based fusion classifiers and majority voting strategy. We evaluate the proposed method using both tenfold cross validation and independent test. Results show that our method achieves a significant improvement on the prediction performance for both kinase-specific and non-kinase-specific phosphorylation sites.

Conclusions: The experimental results demonstrate that the proposed method is quite effective in predicting phosphorylation sites. Promising results are derived from the new structural neighborhood properties, the novel way of feature selection, as well as the ensemble method.

Background: Microarray technology allows biologists to monitor expression levels of thousands of genes among various tumor tissues. Identifying relevant genes for sample classification of various tumor types is beneficial to clinical studies. One of the most widely used classification strategies for multiclass classification data is the One-Versus-All (OVA) schema that divides the original problem into multiple binary classification of one class against the rest. Nevertheless, multiclass microarray data tend to suffer from imbalanced class distribution between majority and minority classes, which inevitably deteriorates the performance of the OVA classification.

Results: In this study, we propose a novel iterative ensemble feature selection (IEFS) framework for multiclass classification of imbalanced microarray data. In particular, filter feature selection and balanced sampling are performed iteratively and alternatively to boost the performance of each binary classification in the OVA schema. The proposed framework is tested and compared with other representative state-of-the-art filter feature selection methods using six benchmark multiclass microarray data sets. The experimental results show that IEFS framework provides superior or comparable performance to the other methods in terms of both classification accuracy and area under receiver operating characteristic curve. The more number of classes the data have, the better performance of IEFS framework achieves.

Conclusions: Balanced sampling and feature selection together work well in improving the performance of multiclass classification of imbalanced microarray data. The IEFS framework is readily applicable to other biological data analysis tasks facing the same problem.

Background: The Cytochrome P450 enzymes are commonly known for their major role in metabolism. Besides its metabolic role, CYP2E1 gene expression has been associated with the onset of diabetic nephropathy. CYP2E1 protein elevation has also been reported to be responsible for the production of reactive oxygen species. The aims of this study were (i) to optimize and validate a targeted proteomic approach for quantitating CYP2E1 and validating it as a suitable clinical test, (ii) to investigate the concurrency between ESI-LCMS-MS quantitated circulating CYP2E1 and gold standard indices in the context of outpatient point-of-care clinical settings involving various groups of diabetic patients and (iii) to investigate the concurrency profile of circulating CYP2E1 protein, CYP2E1 gene expression and reactive oxygen species (ROS). This is a cross sectional study involving three groups of subjects (n = 166): control, pre-diabetes, and diabetes. We optimized a targeted proteomic approach for absolute quantification of CYP2E1. "YPEIEEK" and "GTVVVPTLYDNQEFPDPEK" were the representative peptides of CYP2E1 for our analytical method. Deuterated forms of "YPEIEEK" and "GTVVVPTLYDNQEFPDPEK" were used as internal standards. Lymphocytes were isolated from whole blood, microsomes were prepared, followed by in-solution digestion for production of tryptic peptides. Amounts of "YPEIEEK" and "GTVVVPTLYDNQEFPDPEK" from patients' samples were calculated from a calibration curve.

Results: "YPEIEEK" is a unique and reliable representative peptide for CYP2E1 quantification. "GTVVVPTLYDNQEFPDPEK" showed poor reproducibility and sensitivity. Incremental amounts of CYP2E1 protein in the peripheral circulation clearly showed concurrency with CYP2E1 gene expression and ROS levels in our study population. Elevations of CYP2E1 were observed even when gold standard clinical indicator for glycemic control (HbA1c) was within normal reference limits. Quantitated amounts of CYP2E1 protein in the pre-diabetes and diabetes groups showed significant difference relative to control group (p < 0.001). No significant differences were observed between the medians of pre-diabetes and diabetes groups (p = 0.870).

Conclusions: CYP2E1 protein in peripheral blood can be reliably quantitated by the validated targeted proteomic approach method. Quantifiable amounts of CYP2E1 preceded abnormal HbA1C levels which indicates quantitation of CYP2E1 could be useful as an additional tool for early indication of diabetic risks and it complications.