Inferring phylogenies of evolving sequences without multiple sequence alignment

Alignment-free methods, in which shared properties of sub-sequences (e.g. identity or match length) are extracted and used to compute a distance matrix, have recently been explored for phylogenetic inference. However, the scalability and robustness of these methods to key evolutionary processes remain to be investigated. Here, using simulated sequence sets of various sizes in both nucleotides and amino acids, we systematically assess the accuracy of phylogenetic inference using an alignment-free approach, based on D2 statistics, under different evolutionary scenarios. We find that compared to a multiple sequence alignment approach, D2 methods are more robust against among-site rate heterogeneity, compositional biases, genetic rearrangements and insertions/deletions, but are more sensitive to recent sequence divergence and sequence truncation. Across diverse empirical datasets, the alignment-free methods perform well for sequences sharing low divergence, at greater computation speed. Our findings provide strong evidence for the scalability and the potential use of alignment-free methods in large-scale phylogenomics.

Characterization of sequence and structural features of the Candida krusei Enolase

The incidence of human infections by the fungal pathogen Candida species has been increasing in recent years. Enolase is an essential protein in fungal metabolism. Sequence data is available for human and a number of medically important fungal species. An understanding of the structural and functional features of fungal enolases may provide the structural basis for their use as a target for the development of new anti-fungal drugs. We have obtained the sequence of the enolase of Candida krusei (C. krusei), as it is a significant medically important fungal pathogen. We have then used multiple sequence alignments with various enolase isoforms in order to identify C. krusei specific amino acid residues. The phylogenetic tree of enolases shows that the C. krusei enolase assembles on the tree with the fungal genes. Importantly, C. krusei lacks four amino acids in the active site compared to human enolase, as revealed by multiple sequence alignments. These differences in the substrate binding site may be exploited for the design of new anti-fungal drugs to selectively block this enzyme. The lack of the important amino acids in the active site also indicates that C. krusei enolase might have evolved as a member of a mechanistically diverse enolase superfamily catalying somewhat different reactions.

Accelerating Multiple Sequence Alignment with the Cell BE Processor

The Cell Broadband Engine (BE) Architecture is a new heterogeneous multi-core architecture targeted at compute-intensive workloads. The architecture of the Cell BE has several features that are unique in high-performance general-purpose processors, most notably the extensive support for vectorization, scratch pad memories and explicit programming of direct memory accesses (DMAs) and mailbox communication. While these features strongly increase programming complexity, it is generally claimed that significant speedups can be obtained by using Cell BE processors. This paper presents our experiences with using the Cell BE architecture to accelerate Clustal W, a bio-informatics program for multiple sequence alignment. We report on how we apply the unique features of the Cell BE to Clustal W and how important each is in obtaining high performance. By making extensive use of vectorization and by parallelizing the application across all cores, we demonstrate a speedup of 24.4 times when using 16 synergistic processor units on a QS21 Cell Blade compared to single-thread execution on the power processing unit. As the Cell BE exploits a large number of slim cores, our highly optimized implementation is just 3.8 times faster than a 3-thread version running on an Intel Core2 Duo, as the latter processor exploits a small number of fat cores.

Detecting recombination in 4-taxa DNA sequence alignments with Bayesian hidden Markov models and Markov chain Monte Carlo

This article presents a statistical method for detecting recombination in DNA sequence alignments, which is based on combining two probabilistic graphical models: (1) a taxon graph (phylogenetic tree) representing the relationship between the taxa, and (2) a site graph (hidden Markov model) representing interactions between different sites in the DNA sequence alignments. We adopt a Bayesian approach and sample the parameters of the model from the posterior distribution with Markov chain Monte Carlo, using a Metropolis-Hastings and Gibbs-within-Gibbs scheme. The proposed method is tested on various synthetic and real-world DNA sequence alignments, and we compare its performance with the established detection methods RECPARS, PLATO, and TOPAL, as well as with two alternative parameter estimation schemes.

An Efficient Parallel Algorithm for Multiple Sequence Similarities Calculation Using a Low Complexity Method

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Better prediction of protein contact number using a support vector regression analysis of amino acid sequence

Background: Protein tertiary structure can be partly characterized via each amino acid's contact number measuring how residues are spatially arranged. The contact number of a residue in a folded protein is a measure of its exposure to the local environment, and is defined as the number of C-beta atoms in other residues within a sphere around the C-beta atom of the residue of interest. Contact number is partly conserved between protein folds and thus is useful for protein fold and structure prediction. In turn, each residue's contact number can be partially predicted from primary amino acid sequence, assisting tertiary fold analysis from sequence data. In this study, we provide a more accurate contact number prediction method from protein primary sequence. Results: We predict contact number from protein sequence using a novel support vector regression algorithm. Using protein local sequences with multiple sequence alignments (PSI-BLAST profiles), we demonstrate a correlation coefficient between predicted and observed contact numbers of 0.70, which outperforms previously achieved accuracies. Including additional information about sequence weight and amino acid composition further improves prediction accuracies significantly with the correlation coefficient reaching 0.73. If residues are classified as being either contacted or non-contacted, the prediction accuracies are all greater than 77%, regardless of the choice of classification thresholds. Conclusion: The successful application of support vector regression to the prediction of protein contact number reported here, together with previous applications of this approach to the prediction of protein accessible surface area and B-factor profile, suggests that a support vector regression approach may be very useful for determining the structure-function relation between primary sequence and higher order consecutive protein structural and functional properties.

Prediction of cis/trans isomerization in proteins using PSI-BLAST profiles and secondary structure information

Background The majority of peptide bonds in proteins are found to occur in the trans conformation. However, for proline residues, a considerable fraction of Prolyl peptide bonds adopt the cis form. Proline cis/trans isomerization is known to play a critical role in protein folding, splicing, cell signaling and transmembrane active transport. Accurate prediction of proline cis/trans isomerization in proteins would have many important applications towards the understanding of protein structure and function. Results In this paper, we propose a new approach to predict the proline cis/trans isomerization in proteins using support vector machine (SVM). The preliminary results indicated that using Radial Basis Function (RBF) kernels could lead to better prediction performance than that of polynomial and linear kernel functions. We used single sequence information of different local window sizes, amino acid compositions of different local sequences, multiple sequence alignment obtained from PSI-BLAST and the secondary structure information predicted by PSIPRED. We explored these different sequence encoding schemes in order to investigate their effects on the prediction performance. The training and testing of this approach was performed on a newly enlarged dataset of 2424 non-homologous proteins determined by X-Ray diffraction method using 5-fold cross-validation. Selecting the window size 11 provided the best performance for determining the proline cis/trans isomerization based on the single amino acid sequence. It was found that using multiple sequence alignments in the form of PSI-BLAST profiles could significantly improve the prediction performance, the prediction accuracy increased from 62.8% with single sequence to 69.8% and Matthews Correlation Coefficient (MCC) improved from 0.26 with single local sequence to 0.40. Furthermore, if coupled with the predicted secondary structure information by PSIPRED, our method yielded a prediction accuracy of 71.5% and MCC of 0.43, 9% and 0.17 higher than the accuracy achieved based on the singe sequence information, respectively. Conclusion A new method has been developed to predict the proline cis/trans isomerization in proteins based on support vector machine, which used the single amino acid sequence with different local window sizes, the amino acid compositions of local sequence flanking centered proline residues, the position-specific scoring matrices (PSSMs) extracted by PSI-BLAST and the predicted secondary structures generated by PSIPRED. The successful application of SVM approach in this study reinforced that SVM is a powerful tool in predicting proline cis/trans isomerization in proteins and biological sequence analysis.

Predicting residue-wise contact orders in proteins by support vector regression

Background The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. Results We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. Conclusion The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

Crystal structure of Rv2118c: an AdoMet-dependent methyltransferase from Mycobacterium tuberculosis H37Rv

Rv2118c belongs to the class of conserved hypothetical proteins from Mycobacterium tuberculosis H37Rv. The crystal structure of Rv2118c in complex with S-adenosyl-Image -methionine (AdoMet) has been determined at 1.98 Å resolution. The crystallographic asymmetric unit consists of a monomer, but symmetry-related subunits interact extensively, leading to a tetrameric structure. The structure of the monomer can be divided functionally into two domains: the larger catalytic C-terminal domain that binds the cofactor AdoMet and is involved in the transfer of methyl group from AdoMet to the substrate and a smaller N-terminal domain. The structure of the catalytic domain is very similar to that of other AdoMet-dependent methyltransferases. The N-terminal domain is primarily a β-structure with a fold not found in other methyltransferases of known structure. Database searches reveal a conserved family of Rv2118c-like proteins from various organisms. Multiple sequence alignments show several regions of high sequence similarity (motifs) in this family of proteins. Structure analysis and homology to yeast Gcd14p suggest that Rv2118c could be an RNA methyltransferase, but further studies are required to establish its functional role conclusively.

Molecular Characterization and Functional Commonality of Nucleophosmin/Nucleoplasmin in Two Cyprinid Fish

Nucleophosmin/nucleoplasmin has been studied mostly in mammals and amphibians. To clarify the characteristics and function of nucleophosmin/nucleoplasmin in teleost fish, we cloned a full-length cDNA sequence from two cyprinid fish, Carassius auratus gibelio and Carassius auratus. Molecular characterization and multiple sequence alignments suggested that they are the homologs of nucleophosmin. RT-PCR and Western blot detected a specific expression in gonads, and immunofluorescence localization revealed their distribution in oogenic and spermatogenic cells. Furthermore, a sperm decondensation function was demonstrated by immunodepletion and in vitro sperm decondensation experiments. The data suggest that the cloned nucleophosmin should share expressional and functional characterization with nucleoplasmin and therefore provide novel evidence for a functional commonality of nucleophosmin and nucleoplasmin in fish.

不同抗旱性青稞LEA2/LEA3蛋白基因的克隆与表达

作物的抗旱性是一个多基因控制的、极为复杂的数量性状，植物对干旱在分子水平上的差异反应通过植物组织生理和细胞生物学水平，最终表现为植物抗旱性的不同。在我国，旱地农业超过耕地面积的50%，但水资源短缺，因此培育和选育抗旱高产作物是发展节水型农业最有效的途径。 青藏高原气候恶劣、年均降雨量少，也是世界大麦初生起源中心，因而蕴藏了十分丰富的与抗逆相关的种质资源材料，从这些特殊的资源材料克隆抗旱基因，不仅对培育抗旱、优质、高产大麦新品种具有重要理论意义和经济价值，而且对整个作物抗旱基础和育种应用研究都具重大促进作用。 为了筛选青稞（裸大麦，Hordeum vulgare ssp. vulgare）抗旱性材料，本研究选用来自青藏高原不同地区的84份青稞为材料，在叶片失水率(water loss rate, WLR)检测分析的基础上，选择失水率值差异显著的12个品种，通过相对含水量（relative water content, RWC）和反复干旱法评价其抗旱性，并通过植株对干旱胁迫下的丙二醛（MDA）含量和游离脯氨酸（free-proline）含量变化，了解不同抗旱性材料的生理反应特性。选择抗旱性强弱不同的品种各两份进行LEA2蛋白基因(Dhn6基因)、LEA3蛋白基因(HVA1基因)的克隆，比较LEA蛋白结构差异与作物抗旱性之间的关系。同时，对抗旱性不同的青稞品种受到干旱时间不同的失水变化率（dynamics water loss rate, DWLR）进行了检测；对抗旱性不同的青稞对照材料进行2 h、4 h、8 h和12 h的快速干旱处理，通过SYBR Green实时荧光定量RT-PCR技术对Dhn6基因、Dhn11基因、Dhn13基因和HVA1基因在不同抗旱性材料受到不同干旱时间处理后的相对表达水平进行了检测。本研究对LEA蛋白基因在抗旱性不同的青稞材料中的干旱胁迫分子水平上的差异反应进行了研究，也对植物的抗旱机理进行了初步探讨。主要研究结果如下： 1. 青稞苗期进行离体叶片失水率测定结果表明，来自青藏高原的84份青稞材料的WLR在0.086~0.205gh-1g-1DW之间。选择WLR低于0.1gh-1g-1DW和WLR高于0.18gh-1g-1DW的品种各6份，并对苗期分别进行未干旱及干旱12小时的处理。相对含水量检测结果表明，低失水率青稞材料干旱后的具有更高的相对含水量，盆栽缺水试验也显示叶片失水率低的材料耐旱能力强于失水率高的材料。通过水合茚三酮法测定离体叶片游离脯氨酸的含量，结果表明，所有品种未干旱处理时，游离脯氨酸含量差异不大（17.10~25.74 µgg-1FW）；干旱12小时后，低失水率的品种游离脯氨酸含量明显增高（32.99~53.45µgg-1FW），高失水率品种的游离脯氨酸含量与干旱前变化不明显(P<0.05)。硫代巴比妥酸法测定离体叶片丙二醛(MDA)含量，结果显示，12份所选对照品种中，丙二醛的含量在0.97~2.74nmolg-1FW，干旱12小时后丙二醛的含量显著上升（1.46~4.74nmolg-1FW），高失水率的6个品种的丙二醛含量在未干旱和干旱处理时都明显高于低WLR品种。本研究结果表明青稞的低失水率、低丙二醛含量、高相对含水量和高脯氨酸含量具相关性（P<0.05）。综上研究，我们认为作物失水率的测定可以作为快速检测作物抗旱性的指标之一，因此，强抗旱品种喜玛拉10号(TR1)、品比14号(TR2)和弱抗旱品种冬青8号(TS1)、QB24 (TS2)被选作抗旱基因克隆和表达分析的研究材料。 2. 高等植物胚胎发育晚期丰富蛋白(late embryogenesis abundant proteins, LEA proteins)与植物耐脱水性密切相关，为了探讨青稞LEA蛋白结构差异性与植物抗旱性的关系，本研究以强抗旱品种（喜玛拉10号、品比14号）和弱抗旱品种（冬青8号、QB24）为材料，利用同源克隆法，通过RT-PCR，分别克隆了与抗旱性密切相关的Dhn6基因和HVA1基因。Dhn6基因序列分析结果表明，强抗旱品种品比14号和弱抗旱品种冬青8号Dhn6基因所克隆到的序列为1026bp，它们之间只有5个碱基的差异；喜玛拉10号和QB24克隆到的序列长963bp。在强弱不同的抗旱品种中有22个核苷酸易突变位点，相应的脱水素氨基酸序列推导结果表明，22个核苷酸突变位点中，仅有8个位点导致相应的氨基酸残基的改变，其余的位点系同义突变，另外，21个富含甘氨酸序列的缺失并没有联系作物抗旱性特征。推测这些同义突变位点的氨基酸残基对维持青稞DHN6蛋白的正常结构和功能起着非常重要的作用，也可能DHN6蛋白对青稞长期适应逆境胁迫和遗传进化的结果。对HVA1基因的序列分析结果表明，冬青8号、QB24、品比14号和喜玛拉10号的目的基因核苷酸序列全长分别为661bp、697bp、694bp和691bp，它们都包含1个完整的开放阅读框。相应的LEA3蛋白氨基酸序列结果表明，11个高度保守的氨基酸残基组成基元重复序列的拷贝数与青稞抗旱性之间没有必然关系，在强抗旱品种（喜玛拉10号、品比14号）中三个共同的氨基酸突变位点Gln32、Arg33和Ala195可能对抗旱蛋白的结构和功能有影响；另外，强抗旱青稞品种LEA3蛋白质中11-氨基酸保守基元序列拷贝数和极性氨基酸占蛋白的比例更高，推测LEA3蛋白中基元序列拷贝数和极性氨基酸占蛋白的比例对该蛋白的结构和功能影响更大。 3. LEA蛋白基因的表达水平的上调与植物的耐脱水性密切相关，我们对强抗旱性材料（喜玛拉10号、品比14号）和弱抗旱材料（冬青8号、QB24）进行干旱处理2 h、4 h、6 h、8 h和10 h的失水变化率进行测定，结果表明弱抗旱品种在2~4小时之间失水率变化最明显，而四个对照品种的失水率在8小时后和24小时的失水率值变化不大。进一步提取青稞苗期进行2 h、4 h、8 h和12 h的干旱处理后的总RNA，通过SYBR Green实时荧光定量RT-PCR技术对青稞脱水素基因(Dhn6、Dhn11和Dhn13)和LEA3蛋白基因(HVA1)的相对表达水平受干旱时间和作物抗旱性的影响进行了检测。研究发现，抗旱性不同的青稞品种随干旱处理的时间延长，Dhn6、Dhn11、Dhn13和HVA1基因的相对表达水平不同。 Dhn6基因的相对表达水平在强抗旱青稞品种干旱8小时后快速上升，但在弱抗旱青稞品种干旱处理12小时后检测到更高表达量；Dhn11基因在对照青稞抗旱品种的表达累积水平随干旱时间的延长持续下降；整个干旱过程中，Dhn13基因的相对表达水平在弱抗旱品种持续上升，在强抗旱品种中干旱处理8小时快速上升并达到最高，干旱12小时后降低。与脱水素基因相比较，强抗旱青稞品种在干旱2小时后HVA1基因的相对表达水平显著升高，相对表达量随干旱处理的时间持续上升，在干旱12小时后达到最高；与之相比较，在整个干旱过程中，弱抗旱品种的相对表达水平显著低于强抗旱品种，在干旱8小时之前弱抗旱品种的相对表达水平变化不明显；在干旱8~12小时后却显著上升。上述结果表明，不同的LEA蛋白在植物耐脱水过程中的干旱表达累积水平不同；干旱不是诱导高等植物Dhn11基因表达的主要因素；植物的抗旱性不同，不同LEA蛋白基因对干旱的反应有差异。推测某些LEA蛋白基因的干旱胁迫早期表达累积程度与植物的抗旱性直接相关；其中，Dhn11基因和Dhn12基因不同的表达模式可能与干旱调控表达顺式作用成分(dehydration responsive element, DRE)的有无或结构上的差异有关。 本研究结果认为，(1)失水率和相对含水量可作为植物抗旱性检测的指标之一；(2) DHN6同义突变位点的氨基酸残基对维持该蛋白的正常结构和功能起着重要作用；(3) 11-氨基酸保守基元序列拷贝数和极性氨基酸的比例对LEA3蛋白结构和功能有重要影响；(4)LEA蛋白表达随着干旱胁迫程度而增加，但Dhn11基因并不受干旱诱导表达；(5)作物的抗旱性不同，LEA蛋白对干旱的累积反应并不相同，干旱早期LEA蛋白的累积程度可能会影响植物的抗旱性。 Drought resistance was a complex trait which involved multiple physiological and biochemical mechanisms and regulation of numerous genes. Because its complex traits, it is difficult to understand the mechanisms of drought resistance in plants. Plants respond to water stress through multiple physiological mechanisms at the cellular, tissue, and whole-plant levels. Tibetan hulless barley, a pure line, is a selfing annual plant that has predominantly penetrated into the Qinghai-Tibetan Plateau and remains stable populations there. The wide ecological range of Tibetan hulless barley differs in water availability, temperature, soil type and vegetation, which makes it possess a high potential of adaptive diversity to abiotic stresses. This adaptive genetic diversity indicates that the potential of Tibetan hulless barley serves as a good source for drought resistance alleles for breeding purposes. 12 contrasting drought-tolerant genotypes were selected to measure relative water content (RWC), maldondialdehyde (MDA) and proline content, based on values of water loss rate (WLR) and repeated drought methods from Tibetan populations of cultivated hulless barley. As a result of the screening, sensitive and tolerant genotypes were identified to clarify relationships between characteristics of LEA2/LEA3 genes sequences and expression and drought-tolerant genotypes, associated with resistance to water deficit. In addition, dynamics water loss rate (DWLR) was measured to observe the changes on diffrential drought-tolerant genotypes. Real-time quantitative RT-PCR was applied to detect relative expression levels of Dhn6, Dhn11, Dhn13 and HVA1 genes in sensitive and tolerant genotypes with 2 h, 4 h, 8h and 12 h of dehydration. In the present study, differential sequences and expression of LEA2/LEA3 genes were explored in Tibetan hulless barley, associated with phenotypically diverse drought-tolerant genotypes. 1. The assessments of WLR and RWC were considered as an alternative measure of plant water statues reflecting the metabolic activity in plants, and the parameters of MDA and proline contents were usually consistent with the resistance to water stress. The values of detached leaf WLR of the tested genotypes were highly variable among 84 genotypes, ranging from 0.086 to 0.205 g/h.g DW. The 12 most contrasting genotypes (6 genotypes with the lowest values of WLR and 6 genotypes with the highest values of WLR) were further validated by measuring RWC, MDA and free-proline contents, which were well watered and dehydrated for 12 h. Results of RWC indicated that the values of 12 contrasting genotypes RWC ranged from 89.94% to 93.38% under condition of well water, without significant differences, but 6 genotypes with lower WLR had higher RWC suffered from 12 h dehydration. The results indicated that lower MDA contents, lower scores of WLR and higher proline contents were associated with drought-tolerant genotypes in hulless barley. Remarkably, proline amounts were increased more notable in 6 tolerant genotypes than 6 sensitive genotypes after excised leaves were dehydrated for 12 h, with control to slight changes under condition of well water. Results of MDA contents showed that six 6 tolerant genotypes had lower MDA contents than the 6 sensitive genotypes under both stressed and non-stressed conditions. As a result of that screening, drought- resistant genotypes (Ximala 10 and Pinbi 14) and drought-sensitive genotypes (Dongqing 8 and QB 24) were chosen for comparing the differential characteristics of LEA2/LEA3 genes and their expression analysis. It was conclusion that measurements of WLR could be considered an alternative index as screening of drought-tolerant genotypes in crops. 2. Late embryogenesis abundant (LEA) proteins were thought to protect against water stress in plants. To explore the relationships between configuration of LEA proteins and phenotypically diverse drought-tolerant genotypes, sequences of LEA genes and their deduced proteins were compared in Tibetan hulless barley. Results of comparing Dhn6 gene in Ximala 10 and QB24 indicated that absence of 63bp was found, except that only 5 mutant nucleotides were found. While 22 mutant sites were taken place in Dhn6 gene between sensitive and tolerant lines, 14 synonymous mutation sites appeared in the contrasting genotypes. The additional/absent polypeptide of 21 polar amino acid residues was not consistent with phenotypically drought-tolerant genotypes in hulless barley. It was deduced that synonymous mutation sites would play important roles in holding out right configurations and functions on DHN6 protein. The sequencing analysis results indicated that each cloned HVA1 gene from four selected genotypes contained an entire open reading frame. The whole sequence of HVA1 gene from Dongqing 8, QB24, Pinbi 14 and Ximala 10 was respectively 661bp, 697bp, 694bp and 691bp. Results of DNA sequence analyses showed that the differences in nucleotides of HVA1 gene in sensitive genotypes were not consistent with that of tolerant genotypes, except for absence of 33 nucleotides from +154 to +186 (numbering from ATG) in QB24. Database searches using deduced amino acid sequences showed a high homology in LEA3 proteins in the selected genotypes. Multiple sequence alignments revealed that LEA3 protein from Dongqing 8 was composed of 8 repeats of an 11 amino acid motif, less the fourth motif than Pinbi 14, Ximala 10 and QB24. Consistent mutant amino acid residues appeared in contrasting genotypes by aligning and comparing the coding sequence region, including Gln32, Arg33 and Ala195 in tolerant genotypes as compared to Asp32, Glu33 and Thr195 (Thr184 in Dongqing 8) in sensitive lines. It was concluded that consistent appearance of Gln32, Arg33 and Ala195 would contributed to functions of LEA3 protein in crops, as well as higher proportion of 11-amino-repeating motifs and polar amino acid residues. 3. Most of the LEA genes are up-regulated by dehydration, salinity, or low temperature, are also induced by application of exogenous ABA, which increases in concentration in plants under various stress conditions and acts as a mobile stress signal. Higher levels of proteins of LEA group 3 accumulated was correlated well with high level of desiccation tolerance in severely dehydrated plant seedlings. Dehydrins (DHNs), members of LEA2 protein, are an immunologically distinct protein family, and Dhn genes expression is associated with plant response to dehydration. Dynamic water loss rate was measured between sensitive genotypes and tolerant genotypes after they were dehydrated for 2 h, 4 h, 6h and 8 h. Detailed measurements of WLR at the early stage of dehydration (2, 4, 6, and 8 h) showed that WLR was stabilizing after 8 h, and there were no significant changes between these values and WLR after 24 h. Drought stress was applied to 10-day-old seedlings by draining the solution from the container for defined dehydration periods. Leaf tissues of the selected genotypes were harvested from control plants (time 0); and after 2, 4, 8, and 12 h of dehydration. Differential expression trends of Dhn6, Dhn11, Dhn13 and HVA1 genes were detected in phenotypically diverse drought-tolerant hulless barleys, related to different time of dehydration. Results of quantitative real-time PCR indicated that relative level of HVA1 expression was always higher in tolerant genotypes, rapidly increasing at the earlier stages (after 2-4 h of dehydration). However, HVA1 expressions of sensitive genotypes had a fast increase from 8 h to 12 h of stress. Significant differences in expression trends of dehydrin genes between tolerant genotypes and sensitive lines were detected, mainly in Dhn6 and Dhn13 gene, depending on the duration of the dehydration stress. The relative expression levels of Dhn6 gene were significantly higher in tolerant genotypes after 8 h dehydration, by control with notable higher expression levels after 12 h water stress in sensitive ones. The relative expression levels of Dhn13 gene tended to ascend during exposure to dehydration in drought-sensitive genotypes. However, fluctuate trends of Dhn13 expression level were detected in drought-resistant lines, including in lower expression levels of 12 h dehydration as compared to 8 h water stress. It was conclusion that (1) diverse LEA proteins would play variable roles in resisting water stress in plants; (2) expression of Dhn11 gene was not induced by dehydrated signals because of the trends of expression descended in contrasting genotypes suffered from water deficit and (3) variable accumulations on LEA proteins would be appear in diverse drought-tolerant genotypes during dehydrations. It is deduced that higher accumulations of Dhn6 and Dhn13 expression in 8 h dehydration are related to diverse drought-tolerant lines in crops. The present results indicated that different dehydrin genes would play variable functional roles in resisting water stress when plants were suffered from water deficit. The authors suggest physiologically different reactions between resistant and sensitive genotypes may be the results of differential expression of drought-resistant genes and related signal genes in plants. In addition, contrarily induced expression of Dhn11 and Dhn12 was related to dehydration responsive element (DRE) in barleys. The present study indicated that (1) measurements of WLR and RWC could be considered as one index of drought-tolerant screenings; (2) synonymous mutation sites would play important roles in holding out right configurations and functions on DHN6 protein, (3) higher proportion of 11-amino-repeating motifs and polar amino acid residues would contribute to functions on LEA3 protein, (4) the longer drought, the more accumulation on LEA proteins, except for Dhn11 gene in crops and (5) differential responses on expression of LEA protein genes would result in physiological traits of drought tolerance in plants.

Cloning and expression of tumor necrosis factor (TNF alpha) cDNA from red seabream Pagrus major

A fragment of TNFalpha cDNA sequence from red seabream was cloned by homology cloning approach with two degenerated primers which were designed based on the conserved regions of other animals' TNF sequences. The sequence was elongated by 3' and 5' RACE to get the full length CDS sequence. This sequence contained 1264 nucleotides that included a 5' UTR of 85 bp, a 3' UTR of 514 bp and an open reading frame (ORF) of 666 bp which could encode 222 amino acids propeptide. In 3' UTR, there were several mRNA instability motifs and three endotoxin-responsive sequences, but the sequence lacked the polyadenylation signal. The deduced peptide had a clear transmembrane domain, a TNFalpha family signature and a TNF2 family profile. The cell attachment sequence and the glycosaminoglycan attachment sites were also found in the sequence. The red seabream TNF sequence shared relatively high similarity with both mammalian TNFalpha and TNFbeta by multiple sequence alignments. Phylogenetic analysis showed that the piscine TNFalpha were located independently in a different branch compared with mammalian TNFalpha and TNFbeta. Based on the primary and secondary structure analysis and gene expression study, we could concluded that the red seabream TNF should be a TNFalpha, not TNFbeta. RT-PCR was used to study TNFa transcript expression. 24 h after the red seabream was challenged by Vibrio anguillarum, the RS TNFalpha transcript expression were detected in blood, brain, gill, heart, head kidney, kidney, Ever, muscle and spleen. Results showed that TNFalpha mRNA was constitutively expressed in parts of the tissues both in stimulated and unstimulated fish and the expression could be enhanced after the pathogen infection.