A trait-based approach to assess climate change sensitivity of freshwater invertebrates across Swedish ecoregions

Freshwater habitats and organisms are among the most threatened on Earth, and freshwater ecosystems have been subject to large biodiversity losses. We developed a Climate Change Sensitivity （CCS） indicator based on trait information for a selection of stream- and lake-dwelling Ephemeroptera, Plecoptera and Trichoptera taxa. We calculated the CCS scores based on ten species traits identified as sensitive to global climate change. We then assessed climate change sensitivity between the six main ecoregions of Sweden as well as the three Swedish regions based on lilies. This was done using biological data from 1,382 stream and lake sites where we compared large-scale （ecoregional） patterns in climate change sensitivity with potential future exposure of these ecosystems to increased temperatures using ensemble-modelled future changes in air temperature. Current （1961-1990） measured temperature and ensemble-modelled future （2100） temperature showed an increase from the northernmost towards the southern ecoregions, whereas the predicted temperature change increased from south to north. The CCS indicator scores were highest in the two northernmost boreal ecoregions where we also can expect the largest global climate change-induced increase in temperature, indicating an unfortunate congruence of exposure and sensitivity to climate change. These results are of vital importance when planning and implementing management and conservation strategies in freshwater ecosystems, e.g., to mitigate increased temperatures using riparian buffer strips. We conclude that traits information on taxa specialization, e.g., in terms of feeding specialism or taxa having a preference for high altitudes as well as sensitivity to changes in temperature are important when assessing the risk from future global climate change to freshwater ecosystems [Current Zoology 60 （2）： 221-232, 2014].     

A hybrid SOM-SVM approach for the zebrafish gene expression analysis

Microarray technology can be employed to quantitatively measure the expression of thousands of genes in a single experiment. It has become one of the main tools for global gene expression analysis in molecular biology research in recent years. The large amount of expression data generated by this technology makes the study of certain complex biological problems possible, and machine learning methods are expected to play a crucial role in the analysis process. In this paper, we present our results from integrating the self-organizing map （SOM） and the support vector machine （SVM） for the analysis of the various functions of zebrafish genes based on their expression. The most distinctive characteristic of our zebrafish gene expression is that the number of samples of different classes is imbalanced. We discuss how SOM can be used as a data-filtering tool to improve the classification performance of the SVM on this data set.     

Multi-class cancer classification through gene expression profiles:microRNA versus mRNA

Both microRNA （miRNA） and mRNA expression profiles are important methods for cancer type classification. A comparative study of their classification performance will be helpful in choosing the means of classification. Here we evaluated the classification performance of miRNA and mRNA profiles using a new data mining approach based on a novel SVM （Support Vector Machines） based recursive fea- ture elimination （nRFE） algorithm. Computational experiments showed that information encoded in miRNAs is not sufficient to classify cancers; gut-derived samples cluster more accurately when using mRNA expression profiles compared with using miRNA profiles; and poorly differentiated tumors （PDT） could be classified by mRNA expression profiles at the accuracy of 100% versus 93.8% when using miRNA profiles. Furthermore, we showed that mRNA expression profiles have higher capacity in normal tissue classifications than miRNA. We concluded that classification performance using mRNA profiles is superior to that of miRNA profiles in multiple-class cancer classifications.     

Comparative Gene Expression Analysis of Mouse and Human Cardiac Maturation

Understanding how human cardiomyocytes mature is crucial to realizing stem cell-based heart regeneration, modeling adult heart diseases, and facilitating drug discovery. However, it is not feasible to analyze human samples for maturation due to inaccessibility to samples while cardiomy-ocytes mature during fetal development and childhood, as well as difficulty in avoiding variations among individuals. Using model animals such as mice can be a useful strategy;nonetheless, it is not well-understood whether and to what degree gene expression profiles during maturation are shared between humans and mice. Therefore, we performed a comparative gene expression analysis of mice and human samples. First, we examined two distinct mice microarray platforms for shared gene expression profiles, aiming to increase reliability of the analysis. We identified a set of genes display-ing progressive changes during maturation based on principal component analysis. Second, we demonstrated that the genes identified had a differential expression pattern between adult and ear-lier stages (e.g., fetus) common in mice and humans. Our findings provide a foundation for further genetic studies of cardiomyocyte maturation.     

Reference genes identified in the silkworm Bombyx moil during metamorphism based on oligonucleotide microarray and confirmed by qRT-PCR

Gene expression quantification at mRNA level is very important for postgenomic studies, as gene expression level is the reflection of the special biological function of the target gene. Methods used for gene expression quantification, such as microarray or quantitative real-time polymerase chain reaction （qRT-PCR）, require stable expressed reference genes. Thus, finding suitable control genes is essential for gene quantification. In this study, a genome-wide survey of reference genes during metamorphism was performed on silkworm Bombyx mori. Twelve genes were chosen as putative reference genes based on a whole genome oligonucleotide microarray normalized by external controls. Then, qRT- PCR was employed for further validation and selection of potential reference gene candidates. The results were analyzed, and stable genes were selected using geNorm 3.4 and NormFinder software. Finally, considering factors from every aspect, translation initiation factor 4A, translation initiation factor 3 subunit 4, and translation initiation factor 3 subunit 5 （represented by sw22934, sw14876, and sw13956） were selected as reliable internal controls across the examined developmental stages, while cytoplasmic actin （sw22671）, the commonly used reference gene in a previous study was shown to vary drastically throughout the examined developmental stages. For future research, we recommend the use of the geometric mean of those three stable reference genes as an accurate normalization factor for data normalization of different developmental stages during metamorphism.     

CDS: a fold-change based statistical test for concomitant identification of distinctness and similarity in gene expression analysis

The problem of identifying differential activity such as in gene expression is a major defeat in biostatistics and bioinformatics.Equally important,however much less frequently studied,is the question of similar activity from one biological condition to another.The foldchange,or ratio,is usually considered a relevant criterion for stating difference and similarity between measurements.Importantly,no statistical method for concomitant evaluation of similarity and distinctness currently exists for biological applications.Modem microarray,digital PCR(dPCR),and Next-Generation Sequencing(NGS) technologies frequently provide a means of coefficient of variation estimation for individual measurements.Using fold-change,and by making the assumption that measurements are normally distributed with known variances,we designed a novel statistical test that allows us to detect concomitantly,thus using the same formalism,differentially and similarly expressed genes(http://cds.ihes.fr).Given two sets of gene measurements in different biological conditions,the probabilities of making type I and type II errors in stating that a gene is differentially or similarly expressed from one condition to the other can be calculated.Furthermore,a confidence interval for the fold-change can be delineated.Finally,we demonstrate that the assumption of normality can be relaxed to consider arbitrary distributions numerically.The Concomitant evaluation of Distinctness and Similarity(CDS) statistical test correctly estimates similarities and differences between measurements of gene expression.The implementation,being time and memory efficient,allows the use of the CDS test in high-throughput data analysis such as microarray,dPCR,and NGS experiments.Importantly,the CDS test can be applied to the comparison of single measurements(N:1) provided the variance(or coefficient of variation) of the signals is known,making CDS a valuable tool also in biomedical analysis where typically a single measurement per subject is available.     

Late Pliocene diversity and distribution of Drynaria(Polypodiaceae) in western Yunnan explained by forest vegetation and humid climates

The palaeodiversity of flowering plants in Yunnan has been extensively interpreted from both a molecular and fossil perspective. However, for cryptogamic plants such as ferns, the palaeodiversity remains poorly known. In this study, we describe a new ferny fossil taxon, Drynaria lanpingensis sp. nov. Huang,Su et Zhou(Polypodiaceae), from the late Pliocene of northwestern Yunnan based on fragmentary frond and pinna with in situ spores. The frond is pinnatifid and the pinnae are entirely margined. The sori are arranged in one row on each side of the primary vein. The spores have a semicircular to bean-shaped equatorial view and a tuberculate surface. Taken together with previously described fossils, there are now representatives of three known fossil taxa of Drynaria from the late Pliocene of western Yunnan.These finds suggest that Drynaria diversity was considerable in the region at that time. As Drynaria is a shade-tolerant plant, growing preferably in wet conditions in the understory of forests, its extensive existence may indicate forest vegetation and humid climates in western Yunnan during the late Pliocene.This is in line with results from floristic investigations and palaeoclimatic reconstructions based on fossil floras.     

Maxi-anion channel as a candidate pathway for osmosensitive ATP release from mouse astrocytes in primary culture

In the present study, we aimed to evaluate the pathways contributing to ATP release from mouse astrocytes during hypoosmotic stress. We first examined the expression of mRNAs for proteins constituting possible ATP- releasing pathways that have been suggested over the past several years. In RT-PCR analysis using both control and osmotically swollen astrocytes, amplification of cDNA fragments of expected size was seen for connexins （Cx32, Cx37, Cx43）, pannexin 1 （Pxl）, the P2X7 receptor, MRP1 and MDR1, but not CFTR. Inhibitors of exocytotic vesicular release, gap junction hemi-channels, CFTR, MRP1, MDR1, the P2X7 receptor, and volume-sensitive outwardly rectifying chloride channels had no significant effects on the massive ATP release from astrocytes. In contrast, the hypotonicity-induced ATP release from astrocytes was most effectively inhibited by gadolinium （50 μM）, an inhibitor of the maxi-anion channel, which has recently been shown to serve as a pathway for ATP release from several other cell types. Thus, we propose that the maxi-anion channel constitutes a major pathway for swelling-induced ATP release from cultured mouse astrocytes as well.     

Widely predicting specific protein functions based on protein-protein interaction data and gene expression profile

GESTs (gene expression similarity and taxonomy similarity), a gene functional prediction approach previously proposed by us, is based on gene expression similarity and concept similarity of functional classes defined in Gene Ontology (GO). In this paper, we extend this method to protein-protein interac-tion data by introducing several methods to filter the neighbors in protein interaction networks for a protein of unknown function(s). Unlike other conventional methods, the proposed approach automati-cally selects the most appropriate functional classes as specific as possible during the learning proc-ess, and calls on genes annotated to nearby classes to support the predictions to some small-sized specific classes in GO. Based on the yeast protein-protein interaction information from MIPS and a dataset of gene expression profiles, we assess the performances of our approach for predicting protein functions to “biology process” by three measures particularly designed for functional classes organ-ized in GO. Results show that our method is powerful for widely predicting gene functions with very specific functional terms. Based on the GO database published in December 2004, we predict some proteins whose functions were unknown at that time, and some of the predictions have been confirmed by the new SGD annotation data published in April, 2006.     

Defining reference genes for quantitative real-time PCR analysis of anther development in rice

Quantitative real-time polymerase chain reaction （qPCR） is one of the most accurate and widely used methods for gene expression analysis. However, the choice of reference genes for normalization is critical for accurate quantifica- tion of gene expression. As development of genomics, mining large-scale datasets such as microarray and RNAsequencing data becomes a new approach for exploitation of new reference genes. In this study, we analyzed an RNAsequencing dataset of rice anther and 167 microarray datasets involving different tissues and developing stages of rice anthers and pollens. We selected 12 candidate genes and other 5 reference genes, including ACT1, eEF-1α, GAPDH, Exp2, and CCDC72 used in previous studies, and evaluated their expression in eight tissues and different developmental stages of anthers in rice variety 9311 and Yuetai. UPF3, elF4A-3, GAPDH, and PPP6 were identified as the most suitable reference genes for qPCR analysis of anther development in rice. The new candidate reference genes showed more stable expression than the traditionally used reference genes. These results provide a set of reliable reference genes for studies in rice anther developmental process.     

Hidden Markov models incorporating fuzzy measures and integrals for protein sequence identification and alignment

Profile hidden Markov models （HMMs） based on classical HMMs have been widely applied for protein sequence identification. The formulation of the forward and backward variables in profile HMMs is made under statistical independence assumption of the probability theory. We propose a fuzzy profile HMM to overcome the limitations of that assumption and to achieve an improved alignment for protein sequences belonging to a given family. The proposed model fuzzifies the forward and backward variables by incorporating Sugeno fuzzy measures and Choquet integrals, thus further extends the generalized HMM. Based on the fuzzified forward and backward variables, we propose a fuzzy Baum-Welch parameter estimation algorithm for profiles. The strong correlations and the sequence preference involved in the protein structures make this fuzzy architecture based model as a suitable candidate for building profiles of a given family, since the fuzzy set can handle uncertainties better than classical methods.     

Construction of Oryza sativa genome contigs by fingerprint strategy

We described the construction of BAC contigs of the genome of a indica variety of Oryza sativa.Guang Lu Ai 4. An entire representative(Sixfold coverage of rice chromosomes)and genetically stable BAC library of rice genome constructed in this lab has been systematically analysed by restriction enzyme fragmentation and polyacrylamide gel electrophoresis.And all the images thus obtained were subject to image-processing,which consisted of preliminary location of bands,cooperative tracking of lanes by correlation of adjacent bads.a precise densitometric pass,alignment at the marker bands with the standard,optional interactive editing,and normalization of the accepted bands.The contigs were generated based on the Computer Software specially designed for genome mapping.The number of contigs with 600 kb in length on average was 464.of contigs with 1000kb in length on average was 107; of contigs with 1500 kb in length on average was Construction of Oryza Sativa genome contigs.23.Therefor,all the contigs we have obtained ampunted up to 420 megabases in length.Considering the size of rice genome(430 megabased),the contigs generated in this lab have covered nearly 98% of the rice genome.We are now in the process of mapping the contigs to chromosomes.     

Mobility affects copulation and oviposition dynamics in Pieris brassicae in seminatural cages

When, how often and for how long organisms mate can have strong consequences for individual fitness and are crucial aspects of evolutionary ecology. Such determinants are likely to be of even greater importance in monandrous species and species with short adult life stages. Previous work suggests that mobility, a key dispersal? related trait, may affect the dynamics of copulations, but few studies have investigated the impact of individual mobility on mating latency, copulation duration and oviposition latency simultaneously. In this paper, we monitored the copulation dynamics of 40 males and 40 females, as well as the oviposition dynamics of the females of the Large White butterfly Pieris brassicae, a facultative long-distance disperser butterfly. Individuals from a breeding were selected to create a uniform distribution of mobility and we recorded the timing, number and duration of all copulations in a semiexperimental system. We showed that mobility, measured as the time spent in flight under stressful conditions (a proxy of dispersal tendency), correlates with all aspects of copulation dynamics: mobile males and females mated earlier and for shorter periods than less mobile individuals. In turn, late mating females increased the time between copulation and oviposition. These results feed the previously described mobility syndrome of R brassicae, involving morphological and physiological characters, with life-history traits. We suggest that the reduction of mating latency and copulation duration has an adaptive value in dispersing individuals, as their life expectancy might be shorter than that of sedentary individuals.     

Whole miRNome-wide Differential Co-expression of MicroRNAs

Co-regulation of genes has been extensively analyzed, however, rather limited knowledge is available on co-regulations within the miRNome. We investigated differential co-expression of microRNAs (miRNAs) based on miRNome profiles of whole blood from 540 individuals. These include patients suffering from different cancer and non-cancer diseases, and unaffected controls. Using hierarchi-cal clustering, we found 9 significant clusters of co-expressed miRNAs containing 2-36 individual miRNAs. Through analyzing multiple sequencing alignments in the clusters, we found that co-expression of miRNAs is associated with both sequence similarity and genomic co-localization. We calculated correlations for all 371,953 pairs of miRNAs for all 540 individuals and identified 184 pairs of miRNAs with high correlation values. Out of these 184 pairs of miRNAs, 16 pairs (8.7%) were differentially co-expressed in unaffected controls, cancer patients and patients with non-cancer diseases. By computing correlated and anti-correlated miRNA pairs, we constructed a network with 184 putative co-regulations as edges and 100 miRNAs as nodes. Thereby, we detected specific clusters of miRNAs with high and low correlation values. Our approach represents the most comprehensive co-regulation analysis based on whole miRNome-wide expression profiling. Our findings further decrypt the interactions of miRNAs in normal and human pathological processes.