Integration of pre-normalized microarray data using quantile correction

An enormous amount of microarray data has been collected and accumulated in public repositories. Although some of the depositions include raw and processed data, significant parts of them include processed data only. If we need to combine multiple datasets for specific purposes, the data should be adjusted prior to use to remove bias between the datasets. We focused on a GeneChip platform and a pre-processing method, RMA, and examined simple quantile correction as the post-processing method for integration. Integration of the data pre-processed by RMA was evaluated using artificial spike-in datasets and real microarray datasets of atopic dermatitis and lung cancer. Studies using the spike-in datasets show that the quantile correction for data integration reduces the data quality at some extent but it should be acceptable level. Studies using the real datasets show that the quantile correction significantly reduces the bias. These results show that the quantile correction is useful for integration of multiple datasets processed by RMA, and encourage effective use of public microarray data.     

Dynein prevents erroneous kinetochore-microtubule attachments in mitosis

Equal distribution of the genetic material during cell division relies on efficient congression of chromosomes to the metaphase plate. Prior to their alignment, the Dynein motor recruited to kinetochores transports a fraction of laterally-attached chromosomes along microtubules toward the spindle poles. By doing that, Dynein not only contributes to chromosome movements, but also prevents premature stabilization of end-on kinetochore-microtubule attachments. This is achieved by 2 parallel mechanisms: 1) Dynein-mediated poleward movement of chromosomes counteracts opposite polar-ejection forces (PEFs) on chromosome arms by the microtubule plus-end-directed motors chromokinesins. Otherwise, they could stabilize erroneous syntelic kinetochore-microtubule attachments and lead to the random ejection of chromosomes away from the spindle poles; and 2) By transporting chromosomes to the spindle poles, Dynein brings the former to the zone of highest Aurora A kinase activity, further destabilizing kinetochore-microtubule attachments. Thus, Dynein plays an important role in keeping chromosome segregation error-free by preventing premature stabilization of kinetochore-microtubule attachments near the spindle poles.     

Changes in soil organic carbon,nitrogen, pH and bulk density with the development of larch (Larix gmelinii) plantations in China

Under the government of China's environmental program known as Returning Farmland To Forests (RFTF), about 28 million hectares of farmland have been converted to tree plantation. This has led to a large accumulation of biomass carbon, but less is known about underground carbon‐related processes. One permanent plot (25 years of observation) and four chronosequence plot series comprising 159 plots of larch (Larix gmelinii) plantations in northeastern China were studied. Both methods found significant soil organic carbon (SOC) accumulation (96.4 g C m^?2 yr^?1) and bulk density decrease (5.7 mg cm^?3 yr^?1) in the surface soil layer (0–20 cm), but no consistent changes in deeper layers, indicating that larch planting under the RFTF program can increase SOC storage and improve the physical properties of surface soil. Nitrogen depletion (4.1–4.3 g m^?2 yr^?1), soil acidification (0.007–0.022 pH units yr^?1) and carbon/nitrogen (C/N) ratio increase (0.16–0.46 per year) were observed in lessive soil, whereas no significant changes were found in typical dark‐brown forest soil. This SOC accumulation rate (96.4 g m^?2 yr^?1) can take 39% of the total carbon sink capacity [net ecosystem exchange (NEE)] of larch forests in this region and the total soil carbon sequestration could be 87 Tg carbon within 20 years of plantation by approximating all larch plantations in northeastern China (4.5 Mha), showing the importance of soil carbon accumulation in the ecosystem carbon balance. By comparison with the rates of these processes in agricultural use, the RFTF program of reversing land use for agriculture will rehabilitate SOC, soil fertility and bulk density slowly (< 69% of the depletion rate in agricultural use), so that a much longer duration is needed to rehabilitate the underground function of soil via the RFTF program. Global forest plantations on abandoned farmland or function to protecting farmland are of steady growth and our findings may be important for understanding their underground carbon processes.     

Ecological effects of cell-level processes: genome size,functional traits and regional abundance of herbaceous plant species

Background and Aims

Genome size is known to be correlated with a number of phenotypic traits associated with cell sizes and cell-division rates. Genome size was therefore used as a proxy for them in order to assess how common plant traits such as height, specific leaf area and seed size/number predict species regional abundance. In this study it is hypothesized that if there is residual correlation between genome size and abundance after these traits are partialled out, there must be additional ecological effects of cell size and/or cell-division rate.

Methods

Variation in genome size, plant traits and regional abundance were examined in 436 herbaceous species of central European flora, and relationships were sought for among these variables by correlation and path analysis.

Key Results

Species regional abundance was weakly but significantly correlated with genome size; the relationship was stronger for annuals (R² = 0·145) than for perennials (R² = 0·027). In annuals, genome size was linked to abundance via its effect on seed size, which constrains seed number and hence population growth rate. In perennials, it weakly affected (via height and specific leaf area) competitive ability. These relationships did not change qualitatively after phylogenetic correction. In both annuals and perennials there was an unresolved effect of genome size on abundance.

Conclusions

The findings indicate that additional predictors of regional abundance should be sought among variables that are linked to cell size and cell-division rate. Signals of these cell-level processes remain identifiable even at the landscape scale, and show deep differences between perennials and annuals. Plant population biology could thus possibly benefit from more systematic use of indicators of cell-level processes.     

Bias correction for estimated QTL effects using the penalized maximum likelihood method

A penalized maximum likelihood method has been proposed as an important approach to the detection of epistatic quantitative trait loci (QTL). However, this approach is not optimal in two special situations: (1) closely linked QTL with effects in opposite directions and (2) small-effect QTL, because the method produces downwardly biased estimates of QTL effects. The present study aims to correct the bias by using correction coefficients and shifting from the use of a uniform prior on the variance parameter of a QTL effect to that of a scaled inverse chi-square prior. The results of Monte Carlo simulation experiments show that the improved method increases the power from 25 to 88% in the detection of two closely linked QTL of equal size in opposite directions and from 60 to 80% in the identification of QTL with small effects (0.5% of the total phenotypic variance). We used the improved method to detect QTL responsible for the barley kernel weight trait using 145 doubled haploid lines developed in the North American Barley Genome Mapping Project. Application of the proposed method to other shrinkage estimation of QTL effects is discussed.     

棉铃虫羽化高峰期有效积温预测法的校正

为减小年际间气温变化对昆虫有效积温预测误差的影响,以新疆石河子垦区121团棉铃虫Helicoverpa armigera(Hübner)羽化高峰期为例,利用single sine模型分别计算12年2种有效积温范围(10～30℃和10～35℃)的累计有效积温值,并获得其多年平均值,依此进行棉铃虫羽化高峰期预测;通过当年与12年(有效积温>0日期至羽化高峰日期)平均气温之差,对预测误差进行校正。结果表明:当年平均气温与12年平均值差值越大,预测误差也越大;各代直线回归校正模型均达到显著水平(P<0.05);2种有效积温范围下,校正后各代平均预测误差天数均有所减少,对越冬代误差校正效果最优,校正后各代历史符合率分别为83.33%、100%、100%和100%、100%、93.33%。该校正方法能够显著提高预测准确度,尤其适用于年际间棉铃虫发育期间平均气温变化较大的代别和地区,同时可为多种害虫预测误差校正提供了依据。     

Cell adhesion molecules contribute to Alzheimer's disease: multiple pathway analyses of two genome-wide association studies

Alzheimer's disease (AD) is a kind of complex neurological disorder. The complex genetic architecture of AD makes genetic analysis difficult. Fortunately, a pathway-based method to study the existing genome-wide association studies datasets has been applied into AD. However, no shared Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway was reported. In this study, we performed multiple pathway analyses of French AD genome-wide association studies dataset (discovery dataset, n = 7360, 2032 cases and 5328 controls) and Pfizer dataset (validation dataset, n = 2220, 1034 cases and 1186 controls). First, we performed multiple pathway analyses by Hypergeometric test, improved gene set enrichment analysis (IGSEA) and Z-statistic test in KEGG. Using Hypergeometric test, we identified 54 and 25 significant pathways (p < 0.05) in discovery dataset and validation dataset, respectively. Using IGSEA method, we identified three significant pathways in both discovery and validation datasets, respectively. Using Z-statistic test, we identified 19 significant pathways in validation dataset. Among the significant pathways, cell adhesion molecules (CAM) pathway was identified to be the only consistent signal emerging across multiple analyses in KEGG. After permutation and multiple testing corrections, CAM pathway was significant with p = 2.40E-05 (Hypergeometric test) and p = 3.00E-03 (IGSEA) in discovery dataset. In validation dataset, CAM pathway was significant with p = 1.84E-06 (Hypergeometric test), p = 1.00E-02 (IGSEA) and p = 2.81E-03 (Z-statistic test). We replicated the association by multiple pathway analyses in Gene Ontology using Hypergeometric test (WebGestalt), modified Fisher's exact test (DAVID) and Binomial test (PANTHER). Our findings provided further evidence on the association between CAM pathway and AD susceptibility, which would be helpful to study the genetic mechanisms of AD and may significantly assist in the development of therapeutic strategies.     

Highly multiplexed targeted proteomics using precise control of peptide retention time

Large-scale proteomics applications using SRM analysis on triple quadrupole mass spectrometers present new challenges to LC-MS/MS experimental design. Despite the automation of building large-scale LC-SRM methods, the increased numbers of targeted peptides can compromise the balance between sensitivity and selectivity. To facilitate large target numbers, time-scheduled SRM transition acquisition is performed. Previously published results have demonstrated incorporation of a well-characterized set of synthetic peptides enabled chromatographic characterization of the elution profile for most endogenous peptides. We have extended this application of peptide trainer kits to not only build SRM methods but to facilitate real-time elution profile characterization that enables automated adjustment of the scheduled detection windows. Incorporation of dynamic retention time adjustments better facilitate targeted assays lasting several days without the need for constant supervision. This paper provides an overview of how the dynamic retention correction approach identifies and corrects for commonly observed LC variations. This adjustment dramatically improves robustness in targeted discovery experiments as well as routine quantification experiments.