不同水肥处理对尾叶桉苗木生长及生物量分配的影响

为筛选适宜不同水肥条件的尾叶桉（Eucalyptus urophylla）优良无性系,以34个尾叶桉无性系为研究对象,采用2因素（水分、养分）3水平完全随机区组设计,对不同水肥处理下18个月的尾叶桉苗木生长和各器官生物量进行方差分析和遗传参数评估。结果表明：除少数性状外,尾叶桉生长（树高、地径）和生物量（主干、侧枝、根）在不同区组、水分、养分、水分×养分互作及无性系的差异间均达到显著或极显著水平,表明水分、养分和无性系会影响尾叶桉生长和各器官生物量大小。在水分和养分组合处理下,尾叶桉生长和各个器官生物量在组合33（高水高肥）和组合32（高水中肥）处理下表现较好。全株总鲜质量在组合32处理最大,与组合11处理相比增加了135.70%。主干、根、叶和总生物量的鲜质量与干质量相关系数最高,相关系数在0.90以上。无性系在树高、地径和生物量的方差分量为4.28~31 255.80,大部分性状的单株重复力在0.15以上,且都达到了显著水平。以15%无性系入选率,采用BLUP预测的尾叶桉无性系基因型值筛选出ZQUB39和ZQUC23尾叶桉在水分和养分梯度较低的土壤环境中生长较好,UD42、LDUC1和ZQUA3在水分和养分梯度较高的土壤环境中生长较好。这些优良无性系可能在多种立地进行推广种植。     

Sequencing XMET genes to promote genotype-guided risk assessment and precision medicine

High-throughput next generation sequencing(NGS) is a shotgun approach applied in a parallel fashion by which the genome is fragmented and sequenced through small pieces and then analyzed either by aligning to a known reference genome or by de novo assembly without reference genome. This technology has led researchers to conduct an explosion of sequencing related projects in multidisciplinary fields of science. However, due to the limitations of sequencing-based chemistry, length of sequencing reads and the complexity of genes, it is difficult to determine the sequences of some portions of the human genome, leaving gaps in genomic data that frustrate further analysis. Particularly, some complex genes are difficult to be accurately sequenced or mapped because they contain high GC-content and/or low complexity regions, and complicated pseudogenes, such as the genes encoding xenobiotic metabolizing enzymes and transporters(XMETs). The genetic variants in XMET genes are critical to predicate interindividual variability in drug efficacy, drug safety and susceptibility to environmental toxicity. We summarized and discussed challenges, wet-lab methods, and bioinformatics algorithms in sequencing "complex" XMET genes, which may provide insightful information in the application of NGS technology for implementation in toxicogenomics and pharmacogenomics.     

低温驯化对苗木生理及核酸转录的影响

以华北落叶松幼苗为材料,研究低温驯化对苗木生长发育有关的某些生理指标以及核酸转录的影响。试验结果表明,冷驯化可以提高植物的抗寒性。冷驯化后的幼苗受到－２０℃低温胁迫时,细胞质膜Ｋ＾＋的渗漏比对照少,光合性能提高,ＲＮＡ和可溶性蛋白质增加。     

Evaluation of external RNA controls for the assessment of microarray performance

External RNA controls (ERCs), although important for microarray assay performance assessment, have yet to be fully implemented in the research community. As part of the MicroArray Quality Control (MAQC) study, two types of ERCs were implemented and evaluated; one was added to the total RNA in the samples before amplification and labeling; the other was added to the copyRNAs (cRNAs) before hybridization. ERC concentration-response curves were used across multiple commercial microarray platforms to identify problematic assays and potential sources of variation in the analytical process. In addition, the behavior of different ERC types was investigated, resulting in several important observations, such as the sample-dependent attributes of performance and the potential of using these control RNAs in a combinatorial fashion. This multiplatform investigation of the behavior and utility of ERCs provides a basis for articulating specific recommendations for their future use in evaluating assay performance across multiple platforms.     

Decision Forest Analysis of 61 Single Nucleotide Polymorphisms in a Case-Control Study of Esophageal Cancer; a novel method

Background

Systematic evaluation and study of single nucleotide polymorphisms (SNPs) made possible by high throughput genotyping technologies and bioinformatics promises to provide breakthroughs in the understanding of complex diseases. Understanding how the millions of SNPs in the human genome are involved in conferring susceptibility or resistance to disease, or in rendering a drug efficacious or toxic in the individual is a major goal of the relatively new fields of pharmacogenomics. Esophageal squamous cell carcinoma is a high-mortality cancer with complex etiology and progression involving both genetic and environmental factors. We examined the association between esophageal cancer risk and patterns of 61 SNPs in a case-control study for a population from Shanxi Province in North Central China that has among the highest rates of esophageal squamous cell carcinoma in the world.

Methods

High-throughput Masscode mass spectrometry genotyping was done on genomic DNA from 574 individuals (394 cases and 180 age-frequency matched controls). SNPs were chosen from among genes involving DNA repair enzymes, and Phase I and Phase II enzymes.We developed a novel adaptation of the Decision Forest pattern recognition method named Decision Forest for SNPs (DF-SNPs). The method was designated to analyze the SNP data.

Results

The classifier in separating the cases from the controls developed with DF-SNPs gave concordance, sensitivity and specificity, of 94.7%, 99.0% and 85.1%, respectively; suggesting its usefulness for hypothesizing what SNPs or combinations of SNPs could be involved in susceptibility to esophageal cancer. Importantly, the DF-SNPs algorithm incorporated a randomization test for assessing the relevance (or importance) of individual SNPs, SNP types (Homozygous common, heterozygous and homozygous variant) and patterns of SNP types (SNP patterns) that differentiate cases from controls. For example, we found that the different genotypes of SNP GADD45B E1122 are all associated with cancer risk.

Conclusion

The DF-SNPs method can be used to differentiate esophageal squamous cell carcinoma cases from controls based on individual SNPs, SNP types and SNP patterns. The method could be useful to identify potential biomarkers from the SNP data and complement existing methods for genotype analyses.

     

基于投入产出表的中国水足迹走势分析

水足迹是近年来国内外研究水资源压力的常用方法.基于投入产出表的水足迹分析方法,分析了我国1997-2007年的水足迹状况,改进了耗水系数的计算方法,研究了基于稀释理论的灰水足迹计算方法,计算了外部水足迹及额外水足迹负重以及相应系数,分析了我国水足迹消费的商品(服务)结构.结果表明,1997-2007年我国年均水足迹总量为2.83万亿m3,总体呈现下降趋势,其中蓝水足迹为2183亿m3,灰水足迹为2.62万亿m3(以Ⅲ类水标准核算).在水足迹总量中,间接水足迹占据比例达到90％,可见水资源压力的产生主要基于商品或服务的消费.我国水足迹基本上依靠自给,同时我国承担其他国家的水资源压力的比例很大,但是整体上呈现下降趋势.从水足迹消费商品(服务)结构上看,与饮食相关的商品或服务占较大比例.     

Genome-wide assessment of population structure and genetic diversity of Eucalyptus urophylla based on a multi-species single-nucleotide polymorphism chip analysis

Tree Genetics & Genomes - The fruit of American cranberry (Vaccinium macrocarpon Ait.) is known for its tart, acidic taste. Although some acidity is required for expressing fruit flavor, the...     

Evaluating variations of genotype calling: a potential source of spurious associations in genome-wide association studies

Genome-wide association studies (GWAS) examine the entire human genome with the goal of identifying genetic variants (usually single nucleotide polymorphisms (SNPs)) that are associated with phenotypic traits such as disease status and drug response. The discordance of significantly associated SNPs for the same disease identified from different GWAS indicates that false associations exist in such results. In addition to the possible sources of spurious associations that have been investigated and discussed intensively, such as sample size and population stratification, an accurate and reproducible genotype calling algorithm is required for concordant GWAS results from different studies. However, variations of genotype calling of an algorithm and their effects on significantly associated SNPs identified in downstream association analyses have not been systematically investigated. In this paper, the variations of genotype calling using the Bayesian Robust Linear Model with Mahalanobis distance classifier (BRLMM) algorithm and the resulting influence on the lists of significantly associated SNPs were evaluated using the raw data of 270 HapMap samples analysed with the Affymetrix Human Mapping 500K Array Set (Affy500K) by changing algorithmic parameters. Modified were the Dynamic Model (DM) call confidence threshold (threshold) and the number of randomly selected SNPs (size). Comparative analysis of the calling results and the corresponding lists of significantly associated SNPs identified through association analysis revealed that algorithmic parameters used in BRLMM affected the genotype calls and the significantly associated SNPs. Both the threshold and the size affected the called genotypes and the lists of significantly associated SNPs in association analysis. The effect of the threshold was much larger than the effect of the size. Moreover, the heterozygous calls had lower consistency compared to the homozygous calls.