抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Principles of Neural Science

KEGG(Kyoto Encyclopedia of Genes and Genomes)〔和文〕 (特集 ゲノム医学の現在と未来--基礎と臨床) -- (データベース)

中枢神経系疾患の治療は正常細胞（ニューロン）の機能維持を目的とするが，脳血管障害のように機能障害の原因が細胞の死滅に基づくことは多い．一方，脳腫瘍の治療においては薬物療法や放射線療法といった腫瘍細胞の死滅を目標とするものが大きな位置を占める．いずれの場合にも，細胞死の機序を理解することは各種病態や治療法の理解のうえで重要である．現在のところ最も研究の進んでいる細胞死の型はアポトーシスである．そのなかで重要な位置を占めるミトコンドリアにおける反応および抗アポトーシス因子について概要を紹介する．

Neuroscience 細胞死：最近の知見

To better determine the history of modern birds, we performed a genome-scale phylogenetic analysis of 48 species representing all orders of Neoaves using phylogenomic methods created to handle genome-scale data. We recovered a highly resolved tree that confirms previously controversial sister or close relationships. We identified the first divergence in Neoaves, two groups we named Passerea and Columbea, representing independent lineages of diverse and convergently evolved land and water bird species. Among Passerea, we infer the common ancestor of core landbirds to have been an apex predator and confirm independent gains of vocal learning. Among Columbea, we identify pigeons and flamingoes as belonging to sister clades. Even with whole genomes, some of the earliest branches in Neoaves proved challenging to resolve, which was best explained by massive protein-coding sequence convergence and high levels of incomplete lineage sorting that occurred during a rapid radiation after the Cretaceous-Paleogene mass extinction event about 66 million years ago.

/pdf/whole-genome-analyses-resolve-early-branches-in-the-tree-of-2wufsv5juy.pdf

Whole-genome analyses resolve early branches in the tree of life of modern birds

The information from multiple microarray experiments can be integrated in an objective manner via meta-analysis. However, multiple meta-analysis approaches are available and their relative strengths have not been directly compared using experimental data in the context of different gene expression scenarios and studies with different degrees of relationship. This study investigates the complementary advantages of meta-analysis approaches to integrate information across studies, and further mine the transcriptome for genes that are associated with complex processes such as behavioral maturation in honey bees. Behavioral maturation and division of labor in honey bees are related to changes in the expression of hundreds of genes in the brain. The information from various microarray studies comparing the expression of genes at different maturation stages in honey bee brains was integrated using complementary meta-analysis approaches. Comparison of lists of genes with significant differential expression across studies failed to identify genes with consistent patterns of expression that were below the selected significance threshold, or identified genes with significant yet inconsistent patterns. The meta-analytical framework supported the identification of genes with consistent overall expression patterns and eliminated genes that exhibited contradictory expression patterns across studies. Sample-level meta-analysis of normalized gene-expression can detect more differentially expressed genes than the study-level meta-analysis of estimates for genes that were well described by similar model parameter estimates across studies and had small variation across studies. Furthermore, study-level meta-analysis was well suited for genes that exhibit consistent patterns across studies, genes that had substantial variation across studies, and genes that did not conform to the assumptions of the sample-level meta-analysis. Meta-analyses confirmed previously reported genes and helped identify genes (e.g. Tomosyn, Chitinase 5, Adar, Innexin 2, Transferrin 1, Sick, Oatp26F) and Gene Ontology categories (e.g. purine nucleotide binding) not previously associated with maturation in honey bees. This study demonstrated that a combination of meta-analytical approaches best addresses the highly dimensional nature of genome-wide microarray studies. As expected, the integration of gene expression information from microarray studies using meta-analysis enhanced the characterization of the transcriptome of complex biological processes.

/pdf/meta-analysis-of-genome-wide-expression-patterns-associated-31z9yj2thf.pdf

Meta-analysis of genome-wide expression patterns associated with behavioral maturation in honey bees.

Single nucleotide polymorphisms (SNPs) associated with average daily gain (ADG) and dry matter intake (DMI), two major components of feed efficiency in cattle, were identified in a genome-wide association study (GWAS). Uni- and multi-SNP models were used to describe feed efficiency in a training data set and the results were confirmed in a validation data set. Results from the univariate and bivariate analyses of ADG and DMI, adjusted by the feedlot beef steer maintenance requirements, were compared. The bivariate uni-SNP analysis identified (P-value <0.0001) 11 SNPs, meanwhile the univariate analyses of ADG and DMI identified 8 and 9 SNPs, respectively. Among the six SNPs confirmed in the validation data set, five SNPs were mapped to KDELC2, PHOX2A, and TMEM40. Findings from the uni-SNP models were used to develop highly accurate predictive multi-SNP models in the training data set. Despite the substantially smaller size of the validation data set, the training multi-SNP models had slightly lower predictive ability when applied to the validation data set. Six Gene Ontology molecular functions related to ion transport activity were enriched (P-value <0.001) among the genes associated with the detected SNPs. The findings from this study demonstrate the complementary value of the uni- and multi-SNP models, and univariate and bivariate GWAS analyses. The identified SNPs can be used for genome-enabled improvement of feed efficiency in feedlot beef cattle, and can aid in the design of empirical studies to further confirm the associations.

/pdf/bivariate-genome-wide-association-analysis-of-the-growth-and-2fmmwdi6x5.pdf

Bivariate genome-wide association analysis of the growth and intake components of feed efficiency.

Mortality records from birth to weaning of 8,301 lambs from a composite population at the U.S. Meat Animal Research Center were analyzed using a competing risks model. The advantage of the competing risks model over traditional survival analyses is that different hazards of mortality can be assigned to different causes, such as disease, dystocia, and starvation. In this study, specific causes of mortality were grouped into dam-related (DAMR; e.g., dystocia and starvation), pneumonia (PNEU), disease (DIS; excluding pneumonia), and other (OTHER) categories. The hazard of mortality was analyzed using a competing risk approach, where each mortality category was assumed to be independent. Continuous- and discrete-time survival analyses were implemented using sire, animal, and maternal effects mixed models. The continuous-time survival analysis used the Weibull model to describe the hazard of mortality for each category of mortality. Under the discrete-time survival analysis, a complementary log-log link function was used to analyze animal-time data sets using weekly intervals for each category of mortality. Explanatory variables were sex, type of birth, contemporary group, and age of dam. The significant influences of type of birth and age of dam effects were consistent across category of mortality, and the sex effect was significant for all categories except the OTHER category. Estimates of variance components indicated strong maternal effects for all categories except for PNEU. Estimates of additive genetic heritabilities from the discrete maternal effects models were 0.08 ± 0.04, 0.09 ± 0.18, 0.16 ± 0.12, 0.19 ± 0.09, and 0.14 ± 0.10 for OVERALL (all causes combined), DIS, DAMR, PNEU, and OTHER categories, respectively. Ignoring the cause of the defining event in mortality and longevity studies may hide important genetic differences. Therefore, the effectiveness of breeding programs relying on models that ignore multiple causes of an event in time-to-event data, such as mortality and longevity, could be affected.

Competing risks analysis of lamb mortality in a terminal sire composite population.

Background
Alternative exon usage (AEU) is an important component of gene regulation. Exon expression platforms allow the detection of associations between AEU and phenotypes such as cancer. Numerous studies have identified associations between gene expression and the brain cancer glioblastoma multiforme (GBM). The few consistent gene expression biomarkers of GBM that have been reported may be due to the limited consideration of AEU and the analytical approaches used. The objectives of this study were to develop a model that accounts for the variations in expression present between the exons within a gene and to identify AEU biomarkers of GBM survival.

/pdf/identification-and-characterization-of-alternative-exon-49v4xexvef.pdf

Identification and characterization of alternative exon usage linked glioblastoma multiforme survival

Neuropeptides are cell to cell signalling molecules that regulate many critical biological processes including development, growth and reproduction. These peptides result from the complex processing of prohormone proteins, making their characterization both challenging and resource demanding. In fact, only 42 neuropeptide genes have been empirically confirmed in cattle. Neuropeptide research using high-throughput technologies such as microarray and mass spectrometry require accurate annotation of prohormone genes and products. However, the annotation and associated prediction efforts, when based solely on sequence homology to species with known neuropeptides, can be problematic. Complementary bioinformatic resources were integrated in the first survey of the cattle neuropeptide complement. Functional neuropeptide characterization was based on gene expression profiles from microarray experiments. Once a gene is identified, knowledge of the enzymatic processing allows determination of the final products. Prohormone cleavage sites were predicted using several complementary cleavage prediction models and validated against known cleavage sites in cattle and other species. Our bioinformatics approach identified 92 cattle prohormone genes, with 84 of these supported by expressed sequence tags. Notable findings included an absence of evidence for a cattle relaxin 1 gene and evidence for a cattle galanin-like peptide pseudogene. The prohormone processing predictions are likely accurate as the mammalian proprotein convertase enzymes, except for proprotein convertase subtilisin/kexin type 9, were also identified. Microarray analysis revealed the differential expression of 21 prohormone genes in the liver associated with nutritional status and 8 prohormone genes in the placentome of embryos generated using different reproductive techniques. The neuropeptide cleavage prediction models had an exceptional performance, correctly predicting cleavage in more than 86% of the prohormone sequence positions. A substantial increase in the number of cattle prohormone genes identified and insights into the expression profiles of neuropeptide genes were obtained from the integration of bioinformatics tools and database resources and gene expression information. Approximately 20 prohormones with no empirical evidence were detected and the prohormone cleavage sites were predicted with high accuracy. Most prohormones were supported by expressed sequence tag data and many were differentially expressed across nutritional and reproductive conditions. The complete set of cattle prohormone sequences identified and the cleavage prediction approaches are available at http://neuroproteomics.scs.uiuc.edu/neuropred.html
 .

https://link.springer.com/content/pdf/10.1186%2F1471-2164-10-228.pdf

Bruce R. Southey

Papers

Meta-analysis of genome-wide expression patterns associated with behavioral maturation in honey bees.

Bivariate genome-wide association analysis of the growth and intake components of feed efficiency.

Competing risks analysis of lamb mortality in a terminal sire composite population.

Identification and characterization of alternative exon usage linked glioblastoma multiforme survival

Characterization of the prohormone complement in cattle using genomic libraries and cleavage prediction approaches.