Restoration of Gene Function by Homologous Recombination: from PCR to Gene Expression in One Step

We have developed a simple method for single-step cloning of any PCR product into a plasmid. A novel selection principle has been applied, in which activation of a drug selection marker is achieved following homologous recombination. In this method a DNA fragment is amplified by PCR with standard oligonucleotides that contain flanking tails derived from the host plasmid and the complete λP_R or rrnA1 promoter regions. The resulting PCR product is then electroporated into an Escherichia coli strain harboring both the phage λ Red functions and the host plasmid. Upon homologous recombination of the PCR fragment into the plasmid, expression of a drug selection marker is fully induced due to restoration of its truncated promoter, thus allowing appropriate selection. Recombinant plasmid vectors encoding β-galactosidase and neomycin phosphotransferase were constructed by using this method in two well-known Red systems. This cloning strategy significantly reduces both the time and costs associated with cloning procedures.     

Using Markers in Gene Introgression Breeding Programs

We investigate the use of markers to hasten the recovery of the recipient genome during an introgression breeding program. The effects of time and intensity of selection, population size, number and position of selected markers are studied for chromosomes either carrying or not carrying the introgressed gene. We show that marker assisted selection may lead to a gain in time of about two generations, an efficiency below previous theoretical predictions. Markers are most useful when their map position is known. In the early generations, it is shown that increasing the number of markers over three per non-carrier chromosome is not efficient, that the segment surrounding the introgressed gene is better controlled by rather distant markers unless high selection intensity can be applied, and that selection on this segment first can reduce the selection intensity available for selection on non-carrier chromosomes. These results are used to propose an optimal strategy for selection on the whole genome, making the most of available material and conditions (e.g., population size and fertility, genetic map).     

Gene Flow Technique for Stage-Structured Populations

The gene flow technique for predicting response to selection with overlapping generations is formulated in terms of demographic parameters for stage-structured population and illustrated with a sequential selection scheme in dairy cows.     

Differential Patterns of Gene Expression and Gene Complement in Laboratory-Evolved Lines of E. coli

Laboratory selection experiments play a prominent role in understandingorganismal adaptation. Although bacteria are not yet commonlyused for such experiments, they are well suited for analysesof both the organismic and the genetic basis of adaptation.Bacteria can be maintained in large populations while occupyinglimited laboratory space, have short generation times, are wellcharacterized physiologically, biochemically, and genetically,and are readily frozen and revived from the freezer. In addition,the genomes of many species are completely sequenced and knowledgeof gene function is unparalleled. Here we review general aspectsof selection experiments, the history of using selection experimentsin combination with thermal biology and genomics, and highlightfindings from six lines of Escherichia coli adapted to hightemperature (41.5°C), including changes in organismal fitness,physiological performance, gene complement and gene expression.Our results are an example of the powerful insights that canbe discovered by combining the tools and analyses of many biologicaldisciplines including genomics, evolutionary biology, genetics,and evolutionary physiology.     

Gene selection via the BAHSIC family of algorithms

MOTIVATION: Identifying significant genes among thousands of sequences on a microarray is a central challenge for cancer research in bioinformatics. The ultimate goal is to detect the genes that are involved in disease outbreak and progression. A multitude of methods have been proposed for this task of feature selection, yet the selected gene lists differ greatly between different methods. To accomplish biologically meaningful gene selection from microarray data, we have to understand the theoretical connections and the differences between these methods. In this article, we define a kernel-based framework for feature selection based on the Hilbert-Schmidt independence criterion and backward elimination, called BAHSIC. We show that several well-known feature selectors are instances of BAHSIC, thereby clarifying their relationship. Furthermore, by choosing a different kernel, BAHSIC allows us to easily define novel feature selection algorithms. As a further advantage, feature selection via BAHSIC works directly on multiclass problems. RESULTS: In a broad experimental evaluation, the members of the BAHSIC family reach high levels of accuracy and robustness when compared to other feature selection techniques. Experiments show that features selected with a linear kernel provide the best classification performance in general, but if strong non-linearities are present in the data then non-linear kernels can be more suitable. AVAILABILITY: Accompanying homepage is http://www.dbs.ifi.lmu.de/~borgward/BAHSIC. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

竹亚科lea3基因的进化分析

选取竹亚科中两个超族、六个族和三个亚族的10个竹种为材料,分别是泰竹、凤尾竹、青皮竹、大叶慈、慈竹、野龙竹、毛竹、香竹、苦竹、菲白竹,分离克隆了它们的lea3基因,并将它们与外类群物种水稻进行序列比对和进化分析。结果发现在分支模型与分支位点模型的检测中,不同竹种所含lea3基因承受了不同的正选择压力,清除选择作用在lea3基因编码区中占主导地位（ω<1）。在位点模型的检测中,共检测出了18个显著性正选择位点,占总氨基酸数目的111%。对这18个显著性正选择位点进行定位后,发现其中的15个位于11个氨基酸串联重复序列附近。这说明lea3基因中的11个氨基酸串联重复序列区比基因其它区域更容易受自然选择作用影响。同时,在位点模型检测结果的基础上,通过对强烈清除选择位点的定位,发现在11个氨基酸串联重复序列区内存在一长段无强烈清除位点的序列区。     

Simulating Evolution by Gene Duplication

By considering the recent finding that unequal crossing over and other molecular interactions are contributing to the evolution of multigene families, a model of the origin of repetitive genes was studied by Monte Carlo simulations. Starting from a single gene copy, how genetic systems evolve was examined under unequal crossing over, random drift and natural selection. Both beneficial and deteriorating mutations were incorporated, and the latter were assumed to occur ten times more frequently than the former. Positive natural selection favors those chromosomes with more beneficial mutations in redundant copies than others in the population, but accumulation of deteriorating mutations (pseudogenes) have no effect on fitness so long as there remains a functional gene. The results imply the following: Positive natural selection is needed in order to acquire gene families with new functions. Without it, too many pseudogenes accumulate before attaining a functional gene family. There is a large fluctuation in the outcome even if parameters are the same. When unequal crossing over occurs more frequently, the system evolves more rapidly. It was also shown, under realistic values of parameters, that the genetic load for acquiring a new gene is not as large as J.B.S. Haldane suggested, but not so small as in a model in which a system for selection started from already redundant genes.     

p35Nck5a基因重复性打靶载体的构建和ES细胞基因打靶研究

为了在小鼠胚胎于细胞（ＥＳ）中引起神经细胞ｃｄｃ２类激酶调节亚基ｐ３５Ｎｃｋ５ａ基因的定点 重复,采用常规的分子克隆技术,构建得到长约１２．２ｋｂ的基因重复性打靶载体ｐＧＤＴＶ。用电 穿孔法将线性化的ｐＧＤＴＶ载体转入ＥＳ细胞,经过Ｇ４１８和ＧＡＮＣ分组药物选择,获得２４５个 双药物抗性的细胞克隆,细胞存活率为６．２２ × １０－５。经ＰＣＲ和基因组Ｓｏｕｔｈｅｒｎ杂交鉴定,２个 ＥＳ细胞克隆发生了ｐ３５Ｎｃｋ５ａ基因的重复,同源重组率为５．０８×１０－７、负向选择系统的应用使 同源重组事件的富集效率提高了７倍。为建立Ａｌｚｈｅｉｍｅｒ病的转基因小鼠模型打下了基础。     

两种过滤特征基因选择算法的有效性研究

对基因表达谱进行特征基因选择不仅能改善疾病分类方法的效能,而且为寻找与疾病相关的特征基因提供新的途径．通过比较用调整p值的t检验、非参数评分两种特征基因选择算法后和未进行选择时支持向量机(SVM)分类器的分类性能、支持向量(SV)的吻合度、错分样本ID的吻合度和对样本均匀翻倍后的稳定性．结果发现：特征选择后线性、核函数为二阶多项式和径向基的SVM分类性能明显提高;特征选择前后的SV及错分样本ID的吻合度均较高;SVM的稳定性较好．由此得出结论：这两种特征选择算法具有一定的有效性．     

Gene duplications contribute to the overrepresentation of interactions between proteins of a similar age

Background

Disruptive selection has been documented in a growing number of natural populations. Yet, its prevalence within individual systems remains unclear. Furthermore, few studies have sought to identify the ecological factors that promote disruptive selection in the wild. To address these issues, we surveyed 15 populations of Mexican spadefoot toad tadpoles, Spea multiplicata, and measured the prevalence of disruptive selection acting on resource-use phenotypes. We also evaluated the relationship between the strength of disruptive selection and the intensity of intraspecific competition??an ecological agent hypothesized to be an important driver of disruptive selection.

Results

Disruptive selection was the predominant mode of quadratic selection across all populations. However, a directional component of selection favoring an extreme ecomorph??a distinctive carnivore morph??was also common. Disruptive selection was strongest in populations experiencing the most intense intraspecific competition, whereas stabilizing selection was only found in populations experiencing relatively weak intraspecific competition.

Conclusions

Disruptive selection can be common in natural populations. Intraspecific competition for resources may be a key driver of such selection.     

Gene frequency patterns in the levene subdivided population model

In the context of a multideme population structure subject to selection, migration, and mating forces, it is desired to ascertain the stable evolutionary outcomes for various classes of selection regimes. These include selection patterns as (i) a mosaic of local directed selection effects, (ii) overdominance throughout with varying intensities of the local heterozygote advantage, (iii) varying degrees of underdominance throughout, (iv) a mixed underdominant-overdominant regime. An accounting of the nature of the equilibrium configurations in the Levene population subdivision model was done with respect to the above classes of selection regimes. In particular, it is established that multiple polymorphic equilibria do not arise for selection structures (i) and (ii), while for the mixed underdominant-overdominant selection form (iv) with appropriate parameter ranges there can exist two stable internal equilibria. A surprising finding is that the number and/or character of the equilibria is not changed by increased population division beyond that of two habitats, while there is a significant difference in the equilibrium possibilities for a one- as against a two-deme population. These results appear to be a special limiting feature of the Levene population subdivision formulation.     

The Roles of Gene Duplication,Gene Conversion and Positive Selection in Rodent Esp and Mup Pheromone Gene Families with Comparison to the Abp Family

Three proteinaceous pheromone families, the androgen-binding proteins (ABPs), the exocrine-gland secreting peptides (ESPs) and the major urinary proteins (MUPs) are encoded by large gene families in the genomes of Mus musculus and Rattus norvegicus. We studied the evolutionary histories of the Mup and Esp genes and compared them with what is known about the Abp genes. Apparently gene conversion has played little if any role in the expansion of the mouse Class A and Class B Mup genes and pseudogenes, and the rat Mups. By contrast, we found evidence of extensive gene conversion in many Esp genes although not in all of them. Our studies of selection identified at least two amino acid sites in β-sheets as having evolved under positive selection in the mouse Class A and Class B MUPs and in rat MUPs. We show that selection may have acted on the ESPs by determining K_a/K_s for Exon 3 sequences with and without the converted sequence segment. While it appears that purifying selection acted on the ESP signal peptides, the secreted portions of the ESPs probably have undergone much more rapid evolution. When the inner gene converted fragment sequences were removed, eleven Esp paralogs were present in two or more pairs with K_a/K_s >1.0 and thus we propose that positive selection is detectable by this means in at least some mouse Esp paralogs. We compare and contrast the evolutionary histories of all three mouse pheromone gene families in light of their proposed functions in mouse communication.     

Gene Flow and Selection in a Two-Locus System

A model of gene flow and selection in two linked loci is analyzed. The problems considered are the effects of linkage on the clines in frequencies at the two loci and the role of gene flow in producing linkage disequilibrium between the loci. Also, the possible significance of linkage as a mechanism for permitting a population of "track" spatial changes in the environment is considered. The results are that when the recombination fraction between the loci is of the same order of magnitude as the selection coefficients or smaller, then linkage is important in determining the gene frequencies and a substantial amount of linkage disequilibrium is present in the cline. Depending on the spatial pattern of selection on the two loci, linkage can either decrease or increase a population's response to local selection.     

Detecting and Measuring Selection from Gene Frequency Data

The recent advent of high-throughput sequencing and genotyping technologies makes it possible to produce, easily and cost effectively, large amounts of detailed data on the genotype composition of populations. Detecting locus-specific effects may help identify those genes that have been, or are currently, targeted by natural selection. How best to identify these selected regions, loci, or single nucleotides remains a challenging issue. Here, we introduce a new model-based method, called SelEstim, to distinguish putative selected polymorphisms from the background of neutral (or nearly neutral) ones and to estimate the intensity of selection at the former. The underlying population genetic model is a diffusion approximation for the distribution of allele frequency in a population subdivided into a number of demes that exchange migrants. We use a Markov chain Monte Carlo algorithm for sampling from the joint posterior distribution of the model parameters, in a hierarchical Bayesian framework. We present evidence from stochastic simulations, which demonstrates the good power of SelEstim to identify loci targeted by selection and to estimate the strength of selection acting on these loci, within each deme. We also reanalyze a subset of SNP data from the Stanford HGDP–CEPH Human Genome Diversity Cell Line Panel to illustrate the performance of SelEstim on real data. In agreement with previous studies, our analyses point to a very strong signal of positive selection upstream of the LCT gene, which encodes for the enzyme lactase–phlorizin hydrolase and is associated with adult-type hypolactasia. The geographical distribution of the strength of positive selection across the Old World matches the interpolated map of lactase persistence phenotype frequencies, with the strongest selection coefficients in Europe and in the Indus Valley.     

Gene copy-number polymorphism in nature

Differences between individuals in the copy-number of whole genes have been found in every multicellular species examined thus far. Such differences result in unique complements of protein-coding genes in all individuals, and have been shown to underlie adaptive phenotypic differences. Here, we review the evidence for copy-number variants (CNVs), focusing on the methods used to detect them and the molecular mechanisms responsible for generating this type of variation. Although there are multiple technical and computational challenges inherent to these experimental methods, next-generation sequencing technologies are making such experiments accessible in any system with a sequenced genome. We further discuss the connection between copy-number variation within species and copy-number divergence between species, showing that these values are exactly what one would expect from similar comparisons of nucleotide polymorphism and divergence. We conclude by reviewing the growing body of evidence for natural selection on copy-number variants. While it appears that most genic CNVs—especially deletions—are quickly eliminated by selection, there are now multiple studies demonstrating a strong link between copy-number differences at specific genes and phenotypic differences in adaptive traits. We argue that a complete understanding of the molecular basis for adaptive natural selection necessarily includes the study of copy-number variation.     

Sex-Specific Selection and Sex-Biased Gene Expression in Humans and Flies

Sexual dimorphism results from sex-biased gene expression, which evolves when selection acts differently on males and females. While there is an intimate connection between sex-biased gene expression and sex-specific selection, few empirical studies have studied this relationship directly. Here we compare the two on a genome-wide scale in humans and flies. We find a distinctive “Twin Peaks” pattern in humans that relates the strength of sex-specific selection, quantified by genetic divergence between male and female adults at autosomal loci, to the degree of sex-biased expression. Genes with intermediate degrees of sex-biased expression show evidence of ongoing sex-specific selection, while genes with either little or completely sex-biased expression do not. This pattern apparently results from differential viability selection in males and females acting in the current generation. The Twin Peaks pattern is also found in Drosophila using a different measure of sex-specific selection acting on fertility. We develop a simple model that successfully recapitulates the Twin Peaks. Our results suggest that many genes with intermediate sex-biased expression experience ongoing sex-specific selection in humans and flies.     

猪α-1,3-半乳糖转移酶基因打靶载体的构建

目的:构建猪α-1,3-半乳糖转移酶(GGTA1)基因的正负筛选打靶载体。方法:以原代猪胚胎成纤维细胞基因组DNA为模板,采用长程PCR方法扩增出GGTA1基因的2条片段;以长约2kb包含部分第9外显子的片段为同源短臂,在XbaⅠ和ClaⅠ位点插入pLoxP质粒正筛选标记neo基因的3'端;以长约5.4kb包括部分第8外显子、全部第8内含子及部分第9外显子的片段为同源长臂,于NotⅠ位点插入该质粒中neo基因的5'端;2.7kb的负筛选标记tk基因位于载体中同源短臂的3'端外侧。结果与结论:酶切、PCR及测序结果表明,同源臂被正确连接至质粒pLoxP,成功构建了猪GGTA1基因正负筛选打靶载体pSL/GT。     

Gene selection with multiple ordering criteria

Background  

A microarray study may select different differentially expressed gene sets because of different selection criteria. For example, the fold-change and p-value are two commonly known criteria to select differentially expressed genes under two experimental conditions. These two selection criteria often result in incompatible selected gene sets. Also, in a two-factor, say, treatment by time experiment, the investigator may be interested in one gene list that responds to both treatment and time effects.