A comparison of directed evolution approaches using the beta-glucuronidase model system

Protein engineers can alter the properties of enzymes by directing their evolution in vitro. Many methods to generate molecular diversity and to identify improved clones have been developed, but experimental evolution remains as much an art as a science. We previously used DNA shuffling (sexual recombination) and a histochemical screen to direct the evolution of Escherichia coli beta-glucuronidase (GUS) variants with improved beta-galactosidase (BGAL) activity. Here, we employ the same model evolutionary system to test the efficiencies of several other techniques: recursive random mutagenesis (asexual), combinatorial cassette mutagenesis (high-frequency recombination) and a versatile high-throughput microplate screen. GUS variants with altered specificity evolved in each trial, but different combinations of mutagenesis and screening techniques effected the fixation of different beneficial mutations. The new microplate screen identified a broader set of mutations than the previously employed X-gal colony screen. Recursive random mutagenesis produced essentially asexual populations, within which beneficial mutations drove each other into extinction (clonal interference); DNA shuffling and combinatorial cassette mutagenesis led instead to the accumulation of beneficial mutations within a single allele. These results explain why recombinational approaches generally increase the efficiency of laboratory evolution.     

Generalized genomic distance-based regression methodology for multilocus association analysis

Large-scale, multilocus genetic association studies require powerful and appropriate statistical-analysis tools that are designed to relate genotype and haplotype information to phenotypes of interest. Many analysis approaches consider relating allelic, haplotypic, or genotypic information to a trait through use of extensions of traditional analysis techniques, such as contingency-table analysis, regression methods, and analysis-of-variance techniques. In this work, we consider a complementary approach that involves the characterization and measurement of the similarity and dissimilarity of the allelic composition of a set of individuals' diploid genomes at multiple loci in the regions of interest. We describe a regression method that can be used to relate variation in the measure of genomic dissimilarity (or "distance") among a set of individuals to variation in their trait values. Weighting factors associated with functional or evolutionary conservation information of the loci can be used in the assessment of similarity. The proposed method is very flexible and is easily extended to complex multilocus-analysis settings involving covariates. In addition, the proposed method actually encompasses both single-locus and haplotype-phylogeny analysis methods, which are two of the most widely used approaches in genetic association analysis. We showcase the method with data described in the literature. Ultimately, our method is appropriate for high-dimensional genomic data and anticipates an era when cost-effective exhaustive DNA sequence data can be obtained for a large number of individuals, over and above genotype information focused on a few well-chosen loci.     

Molecular and genetic characterization of the allelic variants of Du215, Du281, Du323, and Du47G microsatellite loci in parthenogenetic lizard <Emphasis Type="Italic">Darevskia armeniaca</Emphasis> (Lacertidae)

A key issue in the study of unisexual (parthenogenetic) vertebrate species is the determination of their genetic and clonal diversity. In pursuing this aim, various markers of nuclear and mitochondrial genomes can be used. The most effective genetic markers include microsatellite DNA, characterized by high variability. The development and characterization of such markers is a necessary step in the genetic studies of parthenogenetic species. In the present study, using locus-specific PCR, for the first time, an analysis of allelic polymorphism of four microsatellite loci is performed in the populations of parthenogenetic species Darevskia armeniaca. In the studied populations, allelic variants of each locus are identified, and the nucleotide sequences of each allele are determined. It is demonstrated that allele differences are associated with the variation in the structure of microsatellite clusters and single nucleotide substitutions at fixed distances in flanking DNA regions. Structural allele variations form haplotype markers that are specific to each allele and are inherited from their parental bisexual species. It is established which of the parental alleles of each locus were inherited by the parthenogenetic species. The characteristics of the distribution and frequency of the alleles of microsatellite loci in the populations of D. armeniaca determining specific features of each population are obtained. The observed heterozygosity of the populations at the studied loci and the mutation rates in genome regions, as well as Nei’s genetic distances between the studied populations, are determined, and the phylogenetic relationships between them are established.     

Distinctions among Allelic Variants Associated with Chromosome 3 Inversions in DROSOPHILA PSEUDOOBSCURA and DROSOPHILA PERSIMILIS

Efforts were made to discriminate new genetic variants among electrophoretic alleles that are associated with chromosome 3 inversions of Drosophila pseudoobscura and D. persimilis. Apparent genetic similarities for electrophoretic alleles between these two species and among the common inversions they carry were reexamined by altering gel concentration and buffer pH. At the amylase locus, the 1.09 electrophoretic allele could be further separated into two allelic classes that differentiated the WT and KL arrangements. Similarly, the 0.84 electrophoretic allele was divided into two allelic classes, one characteristic of the Santa Cruz phylad arrangements, TL and SC, and the other found in strains of the Standard phylad arrangements and CH. Uncommon amylase alleles proved to be different alleles in the two species. No new allelic variants, however, could be found among strains with the amylase 1.00 allele, the commonest allele in the Standard phylad of both species. No major new allelic variation was detected for acid phosphatase-3 and larval protein-10 that revealed any further differentiation among species or inversions. Variation at all three loci in strains of the Bogota population remained genetically similar to variation in strains of mainland D. pseudoobscura.     

Molecules and migration: biogeographical studies in cruciferous plants

In the past two decades our understanding of plant biogeography has been improved substantially by the introduction of various molecular marker systems. Especially within the angiosperms, maternally inherited chloroplast DNA based data sets have elucidated not only genetic relatedness but also geographic structuring of genetic variation. These findings were based on the observation that DNA molecules might mutate during migration, which consequently found its manifestation in the term phylogeography introduced in the late 80s by John Avise. However, other markers such as codominantly inherited allozymes were used before the advent of DNA techniques and were used in theoretical population genetic studies. In actual phylogeographic studies, highly variable markers, such as AFLPs (amplified fragment length polymorphisms), were needed to unravel recent species histories (e.g. pleistocenic differentiation). The levels of molecular variation at such markers are closer to that of allelic variation measured with allozymes. Hence, an increasing number of studies have relied on highly polypmorphic markers, such as DNA microsatellite loci. Herein, we try to present an overview on the various biogeographic and phylogeographic studies using various molecular (including isozyme) markers and methodological approaches to analyse them, concentrating on studies done with representatives of the Brassicaceae family.     

Techniques de recherche des polymorphismes génétiques

Sequencing the human genome has allowed the discovery of millions of DNA sequence variants. Sequence variations in human DNA are mainly present asSingle Nucleotide Polymorphisms (SNPs); this common form of variation is found about once every 1,000 bases in the human genome and 1.8 million SNPs have now been identified and located. The accessibility of databases of SNPs opens the possibility of studying the influence of these polymorphisms on disease risks as well as on drug responses. Numerous approaches have been set up for the identification of SNPs. In this review we describe the main techniques used for the identification of these polymorphisms. They rely on two major consequences of sequence variations: the apparition or the disappearance of restriction enzyme sites or the alteration of DNA strand hybridization due to the presence of a mismatch. Southern blotting and restriction endonucleases have allowed the development of the technique ofrestriction fragment length polymorphisms (RFLPs), now performed on PCR products. Several other approaches such as denaturing high-performance liquid chromatography or real-time PCR can detect allele differences upon re-hybridization and heteroduplex formation. However, DNA sequencing remains the obligate step for the positive identification of known or unknown SNPs. At last, the development of high-throughput methods allows a large increase in the rate of discovery of SNPs likely.     

Inter and intra-ethnic differences in the distribution of the molecular variants of TPMT, UGT1A1 and MDR1 genes in the South Indian population

Molecular variants of polymorphic drug metabolizing enzymes and drug transporters are attributed to differences in individual's therapeutic response and drug toxicity in different populations. We sought to determine the genotype and allele frequencies of polymorphisms for major phase II drug-metabolizing enzymes (TPMT, UGT1A1) and drug transporter (MDR1) in South Indians. Allelic variants of TPMT (*2,*3A,*3B,*3C & *8), UGT1A1 (TA)6>7 and MDR1 (2677G>T/A & 3435C>T) were evaluated in 450-608 healthy South Indian subjects. Genomic DNA was extracted by phenol-chloroform method and genotype was determined by PCR-RFLP, qRT-PCR, allele specific PCR, direct sequencing and SNaPshot techniques. The frequency distributions of TPMT, UGT1A1 and MDR1 gene polymorphisms were compared between the individual 4 South Indian populations viz., Tamilian, Kannadiga, Andhrite and Keralite. The combined frequency distribution of the South Indian populations together, was also compared with that of other major populations. The allele frequencies of TPMT*3C, UGT1A1 (TA)7, MDR1 2677T, 2677A and 3435T were 1.2, 39.8, 60.3, 3.7, and 61.6% respectively. The other variant alleles such as TPMT*2, *3A, *3B and *8 were not identified in the South Indian population. Sub-population analysis showed that the distribution of UGT1A1 (TA)6>7 and MDR1 allelic variants differed between the four ethnic groups. However, the frequencies of TPMT*3C allele were similar in the four South Indian populations. The distribution of TPMT, UGT1A1 and MDR1 gene polymorphisms of the South Indian population was significantly different from other populations.     

Multiple regression methods show great potential for rare variant association tests

The investigation of associations between rare genetic variants and diseases or phenotypes has two goals. Firstly, the identification of which genes or genomic regions are associated, and secondly, discrimination of associated variants from background noise within each region. Over the last few years, many new methods have been developed which associate genomic regions with phenotypes. However, classical methods for high-dimensional data have received little attention. Here we investigate whether several classical statistical methods for high-dimensional data: ridge regression (RR), principal components regression (PCR), partial least squares regression (PLS), a sparse version of PLS (SPLS), and the LASSO are able to detect associations with rare genetic variants. These approaches have been extensively used in statistics to identify the true associations in data sets containing many predictor variables. Using genetic variants identified in three genes that were Sanger sequenced in 1998 individuals, we simulated continuous phenotypes under several different models, and we show that these feature selection and feature extraction methods can substantially outperform several popular methods for rare variant analysis. Furthermore, these approaches can identify which variants are contributing most to the model fit, and therefore both goals of rare variant analysis can be achieved simultaneously with the use of regression regularization methods. These methods are briefly illustrated with an analysis of adiponectin levels and variants in the ADIPOQ gene.     

Analysis of microsatellite loci of the chloroplast genome in the genus Capsicum (Pepper)

Six plastome microsatellites were examined in 43 accessions of the genus Capsicum. In total, 33 allelic variants were detected. A specific haplotype of chloroplast DNA was identified for each Capsicum species. Species-specific allelic variants were found for most wild Capsicum species. The highest intraspecific variation was observed for the C. baccatum plastome. Low cpDNA polymorphism was characteristic of C. annuum: the cpSSRs were either monomorphic or dimorphic. The vast majority of C. annuum accessions each had alleles of one type. Another allele type was rare and occurred only in wild accessions. The results testified again to genetic conservation of C. annuum and especially its cultivated forms. The phylogenetic relationships established for the Capsicum species on the basis of plastome analysis were similar to those inferred from the morphological traits, isozyme patterns, and molecular analysis of the nuclear genome.     

A practical guide to environmental association analysis in landscape genomics

Landscape genomics is an emerging research field that aims to identify the environmental factors that shape adaptive genetic variation and the gene variants that drive local adaptation. Its development has been facilitated by next‐generation sequencing, which allows for screening thousands to millions of single nucleotide polymorphisms in many individuals and populations at reasonable costs. In parallel, data sets describing environmental factors have greatly improved and increasingly become publicly accessible. Accordingly, numerous analytical methods for environmental association studies have been developed. Environmental association analysis identifies genetic variants associated with particular environmental factors and has the potential to uncover adaptive patterns that are not discovered by traditional tests for the detection of outlier loci based on population genetic differentiation. We review methods for conducting environmental association analysis including categorical tests, logistic regressions, matrix correlations, general linear models and mixed effects models. We discuss the advantages and disadvantages of different approaches, provide a list of dedicated software packages and their specific properties, and stress the importance of incorporating neutral genetic structure in the analysis. We also touch on additional important aspects such as sampling design, environmental data preparation, pooled and reduced‐representation sequencing, candidate‐gene approaches, linearity of allele–environment associations and the combination of environmental association analyses with traditional outlier detection tests. We conclude by summarizing expected future directions in the field, such as the extension of statistical approaches, environmental association analysis for ecological gene annotation, and the need for replication and post hoc validation studies.     

Genotyping of human class I alcohol dehydrogenase. Analysis of enzymatically amplified DNA with allele-specific oligonucleotides

Large inter-individual differences are noted in the susceptibility to alcohol-related problems. Part of this variation may be due to the different isoenzyme patterns of the alcohol-metabolizing enzymes and, consequently, different pharmacokinetics of alcohol degradation. We have used the polymerase chain reaction and oligonucleotide hybridization to amplify and analyze class I alcohol dehydrogenase isoenzyme-specific genomic DNA. The method unambiguously distinguishes between different allelic variants and thus provides a new means of elucidating the alcohol dehydrogenase isoenzyme pattern of humans.     

5-Methylcytosine as a marker for the monitoring of DNA methylation

The extent of the DNA methylation of genomic DNA as well as the methylation pattern of many gene-regulatory areas are important aspects with regard to the state of genetic information, especially their expression. There is growing evidence that aberrant methylation is associated with many serious pathological consequences. As genetic research advances, many different approaches have been employed to determine the overall level of DNA methylation in a genome or to reveal the methylation state of particular nucleotide residues, starting from semiquantitative methods up to new and powerful techniques. In this paper, the currently employed techniques are reviewed both from the point of view of their relevance in genomic research and of their analytical application. The methods discussed include approaches based on chromatographic separation (thin-layer chromatography, high-performance liquid chromatography, affinity chromatography), separation in an electric field (capillary electrophoresis, gel electrophoresis in combination with methylation-sensitive restriction enzymes and/or specific sequencing protocols), and some other methodological procedures (mass spectrometry, methyl accepting capacity assay and immunoassays).     

Geographic patterns: how to identify them and why

Geographic patterns of genetic diversity allow us to make inferences about population histories and the evolution of inherited disease. The statistical methods describing genetic variation in space, such as estimation of genetic variances, mapping of allele frequencies, and principal components analysis, have opened up the possibility to reconstruct demographic processes whose effects have been tested by a variety of approaches, including spatial autocorrelation, cladistic analyses, and simulations. These studies have significantly contributed to our understanding of human genetic variation; however, the molecular data that have accumulated since the mid-1980s have also created new complications. Reasons include the generally limited sample sizes, but, more generally, it is the nature of molecular variation itself that makes it necessary to develop and apply specific models and methods for the treatment of DNA data. The foreseeable diffusion of laboratory techniques for the rapid typing of many DNA markers will force us to change our approach to the study of human variation anyway, moving from the gene level toward the genome level. Because extensive variation among loci is the rule rather than the exception, an important practical tip is to be skeptical of inferences based on single-locus diversity.     

太平洋牡蛎养殖与野生群体遗传变异的微卫星研究

应用微卫星标记技术研究5个中国太平洋牡蛎养殖群体和2个日本太平洋牡蛎野生群体的遗传变异。研究中所使用的7个微卫星位点在养殖和野生群体中都显示出了高多态性,平均等位基因数为19.1～29.9,平均期待杂合度为0.916～0.958。养殖群体和野生群体的平均等位基因丰度及观察杂合度没有显著性差异。遗传分化系数及等位基因杂合度分析显示所有的群体间都有显著性差异。构建的NJ树中,7个群体聚为3支,养殖群体和野生群体可以清楚地分开,在养殖群体中又分为南北两支。分配检验中,97%～100%的正确率证明了微卫星标记在群体识别分析中的可行性。本研究结果对太平洋牡蛎管理模式的设计和选择育种具有重要意义。     

Distribution of single‐nucleotide variants on protein–protein interaction sites and its relationship with minor allele frequency

Recent advances in DNA sequencing techniques have identified rare single‐nucleotide variants with less than 1% minor allele frequency. Despite the growing interest and physiological importance of rare variants in genome sciences, less attention has been paid to the allele frequency of variants in protein sciences. To elucidate the characteristics of genetic variants on protein interaction sites, from the viewpoints of the allele frequency and the structural position of variants, we mapped about 20,000 human SNVs onto protein complexes. We found that variants are less abundant in protein interfaces, and specifically the core regions of interfaces. The tendency to “avoid” the interfacial core is stronger among common variants than rare variants. As amino acid substitutions, the trend of mutating amino acids among rare variants is consistent in different interfacial regions, reflecting the fact that rare variants result from random mutations in DNA sequences, whereas amino acid changes of common variants vary between the interfacial core and rim regions, possibly due to functional constraints on proteins. This study illustrated how the allele frequency of variants relates to the protein structural regions and the functional sites in general and will lead to deeper understanding of the potential deleteriousness of rare variants at the structural level. Exceptional cases of the observed trends will shed light on the limitations of structural approaches to evaluate the functional impacts of variants.     

Genetic relationships of populations and the origins of new infestations of the Mediterranean fruit fly

A polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) approach based on the variation in intron sequences of the glucose-6-phosphate dehydrogenase (Zw) gene was used to assess genetic variability in 26 populations and infestations of the Mediterranean fruit fly (medfly), Ceratitis capitata. Beginning with the exon-primed intron-crossing PCR (EPIC-PCR) method to amplify introns of this gene, five alleles were identified on the basis of DNA sequence variants. Several of these variants affect recognition sites for the restriction enzymes RsaI and TaqI. Using these enzymes in successive digestions of the EPIC-PCR products, each of these alleles can be identified directly from individuals. From this, surveys were conducted to document genotypes and allele frequencies in these samples. The relationships of existing populations and the invasion process represented by new infestations of the medfly were analysed using a principal coordinate analysis and the amova method to quantify the distribution of genetic diversity at different levels in a hierarchical manner. From these results, a framework of genetic relationships among the populations and infestations is presented. In addition, for at least some of the infestations, populations that are probably acting as sources of origin have been identified.