A method for combining molecular markers and phenotypic attributes for classifying plant genotypes

Classifying genotypes into clusters based on DNA fingerprinting, and/or agronomic attributes, for studying genetic and phenotypic diversity is a common practice. Researchers are interested in knowing the minimum number of fragments (and markers) needed for finding the underlying structural patterns of diversity in a population of interest, and using this information in conjunction with the phenotypic attributes to obtain more precise clusters of genotypes. The objectives of this study are to present: (1) a retrospective method of analysis for selecting a minimum number of fragments (and markers) from a study needed to produce the same classification of genotypes as that obtained using all the fragments (and markers), and (2) a classification strategy for genotypes that allows the combination of the minimum set of fragments with available phenotypic attributes. Results obtained on seven experimental data sets made up of different plant species, number of individuals per species’ and number of markers, showed that the retrospective analysis did indeed find few relevant fragments (and markers) that best discriminated the genotypes. In two data sets, the classification strategy of combining the information on the relevant minimum fragments with the available morpho-agronomic attributes produced compact and well-differentiated groups of genotypes.     

Patchy distributions belie morphological and genetic homogeneity in rosy-finches

DNA sequence data often appear to contradict low-level avian taxonomy, which is usually based on patterns of external phenotypic similarity. We examined such an apparent contradiction in the Nearctic rosy-finches. On the basis of several phenotypic characters the finches were divided into three species congeneric with three Asian species. When Nearctic taxa were analyzed in a principal components analysis, 66.9% of phenotypic variation was explained by differences between the Bering Sea and continental populations, sexual dimorphism and a latitudinal cline. Our phylogenetic analysis of mitochondrial ND2 sequences revealed four clades among six species of rosy-finches. Three clades corresponded to three Asian species. The fourth clade included all three Nearctic species. Their haplotypes were not reciprocally monophyletic and the combined genetic variability of all Nearctic taxa was lower than in two of their Asian congeners. A Z-specific intron (ACO1I9) and an autosomal coding locus (MC1R) provided little additional phylogenetic information, most likely because of the longer coalescence times relative to ND2. Phylogeographic analyses of ND2 data revealed significant gene flow among neighboring localities regardless of their taxonomic assignment. Our analyses showed that DNA and phenotypic data are not in conflict, but rather complement each other, and together help clarify species limits. Our data are consistent with a single species in North America, not three.     

Phylogeny of the neotropical moth tribe Josiini (Notodontidae: Dioptinae): comparing and combining evidence from DNA sequences and morphology

DNA sequences were gathered from mitochondrial COII and nuclear ribosomal 18S and 28S genes for 21 moth species in the tribe Josiini (Notodontidae: Dioptinae) and two outgroup genera. These data complement a previously published morphological character set for the same taxa. We examine whether relationships in the Josiini are best reflected by a single phylogenetic analysis of all the data, or by a consensus of separate trees generated from DNA and morphology. Even in cases where analyses of partitioned data produce incongruent cladograms, the underlying disagreement between partitions is relatively small. While both molecular and morphological data provide useful character information by themselves, we conclude that the best supported phylogenetic hypothesis is the one derived from combined analysis.     

Historic data analysis reveals ambient temperature as a source of phenotypic variation in populations of the land snail Theba pisana

Pulmonate land snails are often polymorphic in their shell coloration pattern. To quantify the contribution of environmental parameters to the nondirectional change in phenotypic variation, we used a historic dataset on Theba pisana morph frequencies and climate data for statistical modelling. We found significant correlations of the degree of phenotypic diversity between juveniles and corresponding adult individuals within the same and the subsequent generation. Among climate parameters, the phenotypic diversity of adults correlated significantly and positively with the mean and maximum ambient temperatures in the winter and spring only. There was no correlation between high or low temperatures and the frequency of distinct morphs. Akaike's information criterion‐based model selection revealed the particular importance of only parental phenotypic diversity for next generation juvenile phenotypic diversity. By contrast, phenotypic diversity of the juveniles of the preceding year and the mean temperatures in winter and spring were important for the phenotypic diversity of adult snails. Approximately two‐thirds of the explicable variation in phenotypic diversity of adults was explained by inheritance and approximately one‐third was expained by ambient temperature. The present study shows that genetics and temperature interact to generate nondirectional changes in phenotypic variation within populations, which also can be reflected by changes in the phenotype of individuals. © 2013 The Linnean Society of London, Biological Journal of the Linnean Society, 2013, 109 , 241–256.     

Rapid and reliable fluorescent cycle sequencing of double-stranded templates.

Automated DNA sequencing is an extremely valuable technique which requires very high quality DNA templates to be carried out successfully. While it has been possible to readily produce large numbers of such templates from M13 or other single-stranded vectors for several years, the sequencing of double-stranded DNA templates using the ABI 373 DNA Sequencer has had a considerably lower success rate. We describe how the combination of a new fluorescent, dideoxy sequencing method, called cycle-sequencing, coupled with modifications to template isolation procedures based on Qiagen columns, makes fluorescent sequencing of double-stranded templates a reliable procedure. From a single five milliliter culture enough DNA can be isolated (up to 20 micrograms) to do 4-8 sequencing reactions, each of which yields 400-500 bases of high quality sequence data. These procedures make the routine use of double-stranded DNA templates a viable strategy in automated DNA sequencing projects.     

A new approach to an old conundrum--DNA barcoding sheds new light on phenotypic plasticity and morphological stasis in microsnails (Gastropoda, Pulmonata, Carychiidae)

The identification of microsnail taxa based on morphological characters is often a time-consuming and inconclusive process. Aspects such as morphological stasis and phenotypic plasticity further complicate their taxonomic designation. In this study, we demonstrate that the application of DNA barcoding can alleviate these problems within the Carychiidae (Gastropoda, Pulmonata). These microsnails are a taxon of the pulmonate lineage and most likely migrated onto land independently of the Stylommatophora clade. Their taxonomical classification is currently based on conchological and anatomical characters only. Despite much confusion about historic species assignments, the Carychiidae can be unambiguously subdivided into two taxa: (i) Zospeum species, which are restricted to karst caves, and (ii) Carychium species, which occur in a broad range of environmental conditions. The implementation of discrete molecular data (COI marker) enabled us to correctly designate 90% of the carychiid microsnails. The remaining cases were probably cryptic Zospeum and Carychium taxa and incipient species, which require further investigation into their species status. Because conventional reliance upon mostly continuous (i.e. nondiscrete) conchological characters is subject to fallibility for many gastropod species assignments, we highly recommend the use of DNA barcoding as a taxonomic, cutting-edge method for delimiting microsnail taxa.     

High‐resolution melting analysis: a genotyping tool for population studies on Daphnia

Determining genetic variation at the DNA level within and between natural populations is important for understanding the role of natural selection on phenotypic traits, but many techniques of screening for genetic variation are either cost intensive, not sensitive enough or too labour‐ and time‐consuming. Here, we demonstrate high‐resolution melting analysis (HRMA) as a cost‐effective and powerful tool for screening variable target genes in natural populations. HRMA is based on monitoring the melting of PCR amplicons. Owing to saturating concentrations of a dye that binds at high concentrations to double‐stranded DNA, it is possible to genotype high numbers of samples rapidly and accurately. We analysed digestive trypsins of two Daphnia magna populations as an application example for HRMA. One population originated from a pond containing toxic cyanobacteria that possibly produce protease inhibitors and the other from a pond without such cyanobacteria. The hypothesis was that D. magna clones from ponds with cyanobacteria have undergone selection by these inhibitors, which has led to different trypsin alleles. We first sequenced pooled genomic PCR products of trypsins from both populations to identify variable DNA sequences of active trypsins. Second, we screened variable DNA sequences of each D. magna clone from both populations for single nucleotide polymorphisms via HRMA. The HRMA results revealed that both populations exhibited phenotypic differences in the analysed trypsins. Our results indicate that HRMA is a powerful genotyping tool for studying the variation of target genes in response to selection within and between natural Daphnia populations.     

A Bayesian approach to inferring population structure from dominant markers

Molecular markers derived from polymerase chain reaction (PCR) amplification of genomic DNA are an important part of the toolkit of evolutionary geneticists. Random amplified polymorphic DNA markers (RAPDs), amplified fragment length polymorphisms (AFLPs) and intersimple sequence repeat (ISSR) polymorphisms allow analysis of species for which previous DNA sequence information is lacking, but dominance makes it impossible to apply standard techniques to calculate F-statistics. We describe a Bayesian method that allows direct estimates of FST from dominant markers. In contrast to existing alternatives, we do not assume previous knowledge of the degree of within-population inbreeding. In particular, we do not assume that genotypes within populations are in Hardy-Weinberg proportions. Our estimate of FST incorporates uncertainty about the magnitude of within-population inbreeding. Simulations show that samples from even a relatively small number of loci and populations produce reliable estimates of FST. Moreover, some information about the degree of within-population inbreeding (FIS) is available from data sets with a large number of loci and populations. We illustrate the method with a reanalysis of RAPD data from 14 populations of a North American orchid, Platanthera leucophaea.     

Robust hit identification by quality assurance and multivariate data analysis of a high-content, cell-based assay

Recent technological advances in high-content screening instrumentation have increased its ease of use and throughput, expanding the application of high-content screening to the early stages of drug discovery. However, high-content screens produce complex data sets, presenting a challenge for both extraction and interpretation of meaningful information. This shifts the high-content screening process bottleneck from the experimental to the analytical stage. In this article, the authors discuss different approaches of data analysis, using a phenotypic neurite outgrowth screen as an example. Distance measurements and hierarchical clustering methods lead to a profound understanding of different high-content screening readouts. In addition, the authors introduce a hit selection procedure based on machine learning methods and demonstrate that this method increases the hit verification rate significantly (up to a factor of 5), compared to conventional hit selection based on single readouts only.     

Loop‐mediated isothermal amplification of single pollen grains

The polymerase chain reaction (PCR) has been a reliable and fruitful method for many applications in ecology. Nevertheless, unavoidable technical and instrumental requirements of PCR have limited its widespread application in field situations. The recent development of isothermal DNA amplification methods provides an alternative to PCR, which circumvents key limitations of PCR for direct amplification in the field. Being able to analyze DNA in the pollen cloud of an ecosystem would provide very useful ecological information, yet would require a field‐enabled, high‐throughput method for this potential to be realized. Here, we demonstrate the applicability of the loop‐mediated DNA amplification method (LAMP), an isothermal DNA amplification technique, to be used in pollen analysis. We demonstrate that LAMP can provide a reliable method to identify species from the pollen cloud, and that it can amplify successfully with sensitivity down to single pollen grains, thus opening the possibility of field‐based, high‐throughput analysis.     

Genome-wide copy number analysis of single cells

Copy number variation (CNV) is increasingly recognized as an important contributor to phenotypic variation in health and disease. Most methods for determining CNV rely on admixtures of cells in which information regarding genetic heterogeneity is lost. Here we present a protocol that allows for the genome-wide copy number analysis of single nuclei isolated from mixed populations of cells. Single-nucleus sequencing (SNS), combines flow sorting of single nuclei on the basis of DNA content and whole-genome amplification (WGA); this is followed by next-generation sequencing to quantize genomic intervals in a genome-wide manner. Multiplexing of single cells is discussed. In addition, we outline informatic approaches that correct for biases inherent in the WGA procedure and allow for accurate determination of copy number profiles. All together, the protocol takes ～3 d from flow cytometry to sequence-ready DNA libraries.     

Museum specimens provide reliable SNP data for population genomic analysis of a widely distributed but threatened cockatoo species

Natural history museums harbour a plethora of biological specimens which are of potential use in population and conservation genetic studies. Although technical advancements in museum genomics have enabled genome‐wide markers to be generated from aged museum specimens, the suitability of these data for robust biological inference is not well characterized. The aim of this study was to test the utility of museum specimens in population and conservation genomics by assessing the biological and technical validity of single nucleotide polymorphism (SNP) data derived from such samples. To achieve this, we generated thousands of SNPs from 47 red‐tailed black cockatoo (Calyptorhychus banksii) traditional museum samples (i.e. samples that were not collected with the primary intent of DNA analysis) and 113 fresh tissue samples (cryopreserved liver/muscle) using a restriction site‐associated DNA marker approach (DArTseq^?). Thousands of SNPs were successfully generated from most of the traditional museum samples (with a mean age of 44 years, ranging from 5 to 123 years), although 38% did not provide useful data. These SNPs exhibited higher error rates and contained significantly more missing data compared with SNPs from fresh tissue samples, likely due to considerable DNA fragmentation. However, based on simulation results, the level of genotyping error had a negligible effect on inference of population structure in this species. We did identify a bias towards low diversity SNPs in older samples that appears to compromise temporal inferences of genetic diversity. This study demonstrates the utility of a RADseq‐based method to produce reliable genome‐wide SNP data from traditional museum specimens.     

Patterns of nuclear DNA degeneration over time--a case study in historic teeth samples

The amount of nuclear DNA extracted from teeth of 279 individual red fox Vulpes vulpes collected over a period spanning the last three decades was determined by quantitative polymerase chain reaction (PCR). Although teeth were autoclaved during initial collection, 73.8% of extracts contained sufficient DNA concentration (> 5 pg/ micro L) suitable for reliable microsatellite genotyping but the quantity of nuclear DNA decayed significantly over time in a nonlinear pattern. The success of PCR amplification across four examined canine microsatellites over time was dependent on fragment size. By including data from two different tests for human contamination and from frequencies of allelic dropout and false alleles, the methodological constraints of population genetic studies using microsatellite loci amplified from historic DNA are discussed.     

qDNAmod: a statistical model-based tool to reveal intercellular heterogeneity of DNA modification from SMRT sequencing data

In an isogenic cell population, phenotypic heterogeneity among individual cells is common and critical for survival of the population under different environment conditions. DNA modification is an important epigenetic factor that can regulate phenotypic heterogeneity. The single molecule real-time (SMRT) sequencing technology provides a unique platform for detecting a wide range of DNA modifications, including N6-methyladenine (6-mA), N4-methylcytosine (4-mC) and 5-methylcytosine (5-mC). Here we present qDNAmod, a novel bioinformatic tool for genome-wide quantitative profiling of intercellular heterogeneity of DNA modification from SMRT sequencing data. It is capable of estimating proportion of isogenic haploid cells, in which the same loci of the genome are differentially modified. We tested the reliability of qDNAmod with the SMRT sequencing data of Streptococcus pneumoniae strain ST556. qDNAmod detected extensive intercellular heterogeneity of DNA methylation (6-mA) in a clonal population of ST556. Subsequent biochemical analyses revealed that the recognition sequences of two type I restriction–modification (R-M) systems are responsible for the intercellular heterogeneity of DNA methylation initially identified by qDNAmod. qDNAmod thus represents a valuable tool for studying intercellular phenotypic heterogeneity from genome-wide DNA modification.     

Use of intersimple sequence repeats markers to develop strain-specific SCAR markers for Lentinula edodes

Although Lentinula edodes is the second most important cultivated mushroom worldwide, most industrially cultivated strains have been identified only through traditional phenotypic analysis. Here, we report for the first time the use of sequence characterized amplified region (SCAR) markers for strain differentiation. SCAR markers were created by first generating and sequencing single intersimple sequence repeats fragments, and then designing primers based on these sequences to amplify strain-specific fragments of a certain size. One SCAR primer pair, ISL450F/R7 (amplifying a band of c. 450 bp), was designed to identify one strain of L. edodes (strain No. 7). The SCAR primer pair was then used to correctly amplify the single unique fragment from DNA samples taken from a total of 85 strains representing three separate species. Our data provide the foundation for a precise and rapid PCR-based strain-diagnostic system for L. edodes.     

Assessment of reliability of microarray data and estimation of signal thresholds using mixture modeling

DNA microarray is an important tool for the study of gene activities but the resultant data consisting of thousands of points are error-prone. A serious limitation in microarray analysis is the unreliability of the data generated from low signal intensities. Such data may produce erroneous gene expression ratios and cause unnecessary validation or post-analysis follow-up tasks. In this study, we describe an approach based on normal mixture modeling for determining optimal signal intensity thresholds to identify reliable measurements of the microarray elements and subsequently eliminate false expression ratios. We used univariate and bivariate mixture modeling to segregate the microarray data into two classes, low signal intensity and reliable signal intensity populations, and applied Bayesian decision theory to find the optimal signal thresholds. The bivariate analysis approach was found to be more accurate than the univariate approach; both approaches were superior to a conventional method when validated against a reference set of biological data that consisted of true and false gene expression data. Elimination of unreliable signal intensities in microarray data should contribute to the quality of microarray data including reproducibility and reliability of gene expression ratios.     

Single nucleotide polymorphism barcoding of cytochrome c oxidase I sequences for discriminating 17 species of Columbidae by decision tree algorithm

DNA barcodes are widely used in taxonomy, systematics, species identification, food safety, and forensic science. Most of the conventional DNA barcode sequences contain the whole information of a given barcoding gene. Most of the sequence information does not vary and is uninformative for a given group of taxa within a monophylum. We suggest here a method that reduces the amount of noninformative nucleotides in a given barcoding sequence of a major taxon, like the prokaryotes, or eukaryotic animals, plants, or fungi. The actual differences in genetic sequences, called single nucleotide polymorphism (SNP) genotyping, provide a tool for developing a rapid, reliable, and high‐throughput assay for the discrimination between known species. Here, we investigated SNPs as robust markers of genetic variation for identifying different pigeon species based on available cytochrome c oxidase I (COI) data. We propose here a decision tree‐based SNP barcoding (DTSB) algorithm where SNP patterns are selected from the DNA barcoding sequence of several evolutionarily related species in order to identify a single species with pigeons as an example. This approach can make use of any established barcoding system. We here firstly used as an example the mitochondrial gene COI information of 17 pigeon species (Columbidae, Aves) using DTSB after sequence trimming and alignment. SNPs were chosen which followed the rule of decision tree and species‐specific SNP barcodes. The shortest barcode of about 11 bp was then generated for discriminating 17 pigeon species using the DTSB method. This method provides a sequence alignment and tree decision approach to parsimoniously assign a unique and shortest SNP barcode for any known species of a chosen monophyletic taxon where a barcoding sequence is available.