Validation of SNP Allele Frequencies Determined by Pooled Next-Generation Sequencing in Natural Populations of a Non-Model Plant Species

Sequencing of pooled samples (Pool-Seq) using next-generation sequencing technologies has become increasingly popular, because it represents a rapid and cost-effective method to determine allele frequencies for single nucleotide polymorphisms (SNPs) in population pools. Validation of allele frequencies determined by Pool-Seq has been attempted using an individual genotyping approach, but these studies tend to use samples from existing model organism databases or DNA stores, and do not validate a realistic setup for sampling natural populations. Here we used pyrosequencing to validate allele frequencies determined by Pool-Seq in three natural populations of Arabidopsis halleri (Brassicaceae). The allele frequency estimates of the pooled population samples (consisting of 20 individual plant DNA samples) were determined after mapping Illumina reads to (i) the publicly available, high-quality reference genome of a closely related species (Arabidopsis thaliana) and (ii) our own de novo draft genome assembly of A. halleri. We then pyrosequenced nine selected SNPs using the same individuals from each population, resulting in a total of 540 samples. Our results show a highly significant and accurate relationship between pooled and individually determined allele frequencies, irrespective of the reference genome used. Allele frequencies differed on average by less than 4%. There was no tendency that either the Pool-Seq or the individual-based approach resulted in higher or lower estimates of allele frequencies. Moreover, the rather high coverage in the mapping to the two reference genomes, ranging from 55 to 284x, had no significant effect on the accuracy of the Pool-Seq. A resampling analysis showed that only very low coverage values (below 10-20x) would substantially reduce the precision of the method. We therefore conclude that a pooled re-sequencing approach is well suited for analyses of genetic variation in natural populations.     

Robust Identification of Local Adaptation from Allele Frequencies

Comparing allele frequencies among populations that differ in environment has long been a tool for detecting loci involved in local adaptation. However, such analyses are complicated by an imperfect knowledge of population allele frequencies and neutral correlations of allele frequencies among populations due to shared population history and gene flow. Here we develop a set of methods to robustly test for unusual allele frequency patterns and correlations between environmental variables and allele frequencies while accounting for these complications based on a Bayesian model previously implemented in the software Bayenv. Using this model, we calculate a set of “standardized allele frequencies” that allows investigators to apply tests of their choice to multiple populations while accounting for sampling and covariance due to population history. We illustrate this first by showing that these standardized frequencies can be used to detect nonparametric correlations with environmental variables; these correlations are also less prone to spurious results due to outlier populations. We then demonstrate how these standardized allele frequencies can be used to construct a test to detect SNPs that deviate strongly from neutral population structure. This test is conceptually related to F_ST and is shown to be more powerful, as we account for population history. We also extend the model to next-generation sequencing of population pools—a cost-efficient way to estimate population allele frequencies, but one that introduces an additional level of sampling noise. The utility of these methods is demonstrated in simulations and by reanalyzing human SNP data from the Human Genome Diversity Panel populations and pooled next-generation sequencing data from Atlantic herring. An implementation of our method is available from http://gcbias.org.     

SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries

High-density single-nucleotide polymorphism (SNP) arrays have revolutionized the ability of genome-wide association studies to detect genomic regions harboring sequence variants that affect complex traits. Extensive numbers of validated SNPs with known allele frequencies are essential to construct genotyping assays with broad utility. We describe an economical, efficient, single-step method for SNP discovery, validation and characterization that uses deep sequencing of reduced representation libraries (RRLs) from specified target populations. Using nearly 50 million sequences generated on an Illumina Genome Analyzer from DNA of 66 cattle representing three populations, we identified 62,042 putative SNPs and predicted their allele frequencies. Genotype data for these 66 individuals validated 92% of 23,357 selected genome-wide SNPs, with a genotypic and sequence allele frequency correlation of r = 0.67. This approach for simultaneous de novo discovery of high-quality SNPs and population characterization of allele frequencies may be applied to any species with at least a partially sequenced genome.     

Substantial differences in bias between single‐digest and double‐digest RAD‐seq libraries: A case study

The trade‐offs of using single‐digest vs. double‐digest restriction site‐associated DNA sequencing (RAD‐seq) protocols have been widely discussed. However, no direct empirical comparisons of the two methods have been conducted. Here, we sampled a single population of Gulf pipefish (Syngnathus scovelli) and genotyped 444 individuals using RAD‐seq. Sixty individuals were subjected to single‐digest RAD‐seq (sdRAD‐seq), and the remaining 384 individuals were genotyped using a double‐digest RAD‐seq (ddRAD‐seq) protocol. We analysed the resulting Illumina sequencing data and compared the two genotyping methods when reads were analysed either together or separately. Coverage statistics, observed heterozygosity, and allele frequencies differed significantly between the two protocols, as did the results of selection components analysis. We also performed an in silico digestion of the Gulf pipefish genome and modelled five major sources of bias: PCR duplicates, polymorphic restriction sites, shearing bias, asymmetric sampling (i.e., genotyping fewer individuals with sdRAD‐seq than with ddRAD‐seq) and higher major allele frequencies. This combination of approaches allowed us to determine that polymorphic restriction sites, an asymmetric sampling scheme, mean allele frequencies and to some extent PCR duplicates all contribute to different estimates of allele frequencies between samples genotyped using sdRAD‐seq versus ddRAD‐seq. Our finding that sdRAD‐seq and ddRAD‐seq can result in different allele frequencies has implications for comparisons across studies and techniques that endeavour to identify genomewide signatures of evolutionary processes in natural populations.     

Detection of MPLW515L/K Mutations and Determination of Allele Frequencies with a Single-Tube PCR Assay

A gain-of-function mutation in the myeloproliferative leukemia virus (MPL) gene, which encodes the thrombopoietin receptor, has been identified in patients with essential thrombocythemia and primary myelofibrosis, subgroups of classic myeloproliferative neoplasms (MPNs). The presence of MPL gene mutations is a critical diagnostic criterion for these diseases. Here, we developed a rapid, simple, and cost-effective method of detecting two major MPL mutations, MPLW515L/K, in a single PCR assay; we termed this method DARMS (dual amplification refractory mutation system)-PCR. DARMS-PCR is designed to produce three different PCR products corresponding to MPLW515L, MPLW515K, and all MPL alleles. The amplicons are later detected and quantified using a capillary sequencer to determine the relative frequencies of the mutant and wild-type alleles. Applying DARMS-PCR to human specimens, we successfully identified MPL mutations in MPN patients, with the exception of patients bearing mutant allele frequencies below the detection limit (5%) of this method. The MPL mutant allele frequencies determined using DARMS-PCR correlated strongly with the values determined using deep sequencing. Thus, we demonstrated the potential of DARMS-PCR to detect MPL mutations and determine the allele frequencies in a timely and cost-effective manner.     

The Quantification of Representative Sequences pipeline for amplicon sequencing: case study on within‐population ITS1 sequence variation in a microparasite infecting Daphnia

Next generation sequencing (NGS) platforms are replacing traditional molecular biology protocols like cloning and Sanger sequencing. However, accuracy of NGS platforms has rarely been measured when quantifying relative frequencies of genotypes or taxa within populations. Here we developed a new bioinformatic pipeline (QRS) that pools similar sequence variants and estimates their frequencies in NGS data sets from populations or communities. We tested whether the estimated frequency of representative sequences, generated by 454 amplicon sequencing, differs significantly from that obtained by Sanger sequencing of cloned PCR products. This was performed by analysing sequence variation of the highly variable first internal transcribed spacer (ITS1) of the ichthyosporean Caullerya mesnili, a microparasite of cladocerans of the genus Daphnia. This analysis also serves as a case example of the usage of this pipeline to study within‐population variation. Additionally, a public Illumina data set was used to validate the pipeline on community‐level data. Overall, there was a good correspondence in absolute frequencies of C. mesnili ITS1 sequences obtained from Sanger and 454 platforms. Furthermore, analyses of molecular variance (amova ) revealed that population structure of C. mesnili differs across lakes and years independently of the sequencing platform. Our results support not only the usefulness of amplicon sequencing data for studies of within‐population structure but also the successful application of the QRS pipeline on Illumina‐generated data. The QRS pipeline is freely available together with its documentation under GNU Public Licence version 3 at http://code.google.com/p/quantification-representative-sequences .     

Confidence Intervals for Population Allele Frequencies: The General Case of Sampling from a Finite Diploid Population of Any Size

The estimation of population allele frequencies using sample data forms a central component of studies in population genetics. These estimates can be used to test hypotheses on the evolutionary processes governing changes in genetic variation among populations. However, existing studies frequently do not account for sampling uncertainty in these estimates, thus compromising their utility. Incorporation of this uncertainty has been hindered by the lack of a method for constructing confidence intervals containing the population allele frequencies, for the general case of sampling from a finite diploid population of any size. In this study, we address this important knowledge gap by presenting a rigorous mathematical method to construct such confidence intervals. For a range of scenarios, the method is used to demonstrate that for a particular allele, in order to obtain accurate estimates within 0.05 of the population allele frequency with high probability (%), a sample size of is often required. This analysis is augmented by an application of the method to empirical sample allele frequency data for two populations of the checkerspot butterfly (Melitaea cinxia L.), occupying meadows in Finland. For each population, the method is used to derive % confidence intervals for the population frequencies of three alleles. These intervals are then used to construct two joint % confidence regions, one for the set of three frequencies for each population. These regions are then used to derive a % confidence interval for Jost''s D, a measure of genetic differentiation between the two populations. Overall, the results demonstrate the practical utility of the method with respect to informing sampling design and accounting for sampling uncertainty in studies of population genetics, important for scientific hypothesis-testing and also for risk-based natural resource management.     

Population dynamics of sex-determining alleles in honey bees and self-incompatibility alleles in plants

Mathematical theories of the population dynamics of sex-determining alleles in honey bees are developed. It is shown that in an infinitely large population the equilibrium frequency of a sex allele is 1/n, where n is the number of alleles in the population, and the asymptotic rate of approach to this equilibrium is 2/(3n) per generation. Formulae for the distribution of allele frequencies and the effective and actual numbers of alleles that can be maintained in a finite population are derived by taking into account the population size and mutation rate. It is shown that the allele frequencies in a finite population may deviate considerably from 1/n. Using these results, available data on the number of sex alleles in honey bee populations are discussed. It is also shown that the number of self-incompatibility alleles in plants can be studied in a much simpler way by the method used in this paper. A brief discussion about general overdominant selection is presented.     

Efficient and cost effective population resequencing by pooling and in-solution hybridization

High-throughput sequencing of targeted genomic loci in large populations is an effective approach for evaluating the contribution of rare variants to disease risk. We evaluated the feasibility of using in-solution hybridization-based target capture on pooled DNA samples to enable cost-efficient population sequencing studies. For this, we performed pooled sequencing of 100 HapMap samples across ～ 600 kb of DNA sequence using the Illumina GAIIx. Using our accurate variant calling method for pooled sequence data, we were able to not only identify single nucleotide variants with a low false discovery rate (<1%) but also accurately detect short insertion/deletion variants. In addition, with sufficient coverage per individual in each pool (30-fold) we detected 97.2% of the total variants and 93.6% of variants below 5% in frequency. Finally, allele frequencies for single nucleotide variants (SNVs) estimated from the pooled data and the HapMap genotype data were tightly correlated (correlation coefficient > = 0.995).     

Determination of organophosphate and carbamate resistance allele frequency in diamondback moth populations by quantitative sequencing and inhibition tests

A quantitative sequencing (QS) protocol was established for predicting the frequencies of the A298S and G324A mutations in the diamondback moth (Plutella xylostella) type-1 acetylcholinesterase (AChE) locus, putatively involved in organophosphate (OP) and carbamate (CB) insecticide resistance. The nucleotide resistant signal ratio at each mutation site was generated from sequencing chromatograms and plotted against the corresponding resistance allele frequency. Frequency prediction equations were generated from the plots by linear regression, and the signal ratios were highly correlated with resistance allele frequencies (r² > 0.987). QS analysis of 15 representative regional field populations of DBM in Korea revealed that the allele frequencies of both A298S and G324A were over 70% in most field populations, implying the prevalent state of these resistance-associated mutations. In the AChE inhibition assay, all populations showed reduced sensitivity to paraoxon, DDVP, carbaryl, and carbofuran, supporting the notion that DBM resistance to OPs and CBs is widespread in Korea.     

Sampling for Microsatellite-Based Population Genetic Studies: 25 to 30 Individuals per Population Is Enough to Accurately Estimate Allele Frequencies

One of the most common questions asked before starting a new population genetic study using microsatellite allele frequencies is “how many individuals do I need to sample from each population?” This question has previously been answered by addressing how many individuals are needed to detect all of the alleles present in a population (i.e. rarefaction based analyses). However, we argue that obtaining accurate allele frequencies and accurate estimates of diversity are much more important than detecting all of the alleles, given that very rare alleles (i.e. new mutations) are not very informative for assessing genetic diversity within a population or genetic structure among populations. Here we present a comparison of allele frequencies, expected heterozygosities and genetic distances between real and simulated populations by randomly subsampling 5–100 individuals from four empirical microsatellite genotype datasets (Formica lugubris, Sciurus vulgaris, Thalassarche melanophris, and Himantopus novaezelandia) to create 100 replicate datasets at each sample size. Despite differences in taxon (two birds, one mammal, one insect), population size, number of loci and polymorphism across loci, the degree of differences between simulated and empirical dataset allele frequencies, expected heterozygosities and pairwise F_ST values were almost identical among the four datasets at each sample size. Variability in allele frequency and expected heterozygosity among replicates decreased with increasing sample size, but these decreases were minimal above sample sizes of 25 to 30. Therefore, there appears to be little benefit in sampling more than 25 to 30 individuals per population for population genetic studies based on microsatellite allele frequencies.     

Analysis,Optimization and Verification of Illumina-Generated 16S rRNA Gene Amplicon Surveys

The exploration of microbial communities by sequencing 16S rRNA genes has expanded with low-cost, high-throughput sequencing instruments. Illumina-based 16S rRNA gene sequencing has recently gained popularity over 454 pyrosequencing due to its lower costs, higher accuracy and greater throughput. Although recent reports suggest that Illumina and 454 pyrosequencing provide similar beta diversity measures, it remains to be demonstrated that pre-existing 454 pyrosequencing workflows can transfer directly from 454 to Illumina MiSeq sequencing by simply changing the sequencing adapters of the primers. In this study, we modified 454 pyrosequencing primers targeting the V4-V5 hyper-variable regions of the 16S rRNA gene to be compatible with Illumina sequencers. Microbial communities from cows, humans, leeches, mice, sewage, and termites and a mock community were analyzed by 454 and MiSeq sequencing of the V4-V5 region and MiSeq sequencing of the V4 region. Our analysis revealed that reference-based OTU clustering alone introduced biases compared to de novo clustering, preventing certain taxa from being observed in some samples. Based on this we devised and recommend an analysis pipeline that includes read merging, contaminant filtering, and reference-based clustering followed by de novo OTU clustering, which produces diversity measures consistent with de novo OTU clustering analysis. Low levels of dataset contamination with Illumina sequencing were discovered that could affect analyses that require highly sensitive approaches. While moving to Illumina-based sequencing platforms promises to provide deeper insights into the breadth and function of microbial diversity, our results show that care must be taken to ensure that sequencing and processing artifacts do not obscure true microbial diversity.     

Genetic Integrity and Microgeographic Population Structure of Westslope Cutthroat Trout, Oncorhynchus clarki lewisi, in the Pend Oreille Basin in Washington

Five microsatellite DNA loci (Ots-101 ^*,Ots-107 ^*,Oki-10 ^*, Ogo-3 ^*, and FGT-3 ^*) were screened to evaluate the genetic characteristics and population structure for cutthroat trout from eight tributaries of the Pend Oreille River in northeastern Washington and to compare these collections with two hatchery stocks of westslope cutthroat trout, Oncorhynchus clarki lewisi, Yellowstone cutthroat trout, Oncorhynchus clarki bouvieri and a hatchery rainbow trout, Oncorhynchus mykiss, strain that have been stocked in northeastern Washington. Relatively high levels of variation (numbers of alleles and heterozygosity) were observed in all collections and allele frequencies were quite variable among collections. Evidence of limited introgression by rainbow and/or Yellowstone cutthroat was found at several locations. Both F_ST values and tests of genetic differentiation indicated the existence of numerous, reproductively isolated populations. The population in Slate Creek was very similar to the Kings Lake Hatchery strain, and we conclude that this similarity is the result of historical introductions of this hatchery strain into what was presumably a stream without a native cutthroat population. In one stream, differences in introgression and allele frequencies were found above and below a barrier falls. Because of the substantial level of population differentiation observed among the various collections, we recommend that management and conservation actions be focused at the level of individual streams in order to maintain the productivity and genetic character of the existing populations of cutthroat trout.     

Comparison of Normalization Methods for Construction of Large,Multiplex Amplicon Pools for Next-Generation Sequencing

Constructing mixtures of tagged or bar-coded DNAs for sequencing is an important requirement for the efficient use of next-generation sequencers in applications where limited sequence data are required per sample. There are many applications in which next-generation sequencing can be used effectively to sequence large mixed samples; an example is the characterization of microbial communities where ≤1,000 sequences per samples are adequate to address research questions. Thus, it is possible to examine hundreds to thousands of samples per run on massively parallel next-generation sequencers. However, the cost savings for efficient utilization of sequence capacity is realized only if the production and management costs associated with construction of multiplex pools are also scalable. One critical step in multiplex pool construction is the normalization process, whereby equimolar amounts of each amplicon are mixed. Here we compare three approaches (spectroscopy, size-restricted spectroscopy, and quantitative binding) for normalization of large, multiplex amplicon pools for performance and efficiency. We found that the quantitative binding approach was superior and represents an efficient scalable process for construction of very large, multiplex pools with hundreds and perhaps thousands of individual amplicons included. We demonstrate the increased sequence diversity identified with higher throughput. Massively parallel sequencing can dramatically accelerate microbial ecology studies by allowing appropriate replication of sequence acquisition to account for temporal and spatial variations. Further, population studies to examine genetic variation, which require even lower levels of sequencing, should be possible where thousands of individual bar-coded amplicons are examined in parallel.Emergent technologies that generate DNA sequence data are designed primarily to perform resequencing projects at reasonable cost. The result is a substantial decrease in per base costs from traditional methods. However, these next-generation platforms do not readily accommodate projects that require obtaining moderate amounts of sequence from large numbers of samples. These platforms also have per run costs that are significant and generally preclude large numbers of single-sample, nonmultiplexed runs. One example of research that is not readily supported is rRNA-directed metagenomics study of some human clinical samples or environmental rRNA analysis of samples from communities with low community diversity that require only thousands of sequences. Thus, strategies to utilize next-generation DNA sequencers efficiently for applications that require lower throughput are critical to capitalize on the efficiency and cost benefits of next-generation sequencing platforms.Directed metagenomics based on amplification of rRNA genes is an important tool to characterize microbial communities in various environmental and clinical settings. In diverse environmental samples, large numbers of sequences are required to fully characterize the microbial communities (15). However, a lower number of sequences is generally adequate to answer specific research questions. In addition, the levels of diversity in human clinical samples are usually lower than what is observed in environmental samples (for example, see reference 7).The Roche 454 genome sequencer system FLX pyrosequencer (which we will refer to as 454 FLX hereafter) is the most useful platform for rRNA-directed metagenomics because it currently provides the longest read lengths of any next-generation sequencing platform (1, 14). Computational analysis has shown that the 250-nucleotide read length (available from the 454 FLX-LR chemistry) is adequate for identification of bacteria if the amplified region is properly positioned within variable regions of the small-subunit rRNA (SSU-rRNA) gene (9, 10).In this study, we used the 454 FLX-LR genome sequencing platform and chemistry, which provides >400,000 sequences of ∼250 bp per run. After we conducted this study, a new reagent set (454 FLX-XLR titanium chemistry) was released, which further increases reads to >1,000,000 and read lengths to >400 bp (Roche). The 454 FLX platform dramatically reduces per base costs of obtaining sequence, and physical separation into between 2 and 16 lanes is available; this physical separation on the plate reduces sequencing output overall, up to 40% comparing 2 lanes versus 16 lanes. For applications where modest sequencing depth (∼1,000 sequences per sample) is adequate to address research questions, physical separation does not allow adequate sample multiplexing because even a 1/16 454 FLX-LR plate run is expected to produce ∼15,000 reads. Further, the utility of the platform as a screening tool at 16-plex is limited by cost per run.A solution to make next-generation sequencing economical for projects such as rRNA-directed metagenomics is to use bar-coded primers to multiplex amplicon pools so they can be sequenced together and computationally separated afterward (6). To successfully accomplish this strategy, precise normalization of the DNA concentrations of the individual amplicons in the multiplex pools is essential for effective multiplex sequencing when large numbers of pooled samples are sequenced in parallel. There are several potential methods available for normalizing concentrations of amplicons included in multiplex pools, but the relative and absolute performance of each approach has not been compared.In this study, we present a direct quantitative comparison of three available methods for amplicon pool normalization for downstream next-generation sequencing. The central goal of the study was to identify the most effective method for normalizing multiplex pools containing >100 individual amplicons. We evaluated each pooling approach by 454 sequencing and compared the observed frequencies of sequences from different pooled bar-coded amplicons. From these data, we determined the efficacy of each method based on the following factors: (i) how well normalized the sequences within the pool were, (ii) the proportion of samples failing to meet a minimum threshold of sequences per sample, and (iii) the overall efficiency (speed and labor required) of the process to multiplex samples.     

Multiplex pyrosequencing method to determine CYP2C9*3, VKORC1*2, and CYP4F2*3 polymorphisms simultaneously: its application to a Korean population and comparisons with other ethnic groups

Warfarin is an anticoagulant that is difficult to administer because of the wide variation in dose requirements to achieve a therapeutic effect. CYP2C9, VKROC1, and CYP4F2 play important roles in warfarin metabolism, and their genetic polymorphisms are related to the variability in dose determination. In this study we describe a new multiplex pyrosequencing method to identify CYP2C9*3 (rs1057910), VKORC1*2 (rs9923231), and CYP4F2*3 (rs2108661) simultaneously. A multiplex pyrosequencing method to simultaneously detect CYP2C9*3, VKORC1*2, and CYP4F2*3 alleles was designed. We assessed the allele frequencies of the polymorphisms in 250 Korean subjects using the multiplex pyrosequencing method. The results showed 100 % concordance between single and multiplex pyrosequencing methods, and the polymorphisms identified by pyrosequencing were also validated with the direct sequencing method. The allele frequencies of these polymorphisms in this population were as follows: 0.040 for CYP2C9*3, 0.918 for VKORC1*2, and 0.416 for CYP4F2*3. Although the allele frequencies of the CYP2C9*3 and VKROC1*2 were comparable to those in Japanese and Chinese populations, their frequencies in this Korean population differed from those in other ethnic groups; the CYP4F2*3 frequency was the highest among other ethnic populations including Chinese and Japanese populations. The pyrosequencing methods developed were rapid and reliable for detecting CYP2C9*3, VKORC1*2, and CYP4F2*3. Large ethnic differences in the frequency of these genetic polymorphisms were noted among ethnic groups. CYP4F2*3 exhibited its highest allele frequency among other ethnic populations compared to that in a Korean population.     

Frequency distributions for chloroplast genes in Chlamydomonas zygote clones: Evidence for random drift

Mitochondria and chloroplasts of eucaryotic cells contain populations of DNA molecules. In certain cases, e.g., the chloroplasts of Chlamydomonas reinhardtii and the mitochondria of Saccharomyces cerevisiae, organelles contributed by the two parents are known to fuse in the zygote, creating a single population of DNA molecules. In a cross, this population will include molecules of both parental genotypes. There is reason to suspect that organelle DNA molecules in this population are selected randomly for replication and recombination. This would result in random changes in the frequency of a particular allele or genotype within the organelle gene pool of a single zygote and also within its clone of progeny cells. A given gene frequency would increase in some zygote clones and decrease in others, analogous to random drift of gene frequencies in small Mendelian populations. To test this, we have examined the distribution of chloroplast gene frequencies among the zygote clones produced in each of a number of crosses of Chlamydomonas. These distributions are typically U or L shaped as predicted by the random drift hypothesis. They include uniparental zygote clones, in which a chloroplast allele from one parent has been fixed (frequency 100%) and the alternative allele from the other parent has been lost (frequency 0%). Among the remaining (biparental) zygote clones, there is a linear distribution of allele frequencies, showing a great increase in variance over the input frequencies. In these experiments both biparental and uniparental zygotes show a bias favoring chloroplast alleles from the mt⁺ (maternal) parent, and there is no statistically significant mode at the allele frequency of 0.5 corresponding to the equal input of alleles from the maternal and paternal (mt^?) parents. The observed distributions support the hypothesis that both uniparental inheritance and the high variance of allele frequencies among zygote clones are due to random drift of allele frequencies, coupled with a directional force which favors fixation of the maternal allele. In addition, statistical analysis of the data shows a strong but incomplete tendency for linked chloroplast markers to be fixed or lost together in uniparental zygotes. Possible cellular and molecular mechanisms for these observations are discussed.     

Esterase polymorphism in the corn earworm,Heliothis zea (Boddie): A survey of temporal and spatial allelic variation in natural populations

Allelic variation at the Est-II locus was investigated in 22 natural populations of Heliothis zea from maize, separated spatially and temporally. Of the four alleles observed, Est-II ^b was the predominant one in every population. The relative frequency of Est-II ^b ranged from 0.57 to 0.85, with a mean of 0.72±0.06, and proved to be remarkably stable in space and time. Temporal changes in Est-II allele frequencies were observed at two of the sampling localities; however, principal component analysis and multiple correlation of genetic and environmental components have provided persuasive evidence that abiotic environmental or geographic variation is not related to differences in Est-II allele frequencies. Possible factors responsible for the maintenance of this polymorphism are discussed and include possible effects of the chemical composition of host plants and pesticides.     

Comparative studies of microbial populations in the rumen,duodenum, ileum and faeces of lactating dairy cows

Aims: Understanding factors that influence the composition of microbial populations of the digestive system of dairy cattle will be key in regulating these populations to improve animal performance. Although rumen microbes are well studied, little is known of the dynamics and role of microbial populations in the small intestine of cows. Comparisons of fingerprints of microbial populations were used to investigate the effects of gastrointestinal (GI) segment and animal on community structure. Methods and Results: Samples from four lactating dairy cows with ruminal, duodenal and ileal cannulae were collected. Terminal‐restriction fragment length polymorphism (T‐RFLP) comparisons of small subunit rRNA genes revealed differences in microbial populations between GI segments (P < 0·05). No significant differences in either methanogen populations or microbial community profiles between animals were observed. Quantitative PCR was used to assay relative changes in methanogen numbers compared to procaryote rRNA gene numbers, and direct microscopic counts were used to enumerate total procaryote numbers of the duodenal and ileal samples. Conclusions: T‐RFLP comparisons illustrate significant changes in microbial diversity as digesta passes from one segment to another. Direct counts indicate that microbial numbers are reduced by eight orders of magnitude from the rumen, through the abomasum, and into the duodenum (from c. 10¹² to c. 3·6 × 10⁴ cells per ml). Quantitative PCR analyses of rRNA genes indicate that methanogens are present in the duodenum and ileum. Significance and Impact of the Study: The contribution of microbial populations of the small intestine to the nutrition and health of cattle is seldom addressed but warrants further investigation.     

Viral population analysis and minority-variant detection using short read next-generation sequencing

RNA viruses within infected individuals exist as a population of evolutionary-related variants. Owing to evolutionary change affecting the constitution of this population, the frequency and/or occurrence of individual viral variants can show marked or subtle fluctuations. Since the development of massively parallel sequencing platforms, such viral populations can now be investigated to unprecedented resolution. A critical problem with such analyses is the presence of sequencing-related errors that obscure the identification of true biological variants present at low frequency. Here, we report the development and assessment of the Quality Assessment of Short Read (QUASR) Pipeline (http://sourceforge.net/projects/quasr) specific for virus genome short read analysis that minimizes sequencing errors from multiple deep-sequencing platforms, and enables post-mapping analysis of the minority variants within the viral population. QUASR significantly reduces the error-related noise in deep-sequencing datasets, resulting in increased mapping accuracy and reduction of erroneous mutations. Using QUASR, we have determined influenza virus genome dynamics in sequential samples from an in vitro evolution of 2009 pandemic H1N1 (A/H1N1/09) influenza from samples sequenced on both the Roche 454 GSFLX and Illumina GAIIx platforms. Importantly, concordance between the 454 and Illumina sequencing allowed unambiguous minority-variant detection and accurate determination of virus population turnover in vitro.