Robert Kofler

SciRoKo: a new tool for whole genome microsatellite search and investigation

UNLABELLED SciRoKo is a user-friendly software tool for the identification of microsatellites in genomic sequences. The combination of an extremely fast search algorithm with a built-in summary statistic tool makes SciRoKo an excellent tool for full genome analysis. Compared to other already existing tools, SciRoKo also allows the analysis of compound microsatellites. AVAILABILITY free for use: www.kofler.or.at/Bioinformatics. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

PoPoolation2: identifying differentiation between populations using sequencing of pooled DNA samples (Pool-Seq)

Summary: Sequencing pooled DNA samples (Pool-Seq) is the most cost-effective approach for the genome-wide comparison of population samples. Here, we introduce PoPoolation2, the first software tool specifically designed for the comparison of populations with Pool-Seq data. PoPoolation2 implements a range of commonly used measures of differentiation (FST, Fishers exact test and Cochran-Mantel-Haenszel test) that can be applied on different scales (windows, genes, exons, SNPs). The result may be visualized with the widely used Integrated Genomics Viewer. Availability and Implementation: PoPoolation2 is implemented in Perl and R. It is freely available on http://code.google.com/p/popoolation2/ Contact: christian.schloetterer@vetmeduni.ac.at Supplementary Information: Manual: http://code.google.com/p/popoolation2/wiki/Manual Test data and tutorial: http://code.google.com/p/popoolation2/wiki/Tutorial Validation: http://code.google.com/p/popoolation2/wiki/Validation

PoPoolation: A Toolbox for Population Genetic Analysis of Next Generation Sequencing Data from Pooled Individuals

Recent statistical analyses suggest that sequencing of pooled samples provides a cost effective approach to determine genome-wide population genetic parameters. Here we introduce PoPoolation, a toolbox specifically designed for the population genetic analysis of sequence data from pooled individuals. PoPoolation calculates estimates of θ Watterson, θ π, and Tajimas D that account for the bias introduced by pooling and sequencing errors, as well as divergence between species. Results of genome-wide analyses can be graphically displayed in a sliding window plot. PoPoolation is written in Perl and R and it builds on commonly used data formats. Its source code can be downloaded from http://code.google.com/p/popoolation/. Furthermore, we evaluate the influence of mapping algorithms, sequencing errors, and read coverage on the accuracy of population genetic parameter estimates from pooled data.

Sequencing pools of individuals — mining genome-wide polymorphism data without big funding

The analysis of polymorphism data is becoming increasingly important as a complementary tool to classical genetic analyses. Nevertheless, despite plunging sequencing costs, genomic sequencing of individuals at the population scale is still restricted to a few model species. Whole-genome sequencing of pools of individuals (Pool-seq) provides a cost-effective alternative to sequencing individuals separately. With the availability of custom-tailored software tools, Pool-seq is being increasingly used for population genomic research on both model and non-model organisms. In this Review, we not only demonstrate the breadth of questions that are being addressed by Pool-seq but also discuss its limitations and provide guidelines for users.

Genome-wide patterns of latitudinal differentiation among populations of Drosophila melanogaster from North America

Understanding the genetic underpinnings of adaptive change is a fundamental but largely unresolved problem in evolutionary biology. Drosophila melanogaster, an ancestrally tropical insect that has spread to temperate regions and become cosmopolitan, offers a powerful opportunity for identifying the molecular polymorphisms underlying clinal adaptation. Here, we use genome‐wide next‐generation sequencing of DNA pools (‘pool‐seq’) from three populations collected along the North American east coast to examine patterns of latitudinal differentiation. Comparing the genomes of these populations is particularly interesting since they exhibit clinal variation in a number of important life history traits. We find extensive latitudinal differentiation, with many of the most strongly differentiated genes involved in major functional pathways such as the insulin/TOR, ecdysone, torso, EGFR, TGFβ/BMP, JAK/STAT, immunity and circadian rhythm pathways. We observe particularly strong differentiation on chromosome 3R, especially within the cosmopolitan inversion In(3R)Payne, which contains a large number of clinally varying genes. While much of the differentiation might be driven by clinal differences in the frequency of In(3R)P, we also identify genes that are likely independent of this inversion. Our results provide genome‐wide evidence consistent with pervasive spatially variable selection acting on numerous loci and pathways along the well‐known North American cline, with many candidates implicated in life history regulation and exhibiting parallel differentiation along the previously investigated Australian cline.

Adaptation of Drosophila to a novel laboratory environment reveals temporally heterogeneous trajectories of selected alleles

The genomic basis of adaptation to novel environments is a fundamental problem in evolutionary biology that has gained additional importance in the light of the recent global change discussion. Here, we combined laboratory natural selection (experimental evolution) in Drosophila melanogaster with genome-wide next generation sequencing of DNA pools (Pool-Seq) to identify alleles that are favourable in a novel laboratory environment and traced their trajectories during the adaptive process. Already after 15 generations, we identified a pronounced genomic response to selection, with almost 5000 single nucleotide polymorphisms (SNP; genome-wide false discovery rates < 0.005%) deviating from neutral expectation. Importantly, the evolutionary trajectories of the selected alleles were heterogeneous, with the alleles falling into two distinct classes: (i) alleles that continuously rise in frequency; and (ii) alleles that at first increase rapidly but whose frequencies then reach a plateau. Our data thus suggest that the genomic response to selection can involve a large number of selected SNPs that show unexpectedly complex evolutionary trajectories, possibly due to nonadditive effects.

Sequencing of Pooled DNA Samples (Pool-Seq) Uncovers Complex Dynamics of Transposable Element Insertions in Drosophila melanogaster

Transposable elements (TEs) are mobile genetic elements that parasitize genomes by semi-autonomously increasing their own copy number within the host genome. While TEs are important for genome evolution, appropriate methods for performing unbiased genome-wide surveys of TE variation in natural populations have been lacking. Here, we describe a novel and cost-effective approach for estimating population frequencies of TE insertions using paired-end Illumina reads from a pooled population sample. Importantly, the method treats insertions present in and absent from the reference genome identically, allowing unbiased TE population frequency estimates. We apply this method to data from a natural Drosophila melanogaster population from Portugal. Consistent with previous reports, we show that low recombining genomic regions harbor more TE insertions and maintain insertions at higher frequencies than do high recombining regions. We conservatively estimate that there are almost twice as many “novel” TE insertion sites as sites known from the reference sequence in our population sample (6,824 novel versus 3,639 reference sites, with on average a 31-fold coverage per insertion site). Different families of transposable elements show large differences in their insertion densities and population frequencies. Our analyses suggest that the history of TE activity significantly contributes to this pattern, with recently active families segregating at lower frequencies than those active in the more distant past. Finally, using our high-resolution TE abundance measurements, we identified 13 candidate positively selected TE insertions based on their high population frequencies and on low Tajimas D values in their neighborhoods.

A first survey of the rye (Secale cereale) genome composition through BAC end sequencing of the short arm of chromosome 1R

BackgroundRye (Secale cereale L.) belongs to tribe Triticeae and is an important temperate cereal. It is one of the parents of man-made species Triticale and has been used as a source of agronomically important genes for wheat improvement. The short arm of rye chromosome 1 (1RS), in particular is rich in useful genes, and as it may increase yield, protein content and resistance to biotic and abiotic stress, it has been introgressed into wheat as the 1BL.1RS translocation. A better knowledge of the rye genome could facilitate rye improvement and increase the efficiency of utilizing rye genes in wheat breeding.ResultsHere, we report on BAC end sequencing of 1,536 clones from two 1RS-specific BAC libraries. We obtained 2,778 (90.4%) useful sequences with a cumulative length of 2,032,538 bp and an average read length of 732 bp. These sequences represent 0.5% of 1RS arm. The GC content of the sequenced fraction of 1RS is 45.9%, and at least 84% of the 1RS arm consists of repetitive DNA. We identified transposable element junctions in BESs and developed insertion site based polymorphism markers (ISBP). Out of the 64 primer pairs tested, 17 (26.6%) were specific for 1RS. We also identified BESs carrying microsatellites suitable for development of 1RS-specific SSR markers.ConclusionThis work demonstrates the utility of chromosome arm-specific BAC libraries for targeted analysis of large Triticeae genomes and provides new sequence data from the rye genome and molecular markers for the short arm of rye chromosome 1.

Massive habitat-specific genomic response in D. melanogaster populations during experimental evolution in hot and cold environments

Experimental evolution in combination with whole-genome sequencing (evolve and resequence [E&R]) is a promising approach to define the genotype–phenotype map and to understand adaptation in evolving populations. Many previous studies have identified a large number of putative selected sites (i.e., candidate loci), but it remains unclear to what extent these loci are genuine targets of selection or experimental noise. To address this question, we exposed the same founder population to two different selection regimes—a hot environment and a cold environment—and quantified the genomic response in each. We detected large numbers of putative selected loci in both environments, albeit with little overlap between the two sets of candidates, indicating that most resulted from habitat-specific selection. By quantifying changes across multiple independent biological replicates, we demonstrate that most of the candidate SNPs were false positives that were linked to selected sites over distances much larger than the typical linkage disequilibrium range of Drosophila melanogaster. We show that many of these mid- to long-range associations were attributable to large segregating inversions and confirm by computer simulations that such patterns could be readily replicated when strong selection acts on rare haplotypes. In light of our findings, we outline recommendations to improve the performance of future Drosophila E&R studies which include using species with negligible inversion loads, such as D. mauritiana and D. simulans, instead of D. melanogaster.

Combining experimental evolution with next-generation sequencing: a powerful tool to study adaptation from standing genetic variation

Evolve and resequence (E&R) is a new approach to investigate the genomic responses to selection during experimental evolution. By using whole genome sequencing of pools of individuals (Pool-Seq), this method can identify selected variants in controlled and replicable experimental settings. Reviewing the current state of the field, we show that E&R can be powerful enough to identify causative genes and possibly even single-nucleotide polymorphisms. We also discuss how the experimental design and the complexity of the trait could result in a large number of false positive candidates. We suggest experimental and analytical strategies to maximize the power of E&R to uncover the genotype–phenotype link and serve as an important research tool for a broad range of evolutionary questions.