Similar patterns of linkage disequilibrium and nucleotide diversity in native and introduced populations of the pea aphid, Acyrthosiphon pisum

<p>Abstract</p> <p>Background</p> <p>The pea aphid, <it>Acyrthosiphon pisum</it>, is an emerging genomic model system for studies of polyphenisms, bacterial symbioses, host-plant specialization, and the vectoring of plant viruses. Here we provide estimates of nucleotide diversity and linkage disequilibrium (LD) in native (European) and introduced (United States) populations of the pea aphid. Because introductions can cause population bottlenecks, we hypothesized that U.S. populations harbor lower levels of nucleotide diversity and higher levels of LD than native populations.</p> <p>Results</p> <p>We sampled four non-coding loci from 24 unique aphid clones from the U. S. (12 from New York and 12 from California) and 24 clones from Europe (12 alfalfa and 12 clover specialists). For each locus, we sequenced approximately 1 kb from two amplicons spaced ~10 kb apart to estimate both short range and longer range LD. We sequenced over 250 kb in total. Nucleotide diversity averaged 0.6% across all loci and all populations. LD decayed slowly within ~1 kb but reached much lower levels over ~10 kb. Contrary to our expectations, neither LD nor nucleotide diversity were significantly different between native and introduced populations.</p> <p>Conclusion</p> <p>Both introduced and native populations of pea aphids exhibit low levels of nucleotide diversity and moderate levels of LD. The introduction of pea aphids to North America has not led to a detectable reduction of nucleotide diversity or increase in LD relative to native populations.</p

Identification of co-regulated transcripts affecting male body size in Drosophila

Factor analysis is an analytic approach that describes the covariation among a set of genes through the estimation of 'factors', which may be, for example, transcription factors, microRNAs (miRNAs), and so on, by which the genes are co-regulated. Factor analysis gives a direct mechanism by which to relate gene networks to complex traits. Using simulated data, we found that factor analysis clearly identifies the number and structure of factors and outperforms hierarchical cluster analysis. Noise genes, genes that are not correlated with any factor, can be distinguished even when factor structure is complex. Applied to body size in Drosophila simulans, an evolutionarily important complex trait, a factor was directly associated with body size

Genomic and phenotypic analysis of Vavilov's historic landraces reveals the impact of environment and genomic islands of agronomic traits.

The Vavilov Institute of Plant Genetic Resources (VIR), in St. Petersburg, Russia, houses a unique genebank, with historical collections of landraces. When they were collected, the geographical distribution and genetic diversity of most crops closely reflected their historical patterns of cultivation established over the preceding millennia. We employed a combination of genomics, computational biology and phenotyping to characterize VIR's 147 chickpea accessions from Turkey and Ethiopia, representing chickpea's center of origin and a major location of secondary diversity. Genotyping by sequencing identified 14,059 segregating polymorphisms and genome-wide association studies revealed 28 GWAS hits in potential candidate genes likely to affect traits of agricultural importance. The proportion of polymorphisms shared among accessions is a strong predictor of phenotypic resemblance, and of environmental similarity between historical sampling sites. We found that 20 out of 28 polymorphisms, associated with multiple traits, including days to maturity, plant phenology, and yield-related traits such as pod number, localized to chromosome 4. We hypothesize that selection and introgression via inadvertent hybridization between more and less advanced morphotypes might have resulted in agricultural improvement genes being aggregated to genomic 'agro islands', and in genotype-to-phenotype relationships resembling widespread pleiotropy

Natural genetic variation in transcriptome reflects network structure inferred with major effect mutations: insulin/TOR and associated phenotypes in Drosophila melanogaster

<p>Abstract</p> <p>Background</p> <p>A molecular process based genotype-to-phenotype map will ultimately enable us to predict how genetic variation among individuals results in phenotypic alterations. Building such a map is, however, far from straightforward. It requires understanding how molecular variation re-shapes developmental and metabolic networks, and how the functional state of these networks modifies phenotypes in genotype specific way. We focus on the latter problem by describing genetic variation in transcript levels of genes in the InR/TOR pathway among 72 <it>Drosophila melanogaster </it>genotypes.</p> <p>Results</p> <p>We observe tight co-variance in transcript levels of genes not known to influence each other through direct transcriptional control. We summarize transcriptome variation with factor analyses, and observe strong co-variance of gene expression within the dFOXO-branch and within the TOR-branch of the pathway. Finally, we investigate whether major axes of transcriptome variation shape phenotypes expected to be influenced through the InR/TOR pathway. We find limited evidence that transcript levels of individual upstream genes in the InR/TOR pathway predict fly phenotypes in expected ways. However, there is no evidence that these effects are mediated through the major axes of downstream transcriptome variation.</p> <p>Conclusion</p> <p>In summary, our results question the assertion of the 'sparse' nature of genetic networks, while validating and extending candidate gene approaches in the analyses of complex traits.</p

Scanning Probe Microscopy of silicon layers after Ag+ implantation

Описан способ формирования нанопористого кремния на поверхности монокристаллического Si при имплантации ионами Ag+. Методами СЗМ и СЭМ показано, что в результате на поверхности Si формируются аморфные слои нанопористого кремния со средними размерами пор ~130 нм, в структуре которых синтезируются наночастицы Ag диаметром от 5 до 20 нм.An idea to create nanoporous silicon layers by low-energy high-dose Ag-ion implantation was realized. Surface structures were analyzed by scanning electron microscopy and scanning probe microscopy. It is shown that as a result there are a porous structure with a characteristic size ~130 nm on Si surface with Ag nanoparticles (diameter 5-20nm) inside.Работа выполнена при финансовой поддержке РНФ № 17-12-01176

Population-Based Resequencing of Experimentally Evolved Populations Reveals the Genetic Basis of Body Size Variation in Drosophila melanogaster

Body size is a classic quantitative trait with evolutionarily significant variation within many species. Locating the alleles responsible for this variation would help understand the maintenance of variation in body size in particular, as well as quantitative traits in general. However, successful genome-wide association of genotype and phenotype may require very large sample sizes if alleles have low population frequencies or modest effects. As a complementary approach, we propose that population-based resequencing of experimentally evolved populations allows for considerable power to map functional variation. Here, we use this technique to investigate the genetic basis of natural variation in body size in Drosophila melanogaster. Significant differentiation of hundreds of loci in replicate selection populations supports the hypothesis that the genetic basis of body size variation is very polygenic in D. melanogaster. Significantly differentiated variants are limited to single genes at some loci, allowing precise hypotheses to be formed regarding causal polymorphisms, while other significant regions are large and contain many genes. By using significantly associated polymorphisms as a priori candidates in follow-up studies, these data are expected to provide considerable power to determine the genetic basis of natural variation in body size

Natural Variation in Decision-Making Behavior in Drosophila melanogaster

There has been considerable recent interest in using Drosophila melanogaster to investigate the molecular basis of decision-making behavior. Deciding where to place eggs is likely one of the most important decisions for a female fly, as eggs are vulnerable and larvae have limited motility. Here, we show that many natural genotypes of D. melanogaster prefer to lay eggs near nutritious substrate, rather than in nutritious substrate. These preferences are highly polymorphic in both degree and direction, with considerable heritability (0.488) and evolvability