Population Structure and Diversity in European Honey Bees (Apis mellifera L.)-An Empirical Comparison of Pool and Individual Whole-Genome Sequencing

Background: Whole-genome sequencing has become routine for population genetic studies. Sequencing of individuals provides maximal data but is rather expensive and fewer samples can be studied. In contrast, sequencing a pool of samples (pool-seq) can provide sufficient data, while presenting less of an economic challenge. Few studies have compared the two approaches to infer population genetic structure and diversity in real datasets. Here, we apply individual sequencing (ind-seq) and pool-seq to the study of Western honey bees (Apis mellifera). Methods: We collected honey bee workers that belonged to 14 populations, including 13 subspecies, totaling 1347 colonies, who were individually (139 individuals) and pool-sequenced (14 pools). We compared allele frequencies, genetic diversity estimates, and population structure as inferred by the two approaches. Results: Pool-seq and ind-seq revealed near identical population structure and genetic diversities, albeit at different costs. While pool-seq provides genome-wide polymorphism data at considerably lower costs, ind-seq can provide additional information, including the identification of population substructures, hybridization, or individual outliers. Conclusions: If costs are not the limiting factor, we recommend using ind-seq, as population genetic structure can be inferred similarly well, with the advantage gained from individual genetic information. Not least, it also significantly reduces the effort required for the collection of numerous samples and their further processing in the laboratory.This work was supported by National Natural Science Foundation of China (Grant No. 31902219) and Modern Agro-industry Technology Research System (Grant No. CARDS-45-KXJ1). The SmartBees project was funded by the European Commission under its FP7 KBBE programme (2013.1.3-02, SmartBees Grant Agreement number 613960). MP and J.L were supported by the Applied Genomics and Bioinformatics research group (IT1233-19) funded by the Basque Government grant IT1233-19. Additionally, JL was funded by the grant PRE_2017_2_0169 from the Department of Education of the Basque Government

Authoritative subspecies diagnosis tool for European honey bees based on ancestryinformative SNPs

Background With numerous endemic subspecies representing four of its five evolutionary lineages, Europe holds a large fraction of Apis mellifera genetic diversity. This diversity and the natural distribution range have been altered by anthropogenic factors. The conservation of this natural heritage relies on the availability of accurate tools for subspecies diagnosis. Based on pool-sequence data from 2145 worker bees representing 22 populations sampled across Europe, we employed two highly discriminative approaches (PCA and F-ST) to select the most informative SNPs for ancestry inference. Results Using a supervised machine learning (ML) approach and a set of 3896 genotyped individuals, we could show that the 4094 selected single nucleotide polymorphisms (SNPs) provide an accurate prediction of ancestry inference in European honey bees. The best ML model was Linear Support Vector Classifier (Linear SVC) which correctly assigned most individuals to one of the 14 subspecies or different genetic origins with a mean accuracy of 96.2% +/- 0.8 SD. A total of 3.8% of test individuals were misclassified, most probably due to limited differentiation between the subspecies caused by close geographical proximity, or human interference of genetic integrity of reference subspecies, or a combination thereof. Conclusions The diagnostic tool presented here will contribute to a sustainable conservation and support breeding activities in order to preserve the genetic heritage of European honey bees.The SmartBees project was funded by the European Commission under its FP7 KBBE programme (2013.1.3-02, SmartBees Grant Agreement number 613960) https://ec.europa.eu/research/fp7.MP was supported by a Basque Government grant (IT1233-19). The funders provided the financial support to the research, but had no role in the design of the study, analysis, interpretations of data and in writing the manuscript

Porcine SLITRK1: Molecular cloning and characterization

The membrane protein SLITRK1 functions as a developmentally regulated stimulator of neurite outgrowth and variants in this gene have been implicated in Tourette syndrome. In the current study we have cloned and characterized the porcine SLITRK1 gene. The genomic organization of SLITRK1 lacks introns, as does its human and mouse counterparts. RT-PCR cloning revealed two SLITRK1 transcripts: a full-length mRNA and a transcript variant that results in a truncated protein. The encoded SLITRK1 protein, consisting of 695 amino acids, displays a very high homology to human SLITRK1 (99%). The porcine SLITRK1 gene is expressed exclusively in brain tissues

The Necessity of Economic Structural Transformation in Developing Countries toward a Knowledge-based Economy Case Study: Iran

ABSTRACT Since the early 1990s, due to rapid growth of knowledge and globalization of economy, the production patterns, distribution and consumption of financial products have undergone profound changes and the preliminarily signs of the formation of a new economic systemin which knowledge is the most important productive factor have emerged. In knowledge based economic system terms of economic performance have changed, therefore new threats and opportunities have come to existence. The present article applies a descriptive-analytical method to study these threats and opportunities using a new economic system in developing countries. The main objective of this article is to explain the necessity of structural transformation of economy in developing countries, like Iran, toward a knowledge-based economy in order to avoid under development deepening and achieve an acceptable rate of growth and progress

Measuring Ecological Footprint of Fossil Fuels in Economic Sectors of Iran: An Input-Output Approach

One of the essential indices for measuring sustainable development is ecological footprint. This paper which focuses on concept of ecological footprint of fossil fuels, tries to answer two important questions. The first question is wether the pattern of export and import of energy content in Iran confirms its comparative advantage? The second question is how much is the ecological footprint of Iranian economic sectors in year 2011? To measure ecological footprint of fossil fuels, we employ two different databases in this article, first activity by activity symmetric I-O table calculated by Iranian Statistical Center for year 2011 and second, Hydrocarbon Balance Sheet of year 2011. Our main results are presented based on two scenarios. In the first scenario, production technology is identical between Iran and other countries, and in the second scenario production technology isn’t the same. Our results based on two scenarios show that in macro level Iranian economy has trade surplus in fossil fuels content. But in sectoral level, 23 and 18 economic sectors have trade deficit in energy content based on first and second scenarios respectively. Ecological footprint based on our first scenario is more than 191 million hectares and the deficit per person is 2.3 hectare. In the second scenario the ecological footprint is 184 million hectares and the deficit per person is 2.2 hectares. Our conclusion is that because of low level of energy productivity in Iran, the results of second scenario are more realistic

Investigating the Efficiency of Combined Cycle Power Plants with the Data Envelopment Analysis Process (with an Emphasis on Air Pollution)

Performance management is one of the most significant strategies in promoting the efficiency of organizations and is highly sensitive. It is important to check the efficiency of combined cycle power plants because of their major contribution to power generation and air pollution. This study was conducted to evaluate the economic and environmental efficiency of Combined Cycle Power Plants (CCPPs). The inputs and outputs required to evaluate the performance of the power plants were determined according to expert opinions. Then, the 7-year statistics and information of the Qom, Neishabour, Shahid Rajaee, Yazd and Kerman power plants were collected as the desired CCPPs in Iran. The Window Data Envelopment Analysis (WDEA) method was used for evaluating the efficiency of the power plants. The 3-year window length showed that most of the power plants were efficient. Only the Rajaee, Neishabour and Yazd power plants were ineffective in some years. The mean efficiency of the power plants in the 4-year window length showed that the plants were efficient from 2008 to 2010

Porcine synapsin 1: SYN1 gene analysis and functional characterization of the promoter

AbstractSynapsin 1 (SYN1) is a phosphoprotein involved in nerve signal transmission. The porcine SYN1 promoter orthologue was cloned and characterized to provide a means of expressing a transgene specifically in neurons. The nucleotide sequence of the promoter displayed a high degree of conservation of elements responsible for neuron-specific expression. Expression analysis of SYN1 demonstrated presence of transcript during embryonic development. Analysis of GFP expression in transgenic zebrafish embryos suggests that the pig SYN1 promoter directs expression in neuronal cells. Thus, the SYN1 promoter is a good candidate for use in the generation of pig models of human neurodegenerative disorders

Molecular Cloning and Characterization of Porcine Na⁺/K⁺-ATPase Isoforms α1, α2, α3 and the ATP1A3 Promoter

<div><p>Na⁺/K⁺-ATPase maintains electrochemical gradients of Na⁺ and K⁺ essential for a variety of cellular functions including neuronal activity. The α-subunit of the Na⁺/K⁺-ATPase exists in four different isoforms (α1–α4) encoded by different genes. With a view to future use of pig as an animal model in studies of human diseases caused by Na⁺/K⁺-ATPase mutations, we have determined the porcine coding sequences of the α1–α3 genes, <i>ATP1A1</i>, <i>ATP1A2</i>, and <i>ATP1A3</i>, their chromosomal localization, and expression patterns. Our <i>ATP1A1</i> sequence accords with the sequences from several species at five positions where the amino acid residue of the previously published porcine <i>ATP1A1</i> sequence differs. These corrections include replacement of glutamine 841 with arginine. Analysis of the functional consequences of substitution of the arginine revealed its importance for Na⁺ binding, which can be explained by interaction of the arginine with the C-terminus, stabilizing one of the Na⁺ sites. Quantitative real-time PCR expression analyses of porcine <i>ATP1A1</i>, <i>ATP1A2</i>, and <i>ATP1A3</i> mRNA showed that all three transcripts are expressed in the embryonic brain as early as 60 days of gestation. Expression of α3 is confined to neuronal tissue. Generally, the expression patterns of <i>ATP1A1</i>, <i>ATP1A2</i>, and <i>ATP1A3</i> transcripts were found similar to their human counterparts, except for lack of α3 expression in porcine heart. These expression patterns were confirmed at the protein level. We also report the sequence of the porcine <i>ATP1A3</i> promoter, which was found to be closely homologous to its human counterpart. The function and specificity of the porcine <i>ATP1A3</i> promoter was analyzed in transgenic zebrafish, demonstrating that it is active and drives expression in embryonic brain and spinal cord. The results of the present study provide a sound basis for employing the <i>ATP1A3</i> promoter in attempts to generate transgenic porcine models of neurological diseases caused by <i>ATP1A3</i> mutations.</p></div

Population Structure and Diversity in European Honey Bees (Apis mellifera L.)&mdash;An Empirical Comparison of Pool and Individual Whole-Genome Sequencing

Background: Whole-genome sequencing has become routine for population genetic studies. Sequencing of individuals provides maximal data but is rather expensive and fewer samples can be studied. In contrast, sequencing a pool of samples (pool-seq) can provide sufficient data, while presenting less of an economic challenge. Few studies have compared the two approaches to infer population genetic structure and diversity in real datasets. Here, we apply individual sequencing (ind-seq) and pool-seq to the study of Western honey bees (Apis mellifera). Methods: We collected honey bee workers that belonged to 14 populations, including 13 subspecies, totaling 1347 colonies, who were individually (139 individuals) and pool-sequenced (14 pools). We compared allele frequencies, genetic diversity estimates, and population structure as inferred by the two approaches. Results: Pool-seq and ind-seq revealed near identical population structure and genetic diversities, albeit at different costs. While pool-seq provides genome-wide polymorphism data at considerably lower costs, ind-seq can provide additional information, including the identification of population substructures, hybridization, or individual outliers. Conclusions: If costs are not the limiting factor, we recommend using ind-seq, as population genetic structure can be inferred similarly well, with the advantage gained from individual genetic information. Not least, it also significantly reduces the effort required for the collection of numerous samples and their further processing in the laboratory