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      Unique DNA Methylation Profiles Are Associated with cis-Variation in Honey Bees

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          DNA methylation is an important epigenetic modification that mediates diverse processes such as cellular differentiation, phenotypic plasticity, and genomic imprinting. Mounting evidence suggests that local DNA sequence variation can be associated with particular DNA methylation states, indicating that the interplay between genetic and epigenetic factors may contribute synergistically to the phenotypic complexity of organisms. Social insects such as ants, bees, and wasps have extensive phenotypic plasticity manifested in their different castes, and this plasticity has been associated with variation in DNA methylation. Yet, the influence of genetic variation on DNA methylation state remains mostly unknown. Here we examine the importance of sequence-specific methylation at the genome-wide level, using whole-genome bisulfite sequencing of the semen of individual honey bee males. We find that individual males harbor unique DNA methylation patterns in their semen, and that genes that are more variable at the epigenetic level are also more likely to be variable at the genetic level. DNA sequence variation can affect DNA methylation by modifying CG sites directly, but can also be associated with local variation in cis that is not CG-site specific. We show that covariation in sequence polymorphism and DNA methylation state contributes to the individual-specificity of epigenetic marks in social insects, which likely promotes their retention across generations, and their capacity to influence evolutionary adaptation.

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          Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

          DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
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            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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              Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data

              Summary: The two main functions of bioinformatics are the organization and analysis of biological data using computational resources. Geneious Basic has been designed to be an easy-to-use and flexible desktop software application framework for the organization and analysis of biological data, with a focus on molecular sequences and related data types. It integrates numerous industry-standard discovery analysis tools, with interactive visualizations to generate publication-ready images. One key contribution to researchers in the life sciences is the Geneious public application programming interface (API) that affords the ability to leverage the existing framework of the Geneious Basic software platform for virtually unlimited extension and customization. The result is an increase in the speed and quality of development of computation tools for the life sciences, due to the functionality and graphical user interface available to the developer through the public API. Geneious Basic represents an ideal platform for the bioinformatics community to leverage existing components and to integrate their own specific requirements for the discovery, analysis and visualization of biological data. Availability and implementation: Binaries and public API freely available for download at, implemented in Java and supported on Linux, Apple OSX and MS Windows. The software is also available from the Bio-Linux package repository at Contact:

                Author and article information

                Role: Associate Editor
                Genome Biol Evol
                Genome Biol Evol
                Genome Biology and Evolution
                Oxford University Press
                September 2019
                12 August 2019
                12 August 2019
                : 11
                : 9
                : 2517-2530
                Behaviour and Genetics of Social Insects Laboratory, School of Life and Environmental Sciences, University of Sydney , Australia
                Author notes
                Corresponding author: E-mail: boris.yagound@ .
                © The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (, which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact

                Pages: 14
                Funded by: Australian Research Council 10.13039/501100000923
                Award ID: DP150100151
                Funded by: School of Life and Environmental Sciences
                Funded by: University of Sydney, the Fyssen Foundation
                Funded by: Hermon Slade Foundation
                Award ID: HSF1801
                Funded by: Westmead Research Hub
                Funded by: Westmead Institute for Medical Research
                Funded by: Cancer Institute New South Wales 10.13039/501100001171
                Funded by: National Health and Medical Research Council 10.13039/501100000925
                Funded by: Ian Potter Foundation 10.13039/501100001047
                Research Article


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