DOI: 10.5061/dryad.8gtht76n0
title: A novel method for using RNA-seq data to identify imprinted genes in social Hymenoptera with multiply mated queens

description: Genomic imprinting results in parent-of-origin dependent gene expression
 biased towards either the maternally- or paternally-derived allele at the
 imprinted locus. The kinship theory of genomic imprinting argues that this
 unusual expression pattern is a manifestation of intra-genomic conflict
 between the maternally- and paternally-derived halves of the genome that
 arises because they are not equally related to the genomes of social
 partners. The theory thus predicts that imprinting may evolve wherever
 there are close interactions among asymmetrically related kin. The social
 Hymenoptera with permanent caste differentiation are suitable candidates
 for testing the kinship theory because haplodiploid sex determination
 creates strong relatedness asymmetries and nursing workers interact
 closely with kin. However, progress in the search for imprinted genes in
 the social Hymenoptera has been slow, in part because tests for imprinting
 rely on reciprocal crosses that are impossible in most species. Here, we
 develop a method to systematically search for imprinting in haplodiploid
 social insects without crosses, using instead samples of pooled
 individuals collected from natural colonies. We tested this protocol using
 data available for the leaf-cutting ant Acromyrmex echinatior, providing
 the first genome-wide search for imprinting in any ant. While we
 identified several genes as potentially imprinted, none of the four genes
 tested could be verified as imprinted using digital droplet PCR,
 highlighting the need for higher quality genomic assemblies that
 accurately map duplicated genes.
description: Detailed information regarding data collection can be found in
 the manuscript, and a detailed description of each data file is included
 in the README.txt, but are summarised briefly here:
 <b>ASE_data_frame.csv: </b>gives the output of the
 bioinformatics pipeline run by Qiye Li and Zongji Wang. In short, they
 used the data published in Li et al 2014, aligned reads using a
 Burrows-Wheeler aligner, followed by BLAT. SNPs were then identified using
 RES-Scanner in both DNA and RNA, and the numbers of reads supporting each
 SNP-allele recorded. Fisher's exact tests were conducted for each SNP
 to test for differences in the ratio of alleles between DNA and RNA at the
 same locus. This file records those SNPs that showed significant
 differences between DNA and RNA, and gives the number of reads supporting
 each allele for each sample, as well as information for each gene. SNPs
 that could not be placed within an annotated gene were not included. The
 raw data can be downloaded with the original article at the NCBI GEO
 accession GSE51576. For questions regarding the bioinformatics steps
 preceeding this table, contact QL or ZW. 
 <strong>Compiled_ddPCR_results.csv: </strong>gives
 the data output from the ddPCR experiments. Including the number of
 droplets that were positive for both alleles, positive for only one
 allele, and negative droplets. This was used to calculate the relative
 proportion of the focal allele, and the poisson distributed confidence
 intervals around this estimate are also given (as templates will show a
 poisson distribution among droplets). 
 <b>dilution_data.csv: </b>also gives ddPCR data. This
 data shows the output from the tests of the relative concentration of
 different genes following serial dilution. The Sample column gives the
 relative dilution levels (1 to 0.016)
description: See README.txt for description of the data, files and script
 uploaded.  In short, there are three data files
 uploaded in input_data (one for the allele-specific expression:
 ASE_data_frame.csv, one for the ddPCR allele-specific
 PCR: compiled_ddPCR_results.csv, and one for the copy number dilution
 assay: dilution_data.csv). There is one RMarkdown script
 (Howe_et_al_RScript.Rmd), which conducts all analyses, relying on only
 basic R packages that must be installed.  Some
 intermediate data-values are missing from the ddPCR file (ie. the absolute
 number of droplets for each channel) due to a recording error. The
 fraction and confidence intervals are reported however.