SNV calls for GIAB data at simulated contamination levels.

<p>BWA alignments were used to generate filtered SNV lists for GATK, Isaac variant caller, and SAMtools at simulated contamination levels of 0%, 25%, 50%, 75%, 90%, 95%, 98%, and 99%. Variant lists were overlapped to GIAB high quality variants to determine false positive and false negative rates.</p><p>^<b>a</b>From bases overlap ENSEMBL v75 canonical transcripts.</p><p>SNV calls for GIAB data at simulated contamination levels.</p

Total insertion calls and tool-specific insertion calls for each aligner and variant caller run with and without filtering.

<p>The union of variant calls for each tool was calculated and false positive and false negative rates determined relative to high quality GIAB variants. Tool-specific calls were also calculated, defined as insertions specific to a single tool.</p><p>^<b>a</b>From bases overlap ENSEMBL v75 canonical transcripts.</p><p>Total insertion calls and tool-specific insertion calls for each aligner and variant caller run with and without filtering.</p

Total deletion calls and tool-specific deletion calls for each aligner and variant caller run with and without filtering.

<p>The union of variant calls for each tool was calculated and false positive and false negative rates determined relative to high quality GIAB variants. Tool-specific calls were also calculated, defined as deletions specific to a single tool.</p><p>^<b>a</b>From bases overlap ENSEMBL v75 canonical transcripts.</p><p>Total deletion calls and tool-specific deletion calls for each aligner and variant caller run with and without filtering.</p

Variant calls grouped by frequency of detection.

<p>Unfiltered variants were grouped based on the frequency of detection within nine possible aligner/variant caller pairs and segregated into four bins; variants in all 9 pairs, variants in at least 1 pair, variants in 2–8 pairs, and variants unique to 1 pair.</p><p>^<b>a</b>From bases overlap ENSEMBL v75 canonical transcripts.</p><p>Variant calls grouped by frequency of detection.</p

Total SNV calls and tool-specific SNV calls for each aligner and variant caller run with and without filtering.

<p>The union of variant calls for each tool was calculated and false positive and false negative rates determined relative to high quality GIAB variants. Tool-specific calls were also calculated, defined as SNVs specific to a single tool.</p><p>^<b>a</b>From bases overlap ENSEMBL v75 canonical transcripts.</p><p>Total SNV calls and tool-specific SNV calls for each aligner and variant caller run with and without filtering.</p

Analysis Workflow.

<p>BAM files from BWA, Isaac aligner, and Bowtie2 were paired with each of GATK, Isaac variant caller, and SAMTools run both with and without additional filtering (VQSR, BAQ, and LowGQX respectively). Output vcf files were regularized using custom code and variants from GIAB high quality regions taken forward to generate false positive and false negative rates.</p

Software concordance ROC curves.

<p>Merged variant calls for each tool were calculated and ROC curves generated using the genome quality score. Aligners are compared in row 1, variant callers without filtering in row 2, and variant callers with filtering in row 3.</p

Interplay of dFOXO and Two ETS-Family Transcription Factors Determines Lifespan in <i>Drosophila melanogaster</i>

<div><p>Forkhead box O (FoxO) transcription factors (TFs) are key drivers of complex transcriptional programmes that determine animal lifespan. FoxOs regulate a number of other TFs, but how these TFs in turn might mediate the anti-ageing programmes orchestrated by FoxOs <i>in vivo</i> is unclear. Here, we identify an E-twenty six (ETS)-family transcriptional repressor, <i>Anterior open</i> (<i>Aop</i>), as regulated by the single <i>Drosophila melanogaster</i> FoxO (dFOXO) in the adult gut. AOP, the functional orthologue of the human Etv6/Tel protein, binds numerous genomic sites also occupied by dFOXO and counteracts the activity of an ETS activator, <i>Pointed</i> (<i>Pnt</i>), to prevent the lifespan-shortening effects of co-activation of dFOXO and PNT. This detrimental synergistic effect of dFOXO and PNT appears to stem from a mis-regulation of lipid metabolism. At the same time, AOP activity in another fly organ, the fat body, has further beneficial roles, regulating genes in common with <i>dfoxo</i>, such as the secreted, non-sensory, odorant binding protein (<i>Obp99b</i>), and robustly extending lifespan. Our study reveals a complex interplay between evolutionarily conserved ETS factors and dFOXO, the functional significance of which may extend well beyond animal lifespan.</p></div

dFOXO regulates expression of <i>Aop</i> in the adult gut.

<p><b>A</b> Schematic of the <i>Aop</i> locus with black boxes representing exons, red boxes – regions detected as bound by GFP-dFOXO in the ChIP-chip experiment on induced <i>S₁106>GFP-dfoxo</i> females (dFOXO gut/fat body), yellow box - region detected as bound by dFOXO in wild-type females (dFOXO whole fly, data obtained from reference <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004619#pgen.1004619-Alic2" target="_blank">[17]</a>), and black bars – position of amplicons used for qPCR in B. <b>B</b> The enrichment of 5′ or 3′ end of the <i>Aop</i> locus, relative to <i>U6</i>, after anti-GFP IP of chromatin from RU486-induced <i>S₁106>dfoxo</i> females (mock), anti-GFP IP of chromatin from RU486-induced <i>S₁106>GFP-dfoxo</i> females (gut/fat body) or anti-dFOXO IP of wild-type female chromatin (whole fly). Means ± SEM of three biological repeats are shown, with enrichment in the mock control set to one. ANOVA on log-transformed data detected significant differences (p = 0.03 per region) and the enrichment of the 5′ region was different in gut/fat body from the mock (one-tailed t-test, p = 6×10⁻³), while the 3′ region was enriched in the whole fly (one-tailed t-test, p = 5×10⁻³). <b>C</b><i>Aop</i> mRNA was quantified relative to <i>Act</i> by qPCR in guts or fat bodies of <i>S₁106>dfoxo</i>, or <i>TIGS>dfoxo</i> flies induced or not with RU486. Boxplots show log-10 derived relative expression with - RU486 values set to zero. Data for <i>S₁106>dfoxo</i> females were analysed with a mixed-effects linear model with dissection batch as a random effect. The effects of RU486, tissue and their interaction was significant (p<0.05) and RU486 caused significant up-regulation of <i>Aop</i> in the gut (one-tailed t-test, n = 3–4, p = 2×10⁻³) but not the fat body (one-tailed t-test, n = 4, p>0.05). Significant changes were observed in <i>TIGS>dfoxo</i> guts (t-test, n>3, p = 0.02).</p

dFOXO targets in the adult gut and fat body.

<p><b>A</b> Proportional Venn diagram showing the sets of genes that were differentially regulated by <i>dfoxo</i> induction in the gut or the fat body. The number of genes that were bound by GFP-dFOXO within each differentially expressed-gene set are given in black. p values for significant set overlaps are indicated. <b>B</b> Biological process GO categories differentially regulated (p<10⁻¹⁰) in the fat body or gut upon induction of <i>dfoxo</i> as determined by Catmap analysis. Any redundant categories (overlap by more than 75%) were removed, retaining the most specific category. The full list is given in <b><a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004619#pgen.1004619.s010" target="_blank">Dataset S1</a></b>. The intensity of red shows the log₁₀-transformed p-value associated with differential regulation for each category.</p