Genomic Variation and Its Impact on Gene Expression in Drosophila melanogaster

Understanding the relationship between genetic and phenotypic variation is one of the great outstanding challenges in biology. To meet this challenge, comprehensive genomic variation maps of human as well as of model organism populations are required. Here, we present a nucleotide resolution catalog of single-nucleotide, multi-nucleotide, and structural variants in 39 Drosophila melanogaster Genetic Reference Panel inbred lines. Using an integrative, local assembly-based approach for variant discovery, we identify more than 3.6 million distinct variants, among which were more than 800,000 unique insertions, deletions (indels), and complex variants (1 to 6,000 bp). While the SNP density is higher near other variants, we find that variants themselves are not mutagenic, nor are regions with high variant density particularly mutation-prone. Rather, our data suggest that the elevated SNP density around variants is mainly due to population-level processes. We also provide insights into the regulatory architecture of gene expression variation in adult flies by mapping cis-expression quantitative trait loci (cis-eQTLs) for more than 2,000 genes. Indels comprise around 10% of all cis-eQTLs and show larger effects than SNP cis-eQTLs. In addition, we identified two-fold more gene associations in males as compared to females and found that most cis-eQTLs are sex-specific, revealing a partial decoupling of the genomic architecture between the sexes as well as the importance of genetic factors in mediating sex-biased gene expression. Finally, we performed RNA-seq-based allelic expression imbalance analyses in the offspring of crosses between sequenced lines, which revealed that the majority of strong cis-eQTLs can be validated in heterozygous individuals

A yeast one-hybrid and microfluidics-based pipeline to map mammalian gene regulatory networks

The comprehensive mapping of gene promoters and enhancers has significantly improved our understanding of how the mammalian regulatory genome is organized. An important challenge is to elucidate how these regulatory elements contribute to gene expression by identifying their trans-regulatory inputs. Here, we present the generation of a mouse-specific transcription factor (TF) open-reading frame clone library and its implementation in yeast one-hybrid assays to enable large-scale protein–DNA interaction detection with mouse regulatory elements. Once specific interactions are identified, we then use a microfluidics-based method to validate and precisely map them within the respective DNA sequences. Using well-described regulatory elements as well as orphan enhancers, we show that this cross-platform pipeline characterizes known and uncovers many novel TF–DNA interactions. In addition, we provide evidence that several of these novel interactions are relevant in vivo and aid in elucidating the regulatory architecture of enhancers

Table S2 - RNASeq_ZEB1_KD

Effect of ZEB1 knockdown on global gene expression in 3T3-L1 cells as measured at days 0 and 2

Genomic variation and its impact on gene expression in Drosophila melanogaster

Understanding the relationship between genetic and phenotypic variation is one of the great outstanding challenges in biology. To meet this challenge, comprehensive genomic variation maps of human as well as of model organism populations are required. Here, we present a nucleotide resolution catalog of single-nucleotide, multi-nucleotide, and structural variants in 39 Drosophila melanogaster Genetic Reference Panel inbred lines. Using an integrative, local assembly-based approach for variant discovery, we identify more than 3.6 million distinct variants, among which were more than 800,000 unique insertions, deletions (indels), and complex variants (1 to 6,000 bp). While the SNP density is higher near other variants, we find that variants themselves are not mutagenic, nor are regions with high variant density particularly mutation-prone. Rather, our data suggest that the elevated SNP density around variants is mainly due to population-level processes. We also provide insights into the regulatory architecture of gene expression variation in adult flies by mapping cis-expression quantitative trait loci (cis-eQTLs) for more than 2,000 genes. Indels comprise around 10% of all cis-eQTLs and show larger effects than SNP cis-eQTLs. In addition, we identified two-fold more gene associations in males as compared to females and found that most cis-eQTLs are sex-specific, revealing a partial decoupling of the genomic architecture between the sexes as well as the importance of genetic factors in mediating sex-biased gene expression. Finally, we performed RNA-seq-based allelic expression imbalance analyses in the offspring of crosses between sequenced lines, which revealed that the majority of strong cis-eQTLs can be validated in heterozygous individuals

Data from: Identification of ZEB1 as a central component of the adipogenic gene regulatory network

Adipose tissue is a key determinant of whole body metabolism and energy homeostasis. Unraveling the regulatory mechanisms underlying adipogenesis is therefore highly relevant from a biomedical perspective. Our current understanding of fat cell differentiation is centered on the transcriptional cascades driven by the C/EBP protein family and the master regulator PPARγ. To elucidate further components of the adipogenic gene regulatory network, we performed a large-scale transcription factor (TF) screen overexpressing 734 TFs in mouse pre-adipocytes and probed their effect on differentiation. We identified 23 novel pro-adipogenic TFs and characterized the top ranking TF, ZEB1, as being essential for adipogenesis both in vitro and in vivo. Moreover, its expression levels correlate with fat cell differentiation potential in humans. Genomic profiling further revealed that this TF directly targets and controls the expression of most early and late adipogenic regulators, identifying ZEB1 as a central transcriptional component of fat cell differentiation

Table S1 - TF_screen

Percentage differentiated 3T3-L1 cells in response to transcription factor overexpression

Examples of <i>cis-</i>eQTLs and their associated genes.

<p>DGRP lines in (A) and (B) are grouped by their allele. Male and female expression levels are depicted in blue and dark pink, respectively. (A) Sex-biased <i>cis</i>-eQTL. A SNP (3R:8,875,391) is associated with higher gene expression levels in females only. (B) Indel-based <i>cis</i>-eQTLs associated with gene expression. Two insertions (7 bp, 3L:332,512; 1 bp, 3L:332,594, r² = 0.20) are associated with markedly different expression levels in males and females. (C) <i>cis</i>-association overview. Plot illustrating the variant and association data for a single gene (<i>mthl9</i>) on a rolling window basis. The gene is shown on the top track, with UTRs in grey and coding regions in black. Significant <i>cis</i>-eQTLs are drawn below and color-coded by significance for each sex separately (red most significant). Linkage (r²>0.5) is shown by arcs, color-coded according to r², with higher values in red. Rows represent all 39 DGRP lines and the left column shows gene expression levels for each line and sex separately (red indicates the highest expression level and green the lowest). The grid contains a representation of variants in rolling 50 bp windows (successive windows overlapping by 45 bp) with net insertions in red, net deletions in blue, and variants not affecting the sequence size (mostly SNPs) in black. The height of each variant indicates the net size of variants with the window, up to 20 bp. The two shaded vertical bars mark the <i>cis</i>-eQTLs shown in (B).</p

Validation of <i>cis</i>-associations in F1.

<p>(A) Allelic imbalance measured for ∼7,100 transcripts in F1 (362/765 and reciprocal) with RNA-seq. Dots represent the fold-change (log2) between allele-specific reads counts. Red dots indicate transcripts with significant allelic imbalance in both crosses at a false discovery rate of 10%. Circles mark transcripts that demonstrate significant allelic imbalance and that were found to be associated with <i>cis</i>-eQTL in females (note that only <i>cis</i>-eQTLs were considered when the allele between both parental lines was not the same). (B) The proportion of <i>cis</i>-eQTL-associated transcripts that show allelic expression imbalance in F1s scales with the strength of the <i>cis</i>-eQTL (P<0.001, permutation-based, see Methods for details).</p

<i>Cis-</i>associations of variants with gene expression.

<p>(A) and (B) Variant density (blue) and significance of allele associations (red), in males around (A) the transcription start site (TSS) and (B) the transcription end site (TES) averaged out over all transcripts in a 10 kb window. The solid lines are cubic smoothing splines, fit to the data. Transcripts on both strands are orientated such that transcription takes place in the positive direction of the x-axis. The inlet in (A) corresponds to a 100 kb window length. (C) <i>cis-</i>eQTLs discovered in males, females, or both sexes (FDR<10%). (D) Breakdown of <i>cis-</i>eQTL-associated genes by sex. (E) Breakdown of <i>cis</i>-eQTL associated genes, discovered in males or females, by type of variant (<i>i.e.</i>, SNP and non-SNP).</p

Overview of variants.

<p>SNPs are shown in black/grey, insertions in red, deletions in blue, and complex variants in orange. (A) Number of base pairs affected by variants discovered per line, with lines ordered by depth of coverage (green dotted line). The line “Berkeley” is the reference line. (B) Number of unique variants by size (note that variants longer than 1,000 bp are grouped in a single x-coordinate). (C) Representation of variant density (0–10 SNPs/kb, 0–5 indels/kb, 0–5 complex variants/kb) across the euchromatic genome (concentric circles) in 50 kb bins. Large variants (>100 bp) mapping against a close homologous sequence (>90% sequence identify) are linked in the center with green lines representing intra-chromosomal- and black lines inter-chromosomal duplications. (D) Number of unique variants by number of lines.</p