DNA damage defines sites of recurrent chromosomal translocations in B lymphocytes

Abstract

Recurrent chromosomal translocations underlie both haematopoietic and solid tumours. Their origin has been ascribed to selection of random rearrangements, targeted DNA damage, or frequent nuclear interactions between translocation partners; however, the relative contribution of each of these elements has not been measured directly or on a large scale. Here we examine the role of nuclear architecture and frequency of DNA damage in the genesis of chromosomal translocations by measuring these parameters simultaneously in cultured mouse B lymphocytes. In the absence of recurrent DNA damage, translocations between Igh or Myc and all other genes are directly related to their contact frequency. Conversely, translocations associated with recurrent site-directed DNA damage are proportional to the rate of DNA break formation, as measured by replication protein A accumulation at the site of damage. Thus, non-targeted rearrangements reflect nuclear organization whereas DNA break formation governs the location and frequency of recurrent translocations, including those driving B-cell malignancies.

Figure 1. Characterization of the Igh, Myc and Mycn interactomes in B lymphocytes

a, Genome-wide interaction profile of Igh 3′Eα, Myc and Mycn in activated B cells. Plots show the percentage of HindIII fragments carrying 4C-seq reads. b, Contact frequency of Igh with chromosome 5 in activated B cells (lane 1), anti-HEL homozygous activated B cells (lane 2), or resting B cells (lane 3). Histone acetylation (lane 4), RNA Pol II (lane 6) and mRNA (lane 7) density is also shown. Lanes 5 and 8 show Myc and Mycn contacts, respectively. Lane 9 represents Igh contacts in MEFs. c, Comparison of Pol II and Igh 4C-seq data per chromosome normalized as reads per mappable megabase.

Figure 2. Genomic distribution of AID-independent translocations correlates with nuclear contact profiles

a, Genome-wide view of rearrangements to Igh^I-SceI in Aid^−/− B cells. b, Cross-comparison of contacts and translocations between Myc or Igh and mouse chromosome 17 in activated Aid^−/− B cells. c, Empirical cumulative distribution showing Igh^I-SceI Aid^−/− translocations per 200-kb non-overlapping windows as a function of Igh 4C-seq data subdivided as quartiles (Q1–4). NI represents windows with no aligned reads. d, Comparison of AID-independent translocations versus Igh 4C-seq per chromosome per mappable megabase. The degree of correlation is represented by Pearson’s r.

Figure 3. Lack of correlation between translocation hotspots and nuclear architecture

a, Genome-wide hotspots in activated B cells transduced with I-SceI and AID retroviruses (rv). b, Translocation hotspots (bottom lane) and Myc and Igh contacts in chromosome 8. c, Igh contacts with RefSeq genes. Hotspot⁺ genes are highlighted in red, and for a subset of them the number of translocations is provided in parentheses. The two hotspot⁻ genes (Rplp2 and Rac2) highlighted in blue are discussed in more detailed in panel e. d, Scatter plot showing Igh translocations per hotspot versus contacts. Data are plotted as sequence tags per kb per million sequences (t.p.k.m.). e, Line graph showing the 4C-seq correlation (Spearman’s ρ) between Igh (in various cell types), Rpbp2, Rac2, Myc and Mycn (in activated B cells) versus Igh in activated B cells. The 99% bootstrapping confidence intervals are shown in grey.

Figure 4. Genome-wide map of AID-mediated DNA damage

a, RPA occupancy at Igh in activated B cells. Genotype and RPA sequence reads per million values are shown. b, Same analysis as in panel a for Cd83. For all tracks, background sequencing was filtered out via a threshold. c, One-hundred and fifty-three RPA islands (red dots) detected in IgκAID 53BP1^−/− B cells fourfold above background (measured in Aid^−/−53BP1^−/− cells). Data are plotted as reads per kb per million sequences (r.p.k.m.). d, RPA islands associated with TSSs from Pax5, Pim1 and Mir155. e, Hypermutation frequency relative to RPA recruitment at TSSs (±2 kb) in a subset of RPA⁺ (red dots) and RPA⁻ (blue dots) genes. Spearman’s ρ is provided.

Figure 5. AID activity predicts the location and frequency of targeted chromosomal translocations

a, Scatter plot showing the correlation between Igh translocations per hotspot and RPA recruitment. b, Same as panel a but Igh contact frequency is used instead of translocations. c, Upper schematic: distribution of RPA islands (red dots) and translocation hotspots (blue dots) in chromosome 7. Middle: Igh 4C-seq profile demarcating the Nsmce1-Il4ra-Il21r loci. Bottom: RPA islands, translocations and contact frequency for each gene.