Identification of a genomic enhancer that enforces proper apoptosis induction in thymic negative selection

During thymic negative selection, autoreactive thymocytes carrying T cell receptor (TCR) with overtly strong affinity to self-MHC/self-peptide are removed by Bim-dependent apoptosis, but how Bim is specifically regulated to link TCR activation and apoptosis induction is unclear. Here we identify a murine T cell-specific genomic enhancer EBAB (Bub1-Acoxl-Bim), whose deletion leads to accumulation of thymocytes expressing high affinity TCRs. Consistently, EBAB knockout mice have defective negative selection and fail to delete autoreactive thymocytes in various settings, with this defect accompanied by reduced Bim expression and apoptosis induction. By contrast, EBAB is dispensable for maintaining peripheral T cell homeostasis via Bim-dependent pathways. Our data thus implicate EBAB as an important, developmental stage-specific regulator of Bim expression and apoptosis induction to enforce thymic negative selection and suppress autoimmunity. Our study unravels a part of genomic enhancer codes that underlie complex and context-dependent gene regulation in TCR signaling.


Statistics
For all statistical analyses, confirm that the following items are present in the figure legend, table legend, main text, or Methods section.

n/a Confirmed
The exact sample size (n) for each experimental group/condition, given as a discrete number and unit of measurement A statement on whether measurements were taken from distinct samples or whether the same sample was measured repeatedly The statistical test(s) used AND whether they are one-or two-sided Only common tests should be described solely by name; describe more complex techniques in the Methods section.
A description of all covariates tested A description of any assumptions or corrections, such as tests of normality and adjustment for multiple comparisons A full description of the statistical parameters including central tendency (e.g. means) or other basic estimates (e.g. regression coefficient) AND variation (e.g. standard deviation) or associated estimates of uncertainty (e.g. confidence intervals) For null hypothesis testing, the test statistic (e.g. F, t, r) with confidence intervals, effect sizes, degrees of freedom and P value noted Give P values as exact values whenever suitable.

For Bayesian analysis, information on the choice of priors and Markov chain Monte Carlo settings
For hierarchical and complex designs, identification of the appropriate level for tests and full reporting of outcomes Estimates of effect sizes (e.g. Cohen's d, Pearson's r), indicating how they were calculated Our web collection on statistics for biologists contains articles on many of the points above.

Software and code
Policy information about availability of computer code Data collection Flow cytometry data were collected with EC800 analyzer analysis software and BD FACS Diva. RNA-seq data were obtained by Illumina Hiseq platform.

Data analysis
For flow cytometry analysis, EC800 analyzer analysis software, BD FACS Diva and FlowJo (V. 10) were used. For other data analyses, microsoft excel and graphpad PRISM were used.
For manuscripts utilizing custom algorithms or software that are central to the research but not yet described in published literature, software must be made available to editors/reviewers. We strongly encourage code deposition in a community repository (e.g. GitHub). See the Nature Research guidelines for submitting code & software for further information.

Data
Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: -Accession codes, unique identifiers, or web links for publicly available datasets -A list of figures that have associated raw data -A description of any restrictions on data availability RNA-seq data that support the findings of this study have been deposited in DNA Data Bank of Japan (DDBJ) with the accession code DRA004726 and DRA008123.

nature research | reporting summary
October 2018 Field-specific reporting Please select the one below that is the best fit for your research. If you are not sure, read the appropriate sections before making your selection.

Life sciences Behavioural & social sciences Ecological, evolutionary & environmental sciences
For a reference copy of the document with all sections, see nature.com/documents/nr-reporting-summary-flat.pdf

Life sciences study design
All studies must disclose on these points even when the disclosure is negative.

Sample size
The sample size was chosen as follows. First, the number of animals was minimized as much as possible in light of animal ethics. Second, against effect size estimated in each experiment, ≥ 80%-90% power was favored. Third, in most cases, n = 5 was set as a threshold according to the previous report (Krzywinski, M. & Altman, N. Points of significance: Comparing samples-part I. Nat Methods 11, 215-216 (2014)). These three criterion functioned to determine the sample size as n = 5-8 in most experiments. Moreover, dot-plot representation of data provided insights into how the samples were distributed, and thus into the extent of difference of two groups. This, in the specific cases, led us to conclude that relatively small number of animals (i.e. less than 5 animals) was enough to support our conclusion.
Data exclusions No data exclusions were performed.

Replication
All experiments have been performed several times using multiple mice. Different methods, transgenic mice models, and ex vivo systems, were used to support our findings together.
Randomization All experiments were performed without randomization. In most cases, e.g. a KO mouse was analyzed with its littermate, and/or sex-matched control, side-by-side on the same day.

Blinding
Blinding was performed in the injection process of OT-II negative selection assay. In other experiments, blinding was not done.

Reporting for specific materials, systems and methods
We require information from authors about some types of materials, experimental systems and methods used in many studies. Here, indicate whether each material, system or method listed is relevant to your study. If you are not sure if a list item applies to your research, read the appropriate section before selecting a response.

Ethics oversight
All animal protocols were approved by the Animal Care and Use committee of Advanced Telecommunications Research Institute International (permission numbers: AN20140002, AN20150002, AN20160002, AN20170002, and AN20180002) and by the committee of Kyoto university (permission numbers: L18-1, L18-1-2, and L19-2).
Note that full information on the approval of the study protocol must also be provided in the manuscript.

Flow Cytometry
Plots Confirm that: The axis labels state the marker and fluorochrome used (e.g. CD4-FITC).
The axis scales are clearly visible. Include numbers along axes only for bottom left plot of group (a 'group' is an analysis of identical markers).
All plots are contour plots with outliers or pseudocolor plots.
A numerical value for number of cells or percentage (with statistics) is provided.

Sample preparation
The thymus and spleen harvested from mice were cut into several smaller pieces in a petri dish containing RPMI1640 medium. The obtained pieces were homogenized using a slide glass, or 100um cell strainer and plunger of 1mL syringe, and single cell suspension was obtained. Single cell suspension was collected into a tube and washed several times with fresh medium. For the spleen, erythrocytes were hemolyzed. After washing, large debris and cell clumps were removed from the sample using 70um cell strainer.

Software
Data were collected with EC800 analyzer analysis software and BD FACS Diva. Obtained data were analyzed using EC800 analyzer analysis software and FlowJo (V.10).
Cell population abundance Abundance of the relevant cell populations was ascertained by a post-sort purity check or qPCR experiments for surface marker genes such as CD69 against at least one representative sample. Post-sort fractions were 70-95 % depending on experiments as determined by a post-sort purity check. Regarding qPCR-based validations, for example, expression of CD69 in the sorted fraction was > 6 times higher than that in the negative fraction.

Gating strategy
The cells were gated on FSC/SSC basis on the location known to contain lymphoid cells. Unstained and control sample were used to determine the gates.
Tick this box to confirm that a figure exemplifying the gating strategy is provided in the Supplementary Information.