# QTL mapping (BXD mice) **TL;DR:** the BXD mice are inbred strains bred down from two parents, B6 and DBA/2, so each strain's genome is a mosaic of blocks from one or the other. We paint each strain by which parent gave it each block and stack that under a GeneNetwork QTL scan, so a trait peak sits over the blocks that drive it. ## Prerequisites - `curl`, to fetch GeneNetwork's QTL scan - `jq`, to reshape it - `python3`, for the painting - htslib (`bgzip`, `tabix`), for the painting - A JBrowse instance to add the tracks to (see the [web quickstart](https://jbrowse.org/jb2-staging/docs/quickstart_web), or the [desktop quickstart](https://jbrowse.org/jb2-staging/docs/quickstart_desktop) to add the built files with no hosting step) On Debian/Ubuntu, `apt install curl jq python3 tabix` covers it. The QTL scan is [downloaded already computed](#track-2-the-qtl-manhattan). ## Where the data comes from BXD consensus genotypes and QTL scans from GeneNetwork ([Wang et al. 2016](https://doi.org/10.1038/ncomms10464)). - the BXD consensus genotypes, 198 strains: https://gn1.genenetwork.org/genotypes/BXD.geno - the coat-color scan (trait 11280), from GeneNetwork's mapping API: https://genenetwork.org/api/v_pre1/mapping?db=BXDPublish&method=gemma&trait_id=11280 - the chromosome painting, rehosted for the track config: https://jbrowse.org/demos/bxd/bxd_painting.bed.gz ## The BXD panel The [BXD family](https://genenetwork.org) is a panel of ~200 mouse recombinant-inbred (RI) strains bred from a cross of C57BL/6J (the "B" parent) and DBA/2J (the "D" parent). Each strain's genome is a fixed pattern of B and D blocks, and the same strains have been phenotyped for thousands of traits at [GeneNetwork](https://genenetwork.org). This tutorial builds two JBrowse tracks from the same BXD panel, on mm10: - a chromosome-painting track (the [multi-row feature display](https://jbrowse.org/jb2-staging/docs/user_guides/multirow_feature_track)) showing each strain's B and D blocks, and - a QTL Manhattan track (the [Manhattan display](https://jbrowse.org/jb2-staging/docs/user_guides/gwas_track)) from a single-marker scan of a real BXD phenotype. The GWAS/Manhattan and multi-row feature tracks shown here also render inline through the [Python anywidget interface](https://jbrowse.org/jb2-staging/docs/jbrowse_anywidget) (or [](https://jbrowse.org/jb2-staging/docs/jbrowser) in R), so you can run the scan and view the peak in one Python or R session. ## The data: BXD consensus genotypes GeneNetwork distributes the consensus BXD genotypes as a plain-text `.geno` file. Each row is a marker (with a `cM` genetic-map and an mm10 `Mb` physical position, we use `Mb`). Each column is a strain, with a one-letter genotype, `B`, `D`, `H` (heterozygous) or `U` (unknown): ``` @name:BXD @mat:B @pat:D Chr Locus cM Mb BXD1 BXD2 BXD5 ... 1 rs31443144 0.11 3.010274 B B D ... 1 rs6269442 0.21 3.492195 B B D ... ``` Download it from [gn1.genenetwork.org/genotypes/BXD.geno](https://gn1.genenetwork.org/genotypes/BXD.geno) (please cite [Wang et al. 2016, _Nat Commun_ 7:10464](https://doi.org/10.1038/ncomms10464)). Its own header describes what the columns are: "198 BXD strains and ... the reciprocal F1s", of which "191 are independent, whereas 7 are substrains". The painting below skips the F1 columns: an F1 is heterozygous at every marker by construction, and the scan is computed over the strains. On JBrowse Desktop, add the `.bed.gz`/`.tsv.gz` files you build through **Add track** with no hosting step needed ([desktop quickstart](https://jbrowse.org/jb2-staging/docs/quickstart_desktop)). ## Track 1: chromosome painting The painting is a [multi-row feature display](https://jbrowse.org/jb2-staging/docs/user_guides/multirow_feature_track): one row per strain, each block colored by genotype. To make it, walk each strain's markers along every chromosome and emit one BED interval per run of consecutive same-genotype markers (run-length encoding), coloring `B`/`D`/`H` and writing the strain name into an extra `sample` column: ``` #chrom chromStart chromEnd name score strand thickStart thickEnd itemRgb sample genotype chr1 3001490 20291558 B 0 . 3001490 20291558 65,105,225 BXD1 B chr1 20291558 53451539 D 0 . 20291558 53451539 220,60,50 BXD1 D chr1 53451539 69355875 B 0 . 53451539 69355875 65,105,225 BXD1 B ``` The [`bxd_geno_to_painting_bed.py`](https://github.com/GMOD/jbrowse-components/blob/main/scripts/bxd_geno_to_painting_bed.py) script does exactly this run-length encoding. Run it on the downloaded `.geno`, then sort, `bgzip`, and `tabix` the result: ```bash curl -fO https://raw.githubusercontent.com/GMOD/jbrowse-components/main/scripts/bxd_geno_to_painting_bed.py python3 bxd_geno_to_painting_bed.py BXD.geno bxd_painting.bed jbrowse sort-bed bxd_painting.bed | bgzip > bxd_painting.bed.gz tabix -p bed bxd_painting.bed.gz ``` [`sort-bed`](https://jbrowse.org/jb2-staging/docs/cli#jbrowse-sort-bed) keeps the `#`-header line on top and sorts the rest under `LC_ALL=C`, so the adapter can read the column names off the file and the order does not shift with your locale. Then configure a `FeatureTrack` whose `LinearMultiRowFeatureDisplay` partitions on the `sample` column and colors each block from its `itemRgb` field. Both tracks reference the `mm10` assembly, so set that up first if you haven't. See the [assemblies configuration guide](https://jbrowse.org/jb2-staging/docs/config_guides/assemblies). ```json { "type": "FeatureTrack", "trackId": "bxd_chromosome_painting_mm10", "name": "BXD chromosome painting (GeneNetwork, 198 strains)", "assemblyNames": ["mm10"], "adapter": { "type": "BedTabixAdapter", "disableGeneHeuristic": true, "uri": "https://jbrowse.org/demos/bxd/bxd_painting.bed.gz" }, "displays": [ { "type": "LinearMultiRowFeatureDisplay", "partitionField": "sample", "legend": [ { "label": "B (C57BL/6J)", "color": "rgb(65,105,225)" }, { "label": "D (DBA/2J)", "color": "rgb(220,60,50)" }, { "label": "H (heterozygous)", "color": "rgb(150,150,150)" } ] } ] } ``` - `partitionField: "sample"` splits the one file into one labeled row per strain. - A BED carrying `itemRgb` is painted with it automatically ([`color`](https://jbrowse.org/jb2-staging/docs/config/linearmultirowfeaturedisplay/#slot-color)), so every block gets its genotype color straight from the file. - [`legend`](https://jbrowse.org/jb2-staging/docs/config/linearmultirowfeaturedisplay/#slot-legend) names the two parents the colors stand for, a mapping the BED itself does not record. Its entries also drive the track menu's **Categories** toggles, so hiding `H` isolates the B/D contrast. - `disableGeneHeuristic: true` keeps the BED adapter from reading each block as a gene: the `thickStart`/`thickEnd` columns trip its BED12 transcript detection. ## Track 2: the QTL Manhattan GeneNetwork maps these traits itself, and its API serves the whole per-marker result of a GEMMA run, the mixed model that accounts for how closely the BXD strains are related. Fetch a trait's scan by its GeneNetwork id and reshape it with `jq`. Each record carries a marker, its mm10 position in Mb, a LOD score and a p-value: ```bash GN='https://genenetwork.org/api/v_pre1/mapping?db=BXDPublish&method=gemma' curl -fsSL "$GN&trait_id=11280" -o coat_color.json # 11280 = coat color { printf '#chrom\tstart\tend\tname\tscore\tstrand\tlod\n' jq -r '.[0][] | [ "chr" + (.chr|tostring), ((.Mb*1000000)|round), ((.Mb*1000000)|round + 1), .name, ".", ".", (.lod_score*10000|round/10000) ] | @tsv' coat_color.json | sort -k1,1 -k2,2n } | bgzip > bxd_gwas_coatcolor.tsv.gz tabix -p bed bxd_gwas_coatcolor.tsv.gz ``` Trait ids are the numbers in a GeneNetwork trait's own URL, and [`bxd_phenocovar.csv`](https://github.com/rqtl/qtl2data/tree/master/BXD) in the qtl2data BXD release lists them with their descriptions. `11280` is the hair coat color scale, scored across more strains than most. That writes a tabix'd BED-like table, one line per marker: ``` #chrom start end name score strand lod chr4 81304223 81304224 rs3708061 . . 48.1126 ``` A `GWASTrack`/`GWASAdapter` reads one column of that file as the Manhattan score. It defaults to a pre-computed `-log10(p)` in a column called `neg_log_pvalue`, so a LOD column needs [`scoreColumn`](https://jbrowse.org/jb2-staging/docs/config/gwasadapter/#slot-scorecolumn) naming it. [`scoreTransform`](https://jbrowse.org/jb2-staging/docs/config/gwasadapter/#slot-scoretransform) stays at its default, since a LOD is already on the scale the plot draws; it is what a raw or natural-log p-value column would need. See the [GWAS track guide](https://jbrowse.org/jb2-staging/docs/config_guides/gwas_track). ```json addtrack { "type": "GWASTrack", "trackId": "bxd_gwas_coatcolor_mm10", "name": "BXD QTL: coat color (GEMMA, Tyrp1, chr4)", "assemblyNames": ["mm10"], "adapter": { "type": "GWASAdapter", "uri": "bxd_gwas_coatcolor.tsv.gz", "scoreColumn": "lod" }, "displays": [ { "type": "LinearManhattanDisplay" } ] } ``` ## Reading the coat-color peak The coat-color scan puts a plateau of tied markers on chr4, whose interval contains _Tyrp1_. To line the painting up with it, right-click the painting at that column and pick the "Sort rows by color here" option (a saved session can bake the same sort in through the display's `sortRowsBy` position). Rows then order by their B/D genotype at the peak: the split directly beneath it is the contrast the scan scores, and it breaks up into mixed B/D blocks away from the locus.