Selection pressure between two genomes (dN/dS)

The ratio of non-synonymous to synonymous substitution rates, dN/dS, measures the selection pressure on a protein-coding gene between two species. We:

• build a human against rhesus macaque ortholog table with jcvi, and measure dN and dS on every pair with kaks_from_pairs.py
• load both genomes and genes, and the table as a synteny track
• color each ortholog link by the ratio
• read the lysozyme (LYZ) neighbourhood on human chromosome 12, with the conserved neighbour YEATS4 as the control

Prerequisites#

• a JBrowse to open the files in: Desktop takes a local file by path, Web through Add track
• jcvi
• DIAMOND
• python3 with biopython
• htslib (bgzip, tabix)
• wget
• node, for the JBrowse CLI

jcvi compiles C extensions at install time, and the compile fails on some Python versions. If pip install jcvi fails, uv venv --python 3.12 followed by uv pip install jcvi biopython gives an interpreter it builds on.

# Debian/Ubuntu
sudo apt install tabix diamond-aligner nodejs
# or conda, which has every tool above
conda install -c bioconda -c conda-forge htslib diamond nodejs
# any platform
pip install jcvi biopython
npm install -g @jbrowse/cli@next

The data#

The assemblies are GCA_000001405.29 (human GRCh38) and GCA_003339765.3 (rhesus macaque Mmul_10), with gene models and coding sequence from Ensembl release 116.

The tracks below read local files that the build script writes from these, so run it first, or run Producing the human-rhesus ortholog table and its rates on a GFF3, a protein FASTA and a CDS FASTA per genome of your own. The script fetches everything itself.

What dN/dS says#

A coding substitution is synonymous (the codon changes, the amino acid does not) or non-synonymous.

• dS is the synonymous rate. Selection acts weakly on synonymous changes, so dS approximates the mutation rate.
• dN is the non-synonymous rate, which reflects the selection acting on those changes.
• dN/dS below 1 indicates purifying selection, where most genes sit. Above 1 needs positive selection to explain.

Producing the human-rhesus ortholog table and its rates#

dS has to be large enough to estimate and small enough not to saturate. Rhesus macaque sits in that window against human.¹

Calling human-rhesus orthologs with jcvi#

jcvi takes a BED and a proteome per genome under one set of ids. The BED comes from the GFF3, one primary transcript per gene on the assembled chromosomes, and the adapter reads the same file:

python -m jcvi.formats.gff bed --type=mRNA --key=transcript_id \
  --primary_only human.gff3.gz -o human.all.bed
awk -F'\t' '$1 ~ /^([0-9]+|X|Y)$/' human.all.bed > human.bed

The end-to-end script translates each CDS into human.pep and rhesus.pep, keeping the transcripts the BED names under the same ids. DIAMOND aligns human against rhesus, and jcvi chains the hits:

diamond makedb --in rhesus.pep -d rhesus.pep
diamond blastp --threads 14 --query human.pep --db rhesus.pep \
  --out human.rhesus.last --max-target-seqs 20 --evalue 1e-10 --outfmt 6
python -m jcvi.compara.catalog ortholog --no_strip_names --dbtype prot \
  --align_soft diamond_blastp --no_dotplot human rhesus

Two input mistakes leave jcvi with no orthologs:

• the alignment file has to be query = the first species, subject = the second. Reversed, jcvi looks up every id in the wrong BED and the run ends with A total of 0 anchor was found
• Ensembl versions transcript ids in its FASTA and not in its GFF3 (ENST00000641515.7 against ENST00000641515), so nothing matches. The script strips the version, and kaks_from_pairs.py takes --strip-version

Measuring dN and dS on each pair#

The pair list is the two gene columns of human.rhesus.anchors. The script skips human.rhesus.lifted.anchors, which recruits extra pairs near an established syntenic block. Their median dS is several times that of the chained pairs, which marks them as paralogs.

# skip the ### lines that separate blocks
awk '!/^#/ && NF >= 2 {print $1 "\t" $2}' human.rhesus.anchors > pairs.tsv
# one CDS file for both genomes, whose ids (ENST, ENSMMUT) are distinct
cat human.cds.fa.gz rhesus.cds.fa.gz > both.cds.fa.gz

curl -fO https://raw.githubusercontent.com/GMOD/jbrowse-components/main/scripts/kaks_from_pairs.py

python3 kaks_from_pairs.py pairs.tsv both.cds.fa.gz \
  --key record --strip-version --min-syn-subs 3 --max-ds 0.3 -o primate.blocks
gzip -kf primate.blocks human.bed rhesus.bed

kaks_from_pairs.py aligns each pair as protein, back-translates to codons so that nothing shifts frame, and runs Nei-Gojobori.

Filtering paralogs and low-count pairs#

True orthologs share one divergence time, so their dS values cluster. A pair well above the cluster is a paralog the aligner preferred, and --max-ds drops every pair whose dS exceeds its value.

The top of a table sorted by dN/dS is the pairs with almost nothing to divide by: HBA1 lands there off a single synonymous difference. --min-syn-subs is a floor on that count, and drops every pair with fewer synonymous differences than its value.

Every row also has that count and a two-sided Fisher exact p, the test MEGA prescribes for small substitution counts. The track config below exposes both as attributeColumns, so clicking a link shows the evidence under its color.

Loading the human and rhesus genomes and genes#

A gene-level synteny view reads no sequence, so each assembly is a .chrom.sizes file (a name and a length per line) that the script writes from the GFF3's ##sequence-region header. We load human here and rhesus the same way under the name rhesus:

{ "name": "human", "uri": "human.chrom.sizes" }

jbrowse add-assembly human.chrom.sizes \
  --name human \
  --load copy

human.chrom.sizes

Each panel draws genes from a track under its assembly. The script writes human.genes.gff3.gz and rhesus.genes.gff3.gz, bgzipped and tabix-indexed (prep). For your own annotation the GFF3 needs the same refNames as the assembly:

{
  "type": "FeatureTrack",
  "trackId": "human_genes",
  "name": "human genes",
  "assemblyNames": ["human"],
  "adapter": {
    "type": "Gff3TabixAdapter",
    "uri": "human.genes.gff3.gz"
  }
}

jbrowse add-track human.genes.gff3.gz \
  --trackId human_genes \
  --name "human genes" \
  --assemblyNames human \
  --load copy

{
  "type": "FeatureTrack",
  "trackId": "human_genes",
  "name": "human genes",
  "assemblyNames": ["human"],
  "adapter": {
    "type": "Gff3TabixAdapter",
    "uri": "human.genes.gff3.gz"
  }
}

Add the rhesus track the same way, with rhesus_genes under rhesus.

Loading the ortholog table as a synteny track#

primate.blocks lists each pair's two gene ids, then dN, dS, the synonymous substitution count and the Fisher p, the .blocks shape MCScanBlocksAdapter reads. attributeColumns names the columns after the two gene columns, and the detail panel lists each as a feature attribute:

{
  "type": "SyntenyTrack",
  "trackId": "primate_orthologs",
  "name": "Human / rhesus orthologs (dN/dS)",
  "assemblyNames": ["human", "rhesus"],
  "adapter": {
    "type": "MCScanBlocksAdapter",
    "uri": "primate.blocks.gz",
    "blockAssemblies": ["human", "rhesus"],
    "bedLocations": ["human.bed.gz", "rhesus.bed.gz"],
    "attributeColumns": ["dn", "ds", "syn_subs", "fisher_p"]
  }
}

jbrowse add-track-json '{
  "type": "SyntenyTrack",
  "trackId": "primate_orthologs",
  "name": "Human / rhesus orthologs (dN/dS)",
  "assemblyNames": ["human", "rhesus"],
  "adapter": {
    "type": "MCScanBlocksAdapter",
    "uri": "primate.blocks.gz",
    "blockAssemblies": ["human", "rhesus"],
    "bedLocations": ["human.bed.gz", "rhesus.bed.gz"],
    "attributeColumns": ["dn", "ds", "syn_subs", "fisher_p"]
  }
}'

{
  "type": "SyntenyTrack",
  "trackId": "primate_orthologs",
  "name": "Human / rhesus orthologs (dN/dS)",
  "assemblyNames": ["human", "rhesus"],
  "adapter": {
    "type": "MCScanBlocksAdapter",
    "uri": "primate.blocks.gz",
    "blockAssemblies": ["human", "rhesus"],
    "bedLocations": ["human.bed.gz", "rhesus.bed.gz"],
    "attributeColumns": ["dn", "ds", "syn_subs", "fisher_p"]
  }
}

Color by value → dN/dS in the palette button menu sets the view's encoding.color, a color scale that reads dn and ds, on a ramp with 1 at the middle and 2 at the top.

Two view settings matter for a view this sparse:

• Opacity on the sliders button in the view header sets encoding.opacity, which starts low for whole-genome views where ribbons overlap. 0.95 shows the color as it is.
• Curved lines on the same menu sets mark: { interpolate: 'bump' }, which separates stacked neighbours.

Reading lysozyme (LYZ) against its neighbours by dN/dS#

The session below opens, from the hosted copy, the stretch around lysozyme (LYZ) on human chromosome 12 where gene order matches rhesus, colored by dN/dS. In your own build, pick Color by value → dN/dS.

{
  "defaultSession": {
    "name": "Selection pressure across a primate gene neighbourhood",
    "views": [
      {
        "type": "LinearSyntenyView",
        "views": [
          {
            "assembly": "human",
            "loc": "12:67,835,000-70,835,000",
            "tracks": ["human_genes"]
          },
          {
            "assembly": "rhesus",
            "loc": "11:67,401,000-70,319,000",
            "tracks": ["rhesus_genes"]
          }
        ],
        "tracks": [["primate_orthologs"]],
        "encoding": { "color": "dnds", "opacity": 0.95 },
        "mark": { "interpolate": "bump" }
      }
    ]
  }
}

jbrowse set-default-session --session - << 'EOF'
{
  "name": "Selection pressure across a primate gene neighbourhood",
  "views": [
    {
      "type": "LinearSyntenyView",
      "views": [
        {
          "assembly": "human",
          "loc": "12:67,835,000-70,835,000",
          "tracks": ["human_genes"]
        },
        {
          "assembly": "rhesus",
          "loc": "11:67,401,000-70,319,000",
          "tracks": ["rhesus_genes"]
        }
      ],
      "tracks": [["primate_orthologs"]],
      "encoding": { "color": "dnds", "opacity": 0.95 },
      "mark": { "interpolate": "bump" }
    }
  ]
}
EOF

✕

Open in JBrowse Web ↗Open in JBrowse Desktop ↗

Open in JBrowse Desktop ↗

Needs JBrowse Desktop 5.0 or newer. If nothing opens, copy the link and paste it into Desktop's Open JBrowse Web link..., on the start screen or under File → Session.

Copy

https://jbrowse.org/code/jb2/main/?config=https%3A%2F%2Fjbrowse.org%2Fdemos%2Fprimate_selection%2Fconfig.json&session=spec-%7B%22views%22%3A%5B%7B%22type%22%3A%22LinearSyntenyView%22%2C%22views%22%3A%5B%7B%22assembly%22%3A%22human%22%2C%22loc%22%3A%2212%3A67%2C835%2C000-70%2C835%2C000%22%2C%22tracks%22%3A%5B%7B%22trackId%22%3A%22human_genes%22%2C%22labels%22%3A%7B%22description%22%3A%7B%22show%22%3Afalse%7D%7D%2C%22displayMode%22%3A%22compact%22%7D%5D%7D%2C%7B%22assembly%22%3A%22rhesus%22%2C%22loc%22%3A%2211%3A67%2C401%2C000-70%2C319%2C000%22%2C%22tracks%22%3A%5B%7B%22trackId%22%3A%22rhesus_genes%22%2C%22labels%22%3A%7B%22description%22%3A%7B%22show%22%3Afalse%7D%7D%2C%22displayMode%22%3A%22compact%22%7D%5D%7D%5D%2C%22tracks%22%3A%5B%5B%22primate_orthologs%22%5D%5D%2C%22encoding%22%3A%7B%22color%22%3A%22dnds%22%2C%22opacity%22%3A0.95%7D%2C%22mark%22%3A%7B%22interpolate%22%3A%22bump%22%7D%7D%5D%7D&sessionName=JBrowse+docs%3A+selection_pressure%2Flysozyme

Large dataset: slow to open.

Or rebuild it from your own data:

Steps

Quickest: open the view, then File → Open track... for your files.

From scratch:

1. Open your genomes: Open new genome in JBrowse Desktop, then File → Open genome... for each of the rest, or jbrowse add-assembly for each in JBrowse Web.This figure's rows, top to bottom: human, rhesus.
2. Open the view: Add → Linear synteny view, and set the rows to those assemblies in the import form.
3. Add your file: click the arrow between two rows and choose New track. Needs an MCScan .blocks file plus one BED per genome.Or pick a synteny track you already have under Quick start, which fills in the rows.This figure uses “Human / rhesus orthologs (dN/dS)”.
4. Click Launch.
5. Synteny view header → palette button → Color by value → dN/dSThe palette button's tooltip reads "Color by: ...".
6. Synteny display settings (the sliders button in the view header) → Opacity → drag to 0.95Lower values let dense overlapping ribbons show through each other.
7. Synteny display settings (the sliders button in the view header) → Curved lines (checked)
8. Row 1 (human)
   1. Add your track: + → Add track in this view's track selector, or check it there. Needs a bgzip-compressed, tabix-indexed GFF3 (.gff.gz + .tbi).This figure uses “Human genes (GRCh38, Ensembl 116)”.
      1. Track menu → Show → Descriptions (unchecked)
      2. Track menu → Feature height → Compact
   2. Go to your region in the location box.This figure is at 12:67,835,000-70,835,000.
9. Row 2 (rhesus)
   1. Add the next track the same way. Needs a bgzip-compressed, tabix-indexed GFF3 (.gff.gz + .tbi).This figure uses “Rhesus macaque genes (Mmul_10, Ensembl 116)”.
      1. Track menu → Show → Descriptions (unchecked)
      2. Track menu → Feature height → Compact
   2. Go to your region in the location box.This figure is at 11:67,401,000-70,319,000.

Agent

Paste into a coding agent, with your goal on the first line.

Copy

My goal: [write yours, e.g. this view of my own files, or these track settings in my config.json]

Start from this JBrowse view.
- Config it loads: https://jbrowse.org/demos/primate_selection/config.json
- Tracks:
  - Human / rhesus orthologs (dN/dS) (primate_orthologs), SyntenyTrack, an MCScan .blocks file plus one BED per genome, drawn as LinearSyntenyDisplay
  - Human genes (GRCh38, Ensembl 116) (human_genes), FeatureTrack, a bgzip-compressed, tabix-indexed GFF3 (.gff.gz + .tbi), drawn as LinearBasicDisplay
  - Rhesus macaque genes (Mmul_10, Ensembl 116) (rhesus_genes), FeatureTrack, a bgzip-compressed, tabix-indexed GFF3 (.gff.gz + .tbi), drawn as LinearBasicDisplay

Docs: https://jbrowse.org/jb2/docs/agents_authoring/ (writing a config), https://jbrowse.org/jb2/docs/agents/ (driving a running JBrowse). Use the jbrowse-authoring, jbrowse-hosted-data and jbrowse-capture skills if you have them. Check any config with `npx @jbrowse/cli validate`, then render it and look: a config that loads is not yet a track that drew.

The session spec that draws the view:
{
  "views": [
    {
      "type": "LinearSyntenyView",
      "views": [
        {
          "assembly": "human",
          "loc": "12:67,835,000-70,835,000",
          "tracks": [
            {
              "trackId": "human_genes",
              "labels": {
                "description": {
                  "show": false
                }
              },
              "displayMode": "compact"
            }
          ]
        },
        {
          "assembly": "rhesus",
          "loc": "11:67,401,000-70,319,000",
          "tracks": [
            {
              "trackId": "rhesus_genes",
              "labels": {
                "description": {
                  "show": false
                }
              },
              "displayMode": "compact"
            }
          ]
        }
      ],
      "tracks": [
        [
          "primate_orthologs"
        ]
      ],
      "encoding": {
        "color": "dnds",
        "opacity": 0.95
      },
      "mark": {
        "interpolate": "bump"
      }
    }
  ]
}

Redraw the figure headlessly

Copy

cat > session.json <<'JSON'
{
  "views": [
    {
      "type": "LinearSyntenyView",
      "views": [
        {
          "assembly": "human",
          "loc": "12:67,835,000-70,835,000",
          "tracks": [
            {
              "trackId": "human_genes",
              "labels": {
                "description": {
                  "show": false
                }
              },
              "displayMode": "compact"
            }
          ]
        },
        {
          "assembly": "rhesus",
          "loc": "11:67,401,000-70,319,000",
          "tracks": [
            {
              "trackId": "rhesus_genes",
              "labels": {
                "description": {
                  "show": false
                }
              },
              "displayMode": "compact"
            }
          ]
        }
      ],
      "tracks": [
        [
          "primate_orthologs"
        ]
      ],
      "encoding": {
        "color": "dnds",
        "opacity": 0.95
      },
      "mark": {
        "interpolate": "bump"
      }
    }
  ]
}
JSON

cat > callouts.json <<'JSON'
[
  {
    "type": "text",
    "text": "LYZ, the only pair above 1. Every neighbour is blue",
    "fontSize": 18,
    "maxWidth": 300,
    "anchor": {
      "view": [
        0,
        0
      ],
      "trackId": "human_genes",
      "loc": "12:69,351,000",
      "fracY": 1,
      "dy": 45,
      "alignX": "right",
      "dx": 95
    }
  },
  {
    "type": "arrow",
    "fromAnchor": {
      "view": [
        0,
        0
      ],
      "trackId": "human_genes",
      "loc": "12:69,351,000",
      "fracY": 1,
      "dy": 52,
      "alignX": "right",
      "dx": 88
    },
    "anchor": {
      "view": [
        0,
        0
      ],
      "trackId": "human_genes",
      "loc": "12:69,351,000",
      "fracY": 1,
      "dy": 52,
      "dx": 8
    }
  }
]
JSON

npx @jbrowse/capture --instance https://jbrowse.org/code/jb2/main/ \
  --config https://jbrowse.org/demos/primate_selection/config.json \
  --width 1500 --height 580 \
  --timeout 300000 \
  --spec session.json --annotations callouts.json -o figure.png

More: Using JBrowse with AI agents.

CLI

Adds these tracks to your config.json, styled as in the figure. Point each uri at your file (replace YOUR_FILE).

Copy

jbrowse add-track-json '{
  "type": "FeatureTrack",
  "trackId": "human_genes",
  "name": "Human genes (GRCh38, Ensembl 116)",
  "assemblyNames": [
    "human"
  ],
  "adapter": {
    "type": "Gff3TabixAdapter",
    "uri": "YOUR_FILE"
  },
  "displayDefaults": {
    "labels": {
      "description": {
        "show": false
      }
    },
    "displayMode": "compact"
  }
}'

jbrowse add-track-json '{
  "type": "FeatureTrack",
  "trackId": "rhesus_genes",
  "name": "Rhesus macaque genes (Mmul_10, Ensembl 116)",
  "assemblyNames": [
    "rhesus"
  ],
  "adapter": {
    "type": "Gff3TabixAdapter",
    "uri": "YOUR_FILE"
  },
  "displayDefaults": {
    "labels": {
      "description": {
        "show": false
      }
    },
    "displayMode": "compact"
  }
}'

Run beside config.json, or add --out <dir>. Needs human, rhesus in the config (jbrowse add-assembly).

Notebook

This view in a notebook, with jbrowse-anywidget. Swap a track's uri for your file.

Copy

from jbrowse_anywidget import JBrowseApp, fetch_hub

config = fetch_hub("https://jbrowse.org/demos/primate_selection/config.json")
app = JBrowseApp(
    assemblies=config["assemblies"],
    tracks=config.get("tracks", []),
    views=[
        {
            "type": "LinearSyntenyView",
            "views": [
                {
                    "assembly": "human",
                    "loc": "12:67,835,000-70,835,000",
                    "tracks": [
                        {
                            "trackId": "human_genes",
                            "labels": {
                                "description": {
                                    "show": False
                                }
                            },
                            "displayMode": "compact"
                        }
                    ]
                },
                {
                    "assembly": "rhesus",
                    "loc": "11:67,401,000-70,319,000",
                    "tracks": [
                        {
                            "trackId": "rhesus_genes",
                            "labels": {
                                "description": {
                                    "show": False
                                }
                            },
                            "displayMode": "compact"
                        }
                    ]
                }
            ],
            "tracks": [
                [
                    "primate_orthologs"
                ]
            ],
            "encoding": {
                "color": "dnds",
                "opacity": 0.95
            },
            "mark": {
                "interpolate": "bump"
            }
        }
    ],
)
app  # display the widget

Image

jbrowse-img draws this view as an SVG, no browser needed. Swap --config or a track for your own.

Copy

cat > session.json <<'JSON'
{
  "views": [
    {
      "type": "LinearSyntenyView",
      "views": [
        {
          "assembly": "human",
          "loc": "12:67,835,000-70,835,000",
          "tracks": [
            {
              "trackId": "human_genes",
              "labels": {
                "description": {
                  "show": false
                }
              },
              "displayMode": "compact"
            }
          ]
        },
        {
          "assembly": "rhesus",
          "loc": "11:67,401,000-70,319,000",
          "tracks": [
            {
              "trackId": "rhesus_genes",
              "labels": {
                "description": {
                  "show": false
                }
              },
              "displayMode": "compact"
            }
          ]
        }
      ],
      "tracks": [
        [
          "primate_orthologs"
        ]
      ],
      "encoding": {
        "color": "dnds",
        "opacity": 0.95
      },
      "mark": {
        "interpolate": "bump"
      }
    }
  ]
}
JSON

npx @jbrowse/img synteny --config https://jbrowse.org/demos/primate_selection/config.json \
  --spec session.json \
  --width 1500 --out figure.svg

For a PNG, --out figure.png (needs rsvg-convert: apt install librsvg2-bin, brew install librsvg).

Session

The session spec behind the figure, over this config.

Copy

{
  "views": [
    {
      "type": "LinearSyntenyView",
      "views": [
        {
          "assembly": "human",
          "loc": "12:67,835,000-70,835,000",
          "tracks": [
            {
              "trackId": "human_genes",
              "labels": {
                "description": {
                  "show": false
                }
              },
              "displayMode": "compact"
            }
          ]
        },
        {
          "assembly": "rhesus",
          "loc": "11:67,401,000-70,319,000",
          "tracks": [
            {
              "trackId": "rhesus_genes",
              "labels": {
                "description": {
                  "show": false
                }
              },
              "displayMode": "compact"
            }
          ]
        }
      ],
      "tracks": [
        [
          "primate_orthologs"
        ]
      ],
      "encoding": {
        "color": "dnds",
        "opacity": 0.95
      },
      "mark": {
        "interpolate": "bump"
      }
    }
  ]
}

Gene order is the same in both genomes here, so color is the only thing that varies. Click the orange LYZ ribbon for its synonymous count and Fisher p in the detail panel. Messier and Stewart reported adaptive evolution of primate lysozyme in 1997; the published result rests on codon models across many primate lineages.

YEATS4, a conserved neighbour, as the control for LYZ#

YEATS4 begins just past where LYZ ends, so the two share a locus and a divergence time. Click the blue YEATS4 ribbon beside LYZ for the same evidence at the other end of the ramp. A conserved gene accumulates measurable synonymous change while its non-synonymous change stays near zero, so its synonymous count clears the floor and the Fisher test reaches significance at the low end too.

Reproduce it end to end#

build_primate_selection.sh runs everything above and writes a config.json with both assemblies, both gene tracks, the ortholog track and a session opening the locus:

1. Turn each GFF3 into a BED and each CDS into a proteome keyed the same way, stripping Ensembl's transcript versions so the ids match.
2. Align human against rhesus with DIAMOND and chain the hits with jcvi, keeping the chained anchors and not the lifted ones.
3. Measure dN and dS on each pair, dropping pairs with too few synonymous differences or a dS far above the cluster.
4. Print the count of pairs genome-wide with dN/dS above 1, and dN/dS and dS for every pair around LYZ, and write the config.

curl -fO https://raw.githubusercontent.com/GMOD/jbrowse-components/main/scripts/build_primate_selection.sh
bash build_primate_selection.sh
npx --yes serve primate_selection_build/jbrowse2  # then open the printed URL

See also#

• Tutorial: Synteny visualization (a polyploid against itself)
• Tutorial: Synteny from an ortholog table (grape, peach, cacao)
• Tutorial: Synteny from MCScan anchors (grape, peach)

Citations#

• Nei and Gojobori (1986). Simple methods for estimating the numbers of synonymous and nonsynonymous nucleotide substitutions
• Messier and Stewart (1997). Episodic adaptive evolution of primate lysozymes
• Tang et al. (2024). jcvi: A versatile toolkit for comparative genomics analysis

Feedback on this tutorial is welcome: contact us.