Sinteny analysis using BAM file
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20 months ago

I have some genomes assamblies (BAM file) from Illumina sequencing. I would like to evaluate sinteny breaks in the chromosome 1. However, I have found software that make sinteny analysis, like Nucmer, but they use fasta file as a input and reference genome in fasta format as well. I would to know how could I make similar analysis or how could be the correct pipeline to transform my bam files to fasta and then make the analysis.

Thanks in advance,

assembly genome gene sequence • 502 views
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assuming your BAMs are already mapped to the reference genome, just create a consensus sequence for each sample

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You can export a concensus from your BAM file as fasta (see: Generating consensus sequence from bam file ) and then use the software you mention above.

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Could I use the compiled VCF with 50 genomes?, That was fiiltered by SNPs. Is that the correct file?

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20 months ago

If you have just genomic co-ordinates, you can use Ensembl REST to automate a synteny lookup analysis. Here, I do it between Human and Mouse via LASTZ_NET alignments. Please edit as you wish:

library(httr)
library(jsonlite)
library(xml2)

server <- 'http://rest.ensembl.org'

lookup <- c(
  '1:100000-200000',
  '1:50000000:50100000')

for (i in 1:length(lookup)) {
  ext <- paste0(
    '/alignment/region/homo_sapiens/',
    lookup[i],
    ':1?species_set=homo_sapiens;species_set=mus_musculus;method=LASTZ_NET')
    #':1?species_set=homo_sapiens;species_set=mus_musculus;method=EPO')

  message('--Looking up region: ', lookup[i])

  response <- GET(paste(server, ext, sep = ""), content_type("application/json"))

  if (any(grepl('no alignment available for this region', content(response)[[1]]))) {
      message('----', NA)
  } else {
    stop_for_status(response)

    human_coord <- paste0(
      content(response)[[1]]$alignments[[1]]$seq_region, ':',
      content(response)[[1]]$alignments[[1]]$start, '-',
      content(response)[[1]]$alignments[[1]]$end)
    human_seq <- content(response)[[1]]$alignments[[1]]$seq

    mouse_coord <- paste0(
      content(response)[[1]]$alignments[[2]]$seq_region, ':',
      content(response)[[1]]$alignments[[2]]$start, '-',
      content(response)[[1]]$alignments[[2]]$end)
    mouse_seq <- content(response)[[1]]$alignments[[2]]$seq

    message('\tHuman region:\t\t\t', human_coord)
    message('\tHuman sequence:\t\t\t', human_seq)

    message('\tSyntenic mouse region:\t\t', mouse_coord)
    message('\tSyntenic mouse sequence:\t', mouse_seq)

    Sys.sleep(5)

    message('\n')
  }
}

--Looking up region: 1:100000-200000
    Human region:           1:100000-100208
    Human sequence:         CACTAAGCACACAGAGAATAATGTCTAGAATCTGAGTGCCATGTTATCAAATTGTACTGAGACTCT-TGCAGTCACACAGGCTGACATGTAAGCATCG---CCATGCCTAGTACAGACTCTCCCTGCAGATGAAATTATATGGGATGCTAAATTATAATGAGAACAATGTTTGGTGAGCCAAAACTACAACAAGGGAAGCTAATTGGATGAAT
    Syntenic mouse region:      1:176696703-176696893
    Syntenic mouse sequence:    -------CACACTG-----GATTTGTAGAAGCAGGGTAATGCGTTGTC--------CTGGGACTTTCTGTAGTCACTGGAAGTGAACTGTTATTATTGGTATTATACATTGAACACTCTTTAAATACAGATGTACTTATATGGGATGCTGATTTATAATCAGAATCATGTTTGGTGAATGATGA--ACCAGGAGAAAATTTGATTGGATAAAT


--Looking up region: 1:50000000:50100000
    Human region:           1:50002687-50002969
    Human sequence:         TGGCCATAGAGAACTTCAACAGAGGAATT-AACTGTGGAGGACTG----GTGTGTAAGAGACAGAAAAGACTACCAGAGGCCTTTCACCTTAATGCTACTATCTTTTTTATTACTAG---GATATGCATTACAGGATGCTAAGAGCCTCAAATTTCCTATGTTCCTACTCTCTGTATG-GATGCCAAGTTTAAATTTTAAAATCTTATTAT--AATT-CAAAAAT----------CACAAAAAAGTAAAGTAAAAATAACAGAA-----GTTAAATTAACAAAATAAAAGTTAAT---------AGAAGTTAATCAAAG
    Syntenic mouse region:      4:110403744-110404052
    Syntenic mouse sequence:    TGGCCACAAAGACCATCCAGAGGGGGCTTTAACAATGATGGACTGCAAAATGCATG-GACATGGGAAAGACTAGTCCAGTTCTTTTAACTTCCTGCTCCTACTTTTGTTTTAACTAAAATGATATACACTAAAGAA-----AGAGCCTTGTATTGTTTATGTTCCTACTTTCTTTTTATAATTCTAAATTTA----TTGATAGCTCAATGTGCAATTGTAAAGATATGGCTTGGACACTGGGAAGGTAGCTAGATATATTTGAGTAATGATCATTTTAGTTAAAAAAAACTTTCTCTTCTTTCCAGAATTCAGACTGAG
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