Detect sex chromosomes from WGS on a bird species (with reference genome)
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19 months ago
beausoleilmo ▴ 400

I'm wondering if there is a way to identify if there is a presence of sex chromosomes from WGS data. The reference genome is https://www.ncbi.nlm.nih.gov/genome/?term=txid48883[Organism:noexp] (it's a female https://www.ncbi.nlm.nih.gov/nuccore/AKZB00000000.1; female birds are heteromorphic (ZW)) and the data that I'd like to test is from this project: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA263122.

Is there a program to do that or a way to test fort that?

WGS chromosomes • 495 views
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align your reads, if the ZW chromosome has unique regions, you can check for coverage.

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The thing is that the reference genome doesn't have "chromosome" level data. Only scaffold. So the only way I see would be using LiftOver. But I'm wondering if there is something developed for that...

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Yeah, it's all unplaced, you'll need to map it to another genome one way or another

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Can you identify which scaffold is part of the ZW chromosome? Blasting some proteins can give you a list of sequences to use as targets.

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I've never done that. I'm pretty sure there is a way to find the probability associated with aligning DNA strands to only sex chromosome of another species to find if the species would me homo or heterochromatic. I've just never seen anybody doing that.

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I know this is an old question now - but a way to approach this is to use a chromosome-level assembly as a reference against which you BLAST your sequences. So take separate Z and W fasta files from a related species that has a chromosome-level assembly, and then BLAST your sequences against them. You could use, for example, chicken or Zebrafinch Z's and W's. For those that map (above a certain threshold of length and similarity) you can get the read names from those (with, say, awk), and then you're off to the races. If you're interested in only the sex scaffolds, you can subset them into a new file, or filter them out if you're wanting to exclude them. You can do so with, say, picard FilterSamReads or seqtk subseq. If all you're interested is sexing, you could look at the % of the genome ID'd as either chromosome. If you have lots of reads mapping to W, fair chance you've got a F, but if you've only got reads mapping to Z, it's probably an M. Seems like a convoluted way to approach that question, but it could work, haha.

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13 months ago
dalynoll • 0

did you solve this? I have the same problem

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Not really. I was hoping for a more “how to” solution since I’m not the most knowledgeable in this topic and that I’m not familiar with all the tools to do this. So I’m still looking. Wouldn’t it be cool to have a way to do that?

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