SNPs detection in transcriptomics to define genetic variation between individuals
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3.8 years ago
roncalli • 0

Hi,

I am new to the SNP calling analysis and my question regard "expectations". I am trying to compare 3 de novo assemblies for calanoid copepod (non-model) and I would like to use the SNP calling as a way to assess the genetic variation between individuals. I do know from other paper that high genetic diversity is expected in my species and I am trying to link the SNP calling with this. I have seen that for humans 0.1% of SNPs diversity is enough to claim that 2 individuals are from different population but I am not sure if I can use this "expected" value also for copepods.

So my question is: Is there a way, based on % of "shared" and unique SNPs that I can support my theory of genetic diversity? Any "magic number" that would support the difference between individuals?

Thanks for the help,

Vittoria

RNA-Seq SNP genetic variation de novo assembly • 791 views
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Entering edit mode
3.8 years ago
colindaven ★ 2.9k

Interesting. I don't know of any magic numbers.

Instead of comparing assemblies directly, which would always ignore heterozygote variation (assemblies are likely to be haploid), I would suggest another approach.

  • a) merge assemblies. Software: cd-hit, supertranscript
  • b) rename contigs in merged transcriptome
  • c) map reads with bwa to merged trancriptome.
  • d) call variants, eg freebayes or bbmap callvariants.sh

This has the advantage of being standard conform.

You could also annotate your merged assembly with Interproscan for example to look at function

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Entering edit mode
3.8 years ago
roncalli • 0

Hi,

Thanks for the answer. Interestingly I did followed your suggestion already and this is what I did:

1) generate a merged assembly used as reference 2) mapped back to it each samples (raw reads) from a single individual 3) identified SNPs using samtool for calling variants

Now. How do I interpret the results? I am planning to generate a Venn diagram to see which SNPs are shared and which are "unique". My question now is "What is the % unique SNPs that would claim that individuals are from different population?"

I am very confused by the human #.

Thanks for the help,

Vittoria

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Entering edit mode

This is a very specific biological question. I would guess the ability to detect SNPs would be strongly affected by the number of transcripts expressed in each individual. I don't think anyone here can provide you with a definitive answer, the best bet would be to go through other non-model organisms to find more expectation values. Molecular breeding research might also help.

I would also show haplotypes - eg through visualization - of conserved well known genes (with SNPs) of the three samples.

Multisample SNP calling - through Freebayes etc - would at least give you the three samples together.

Lastly, this leads you very definitely towards molecular phylogenetics, trees and various relationship matrices.

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