Dear Carmelo, Thank you sooo much for your super details comments and suggestions! Also again I am very glad that I participated in the Physalia course with you, not to imagine you still remember me for that!
Some thoughts on your comments: 1. Yes my plan is to only focus on the hybrid morph and the parental morphs. Maybe a bit more on the shape side, yes I am interested in the individual head shape, which is quite distinct among morphs. However I found significant size-shape interaction, and the size distribution of two morphs (one parental and one hybrid) and the other parental morph doesn't overlap. Will it be a problem? Or I will just take size also as a covariable? For the input file of shape data, should I just try the coordinate, and then the distance? I guess the distance is more about differentiation so not be the case for me. 2. How to select the SNPs if I will take the SNPs as input data. As you said, it is a great idea to choose the fixed markers from the parental morphs and encode them as numbers. I will try this to see how many markers I will get. As I work with ddRAD and missingness up to 30% is common, I was thinking to filter the SNPs on: 1) low missingness (present in 90% individuals, etc.) and 2) high Fst value ( I guess the extreme case will be the fixed ones in the parental morphs?). In a genetic PCA, we normally replace the missing data with the mean, so missingness may not be a huge problem but whether the filtering/sub-sampling of SNPs makes sense is important. 3. Take the ancestry proportion calculated by Admixture as the input. I also get this idea since it is the most straightforward way to target introgression. I guess either: 1) 2b-PLS, 2) general linear models, and 3) a Mantel test may work. To summarize, as you said, the input file matters for the exact question I want to ask. Ancestry proportion will transform the high dimensional genetic variation into a univariate factor. However this might be the most straightforward way to do it (in different ways) than taking SNPs of interest, which will maintain more variations but difficult to interpret the finding, I guess. Thank you very much again! Best regards, Han 在2022年11月2日星期三 UTC 05:54:40<Carmelo Fruciano> 写道： > > > Il 01/11/22 18:02, Han Xiao ha scritto: > > Dear morpho people, > > > > I am writing to ask a rarely discussed question, which is to test > > associations between genomic data and shape variation. > > Dear Han, > yes, this is a topic that is perhaps less frequently discussed than > others. As a participant to one of the editions of my geometric > morphometric course, you may recall we covered this general topic to > some extent. > > > To describe my system and bit first, I am working with four sympatric > > fish morphs in a lake. I have both genetic data (SNP generated by > > ddRADSeq, around 12000 SNPs) and shape data (landmarks and > > semilandmarks-based GM for the head shape) of the same fish samples. The > > genetics indicate that three morphs are genetically distinct, while one > > is of hybridization origin between two morphs with different degrees of > > introgression. I like to ask the question: for the three related morphs > > (two parental morphs and one hybrid morph) there any correlation between > > the degree of genetic introgression and the shape variation? > > Presumably, if this is your main question and by "shape variation" you > mean "individual shape", you would be performing the analysis mainly on > the only introgressed morph (whose individuals I have to assume based on > your text have varying levels of introgression), using information from > the two "parental" morphs. > > > I was suggested to apply a 2b-PLS to test it. Then I searched for some > > literature and find a few cases. However, the studies vary for the input > > data of both genetics and morphometrics. For genetics, people have used > > genetic distances (calculated as Fst/(1-Fst), Fst is a measurement of > > genetic differentiation), Prevosti distance, allele frequencies (a few > > microsatellites), and expression results (numeric and continuous). For > > the shape data, people used Eucidean distances, GPA coordinates, > > centroid sizes, etc. > > About the genetic measures, if the question is about the degree of > introgression (of one morph into another when producing the third > morph), it is doubtful that any of the measures you mention would > adequately capture that. For instance, within your introgressed morph > genetic variation among individuals may not be produced exclusively by > varying levels of introgression. So FST would be a poor choice because > it would capture genetic variation produced by other causes (e.g., > neutral variation). There are other reasons why FST may be a poor > choice, but let's keep it at that. > > Perhaps a semi-decent solution to quantify the degree of introgression > would be to subset your SNP panel to only those SNPs (if any) which are > fixed between "parental" morphs (and which are biallelic in the > introgressed morph), code them to reflect their "polarity" (e.g., 0 the > allele in one parental morph, 1 the allele in the other parental morph) > rather than using the actual nucleotides, and then use the data scored > this way for your individuals from the introgressed morph to do tests > with morphology. > > The above is just a very rough solution, with ample margins of > improvement depending on the details of your system (e.g., ongoing gene > flow between the two "parental" morphs, with most of alleles not being > fixed between them). But, as you may imagine, this goes well beyond this > brief reply and would require more in-depth knowledge of your specific > situation (notice how I had to make several assumptions about how > genetic variation is distributed among your morphs). > Notice also that if the level of introgression is all you care about > (regardless of which loci it comes from) you may obtain a much better > and "faster" (i.e., less work for you) solution by using individual > estimates of levels of admixture between morphs from one of the software > used for analysis of genetic admixture (which you have probably used > anyway). > > > So my questions are: > > 1. Do you all agree that sb-PLS should also make sense for such a > > comparison? > > PLS may be a good solution to identify how the shape and levels of > introgression co-vary. Tests based on a measure of association (e.g., > Escoufier RV) may be used to test the null hypothesis that they are > independent. > If your estimate of level of introgression is univariate (notice that in > the rough solution I suggested above this may not be the case), you may > also consider general linear models (and associated tests of > significance) using the level of introgression as a predictor. > > > 2. What you will suggest for the input files? (I do have some > > considerations to discuss) > > See above. I suppose the main issue is a bit beyond input files per se > and more about how you quantify/represent introgression. > > > 3. Is there any other analysis you will recommend? > > > I know normally people will use GWAS to search for associations, > > however, I am looking for something that can tolerate a smaller sample > > size (30 fish per morph). > > This is absolutely correct. But, more fundamentally, GWAS' goal is quite > distinct from the hypothesis you want to test. > > > Also, the potential transgressive shape of > > hybrids may be a confounding factor, especially there is different > > allometry observed. > > Yes. But transgressive segregation may not be a concern if you are just > interested in whether and how levels of introgression scored within a > single "introgressed" morph is associated to shape variation. > > Best, > Carmelo > > -- > ================== > Carmelo Fruciano > Italian National Research Council (CNR) > IRBIM Messina > http://www.fruciano.org/ > ================== > -- You received this message because you are subscribed to the Google Groups "Morphmet" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/morphmet2/263cb8f5-b0c8-413f-bda2-d35082109581n%40googlegroups.com.
