Hello Khan - There are really so many options! I might be able to recommend something specific if you describe your goals in a bit more detail. For example, do you want to find sites that are under divergent selection between species (HKA test)? Or estimate the overall level of introgression between populations / species (ABBA-BABA test, dadi)? Or find genome regions that are introgressing more than others (Gompert and Buerkle, 2011)? Or find sites under selection within each species (Bayescan)? Or maybe you are interested in physical barriers to migration (BEDASSLE), or perhaps association of certain SNPs with environmental variables (BayEnv)? 

In any case, to do most of the fun analyses above, you would need to RAD multiple populations (at the individual level, not pooled - except for BEDASSLE and BayEnv, these take pooled data as well) of each species,  plus - if introgression analysis is indeed the goal - a single outgroup individual (to identify ancestral states).

Mikhail

Thanks Mikhail- Your suggestions are really very precious. my aims of the project are to investigate the genetic structure and level of introgression of the putative hybrid swarms of four pure species and their hybrids swarms throughout their genotyping-by-sequencing set of SNPs and to use the SNP data set to search for genomic regions under selection. we will cover all the pure allopatric populations, pure species and individuals in sympatric populations; and hybrids species and their individuals  in the sympatric populations. 

so you are looking for genomic regions under divergent selection between species, correct? I am assuming that the hybrids are recent (ongoing introgression) so you might wish to look at genomic clines as per Gompert and Buerkle 2011 to find "outlier" regions that introgress less than others (ostensibly, due to selection). Plus, a typical admixture analysis using ADMIXTURE (to assess per-individual admixture level) and a between-species HKA test for regions that seem to resist introgression to substantiate that it is indeed due to divergent selection. All that is possible assuming you have a draft genome reference?

Thanks a lot @ Mikhail

note that outlier 'regions' can only be discerned if you are mapping the RAD reads back to a genome, and HKA requires an outgroup. Also the ML-HKA is slow and hard to pipeline. bayescan is relatively easy and will tell you loci with non-neutral patterns of divergence (positive or balancing selection) between a pair of species. one thing to consider is the amount of polymorphism you have within a read (dependent on the species). If there are several pm sites within a RAD locus then bayescan could work well, but if you try to do it on one SNP per locus theres only two alleles youre scoring. Just some things to think about :)

Bayescan is probably a good start - but its important to remember these are anonymous loci and they could - and likely are - deviating from background levels for a variety of reasons that are not due to divergent selection (population structure, background selection, sequencing artefacts). You'll get some diagnostic loci and might get lucky and get something linked to a relevant region, but just keep in mind alternative explanations! We have a paper coming out soon discussing a bit of this and this article (now in TREE) tackles some of the issues as well https://peerj.com/preprints/488.pdf

Baysecan will definitely work as long as the divergence between the species in question is not too great - i.e., as long as the majority of polymorphisms are not nearing fixation in any of the species.

Dear Gulzar, we analyzed segregation patterns of RAD loci in a hybrid swarm of two Salix species. Maybe it will help you: Gramlich S, Wagner, ND, Hörandl E. (2018). RAD-seq reveals genetic structure of the F2-generation of natural willow hybrids (Salix L.) and a great potential for interspecific introgression. BMC Plant Biology 18:317 https://doi.org/10.1186/s12870-018-1552-6 To check for hybridization and introgression you may also use HyDe (Blischak et al 2018)

Thanks a lot Dear Natascha.