Category: functional vs. non-functional genes

Genetic Structure Redux

Genetic structure, from Western Biopolitics.

Something (slightly edited) from my old Western Biopolitics site about genetic structure, based on this paper, with a few new comments at the end.

Although this is highly preliminary, this is all completely consistent with what I (and James Bowery and Ben Tillman) have been saying for years: simple Fst measurements of genetic distance, while crucially important and necessary, are not sufficient to give the complete picture for EGI. Genetic distance based on structure is likely greater than that estimated from Fst for humans as well as for oak. Further, the genetic structure estimates can be viewed, as I’ve been saying, as an extra, independent measure of genetic distinctiveness superimposed on top of the foundation of Fst distance. Therefore, a complete estimation of EGI must include consideration of genetic structure, and this paper is an initial, preliminary attempt at quantifying that structure. More to come, we hope. This research groups compares analyses of combinations of coinherited alleles compared to the “one-by-one” Fst method. This paper is free online, take a close look at Table 1 – as the level of genetic structural complexity increases, genetic distance between the oak groups also increases. Note in all cases, emphasis added.

…is characterized by special combinations of genes. (To emphasize this aspect, genic integration might be the more appropriate term.) The main motivation for this paper was the realization that impacts of particular forces, selective or not, on population differentiation may not be observable at every level of genetic integration. Measurements of differentiation among populations based on gene frequencies, for example, provide no specific insights into the effects of mating systems nor of epistatic interaction on population differentiation. This is due to the fact that gene frequencies refer to the lowest level of genetic integration, namely its absence. This level, which is commonly addressed as a population’s gene-pool, is conceived to consist of the set of all individual genes present in the population members for a specified set of genetic traits. Genetic studies of population differentiation are almost always based on this “beanbag” (critically reflected by Mayr [2] and defended by Haldane [3]; for concise reasoning of the persistence of the gene-pool concept see e.g. [4] or [5]). Studies of differentiation at multiple loci are no exception, since they commonly report averages over single-locus differentiation indices. Also disregarded in studies of gene-pool differentiation are gene associations that deviate from Hardy-Weinberg proportions (homologous, or intralocus, association) or gametic equilibria (non-homologous, or interlocus, association). 

Considering that forms and degrees of gene association may differ at different levels of genetic integration, it thus appears that previous studies on patterns of population differentiation have provided very little information on levels of genetic integration above the gene-pool. One important reason for the usual focus on gene-pool differentiation is probably the lack of a method for measuring population differentiation consistently at all levels of genetic integration. Consistency means that comparison of the amount of differentiation among a set of populations between levels of integration provides information about the complexity of the gene associations that distinguish them. 

Since gene associations do not decrease as level of integration increase, neither should differentiation. Moreover, the extent of an increase in differentiation between subsequent levels should in some way reflect the degree of complexity of the additional gene associations, with equality as an indication of lack of additional complexity by some standard. Such a differentiation measure must thus be based on a conceptual characterization of the complexity of gene associations. The existence of such a measure would not only facilitate experimental studies… 

It turned out that the large increases in differentiation between levels that were observed in the real data were not producible in numerous simulations of simple selection models, indicating that these models cannot explain the complexity of the real data. 

Proceeding from lower to higher levels of integration, one expects an increase in differentiation among populations simply because of the larger varietal potential inherent in more complex structures. 

Table 1 lists the distance matrix of pairwise distances…between stands and their mean as well as the symmetric population differentiation…SD and its components…j, both based on the elementary genic difference between genetic types, for each of three levels of integration: the gene-pool distance is the average of the six single-locus allelic distances; the single-locus diplophase distance is also the average over the loci; the multilocus diplophase distance. It is seen that for each pair of stands, all pairwise distances…increase considerably with the level of integration. 

Thus it appears that differentiation among populations with respect to their forms of gene association may be a normal occurrence. This insight questions the common practice of restricting the measurement of population differentiation to the allelic level (e.g. FST), thereby ignoring the considerable effects of gene association on population differentiation.

The authors then try to end the paper on a conservative, hedging note, perhaps to please reviewers:

This analysis is the first of its kind. Therefore, we cannot venture a prediction about whether the above findings on covariation between levels of integration constitute a general trend. It is conceivable, for example, that these findings are mainly determined by the conspicuously large polymorphism characteristic of the microsatellite markers used in this study. Other genetic markers may tell different stories.

Actually, there really is no logical reason to suppose that their findings are not generally applicable. It in fact makes perfect sense, as I (and others) have been arguing for years, that the correlation structure inherent in the genome is a general form of heritable genetic information above and beyond Fst, and that, therefore, this structure is an important part of genetic interests. There is no reason it must be limited to microsatellites; it is almost certainly an inherent, “emergent” characteristic of genetic information in all organisms. And, certainly, within and between human populations.

Therefore, it can be expected that genetic differentiation between human populations will be greater when overall structure (e.g., the combinations of coinherited alleles/genetic sequences) is considered, compared to Fst, and, that both Fst and genetic structure constitute genetic interests, both are important and both must be measured.

Genetic interests = Fst + Genetic Structure
And this paper is the initial step in the necessary quantification of genetic structure.
Yet more excerpts:

Conclusions: This new approach to the analysis of genetic differentiation among populations demonstrates that the consideration of gene associations within populations adds a new quality to studies on population differentiation that is overlooked when viewing only gene-pools. 

In general, traits are genetic only if they are inheritable, and the goal of inheritance analysis is to identify genes as the basic units of inheritance. The term genetic integration is used here to designate the combination or arrangement of these elementary objects “gene” into the haplotypes of gametes, into the genotypes at diploid (or polyploid) nuclei of diplophase individuals, or into the cytotypes of mitochondria or plastids, for example. 

At higher levels of genetic integration, where the objects of interest represent compositions of several individual genes together with their gene-types, association among gene-types becomes relevant for differentiation studies.

…neither the gene association within single loci (homologous association nor the gene association among loci (non-homologous association) is of the same form in any two stands, and in particular that association is present. Both the distances and the snail components show a much larger increase between the single-locus diplophase and the multilocus diplophase than between the gene-pool and the single-locus diplophase. 

Hence the non-homologous gene associations make a distinctly greater contribution to the differentiation than the homologous gene associations.

“Non-homologous gene associations” being a predominant component of what I refer to as “genetic structure.”

And consider the implications with respect for both EGI and parental kinship with intermarriage.

Genetic structure…here to stay.

New comments:

One question is whether the increase in genetic interests inherent between population (or individual) comparisons when taking genetic structure into account will be proportionately the same with increasing general genetic distance, or will the genetic structure differences increase proportionately with increasing genetic distance. For example, let’s hypothesize that genetic structure increases the genetic interest a Dane has with another Dane compared to a Greek by 50%, compared to allele-by-allele considerations. Will the increase in genetic interest of Dane vs. Nigerian also be 50%, or greater (it almost certainly could not be less). I hypothesize it would be greater, because the increase in allele-by-allele differences with greater genetic distance would lead to a proportionate increase in the genetic structure combination differences possible. Image ways of shuffling decks of cards where it is possible for the individual cards to differ between decks – the more individual card difference, the greater the number of novel card combinations between decks. This would of course need to be shown with the data (not that population geneticists would touch such a politically incorrect subject – they won’t even do genetic kinship studies). 
On a functional basis, one needs to consider epistasis. Certainly, there are cases where individual genes can influence phenotype; however, in the vast majority of cases, important phenotypic traits (the HBDers vaunted “form and function”) are affected by numbers of genes working together. This by the way is an important riposte to some of Dawkins’ more stupid extensions of his “selfish gene” meme, more properly, that should be plural, as in “selfish genes.” Or, perhaps, the “selfish genome.” In the end, selection acts upon the entire organism that is the product of all its (functional) genes. A given individual gene can of course affect the phenotype and influence that gene’s own selection, but even in that case, it does so in the context of the entire functional genome.
As I’ve written before, one cannot base genetic interests solely on “functional genes.” Putting aside that the distinction between functional and non-functional is becoming increasingly blurred due to findings that show that much of the “non-functional” genome actually does have function, the point is that even truly non-functional genes, if they vary in frequency between peoples, carry information on kinship and, even more to the point, as part of the distinctive genome, constitute a fraction of kinship, and thus have inherent value in this manner. After all, if genetic interests are based on genetic kinship, therefore all genes that constitute that kinship, as well as carry information that helps quantitate that kinship, have value. One can of course argue that functional genes that influence their own selection are of greater value on a “per gene” basis, but one cannot simply dismiss non-functional genes are being irrelevant to genetic interests.