Grab the Gauge
08-17-2016, 04:37 AM
http://www.unz.com/gnxp/middle-eastern-populations-have-higher-recessive-disease-load/
Aside from the the random wrong historical inference stuff, the paper is kind of a big deal (I think Nature Genetics worthy, but I don’t know anything about this stuff in regards to publications). It confirms in the broadest outlines a lot of what we knew. The further you go from Africa the less genetically diverse populations get when it comes to looking at polymorphism diversity. Native Americans have fewer segregating polymorphisms than Eurasian populations, for example. One way to model this is as serial bottlenecks out of Africa. I think that’s too simple of a picture, as there has been a lot of gene flow and admixture over the last 10,000 years, but on the coarsest of all scales it’s not totally misleading.
But a peculiar aspect of these dynamics is that when you look at runs of homozygosity in the genome, which usually measure more recent inbreeding, the Middle East and South Asia tends to have higher lower genetic diversity. To get a sense of South Asian populations, you can read The promise of disease gene discovery in South Asia. Because of caste/jati endogamy a lot of the South Asian groups have less genetic diversity than you might expect. This has disease implications.
Middle Eastern, North African, and Pakistani populations are even more extreme. You can see it in the figure above. Across short runs of homozogosity the results converge onto what you’d expect, roughly. But Middle Eastern populations are a huge anomaly at long runs. That’s because of this:
From 20–50% of all marriages in the GME are consanguineous (as compared with <0.2% in the Americas and Western Europe)1, 2, 3, with the majority between first cousins. This roughly 100-fold higher rate of consanguinity has correlated with roughly a doubling of the rate of recessive Mendelian disease19, 20. European, African, and East Asian 1000 Genomes Project populations all had medians for the estimated inbreeding coefficient (F) of ~0.005, whereas GME F values ranged from 0.059 to 0.098, with high variance within each population (Fig. 2c). Thus, measured F values were approximately 10- to 20-fold higher in GME populations, reflecting the shared genomic blocks common to all human populations. F values were dominated by structure from the immediate family rather than historical or population-wide data trends (Supplementary Fig. 8). Examination of the larger set of 1,794 exomes that included many parent–child trios also showed an overwhelming influence of structure from the immediate family, with offspring from first-cousin marriages displaying higher F values than those from non-consanguineous marriages (Fig. 2d).
The authors masked alleles which were part of the reason that individuals were included in the data set in the first place (to prevent ascertainment bias). Rather, they were focused on genome-wide patterns of loss of function and derived alleles. Because they were looking at many low frequency variants naturally they found a lot of new variation, totally unobserved in European dominated genetic data sets. This is why bringing genomics to the world is kind of a big deal.
For me this was the most interesting, and sad, result:
Despite millennia of elevated rates of consanguinity in the GME, we detected no evidence for purging of recessive alleles. Instead, we detected large, rare homozygous blocks, distinct from the small homozygous blocks found in other populations, supporting the occurrence of recent consanguineous matings and allowing the identification of genes harboring putatively high-impact homozygous variants in healthy humans from this population. Applying the GME Variome to future sequencing projects for subjects originating from the GME could aid in the identification of causative genes with recessive variants across all classes of disease. The GME Variome is a publicly accessible resource that will facilitate a broad range of genomic studies in the GME and globally.
The theory is simple. If you have inbreeding, you bring together deleterious recessive alleles, and so they get exposed to selection. In this way you can purge the segregating genetic load. It works with plants. But humans, and complex animals in general, are not plants. More precisely the authors “compared the distributions of derived allele frequencies (DAFs) in GME and 1000 Genomes Project populations.” If the load was being purged the frequency of deleterious alleles should be lower in the inbreeding populations. It wasn’t.
Aside from the the random wrong historical inference stuff, the paper is kind of a big deal (I think Nature Genetics worthy, but I don’t know anything about this stuff in regards to publications). It confirms in the broadest outlines a lot of what we knew. The further you go from Africa the less genetically diverse populations get when it comes to looking at polymorphism diversity. Native Americans have fewer segregating polymorphisms than Eurasian populations, for example. One way to model this is as serial bottlenecks out of Africa. I think that’s too simple of a picture, as there has been a lot of gene flow and admixture over the last 10,000 years, but on the coarsest of all scales it’s not totally misleading.
But a peculiar aspect of these dynamics is that when you look at runs of homozygosity in the genome, which usually measure more recent inbreeding, the Middle East and South Asia tends to have higher lower genetic diversity. To get a sense of South Asian populations, you can read The promise of disease gene discovery in South Asia. Because of caste/jati endogamy a lot of the South Asian groups have less genetic diversity than you might expect. This has disease implications.
Middle Eastern, North African, and Pakistani populations are even more extreme. You can see it in the figure above. Across short runs of homozogosity the results converge onto what you’d expect, roughly. But Middle Eastern populations are a huge anomaly at long runs. That’s because of this:
From 20–50% of all marriages in the GME are consanguineous (as compared with <0.2% in the Americas and Western Europe)1, 2, 3, with the majority between first cousins. This roughly 100-fold higher rate of consanguinity has correlated with roughly a doubling of the rate of recessive Mendelian disease19, 20. European, African, and East Asian 1000 Genomes Project populations all had medians for the estimated inbreeding coefficient (F) of ~0.005, whereas GME F values ranged from 0.059 to 0.098, with high variance within each population (Fig. 2c). Thus, measured F values were approximately 10- to 20-fold higher in GME populations, reflecting the shared genomic blocks common to all human populations. F values were dominated by structure from the immediate family rather than historical or population-wide data trends (Supplementary Fig. 8). Examination of the larger set of 1,794 exomes that included many parent–child trios also showed an overwhelming influence of structure from the immediate family, with offspring from first-cousin marriages displaying higher F values than those from non-consanguineous marriages (Fig. 2d).
The authors masked alleles which were part of the reason that individuals were included in the data set in the first place (to prevent ascertainment bias). Rather, they were focused on genome-wide patterns of loss of function and derived alleles. Because they were looking at many low frequency variants naturally they found a lot of new variation, totally unobserved in European dominated genetic data sets. This is why bringing genomics to the world is kind of a big deal.
For me this was the most interesting, and sad, result:
Despite millennia of elevated rates of consanguinity in the GME, we detected no evidence for purging of recessive alleles. Instead, we detected large, rare homozygous blocks, distinct from the small homozygous blocks found in other populations, supporting the occurrence of recent consanguineous matings and allowing the identification of genes harboring putatively high-impact homozygous variants in healthy humans from this population. Applying the GME Variome to future sequencing projects for subjects originating from the GME could aid in the identification of causative genes with recessive variants across all classes of disease. The GME Variome is a publicly accessible resource that will facilitate a broad range of genomic studies in the GME and globally.
The theory is simple. If you have inbreeding, you bring together deleterious recessive alleles, and so they get exposed to selection. In this way you can purge the segregating genetic load. It works with plants. But humans, and complex animals in general, are not plants. More precisely the authors “compared the distributions of derived allele frequencies (DAFs) in GME and 1000 Genomes Project populations.” If the load was being purged the frequency of deleterious alleles should be lower in the inbreeding populations. It wasn’t.