Tag Archives: south asia

Outbreeding Works in a Single Generation

As I have mentioned before, cousin marriages were fairly common among my family. My parents are first cousins. So are my father’s parents. My mother’s parents are second cousins once removed. So instead of 32 great-great-great grandparents, I have only about 18.

Since my wife and I are not related, I wondered how my inbred genome had transmitted to our daughter.

Using David Pike’s ROH utility, I computed the regions of homozygosity for my parents, me, my wife, and my daughter, all tested by 23andme.

I used the default settings for the utility. The total Mb gives the total size in megabases of the long autosomal regions where both alleles are the same. The longest ROH gives the size of the longest such region. Percent Homozygous is the percentage of the genome where the two alleles are the same.

I included the worst chromosome column because of my chromosome 9, which is beyond crazy. This column gives the percent homozygosity of the worst chromosome.

Person Total Mb Longest ROH (Mb) % Homozygous Worst chromosome (%)
Dad 297.45 57.4 72.498% 76.921%
Mom 112.13 22.99 70.662% 79.802%
Me 402.78 71.38 73.588% 93.542%
Wife 37.33 9.64 70.003% 72.411%
Daughter 42.40 8.82 69.936% 71.759%

As you can see, my Dad has higher levels of homozygosity than my Mom as expected and I have the highest levels. My wife is not inbred at all and our daughter has ROH results about the same as my wife. So one generation of marrying someone unrelated, even if from the same/similar ethnicity, has removed all the long runs of homozygosity bred over generations. Good news!

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Inbreeding

I have found out I am actually from West Virginia. Ok, I am just joking.

I knew that my family had a history of marriages among relatives. After all I have only 10 great-great-grandparents instead of the usual 16. With my genome in hand, I set about to quantify the inbreeding.

First, I used David Pike’s Homozygosity tool. It analyzes your genome to find significant runs where the same haplotype is inherited from both parents. Large portions of the human genome are like that. The length of these homozygous regions, however, varies depending on the relation of your parents. If your parents are closely related (first cousins in my case), then you will have longer runs. If your parents are distantly related, then over the generations those genes have had a chance to recombine and so you will have shorter runs that are homozygous.

Overall, the percentage of my autosomal (i.e. on chromosomes 1-22) SNPs that are homozygous is 71.767 and I have 41 runs of homozygosity (ROH) of length at least 200. Here are some of my longest runs:

  • Chr 1 has a ROH of length 6009 (30.95 Mb)
  • Chr 8 has a ROH of length 5819 (33.00 Mb)
  • Chr 9 has a ROH of length 5877 (57.81 Mb)
  • Chr 9 has a ROH of length 5941 (24.38 Mb)

Let’s look at my homozygosity percentage by chromosome.

Chr 1: 71.734 %
Chr 2: 69.952 %
Chr 3: 65.741 %
Chr 4: 71.563 %
Chr 5: 69.270 %
Chr 6: 76.025 %
Chr 7: 69.445 %
Chr 8: 72.690 %
Chr 9: 93.323 %
Chr 10: 69.765 %
Chr 11: 71.866 %
Chr 12: 68.443 %
Chr 13: 74.184 %
Chr 14: 68.571 %
Chr 15: 73.087 %
Chr 16: 66.541 %
Chr 17: 77.555 %
Chr 18: 67.763 %
Chr 19: 66.267 %
Chr 20: 66.228 %
Chr 21: 79.902 %
Chr 22: 69.896 %

A majority of chromosomes seem to have reasonable percentages while chromosomes 4, 6, 8, 11, 13, 15, 17 and 21 are high. However, chromosome 9 is really weird: It is 93.323% homozygous.

David Pike writes that:

So far the largest ROHs in 23andMe V2 data that I am aware of consist of:

  • 9191 consecutive tested SNPs, corresponding to a DNA segment of length 49.99 Mb.
  • 6129 consecutive tested SNPs, corresponding to a DNA segment of length 39.05 Mb.
  • 5594 consecutive tested SNPs, corresponding to a DNA segment of length 28.95 Mb.
  • 4644 consecutive tested SNPs, corresponding to a DNA segment of length 27.71 Mb.

The highest percentage for overall autosomal homozygosity that I have so far seen from 23andMe V2 data is 71.763%.

As you can see, I am an extreme case.

A number of members at DNA Forums reported their homozygous percentage. Of all those listed, mine is the 2nd highest.

According to the paper Genomic Runs of Homozygosity Record Population History and Consanguinity:

South/Central Asians and West Asians have more than three times as many ROH in all categories over 4 Mb long than sub-Saharan Africans and other Eurasians. 19% of individuals from these populations have ROH over 16 Mb in length, consistent with the high prevalence of consanguineous marriage (marriage between individuals who are second cousins or closer) in these populations.

My total ROH length (segments > 0.5Mb) is about 282Mb which is about 1.2 standard deviations above the Central/South Asian sample mean in that paper. But I am more than 1.7 standard deviations above the mean for longer segments (>5Mb).

Let’s take a look at a graph from the paper’s supplemental material which plots total ROH length versus number of homozygous segments:

My inbreeding coefficient based on the length of long (>5Mb) runs of homozygosity in my genome (fROH5) is about 0.11 while the average in the Central and South Asian sample for the HGDP dataset is 0.015 (not directly comparable due to different number of SNPs used to calculate).

Finally, I used Plink to calculate my inbreeding coefficient F using all the South Asians from my reference datasets. That coefficient comes out to be 0.1184.

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Harappa Ancestry Project

I have become interested (some would say obsessed) with genetics recently. I wrote about getting my DNA test done and there’s a lot more about my own results that I plan to bore you with.

One fun application of genetic testing is inferring ancestry: Which ancestral group are you descended from? Can we estimate the admixture of the different population groups you are descended from?

Most DNA testing companies provide information about ancestry and genetic genealogy has taken off. With several genome databases (HapMap, HGDP, etc) and software (like plink, admixture, Structure) publicly available, the days of the genome bloggers are here. And I am trying to be the latest one.

In starting this project, I have been inspired by the Dodecad Ancestry Project by Dienekes Pontikos and Eurogenes Ancestry Project by David Wesolowski. The catalyst for this project was my friend Razib who I bug whenever I need to talk genetics.

What is Harappa Ancestry Project?
It is a project to analyze (autosomal) genetic data of participants of South Asian origin for the purpose of providing detailed ancestry information. So the focus of the project is on South Asians: Indians, Pakistanis, Bangladeshis and Sri Lankans.

The project will collect 23andme raw genetic data from participants to better understand the ancestry relationships of different South Asian ethnicities.

I have named it after Harappa, an archaeological site of the Indus Valley Civilization in Punjab, Pakistan.

Participation
People of South Asian origin, or from neighboring countries, are eligible to participate. The list of countries of origin I am accepting are as follows:

  • Afghanistan
  • Bangladesh
  • Bhutan
  • Burma
  • India
  • Iran
  • Maldives
  • Nepal
  • Pakistan
  • Sri Lanka
  • Tibet

Right now, I am only accepting raw data samples from people who have tested with 23andme.

Please do not send samples from close relatives. I define close relatives as 2nd cousins or closer. If you have data from yourself and your parents, it might be better to send the samples from your parents (assuming they are not related to each other) and not send your own sample.

If you are unsure if you are eligible to participate, please send me an email (harappa@zackvision.com) to inquire about it before sending off your raw data.

What to send?
Please send your All DNA raw data text file (zipped is better) downloaded from 23andme to harappa@zackvision.com along with ancestral background information about you and all four of your grandparents. Background information would include where they were born, mother tongue, caste/community to which they belonged, etc. Please provide as much ancestry information as possible and try to be specific. Do especially include information about any ancestry from outside South Asia.

Data Privacy
The raw genetic data and ancestry information that you send me will not be shared with anyone.

Your data will be used only for ancestry analysis. No analysis of physical or health/medical traits will be performed.

The individual ancestry analysis published on this blog will be done using an ID of the form HRPnnnn known to only you and me.

What do you get?
All results of ancestry analysis (individual and group) will be posted on this blog under the Harappa Ancestry Project category. This will include admixture analysis as well as clustering into population groups etc.

I suggest you read about Dienekes’ analysis on South Asians for an idea about what to expect.

You can access all blog posts related to this project from the Harappa Ancestry Project link on the navigation menu on every page of my website. You can also subscribe to the project feed.

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