New discoveries overturn the familiar adage that X-DNA is usually from a farther back ancestor than autosomal DNA

As of today, you can test the new discoveries against the old adage by comparing any amount of X-DNA to the same amount of autosomal DNA.

Two months ago I discussed findings suggesting that shared DNA on the X Chromosome is normally more recent than autosomal DNA (atDNA) that you share with your DNA matches. What I had seen in the data was that, for any degree of relationship, people don’t typically share more X-DNA than atDNA. I realized that the X Chromosome simply isn’t big enough to outlast all atDNA combined.

Since a whole X Chromosome copy is passed from fathers to daughters and since X-DNA can’t be passed from fathers to sons, the X Chromosome has fewer opportunities for recombination than atDNA. Despite the fact that Chromosome 1 is over 1.5x larger than the X Chromosome, we might expect X-DNA to typically be shared from a farther back ancestor than DNA from Chromosome 1. And so we would’ve been reasonable to say something like “X-DNA outlasts DNA from any one autosome,” although that would’ve been a wild guess. It turns out that we would’ve been right, although probably not in the case of two male DNA testers.

But it’s a huge leap to go from the above statement to saying that X-DNA usually outlasts DNA from all atDNA combined. And it’s incorrect. You can think about it like this: 182 cMs of X-DNA at 23andMe is a whole copy of the X Chromosome. More often than not, when you share that much X-DNA with someone they’re going to be a close family member. Conversely, 182 cMs of atDNA is usually a 2nd cousin or 2nd cousin once removed.

As of today, you have the ability to test the new theory against the old adage. Today I have released a new relationship predictor for X-DNA only.

You can check every value, from 364 cMs of X-DNA shared between two full-sisters all the way down to 8 cMs shared. Normally, for an atDNA predictor you’d want to use one with population weights. But, since I haven’t included population weights in the new X-DNA predictor, you’ll now want to use the unweighted atDNA predictor for any comparisons.

Please note that the X-DNA probabilities come from data in which a match may or not have shared atDNA. This is not a predictor built solely for matches who share X-DNA but no atDNA, although it will also work in that scenario. It would be useful to have a separate relationship predictor for matches who share X-DNA but no atDNA, but there isn’t a relationship prediction tool for that yet.

The data used for these predictions came from Caballero et al. (2019). In this case, the refined genetic map of Bhérer et al. (2017) was used as well as the crossover interference parameters of Campbell et al. (2015).

Although I built the X-DNA predictor mostly for the purpose of testing whether X-DNA or atDNA was usually from a more distant ancestor, the tool will also be useful for determining which relationship types are most probable for your X-DNA matches. While atDNA is more useful for such purposes, more information is always better. It’s likely that a combination of X-DNA probabilities and atDNA probabilities, where the atDNA probabilities were given more weight, would result in the best predictions. This is a scenario in which we could be applying machine learning. Just one word of caution: Because of the large variability of the X Chromosome, it’s more probable that a relationship type will have approximately zero probability, despite being possible. This is also possible with atDNA, but not as likely.

I hope you enjoy comparing the new X-DNA predictions with those of the unweighted atDNA predictor. I’d be glad to hear what you find. Can you find a cM value for which X-DNA is usually from a farther back ancestor or ancestor pair than atDNA?

The tools available that use the same peer-reviewed data source are as follows:

DNA-Sci — advancing the science of relationship predictions. Feel free to ask a question or leave a comment. And make sure to check out these ranges of shared X-DNA, shared atDNA percentages, and shared atDNA centiMorgans. Or, try a tool that lets you find the amount of an ancestor’s DNA you cover when combining multiple kits. I also have some older articles that are only on Medium.