For me, the topic of convergence in yDNA first came up early
in 2014. I had just posted a paper and
one of the comments was – “What about convergence?” I said to myself, “What convergence?” I admit I had to look up the topic.
Convergence: A
term used in genetic genealogy to describe the process whereby two different
haplotypes mutate over time to become identical or near identical resulting in
an accidental or coincidental match. - Turner A & Smolenyak M 2004.
My response back to the comment was - “All of the haplotypes
in my paper are unique.” My data did not
exhibit convergence.
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Convergence casts a shadow on genetic genealogy |
I started to poke around on the topic of convergence within
yDNA STR haplotypes and the immediate impression that I got was that folks were
ready to give up on STRs in favor of SNPs and the sky was falling. Chicken Little was running around in the
genetic genealogy circles. Here is a
small sample:
“Y-STRs are
effectively dead” - Dienekes Pontikos, 2011
“Convergence of Y
chromosome STR haplotypes from different SNP haplogroups compromises accuracy
of haplogroup prediction” – Wang, et al, 2013
Okay, convergence happens, but it’s an illusion.
Let’s take a big step backwards in this story. Did you know that most scientific papers
relating to genetic genealogy use 17 STR markers or less? Some use as few as 9 or 10. For any of you who ever took one of the
original 12 STR marker tests, you know that the results were essentially
useless for anything except deep haplogroup association and history.
Many researchers in the last couple of years are using the AmpFLSTR®
Yfiler® to get their 17 marker results.
This equipment is approved for forensic cases. Research papers are not forensic cases and
researchers don’t need to limit themselves to 17 markers. Thirty-seven marker yDNA tests have been
available since 2004.
Why does the number of STR markers matter? I’m going to release my inner math geek to
help explain. If we look at marker DYS19,
usually listed first in science papers and third in Family Tree DNA results, it
can have a value within the range of 7 to 22 across all haplogroups. Looking at R1b specifically, DYS19 ranges
from 10 to 17 and statistically at two standard deviations (2 sigma) the range
of values narrows to 13, 14 and 15. From
a probability point of view, there is a 1 in 3 chance that DYS19 will be 13, 14
or 15. Making the odds even better in
our favor, 95% of the time DYS19 for R1b will already be 13, 14 or 15. This means there is a 1 in 2 chance that
DYS19 could change to another value on its way to converging with another
haplotype.
Taking standard deviation into account to determine the
possible number of values for the STR markers and then multiplying each
probability gives the odds that a haplotype could converge.
STR
|
DYS393
|
DYS390
|
DYS19
|
DYS391
|
DYS385a
|
DYS385b
|
DYS426
|
DYS388
|
DYS439
|
DYS389i
|
DYS392
|
DYS389ii
|
Total
|
# of possible
marker values
|
2
|
4
|
2
|
2
|
2
|
4
|
1
|
1
|
2
|
2
|
2
|
2
|
4096
|
There is a 1 in 4096 chance that two R1b 12 marker
haplotypes could converge. This is not
the probability that one marker will change. This is the probability that all 12 markers
will change enough to match another haplotype.
These are very good odds and the reason why a 12-marker test is
practically useless.
With a high probability that 12 STR markers will converge, haplotypes
start to blend together. Two different
haplogroups or family lines will appear to be the same. Converging also means that when we calculate
the time to the most recent common ancestor (TMRCA), it will look like less
time has passed. Convergence makes a 12-marker
test result unusable for genealogical matching, haplogroup prediction and TMRCA
calculations. The Chicken Littles are
correct, we have a problem with 12 marker STR results.
What about 17 markers, a quasi-industry standard for science
papers? Taking the same approach with statistics
and probability, a 17-marker yDNA R1b result has a 1 in 2 million chance of
converging with another haplotype. Each
haplogroup has slightly different odds.
There is a 1 in 500,000 chance of an R1a 17 marker haplotype converging. Those odds are better than any lottery. Convergence is still a problem at 17 markers.
When Dienekes Pontikos proclaimed the death of yDNA STRs, he
was commenting on the attempt to get good TMRCA dates from 10-marker
results. I agree, you can’t get valid
TMRCA dates from 10-markers. When Wang,
et al, determined that convergence compromises haplogroup prediction, they were
correct, 17 marker haplotypes can converge to make one haplogroup look like
another.
In a quick analysis of 4,300 unique 37-marker R1b haplotypes,
the average genetic distance is 17 steps for 37 markers. That means there are 17 mutations required
for convergence in a 37-marker haplotype.
Nearly half of the markers in the haplotypes would need to change. When we look at the probability of 25-marker
haplotype convergence, the chances are 1 in 84 million. Considering there are about 3.6 billion men
on the planet, one in 84 million is still in the realm of possibility. By the time we get to 37-markers, the odds
are 1 in 49 trillion.
There is a 1 in 49 trillion
chance that all the necessary mutations will occur in order for two 37-marker
haplotypes to converge. The odds are likely
much higher. I’ve only looked at the probable
values for each marker and I haven’t taken into account the STR mutation rates,
the possibility that a marker will change over time.
There is essentially no such thing as convergence when 37 or
more markers are tested and researched.
If you eliminate the possibility of convergence by using 37 STR markers,
then immediately TMRCA calculation become more accurate and haplotypes from
different haplogroups no longer resemble each other. The reports of the death of yDNA STR results have
been greatly exaggerated.
I can’t tell you why researchers are currently stuck on 17
markers. I can tell you that any research
using less than 37 markers runs the risk of convergence in their data, which in
turn could lead to the wrong conclusions.
I still consider genetic genealogy to be in its infancy. Every month new research papers are published
and the new concepts introduced are latched onto immediately. It is understandable that papers from over a
decade ago used a dozen STRs and a handful of SNPs, that was the height of
technology. If the latest technology and
best data are not being used in today’s research papers, is that equivalent to
scientific negligence? Or, am I missing
something and this is a case of scientific ignorance on my part?