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Group #1 - ANCESTRAL Y-SEARCH Study for the HAM Surname DNA Project

This Group has been tested as I1b

    GOAL:   To determine the possible ancestral origins for the HAM DNA Group #4.

Date:      January  17,  2007

The HAM DNA Group 4 Ancestral output from Dean McGee's Utility can be found here.


                                                                                                          Group 004

GOAL:   To determine the possible ancestral origins for the HAM DNA Group #4.

PROCEDURE:


    1) Run Dean McGee's Utility to determine the Genetic Distance for the Group.
    2) Determine the ancestral haplotype for the group by use of Genetic Distance sums.
         The largest sums for the most markers tested should indicate the most ancestral haplotype(s).
    3) Deduce the Ancestral Haplotype by study of the changing (or mutating) markers for the Group.
    4) Graph out the Ancestral Haplotype using PHYLIP to verify the age by comparison to the Group.
    5) Search the Y-Search database for matches to the ancestral haplotype.
         - From this search, report out the percentage matches that do not exist in the US.

I believe these results could then be used to provide some direction for locating ancestors in future research.


Step 1) Obtain Genetic Distance for Group #4, as given from Dean McGee's Utility:




HAM DNA Group #4 Genetic Distance SUMS
ID4
4
1
7
6

W
m
V
A
4
7
4
1
2

R
i
V
A
44176 WmVA 250
47412 RiVA 025
SUM:
0
0

Related Probably Related Possibly Related
FTDNA's Interpreting Genetic Distance for 12 Markers
FTDNA's Interpreting Genetic Distance for 25 Markers
FTDNA's Interpreting Genetic Distance for 37 Markers
- Infinite allele mutation model is used
- Values on the diagonal indicate number of markers tested

Step 2:  Determine the ancestral haplotype for the group by use of Genetic Distance sums.

Sorting the SUMS per participant in Group #4 is pretty easy, we only have two participants that match perfectly:


  Participant                       SUM     # of markers


44176  William  VA              0             25
47412 Richard  VA              0             25



The largest sums should indicate the most genetically distant, and therefore the further back in time it takes to reach the Most Recent Common Ancestor.  At this time, we have no more participants to take this line back further in time. Therefore, we could use either kit #44176 or kit #47412
for this study.

Kits
44176 and 47412 have the largest sums for Genetic Distance, which I am using as a definition for the term "Ancestral."

44176 and 47412 have at least 25 markers tested, which should be sufficient to examine for the Ancestral Haplotype.


Step 3:  Deduce the Ancestral Haplotype by study of the changing (or mutating) markers for the Group.

    We have the most ancient for the group, as determined by the sums from the Genetic Distance columns.
 Now, our task is to determine what the Ancestral haplotype should look like by comparing the mutating markers for these individuals.


 GROUP 4

  
 
               
3
9
3
3
9
0
1
9
 
3
9
1
3
8
5
a
3
8
5
b
4
2
6
3
8
8
4
3
9
3
8
9
1
3
9
2
3
8
9
2
4
5
8
4
5
9
a
4
5
9
b
4
5
5
4
5
4
4
4
7
4
3
7
4
4
8
4
4
9
4
6
4
a
4
6
4
b
4
6
4
c
4
6
4
d
4
6
0
G
A
T
A
H
4
Y
C
A
II
a
Y
C
A
II
b
4
5
6
6
0
7
5
7
6
5
7
0
C
D
Y
 a 
 C
 D
 Y
 b 
 4
 4
 2
4
3
8

44176
William HAM, Sr. (EST 1726 VA -  1799 SC)
13
23
15
11
12
14
11
13
13
12
11
29
18
10
10
11
11
25
15
21
29
11
16
16
17














47412
Richard HAM (Est 1660 England - BEF 1726 VA) 13
23
15
11
12
14
11
13
13
12
11
29
18
10
10
11
11
25
15
21
29
11
16
16
17
















Out of the first 25 markers, the markers that are mutating for 44176 and 47412 (indicated with a cyan background) are:
        (none yet determined)
The Mutating markers for these more distance kits:    

           ( We have no indication of mutating markers at this time.)


Kit #
DYSxx
DYSxx
DYSxx
44176
xx
 xx
xx
47412
xx
 xx
xx





In order to determine our Ancestral Haplotype, we will use what is most different for these three individuals and work our way up to 43250 (white background).  That is, we want to look for the markers that are different from the three colored in GREEN here.  We want to work toward the values for 27814, but keep in mind that we want to stay closer to the individuals with the green background.

First we can see that DYS19 is NOT mutating for 27814, but is only changing for one individual in green. We will use that value of "15" for DYS19 in our Ancestral Haplotype.
Next, we will select the value of 12 for DYS439, and so on.

Taking the values that are different for each of the rest of the mutating markers (cyan, above), then becomes:

                     
ANCESTRAL:           

           DYSxx   = xx
           DYSxx   = xx



ANCESTRAL     13    23    15    11    12    14    11    13    13    12    11    29    18    10    10   11    11    25    15    21   29    11    16    16    17  


Step  4:    Graph out the Ancestral Haplotype using PHYLIP to verify the age by comparison to the Group.

Input data for
Dean McGee's Utility for Group #4   with the inclusion of the ANCESTRAL Haplotype:

44176 RiVA    13    23    15    11    12    14    11    13    13    12    11    29    18    10    10    11    11    25    15    21    29    11    16    16    17 
47412 WmVA    13    23    15    11    12    14    11    13    13    12    11    29    18    10    10    11    11    25    15    21    29    11    16    16    17   
ANCESTRAL     13    23    15    11    12    14    11    13    13    12    11    29    18    10    10    11    11    25    15    21    29    11    16    16    17 



After running Dean McGee's Utility for Group #4 with the inclusion of the ANCESTRAL Haplotype, the PHYLIP compatible TMRCA table comes to:

3
44176_RiVA 350 0 350
47412_WmVA 350 350 0
 ANCESTRAL 0 350 350




And the resulting Graph (does not yet have a reasonable choice for the Ancestral Haplotype):

HAM DNA Group04 Ancestral Haplotype Group

This "ANCESTRAL" is exactly the same as kits 44176 and 47412, but the PHYLIP procedure wants to graph it out a little differently simply due to the order of data entry. 

This is not really far enough back in time, as we wanted something that would give us a range of about 700 years ago.

Having a at least one Haplotype, now use it for the Y-Search for matches to the Group #4 Haplotype.



Step 5:

    Search the YSEARCH Database (www.ysearch.org) for matches to this "Ancestral" Haplotype:

ANCESTRAL     13    23    15    11    12    14    11    13    13    12    11    29    18    10    10   11    11    25    15    21   29    11    16    16    17  


We do not have enough information about mutating markers in order to determine the Ancestral haplotype. However, in effect, we are looking for the location to match this Group #4 some 350 years ago.

Matching entered genetic markers on at least 25 markers, allowing a genetic distance of 1 per marker matched above 9
I am looking for about 1500 matches, in an effort to have reliable statistics.

This Y-Search on the "Ancestral" Haplotype, and got a search that yielded 1916 matches, using this search:

http://www.ysearch.org/search_results.asp?uid=&freeentry=true&L1=13&L2=23&L3=15&L4=0&L5=11&L6=12&L7=14&L8=11&L9=13&L10=13&L11=12&L12=11&L13=29&L14=18&L15=10&L16=10&L17=11&L18=11&L19=25&L20=15&L21=21&L22=29&L23=11&L24=16&L25=16&L26=17&L27=0&L28=0&L29=0&L30=0&L31=0&L32=0&L33=0&L34=0&L35=0&L36=0&L37=0&L38=0&L39=0&L40=0&L41=0&L54=0&L55=0&L56=0&L57=0&L58=0&L59=0&L60=0&L61=0&L62=0&L63=0&L42=0&L64=0&L65=0&L66=0&L67=0&L68=0&L69=0&L70=0&L71=0&L49=0&L72=0&L73=0&L51=0&L74=0&L75=0&L76=0&L77=0&L78=0&L79=0&L80=0&L43=0&L44=0&L45=0&L46=0&L47=0&L48=0&L50=0&L52=0&L53=0&L81=0&L82=0&L83=0&L84=0&L85=0&L86=0&L87=0&L88=0&L89=0&L90=0&L91=0&L92=0&L93=0&L94=0&L95=0&L96=0&L97=0&L98=0&L99=0&L100=0&min_markers=8&mismatches_max=0&mismatch_type=sliding&mismatches_sliding_starting_marker=9&haplo=&region=


I then searched through these matches for all of the "known" and NON-USA matches, and tallied up the totals (xxx were non-USA), then worked out percentages of where this "Ancestral" Haplotype should be found in the world.



The results:

1916 matches obtained.


  861 returned a Country other than the US or "unknown"

----------------------------------------------------------------------------------

England        354           41.1 %
Ireland           155           18.0 %
Scotland       139           16.1 %
Germany         71             8.3 %
Wales               28             3.3 %
France             23             2.7 %
Netherlands   14              1.6 %
Switzerland    11              1.3 %
Spain                  8              0.9 %
Canada              8              0.9 %
Poland               7              0.8 %
Bahamas          5               0.6 %
Russia               5               0.6 %
Italy                    4               0.5 %
Sweden            2               0.2 %
Denmark          2               0.2 %
Norway            2                0.2 %
                    ---------
                       834

OTHER (less than 1 % each):        27

Australia          2
Azores             2
Belgium           2
Denmark          2
Norway            2
Puerto Rico    2
Algeria             1
Albania            1
Barbados       1
Bosnia Herzegovina  1
Columbia       1
Chile               1
Croatia           1
Cuba              1
Czech Republic   1
Hungary        1
Serbia            1
Slovakia        1
Slovenia        1
Turkey           1
Ukraine         1



Presuming that we could determine something from these totals, I would guess that this group should be found mostly in England, with smaller portions from Ireland and Scotland. It would appear that they should be twice as likely to be from England than from either Ireland or Scotland, and nearly 5 times as likely to be from England than from Germany.

The problem that I am observing is the Genetic Distance, which appears to be larger than I would have wanted it to be. (Given the current search options from YSearch, I did not permit more than one mutation per marker, in an attempt to obtain some meaningful results. )

Problems appear to be lack of data, as I had to use
a genetic distance of 1 per marker matched above 9 markers.  It has occurred to me that the search may have to be repeated or corrected when more data becomes available.

Very similar results as Group #2 (R1b1c as opposed to I1a), until the list falls below England, Ireland, Scotland, and Germany. 
More differences from Group #2 appear when the distribution is listed within each country (below).  For example, this group appears to have some matches in the Netherlands, and in Switzerland, there is a concentration around Bern/Berne.

It is interesting that for these countries, many give city or county locations.  For example, we can almost see how many locations are in common for the majority matching in England, Ireland, or Scotland.


ENGLAND:

From the totals that I have for England, and without going to very much trouble of attempting to determine the name of the County for the cities, I get a rough account of the results that look something like this:

Worchestershire         26
Devonshire                  13
London                           9
Yorkshire                       8
Cornwall                        6
Kent                                5
Norfolk                           4
Suffolk                           4
Lancashire                   3
Leicestershire             3
Liverpool                      3
Northamptonshire     3
Sussex                          3
Warwickshire              3



So, it is apparent that from the locations in England, the most likely locations of origin should be closely matched by Worchestershire, followed next by Devonshire, London, Yorkshire, Cornwall, and so on.  Group #1 appears to be twice as likely to be from Worchestershire than Devonshire or London.

IRELAND:

From the results for Ireland, the obvious appears to be County Down, Tyrone, Ulster, and Northern Ireland having the largest totals.

The totals as I have them:

County Down          7
Tyrone                       7
Ulster                         7
Northern Ireland      6
County Antrim         4
County Cavan         4
County Cork           4
Dublin                       4
Donegal                   3



SCOTLAND:

The totals as I have them for Scotland:

Edinburgh         7
Glascow            7
Inverness          5
Argyllshire        4
Dumfriesshire   4
Perthshire         4
Aberdeen          3
Shetland Isles  3
Borders             2
Lanarkshire      2
Moray                 2


GERMANY

Hess/Hessen          5
Bavaria/Bayern      3
Schlesian/Silesia   3
Pommern                2
Rhineland               2
Wurtemberg           2


-----------------------------------------
WALES

Begelly                      3
Bala                            2
Caernarvonshire    2
Carmarthenshire   2


-----------------------------------------
FRANCE

Alsace            3
Ambert           1
Lorraine        1
Normandy    1
Picardie         1
Saint Hilaire  1

-----------------------------------------
NETHERLANDS (or Holland)

Amsterdam         1
Bathmen             1
Brouwershaven, Schown, Zeeland    1
Dordrecht           1
sHertogenbosch   1
Herwynen          1
Leiden                1
Westphalia        1


-----------------------------------------
SWITZERLAND

Wimmis, Bern/Berne        4
Langnau                              1
Langnau i.E., Bern            1
Schwarzenburg, Bern/Berne    1
Fullinsdorf                           1
Oberhof, Aargau                1
Palitinate                             1





 - Dave Hamm    Jan 17, 2007