Genetic Genealogy A Report on The CLOUD DNA Project. 1.Our Data Examined 2.Intro to Genetic Genealogy & DNA Genealogical DNA and its Components 4.Examining & Interpreting DNA Data 5.Drawing for Door Prize

DNA in Genealogy (Genetic Genealogy) What is it? –A new & exciting field of science. –An adjunct to traditional genealogy (not stand-alone proof). What can it do? –Help break down ancestral brick walls. –Verify lineages. –Validate documentation. –Show who you’re NOT related to (eliminate unnecessary time and money following ‘unrelated’ leads.) –Indicate a common ancestor with another person. –Predict a range of time when the common ancestor lived.

mtDNA – traces maternal line. Y-DNA – traces paternal line. SNP – traces deep ancestry. STR – traces recent ancestry.

DNA Used for Genealogy 1.mtDNA – passed from a mother to her children. –Changes too slowly to be useful for recent relationships. –Woman’s surname changes, so maternal line is more difficult to trace. 2.Y-DNA – passed from a father to his son. –Changes often enough to be used for recent relationships. –Father’s surname passed through generations, making paternal line easier to trace.

The DNA Data consists of: –Kit number –Surname –Haplogroup (SNP – deep ancestry) –Haplotype (STR – recent ancestry)

father grand- father great- grand- father paternal line Y-DNA maternal line mtDNA sondaughter great- grand- mother grand- mother mother (Common Surname)(Surname changes)

Interpreting the Data

Required information: Pedigrees of all lines: as much as is known as accurate as possible dates places spouses DNA data

Understanding the Data Kit number Surname Haplogroup DYS# – aka marker or locus (locii) Alleles – aka markers Family Group – assigned by project administrator SNP (slow – deep ancestry) STR (faster – recent ancestry)

Interpreting the Data Family Groups – assigned by project administrator (using DNA & Pedigree)

Interpreting the Data Family Groups – assigned by project administrator (using DNA & pedigree) Group usually has Common Pedigree or Surname.

Interpreting the Data Family groups – assigned by project administrator (arbitrary ? pedigree ?) Usually common surname or pedigree. DNA data – same haplogroup

Interpreting the Data Family groups – assigned by project administrator (arbitrary ? pedigree ?) Usually common surname or pedigree. DNA data – haplotypes or “signatures” – and same haplogroup Red haplogroup – deduced from haplotype Green haplogroup – confirmed by SNP test

Interpreting the Data Family groups – assigned by project administrator (use DNA data or pedigree ?) Usually common surname or pedigree. DNA data – haplotypes or “patrilineal signatures”

Interpreting the Data Within the same haplogroup – look for similar – and different – allele values. These are the same – probably inherited from ancient ancestor.

Interpreting the Data Within the same haplogroup – look for similar – and different – allele values. These are different – they either signal a mutation at a common ancestor’s birth or a mutation at the birth of the person tested. “Triangulation” needed to find where mutation occurred.

Triangulation TomDickHarry Tom, Dick & Harry belong to a DNA surname project (and appear to share the same modal haplotype – pink).

Triangulation TomDickHarry The results come in and – Tom and Harry have the same mutation.

Triangulation Tom Dick Harry They may share a common ancestor, but – not with Dick. ? ? ? ? ??

Triangulation Tom Dick Harry ?? ? ? ? More information is needed to resolve Tom and Harry’s MRCA and their MRCA with Dick. ??

Interpreting the Data Within the same haplogroup – look for similar – and different – allele values * Note difference between haplogroups R1b1 and I2b (see values in pink). (16 markers are different – more than 4 or 5 markers different – on 25 markers – implies no relationship.) But, we already knew that, didn’t we? R1b and I 2b are different haplogroups and cannot be related.

Interpreting the Data Does this mean that the line of Ruben is not descended from a CLOUD? NO – it just means this line descends from different Cloud family line than that of William Cloud the immigrant. A surname is a relatively recent, arbitrary and artificial means of identifying family lines. The line of William may have gotten it 500 or 600 years ago. We don’t know when the line of Ruben got it, or from whom. In our society, the surname simply represents patrilinear descent. Those that descend from the women in our line won’t have the surname.

Interpreting the Data We have two interesting and unique examples of non-surname participants in the Cloud DNA Project.

Interpreting the Data We have two interesting and unique examples of non-surname participants in the Cloud DNA Project. The oral history of the line of Robert Cloud said that Robert’s mother gave him her maiden name of Cloud rather than that of the man who got her pregnant.

Interpreting the Data We have two interesting and unique examples of non-surname participants in the Cloud DNA Project. A 12-marker test was enough to prove her line was NOT related to the Cloud families living in the area – adding support to their oral history. A difference of 2 or more at 12 markers implies no relationship. (12/12 or 11/12 means a relationship MAY exist.) This 7/12 or 6/12 match (or mismatch) proves NO relation to the CLOUD lines that lived in the area at the time.

Interpreting the Data We have two interesting and unique examples of non-surname participants in the Cloud DNA Project. A 12-marker test was enough to prove her line was NOT related to the Cloud families living in the area – adding support to their oral history. Does this mean they are not Clouds ? NO – it only means they acquired the CLOUD surname more recently than some other groups. It also implies that their earlier patrilinear descent came through a different surname.

Interpreting the Data We have two interesting and unique examples of non-surname participants in the Cloud DNA Project. Next – The Rhinehart family suspected there might have been an adoption or other event based on numerous circumstances they had observed.

Interpreting the Data We have two interesting and unique examples of non-surname participants in the Cloud DNA Project. Their DNA test turned out to be a perfect match for several members of the CLOUD project. They match out to 67 markers, implying that they almost certainly descend from a CLOUD ancestor from the line of William the immigrant. Because they appear to be descended from the line of either Joseph CLOUD (b PA) and/or of William CLOUD the immigrant, they were invited to join our Project.

Interpreting the Data Remember DYS-389i and 389ii ? These two markers must be interpreted differently than the others. The second part of this marker is additive with the first. DYS-389i DYS-389ii 13 DYS-389ii =

Interpreting the Data Remember DYS-389i and 389ii ? These two markers must be interpreted differently than the others. The second part of this marker is additive with the first. DYS-389iDYS-389ii 1329 Some companies give the allele values without adding them: DYS-389iDYS-389ii FTDNA Alternate( = 29 )

DYS-389i & ii (cont.) FTDNAAlternate R1b Modal Our 1 st mutation Our 2 nd mutation ii lost 1 16 to 15 i gained 1 13 to 14 It is a two-step mutation from R1b Modal of to

Interpreting the Data Let’s continue examining the data.

Interpreting the Data The R1b modal value for DYS-389i - ii is ( ). Two members of the William group are ( ), a 1-step mutation from R1b modal. The majority of the William-the-immigrant group are ( ), a 2-step mutation from R1b modal. The most likely explanation is the two lines with descend from a line that experienced the first mutation (DYS-389-ii from 16 to 15) and the others are from a later line that experienced the additional mutation to (389-i 13 to 14). It is less likely one or more of the lines experienced a mutation in parallel with another, creating a separate signature for both of their separate branches ( )

Examine a hypothetical scenario. Show problems that can occur.

Interpreting the Data Mutations passed to descendants

Interpreting the Data Parallel Mutations

Interpreting the Data Typical Application Missing (unknown) Links Examples of Inconclusive Data Identical Signatures (haplotypes) – implies wrong MRCASimilar Mutations –can imply wrong Ancestor

The End (almost)

Resources The Cloud Family Association Home Page The Cloud Surname DNA Project website Cloud DNA Project The Family Tree DNA website The Cloud Family forum: ISOGG – International Society of Genetic Genealogy

Resources The Cloud Family Association Home Page The Cloud Surname DNA Project website Cloud DNA Project The Family Tree DNA website The Cloud Family forum: ISOGG – International Society of Genetic Genealogy

Resources The Cloud Family Association Home Page The Cloud Surname DNA Project website Cloud DNA Project The Family Tree DNA website The Cloud Family forum: ISOGG – International Society of Genetic Genealogy

Resources The Cloud Family Association Home Page The Cloud Surname DNA Project website Cloud DNA Project The Family Tree DNA website The Cloud Family forum: ISOGG – International Society of Genetic Genealogy

Resources The Cloud Family Association Home Page The Cloud Surname DNA Project website Cloud DNA Project The Family Tree DNA website The Cloud Family forum: ISOGG – International Society of Genetic Genealogy

Resources The Cloud Family Association Home Page The Cloud Surname DNA Project website Cloud DNA Project The Family Tree DNA website The Cloud Family forum: ISOGG – International Society of Genetic Genealogy

Genetic Genealogy A Report on The CLOUD DNA Project. 1.Our Data Examined 2.Intro to Genetic Genealogy & DNA Genealogical DNA and its Components 4.Examining & Interpreting DNA Data 5.Drawing for Door Prize