Logo: © Ancestry.com Operations, Inc. Used for editorial purposes. Source: ancestry.com
If you have taken an AncestryDNA test and linked it to a family tree, you have almost certainly encountered ThruLines — Ancestry’s tool for suggesting how your DNA matches might connect to ancestors already in your tree. When it works well, ThruLines is genuinely impressive: it can surface a potential ancestor you had never considered, organize dozens of DNA matches under a single common ancestor hypothesis, and give you a clear research lead to pursue. When it works poorly — and it frequently does — it can send you confidently down entirely the wrong branch of your family tree, armed with a convincing-looking diagram built on borrowed errors from other people’s unsourced trees.
Understanding exactly what ThruLines is, how it generates its hypotheses, where it succeeds, and where it systematically fails is essential for any intermediate genealogist using AncestryDNA as a research tool. ThruLines is one of the most powerful features in consumer genetic genealogy — and one of the most frequently misunderstood.
What ThruLines Actually Is
ThruLines is a hypothesis-generating tool. Ancestry is explicit about this in its own documentation: ThruLines shows you how you[1] may be related to your DNA matches. It is not proof of relationship. It does not analyze DNA segments. It does not verify the accuracy of the trees it draws on. It is, at its core, a sophisticated pattern-matching algorithm that compares your family tree against your DNA matches’ family trees — and against all searchable public trees in Ancestry’s database — looking for overlapping ancestors.
When ThruLines finds that multiple DNA matches all have the same person in their trees, and that person could plausibly connect to someone already in your tree, it surfaces that person as a “Potential Ancestor” — presented in a visual diagram showing the proposed relationship path. Solid lines in the diagram represent relationships you have documented in your own tree; dotted lines represent proposed connections[2] drawn from other users’ trees.
The more DNA matches that trace independently to the same proposed ancestor, the stronger the ThruLines suggestion tends to be. A ThruLines card showing fifteen DNA matches all descending from the same great-great-grandparent is a much more compelling hypothesis than one showing a single match descending through a chain of dotted lines. But in both cases, it remains a hypothesis — a research lead, not a conclusion.
🔍 What ThruLines Does Well
Used correctly, ThruLines is one of the most practically useful features in consumer genetic genealogy, and nothing quite like it exists at any other testing company. Its core strengths are worth understanding clearly.
Organizing matches by ancestor. For researchers with thousands of DNA matches — most active AncestryDNA users — the match list is an overwhelming wall of names. ThruLines imposes structure on that chaos by grouping matches under shared ancestor hypotheses. Seeing thirty matches organized under a single proposed great-great-grandparent tells you immediately which corner of your family tree a cluster of matches likely connects to, even before you have verified the specific ancestor.
Surfacing potential ancestors. ThruLines can propose ancestors you had never encountered in your own research, drawn from the overlap of your matches’ trees. When those proposals are supported by multiple independent matches and corroborated by documentary evidence, they can represent genuine discoveries — new ancestors identified through the convergence of genetic and documentary evidence from multiple researchers working independently.
Identifying research priorities. A ThruLines card with many matches pointing to a specific ancestor tells you where other researchers have concentrated effort — and therefore where records are likely to be more thoroughly documented. It is a useful guide to where collaborative genealogical work has already been done, even if you need to verify every connection independently.
Cross-referencing with SideView. AncestryDNA’s SideView technology assigns[3] each DNA match to either your maternal or paternal side, even without a parent having tested. Combined with ThruLines, this allows researchers to quickly identify whether a proposed ancestor connection is on the expected side of the family — a useful first-level sanity check on a ThruLines hypothesis.
Where ThruLines Falls Short
ThruLines’ limitations are as important to understand as its strengths. Several structural problems affect its reliability in ways that intermediate researchers need to internalize.
Garbage in, garbage out. ThruLines is entirely dependent on the accuracy of the family trees it draws on — your tree, your matches’ trees, and the millions of other searchable trees in Ancestry’s database. Ancestry’s tree database contains an enormous number of errors: unsourced entries copied from other unsourced trees, wrong dates, wrong parents, conflated individuals with similar names, and outright fabrications. When ThruLines draws a proposed relationship path through an inaccurate tree, it produces a confidently presented but entirely wrong hypothesis. And because Ancestry’s database contains millions of trees, the same error can appear in hundreds of trees simultaneously — giving a false hypothesis the appearance of strong multi-source support.
ThruLines does not go through the DNA. This is perhaps the most important point that intermediate researchers miss. Despite the name, ThruLines does not analyze DNA segment data to validate its hypotheses. It is a tree-comparison algorithm that uses DNA match data only to identify which users share detectable DNA with you — the relationship paths it proposes are drawn entirely from tree comparisons. A ThruLines hypothesis can be completely wrong about the proposed ancestor while the underlying DNA match is entirely real, because the match shares DNA with you through a different common ancestor that neither tree has correctly documented.
Common surnames amplify errors. ThruLines performs significantly less reliably for common surnames — Smith, Johnson, Miller, and their equivalents in other languages. When many people in an era and region share a surname, tree builders frequently assign individuals to the wrong family, and ThruLines can connect matches through these incorrectly merged individuals without any way to detect the error. For researchers working with common German surnames — a category that includes some Dillman variant spellings — this is a meaningful limitation.
Pre-1800 ancestors carry higher error rates. The further back a proposed ancestor lived, the more likely the connecting tree paths are to contain errors. Records are sparser, trees are less reliably sourced, and the number of possible descendants connecting through any given ancestor grows exponentially. A ThruLines card proposing a connection to a 17th-century ancestor through a chain of dotted lines deserves significant skepticism regardless of how many matches appear on it.
Identity merging problems. ThruLines’ algorithm sometimes merges individuals who should be distinct — treating two people with similar names in the same era as a single person, or incorrectly connecting a proposed ancestor to a known ancestor in your tree. These merges can create ThruLines hypotheses that are structurally coherent but factually impossible — a proposed ancestor who, if the dates were checked, would have had to father children at age four.
Match tree dependency. If a DNA match makes their tree private or unsearchable, or removes the connecting individual, the ThruLines path through that match collapses. ThruLines cards can appear and disappear as matches change their tree settings — which means the hypotheses are not stable over time and should not be relied on as persistent evidence.
How to Use ThruLines Productively
None of ThruLines’ limitations mean it should be ignored — they mean it should be used correctly. A practical workflow for intermediate researchers:
Treat every ThruLines card as a research hypothesis, not a finding. The moment ThruLines proposes a potential ancestor, your job as a researcher has not ended — it has begun. The hypothesis needs to be tested against primary source evidence before it can be accepted as part of your documented tree.
Evaluate the strength of the card before investing research time. How many independent matches support the hypothesis? Are the connecting paths solid lines (your documented tree) or dotted lines (other users’ trees)? Do the proposed ancestors’ dates and places make logical sense? A card with fifteen matches and mostly solid connecting lines deserves more investigation than a card with one match and a chain of dotted lines reaching back to the 17th century.
Look for independent verification. Before accepting a ThruLines-proposed ancestor, find primary source records — birth, marriage, death, and census records — that document the proposed ancestor and the relationship chain. Do not rely on other Ancestry trees as verification; those trees may be the very source of the ThruLines hypothesis you are trying to verify.
Check the matches’ trees directly. Click through to the trees of the matches shown on a ThruLines card and look at what sources, if any, support the proposed connections. An unsourced tree that was last edited in 2009 is a very different proposition from a carefully sourced tree maintained by an active researcher.
Use the Genealogical Proof Standard (GPS)[4]. As discussed in our conventions and consistent with best practice in genealogical research, a reasonably exhaustive search, analysis of conflicting evidence, and a soundly reasoned written conclusion are the standards for establishing genealogical relationships. ThruLines can generate a hypothesis that feeds into that process — but it cannot substitute for it.
ThruLines and the Error Propagation Problem
One of the most significant structural problems ThruLines creates for the genealogy community is error propagation. When an incorrect ancestor appears in a ThruLines card, researchers who accept the hypothesis without verification add that incorrect ancestor to their own trees — which then become sources for other researchers’ ThruLines hypotheses, spreading the error further. A single incorrect tree entry, propagated through ThruLines to hundreds of researchers who accept it without verification, can become embedded in thousands of trees within months.
This is not a hypothetical concern. Genealogical community forums contain numerous documented cases of specific errors — wrong parents, wrong birth years, wrong individuals — that spread through Ancestry’s tree database via ThruLines-assisted copying, to the point where correcting the error requires convincing dozens or hundreds of other researchers to update their trees before the ThruLines hypothesis changes. As one experienced researcher has noted, a single small mistake can cause things to be wrong[5] in ThruLines for every researcher connected to that line — and it will not be fixed until all the DNA matches fix the mistake in their own trees.
AncestryDNA Pro Tools and ThruLines
AncestryDNA’s Pro Tools subscription ($9.99/month or $99/year) adds capabilities that make ThruLines more useful for advanced researchers. The Enhanced Shared Matches feature — available only with Pro Tools — allows researchers to identify which matches are shared between any two people in their match list, not just between themselves and a match. This is particularly useful for validating ThruLines hypotheses: if multiple matches who appear on the same ThruLines card also share DNA with each other, that pattern of shared matching provides genetic evidence that they likely share the proposed common ancestor — independent of any tree data.
What This Means for Dillman Researchers
For Dillman Family Association (DFA) members using AncestryDNA, ThruLines is a valuable but imperfect tool. Given that many Dillman lines trace to German-speaking regions in the 18th and 19th centuries — periods and places where records are sparser and tree errors are common — ThruLines hypotheses for deeper Dillman lines should be approached with particular caution. A ThruLines card proposing a specific German village ancestor from the 1700s, supported by a chain of dotted lines through trees that may themselves be unsourced, requires primary source verification before it can contribute to the DFA’s documented research.
ThruLines is most reliable for Dillman lines in the American period — 19th and early 20th century ancestors where census records, vital records, and other primary sources are abundant and accessible online. For those lines, a well-supported ThruLines card can be an efficient way to identify which matches belong to which family branches and to prioritize documentary research.
The Dillman DNA Project coordinates genetic genealogy research across Dillman lines, and comparing ThruLines hypotheses with other project members’ research is one way to cross-check proposed ancestors against the collective knowledge of the DFA research community.
Sources
- Ancestry, “ThruLines — How It Works,” support.ancestry.com/s/article/ThruLines (accessed May 2026).
- Ancestry, “ThruLines — Reading Your Results,” support.ancestry.com/s/article/ThruLines (accessed May 2026).
- Ancestry, “SideView Technology,” support.ancestry.com/s/article/SideView (accessed May 2026).
- Board for Certification of Genealogists, “Genealogical Proof Standard,” bcgcertification.org (accessed May 2026).
- Roberta Estes, “ThruLines — Help or Hindrance?” DNAeXplained, dna-explained.com (accessed May 2026).
AI Disclosure: This article was researched and written with the assistance of Claude, an AI assistant developed by Anthropic. All facts have been reviewed for accuracy, but readers are encouraged to verify information independently, particularly for time-sensitive details such as feature availability and interface changes.
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