New Chromopainter Analysis

New Chromopainter analysis is ready. Structure much the same as earlier analysis but I have this time added more populations and population controls.

ANALYSIS RESULT

OVERVIEW:

ChunkCounts:

ChunkCounts or number of segments shows the Saami and Finns appears similar to many donor populations and together shows the strongest affiliation to the Vologda Russians, but on average the Saami shows stronger affinity to the Koryaks, to the Chuvash and to the Vologda Russians. The Finns on the other hands shows stronger affinity to the Lithuanians.

The Scandinavians shows a very similar profile to the donor populations seeming closest to the British, French and Lithuanains and in general appears closer to the Meditterian populations.

The Lithuanians and Estonians seems closest to the eastern populations like Lithuanians, Belorussians, Ukrainians, Vologda Russians and Mordovians. In general more distant to the Medditerian populations.

We see that most controls have been assigned to the right populations. The exception is the Hungarian that got assign to the Belorussian population, the French who got assigned tot he British population, the Romanian who got assigned to the Lithuanian population, the Spanish who got assigned to the Basque population and the Ukranian LV who got assigned to the Lithuanian population. Some of these affiliation appears rather weak suggesting mixed backgroun or origins more distant from the donor populations.

ChunkLenght:

The picture for total shared is much the same as the analysis above.

Mutations:

The picture is much the same as the analysis above.

Mutation Density:

Mutation density calculation have changed. Instead of earlier as number of mutations divided by proportions now instead number of mutations is divided by total shared (ChunkLenght). The numbers are presented as percentages but is really ratios.

The numbers show much the same that have been seen before. The Saami appear as before to have largest mution density to most of the donor populations, then the Norwegians, then the Swedes, then the Finns and finally Estonians and Lithuanians.

In the controls we can see that several control individuals like f.ex the British shows a similar mutation density as the Lithanians and Estonians, while f.ex the Spanish appears to have very high mutation density compared to most of the panel. The reason for these may be many: 1) the Spanish are an older and larger population and therefore have accumulated more mutations over time 2) there is "foreign" haplotypes among the Spanish or in this control that increase mutation density.

One should here expect to see the lowest mutation density to your own population but only a few of the control individuals have correct assignment, however for several individuals it appears to be a regional lower mutation density to neighbouring populations and sometimes also more distant ones.

The problem is probably cased by difference in number of unique mutations between the populations making direct comparisment difficult. However in general it appears like especially Lithuanians appears more "matchy" to other populations when it comes to mutation diversity meaning their haplotypes matching other populations appears to have less mutation difference. Some other reason may also be that 289k may not bee enough to give proper numbers of mutation counts to give a clear picture. In previous analysis the PCA of the mutation counts was much more fuzzy than those made from ChunkCounts and ChunkLenght.

INDIVIDUAL RESULTS:

ChunkCounts:

ChunkLenght:

Mutations:

Mutation Density:

Ancient Gotlanders in Finestructure

EDIT 30/08-2013: I now consider this analysis outdated. Please check the more recent posts with reanalysis of Ajv52, Ajv70, Ire8, Gok4 and Ste7.

We continue the analysis of the ancient Gotlanders vs our project participants.

In the last analysis using ADMIXTURE we assumed that all SNP's where independent from each other. However in reality we are working with segments of linked SNP's or haplotypes. Chromopainter can analyse haplotype and Finestructure can build a tree based on these.

Input: 22k SNP's. MCMC: 100 000, 100 000, Tree: 10 000, 100 000. HapMap recombination map. c-factor: 0.0262 (effective number of independent genetic element).

THE RESULTS:

FIRST ANALYSIS:

ChunkCounts:

The number of shared segments tree appears to set the ancient Gotlanders at its own branch already at the root of the tree. The closest neighbour is the common Finnish and Saami branch. The branching seem to indicate that Finns and Saamis are closer to the ancient Gotlanders than other populations.

The Finnish cluster is closer maybe indicate a closer relationship than the Saami. It would then be in accordance with the earlier ADMIXTURE analysis:

Note that the the various degree of sharing to the ancient Gotlanders at the rightmost vertical partly yellow strip. Yellow indicate more distant relationship gradiant towards blue is closer relationship (see vertical bar to the right of the matrix).

The ancient Gotlanders appears to have various degree of sharing to other individuals. The reason why the tree is so fragmentet is because of the very low c-factor. It indicate that the elemets are very fragmentet because of few markers (22k). A c-factor of 0 is basically independent SNP's while a c-factor of 1 is basically linked SNP's. In our last Finestructure analysis this factor using 289k was a round 0.48

ChunkLength.

The total lenght of shared segments indicate much the same structure as mentioned above but with some internal movement.

EXPERIMENTING:

I did however during my own experiments with Finestructure play around with the c-factor parameter. If I set it to 1 meaning considering the result as one independent genetic element the results changed.

ChunkCounts:

We see now that the Saamis and Finns changed place, the Saamis closest to the ancient Gotlanders while a subsection of the Saami and Saami related individuals moved to the top. We now also see the more familier typical Finestructure matrix clustering.

We can now also see from the coloring vs the ancient Gotlanders that its only the two Saami groups that have increased sharing with the ancient Gotlanders at the rightmost vertical that move into pink meaning the closest.

ChunkLenght:

The total segments shared give a similar story but all the Saamis are now into the same cluster. The coloring seem to indicate that Saamis have the closest relationship, then Scandinavians, then Lithuanians and then finally Finns. This is not in accordance with the earlier ADMIXTURE analysis.

DISCUSSION:

The first analysis appears to be in accordance with ADMIXTURE and is after the book prescribed by the authors of Finestructure. Finns are the closest to the ancient Gotlanders when assuming many genetic elements,

However if assuming only one genetic element the result is in accordance with Chromopainter raw output data for ChunkCounts and ChunkLenght that says that on population average Saamis are the closest to the ancient Gotlanders, then Scandinavians, then Lithuanians and finally Finns.

In my earlier analysis below using only Chromopainter without the help of Finestructure the population assigment for individuals have been correct for most individuals and this analysis appears to show correct and known relationships between the populations in question when assuming c-factor of 1. If assuming a c-factor of 0 the analysis would probably converge more with the ADMIXTURE analysis.

It seems therefor to me that the clustering of Finns close to the Saami maybe be due to more recent connections like migration of Finns to Saami. This because the connection to the ancient Gotlander appears more distant for Finns than for Saami.

The connection of the ancient Gotlander to the Scandinavians seems to be direct. It doesnt seem to have gone through the North-Saamis or Finns as they look like today to Scandinavians. However we know little about the genetics of the South-Saamis. The individuals of partly South-Saami ancestry that show up in the MDS-plots have not maanged to differentiate themself enough in this analysis from Scandinavians.

(Updated 01/07/2012)

Ancient gotlanders vs worldwide variation

EDIT 30/08-2013: I now consider this analysis outdated. Please check the more recent posts with reanalysis of Ajv52, Ajv70, Ire8, Gok4 and Ste7.

I got some second opinions after my last analysis so this time I have compared it to most of my worldwide dataset. The new analysis gave much the same result as the previous one for the ancient gotlanders "Comp22k", however for some of the runner ups the result changed somewhat.

Analysis technical details: ADMIXTURE run K=8, n=2254 individuals, 22k SNPs. All individuals where phased and divided into two individuals before ADMIXTURE analysis. After ADMIXTURE analysis each individual was merged into one individual. This because the ancient data from Gotlanders are "haploid" while all individual and population data is diploid.

THE RESULTS

The table below have been sorted in decreasing order by percentage belonging to cluster "European". The clusters have been named after what geographic area it has shown the highest frequency. Identified clusters are American, Oceania, East-Asia, Siberia, Medeterian, Europe, Central-Asia and Africa.

The graph below have been sorted in decreasing order by percentage belonging to cluster "European" as above.

As we can see the Saamis went down from number second in the first analysis to number ten in the this analysis. The main reason for this is that Saamis have a major Siberian component it shares with the Chuvash. The Chuvash on the other hand moved from number four to number twenty. The previous analysis appears to have moved the "European" component far north-east.

Finns that is our project Finns appears to have kept high on the list and only moved from number three to number four. The 1000 Genome Finns that was not part of the previous analysis however moved into second place.

The Estonians went up on the list from no five in the previous analysis up to number third. The Lithuanians went up from number seven to number five.

Norwegian and Swedes went up from number nine and ten to number six and seven.

DISCUSSION

As we can see the ancient Gotlanders had the highest "European" among all the todays populations.

What imidiatly catch the eye is the higher "Africa" component. Its not similar to any of the contemporary populations, not before we reach Spain we see anything close to this frequency. I suppose several hypothesis: 1) its a glitch by ADMIXTURE 2) its remnant from contact with Africans in the Iberian ice refugee 3) some other unknown reason.

We see that the Central-Asian component for the ancient Gotlanders is the smallest in the dataset of neighbouring populations. The closest neighbours is the 1000G Finns and Saami. This may suggest that Central-Asian influence did to less extent reach the ancient Gotlanders, Finns and Saami than other Fennoscandian populations.

We see that the Medeterian component to the ancient Gotlanders is low and in the same neigbourhood as for Finns, Saamis and Estonians. This ïndicate that the Medeterian influence to less degree reached the ancient Gotlanders, Finns, Saamis and Estonians.

The Siberian and other more distant components the ancient Gotlanders appears to have been less influenced by this components than Saamis and Finns, similar to Estonians, but higher than for Norwegians, Swedes and Lithuanians. This could indicate a later Siberian influence that didnt reach the ancient Gotlanders. Note the unfamiliar composition of elements. The ancient Gotlander have the highest frequenncy of the American and Oceanic compoinent in the dataset and zero clustering to the East-Asian component.

LOOKING BACK AT EARLIER ANALYSIS:

In earlier analysis I have shown that Lithuanians, Estonians and Lithuanians in particular appears to have some of the lowest mutation densities to the continental-european populations. As far as I can tell at this stage this is not in compatible with having at the same time the most similar components to the ancient Gotlanders. The Saamis on the other hand appeared to show higher mutation counts to most of other populations. More analysis with other software like Chromopainter may shed some more light on this question.

Note if we remove the Siberian, American, Oceanic and East-Asian component from the Saamis, the Saami would appears as number four among the populations with the highest European component with the ancient Gotlanders as number three and with both Fnns as number one and two, with Estonians and Lithuanians as runner ups.

INDIVIDUAL RESULTS

Individual estimated admixtures:

Top 10 individuals with the smallest estimated component difference:

(Updated 26/06/12)

MDS plot update 75 participants

We have received some more participants. As usual the MDS plot then will be updated. This time I have added the Chuvash, Mordovians and Ukrainians to the reference population set as it appears to provoke the Saamis and Finns to seperate from each other. In this plot I have reduced the number of individuals from each reference population to 8 for practical reasons as it allows use of the Excel based 3D plotting program that have limited capacity. Also unbalanced number of samples may scew the result.

We see in the first dimension a familiar structure to what we have seen before but mirrored in the opposite direction. To the far left on the X-axis we see the Italians. On the far right we see the Chuvash and two Saami individuals. From the Italians toward the Chuvash and the Saami we see a split into two branches where continental European populations is in the upper branch while the Brits, Scandinavians, Finns and the Saami dominate at the lower branch.

The MDS program picks a subset of the total used SNP that show the largest indepented variance in the dataset. Dimension 1 or the x-axis here clearly show that its the east and west dimension that have the largest variance or difference where Italians appears the most west while the Chuvash and the Saami have the most east. The other populations appears as gradients between these extremes.

Dimension 2 or the y-axis appears to show more a north-south dimension. It seperate Fennoscandians from the continental populations with the exception of the British who appears to follow the Scandinavians the first step at the root of the Fennoscandian branch. We here see the Estonians in the gap between Finns and the Ukrainian, Lithuanian, Vologda Russiand and Mordovian cluster.

We then move to the 3 dimension or the y-axis on the plot. In the plot below its combined with the dimension 1 or the x-axis. We see here a shape that we also have seen in earlier analysis but the interpreation may be more difficult. We see at the top a cluster with especially Lithuanians and Belorussians at the uppermost part, then follows Finns, Mordovians, Vologda Russians, Scandinavians, continental Europeans and the Saami. The Chuvash at the bottom.

As we can see here it appears Saamis have frequencies of SNP's in this third dimension that resemble French, Romanians and Italians the most but as we can see from the dimension 1-2 that Saamis in the first dimension appears to have a frequency of SNP in that dimension that in part most resemble the Chuvash. So it may be the Chuvash that pull the Saamis so far south as before mentioned western Europeans (you may also get this impression by look it in 3D). Also note that it appears that especially Italians have a frequency of SNP similar to the Chuvash in this dimension. What make Chuvash and Italians connect here I do not know at the moment. However if we compare the earlier Chromopainter runs there is no direct and recent connection between the Saami and the Italians or French as seen through mutation density and segmentsize.

Fennoscandians and Neolitic Gotlanders

EDIT 30/08-2013: I now consider this analysis outdated. Please check the more recent posts with reanalysis of Ajv52, Ajv70, Ire8, Gok4 and Ste7.

In end of April 2012 the ancient Gotlander hunter gatherers genome was published by the University of Uppsala. I will now provide an ADMIXTURE based analysis of these samples using project and public published population panels.

The samples was downloaded from authors website and then subject to most of the quality controls as done by the authors. I extracted the relevant SNP for the Ajv's and Ire8 ending up with 22k SNP using three individuals combined into a composite individual.

The composite sample was then subject to control ADMIXTURE and MDS analysis using "haplotized" (phased in BEAGLE) French, Yoruba and Han's as reference populations. The composite individual clustered entirely with French.

I then merged the composite individual with an "haplotized" (phased in BEAGLE) European panel with populations all within the European continent from different public available population panels and run it through ADMIXTURE at K3. Closely related individuals in the panel was removed. One Russian was removed because of odd clustering, reason unknown.

The result was then averaged over populations to get an overview:

As we can see the individuals clustered into 3 main components, North-East Europe, Caucasus and the Mediterian. The Gotland composite neolitic hunter gatherer tops the list of North-East Europe populations, then the Saami and very close follow up the Finns.

As we can see the old Gotlanders appears to have significant Mediterian influence but almost zero Caucasian influence. This may be due admixture or common ancestry with the Mediterian populations. The Caucasian influence appears to be almost as low as the Basque. This may suggest that the Caucasian influence arrived later than the Mediterian one,

In modern individuals you may see that that Scandinavians, British, Lithuanians, Estonians and Finns appears less affected by Caucasian influence than continental European populations like Chuvash, Vologda Russians, Belorussians, Hungarians,French, Spanish, Romanians, Italians and Sardinians. Among the Saamis we see an elevated Caucasian influence. Its possibly linked somehow to the Chuvash. See posts below.

The Mediterrian influence appears to have been less in the North-East among Chuvash, Saami, Finns, Vologda Russians and Estonians, Note the somewhat higher rate among the old Gotlander. This all suggest that the Meditterian influence arrived second after the initial post glacier migration then later a migration from the Caucasus. The latter from Caucasus didnt reach the Basque. There may be support for this suggestion in the paper by Huyghe 2010:

The Caucasion migration appears to have reached the Saamis in particular from the vicinity of Chuvash and then through the Vologda Russians. See Chromopainter analysis below.

SUMMARY: It appears like Finns and Saamis have the best match of modern variation with these ancient Gotlander hunter gatherers. Note however that in this analysis not enough Saamis to provide proper clustering in ADMIXTURE or MDS. This means Finns and Saamis quite often have been lumped togheter in this kind of analysis.

(Updated 31/5/2012)

Scandinavians - Young East, Old West?

(Updated 7th June 2012)

I will this time look more into the details of the Scandinavians based on the main post with the latest large Chromopainter run (see two posts below).

In the last post we could infer something about the genetic history of Finns. I will here try to look into the genetic data of the our Scandinavain participants together with Saamis and Lithaanians as reference.

Please note I dont have geneological info for all so the analysis will contain certain degree of uncertainty.

Proportions:

First note that that the bars and colors for the Koryak in this presentation are made indepentent of the one from the other populations. The score for proportions is calculated by simply multiplying the proportions for each populations. The rest of the tables use averages.

The proportions score for Scandianvans appears to have little variations and the proportions to all donor populations appears similar. The only differences we appears to see is towards the Saamis and Saami mixed individuals, Lithuanians and Swedes who have partly Finnish origin. Our Lithuanian controls shows strongest affiliation with the Lithuanian donor population.

Number of Shared Segments (ChunkCounts)

Same comment as above.

Total Shared (ChunkLenght)

Same comment as above. Note that the average sums to 707 for all.

Shared Segment Size:

The segment size, that is the total lenght of segments (ChunkLenght) divided by number of shared segments after correcting for proportions.

Here we see our Lithuanian controls dominate the top with the largest segments to Lithuanians and Belorus while the Saami is at the lower lower half with the smallest segments except for larger segments to the Koryak and Chuvash.
We see in general that French, British and Lithuanians appears closest to the Swedes as they have the largest segmentsizes. The most distant appears to be Chuvash, Italians and Romanians. Same with Norwegians.

We also see that after the Lithuanians and Estonians its mostly Norwegians who appears to have in general the smaller segmentsize to the continental european donor populations. On the upper half of the table Swedes dominate until the Saami at the top of the table.

This may suggest that many Swedes are in general more closer to the continental Europeans than Norwegians.

Mutation densities or counted mutations divided by proportion:

The counts of related but not indentical haplotypes corrected for proportions shows as expected the Lithuanians controls at the bottom of the table with the least general mutation divergence the continental European populations and especially to Lithuanians but also Belorussians and Hungarians.

In general we see that Swedes appears to have least divergence to the Belorussians, Lithuanians and British. The largest divergence appears to be to Chuvash, Romanian and Hungarians. The Norwegians appears to be least divergent to Hungarians, Belorussians, Lithuanians. The largest divergence is to the Chuvash, Romanians and Italians. In total Norwegians appears to have some larger divergence than Swedes. That is consistent with Norwegians having smaller segmentsize.

So it appears from the general interferance that Swedes and Norwegians have different divergence influences when it comes to mutations. The connection of Norwegians beeing mutationally closest to Hungarians and at the same time more distant to Swedes is abit suprising but the difference is not great and may be within margin of error.

We see Saami distribute mostly at the upper upper half, we then see that the Swedes and Norwegians appears to distribute down to the lower half. In the lower lower half we find Lithuanian controls. At the top we see U1 who has confirmed geneologically half Scandinavian orign and half British Isles and some minor non-european admixture. The origin of NO14 is also half Fennoscandian and other half Belgian/Dutch. This may for some reason explain their higher mutational density beeing similar to one of the most divergent Saami.

The close runner ups SWE8 and SWE19 have ancestry/partly ancestry from central-Sweden. It may suggest the existence of "older Scandinavian" stock in central-Sweden that have been less affected by later migrations from continental-Europe.

Please note that the correlation between Mutation density vs Segmentsize is -0.61. This means that in general that if segmentsize increase or decrease mutation density is likely to decrease or increase.


Summary:

Scandinavians appear to have received different influences at different times. The average segmentsize also seem to suggest that part of the Swedish populations have diverged later from the continental populations than Norwegians. There also seem to maybe exists Scandinavian "isolates" as seen through the high mutation counts after correcting for proportions especially for some Swedes even the average Mutation density appears similar to Lithuanians..

However this interpretation must be taken by caution as these individuals do not appears as consistent as Saamis in their placement in the different tables. As an example SWE8 who appears as close runner up to SA2 in Mutation density appears average when it comes to segmentsize and ChunkCount density. SA2 however do appears consistent in all these cateogories with small segmentsize, high ChunkCount density and high Mutation density - all consistently suggesting large divergence time.

Differating Finns - Eastern and Western Histories?

(Updated 7th June 2012.)

I will this time look more into the details of the previous post with the large Chromopainter run.

In the process of generating the data and the making of the previous post I noticed there was a certain variation among Finns. I will here try to look into the genetic data of the our Finnish participants together with Saamis, Estonians and Lithuanians as reference.

Please note I dont have geneological info for all so the analysis will contain certain degree of uncertainty.


Proportions:

Lets first look at the proportions. First note that that the bars and colors for the Koryak in this persentation is made indepentent of the one from the other populations. The Score is calculated by simply multiplying the proportions for each populations. Later averages will be used.

The score basically appears as a reverse of the Koryak and Chuvash. We clearly see a gradiant from Saamis to the Estonians and Lithuanians. Lithuanians and Estonians shows of course strongest similarity to the Lithuanian and Belorussian donor populations while the Vologda Russian influence appears to be similar distributed among Finns even among the Saamis. Chuvash and Koryak seem to the main reason for division of Finns here.

Number of Shared Segments or ChunkCounts

Same comments as above.

Total Shared or ChunkLength

Same comment as above.

Segment size:

The segment size, that is the total shared divided by number of shared segments corrected for proportion. We still see the Saami and Lithuanians at each end.

As we can see here from the occurance of green Finns appears to share larger segment sizes with Vologda Russians, Lithuanians and Belorussians, some Finns even with some Chuvash influence. On the other side Finns have smallest segments to Italians, Romanians and Hugarians.


Mutation densities or counted mutations divided by proportion:

The muation densities also again shows the Saamis and Estonians at different ends of the scale.

As we can see here Lithuanians appears to have the most red and yellow vs Finns. Not before we meet the Saami it turn green. Then we have the Hungarians and British. The most distant appears to be the Chuvash, Romanians and French.

Conclusion:

The data seem to suggest different influences for the Finnish populations that divide them genetically. The different segmentsizes and mutation densities suggest that the influences have arrived at different times from same or different sources.