Iberian caveman from La Braña

Finally I got downloaded the ancient La Braña genome.  It is publicly available from the NCBI sequence read archive.  I refined it by GATK, a program reading genome sequences and calling SNPs.  A bit over 1 million SNPs were called,  over 100k overlapped with  the 1M Illumina set used by 23andme, but only 20 kSNP’s overlapped with my standard LD-pruned set.  It is less than  some other projects have been able to reach, but still usable, although some amount of inaccuracy is seen in individual results.  The big view and locations of populations on MDS-plots  are still very correct.   

Playing around with PCA, which I have used earlier,  I found it being poorly applicable in this case and I moved to MDS.   It was obvious that the LaBrana1 sample being something different than any present-day population didn’t share as much common SNP-level principal components with them as MDS can retrieve using genetic distances. 

Comparing to other online results shows some similarity and also differences.  What made me pondering was the obvious Asian affinity of LaBrana1 shown on the Eurasian plot.   This Asian affinity was shown around at the same level with most eastern Russians, like most eastern samples from Vologda and most eastern Mordvins.  This is very close what I have seen achieved by some other projects, but surprisingly Lazaridis et al.  didn’t show Asian affinity for LaBrana1.   Unfortunately he didn’t inform us about the amount of SNPs used on his PCA-plot (or I didn't find it), but the study tells that only a 10 kSNP overlapping set was obtained for LaBrana1 and even less for some other ancient samples.  But maybe I am wrong.   Maybe I know more after testing  other ancient WHG samples. 

MDS plottings and IBS-statistics show closest similarity with Northern European populations.   My data lacks of Basques, so I can’t say how close the LaBrana1 they might be.  In general South Europeans are more distant for LaBrana1 than North Europeans and Near Easteners are even more distant.   The closest population at average IBS-level was Western/Southwestern Finns,  but the difference to Estonians and Lithuanians was quite small. 

European MDS

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Eurasian MDS

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IBS-statistics for top ten individuals

Estonian            0.8101938

Lithuanian          0.8101357

FI0007              0.8099396

Belorussian         0.8098805

SC0001              0.8098763

Estonian            0.8098527

Lithuanian          0.8097566

FI0005              0.8096651

Lithuanian          0.809652

Russian             0.8094852

IBS average statistics including all population from my extended European data set (East and North Asians excluded)

 

Estonians, the genetic comparison

I succeeded to download 13 Estonian samples from the study “Upper Palaeolithic Siberiangenome reveals dual ancestry of Native Americans “  released by Estonian Biocenter.   After the qualification I had 11 samples, two was removed due to being too close relatives with other samples.   I have only a few comments about the Finestructure, otherwise I only hope you enjoy the results.

• the Finestructure analysis is based on IBS-similarity.
• I removed Lithuanians from the Finestructure run because they show very high national IBS-similarity and it distorts results in the aggregate mode.  This happens although the aggregate level is quite low in my analysis.   This means practically that Estonians are compared to Slavs (Belarussians).
• processes using MCMC-aggregate features usually change individual results and usually you can’t compare individual results on Finestructure matrixes.  To see individual results you have to look the raw data matrix, not the aggregate matrix, but in my run the difference between raw and aggregate is very small.   In this context I refer to my previous analyses and to the effects of young isolations, they tend to distort aggregated results.
• as also in my previous Finestructure analysis, the South European result seems to be somewhat inaccurate, but Northern Europe looks quite good. 
• the tree result on the matrix seems to imply more differences than similarities between samples.  So for example the Finns on the matrix are split into two or three groups.   It is at least for me impossible to estimate the balance of similarities and differences between individuals and populations in existing software analyzing tools.   It is strongly up to the selected tools, and accordingly to the authors, how similarities and differences are weighted.   Some authors prefer similarities, even in case it is very small, and disregard differences.  This can be seen by comparing results and analyzing tools.   This question is interesting and reminds of the complex history of each population and used data which can be inadequate. 

PCA world

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PCA extended Europe

Dimensions 1 and 2:

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Dimensions 1 and 3:

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PCA Europe

Dimensions 1 and 2:

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Dimensions 1 and 3:

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Finestructure

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Looking closer: The Finnish cluster in Europe

New PCA's

A new PCA analysis including only Europeans.   The first plot including dimensions 1 and 2 shows for Finns East European and Scandinavian affinities, more precisely for the Eastern Finns the East European affinity closer eastern Vologda samples and the Western Finns match closer western Vologda samples and Belarussians.    Scandinavian affinity on second dimension looks quite constant for all Finns.   This result could mean that the common affinity between Finns and Scandinavians is older than the present genetic shape of these populations (Finns and Scandinavians) and the difference in the East European affinity among Finns idicates also different origins for Eastern and Western Finns in Eastern Europe. This explanation is supported also by the position of Scandinavian and some CEU samples who seem to diverge from Central Europeans toward Finns (dimension 2). The second plot, showing dimensions 1 and 3, confirms the East European affinity of Finns.  Scandinavians keep their position near Central Europeans. 

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Retesting Finestructure

I have a new interesting experiment with Finestructure.   I played with it a couple years ago testing it several days and found some problems.  It seemed to exaggerate young and small isolated populations by increasing their similarities with other populations in straight relation to the shared haplotypes within the isolation.  This effect is a bit difficult to describe exactly by words although testing revealed it certainly. After seeing this problem I decided to give up with Finestructure.  Maybe the problem was partially in Chromopainter and it’s data selections.   Now, in my new experiment I used IBS data as an input to the Finestructure.  The authors of Finestructure claim that IBS data is much worse than the data generated by Chromopainter.  My results show that IBS data gives fair good results, better than in my previous tests with Chromopainter data which was pretty much distorted by the problem I described above.   Pretty much testing ought to be done before this can be proved stone cold, and even then many readers will not believe me now, so just now it is enough for me to know this.   I think that the effect is basically the same I have seen so many times in population genetic tests;   many analyses “infer” that most homogeneous populations, owning highest shared genome similarity, are root populations.  This means that those analyses often select typical genetic features from most homogeneous subpopulations.  But this is a big mistake; in many cases the most homogeneous subpopulation is younger than the root population, the one they once diverged from.     In other words:  the portrait doesn’t come better by increasing contrast, because we likely will lose nuances and sometimes also profile resembles the neighbor.    
  

So I spent a little time more with testing and I think that I found a way to avoid the false gene pumping between populations described above.   Definitely, this test done with IBS-data looks very clean.   Some problems can be seen in sorting out Mediterranean populations, but in Northern and Eastern Europe the grouping result is amazing.   The Finns cluster with Northern Russians, which is of course right and follows the known history.  Northwest Russia was the homeland for many Finnic speaking groups before the russification took place.    Tree model can’t figure simultaneously the Finns belonging also to the Fennoscandinavian group.    

The graphic shows also affinities between individuals.

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PCA update, a Scandinavian sample more

I have now finished the sample gathering and will go on with more specific analyses.   Here are the last update of PCA plots with the basic data.  I think that all PC- analyses have been quite good, matching well with first-rate academic studies I have seen.

Europe, dimensions 1 and 2:

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Europe, dimensions 1 and 3:

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Mordovian affinity in Finland

The genetic origin of Finns is for the big public unknown.  If you follow the public discussion,   including random scientific views, you find ideas that resemble more a conspiracy theory than common sense.  It is hard to find neutral scientific work with natural explanations.  I am going to bite a small piece of this cake.   Unfortunately I can’t do very inclusive work because I have not same resources than professional scientists working with resources they have, but I have my liberty to do my own work.  It is not away from anyone.   It is possible to do fair work if you familiarize yourself with methods and data, and you know something about the Finnish history. 

Test goals

My goal is to see what is common with Eastern Finns and two key populations in Russia; Mordovians and North Asians.   Finnish scientists define Eastern Finns as a mixture of Karelians and Tavastians.   The history of Tavastians is quite well documented by linguists and archaeologists from the first millennium and there is no reason to ponder who they are. Tavastians are ancient Finns who have lived in Finland a very long time.  The history of Karelians is less clear.  They appeared to the historical scene around 1000 years ago, just after the Slavic eastern expansion started.  During those times numerous Finnic speaking groups lived in the area of present-day Russia.   There are many possibilities for the origin of Karelians; they can be their own origin or a mix of several Finnic groups to the east from Finland or in the neighborhood of ancient Tavastians in Finland.   Today Finnish enthusiasts have done great work with the East Finnish Ydna and resolved routes where their paternal lines came from.   Mostly Eastern Finnish paternal results suggest the origin from Russia, inside the area from Finland to near Moscow.   But my goal is to see inside autosomal genetic ancestry.  Autosomal genes tell more about admixtures between populations. 

Additionally I try to find out the possible Asian admix among Eastern Finns.   As I earlier found the North Asian admixture usually seen among Finns is vague.  Look at here and here.  It exists only if we use samples from Mediterranean or Atlantic regions, or from Central Europe with prominent Mediterranean or Atlantic affinity.   Obviously those samples dominate the test arrangement and assign some Northeast European genetic attributes to North Asian, if they are common with them.  The lesson would be:  don’t use presumable non-ancestral samples if you want to make good analyses in certain time span. Easier said than done.

 

Test arrangement

Samples

• Han Chinese – defining East Asian affinity
• Nganassans  – defining North Asian affinity
• Mordovians – defining Northeast European / East-Finnic ancestry
• Belorussians – defining Slavic ancestry
• Scandinavians – defining Fennoscandinavian ancestry
• East Finns – 3 samples
• West Finns – 5 samples for comparison

Data selections and preparation

• Asian and North/Northeast European groups are around in same size to prevent under/oversampling in finding Asian admixtures.

• Mordovians are selected using pre-analysis including individuals with most Finnish looking genetic profile.   Another end of Mordovians resembles Slavs.

•  Nganassans are pruned, without outliers.  Outliers had European admixture around 10-50%. 

•  Scandinavians are the group with least Finnish admixture, selected using pre-analysis.  Two of them in my Scandinavian sample group (7 individuals) were dropped out for this reason.

      Software

 

• Structure 2.3.4 (rel. 2012)

• run parameter: initial 20000 cycles, analysis 200000 cycles

Results

 

K=3 

                                                  Pop       1      2      3      Individuals
 
                                                  Han:     0,996  0,003  0,000       10
                                                  Ngan:   0,971  0,029  0,000        9
                                                  Mrd:     0,003  0,279  0,718        5
                                                  EFinn:  0,004  0,303  0,693        3
                                                  Belarus:0,001  0,014  0,985        5
                                                  Scand:   0,001  0,016  0,983        5

  K=4

 

                                                    

                                                      Pop       1      2      3      4      Individuals

                                                      Han:     0.022  0.977  0.000  0.001       10
                                                      Ngan:   0.044  0.955  0.000  0.000        9
                                                      Mrd:     0.297  0.000  0.698  0.005        5
                                                      EFinn:  0.304  0.001  0.692  0.002        3
                                                      Belarus:0.027  0.000  0.973  0.000        5
                                                      Scand:   0.027  0.000  0.970  0.003        5

K=5 

 

                                                   

                                                     Pop       1      2      3      4      5      Individuals

                                                     Han:     0.007  0.680  0.313  0.000  0.000       10
                                                     Ngan:   0.011  0.249  0.740  0.000  0.000        9
                                                     Mrd:     0.808  0.000  0.001  0.013  0.178        5
                                                     EFInn:  0.790  0.000  0.000  0.209  0.000        3
                                                     Belarus:0.999  0.000  0.000  0.001  0.000        5
                                                     Scand:   0.997  0.000  0.000  0.002  0.001        5
 

 West Finns, K=3

 

The result shows for Western Finns around a half of the supposed Northeast European admix, being in the halfway between Scandinavians and Mordovians.  This fits well with Finnish genetic studies where Western Finns are in the halfway between Eastern Finns (Eastern Finns and Mordovians have equally NE-European affinity) and Scandinavians. Western Finns trigger a bit different Northeast European cluster than Eastern Finns, including some common affinity between Western Finns, Mordovians, Belorussians and Scandinavians.

 

                                                   

                                                    Pop       1      2      3      Individuals

                                                    Han:     0.022  0.978  0.000       10
                                                    Ngan:   0.045  0.955  0.000        9
                                                    Mrd:     0.347  0.000  0.653        5
                                                    WFinn: 0.170  0.000  0.830        5
                                                    Belarus:0.059  0.000  0.941        5
                                                    Scand:   0.059  0.000  0.941        5