Josefina Motti

An alternative model for the early peopling of southern South America revealed by analyses of three mitochondrial DNA haplogroups.

After several years of research, there is now a consensus that America was populated from Asia through Beringia, probably at the end of the Pleistocene. But many details such as the timing, route(s), and origin of the first settlers remain uncertain. In the last decade genetic evidence has taken on a major role in elucidating the peopling of the Americas. To study the early peopling of South America, we sequenced the control region of mitochondrial DNA from 300 individuals belonging to indigenous populations of Chile and Argentina, and also obtained seven complete mitochondrial DNA sequences. We identified two novel mtDNA monophyletic clades, preliminarily designated B2l and C1b13, which together with the recently described D1g sub-haplogroup have locally high frequencies and are basically restricted to populations from the extreme south of South America. The estimated ages of D1g and B2l, about ∼15,000 years BP, together with their similar population dynamics and the high haplotype diversity shown by the networks, suggests that they probably appeared soon after the arrival of the first settlers and agrees with the dating of the earliest archaeological sites in South America (Monte Verde, Chile, 14,500 BP). One further sub-haplogroup, D4h3a5, appears to be restricted to Fuegian-Patagonian populations and reinforces our hypothesis of the continuity of the current Patagonian populations with the initial founders. Our results indicate that the extant native populations inhabiting South Chile and Argentina are a group which had a common origin, and suggest a population break between the extreme south of South America and the more northern part of the continent. Thus the early colonization process was not just an expansion from north to south, but also included movements across the Andes.

Software for Y-haplogroup predictions: a word of caution

The development of online software designed for genetic studies has been exponentially growing, providing numerous benefits to the scientific community. However, they should be used with care, since some require adjustments. The efficiency of two programs for haplogroup prediction was tested with 119 samples of known haplotypes and haplogroups from Argentine populations. Quantitative estimates of the predictive quality of both software systems were computed with the uncertainty coefficient; and sensitivity, specificity, positive, and negative likelihood ratios were also calculated to assert the reliability of both programs, showing high probabilities of assigning an incorrect haplogroup.

About the letter “Comments on the article, “Software for Y-Haplogroup Predictions, a Word of Caution”

Dear Sirs: The letter by Dr. Athey entitled “Comments on the article, “Software for Y-Haplogroup Predictions, a Word of Caution” discusses a paper of our authoring in the present Journal [1]. Though at first glance his opinion may seem reasonable, a careful analysis reveals a series of mistakes committed by Dr. Athey. In the mentioned letter, one of the main concerns of Dr. Athey is the amount of short tandem repeats (STRs) that were analyzed. He comments that seven markers should be avoided, explaining that an increase of that amount augments the probability of assignment, stating that “With the addition of a sufficient number of markers, the prediction probability for the correct haplogroup can be ‘driven’ past 99% in nearly all cases, and this almost always occurs by the point where 20 markers have been used.” Nonetheless, he does not make reference to any sort of validation study, so said 99% must only refer to the probability of assignment his own software provides. What is more, Dr. Athey seems oblivious that our paper examined this software’s predictive values in different cutoff points, up to 95% of probability of assignment, still obtaining inadequate predictive values on said cutoff point. Twelve of our haplotypes proposed from 100% to 99.6% probability of assignment to the R1b haplogroup in the Haplogroup Predictor, while none of those samples belong to the said haplogroup. In the R haplogroup, one haplotype gives 99.8% probability to an erred haplogroup (E1b1b), while 14 give from 100% to 99.4%, assigning these samples to the R1b haplogroup, and were considered as correct predictions. Note that in these cases, the predicted haplogroup follows the nomenclature of the software, and the probability was not pooled by major branches. If the seven markers of the minimal haplotype were not a proper set, Dr. Athey’s software should not provide such high probabilities of assignment in these cases, since it misleads the user. Unfortunately, Dr. Athey’s mention that seven Y-STRs are too few occurs only in his letter; neither of the two papers of his authoring [2, 3] available at the Haplogroup Predictor’s website (http:// www.hprg.com/hapest5/) nor the software instructions (http://www.hprg.com/hapest5/page4.html) explain that the user should employ more than seven markers. Otherwise, we would not have attempted to use it. Moreover, a simple glance at recent literature where the Haplogroup Predictor was employed clearly shows that researchers do not use such high amounts of Y-STRs when they rely on the Haplogroup Predictor; for instance, Salas et al. [4] used the seven Y-STRs we did, plus DYS 385 and Petrejcikova et al. [5] only 12 Y-STRs. His statement “...indeed, the seven-marker dataset apparently resulted from a study carried out over five M. Muzzio :V. Ramallo : J. M. B. Motti :M. R. Santos : J. S. Lopez Camelo :G. Bailliet Laboratorio de Genetica Molecular Poblacional, Instituto Multidisciplinario de Biologia Celular (IMBICE), CICPBA, CCT, La Plata–CONICET, La Plata, Argentina

Genealogical surveys show a high rate of non-paternal surname transmission with regional differences in Argentina.

Surnames are a vertically transmitted cultural trait that in Argentina follows the paternal line of descent when the paternity is known. There was a lack of empirical information regarding non-paternal surname transmissions among the general population, so we performed 2,550 genealogical interviews, which included 6,954 surname passes, in different regions of this country. We compared the proportion of non-paternal transmissions between the propositus and parental generation and found no significant difference between them (p<0.01). Inter-population comparisons allowed us to describe 4 regional groups. We also drew models and simulations to estimate how many generations it would take to find that only half of the population maintained the paternal transmission. The lowest proportion of non-paternal transmission was 7.3%, estimating 9 generations (between 225 and 315 years) to find that, at most, half its population keeps following the paternal transmission; the highest proportion was 23%, taking 3 generations (75-105 years). Our results show a high proportion of unrecognized paternities among the general population, a very quick loss of association between male lineages and surnames, and regional proportions with significant differences between each other.

Population structure in Argentina

We analyzed 391 samples from 12 Argentinian populations from the Center-West, East and North-West regions with the Illumina Human Exome Beadchip v1.0 (HumanExome-12v1-A). We did Principal Components analysis to infer patterns of populational divergence and migrations. We identified proportions and patterns of European, African and Native American ancestry and found a correlation between distance to Buenos Aires and proportion of Native American ancestry, where the highest proportion corresponds to the Northernmost populations, which is also the furthest from the Argentinian capital. Most of the European sources are from a South European origin, matching historical records, and we see two different Native American components, one that spreads all over Argentina and another specifically Andean. The highest percentages of African ancestry were in the Center West of Argentina, where the old trade routes took the slaves from Buenos Aires to Chile and Peru. Subcontinentaly, sources of this African component are represented by both West Africa and groups influenced by the Bantu expansion, the second slightly higher than the first, unlike North America and the Caribbean, where the main source is West Africa. This is reasonable, considering that a large proportion of the ships arriving at the Southern Hemisphere came from Mozambique, Loango and Angola.