María Rita Santos

Brief communication: Restricted geographic distribution for Y-Q* paragroup in South America.

We analyzed 21 paragroup Q* Y chromosomes from South American aboriginal and urban populations. Our aims were to evaluate the phylogenetic status, geographic distribution, and genetic diversity in these groups of chromosomes and compare the degree of genetic variation in relation to Q1a3a haplotypes. All Q* chromosomes from our series and five samples from North American Q* presented the derivate state for M346, that is present upstream to M3, and determined Q1a3* paragroup. We found a restrictive geographic distribution and low frequency of Q1a3* in South America. We assumed that this low frequency could be reflecting extreme drift effects. However, several estimates of gene diversity do not support the existence of a severe bottleneck. The mean haplotype diversity expected was similar to that for South American Q1a3* and Q1a3a (0.478 and 0.501, respectively). The analysis of previous reports from other research groups and this study shows the highest frequencies of Q* for the West Corner and the Grand Chaco regions of South America. At present, there is no information on whether the phylogenetic status of Q* paragoup described in previous reports is similar to that of Q1a3* paragroup though our results support this possibility.

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

Asociación entre polimorfismos del gen NAT2 y fisura labiopalatina no sindrómica en Argentina

Background: NAT genes are considered candidate genes for the genetic predisposition to non-syndromic Cleft lip with or without cleft palate (NSCLP), since they codify for N-acetyltransferases, enzymes responsible for the biotransformation of arylamines, hydrazine drugs, and a great number of toxins and carcinogens present in diet, cigarette smoke, and environment. Aim: To determine the association between alleles determining slow acetylator phenotype and the risk of NSCLP. Material and methods: We analyzed *5 (481C>T), *6 (590G>A) and *7 (857G>A) alleles which determine the slow acetylator phenotype and *4 (wild type) allele by polymerase chain reaction/restriction fragment length polymorphism in 97 progenitor-case trios of NSCLP in Argentinian Obstetric Wards. We evaluated the transmission disequilibrium (TDT). Results: TDT showed a positive association between allele *5 and NSCLP (odds ratio=1.6; p=0.03). Conclusions: The presence of *5 allele is significantly higher in cases with congenital NSCLP.BACKGROUND NAT genes are considered candidate genes for the genetic predisposition to non-syndromic Cleft lip with or without cleft palate (NSCLP), since they codify for N-acetyltransferases, enzymes responsible for the biotransformation of arylamines, hydrazine drugs, and a great number of toxins and carcinogens present in diet, cigarette smoke, and environment. AIM To determine the association between alleles determining slow acetylator phenotype and the risk of NSCLP. MATERIAL AND METHODS We analyzed *5 (481C>T), *6 (590G>A) and *7 (857G>A) alleles which determine the slow acetylator phenotype and *4 (wild type) allele by polymerase chain reaction/restriction fragment length polymorphism in 97 progenitor-case trios of NSCLP in Argentinian Obstetric Wards. We evaluated the transmission disequilibrium (TDT). RESULTS TDT showed a positive association between allele *5 and NSCLP (odds ratio = 1,6; p = 0,03). CONCLUSIONS The presence of *5 allele is significantly higher in cases with congenital NSCLP.

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.