Meates and its aliases--论文代写范文精选

到目前为止,细胞Y-STR测试，通过这种方式,所有族谱树被发现匹配。在进一步的基因检测,Y-STR结果扩展到揭示所有的爱尔兰人的基因,虽然有不同定义的变异。下面的essay代写范文进行详述。

Redmonds commented, ‘Migration and linguistic change often went hand in hand, and the secret is to identify the aliases … it is especially gratifying therefore when an explicit alias is discovered after the link has been inferred.’ He continued,51 ‘For my part the most satisfactory [Y-chromosome] test was the one carried out into the names Rediough, Ridehalgh and Ridgewick, for it demonstrated that all could share the same origin’. For a rare surname, volunteers can be sought for testing from amongst the adult males of all of its known one-name genealogical trees. I shall describe such a case study in which high resolution, Y-STR testing has fulfilled a role similar to that of several explicit aliases. 

I shall relate the story, so far, of the Meates project. Initially, five one-name genealogical trees, with five Meates progenitors were Y-STR tested. This enabled their ancestral Y-signatures to be established; and, in this way, all five trees were found to match one another. The homeland of these matching trees was early nineteenth- and late eighteenth-century Ireland.52 Eighteenth-century parish registers in Ireland suggested some linguistic confusion between Meates and Mates53 and further testing was undertaken. The majority of Mates trees from County Wicklow were found to match with the Meates trees;54 and, subsequently, also with Meats in England and Wales and two Mate lines.55 In further genetic testing, the Y-STR results were extended to the 37 marker level revealing that all of the Irish progenitors, Meates and Mates, had a characteristic mutation of one marker56 and the English Meats had a different defining mutation.57 These were evidently slight mutations from an ancestral signature58 that appears also for Mate in England and for five random volunteers with the surname Myatt, 59 two of whom live in Staffordshire.60 Local dialect and early documentary evidence for Staffordshire (Appendix D) suggests that Meate could have begun as a two-syllable surname: Mayot. This helps to explain the Y-STR results, which indicate that instances of the variant spellings Meates, Meats, Mates, Mate and Myatt belong to a single, male line family.

Effects of extreme false paternity rates 
The fraction matching in a Y-STR surname study depends partly on the false paternity rate. A false-paternity-event (fpe) is sometimes called instead a non-paternity-event, a misattributed paternity, a male introgression, or a non-patrilineal transmission. It is an event by which a male surnamed Sykes, for example, does not have a true Sykes father in the biological sense of he who transmitted the Y-signature. That can arise in a number of ways: from a concealed wifely infidelity with a non-Sykes father; or, from an unmarried Sykes mother passing her own surname to the child; or, from the adoption of a non-Sykes child renamed Sykes. There is also the possibility of the Sykes name descending with inherited land rather than by paternal descent. 

Any name-change61 within a male line could show up as a false-paternity-event in a Y-STR surname study. False-paternity rates have been investigated in connection with the disputed fidelity of a modern female partner. Paternity used to be tested by blood group but is now ascertained more surely by a type of DNA test. Anderson62 has taken account of the fact that some paternity testing is for men whose paternity is already in doubt. Surveying worldwide studies in this light, he reported an average chance that a man is not the biological father of his partner’s child; his results for Europe were: 29.8% for men with low paternity confidence; 3.7% for men with unknown and high paternity confidence; and, 1.6% for men with high paternity confidence.63 However, appropriate, unbiased estimates are elusive.64 

For example, some people argue that the historical false paternity rate could have been lower than that found for typical modern mating, since it is alleged that society is now less moral.65 King and Jobling comment, ‘Historical rates of [false paternity] are difficult to estimate, though modern rates, where they have been measured, are of the order of a few percent per generation’; for the purposes of a simulation, they included a constant rate of 2% per generation. For completeness, I shall consider a wide range of false paternity rates, from 0% to 30% per generation. Though it is unlikely that extreme values would persist through the generations down all lines of a populous single family, this can serve to illustrate the effects of extreme rates on a Y-STR study.

An approximation of randomly sampled, independent, male lines of descent from a single founder can break down because, for example, a multi-origin surname can be expected to give rise to mismatching Y-signatures from the outset. In this approximation66 however, the probability that a living male will carry the Y-signature (or a slight mutation thereof) of the surname’s progenitor from n generations ago is (1-p)n ; where p is the fractional probability of a false paternity event at each generation. Uncertainties in the number of generations that have elapsed since late medieval times can be represented by values of n ranging67 from 15 to 25; or, for earlier patrilineal name formation in Ireland,68 a value as high as n=35 might be appropriate. I shall also consider an effective value of n=5 to cover a case in which those tested are close nominal relatives.69 The value p=0.30 corresponds to a 30% chance that every child is not the biological offspring of its nominal father; and, as the table below shows, this accumulates to there being only a 17% chance of intact, male line descent after n=5 generations and 0% chance after n=15 or more generations. At the other extreme of false paternity rates, p=0.0 leads on to 100% chance that the Y-signatures will match amongst the descendants of a single founder, for all values of n. The following table shows the probabilities of matching Y-signatures, for various other fixed values of p and n.

This indicates that, for exceptionally high false paternity rate values of p=0.10 or 0.30, there is little chance that a Y-signature will have descended intact down a male line from a late medieval forefather. For low values (p=0.00 or p=0.01), there is a much higher chance. In the particular case of a ‘many bastards’ hypothesis for the early origins of a populous family, a moderately high, effective value of n might apply, along with perhaps higher, early values for p than in a more monogamous context. Though there is much uncertainty, roughly around half matching could arise in a sample of such a one-name family’s men.

Large families in the Sturges and Haggett simulation 
In their computer simulations, Sturges and Haggett considered the number of male offspring of each couple who go on to marry and have their own offspring. They considered two different ways in which that number might differ amongst monogamous couples;70 the two ways had a rather minor effect on their results. For the purposes of their simulations, they fixed each generation at 28 years and deduced that 23 generations had elapsed since the midfourteenth century Black Death. Then, to account for a twenty-five fold increase in the total population, they assumed a 15% increase at each generation; or, in other words, g=1.15 where g is the growth factor per generation. That is to say, they considered the total population had grown by a factor of gn=25 through n=23 generations, though they reduced g slightly to 1.1385 for the native population after deducting estimated growth from net immigration. 

The population of Sykes, for example, is about thirteen-fold greater than these computations allow for a single family. Sykes had a population of 19036 in England, Wales and the Isle of Man in September 2002 according to the Office of National Statistics, ranking it 391st amongst surnames. This contrasts with the predictions of Sturges and Haggett.71 According to their computer model, the average single-ancestor surname will have 86 males after 23 generations and only around two percent of the simulation’s initial one thousand families will have more than 500 surviving males; they add that it is unlikely that their model will produce more than 750 surviving males for a family at the total population size they chose for the simulation. 

To gain more growth for a family, one might consider relaxing some of the constraints, such as by allowing a family to grow through more generations. Allowing a single-ancestor surname to escape the ravages of the Black Death and grow through 30 generations, rather than the 23 generations of the model computations, can increase the prediction of its current population by about 2.5 fold for g=1.14, or by about 3.6 fold for a higher growth rate of g=1.20. A further 2.7 fold increase for the largest families can be expected by increasing the initial number of families in the computer model from 1000 to 100000, though the exceptionally large families would then descend from a still smaller fraction of the initial families.72 In this model, even a rare, fortuitous combination of all the beneficial factors can be barely enough to explain the experimental finding of a populous, single ancestor featured surname.

A large factor can arise to increase the population of a ‘multi-origin’ surname, in that several of its many origins could produce families to contribute to the modern population of a surname. Clearly, for a surname with a significant number of matching Y-signatures, a ‘many origins’ explanation can be substituted by a ‘many bastards’ contention though a polygynous burgeoning of such a surnames population may have been more long term than at its first generation. 

This, of course, still leaves the controversy as to whether the bastards would have kept the same surname. Possible alternative explanations are being sought for a large, single family. The effects of a population bottleneck have been considered in connection with the large degrees of coancestry that have been found for some populous Irish surnames. On the basis of their simulations, King and Jobling comment that the chief effect of a population bottleneck, such as that of the nineteenth-century Irish ‘Great Hunger’, is a marked reduction in the chance of survival for a family’s descendants. However, this changes the computed degree of Yclustering only slightly. They add, ‘We therefore consider it more likely that the longer-term demographic effects of polygyny [rather than the ‘Great Hunger’] are responsible for the differences between Ireland and Britain’.（essay代写)

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