The Genetic equilibrium of reciprocal translocations in man is
difficult to assess because of the fundamental biases in the detection of
The great majority of recorded reciprocal translocations have been
found because one child received an unbalanced genome through malsegregation of
the translocation, and only 3 of the reported families [1, 6, 43] have been
ascertained randomly. In two others [25, 37], the proband was affected by a sex
chromosome aberration. Hence any attempt to analyse the genetic fitness of
balanced translocations must take into account the biases of ascertainment, a
rather difficult task considering the scarcity of data. Many different
translocations have been found but the data on any particular translocation is
insufficient to assess its genetic fitness. We therefore decided to pool all
published data [ 1-48] together with our personal observations [49-50],
deliberately putting together different types of translocations in an attempt
to get an over all impression. Only families where a translocation carrier has
more than one child have been considered. Centric fusions between acrocentrics
have not been included in this study.
At least one example of a partial trisomy has been retarded for each
group of chromosomes, except the F group. Propositi with the partial
monosomies, 5p- , 18p- , 18q- and Dq- have also been found.
In order to estimate the segregation ratio, two approaches can be made
with this material:
(i) an estimation of the risk of malsegregation in the progeny of
(ii) an estimation of the ratio of normal karyotypes to translocation
carriers amongst the phenotypically normal descendants of carriers.
(i) Risk of malsegregation
(A) Children born from a carrier mother.
The overall sample includes 80 sibships containing 69 affected
persons with an unbalanced karyotype in a total of 268 children. The net
frequency of affected individuals is thus 0.26. Three main biases affect this
(1) All the families include at least one affected child (truncated
(2) The probability of ascertainment is related to the actual number
of affected individuals (multiple selection).
(3) Malsegregations resulting in non-viable zygotes are not included
in this survey (bias impossible to assess).
The overall sample can be split up into subsamples in order to apply
(a) Sibships of probands born from a carrier mother.
There are 136 children including 58 affected persons in a total of
The multiple selection equation is
N = number of sibships
R = number of affected children
T = total number of children
p1 = estimated proportion of affected children.
This gives p1= 0,161 ± 0,038.
This value does not agree with the value obtained by application
of the truncated binomial according to the Haldane formula  for which p2 =
0.2587 ± 0.0527
This indicates that bias no. 1 (at least one child affected) is
not the only one operating but that multiple selection is also occurring ( bias
no. 2 ).
(b) Other sibships excluding the sibships of the
There are 132 children, of whom eleven are affected P3 = 0.083 ±
We can split the sample into two parts. In the sibships born from
a carrier grandmother or great-grandmother of a proband, we find 4 affected out
of 72 children (i.e. p4 = 0.056 ± 0.028 ) . This estimate is too low because
of the necessary inclusion of the carrier (the parent of the proband).
The second subsample consists of sibships born from carrier aunts,
great-aunts or female cousins of a proband. There are 7 affected out of 60
children, i.e. P5 = 0.117 ± 0.041 . This is likely to be the least biased
estimate for the whole sample.
It must be remarked that p5 = 0.117 ± 0.041 does not differ
significantly from the estimate (after the correction for multiple selection)
for the sibships of the probands : p1= 0.161 ± 0.038.
(B) Children born from a carrier father.
The whole sample consists of 34 sibships giving a total of 96
children, of which 21 are affected (i.e. P = 0.22).
The same analysis can be performed:
(a) Sibships of probands born from a carrier father.
The multiple selection equation gives a value of p1 = 0.091 +
The truncated binomial would give p2 = 0.380 ± 0.037 and, as
noted for the carrier mothers, this discrepancy indicates that multiple
selection is playing the major role.
(b) Other sibships excluding the sibships of probands.
If the sibships of the probands are excluded then the rest of the
sample is limited to the sibships born from a carrier uncle, great-uncle or
cousin of a proband, and p3 = 2/24 = 0.083 ± 0.053
Empirical risk of malsegregation
From the data it can be surmised that the risk to the progeny of
carrier mothers is of the order of 0.20 to of 0.10. The risk to the progeny of
carrier fathers is probably less. This difference, however, seems less
pronounced than in the case of centric fusions . This difference between
the sexes is also indicated by the fact that the carrier parent is the mother
of the proband in 43 cases, and the father in 13 cases.
(ii) Segregation ratio in phenotypically normal
The maintenance of a balanced translocation in a given population can
be due either to mutational pressure or to a selective advantage by the
carriers. Cases arising from non-carrier parents prove abundantly that mutation
pressure is strong, but it is difficult to measure. A selective advantage could
result from two kinds of effects in the progeny of heterozygotes:
(1) carriers have more children than normal people.
(2) the translocation is more often transmitted than the normal
karyotype. The first hypothesis is difficult to assess because all the families
recorded contain at least two children: i.e. childless families and one-child
families are not analysed. However, the segregation of the translocation among
phenotypically normal persons can be directly analysed.
The whole sample of children born from a carrier parent includes 145
carriers and 101 normals. This segregation differs significantly from the
expected 1 : 1 ratio (?2 = 7.86 for ?= 1). However, here also
ascertainment is heavily biased, and statistical corrections are necessary and
must be adapted to each subsample.
Sibships of the carrier parent of a proband. Of 54 persons born to a
carrier female ancestor, there are 37 carriers and 17 normal. Of 27 persons
born to a carrier male ancestor there are 20 carriers and 7 normals.
Application of the truncated binomial (since the carrier parent is
included by necessity), gives an estimate higher than p = 0.60 which is beyond
the range of the published tables. This could indicate a preferential
transmission of the translocation, but it can be assumed that, in this
subsample, the bias is large not only because of the inclusion of at least one
carrier in each sibship, but also because the likelihood of recording the
family is effectively much greater if there are many carriers than if there are
Hence an application of the multiple selection equation is valid and
gives p = 0.528 ± 0.083 for the progeny of a female carrier ancestor and p =
0.588 + 0.119 for the progeny of a male carrier ancestor. These two estimates
do not differ significantly from each other and are fully compatible with an
expected 1 : 1 segregation among phenotypically normal persons. In othe
In other sibships in which the ascertainment is very close to random,
as far as the translocation in phenotypically normal persons is considered, we
Progeny of a carrier mother, including phenotypically normal children
in the sibships of probands and the sibships of aunts, great-aunts and female
cousins of the probands:
p = 52/106 = 0.49 ± 0.047
Progeny of a carrier father, including phenotypically normal children
in the sibships of probands and in the sibships of uncles, great-uncles and
male cousins of probands:
p = 20/39 = 0.51 ± 0.08
These two values are in agreement with a 1 : 1 segregation ratio and
this is the most bias-free sample we can utilise.
A final remark concerns the distribution of sexes. Among the carrier
children there are 54 males and 74 females but among the normale, there are 48
males and 47 females. This apparently curious sex ratio does not depart
significantly from homogeneity (?2 = 1.52 for ?= 1). However, the multiple
ascertainment bias and other possible mechanisms which could explain this
tendency require further investigation.
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