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M.H.D. Larmuseau et al. / Forensic Science International: Genetics 5 (2011) 95–99

98

Table 2
Tests for population differentiation based on the Y-haplogroup frequencies and Y-haplotypes.
Region

N

Ns

Nh

Noord-Brabant (NL)
Antwerpen (B)
Kempen (B)
Mechelen (B)
Vlaams and Waals Brabant (B)

130
72
77
63
135

128
68
72
61
131

24
13
17
19
26

FST value on Y-SNPs
(P-value)
0.00605 (0.03*)
0.00111 (0.29)
0.00150 (0.27)
0.00297 (0.72)
0.00234 (0.16)

FST value on Y-STRs
(P-value)
0.00398 (0.03*)
0.00031 (0.48)
0.00339 (0.09)
0.00121 (0.74)
0.00131 (0.17)

RST value on Y-STRs
(P-value)
0.00494
0.00059
0.00339
0.00117
0.00131

(0.06)
(0.35)
(0.09)
(0.48)
(0.17)

The Y-chromosomes from one region were compared with all chromosomes from the other regions in Brabant combined. N, number of individuals; Ns, number of individuals
when only one participant was taken into account for pairs with the same family name, the same genealogical region and belonging to the same subhaplogroup; Nh, number
of observed subhaplogroups; NL, The Netherlands; B, Belgium. Significant P-values (P-value < 0.05) are given in bold and with an asterisk.

Based on the 37 Y-STR loci, all non-related individuals were
distinct from each other. This is in contrast to the ‘minimal and
extended haplotypes’ based on nine and eleven STR loci,
respectively. Moreover, several individuals revealed the same
‘minimal and extended haplotypes’ but belonged to a different
subhaplogroup based on SNP-typing. This illustrates the necessity
to genotype more than the usual nine or eleven Y-STRs to declare
biological relatedness between individuals. The usefulness of a
high number of genotyped Y-STRs was also reflected in the ability
to find clusters within the network analyses associated with the
observed subhaplogroups in haplogroups E and J. Moreover, it was
even possible to detect further substructuring within subhaplogroup J2a* (J-M410*) based on the network analysis of all
single-allele Y-STR haplotypes. Nevertheless, it was remarkable
that the network analyses could not differentiate all observed
subhaplogroups within R1b1b2 (R-M269) and I2b (I-M223). This
might be due to the relatively young age of these specific
subhaplogroups making it impossible to differentiate these groups
based on the Y-STRs. Though, the estimated tMRCAs of these
subhaplogroups were not that much younger in comparison with
other subhaplogroups. A different reason might be the high
effective population size of these haplogroups with a high present
variation causing a high occurrence of back mutation and
homoplasy.
Population differentiation based on Y-chr variation was
observed across a transect of approximately 150 km. The genetic
differentiation was statistically significant between the Dutch and
the combined Belgian areas within Brabant based on the
frequencies of the subhaplogroups, rather than on the haplotypes
within the main subhaplogroups. Although the FST-values were
low, the differentiation was indeed detectable along the transect
based on the haplogroup frequencies. There is a clear downward
trend of the frequency of haplogroup R with a difference of 10%
across the most northern and southern part of Brabant. The main
reason for this observation was the downward trend in R1b1b2a1
(R-U106), which is the subhaplogroup with the highest average
frequency in Brabant (27.67%). It is likely that the trend on R-U106
is linked to the genetic barrier between The Netherlands and
France that was previous announced [23,24]. Based on limited data
of Y-chr subhaplogroup frequencies, there seems to be a higher
occurrence of subhaplogroup R1b1b2a1 (R-U106) in The Netherlands (37.2%) than in France (7.1%) [25]. Therefore it is likely that
the differentiation observed in this study, which is mainly based on
R-U106, is indeed related to the suggested barrier of Rosser et al.
[23]. The study on Brabant indicates that the ‘barrier’ between The
Netherlands and France is in fact a long gradient according to
isolation-by-distance instead of a steep clinal shift according to a
barrier to gene flow. Nevertheless, because of the strong
heterogeneous distribution of the paternally inherited surnames
in Belgium related to the different language communities, it was
likely that the suggested barrier was associated with the RomanceGermanic language border within Western Europe [26]. To

understand the present micro-geographical differentiation within
Brabant and its relationship to the language border, the inclusions
of other regions in Belgium into the analysis is required.
The results of this study on Brabant clearly show that significant
differences in Y-chr (sub)haplogroup frequencies on a microgeographical scale are important to be taken into account for
forensic applications. For this reason, future research needs to
focus on genetic differentiation on a regional scale using reliable
genealogical data. This study exemplifies the necessity of
collaboration between forensic and population genetic researchers
and the genetic genealogy community.
Acknowledgements
The authors thank all the volunteers who donated DNA samples
used in this study. They acknowledge the Flemish Society for
Genealogical Research (Antwerp) that was involved in the
collection of the samples and the genealogical data. They are also
grateful to Jeroen Van Houdt and Bram Bekaert for useful
discussions. This study was funded by the Flemish Society for
Genealogical Research (Antwerp) and by a grant from the Flanders
Ministry of Culture. MHDL received a postdoctoral position of the
K.U.Leuven (BOF PDM-Kort).

Appendix A. Supplementary data
Supplementary data associated with this article can be found, in
the online version, at doi:10.1016/j.fsigen.2010.08.020.
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