brief communications

Y-chromosome variation and Irish origins
A pre-neolithic gene gradation starts in the near East and culminates in western Ireland.
reland’s position on the western edge ofEurope suggests that the genetics of its
population should have been relatively
undisturbed by the demographic movements that have shaped variation on themainland. We have typed 221 Y chromosomes from Irish males for seven (slowlyevolving) biallelic and six (quickly evolving)
simple tandem-repeat markers. When thesesamples are partitioned by surname, wefind significant differences in genetic frequency between those of Irish Gaelic and of
foreign origin, and also between those ofeastern and western Irish origin. Connaught, the westernmost Irish province, liesat the geographical and genetic extreme of aEurope-wide cline.
Surnames have been used in Irelandfrom about AD 950 as markers of complex
local kinship systems. As both surnames
and Y chromosomes are paternally inherited, we divided our Irish sample into sevensurname cohorts for which ancient geographical information is known, with someerror. Four are of prehistoric, Gaelic origin(Ulster, Munster, Leinster and Connaught)
and three are diagnostic of historical influx(Scottish, Norman/Norse and English)1.
The biallelic markers (SRY-1532, M9,YAP, SRY-2627 (ref. 2); SRY-8299 (ref. 3);
sY81 (ref. 4); and 92R7 (ref. 5)) define nine
haplogroups (clusters of genetic variants)
which are highly non-randomly distributed
among human populations6, including oursamples. In particular, haplogroup 1 (hg 1)
has a very high frequency in Ireland (78.1%
in the island as a whole).
Surname subdivision reveals a cline inIrish samples, with exogenous samples
clearly showing lower frequencies (English,62.5%; Scottish, 52.9%; Norman/Norse,83.0%) than Gaelic Irish samples (Leinster,73.3%; Ulster, 81.1%; Munster, 94.6%),

I

Figure 1 Distribution of observed and estimated haplogroup 1
Y-chromosome haplotypes in Europe. A cline stretches from a frequency of 1.8% in Turkey to peaks in the Basque country (89%) andthe west of Ireland (98% in Connaught, the westernmost marker).

*

Figure 2 Consensus maximum parsimony networks of Irish Gaelic haplotypes summarizing both single tandem-repeat (DYS19, DYS3891,DYS390, DYS391, DYS392 and DYS393; ref. 14) and biallelic variation. Branch lengths are proportional to the number of mutational steps
and node areas are proportional to haplotype frequencies. Haplogroup (hg) 1, blue; hg 2, yellow; hg 21, green; hg 26, white. Asterisk, estimated ancestral haplotype. The separate clustering of haplogroups and the tight clustering of the Irish hg 1 haplotypes around a few numerous, central variants are constant through all most-parsimonious trees and were resistant to repetition of the analysis with randomized inputs.

which almost reach fixation in the westernmost province (Connaught, 98.3%). These
highly significant differences in the frequency of hg 1 between Irish Gaelic andnon-Gaelic Y chromosomes (P*0.001) andbetween eastern and western Gaelic Y chromosomes (P*0.001) persist when duplicated surnames are removed.
Eighty per cent (n426; ref. 7) of European hg 1 Y chromosomes belong to ‘haplotype 15’, defined by using the complex
p49f/TaqI polymorphic system8. Using thisrelationship, we estimated that hg 1 frequencies follow a cline within Europe9,extending from the Near East (1.8% inTurkey) to a peak in the Spanish Basquecountry (89%; ref. 10) in the west (Fig. 1).
This cline mirrors other genetic gradients in
Europe and is best explained by the migration of Neolithic farmers from the Near
East9. When the surname-divided Irish data
are appended to this cline, it continues tothe western edge of Europe, with hg 1 —the putative pre-Neolithic western European variant — reaching its highest frequency in Connaught (98.3%).
In a maximum-parsimony phylogenetic
analysis of both bialellic and simple tandem-repeat (STR) variation between Irish
Gaelic haplotypes (Fig. 2), the hg 1 chromosomes cluster together tightly, with thehighest-frequency haplotypes occupying
central positions, suggesting a coherent
common ancestry. The smaller number ofNATURE | VOL 404 | 23 MARCH 2000 | www.nature.com

non-hg 1 haplotypes shows no such coherence, consistent with their being immigrants. Their concentration in the eastern
Gaelic cohorts may be indicative of a prehistoric influx or of later gene flow acrossthe linguistic barrier from historicalmigrant groups.
These findings suggest that hg 1 is theearlier, indigenous Irish variant. By taking
the ancestral haplotype as that with themost common allele for each STR and calculating the average squared distance11(assuming a generation time of 27 years anda mutation rate of 0.21%; ref. 12) between it
and all variants (Fig. 2), we estimate a datefor Irish hg 1 coalescence of 4,200 BP (95%
c.i. 1,800–14,800 BP). This relatively recent
date (a global estimate of hg 1 coalescence is30,000 BP; ref. 13) falls well within Ireland’s
9,000-year history of human habitation.
Although error margins are considerable
and include uncertainty related to method,
this also provides an upper bound for any
agriculturally facilitated population expansion, which, at the fringe of Europe, may
have taken place in an insular Mesolithic
population of hg 1 genotype.
Emmeline W. Hill*, Mark A. Jobling†,
Daniel G. Bradley**Department of Genetics, Trinity College,
Dublin 2, Irelande-mail: dbradley@mail.tcd.ie†Department of Genetics, University of Leicester,
University Road, Leicester LE1 7RH, UK351© 2000 Macmillan Magazines Ltdbrief communications
1. MacLysaght, E. The Surnames of Ireland (Irish Academic,Dublin, 1997).
2. Hurles, M. E. et al. Am. J. Hum. Genet. 63, 1793–1806(1998).
3. Whitfield, L. S. et al. Nature 378, 379–380 (1995).
4. Seielstad, M. T. et al. Hum. Mol. Genet. 3, 2159–2161 (1994).
5. Hurles, M. E. et al. Am. J. Hum. Genet. 65, 1437–1448 (1999).
6. Jobling, M. A. & Tyler-Smith, C. Trends Genet. 11, 449–456(1995).

7. Jobling, M. A. Hum. Mol. Genet. 3, 107–114 (1994).
8. Ngo, K. Y. et al. Am. J. Hum. Genet. 38, 407–418 (1986).
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10. Lucotte, G. & Hazout, S. J. Mol. Evol. 42, 472–475 (1996).
11. Goldstein, D. B. et al. Proc. Natl Acad. Sci. USA 92, 6723–6727(1995).
12. Heyer, E. et al. Hum. Mol. Genet. 6, 799–803 (1997).
13. Hammer, M. F. et al. Mol. Biol. Evol. 15, 427–441 (1998)
14. Kayser, M. et al. Int. J. Legal Med. 110, 125–133 (1997).

Critical phenomena

scopic scales, resulting in universal behaviour1. The discovery of critical opalescenceat the critical point of carbon dioxide2,
caused by density fluctuations scattering light in the fluid, stimulated attempts toglimpse these fluctuations at all scales.
A monolayer of phospholipids at theinterface of air and water can be broughtclose to a critical point by varying thetemperature and surface pressure of themonolayer in a Langmuir trough3. We
immobilized the monolayer by transferringit, by horizontal dipping, to a solid,hydrophilic substrate of mica using Langmuir–Blodgett techniques4. We thenimaged critical fluctuations varying in size
from nanometres to micrometres using
contact-mode atomic-force microscopy.
Figure 1a and b shows two different lipid
monolayers — dimyristoyl phosphatidylcholine (DMPC) and dipalmitoyl phosphatidylcholine (DPPC) — close to theircritical points. When the monolayer passes
through the critical point, the acyl chains of
the lipids become disordered and themonolayer becomes thinner. As atomic
force microscopy maps the height contoursof the monolayer, these images show amonolayer structure with domains of one
phase within the other.
The height difference between the two
types of domain corresponds to the chainlength difference between an ordered and adisordered lipid acyl chain. Near the criticalpoint, these domains are dynamic and fluctuate strongly when the monolayer is at theair–water interface; we capture them
immobilized during the transfer process.
The morphology of the domains is very
ramified, owing to the vanishing line tension near criticality. Domains of all sizes
appear, indicating that there is no characteristic length scale — the hallmark of critical fluctuations.
Figure 1c shows a quantitative analysisof the domain patterns in terms of thestructure factor, S(q), where q is the lengthof a two-dimensional wavevector. The
structure-factor data for both DMPC andDPPC scale as a power law, S(q) ` q12x,with x ö 1. Within the accuracy of thedata, this is consistent with the criticalpoint behaviour associated with the universality class of the two-dimensional Isingmodel1.
Lipid domains in monolayers made ofphospholipid mixtures can be immobilized

Fluctuations caught
in the acthen a system approaches a criticalpoint, strong fluctuations develop
on every scale, from molecules tothe entire system. Here we show that criticalfluctuations in the domains in a lipid
monolayer can be captured and measured
by immobilizing it on a solid support andvisualizing the pattern using atomic-force
microscopy. Such fluctuations in physicalproperties may reflect the nanometre-scaledomain organization in the lipid-bilayercomponent of biological membranes.
Large numbers of interacting particles
show dramatic phase transitions and critical phenomena. At a critical point, molecular-scale interactions build up to macro-Wabc 102
101

DMPC 39 °CS (q)1

DMPC 20 °C
10–1
10–2
10–3
10–4
0.1

1

10100

q (µm–1)

Figure 1 Critical fluctuations in phospholipid monolayers imagedby atomic-force microscopy as a height-difference map. a,b,Images of dimyristoyl phosphatidylcholine (25225 mm2 ) anddipalmitoyl phosphatidylcholine (20220 mm2) monolayers attheir respective critical points. The monolayers have been transferred from an air–water interface to solid mica supports. The patterns correspond to lipid domains of one phase immersed into theother. The height difference between the light and dark areas is
about 5 Å. c, Quantitative analysis of many images like those in aand b in terms of the structure factor, S (q ), in arbitrary units,
shown in a double-logaritmic plot as a function of the wavevector,
q. The wavevector is related to distance, r, as q 4 2p/r. The
data for both phospholipids scale as S (q )ö q 12x, with x ö 1 forq 20 mm11. At low q there is a deviation from this power law
because of the finite size of the images analysed.

and imaged using similar techniques. Mixtures of phospholipids with acyl chains ofdifferent lengths show compositional
demixing on the nanometre scale5.
Monolayers are simple model systems of
the lipid bilayer component of cell membranes6. Functions supported by lipid bilayers, such as phospholipase activity7 andprotein binding8, are correlated with lipiddomain formation in the nanometre rangethat is controlled by the underlying phasetransition in the bilayer. Biological membranes contain many different lipid species
that are probably organized heterogeneously in the form of domains9–11 or ‘rafts’12 in
the plane of the membrane, though theprinciples underlying this organization
remain largely unknown. Our results suggest that fluctuations in lipid bilayer properties, for example, density or composition,
may be responsible for lipid-domain formation in biomembranes.
Lars K. Nielsen*, Thomas Bjørnholm†,
Ole G. Mouritsen**Department of Chemistry, Technical University ofDenmark, DK-2800 Lyngby, Denmark†CISMI, Laboratory for Materials Science,
Department of Chemistry, University ofCopenhagen, Fruebjergvej 3, DK-2100 Copenhagen,Denmarke-mail: ogm@kemi.dtu.dk
1. Stanley, H. E. Rev. Mod. Phys. 71, S358–S366 (1999).
2. Andrews, T. Phil. Trans. R. Soc. Lond. 159, 575–590 (1869).
3. Albrecht, O., Gruler, H. & Sackmann, E. J. Phys. (Paris) 39,301–313 (1978).
4. Knobler, C. M. & Schwartz, D. K. Curr. Opin. Colloid Interface
Sci. 4, 46–51 (1999).
5. Nielsen, L. K., Bjørnholm, T. & Mouritsen, O. G. J. Phys. Cond.
Mat. 12, 309–314 (2000).
6. Mouritsen, O. G. & Andersen, O. S. (eds) Biol. Skr. Kgl. Dan.
Vid. Selsk. 49, 1–214 (1998).
7. Hønger, T. et al. Biochemistry 35, 9003–9006 (1996).
8. Mustonen, P. et al. Biochemistry 26, 2991–2997 (1987).
9. Mouritsen, O. G. & Jørgensen, K. Curr. Opin. Struct. Biol. 7,518–527 (1997).
10. Edidin, M. Curr. Opin. Struct. Biol. 7, 528–532 (1997).
11. Korlach, J., Schwille, P., Webb, W. W. & Feigenson, G. W.
Proc. Natl Acad. Sci. USA 96, 8461–8466 (1999).
12. Simons, K. & Ikonen, E. Nature 387, 569–572 (1997).

Alzheimer’s disease

Apolipoprotein E andcognitive performance
ey proteins implicated in the development of Alzheimer’s disease are theb-amyloid precursor protein, which
gives rise to the b-amyloid peptides that
accumulate in the deteriorating brain1,2, andthe different isoforms of apolipoprotein E(apoE). The apoE4 variant increases therisk of developing the disease comparedwith apoE3 (ref. 3). We have tested the spatial memory of transgenic mice carrying
human forms of these proteins and findthat it is impaired in mice with apoE4 but
not those with apoE3, even though the levels of b-amyloid in their brains are comparable. The fact that apoE3, but not apoE4,

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