Spatial trends of genetic variation of domestic ruminants in Europe

Denis Laloë; Katayoun Moazami-Goudarzi; Johannes A. Lenstra; Paolo Ajmone Marsan; Pedro Azor; Roswitha Baumung; Daniel G. Bradley; Michael W. Bruford; Javier Cañón; Gaudenz Dolf; Susana Dunner; Georg Erhardt; Godfrey Hewitt; Juha Kantanen; Gabriela Obexer-Ruff; Ingrid Olsaker; Clemen Rodellar; Alessio Valentini; Pamela Wiener

doi:10.3390/d2060932

Spatial trends of genetic variation of domestic ruminants in Europe

Denis Laloë, Katayoun Moazami-Goudarzi, Johannes A. Lenstra, Paolo Ajmone Marsan, Pedro Azor, Roswitha Baumung, Daniel G. Bradley, Michael W. Bruford, Javier Cañón, Gaudenz Dolf, Susana Dunner, Georg Erhardt, Godfrey Hewitt, Juha Kantanen, Gabriela Obexer-Ruff, Ingrid Olsaker, Clemen Rodellar, Alessio Valentini, Pamela Wiener

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

The introduction of livestock species in Europe has been followed by various genetic events, which created a complex spatial pattern of genetic differentiation. Spatial principal component (sPCA) analysis and spatial metric multidimensional scaling (sMDS) incorporate geography in multivariate analysis. This method was applied to three microsatellite data sets for 45 goat breeds, 46 sheep breeds, and 101 cattle breeds from Europe, Southwest Asia, and India. The first two sPCA coordinates for goat and cattle, and the first sPCA coordinate of sheep, correspond to the coordinates of ordinary PCA analysis. However, higher sPCA coordinates suggest, for all three species, additional spatial structuring. The goat is the most geographically structured species, followed by cattle. For all three species, the main genetic cline is from southeast to northwest, but other geographic patterns depend on the species. We propose sPCA and sMDS to be useful tools for describing the correlation of genetic variation with geography. © 2010 by the authors; licensee MDPI, Basel, Switzerland.

Original language	English
Pages (from-to)	932-945
Number of pages	14
Journal	Diversity
Volume	2
Issue number	6
DOIs	https://doi.org/10.3390/d2060932
Publication status	Published - 1 Jun 2010

Keywords

Cattle
Diversity
Goat
Moran's I
Multidimensional Scaling
PCA
Sheep
Spatial structure
sPCA

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Laloë, D., Moazami-Goudarzi, K., Lenstra, J. A., Ajmone Marsan, P., Azor, P., Baumung, R., Bradley, D. G., Bruford, M. W., Cañón, J., Dolf, G., Dunner, S., Erhardt, G., Hewitt, G., Kantanen, J., Obexer-Ruff, G., Olsaker, I., Rodellar, C., Valentini, A., & Wiener, P. (2010). Spatial trends of genetic variation of domestic ruminants in Europe. Diversity, 2(6), 932-945. https://doi.org/10.3390/d2060932

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abstract = "The introduction of livestock species in Europe has been followed by various genetic events, which created a complex spatial pattern of genetic differentiation. Spatial principal component (sPCA) analysis and spatial metric multidimensional scaling (sMDS) incorporate geography in multivariate analysis. This method was applied to three microsatellite data sets for 45 goat breeds, 46 sheep breeds, and 101 cattle breeds from Europe, Southwest Asia, and India. The first two sPCA coordinates for goat and cattle, and the first sPCA coordinate of sheep, correspond to the coordinates of ordinary PCA analysis. However, higher sPCA coordinates suggest, for all three species, additional spatial structuring. The goat is the most geographically structured species, followed by cattle. For all three species, the main genetic cline is from southeast to northwest, but other geographic patterns depend on the species. We propose sPCA and sMDS to be useful tools for describing the correlation of genetic variation with geography. {\textcopyright} 2010 by the authors; licensee MDPI, Basel, Switzerland.",

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Laloë, D, Moazami-Goudarzi, K, Lenstra, JA, Ajmone Marsan, P, Azor, P, Baumung, R, Bradley, DG, Bruford, MW, Cañón, J, Dolf, G, Dunner, S, Erhardt, G, Hewitt, G, Kantanen, J, Obexer-Ruff, G, Olsaker, I, Rodellar, C, Valentini, A & Wiener, P 2010, 'Spatial trends of genetic variation of domestic ruminants in Europe', Diversity, vol. 2, no. 6, pp. 932-945. https://doi.org/10.3390/d2060932

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T1 - Spatial trends of genetic variation of domestic ruminants in Europe

AU - Laloë, Denis

AU - Moazami-Goudarzi, Katayoun

AU - Lenstra, Johannes A.

AU - Ajmone Marsan, Paolo

AU - Azor, Pedro

AU - Baumung, Roswitha

AU - Bradley, Daniel G.

AU - Bruford, Michael W.

AU - Cañón, Javier

AU - Dolf, Gaudenz

AU - Dunner, Susana

AU - Erhardt, Georg

AU - Hewitt, Godfrey

AU - Kantanen, Juha

AU - Obexer-Ruff, Gabriela

AU - Olsaker, Ingrid

AU - Rodellar, Clemen

AU - Valentini, Alessio

AU - Wiener, Pamela

PY - 2010/6/1

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N2 - The introduction of livestock species in Europe has been followed by various genetic events, which created a complex spatial pattern of genetic differentiation. Spatial principal component (sPCA) analysis and spatial metric multidimensional scaling (sMDS) incorporate geography in multivariate analysis. This method was applied to three microsatellite data sets for 45 goat breeds, 46 sheep breeds, and 101 cattle breeds from Europe, Southwest Asia, and India. The first two sPCA coordinates for goat and cattle, and the first sPCA coordinate of sheep, correspond to the coordinates of ordinary PCA analysis. However, higher sPCA coordinates suggest, for all three species, additional spatial structuring. The goat is the most geographically structured species, followed by cattle. For all three species, the main genetic cline is from southeast to northwest, but other geographic patterns depend on the species. We propose sPCA and sMDS to be useful tools for describing the correlation of genetic variation with geography. © 2010 by the authors; licensee MDPI, Basel, Switzerland.

AB - The introduction of livestock species in Europe has been followed by various genetic events, which created a complex spatial pattern of genetic differentiation. Spatial principal component (sPCA) analysis and spatial metric multidimensional scaling (sMDS) incorporate geography in multivariate analysis. This method was applied to three microsatellite data sets for 45 goat breeds, 46 sheep breeds, and 101 cattle breeds from Europe, Southwest Asia, and India. The first two sPCA coordinates for goat and cattle, and the first sPCA coordinate of sheep, correspond to the coordinates of ordinary PCA analysis. However, higher sPCA coordinates suggest, for all three species, additional spatial structuring. The goat is the most geographically structured species, followed by cattle. For all three species, the main genetic cline is from southeast to northwest, but other geographic patterns depend on the species. We propose sPCA and sMDS to be useful tools for describing the correlation of genetic variation with geography. © 2010 by the authors; licensee MDPI, Basel, Switzerland.

KW - Cattle

KW - Diversity

KW - Goat

KW - Moran's I

KW - Multidimensional Scaling

KW - PCA

KW - Sheep

KW - Spatial structure

KW - sPCA

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U2 - 10.3390/d2060932

DO - 10.3390/d2060932

M3 - Article

SN - 1424-2818

VL - 2

SP - 932

EP - 945

JO - Diversity

JF - Diversity

IS - 6

ER -

Spatial trends of genetic variation of domestic ruminants in Europe

Abstract

Keywords

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