How Geography and Climate Shaped the Genomic Diversity of Italian Local Cattle and Sheep Breeds

Abstract

Understanding the relationships among geography, climate, and genetics is increasingly important for animal farming and breeding. In this study, we examine these inter-relationships in the context of local cattle and sheep breeds distributed along the Italian territory. To this aim, we used redundancy analysis on genomic data from previous projects combined with geographical coordinates and corresponding climatic data. The effect of geographic factors (latitude and longitude) was more important in sheep (26.4%) than that in cattle (13.8%). Once geography had been partialled out of analysis, 10.1% of cattle genomic diversity and 13.3% of that of sheep could be ascribed to climatic effects. Stronger geographic effects in sheep can be related to a combination of higher pre-domestication genetic variability together with biological and productive specificities. Climate alone seems to have had less impact on current genetic diversity in both species, even if climate and geography are greatly confounded. Results confirm that both species are the result of complex evolutionary histories triggered by interactions between human needs and environmental conditions.

Keywords: cattle; cilmate; genome; geography; redundancy analysis; sheep.

Figure 1

Distribution of cattle and sheep breeds on the map of Italy. Locations correspond to the original geographical cradle of the breed. Points and labels colored by species: bovine in red, ovine in blue.

Figure 2

Correlation circle representation of the bioclimatic variables in the first two dimensions of the principal component analysis (PCA) of Climond data. Variables are colored according to their type (deep blue: radiation, green: rain, red: temperature, light blue: moisture). Labels are explained in Table S1. Latitude and longitude were projected as supplementary variables and are shown in grey. Top right within the insert is the corresponding scree plot (eigenvalues, bar plot).

Figure 3

Bubble-plot maps of the climatic PCA scores for: (a) cattle breeds (top) and (b) sheep breeds (bottom) for Axis 1 (left) and Axis 2 (right). Black square bubbles indicate positive score values; white square bubbles indicate negative square values; square size is proportional to the absolute score values.

Figure 4

Bovine genome between−breed analysis. Bubble plots of the values of the bovine breeds scores for the first two principal components (left: PC1; right: PC2). Breeds are located at their original geographical cradle. Black bubbles have positive values and white ones negative values; square size is proportional to the score absolute values.

Figure 5

Cattle genome redundancy analysis (RDA) according to the model genome ∼ geography. Bubble plots of the values of the breed scores for the first two principal components (left: PC1; right: PC2). Black square bubbles are positive; white square bubbles are negative; square size is proportional to the score absolute values.

Figure 6

Bovine genome redundancy analysis (RDA) according to the model genome ∼ climate partialled out for geography. Bubble plots of the breed scores for the first principal component. Black square bubbles are positive; white square bubbles are negative; square size is proportional to the score absolute values.

Figure 7

Ovine genome between-breed analysis. Bubble plots of the bovine breeds scores for the first two principal components (left: PC1; right: PC2). Breeds are located at their original geographical cradle. Black square bubbles are positive; white square bubbles are negative; square size is proportional to the score absolute values.

Figure 8

Ovine genome redundancy analysis (RDA) according to the model genome ∼ geography. Bubble plots of the values of the sheep breeds scores for the first two principal components (left: PC1; right: PC2). Black square bubbles are positive; white square bubbles are negative; square size is proportional to the score absolute values.

Figure 9

Ovine genome redundancy analysis (RDA) according to the model genome ∼ climate, partialled out for geography. Bubble plots of the values of the sheep breed scores for the first principal component. Black square bubbles are positive; white square bubbles are negative; square size is proportional to the score absolute values.