Fine-scale analysis of six beef cattle breeds revealed patterns of their genomic diversity

Figures & data

Table 1. Source of genome-wide data and sample size of analysed breeds.

Breed	Region of origin	Sample size	Genotyping Microarray	Data source
Aberdeen Angus	UK	90	BovineSNP50v1 BeadChip	Decker et al. (2009)
Charolais	France	53	BovineSNP50v1 BeadChip	Decker et al. (2009)
		71	International Dairy & Beef Chip	This study
Hereford	UK	98	BovineSNP50v1 BeadChip	Decker et al. (2009)
Limousin	France	100	BovineSNP50v1 BeadChip	Decker et al. (2009)
		17	International Dairy & Beef Chip	This study
Piedmontese	Italy	30	BovineSNP50v1 BeadChip	Decker et al. (2009)
Romagnola	Italy	29	BovineSNP50v1 BeadChip	Decker et al. (2009)
Slovak Pinzgau	Slovakia	151	BovineSNP50v2 BeadChip	This study

Figure 1. Distribution of single nucleotide polymorphisms (SNPs) (left y axis) and average minor allele frequency (MAF) frequency (right y axis) across autosomes.

Table 2. Genetic diversity indices for each breed.

Breed	Ho ± SD	He ± SD	MAF ± SD	FIS ± SD
Aberdeen Angus	0.316 ± 0.163	0.368 ± 0.200	0.245 ± 0.152	0.022 ± 0.073
Charolais	0.343 ± 0.150	0.412 ± 0.138	0.336 ± 0.143	0.155 ± 0.021
Hereford	0.327 ± 0.157	0.366 ± 0.181	0.257 ± 0.149	0.030 ± 0.094
Limousin	0.340 ± 0.158	0.377 ± 0.141	0.282 ± 0.135	0.077 ± 0.023
Piedmontese	0.348 ± 0.166	0.373 ± 0.177	0.258 ± 0.145	−0.023 ± 0.018
Romagnola	0.317 ± 0.181	0.389 ± 0.224	0.235 ± 0.153	−0.009 ± 0.038
Slovak Pinzgau	0.349 ± 0.151	0.353 ± 0.153	0.261 ± 0.143	−0.011 ± 0.034
Total	0.334 ± 0.162	0.377 ± 0.177	0.268 ± 0.149	0.047 ± 0.079

F_IS: fixation index; H_o: observed heterozygosity; H_e: expected heterozygosity; MAF: minor allele frequency; SD: standard deviation.

Table 3. The length (Mbp) and number (in brackets) of homozygous stretches for each run of homozygosity (ROH) category and breed.

Breed	ROH category	Average ± SD	Range	Proportion in genome (%)
Aberdeen Angus	1–2 Mbp	361.98 ± 148.12 (63.56 ± 13.83)	98.74–845.62 (23.00–98.00)	14.47
	2–4 Mbp	351.60 ± 148.04 (57.50 ± 13.51)	93.40–835.23 (20.00–90.00)	14.06
	4–8 Mbp	278.89 ± 145.38 (31.07 ± 11.62)	76.79–770.69 (12.00–58.00)	11.15
	8–16 Mbp	168.42 ± 121.08 (11.34 ± 6.77)	8.39–624.64 (1.00–31.00)	6.73
	> 16 Mbp	86.58 ± 93.27 (3.29 ± 3.28)	0.00–456.86 (0.00–15.00)	3.46
Charolais	1–2 Mbp	93.04 ± 48.48 (21.08 ± 7.06)	14.07–233.55 (7.00–48.00)	3.72
	2–4 Mbp	87.29 ± 48.58 (17.74 ± 6.51)	7.32–231.72 (3.00–44.00)	3.49
	4–8 Mbp	70.57 ± 44.41 (8.41 ± 3.67)	4.52–221.00 (1.00–20.00)	2.82
	8–16 Mbp	40.47 ± 38.91 (2.79 ± 2.22)	0.00–177.04 (0.00–10.00)	1.62
	> 16 Mbp	21.84 ± 29.45 0.84 ± 1.05)	0.00–141.53 (0.00–5.00)	0.87
Hereford	1–2 Mbp	396.29 ± 201.89 (70.06 ± 22.30)	117.72–1410.24 (24.00–128.00)	15.84
	2–4 Mbp	385.46 ± 201.35 (63.79 ± 2 1.63)	112.82–1404.27 (22.00–124.00)	15.41
	4–8 Mbp	307.34 ± 193.96 34.60 ± 1 5.484)	81.81–328.77 (12.00–90.00)	12.29
	8–16 Mbp	187.20 ± 165.21 (13.12 ± 9.25)	11.45–1133.59 (1.00–57.00)	7.48
	> 16 Mbp	93.29 ± 121.65 (3.67 ± 4.03)	0.00–779.11 (0.00–22.00)	3.73
Limousin	1–2 Mbp	89.67 ± 52.69 (17.47 ± 5.41)	19.88–333.95 (8.00–34.00)	3.59
	2–4 Mbp	84.66 ± 52.73 (14.50 ± 5 .17)	14.00–330.77 (5.00–31.00)	3.38
	4–8 Mbp	66.96 ± 50.11 7.09 ± 3.60)	0.00–308.61 (0.00–20.00)	2.68
	8–16 Mbp	43.20 ± 46.20 (2.87 ± 2.51)	0.00–261.34 (0.00–14.00)	1.73
	> 16 Mbp	22.66 ± 34.84 (0.89 ± 1.23)	0.00–216.55 (0.00–7.00)	0.91
Piedmontese	1–2 Mbp	36.91 ± 30.01 (7.83 ± 4.03)	8.25–158.87 (3.00–20.00)	1.48
	2–4 Mbp	34.66 ± 29.35 (6.55 ± 3.50)	8.25–155.37 (3.00–18.00)	1.39
	4–8 Mbp	25.94 ± 28.43 (2.76 ± 2.53)	0.00–143.30 (0.00–12.00)	1.04
	8–16 Mbp	16.24 ± 22.74 1.07 ± 1.31)	0.00–110.09 (0.00–6.00)	0.65
	> 16 Mbp	9.57 ± 21.01 (0.41 ± 0.87)	0.00–96.33 (0.00–4.00)	0.38
Romagnola	1–2 Mbp	230.73 ± 74.98 (36.17 ± 8.43)	100.05–396.04 (22.00–56.00)	9.22
	2–4 Mbp	225.01 ± 74.29 (32.89 ± 8.09)	96.20–387.61 (21.00–53.00)	8.99
	4–8 Mbp	195.52 ± 69.77 (19.24 ± 5.89)	68.01–362.70 (8.00–34.00)	7.82
	8–16 Mbp	137.84 ± 61.30 (8.90 ± 3.78)	22.46–286.28 (2.00–19.00)	5.51
	> 16 Mbp	79.00 ± 50.67 (3.14 ± 2.05)	0.00–178.42 (0.00–7.00)	3.16
Slovak Pinzgau	1–2 Mbp	73.79 ± 53.67 13.61 ± 7.13)	0.00–347.57 (0.00–37.00)	2.95
	2–4 Mbp	70.22 ± 52.93 11.49 ± 6.43)	0.00–344.42 (0.00–36.00)	2.81
	4–8 Mbp	56.51 ± 49.85 (5.93 ± 3.98)	0.00–337.58 (0.00–19.00)	2.26
	8–16 Mbp	37.32 ± 42.85 (2.46 ± 2.33)	0.00–331.60 (0.00–16.00)	1.49
	>16 Mbp	21.08 ± 34.66 (0.84 ± 1.20)	0.00–263.62 (0.00–7.00)	0.84

Mbp: megabase pair; SD: standard deviation.

Figure 2. Autosome-specific proportion of run of homozygosity (ROH) stretches with a minimum length 1 megabase pair (Mbp).

Figure 3. Relationships between the number and length of run of homozygosity (ROH) stretches (4–8 Mbp, 8–16 Mbp and > 16 Mbp). Mbp: megabase pair.

Table 4. Genomic inbreeding (%) derived from run of homozygosity (ROH) stretches with different length (4–8 Mbp, 8–16 Mbp and > 16 Mbp) for each breed.

Breed	Inbreeding coefficient	Average ± SD	Lower CI	Upper CI	Range
Aberdeen Angus	FROH4-8Mb	11.15 ± 5.81	9.93	12.37	3.07–30.81
	FROH8-16Mb	6.73 ± 4.84	5.72	7.75	0.34–24.97
	FROH>16Mb	3.46 ± 3.73	2.68	4.24	0.00–18.26
Charolais	FROH4-8Mb	2.82 ± 1.78	2.50	3.14	0.18–8.83
	FROH8-16Mb	1.62 ± 1.56	1.34	1.90	0.00–7.08
	FROH>16Mb	0.87 ± 1.18	0.66	1.09	0.00–5.66
Hereford	FROH4-8Mb	12.29 ± 7.75	10.73	13.84	3.27–53.12
	FROH8-16Mb	7.48 ± 6.60	6.16	8.81	0.46–45.31
	FROH>16Mb	3.73 ± 4.86	2.75	4.70	0.00–31.14
Limousin	FROH4-8Mb	2.68 ± 2.00	2.31	3.04	0.00–12.34
	FROH8-16Mb	1.73 ± 1.85	1.39	2.07	0.00–10.45
	FROH>16Mb	0.91 ± 1.39	0.65	1.16	0.00–8.66
Piedmontese	FROH4-8Mb	1.04 ± 1.13	0.61	1.47	0.00–5.73
	FROH8-16Mb	0.65 ± 0.91	0.30	1.00	0.00–4.40
	FROH>16Mb	0.38 ± 0.84	0.06	0.70	0.00–3.85
Romagnola	FROH4-8Mb	7.82 ± 2.79	6.76	8.88	2.72–14.50
	FROH8-16Mb	5.51 ± 2.45	4.58	6.44	0.90–11.44
	FROH>16Mb	3.16 ± 2.03	2.39	3.93	0.00–7.13
Slovak Pinzgau	FROH4-8Mb	2.26 ± 1.99	1.94	2.58	0.00–13.49
	FROH8-16Mb	1.49 ± 1.71	1.21	1.77	0.00–13.26
	FROH>16Mb	0.84 ± 1.39	0.62	1.07	0.00–10.54

SD: standard deviation; CI: confidence interval.

Table 5. Average level of linkage disequilibrium in the genome of the studied breeds.

Breed	No. of SNP pairs	${\mathit{r}}_{\mathit{LD}}^2$ ± SD	SNP pairs with ${\mathit{r}}_{\mathit{LD}}^2$>0.3 (%)
Aberdeen Angus	2450579	0.149 ± 0.077	4.23
Charolais	1320646	0.119 ± 0.031	8.71
Hereford	2419523	0.162 ± 0.088	5.06
Limousin	1995006	0.112 ± 0.043	5.52
Piedmontese	2636210	0.103 ± 0.057	1.44
Romagnola	2535148	0.143 ± 0.053	5.68
Slovak Pinzgau	1330045	0.183 ± 0.056	0.63

SD: standard deviation; SNP: single nucleotide polymorphism; r²_LD; linkage disequilibrium.

Figure 4. The relationship between linkage disequilibrium (LD) and inter-marker distance.

Figure 5. The trend of effective population size for the analysed breeds over the last 60 generations.

Figure 6. Genetic differentiation within and between evaluated populations based on discriminant analysis of principal components (DAPC) (A), first discriminant function of DAPC (B) and individual membership probabilities suggested by a model-based Bayesian clustering approach (C).

Table 6. Genetic relationships among populations based on the Wright’s statistics (under the diagonal) and Nei’s genetic distances (above the diagonal).

	Aberdeen Angus	Hereford	Limousin	Charolais	Piedmontese	Romagnola	Slovak Pinzgau
Aberdeen Angus		0.080	0.059	0.058	0.066	0.097	0.075
Hereford	0.114		0.063	0.055	0.068	0.098	0.072
Limousin	0.082	0.087		0.034	0.038	0.070	0.069
Charolais	0.079	0.076	0.044		0.045	0.074	0.076
Piedmontese	0.088	0.090	0.045	0.052		0.061	0.053
Romagnola	0.131	0.132	0.090	0.092	0.076		0.096
Slovak Pinzgau	0.102	0.099	0.086	0.073	0.070	0.122

Table 7. The membership proportion of individual breeds.

	Slovak Pinzgau	Aberdeen Angus	Piedmontese	Romagnola	Hereford	Limousin	Charolais
Aberdeen Angus	0.007	0.951	0.005	0.004	0.017	0.006	0.009
Hereford	0.014	0.025	0.013	0.005	0.929	0.006	0.007
Limousin	0.010	0.014	0.012	0.007	0.009	0.933	0.015
Charolais	0.004	0.020	0.008	0.004	0.018	0.035	0.911
Piedmontese	0.019	0.010	0.782	0.116	0.009	0.046	0.018
Romagnola	0.005	0.003	0.031	0.951	0.001	0.005	0.004
Slovak Pinzgau	0.966	0.005	0.012	0.006	0.006	0.003	0.001

Bold values mean the highest membership probabilities identified within particular population/group.

Decker JE, Pires JC, Conant GC, McKay SD, Heaton MP, Chen K, Cooper A, Vilkki J, Seabury CM, Caetano AR, et al. 2009. Resolving the evolution of extant and extinct ruminants with high-throughput phylogenomics. Proc Natl Acad Sci U S A. 106:18644–18649.

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