Post-genotyping optimization of dataset formation could affect genetic diversity parameters: an example of analyses with alpine goat breeds

Pogorevc, Neža; Simčič, Mojca; Khayatzadeh, Negar; Sölkner, Johann; Berger, Beate; Bojkovski, Danijela; Zorc, Minja; Dovč, Peter; Medugorac, Ivica; Horvat, Simon

doi:10.1186/s12864-021-07802-z

Table 1 Genetic diversity parameters of 23 goat populations included in AlpInit, Alp1Step, and Alp2Step datasets

From: Post-genotyping optimization of dataset formation could affect genetic diversity parameters: an example of analyses with alpine goat breeds

Breed label	N			nA			mA			*npA (nrA)*			*mpAf*			Ho			He			*Hdef*
Breed label	*AlpInit*	*Alp1Step*	*Alp2Step*	*AlpInit*	*Alp1Step*	*Alp2Step*	*AlpInit*	*Alp1Step*	*Alp2Step*	*AlpInit*	*Alp1Step*	*Alp2Step*	*AlpInit*	*Alp1Step*	*Alp2Step*	*AlpInit*	*Alp1Step*	*Alp2Step*	*AlpInit*	*Alp1Step*	*Alp2Step*	*AlpInit*	*Alp1Step*	*Alp2Step*
FR_CMA	52	48	33	58450	58037	54400	10.35	10.28	9.64	70 (192)	92 (247)	140 (273)	0.01	0.02	0.02	0.83	0.83	0.83	0.81	0.81	0.80	−0.02	−0.02	− 0.03
IT_VLD	24	24	17	51751	51751	45941	9.17	9.17	8.14	140 (179)	154 (196)	142 (220)	0.04	0.04	0.06	0.76	0.76	0.74	0.78	0.78	0.76	0.03	0.03	0.03
CH_SAA	64	39	38	48967	46885	45864	8.67	8.31	8.12	81 (136)	78 (135)	107 (169)	0.03	0.03	0.04	0.76	0.74	0.76	0.75	0.77	0.75	−0.01	0.04	− 0.01
CH_VAL	43	43	31	44043	44043	42644	7.80	7.80	7.55	68 (128)	71 (143)	84 (171)	0.06	0.06	0.06	0.73	0.73	0.73	0.72	0.72	0.72	−0.01	− 0.01	− 0.01
CH_NVR	42	42	37	55837	55837	54918	9.89	9.89	9.73	90 (180)	100 (193)	130 (249)	0.02	0.02	0.02	0.79	0.79	0.78	0.78	0.78	0.78	0.00	0.00	0.00
CH_TSG	37	37	28	58643	58643	53361	10.39	10.39	9.45	99 (183)	111 (200)	98 (184)	0.03	0.03	0.03	0.81	0.81	0.81	0.80	0.80	0.79	−0.01	− 0.01	− 0.03
CH_TGB	31	31	22	39223	39223	36651	6.95	6.95	6.49	41 (59)	43 (67)	50 (98)	0.04	0.04	0.06	0.73	0.73	0.72	0.71	0.71	0.70	−0.03	− 0.03	− 0.03
CH_APP	29	29	19	39237	39237	35852	6.95	6.95	6.35	45 (77)	47 (87)	43 (113)	0.05	0.05	0.07	0.72	0.72	0.72	0.70	0.70	0.69	−0.03	− 0.03	− 0.04
CH_BOT	23	23	19	42695	42695	41167	7.56	7.56	7.29	37 (75)	40 (79)	43 (98)	0.07	0.07	0.08	0.77	0.77	0.77	0.74	0.74	0.74	−0.04	−0.04	− 0.04
CH_PEA	31	31	31	50873	50873	50873	9.01	9.01	9.01	64 (108)	68 (125)	92 (188)	0.03	0.04	0.04	0.81	0.81	0.81	0.78	0.78	0.78	−0.04	−0.04	−0.04
CH_GST	49	49	38	52107	52107	50723	9.23	9.23	8.99	105 (171)	116 (187)	139 (225)	0.05	0.05	0.05	0.79	0.79	0.79	0.78	0.78	0.77	−0.02	−0.02	−0.02
CH_CHA	123	50	50	60731	56987	54484	10.76	10.10	9.65	70 (154)	71 (120)	67 (135)	0.01	0.01	0.02	0.80	0.80	0.79	0.79	0.79	0.79	−0.01	− 0.01	− 0.01
IT_ORO	23	23	20	46994	46994	44199	8.32	8.32	7.83	85 (137)	91 (150)	105 (175)	0.04	0.04	0.05	0.74	0.74	0.73	0.74	0.74	0.73	0.00	0.00	−0.01
IT_ABL	24	24	20	59640	59640	56520	10.57	10.57	10.01	188 (281)	205 (297)	225 (368)	0.03	0.03	0.03	0.82	0.82	0.83	0.82	0.82	0.81	−0.01	−0.01	− 0.02
IT_CMA	158	50	48	66261	62074	54050	11.74	11.00	9.57	124 (287)	91 (248)	50 (162)	0.01	0.01	0.03	0.81	0.82	0.82	0.82	0.82	0.79	0.01	0.01	−0.03
IT_VLP	24	24	20	60047	60047	57493	10.64	10.64	10.18	157 (293)	171 (315)	191 (363)	0.03	0.03	0.03	0.82	0.82	0.82	0.82	0.82	0.82	0.01	0.01	0.00
IT_PSR	22	22	19	54825	54825	52094	9.71	9.71	9.23	128 (209)	139 (222)	150 (269)	0.03	0.03	0.03	0.81	0.81	0.81	0.80	0.80	0.80	−0.01	−0.01	− 0.01
AT_BLB	34	34	28	60302	60302	58164	10.68	10.68	10.30	155 (308)	170 (332)	189 (377)	0.02	0.02	0.03	0.82	0.82	0.82	0.81	0.81	0.81	−0.01	− 0.01	−0.02
AT_CHA	22	22	22	50588	50588	50588	8.96	8.96	8.96	38 (91)	48 (105)	68 (121)	0.03	0.03	0.03	0.81	0.81	0.81	0.79	0.79	0.79	−0.02	−0.02	−0.02
AT_PNZ	27	27	22	55553	55553	51791	9.84	9.84	9.17	149 (273)	164 (291)	158 (306)	0.03	0.03	0.04	0.79	0.79	0.78	0.79	0.79	0.78	0.00	0.00	0.00
AT_TAP	28	28	24	44555	44555	43262	7.89	7.89	7.66	87 (186)	96 (197)	129 (235)	0.05	0.05	0.06	0.76	0.76	0.77	0.74	0.74	0.74	−0.03	− 0.03	− 0.04
SI_DRZ	133	50	50	64369	58802	55097	11.40	10.42	9.76	383 (520)	290 (439)	301 (482)	0.03	0.03	0.04	0.78	0.79	0.79	0.80	0.79	0.79	0.02	0.01	0.00
AT_STP	32	32	27	65543	65543	63180	11.61	11.61	11.19	301 (495)	326 (545)	382 (607)	0.02	0.02	0.03	0.85	0.85	0.85	0.84	0.84	0.83	−0.01	−0.01	−0.02

N sample size
nA total number of observed Alleles within subpopulation
mA mean number of alleles per block
npA number of private Alleles
nrA number of alleles present only in two subpopulations (this and anyone other)
mpAf mean frequency of private Alleles
Ho average observed Heterozygosity
He average expected Heterozygosity
Hdef Heterozygosity deficiency (He-Ho)/He

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