Inbreeding and runs of homozygosity before and after genomic selection in North American Holstein cattle

Abstract

BackgroundWhile autozygosity as a consequence of selection is well understood, there is limited information on the ability of different methods to measure true inbreeding. In the present study, a gene dropping simulation was performed and inbreeding estimates based on runs of homozygosity (ROH), pedigree, and the genomic relationship matrix were compared to true inbreeding. Inbreeding based on ROH was estimated using SNP1101, PLINK, and BCFtools software with different threshold parameters. The effects of different selection methods on ROH patterns were also compared. Furthermore, inbreeding coefficients were estimated in a sample of genotyped North American Holstein animals born from 1990 to 2016 using 50 k chip data and ROH patterns were assessed before and after genomic selection.ResultsUsing ROH with a minimum window size of 20 to 50 using SNP1101 provided the closest estimates to true inbreeding in simulation study. Pedigree inbreeding tended to underestimate true inbreeding, and results for genomic inbreeding varied depending on assumptions about base allele frequencies. Using an ROH approach also made it possible to assess the effect of population structure and selection on distribution of runs of autozygosity across the genome. In the simulation, the longest individual ROH and the largest average length of ROH were observed when selection was based on best linear unbiased prediction (BLUP), whereas genomic selection showed the largest number of small ROH compared to BLUP estimated breeding values (BLUP-EBV). In North American Holsteins, the average number of ROH segments of 1 Mb or more per individual increased from 57 in 1990 to 82 in 2016. The rate of increase in the last 5 years was almost double that of previous 5 year periods. Genomic selection results in less autozygosity per generation, but more per year given the reduced generation interval.ConclusionsThis study shows that existing software based on the measurement of ROH can accurately identify autozygosity across the genome, provided appropriate threshold parameters are used. Our results show how different selection strategies affect the distribution of ROH, and how the distribution of ROH has changed in the North American dairy cattle population over the last 25 years.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-4453-z) contains supplementary material, which is available to authorized users.

Estimates of autozygosity through runs of homozygosity in farmed coho salmon

“…For both POP A and B 284 it was possible to identify short and long segments in most of the animals analyzed, whereas 285 in the POP C a small number of animals (n = 7) presented ROH8-16 Mb and none ROH>16 Mb. 286 In recent years, some studies have investigated different genomic methods to estimate 287 inbreeding coefficients in cattle [12,25,26,45,47,48], pigs [27,28,49,50], goats [51][52][53] and 288 rainbow trout [32]. However, this is the first study aimed at characterizing the ROH patterns 289 and comparing different genomic-and pedigree-based methods to estimate inbreeding 290 coefficients in farmed coho salmon populations.…”

“…In contrast, 294 genomic inbreeding can measure the realized inbreeding of an individual and incorporate the 295 breeding history of the animal, including new mutations, ancient and contemporary 296 inbreeding [27]. 297 A comparison of inbreeding coefficients, showed FGRM gave the highest values, 298 especially for B and C, probably because the alleles IBD and identical by state (IBS) are not 299 differentiated for FGRM [12]. This result is in agreement with results previously found in 300 humans, cattle, and simulation studies [12,15,16].…”

“…297 A comparison of inbreeding coefficients, showed FGRM gave the highest values, 298 especially for B and C, probably because the alleles IBD and identical by state (IBS) are not 299 differentiated for FGRM [12]. This result is in agreement with results previously found in 300 humans, cattle, and simulation studies [12,15,16]. FHOM resulted in negative inbreeding 301 values for all populations ( Table 3), suggesting that the individuals have lower levels of 302 homozygosity than expected in the reference population under Hardy-Weinberg equilibrium 303 [54] and underestimated values should be expected [55].…”

“…Thus, we expected a higher correlation between 329 long ROH segments (ROH8-16 Mb, and ROH>16 Mb) and FPED values. The weak or no 330 correlation may be explained by the depth of pedigree records [55], incorrect or incomplete 331 pedigree information [47], the FPED that assumed the founder individuals are unrelated [12], 332 15 and the fact that FPED does not consider the stochastic nature of recombination and the 333 persistence of ancestral short segments through time, due to the lack of recombination in 334 specific regions [11]. These facts suggest that the FPED may not reflect true inbreeding values.…”

“…51 Inbreeding is traditionally calculated using pedigree records, the estimates might not 52 reflect the true inbreeding level due to 1) the stochastic nature of recombination, 2) the 53 assumption that there are no changes in allele frequencies in time and 3) the persistence of 54 ancestral short segments through time [11]. In addition this approach fails to capture the 55 relatedness among founder animals from the base population [12]. Furthermore, previous 56 studies agreement that errors in pedigrees and incomplete or missing information lead to 57 incorrect or biased inbreeding estimates [13].…”