The value of genomic relationship matrices to estimate levels of inbreeding

Impact of inbreeding on production, fertility, and health traits in German Holstein dairy cattle utilizing various inbreeding estimators

In dairy cattle production, it is important to understand how inbreeding affects production, fertility, and health traits. However, there is still limited use of genomic information to estimate inbreeding, despite advancements in genotyping technologies. To address this gap, we investigated the impact of inbreeding on German Holstein dairy cattle using both pedigree-based and genomic-based inbreeding estimators. We employed one method based on pedigree information (Fped) together with 6 genomic-based methods, including 3 GCTA estimators (Fhat1, Fhat2, Fhat3), VanRaden's first method (FVR1, with observed allele frequencies and FVR0.5 when allele frequencies are set to 0.5), and one based on runs of homozygosity (Froh). Data from 24,489 cows with both phenotypes and genotypes were used, with a pedigree including 232,780 animals born between 1970 and 2018. We analyzed the effects of inbreeding depression on production, fertility, and health traits separately, using single-trait linear animal models as well as threshold models to account for the binary nature of the health traits. For the health traits, we transformed solutions from the liability scale to a probability scale for easier interpretation. Our results showed that the mean inbreeding coefficients from all estimators ranged from -0.003 to 0.243, with negative values observed for most genomic-based methods. We found out that a 1% increase in inbreeding caused a depression ranging from 25.94 kg (Fhat1) to 40.62 kg (Fhat3), 1.18 kg (Fhat2) to 1.70 kg (Fhat3), 0.90 kg (Fhat2) to 1.45 kg (Froh and Fhat3), 0.19 (Fped) to 0.34 d (Fhat3) for 305 d milk yield, fat, protein, and calving interval respectively. The health traits showed slight changes when inbreeding was gradually increased by 5% with digital dermatitis showing rather a contrasting trend to that of mastitis which reduced the more an animal was inbred. Overall, our study highlights the importance of considering both pedigree-based and genomic-based inbreeding estimators when assessing the impact on inbreeding, emphasizing that not all inbreeding is harmful.

Whole-Genome Resequencing Reveals Genetic Diversity and Wool Trait-Related Genes in Liangshan Semi-Fine-Wool Sheep

Understanding the genetic makeup of local sheep breeds is essential for their scientific conservation and sustainable utilization. The Liangshan semi-fine-wool sheep (LSS), a Chinese semi-fine-wool breed renowned for its soft wool, was analyzed using whole-genome sequencing data including 35 LSS, 84 sheep from other domestic breeds, and 20 Asiatic mouflons. We investigated the genetic composition of LSS by conducting analyses of the population structure, runs of homozygosity, genomic inbreeding coefficients, and selection signature. Our findings indicated that LSS shares greater genetic similarity with Border Leicester and Romney sheep than with Tibetan (TIB), Yunnan (YNS), and Chinese Merino sheep. Genomic analysis indicated low to moderate inbreeding coefficients, ranging from 0.014 to 0.154. In identifying selection signals across the LSS genome, we pinpointed 195 candidate regions housing 74 annotated genes (e.g., IRF2BP2, BVES, and ALOX5). We also found the overlaps between the candidate regions and several known quantitative trait loci related to wool traits, such as the wool staple length and wool fiber diameter. A selective sweep region, marked by the highest value of cross-population extended haplotype homozygosity, encompassed IRF2BP2-an influential candidate gene affecting fleece fiber traits. Furthermore, notable differences in genotype frequency at a mutation site (c.1051 + 46T > C, Chr25: 6,784,190 bp) within IRF2BP2 were observed between LSS and TIB and YNS sheep (Fisher's exact test, p < 2.2 × 10-16). Taken together, these findings offer insights crucial for the conservation and breeding enhancement of LSS.

Genomic inbreeding measures applied to a population of mice divergently selected for birth weight environmental variance

This study aimed to compare different inbreeding measures estimated from pedigree and molecular data from two divergent mouse lines selected for environmental birth weight during 26 generations. Furthermore, the performance of different approaches and both molecular and pedigree data sources for estimating Ne were tested in this population. A total of 1,699 individuals were genotyped using a high-density genotyping array. Genomic relationship matrices were used to calculate molecular inbreeding: Nejati-Javaremi (F NEJ), Li and Horvitz (F L&H), Van Raden method 1 (F VR1) and method 2 (F VR2), and Yang (F YAN). Inbreeding based on runs of homozygosity (F ROH) and pedigree inbreeding (F PED) were also computed. F ROH, F NEJ, and F L&H were also adjusted for their average values in the first generation of selection and named F ROH0, F NEJ0, and F L&H0. ∆F was calculated from pedigrees as the individual inbreeding rate between the individual and his parents (∆F PEDt) and individual increases in inbreeding (∆F PEDi). Moreover, individual ∆F was calculated from the different molecular inbreeding coefficients (∆F NEJ0, ∆F L&H, ∆F L&H0, ∆F VR1, ∆F VR2, ∆F YAN, and ∆F ROH0). The Ne was obtained from different ∆F, such as Ne PEDt, Ne PEDi, Ne NEJ0, Ne L&H, Ne L&H0, Ne VR1, Ne VR2, Ne YAN, and Ne ROH0. Comparing with F PED , F ROH , F NEJ and F VR2 overestimated inbreeding while F NEJ0 , F L&H , F L&H0 , F VR1 and F YAN underestimated inbreeding. Correlations between inbreeding coefficients and ∆F were calculated. F ROH had the highest correlation with F PED (0.89); F YAN had correlations >0.95 with all the other molecular inbreeding coefficients. Ne PEDi was more reliable than Ne PEDt and presented similar behaviour to Ne L&H0 and Ne NEJ0. Stable trends in Ne were not observed until the 10th generation. In the 10th generation Ne PEDi was 42.20, Ne L&H0 was 45.04 and Ne NEJ0 was 45.05 and in the last generation these Ne were 35.65, 35.94 and 35.93, respectively F ROH presented the highest correlation with F PED, which addresses the identity by descent probability (IBD). The evolution of Ne L&H0 and Ne NEJ0 was the most similar to that of Ne PEDi. Data from several generations was necessary to reach a stable trend for Ne, both with pedigree and molecular data. This population was useful to test different approaches to computing inbreeding coefficients and Ne using molecular and pedigree data.

Approaching autozygosity in a small pedigree of Gochu Asturcelta pigs

BACKGROUND

In spite of the availability of single nucleotide polymorphism (SNP) array data, differentiation between observed homozygosity and that caused by mating between relatives (autozygosity) introduces major difficulties. Homozygosity estimators show large variation due to different causes, namely, Mendelian sampling, population structure, and differences among chromosomes. Therefore, the ascertainment of how inbreeding is reflected in the genome is still an issue. The aim of this research was to study the usefulness of genomic information for the assessment of genetic diversity in the highly endangered Gochu Asturcelta pig breed. Pedigree depth varied from 0 (founders) to 4 equivalent discrete generations (t). Four homozygosity parameters (runs of homozygosity, FROH; heterozygosity-rich regions, FHRR; Li and Horvitz's, FLH; and Yang and colleague's FYAN) were computed for each individual, adjusted for the variability in the base population (BP; six individuals) and further jackknifed over autosomes. Individual increases in homozygosity (depending on t) and increases in pairwise homozygosity (i.e., increase in the parents' mean) were computed for each individual in the pedigree, and effective population size (Ne) was computed for five subpopulations (cohorts). Genealogical parameters (individual inbreeding, individual increase in inbreeding, and Ne) were used for comparisons.

RESULTS

The mean F was 0.120 ± 0.074 and the mean BP-adjusted homozygosity ranged from 0.099 ± 0.081 (FLH) to 0.152 ± 0.075 (FYAN). After jackknifing, the mean values were slightly lower. The increase in pairwise homozygosity tended to be twofold higher than the corresponding individual increase in homozygosity values. When compared with genealogical estimates, estimates of Ne obtained using FYAN tended to have low root-mean-squared errors. However, Ne estimates based on increases in pairwise homozygosity using both FROH and FHRR estimates of genomic inbreeding had lower root-mean-squared errors.

CONCLUSIONS

Parameters characterizing homozygosity may not accurately depict losses of variability in small populations in which breeding policy prohibits matings between close relatives. After BP adjustment, the performance of FROH and FHRR was highly consistent. Assuming that an increase in homozygosity depends only on pedigree depth can lead to underestimating it in populations with shallow pedigrees. An increase in pairwise homozygosity computed from either FROH or FHRR is a promising approach for characterizing autozygosity.

Construction and genetic characterization of an interspecific raspberry hybrids panel aiming resistance to late leaf rust and adaptation to tropical regions

Raspberries (Rubus spp) are temperate climate fruits with profitable high returns and have the potential for diversification of fruit growing in mid to low-latitude regions. However, there are still no cultivars adapted to climatic conditions and high pressure of diseases that occurs in tropical areas. In this context, our objective was to evaluate the genetic diversity from a 116 raspberry genotypes panel obtained from interspecific crosses in a testcross scheme with four cultivars already introduced in Brazil. The panel was genotyped via genotyping-by-sequencing. 28,373 and 27,281 SNPs were obtained, using the species R. occidentalis and R. idaeus genomes as references, respectively. A third marker dataset was constructed consisting of 41,292 non-coincident markers. Overall, there were no differences in the results when using the different marker sets for the subsequent analyses. The mean heterozygosity was 0.54. The average effective population size was 174, indicating great genetic variability. The other analyses revealed that the half-sibling families were structured in three groups. It is concluded that the studied panel has great potential for breeding and further genetic studies. Moreover, only one of the three marker matrices is sufficient for diversity studies.

Comparing pedigree and genomic inbreeding coefficients, and inbreeding depression of reproductive traits in Japanese Black cattle

BACKGROUND

Pedigree-based inbreeding coefficients have been generally included in statistical models for genetic evaluation of Japanese Black cattle. The use of genomic data is expected to provide precise assessment of inbreeding level and depression. Recently, many measures have been used for genome-based inbreeding coefficients; however, with no consensus on which is the most appropriate. Therefore, we compared the pedigree- ([Formula: see text]) and multiple genome-based inbreeding coefficients, which were calculated from the genomic relationship matrix with observed allele frequencies ([Formula: see text]), correlation between uniting gametes ([Formula: see text]), the observed vs expected number of homozygous genotypes ([Formula: see text]), runs of homozygosity (ROH) segments ([Formula: see text]) and heterozygosity by descent segments ([Formula: see text]). We quantified inbreeding depression from estimating regression coefficients of inbreeding coefficients on three reproductive traits: age at first calving (AFC), calving difficulty (CD) and gestation length (GL) in Japanese Black cattle.

RESULTS

The highest correlations with [Formula: see text] were for [Formula: see text] (0.86) and [Formula: see text] (0.85) whereas [Formula: see text] and [Formula: see text] provided weak correlations with [Formula: see text], with range 0.33-0.55. Except for [Formula: see text] and [Formula: see text], there were strong correlations among genome-based inbreeding coefficients ([Formula: see text] 0.94). The estimates of regression coefficients of inbreeding depression for [Formula: see text] was 2.1 for AFC, 0.63 for CD and -1.21 for GL, respectively, but [Formula: see text] had no significant effects on all traits. Genome-based inbreeding coefficients provided larger effects on all reproductive traits than [Formula: see text]. In particular, for CD, all estimated regression coefficients for genome-based inbreeding coefficients were significant, and for GL, that for [Formula: see text] had a significant.. Although there were no significant effects when using overall genome-level inbreeding coefficients for AFC and GL, [Formula: see text] provided significant effects at chromosomal level in four chromosomes for AFC, three chromosomes for CD, and two chromosomes for GL. In addition, similar results were obtained for [Formula: see text].

CONCLUSIONS

Genome-based inbreeding coefficients can capture more phenotypic variation than [Formula: see text]. In particular, [Formula: see text] and [Formula: see text] can be considered good estimators for quantifying inbreeding level and identifying inbreeding depression at the chromosome level. These findings might improve the quantification of inbreeding and breeding programs using genome-based inbreeding coefficients.

Genetic gain and inbreeding from simulation of different genomic mating schemes for pig improvement

BACKGROUND

Genomic selection involves choosing as parents those elite individuals with the higher genomic estimated breeding values (GEBV) to accelerate the speed of genetic improvement in domestic animals. But after multi-generation selection, the rate of inbreeding and the occurrence of homozygous harmful alleles might increase, which would reduce performance and genetic diversity. To mitigate the above problems, we can utilize genomic mating (GM) based upon optimal mate allocation to construct the best genotypic combinations in the next generation. In this study, we used stochastic simulation to investigate the impact of various factors on the efficiencies of GM to optimize pairing combinations after genomic selection of candidates in a pig population. These factors included: the algorithm used to derive inbreeding coefficients; the trait heritability (0.1, 0.3 or 0.5); the kind of GM scheme (focused average GEBV or inbreeding); the approach for computing the genomic relationship matrix (by SNP or runs of homozygosity (ROH)). The outcomes were compared to three traditional mating schemes (random, positive assortative or negative assortative matings). In addition, the performance of the GM approach was tested on real datasets obtained from a Large White pig breeding population.

RESULTS

Genomic mating outperforms other approaches in limiting the inbreeding accumulation for the same expected genetic gain. The use of ROH-based genealogical relatedness in GM achieved faster genetic gains than using relatedness based on individual SNPs. The G_ROH-based GM schemes with the maximum genetic gain resulted in 0.9%-2.6% higher rates of genetic gain ΔG, and 13%-83.3% lower ΔF than positive assortative mating regardless of heritability. The rates of inbreeding were always the fastest with positive assortative mating. Results from a purebred Large White pig population, confirmed that GM with ROH-based GRM was more efficient than traditional mating schemes.

CONCLUSION

Compared with traditional mating schemes, genomic mating can not only achieve sustainable genetic progress but also effectively control the rates of inbreeding accumulation in the population. Our findings demonstrated that breeders should consider using genomic mating for genetic improvement of pigs.

Genomic inbreeding coefficients using imputed genotypes: assessing differences among SNP panels in Holstein-Friesian dairy cows

The objective of this study was to evaluate the effect of imputation of single nucleotide polymorphisms (SNP) on the estimation of genomic inbreeding coefficients. Imputed genotypes of 68,127 Italian Holstein dairy cows were analyzed. Cows were initially genotyped with two high density (HD) SNP panels, namely the Illumina Infinium BovineHD BeadChip (678 cows; 777,962 SNP) and the Genomic Profiler HD-150K (641 cows; 139,914 SNP), and four medium density (MD): GeneSeek Genomic Profiler 3 (10,679 cows; 26,151 SNP), GeneSeek Genomic Profiler 4 (33,394 cows; 30,113 SNP), GeneSeek MD (12,030 cows; 47,850 SNP) and the Labogena MD (10,705 cows; 41,911 SNP). After imputation, all cows had genomic information on 84,445 SNP. Seven genomic inbreeding estimators were tested: (i) four PLINK v1.9 estimators (F, F_hat1,2,3), (ii) two genomic relationship matrix (grm) estimators [VanRaden's 1^st method, but with observed allele frequencies (F_grm) and VanRaden's 3^rd method that is allelic free and pedigree dependent (F_grm2)], and (iii) a runs of homozygosity (roh) - based estimator (F_roh). Genomic inbreeding coefficients of each SNP panel were compared with genomic inbreeding coefficients derived from the 84,445 imputation SNP. Coefficients of the HD SNP panels were consistent between genotyped-imputed SNP (Pearson correlations ~99%), while variability across SNP panels and estimators was observed in the MD SNP panels, with Labogena MD providing, on average, more consistent estimates. The robustness of Labogena MD, can be partly explained by the fact that 97.85% of the SNP of this panel is included in the 84,445 SNP selected by ANAFIBJ for routine genomic imputations, while this percentage for the other MD SNP panels varied between 55 and 60%. Runs of homozygosity was the most robust estimator. Genomic inbreeding estimates using imputation SNP are influenced by the SNP number of the SNP panel that are included in the imputed SNP, and performance of genomic inbreeding estimators depends on the imputation.

A comparison of marker-based estimators of inbreeding and inbreeding depression

BACKGROUND

The availability of genome-wide marker data allows estimation of inbreeding coefficients (F, the probability of identity-by-descent, IBD) and, in turn, estimation of the rate of inbreeding depression (ΔID). We investigated, by computer simulations, the accuracy of the most popular estimators of inbreeding based on molecular markers when computing F and ΔID in populations under random mating, equalization of parental contributions, and artificially selected populations. We assessed estimators described by Li and Horvitz (F_LH1 and F_LH2), VanRaden (F_VR1 and F_VR2), Yang and colleagues (F_YA1 and F_YA2), marker homozygosity (F_HOM), runs of homozygosity (F_ROH) and estimates based on pedigree (F_PED) in comparison with estimates obtained from IBD measures (F_IBD).

RESULTS

If the allele frequencies of a base population taken as a reference for the computation of inbreeding are known, all estimators based on marker allele frequencies are highly correlated with F_IBD and provide accurate estimates of the mean ΔID. If base population allele frequencies are unknown and current frequencies are used in the estimations, the largest correlation with F_IBD is generally obtained by F_LH1 and the best estimator of ΔID is F_YA2. The estimators F_VR2 and F_LH2 have the poorest performance in most scenarios. The assumption that base population allele frequencies are equal to 0.5 results in very biased estimates of the average inbreeding coefficient but they are highly correlated with F_IBD and give relatively good estimates of ΔID. Estimates obtained directly from marker homozygosity (F_HOM) substantially overestimated ΔID. Estimates based on runs of homozygosity (F_ROH) provide accurate estimates of inbreeding and ΔID. Finally, estimates based on pedigree (F_PED) show a lower correlation with F_IBD than molecular estimators but provide rather accurate estimates of ΔID. An analysis of data from a pig population supports the main findings of the simulations.

CONCLUSIONS

When base population allele frequencies are known, all marker-allele frequency-based estimators of inbreeding coefficients generally show a high correlation with F_IBD and provide good estimates of ΔID. When base population allele frequencies are unknown, F_LH1 is the marker frequency-based estimator that is most correlated with F_IBD, and F_YA2 provides the most accurate estimates of ΔID. Estimates from F_ROH are also very precise in most scenarios. The estimators F_VR2 and F_LH2 have the poorest performances.

Fine-tuning genomic and pedigree inbreeding rates in equine population with a deep and reliable stud book: the case of the Pura Raza Española horse

BACKGROUND

Estimating inbreeding, which is omnipresent and inevitable in livestock populations, is a primary goal for management and animal breeding especially for those interested in mitigating the negative consequences of inbreeding. Inbreeding coefficients have been historically estimated by using pedigree information; however, over the last decade, genome-base inbreeding coefficients have come to the forefront in this field. The Pura Raza Española (PRE) horse is an autochthonous Spanish horse breed which has been recognised since 1912. The total PRE population (344,718 horses) was used to estimate Classical (F), Ballou's ancestral, Kalinowski's ancestral, Kalinowski's new and the ancestral history coefficient values. In addition, genotypic data from a selected population of 805 PRE individuals was used to determine the individual inbreeding coefficient using SNP-by-SNP-based techniques (methods of moments -F_HOM-, the diagonal elements of the genomic -F_G-, and hybrid matrixes -F_H-) and ROH measures (F_RZ). The analyse of both pedigree and genomic based inbreeding coefficients in a large and robust population such as the PRE horse, with proven parenteral information for the last 40 years and a high degree of completeness (over 90% for the last 70 years) will allow us to understand PRE genetic variability better and the correlations between the estimations will give the data greater reliability.

RESULTS

The mean values of the pedigree-based inbreeding coefficients ranged from 0.01 (F for the last 3 generations -F3-) to 0.44 (ancestral history coefficient) and the mean values of genomic-based inbreeding coefficients varied from 0.05 (F_RZ for three generations, F_H and F_HOM) to 0.11 (F_RZ for nine generations). Significant correlations were also found between pedigree and genomic inbreeding values, which ranged between 0.58 (F3 with F_HOM) and 0.79 (F with F_RZ). In addition, the correlations between F_RZ estimated for the last 20 generations and the pedigree-based inbreeding highlight the fact that fewer generations of genomic data are required when comparing total inbreeding values, and the opposite when ancient values are calculated.

CONCLUSIONS

Ultimately, our results show that it is still useful to work with a deep and reliable pedigree in pedigree-based genetic studies with very large effective population sizes. Obtaining a satisfactory parameter will always be desirable, but the approximation obtained with a robust pedigree will allow us to work more efficiently and economically than with massive genotyping.

Assessment of Genetic Diversity, Runs of Homozygosity, and Signatures of Selection in Tropical Milking Criollo Cattle Using Pedigree and Genomic Data

The objective of this study was to evaluate the genetic diversity of the Tropical Milking Criollo cattle (TMC) breed in Mexico through parameters derived from pedigree and genomic information assessment. The pedigree file consisted of 3780 animals. Seventy-nine bovines were genotyped with the medium-density single nucleotide polymorphism chip and considered a reference population for pedigree analysis. The effective population size and the probability of gene origin used to assess the evolution of genetic diversity were calculated with pedigree information. Inbreeding coefficients were evaluated based on pedigree (FPed), the genomic relationship matrix (FGRM), and runs of homozygosity (FROH) of different length classes. The average inbreeding was 2.82 ± 2.66%, −0.7 ± 3.8%, and 10.9 ± 3.0% for FPED, FGRM, and FROH, respectively. Correlation between FPED and FROH was significant only for runs of homozygosity > 4 Mb, indicating the FPED of a population with an average equivalent complete generation of five only recovers the most recent inbreeding. The parameters of the probability of gene origin indicated the existence of genetic bottlenecks and the loss of genetic diversity in the history of the TMC cattle population; however, pedigree and genomic information revealed the existence of current sufficient genetic diversity to design a sustainable breeding program.

Genomic characterization of autozygosity and recent inbreeding trends in all major breeds of US dairy cattle

Maintaining a genetically diverse dairy cattle population is critical to preserving adaptability to future breeding goals and avoiding declines in fitness. This study characterized the genomic landscape of autozygosity and assessed trends in genetic diversity in 5 breeds of US dairy cattle. We analyzed a sizable genomic data set containing 4,173,679 pedigreed and genotyped animals of the Ayrshire, Brown Swiss, Guernsey, Holstein, and Jersey breeds. Runs of homozygosity (ROH) of 2 Mb or longer in length were identified in each animal. The within-breed means for number and the combined length of ROH were highest in Jerseys (62.66 ± 8.29 ROH and 426.24 ± 83.40 Mb, respectively; mean ± SD) and lowest in Ayrshires (37.24 ± 8.27 ROH and 265.05 ± 85.00 Mb, respectively). Short ROH were the most abundant, but moderate to large ROH made up the largest proportion of genome autozygosity in all breeds. In addition, we identified ROH islands in each breed. This revealed selection patterns for milk production, productive life, health, and reproduction in most breeds and evidence for parallel selective pressure for loci on chromosome 6 between Ayrshire and Brown Swiss and for loci on chromosome 20 between Holstein and Jersey. We calculated inbreeding coefficients using 3 different approaches, pedigree-based (F_PED), marker-based using a genomic relationship matrix (F_GRM), and segment-based using ROH (F_ROH). The average inbreeding coefficient ranged from 0.06 in Ayrshires and Brown Swiss to 0.08 in Jerseys and Holsteins using F_PED, from 0.22 in Holsteins to 0.29 in Guernsey and Jerseys using F_GRM, and from 0.11 in Ayrshires to 0.17 in Jerseys using F_ROH. In addition, the effective population size at past generations (5-100 generations ago), the yearly rate of inbreeding, and the effective population size in 3 recent periods (2000-2009, 2010-2014, and 2015-2018) were determined in each breed to ascertain current and historical trends of genetic diversity. We found a historical trend of decreasing effective population size in the last 100 generations in all breeds and breed differences in the effect of the recent implementation of genomic selection on inbreeding accumulation.

Genetic Diversity and Selection Signatures in Jianchang Black Goats Revealed by Whole-Genome Sequencing Data

Understanding the genetic composition of indigenous goats is essential to promote the scientific conservation and sustainable utilization of these breeds. The Jianchang Black (JC) goat, a Chinese native breed, is solid black and exhibits crude feed tolerance, but is characterized by a low growth rate and small body size. Based on the whole-genome sequencing data for 30 JC, 41 Jintang Black (JT), and 40 Yunshang Black (YS) goats, and 21 Bezoar ibexes, here, we investigated the genetic composition of JC goats by conducting analyses of the population structure, runs of homozygosity (ROH), genomic inbreeding, and selection signature. Our results revealed that JT and YS showed a close genetic relationship with a non-negligible amount of gene flows but were genetically distant from JC, apart from Bezoars. An average of 2039 ROHs were present in the autosomal genome per individual. The ROH-based inbreeding estimates in JC goats generally showed moderate values ranging from 0.134 to 0.264, mainly due to rapid declines in the effective population size during recent generations. The annotated genes (e.g., IL2, IL7, and KIT) overlapping with ROH islands were significantly enriched in immune-related biological processes. Further, we found 61 genes (e.g., STIM1, MYO9A, and KHDRBS2) under positive selection in JC goats via three complementary approaches, which may underly genetic adaptations to local environmental conditions. Our findings provided references for the conservation and sustainable utilization of JC goats.

Genomic patterns of homozygosity and inbreeding depression in Murciano-Granadina goats

Background

Inbreeding depression can adversely affect traits related to fitness, reproduction and productive performance. Although current research suggests that inbreeding levels are generally low in most goat breeds, the impact of inbreeding depression on phenotypes of economic interest has only been investigated in a few studies based on genealogical data.

Results

We genotyped 1040 goats with the Goat SNP50 BeadChip. This information was used to estimate different molecular inbreeding coefficients and characterise runs of homozygosity and homozygosity patterns. We detected 38 genomic regions with increased homozygosity as well as 8 ROH hotspots mapping to chromosomes 1, 2, 4, 6, 14, 16 and 17. Eight hundred seventeen goats with available records for dairy traits were analysed to evaluate the potential consequences of inbreeding depression on milk phenotypes. Four regions on chromosomes 8 and 25 were significantly associated with inbreeding depression for the natural logarithm of the somatic cell count. Notably, these regions contain several genes related with immunity, such as SYK, IL27, CCL19 and CCL21. Moreover, one region on chromosome 2 was significantly associated with inbreeding depression for milk yield.

Conclusions

Although genomic inbreeding levels are low in Murciano-Granadina goats, significant evidence of inbreeding depression for the logarithm of the somatic cell count, a phenotype closely associated with udder health and milk yield, have been detected in this population. Minimising inbreeding would be expected to augment economic gain by increasing milk yield and reducing the incidence of mastitis, which is one of the main causes of dairy goat culling.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40104-022-00684-5.

Long-term impact of conventional and optimal contribution conservation methods on genetic diversity and genetic gain in local pig breeds

There are rich and vast genetic resources of indigenous pig breeds in the world. Currently, great attention is paid to either crossbreeding or conservation of these indigenous pig breeds, and insufficient attention is paid to the combination of conservation and breeding along with their long-term effects on genetic diversity. Therefore, the objective of this study is to compare the long-term effects of using conventional conservation and optimal contribution selection methods on genetic diversity and genetic gain. A total of 11 different methods including conventional conservation and optimal contribution selection methods were investigated using stochastic simulations. The long-term effects of using these methods were evaluated in terms of genetic diversity metrices such as expected heterozygosity (He) and the rate of genetic gain. The results indicated that the rates of true inbreeding in these conventional conservation methods were maintained at around 0.01. The optimal contribution selection methods based either on the pedigree (POCS) or genome (GOCS) information showed more genetic gain than conventional methods, and POCS achieved the largest genetic gain. Furthermore, the effect of using GOCS methods on most of the genetic diversity metrics was slightly better than the conventional conservation methods when the rate of true inbreeding was the same, but this also required more sires used in OCS methods. According to the rate of true inbreeding, there was no significant difference among these conventional methods. In conclusion, there is no significant difference in different ways of selecting sows on inbreeding when we use different conventional conservation methods. Compared with conventional methods, POCS method could achieve the most genetic gain. However, GOCS methods can not only achieve higher genetic gain, but also maintain a relatively high level of genetic diversity. Therefore, GOCS is a better choice if we want to combine conservation and breeding in actual production in the conservation farms.

Correlation of Genomic and Pedigree Inbreeding Coefficients in Small Cattle Populations

Simple Summary

This study aimed to evaluate the consistency of different methodologies and sources of information used to estimate inbreeding coefficients in small populations by analyzing the correlation between them in the Holstein population of Mexico and to choose the best option in order to aid breeding programs to improve the productive traits of Holstein cattle in small-specialized populations.

Abstract

This study aimed to identify inbreeding coefficient (F) estimators useful for improvement programs in a small Holstein population through the evaluation of different methodologies in the Mexican Holstein population. F was estimated as follows: (a) from pedigree information (Fped); (b) through runs of homozygosity (Froh); (c) from the number of observed and expected homozygotic SNP in the individuals (Fgeno); (d) through the genomic relationship matrix (Fmg). The study included information from 4277 animals with pedigree records and 100,806 SNP. The average and standard deviation values of F were 3.11 ± 2.30 for Fped, −0.02 ± 3.55 for Fgeno, 2.77 ± 0.71 for Froh and 3.03 ± 3.05 for Fmg. The correlations between coefficients varied from 0.30 between Fped and Froh, to 0.96 between Fgeno and Fmg. Differences in the level of inbreeding among the parent’s country of origin were found regardless of the method used. The correlations among genomic inbreeding coefficients were high; however, they were low with Fped, so further research on this topic is required.

Estimating inbreeding depression for growth and reproductive traits using pedigree and genomic methods in Argentinean Brangus cattle

Inbreeding depression reduces the mean phenotypic value of important traits in livestock populations. The goal of this work was to estimate the level of inbreeding and inbreeding depression for growth and reproductive traits in Argentinean Brangus cattle, in order to obtain a diagnosis and monitor breed management. Data comprised 359,257 (from which 1,990 were genotyped for 40,678 single nucleotide polymorphisms [SNPs]) animals with phenotypic records for at least one of three growth traits: birth weight (BW), weaning weight (WW), and finishing weight (FW). For scrotal circumference (SC), 52,399 phenotypic records (of which 256 had genotype) were available. There were 530,938 animals in pedigree. Three methods to estimate inbreeding coefficients were used. Pedigree-based inbreeding coefficients were estimated accounting for missing parents. Inbreeding coefficients combining genotyped and nongenotyped animal information were also computed from matrix H of the single-step approach. Genomic inbreeding coefficients were estimated using homozygous segments obtained from a Hidden Markov model (HMM) approach. Inbreeding depression was estimated from the regression of the phenotype on inbreeding coefficients in a multiple-trait mixed model framework, either for the whole dataset or for the dataset of genotyped animals. All traits were unfavorably affected by inbreeding depression. A 10% increase in pedigree-based or combined inbreeding would result in a reduction of 0.34 to 0.39 kg in BW, 2.77 to 3.28 kg in WW, and 0.23 cm in SC. For FW, a 10% increase in pedigree-based, genomic, or combined inbreeding would result in a decrease of 8.05 to 11.57 kg. Genomic inbreeding based on the HMM was able to capture inbreeding depression, even in such a compressed genotyped dataset.

How to achieve a higher selection plateau in forest tree breeding? Fostering heterozygote × homozygote relationships in optimal contribution selection in the case study of Populus nigra

In breeding, optimal contribution selection (OCS) is one of the most effective strategies to balance short- and long-term genetic responses, by maximizing genetic gain and minimizing global coancestry. Considering genetic diversity in the selection dynamic-through coancestry-is undoubtedly the reason for the success of OCS, as it avoids preliminary loss of favorable alleles. Originally formulated with the pedigree relationship matrix, global coancestry can nowadays be assessed with one of the possible formulations of the realized genomic relationship matrix. Most formulations were optimized for genomic evaluation, but few for the management of coancestry. We introduce here an alternative formulation specifically developed for genomic OCS (GOCS), intended to better control heterozygous loci, and thus better account for Mendelian sampling. We simulated a multigeneration breeding program with mate allocation and under GOCS for twenty generations, solved with quadratic programming. With the case study of Populus nigra, we have shown that, although the dynamic was mainly determined by the trade-off between genetic gain and genetic diversity, better formulations of the genomic relationship matrix, especially those fostering individuals carrying multiple heterozygous loci, can lead to better short-term genetic gain and a higher selection plateau.

Changes in Allele Frequencies When Different Genomic Coancestry Matrices Are Used for Maintaining Genetic Diversity

A main objective in conservation programs is to maintain genetic variability. This can be achieved using the Optimal Contributions (OC) method that optimizes the contributions of candidates to the next generation by minimizing the global coancestry. However, it has been argued that maintaining allele frequencies is also important. Different genomic coancestry matrices can be used on OC and the choice of the matrix will have an impact not only on the genetic variability maintained, but also on the change in allele frequencies. The objective of this study was to evaluate, through stochastic simulations, the genetic variability maintained and the trajectory of allele frequencies when using two different genomic coancestry matrices in OC to minimize the loss of diversity: (i) the matrix based on deviations of the observed number of alleles shared between two individuals from the expected numbers under Hardy–Weinberg equilibrium (θ_LH); and (ii) the matrix based on VanRaden’s genomic relationship matrix (θ_VR). The results indicate that the use of θ_LH resulted in a higher genetic variability than the use of θ_VR. However, the use of θ_VR maintained allele frequencies closer to those in the base population than the use of θ_LH.