High-density marker imputation accuracy in sixteen French cattle breeds

Background

Genotyping with the medium-density Bovine SNP50 BeadChip^® (50K) is now standard in cattle. The high-density BovineHD BeadChip^®, which contains 777 609 single nucleotide polymorphisms (SNPs), was developed in 2010. Increasing marker density increases the level of linkage disequilibrium between quantitative trait loci (QTL) and SNPs and the accuracy of QTL localization and genomic selection. However, re-genotyping all animals with the high-density chip is not economically feasible. An alternative strategy is to genotype part of the animals with the high-density chip and to impute high-density genotypes for animals already genotyped with the 50K chip. Thus, it is necessary to investigate the error rate when imputing from the 50K to the high-density chip.

Methods

Five thousand one hundred and fifty three animals from 16 breeds (89 to 788 per breed) were genotyped with the high-density chip. Imputation error rates from the 50K to the high-density chip were computed for each breed with a validation set that included the 20% youngest animals. Marker genotypes were masked for animals in the validation population in order to mimic 50K genotypes. Imputation was carried out using the Beagle 3.3.0 software.

Results

Mean allele imputation error rates ranged from 0.31% to 2.41% depending on the breed. In total, 1980 SNPs had high imputation error rates in several breeds, which is probably due to genome assembly errors, and we recommend to discard these in future studies. Differences in imputation accuracy between breeds were related to the high-density-genotyped sample size and to the genetic relationship between reference and validation populations, whereas differences in effective population size and level of linkage disequilibrium showed limited effects. Accordingly, imputation accuracy was higher in breeds with large populations and in dairy breeds than in beef breeds. More than 99% of the alleles were correctly imputed if more than 300 animals were genotyped at high-density. No improvement was observed when multi-breed imputation was performed.

Conclusion

In all breeds, imputation accuracy was higher than 97%, which indicates that imputation to the high-density chip was accurate. Imputation accuracy depends mainly on the size of the reference population and the relationship between reference and target populations.     

Genetic control of multiple births in low ovulating mammalian species

In mammals, litter size is a highly variable trait. Some species such as humans or cattle are monotocous, with one or sometimes two newborns per birth, whereas others, the polytocous species such as mice or pigs, are highly prolific and often produce a dozen newborns at each farrowing. In monotocous species, however, two or three newborns per birth may sometime be unwanted. In more polytocous species such as sheep or pigs, litter size is studied in order to increase livestock prolificacy. By contrast, twinning rates in humans or cattle may increase birth difficulties and health problems in the newborns. In this context, the aim of our review was to provide a clearer understanding of the genetic and physiological factors that control multiple births in low-ovulating mammalian species, with particular focus on three species: sheep, cattle, and humans, where knowledge of the ovulation rate in one may enlighten findings in the others. This article therefore reviews the phenotypic and genetic variability observed with respect to ovulation and twinning rates. It then presents the QTL and major genes that have been identified in each species. Finally, we draw a picture of the diversity of the physiological mechanisms underlying multiple ovulation. Although several major genes have been discovered in sheep, QTL detection methods in humans or cattle have suggested that the determinism of litter size is complex and probably involves several genes in order to explain variations in the number of ovulations.     

Genetic steady-state under BLUP selection for an infinite and homogeneous population with discrete generations

A matrix derivation is proposed to analytically calculate the asymptotic genetic variance-covariance matrix under BLUP selection according to the initial genetic parameters in a large population with discrete generations. The asymptotic genetic evolution of a homogeneous population with discrete generations is calculated for a selection operating on an index including all information (pedigree and records) from a non-inbred and unselected base population (BLUP selection) or on an index restricted to records of a few ancestral generations. Under the first hypothesis, the prediction error variance of the selection index is independent of selection and is calculated from the genetic parameters of the base population. Under the second hypothesis, the prediction error variance depends on selection. Furthermore, records of several generations of ancestors of the candidates for selection must be used to maintain a constant prediction error variance over time. The number of ancestral generations needed depends on the population structure and on the occurrence of fixed effects. Without fixed effects to estimate, accounting for two generations of ancestors is sufficient to estimate the asymptotic prediction error variance. The amassing of information from an unselected base population proves to be important in order not to overestimate the asymptotic genetic gains and not to underestimate the asymptotic genetic variances.     

Soluble form of ICAM-1, VCAM-1, E- and L-selectin in human milk

In breast milk and paired serum from 70 lactating women and 40 of their term, infection-free neonates, on the 2nd and 5th day postpartum slCAM-1, sVCAM-1, sE- and sL-selectin were measured by ELISA and compared with those in 26 healthy adults (controls). Seven infant formulas and fresh milk from five cows were also analyzed. Human colostrum values of slCAM-1, sVCAM-1 (similar to those in maternal and control serum), sE-selectin and sL-selectin (-10 and -100 times lower than in maternal and control serum) were significantly higher than those in milk, while they varied widely. None of the adhesion molecules was detected in fresh cow's milk or infant formulas. Exclusively breast-fed infants showed significantly higher values of slCAM-1 and sL-selectin on the 2nd day of life than those supplemented also with formula. Only slCAM-1 values correlated positively between colostrum and time-matched maternal serum. These findings show in human milk important amounts of slCAM-1 and sVCAM-1 but minimal amounts of sE- and sL-selectin, which could affect the immune system of the neonate.