So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

Human biochemical genetics

The livestock sector globally is highly dynamic. In developing countries, it is evolving in response to rapidly increasing demand for livestock products. In developed countries, demand for livestock products is stagnating, while many production systems are increasing their efficiency and environmental sustainability. Historical changes in the demand for livestock products have been largely driven by human population growth, income growth and urbanization and the production response in different livestock systems has been associated with science and technology as well as increases in animal numbers. In the future, production will increasingly be affected by competition for natural resources, particularly land and water, competition between food and feed and by the need to operate in a carbon-constrained economy. Developments in breeding, nutrition and animal health will continue to contribute to increasing potential production and further efficiency and genetic gains. Livestock production is likely to be increasingly affected by carbon constraints and environmental and animal welfare legislation. Demand for livestock products in the future could be heavily moderated by socio-economic factors such as human health concerns and changing socio-cultural values. There is considerable uncertainty as to how these factors will play out in different regions of the world in the coming decades.

https://royalsocietypublishing.org/doi/pdf/10.1098/rstb.2010.0134

Livestock production: recent trends, future prospects

https://hal.archives-ouvertes.fr/hal-01173575/document

Invited review: Body condition score and its association with dairy cow productivity, health, and welfare

Undesirable side effects of selection for high production efficiency in farm animals: a review

Reproductive performance of 714 Holstein Friesian dairy cows was monitored between October 1995 and June 1998 using thrice weekly milk progesterone determinations. Defined endocrine parameters such as interval to post-partum commencement of luteal activity, inter-ovulatory interval and length of luteal and inter-luteal intervals were used with a number of traditional measures of reproductive performance to investigate the current status of fertility in a sample of United Kingdom dairy herds. A comparison of the results of the 1995 to 1998 trial with those of a previous (1975 to 1982) milk progesterone database, which included 2503 lactations in British Friesian cows monitored using a similar milk sampling protocol, revealed a decline infertility between these periods. Between 1975-1982 and 1995-1998, pregnancy rate to first service declined from 55·6% to 39·7% (P < 0·001), at a derived average rate approaching 1% per year. This decline was associated with an increase (P < 0·001) in the proportion of animals with one or more atypical ovarian hormone patterns from 32% to 44%. There was a significant (P < 0·001) increase in the incidence of delayed luteolysis during the first cycle post partum (delayed luteolysis type I; 7·3% to 18·2%) and during subsequent cycles (delayed luteolysis type II; 6·4% to 16·8%), although the incidence of prolonged anovulation post partům (delayed ovulation type I; 10·9% to 12·9%) and prolonged inter-luteal intervals (delayed ovulation type II; 12·9% to 10·6%) did not alter significantly. These changes resulted in an increase in mean luteal phase length from 12·9 (s.e. 0·09) to 14·8 (s.e. 0·17) days and an increase in inter-ovulatory interval from 20·2 (s.e. 0·1) to 22·3 (s.e. 0·2) days. The decline infertility was also reflected in traditional measures of fertility since although interval to first service remained relatively unchanged (74·0 (s.e. 0·4) to 77·6 (s.e. 1·1) days) calving interval lengthened from 370 (s.e. 2·2) to 390 (s.e. 2·5) days. Collectively these changes may have contributed to the decline in pregnancy rates observed over the last 20 years.

Declining fertility in dairy cattle: changes in traditional and endocrine parameters of fertility.

The Relationship Between Body Condition Score and Reproductive Performance

The purpose of this study was to estimate genetic parameters for measures of fertility and several health disorders in dairy cows. Data consisted of 33732 records, of which 9163 were on heifers, on 305-day milk yield, health disorders and inseminations. Measures of fertility were calculated from calving and insemination dates and included calving interval, days to first service and conception to first service. Health disorders included milk fever, mastitis and lameness. Genetic and phenotypic (co)variances were estimated using restricted maximum likelihood. Heritability estimates for both health disorders and fertility traits were low, ranging from 0·003 to 0·080. All genetic correlations between 305-day milk yield and health and fertility traits, in cows and heifers together, were antagonistic implying that selection for milk yield may have caused a deterioration in health and fertility. The unfavourable correlation between milk yield and health and fertility traits, plus the economic importance of the latter, suggests that future breeding goals should be expanded to include some health disorders and fertility.

Genetic aspects of common health disorders and measures of fertility in Holstein Friesian dairy cattle.

This study provides estimates of genetic parameters for various diseases, fertility and 305-day milk production traits in dairy cattle using data from a UK national milk recording scheme. The data set consisted of 63891 multiple lactation records on diseases (mastitis, lameness, milk fever, ketosis and tetany), fertility traits (calving interval, conception to first service, number of services for a conception, and number of days to first service), dystocia and 305-day milk, fat and protein yield. All traits were analysed by multi-trait repeatability linear animal models (LM). Binary diseases and fertility traits were further analysed by threshold sire models (TM). Both LM and TM analyses were based on the generalized linear mixed model framework. The LM included herd-year-season of calving (HYS), age at calving and parity as fixed effects and genetic, permanent environmental and residual effects as random. The TM analyses included the same effects as for LM, but HYS effects were treated as random to avoid convergence problems when HYS sub-classes had 0 or 100% incidence. Because HYS effects were treated as random, herd effects were fitted as fixed effects to account for effect of herds in the data. The LM estimates of heritability ranged from 0•389 to 0•399 for 305-day milk production traits, 0•010 to 0•029 for fertility traits and 0•004 to 0•038 for diseases. The LM estimates of repeatability ranged from 0•556 to 0•586 for 305-day milk production traits, 0•029 to 0•086 for fertility traits and 0•004 to 0•100 for diseases. The TM estimates of heritabilities and repeatabilities were greater than LM estimates for binary traits and were in the range 0•012 to 0•126 and 0•013 to 0•168, respectively. Genetic correlations between milk production traits and fertility and diseases were all unfavorable: they ranged from 0•07 to 0•37 for milk production and diseases, 0•31 to 0•54 for milk production and poor fertility and 0•06 to 0•41 for diseases and poor fertility. These results show that future selection programmes should include disease and fertility for genetic improvement of health and reproduction and for sustained economic growth in the dairy cattle industry.

Linear and threshold model genetic parameters for disease, fertility and milk production in dairy cattle

Genotype and feeding system effects and interactions for health and fertility traits in dairy cattle

The Dairy Information System (DAISY) was developed to record fertility and health information for use in research and to help farmers manage their farms. Data from 33 herds recording health and fertility over a 6-year period were used to study genetic relationships of several health, fertility and production traits. There were 10 569 records from 4642 cows of all parities. These were used to estimate genetic parameters for health: mastitis, lameness and somatic cell score (SCS), for fertility: calving interval, days to first service, conception to first service and for production: 305-day milk, butterfat and protein yields. Heritabilities for these traits were also estimated for the first three lactations. (Co)variances were estimated using linear, multitrait restricted maximum likelihood (REML) with an animal model. Mastitis and lameness were treated as all-or-none traits. The incidence of these diseases increased with lactation number, which may lead to variance component estimation problems, as the mean is linked to the variance in binomial distributions. Therefore, a method was used to fix the within-lactation variance to one in all lactations while maintaining the same mean. The heritability for SCS across lactations was 0·15. Heritabilities for other health and fertility traits were low and ranged between 0·013 and 0·047. All genetic correlations with the production traits were antagonistic implying that selection for yield may have led to a deterioration in health and fertility. The genetic correlation between SCS and mastitis was 0·65 indicating that indirect selection for improvements in mastitis may be achieved using somatic cell counts as a selection criterion. The potential use of linear type scores as predictors of the health traits was investigated by regressing health traits on sire predicted transmitting abilities for type. The results indicate that some type traits may be useful as future selection criteria.

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S1357729800009152

Geoff Simm

Papers

The Relationship Between Body Condition Score and Reproductive Performance

Genetic aspects of common health disorders and measures of fertility in Holstein Friesian dairy cattle.

Linear and threshold model genetic parameters for disease, fertility and milk production in dairy cattle

Genotype and feeding system effects and interactions for health and fertility traits in dairy cattle

Estimation of genetic parameters using health, fertility and production data from a management recording system for dairy cattle