Importance of adaptation and genotype × environment interactions in tropical beef breeding systems

This paper examines the relative importance of productive and adaptive traits in beef breeding systems based on Bos taurus and tropically adapted breeds across temperate and (sub)tropical environments. In the (sub)tropics, differences that exist between breeds in temperate environments are masked by the effects of environmental stressors. Hence in tropical environments, breeds are best categorised into breed types to compare their performance across environments. Because of the presence of environmental stressors, there are more sources of genetic variation in tropical breeding programmes. It is therefore necessary to examine the genetic basis of productive and adaptive traits for breeding programmes in those environments. This paper reviews the heritabilities and genetic relationships between economically important productive and adaptive traits relevant to (sub)tropical breeding programmes. It is concluded that it is possible to simultaneously genetically improve productive and adaptive traits in tropically adapted breeds of beef cattle grazed in tropical environments without serious detrimental consequences for either adaptation or production. However, breed-specific parameters are required for genetic evaluations. The paper also reviews the magnitude of genotype × environment (G × E) interactions impacting on production and adaptation of cattle, where 'genotype' is defined as breed (within a crossbreeding system), sire within breed (in a within-breed selection programme) or associations between economically important traits and single nucleotide polymorphisms (SNPs - within a marker-assisted selection programme). It is concluded that re-ranking of breeds across environments is best managed by the use of the breed type(s) best suited to the particular production environment. Re-ranking of sires across environments is apparent in poorly adapted breed types across extreme tropical and temperate environments or where breeding animals are selected in a temperate environment for use in the (sub)tropics. However, G × E interactions are unlikely to be of major importance in tropically adapted beef cattle grazed in either temperate or (sub)tropical environments, although sex × environment interactions may provide new opportunities for differentially selecting to simultaneously improve steer performance in benign environments and female performance in harsher environments. Early evidence suggests that re-ranking of SNPs occurs across temperate and tropical environments, although their magnitude is still to be confirmed in well-designed experiments. The major limitation to genetic improvement of beef cattle over the next decade is likely to be a deficiency of large numbers of accurately recorded phenotypes for most productive and adaptive traits and, in particular, for difficult-to-measure adaptive traits such as resistance to disease and environmental stressors.     

Estimation of genetic parameters for young stock survival in beef x dairy crossbred calves

Young stock survival is a trait of crucial importance in cattle breeding as calf mortality leads to economic losses and represents an animal welfare issue. The aim of this study was to estimate genetic parameters and sire breeding values for young stock survival in beef x dairy crossbred calves. Two traits were analysed with a univariate animal model: young stock survival between 1 to 30 days and 31 to 200 days after birth. Breed combinations with Belgian Blue sires outperformed all other sire breeds. The lowest survival rates were found for breed combinations with Jersey dams or Blonde d’Aquitaine sires. The results showed low but significant heritabilities (0.045 to 0.075) for both survival traits. Differences in breeding values between sires ranged from −2.5% to 3.5% and from −5.4% to 4.7% survival from 1 to 30 days and 31 to 200 days, respectively. Based on these findings, we concluded that it is feasible to breed for improved young stock survival in beef x dairy crossbred calves. This will hopefully contribute to increasing the survival rate of the calves and reduce economic losses for the farmers.     

Gene flow in a national cross-breeding beef population

Future progress in genetic improvement and the monitoring of genetic resources in beef cattle requires a detailed understanding of the population under selection. This study examines the gene flow in the UK beef population with an uncommon breeding structure involving interaction between the beef and dairy populations. British Cattle Movement Service records were used as the primary source of information, and these data were triangulated with UK government statistics, other industry information sources and existing literature to build up a profile of the UK beef industry. Estimates were made of the breed composition of suckler cows, breeding bulls and the prime slaughter population. Cross-bred animals made up 85% and 94%, respectively, of the commercial beef breeding cow and prime slaughter populations. Holstein/Friesian (through cross-breeding) made up the largest proportion of genes in both these populations with 33% and 28%, respectively. The next five most popular breeds were specialist beef breeds: Limousin (22% and 18%), Charolais (11% and 6%), Simmental (9% and 11%), Angus (7% and 8%) and Belgian Blue (6% and 6%). Combined, the top seven beef breeds accounted for 94% of beef genetics in the prime slaughter population, and 80% of this came from non-native breeds. The influence of dairy breeds in the commercial beef breeding population was highlighted by the fact that 44% of replacement commercial beef breeding females were sourced from beef-sired crosses in the dairy herd, and in total 74% of all maternal grand dams of prime slaughter animals were Holstein/Friesian. The use of selection index technology was also investigated by analysing breeding bull sale results, with the correlation between the terminal sire index and sale price of young breeding bulls being generally moderate but significant, ranging from 0.21 to 0.38 across the major beef breeds. The most influential source of genetics in the commercial suckler beef herd was natural service breeding bulls. These were mostly sourced from pedigree breeders, and accounted for 47.8% of the genetics in the prime beef population. Artificial insemination sires were responsible for 16.6% of prime beef genetics, with the remaining 35.6% coming from dairy breeds, 95% of which was Holstein/Friesian.     

Application of genome editing in farm animals: cattle

Milk and meat from cattle and buffaloes contribute 45% of the global animal protein supply, followed by chickens (31%), and pigs (20%). In 2016, the global cattle population of 1.0 billion head produced 6.5 billion tons of cows’ milk, and 66 million tons of beef. In the past century, cattle breeding programs have greatly increased the yield per animal with a resultant decrease in the emissions intensity per unit of milk or beef, but this has not been true in all regions. Genome editing research in cattle to date has focused on disease resistance (e.g. tuberculosis), production (e.g. myostatin knockout; production of all-male offspring), elimination of allergens (e.g. beta-lactoglobulin knockout) and welfare (e.g. polled or hornlessness) traits. Modeling has revealed how the use of genome editing to introduce beneficial alleles into cattle breeds could maintain or even accelerate the rate of genetic gain accomplished by conventional breeding programs, and is a superior approach to the lengthy process of introgressing those same alleles from distant breeds. Genome editing could be used to precisely introduce useful alleles (e.g. heat tolerance, disease resistance) and haplotypes into native locally-adapted cattle breeds, thereby helping to improve their productivity. As with earlier genetic engineering approaches, whether breeders will be able to employ genome editing in cattle genetic improvement programs will very much depend upon global decisions around the regulatory framework and governance of genome editing for food animals.

     

中国绵羊起源、进化和遗传多样性研究进展

中国地方绵羊品种资源丰富,部分品种具有繁殖力高、毛皮品质好、多角、多乳头、大尾脂、抗逆性强等独特性状,这些遗传资源引起了学者们对其进行深入研究的兴趣,但目前仍然存在绵羊起源问题的争议,缺乏对我国绵羊的遗传多样性进行全面系统研究等问题。本文综述了绵羊起源、品种分化等方面的研究进展,并从父系、母系、常染色体分子标记等不同层面介绍了中国绵羊遗传多样性的研究概况,为中国绵羊遗传资源的保护和利用、绵羊新品种(系)的培育以及我国绵羊产业良性发展提供参考。     

Turning science on robust cattle into improved genetic selection decisions

More robust cattle have the potential to increase farm profitability, improve animal welfare, reduce the contribution of ruminant livestock to greenhouse gas emissions and decrease the risk of food shortages in the face of increased variability in the farm environment. Breeding is a powerful tool for changing the robustness of cattle; however, insufficient recording of breeding goal traits and selection of animals at younger ages tend to favour genetic change in productivity traits relative to robustness traits. This paper has extended a previously proposed theory of artificial evolution to demonstrate, using deterministic simulation, how choice of breeding scheme design can be used as a tool to manipulate the direction of genetic progress, whereas the breeding goal remains focussed on the factors motivating individual farm decision makers. Particular focus was placed on the transition from progeny testing or mass selection to genomic selection breeding strategies. Transition to genomic selection from a breeding strategy where candidates are selected before records from progeny being available was shown to be highly likely to favour genetic progress in robustness traits relative to productivity traits. This was shown even with modest numbers of animals available for training and when heritability for robustness traits was only slightly lower than that for productivity traits. When transitioning from progeny testing to a genomic selection strategy without progeny testing, it was shown that there is a significant risk that robustness traits could become less influential in selection relative to productivity traits. Augmentations of training populations using genotyped cows and support for industry-wide improvements in phenotypic recording of robustness traits were put forward as investment opportunities for stakeholders wishing to facilitate the application of science on robust cattle into improved genetic selection schemes.     

Confirmation of two quantitative trait loci regions for nematode resistance in commercial British terminal sire breeds

Sheep internal parasites (nematodes) remain a major health challenge and are costly for pasture-based production systems. Most current breeding programmes for nematode resistance are based on indicator traits such as faecal egg counts (FEC), which are costly and laborious to collect. Hence, genetic markers for resistance would be advantageous. However, although some quantitative trait loci (QTL) have been identified, these QTL are often not consistent across breeds and few breeding strategies for nematode resistance in sheep are currently using molecular information. In this study, QTL for nematode resistance on ovine chromosomes (OAR) 3 and 14, previously identified in the Blackface breed, were explored using commercial Suffolk (n = 336) and Texel lambs (n = 879) sampled from terminal sire breeder flocks in the United Kingdom. FEC were used as the indicator trait for nematode resistance, and these were counted separately for Nematodirus and Strongyles genera. Microsatellite markers were used to map the QTL and the data were analysed using interval mapping regression techniques and variance component analysis. QTL for Nematodirus and Strongyles FEC were found to be segregating on OAR3 at 5% chromosome region-wide significance threshold in both Suffolk and Texel sheep, and Nematodirus FEC QTL were segregating on OAR14 in both breeds. In addition, QTL for growth traits were also found to be segregating at 5% chromosome region-wide on OAR3 and OAR14. The confirmation that FEC QTL segregate in the same position in three widely used breeds widens their potential applicability to purebred Blackface, Suffolk and Texel sheep, with benefits likely to be observed in their commercial crossbred progeny.     

Predictive potential of microsatellite markers on heterosis of fecundity in crossbred sheep

Small Tail Han (STH) sheep is a famous Chinese local breed and has perfect prolificacy performance, but it is inferior to imported mutton sheep breeds on meat production. In this study, six imported male sheep populations (White Suffolk, Black Suffolk, Texel, Dorper, South African Mutton Merino and East Friesian) were crossbred with STH female sheep respectively. The heterosis values of litter size, average daily gain (ADG) and feed conversion ratio (FCR) of crossbred sheep were analyzed for seeking the optimal cross. Meanwhile 28 microsatellite markers were used to measure the genetic distance between imported populations and STH population. Regression between the genetic distance and heterosis was analyzed for evaluating potential of microsatellite on predicting heterosis. Results showed a significant positive linear correlation (r = 0.892, P < 0.05) between heterosis of litter size and genetic distance D _A of six crosses. This implied that these microsatellite markers had moderate potential to forecast heterosis of litter size in sheep. Results of this study also indicated that South African Mutton Merino and East Friesian sheep would be the optimal sire breeds for the litter size and might bring the greatest economic benefit in six imported populations; Suffolk sheep could be prior consideration as sire breeds when breeding objective focused on ADG. Finally these results provided valuable information for Chinese sheep industry.     

Application of Selection Mapping to Identify Genomic Regions Associated with Dairy Production in Sheep

In Europe, especially in Mediterranean areas, the sheep has been traditionally exploited as a dual purpose species, with income from both meat and milk. Modernization of husbandry methods and the establishment of breeding schemes focused on milk production have led to the development of “dairy breeds.” This study investigated selective sweeps specifically related to dairy production in sheep by searching for regions commonly identified in different European dairy breeds. With this aim, genotypes from 44,545 SNP markers covering the sheep autosomes were analysed in both European dairy and non-dairy sheep breeds using two approaches: (i) identification of genomic regions showing extreme genetic differentiation between each dairy breed and a closely related non-dairy breed, and (ii) identification of regions with reduced variation (heterozygosity) in the dairy breeds using two methods. Regions detected in at least two breeds (breed pairs) by the two approaches (genetic differentiation and at least one of the heterozygosity-based analyses) were labeled as core candidate convergence regions and further investigated for candidate genes. Following this approach six regions were detected. For some of them, strong candidate genes have been proposed (e.g. ABCG2, SPP1), whereas some other genes designated as candidates based on their association with sheep and cattle dairy traits (e.g. LALBA, DGAT1A) were not associated with a detectable sweep signal. Few of the identified regions were coincident with QTL previously reported in sheep, although many of them corresponded to orthologous regions in cattle where QTL for dairy traits have been identified. Due to the limited number of QTL studies reported in sheep compared with cattle, the results illustrate the potential value of selection mapping to identify genomic regions associated with dairy traits in sheep.     

Accuracies of genomically estimated breeding values from pure-breed and across-breed predictions in Australian beef cattle

Background

The major obstacles for the implementation of genomic selection in Australian beef cattle are the variety of breeds and in general, small numbers of genotyped and phenotyped individuals per breed. The Australian Beef Cooperative Research Center (Beef CRC) investigated these issues by deriving genomic prediction equations (PE) from a training set of animals that covers a range of breeds and crosses including Angus, Murray Grey, Shorthorn, Hereford, Brahman, Belmont Red, Santa Gertrudis and Tropical Composite. This paper presents accuracies of genomically estimated breeding values (GEBV) that were calculated from these PE in the commercial pure-breed beef cattle seed stock sector.

Methods

PE derived by the Beef CRC from multi-breed and pure-breed training populations were applied to genotyped Angus, Limousin and Brahman sires and young animals, but with no pure-breed Limousin in the training population. The accuracy of the resulting GEBV was assessed by their genetic correlation to their phenotypic target trait in a bi-variate REML approach that models GEBV as trait observations.

Results

Accuracies of most GEBV for Angus and Brahman were between 0.1 and 0.4, with accuracies for abattoir carcass traits generally greater than for live animal body composition traits and reproduction traits. Estimated accuracies greater than 0.5 were only observed for Brahman abattoir carcass traits and for Angus carcass rib fat. Averaged across traits within breeds, accuracies of GEBV were highest when PE from the pooled across-breed training population were used. However, for the Angus and Brahman breeds the difference in accuracy from using pure-breed PE was small. For the Limousin breed no reasonable results could be achieved for any trait.

Conclusion

Although accuracies were generally low compared to published accuracies estimated within breeds, they are in line with those derived in other multi-breed populations. Thus PE developed by the Beef CRC can contribute to the implementation of genomic selection in Australian beef cattle breeding.     

Genomic prediction of reproduction traits for Merino sheep

Economically important reproduction traits in sheep, such as number of lambs weaned and litter size, are expressed only in females and later in life after most selection decisions are made, which makes them ideal candidates for genomic selection. Accurate genomic predictions would lead to greater genetic gain for these traits by enabling accurate selection of young rams with high genetic merit. The aim of this study was to design and evaluate the accuracy of a genomic prediction method for female reproduction in sheep using daughter trait deviations (DTD) for sires and ewe phenotypes (when individual ewes were genotyped) for three reproduction traits: number of lambs born (NLB), litter size (LSIZE) and number of lambs weaned. Genomic best linear unbiased prediction (GBLUP), BayesR and pedigree BLUP analyses of the three reproduction traits measured on 5340 sheep (4503 ewes and 837 sires) with real and imputed genotypes for 510 174 SNPs were performed. The prediction of breeding values using both sire and ewe trait records was validated in Merino sheep. Prediction accuracy was evaluated by across sire family and random cross‐validations. Accuracies of genomic estimated breeding values (GEBVs) were assessed as the mean Pearson correlation adjusted by the accuracy of the input phenotypes. The addition of sire DTD into the prediction analysis resulted in higher accuracies compared with using only ewe records in genomic predictions or pedigree BLUP. Using GBLUP, the average accuracy based on the combined records (ewes and sire DTD) was 0.43 across traits, but the accuracies varied by trait and type of cross‐validations. The accuracies of GEBVs from random cross‐validations (range 0.17–0.61) were higher than were those from sire family cross‐validations (range 0.00–0.51). The GEBV accuracies of 0.41–0.54 for NLB and LSIZE based on the combined records were amongst the highest in the study. Although BayesR was not significantly different from GBLUP in prediction accuracy, it identified several candidate genes which are known to be associated with NLB and LSIZE. The approach provides a way to make use of all data available in genomic prediction for traits that have limited recording.     

Economic weights of maternal and direct traits of pigs calculated by applying gene flow methods

Multiple trait selection indexes in pig breeding programmes should take into account the population structure and time delay between parent selection and expressions of traits in all production levels next to the trait impacts on economic efficiency of production systems. Gene flow procedures could be used for the correct evaluation of maternal and direct traits of pig breeds involved in breeding or crossbreeding systems. Therefore, the aim of this study was to expand a previously developed bioeconomic model and computer program to calculate the marginal economic values by including a gene flow procedure to calculate the economic weights for maternal and direct traits in pig breeds. The new program was then applied to the three-way crossbreeding system of the Czech National Programme for Pig Breeding. Using this program, the marginal economic values of traits for dam breeds Czech Large White in the dam position and Czech Landrace in the sire position, and for the sire breed Pietrain were weighted by the number of discounted gene expressions of selected parents of each breed summarised within all links of the crossbreeding system during the 8-year investment period. Economic weights calculated in this way were compared with the approximate economic weights calculated previously without a gene flow procedure. Taking into account the time delay between parent selection and trait expression (using discounting with half-year discount rates of 2% or 5%) and including more than one generation of parent progeny had little impact on the relative economic importance of maternal and direct traits of breeds involved in the evaluated three-way crossbreeding system. These results indicated that this gene-flow method could be foregone when estimating the relative economic weights of traits in pig crossbreeding systems applying artificial insemination at all production levels.     

Canine genomics and genetics: running with the pack

The domestication of the dog from its wolf ancestors is perhaps the most complex genetic experiment in history, and certainly the most extensive. Beginning with the wolf, man has created dog breeds that are hunters or herders, big or small, lean or squat, and independent or loyal. Most breeds were established in the 1800s by dog fanciers, using a small number of founders that featured traits of particular interest. Popular sire effects, population bottlenecks, and strict breeding programs designed to expand populations with desirable traits led to the development of what are now closed breeding populations, with limited phenotypic and genetic heterogeneity, but which are ideal for genetic dissection of complex traits. In this review, we first discuss the advances in mapping and sequencing that accelerated the field in recent years. We then highlight findings of interest related to disease gene mapping and population structure. Finally, we summarize novel results on the genetics of morphologic variation.     

Influence of selection forms on genetic structure of domestic animals

Analysis of genetic structure of pure and crossbred sheep and cattle with the use of genetic-biochemical markers was carried out. Data on breed- and locus-specific genetic traits, stable in the time, were obtained. In sheep, breed-specific peculiarities of genetic structure partly related with the belonging of breeds to breed groups with fine-, semi-fine and coarse wool. The preferable influence of artificial selection at the phenotype complex traits in comparison with natural selection and animal origin on the genetic structure of crossbred sheep was revealed. However, the more profound effects of natural selection on the genetic structure of crossbred cattle were observed.     

Genome-wide association study of economically important traits in Charolais and Limousin beef cows

Genomic selection has proven effective for advancing genetic gain for key profit traits in dairy cattle production systems. However, its impact to-date on genetic improvement programs for beef cattle has been less effective. Despite this, the technology is thought to be particularly useful for low heritability traits such as those associated with reproductive efficiency. The objective of this study was to identify genetic variants associated with key determinants of reproductive and overall productive efficiency in beef cows. The analysis employed a large dataset derived from the national genetic evaluation program in Ireland for two of the most predominant beef breeds, viz. Charolais (n = 5 244 cows) and Limousin (n = 7 304 cows). Single nucleotide polymorphisms (SNPs) were identified as being statistically significantly associated (adj. P < 0.05) with both reproductive and productive traits for both breed types. However, there was little across breed commonality, with only two SNPs (rs110240246 and rs110344317; adj. P < 0.05) located within the genomic regions of the LCORL and MSTN genes respectively, identified in both Charolais and Limousin populations, associated with traits including carcass weight, cull-cow weight and live-weight. Significant SNPs within the MSTN gene were also associated with both reproduction and production related traits within each breed. Finally, traits including calving difficulty, calf mortality and calving interval were associated with SNPs within genomic regions comprising genes involved in cellular growth and lipid metabolism. Genetic variants identified as associated with both important reproductive efficiency and production related traits from this study warrant further analyses for their potential incorporation into breeding programmes to support the sustainability of beef cattle production.     

The genetic structure of Kulunda sheep]

The analysis of the genetic structure of the Kulunda sheep in eight polymorphous genetic-biochemical systems was carried out. While comparing with the genetic structures of number of sheep breeds, differentiated by the origin history, productivity traits and the breeding regions, the locus-specificity particularities of the Kulunda sheep were described. The importance of creating of the "genetic portrait" for disappearing breeds was discussed.     

The nature,scope and impact of genomic prediction in beef cattle in the United States

Artificial selection has proven to be effective at altering the performance of animal production systems. Nevertheless, selection based on assessment of the genetic superiority of candidates is suboptimal as a result of errors in the prediction of genetic merit. Conventional breeding programs may extend phenotypic measurements on selection candidates to include correlated indicator traits, or delay selection decisions well beyond puberty so that phenotypic performance can be observed on progeny or other relatives. Extending the generation interval to increase the accuracy of selection reduces annual rates of gain compared to accurate selection and use of parents of the next generation at the immediate time they reach breeding age. Genomic prediction aims at reducing prediction errors at breeding age by exploiting information on the transmission of chromosome fragments from parents to selection candidates, in conjunction with knowledge on the value of every chromosome fragment. For genomic prediction to influence beef cattle breeding programs and the rate or cost of genetic gains, training analyses must be undertaken, and genomic prediction tools made available for breeders and other industry stakeholders. This paper reviews the nature or kind of studies currently underway, the scope or extent of some of those studies, and comments on the likely predictive value of genomic information for beef cattle improvement.     

Complete mitogenome reveals genetic divergence and phylogenetic relationships among Indian cattle (Bos indicus) breeds

Indigenous cattle of India belong to the species, Bos indicus and they possess various adaptability and production traits. However, little is known about the genetic diversity and origin of these breeds. To investigate the status, we sequenced and analyzed the whole mitochondrial DNA (mtDNA) of seven Indian cattle breeds. In total, 49 single-nucleotide variants (SNVs) were identified among the seven breeds analyzed. We observed a common synonymous SNV in the COII gene (m.7583G?>?A) of all the breeds studied. The phylogenetic analysis and genetic distance estimation showed the close genetic relationship among the Indian cattle breeds, whereas distinct genetic differences were observed between Bos indicus and Bos taurus cattle. Our results indicate a common ancestor for European Zwergzebu breed and South Indian cattle. The estimated divergence time demonstrated that the Bos indicus and Bos taurus cattle lineages diverged 0.92 million years ago. Our study also demonstrates that ancestors of present zebu breeds originated in South and North India separately ～30,000 to 20,000 years ago. In conclusion, the identified genetic variants and results of the phylogenetic analysis may provide baseline information to develop appropriate strategies for management and conservation of Indian cattle breeds.     

Recent advances in cattle functional genomics and their application to beef quality

The advent of high-throughput DNA sequencing techniques, array technology and protein analysis has increased the efficiency of research in bovine muscle physiology, with the ultimate objective of improving beef quality either by breeding or rearing factors. For genetic purposes, polymorphisms in some key genes have been reported for their association with beef quality traits. The sequencing of the bovine genome has dramatically increased the number of available gene polymorphisms. The association of these new polymorphisms with the variability in beef quality (e.g. tenderness, marbling) for different breeds in different rearing systems will be a very important issue. For rearing purposes, global gene expression profiling at the mRNA or protein level has already shown that previously unsuspected genes may be associated either with muscle development or growth, and may lead to the development of new molecular indicators of tenderness or marbling. Some of these genes are specifically regulated by genetic and nutritional factors or differ between different beef cuts. In recognition of the potential economic benefits of genomics, public institutions in association with the beef industry are developing livestock genomics projects around the world. From the scientific, technical and economical points of view, genomics is thus reshaping research on beef quality.     

Ovine alpha-amylase genes: isolation, linkage mapping and association analysis with milk traits

On the basis of comparisons between cattle and sheep genome mapping information the ovine alpha-amylase gene was examined as a possible genetic marker for milk traits in sheep. The objective of the present study was to isolate, map and determine whether this gene is a candidate gene for milk traits. DNA fragments (832 and 2360 bp) corresponding to two different AMY genes were isolated, and one SNP in intron 3 and one GTG deletion in exon 3 of the 2360 bp DNA fragment were found. The 2360 bp ovine AMY DNA fragment was located on chromosome 1 by linkage mapping using the International Mapping Flock. No association was found between estimated breeding values for milk yield, protein and fat contents and AMY genotypes in a daughter design comprising 13 Manchega families with an average of 29 daughters (12-62) per sire.