Use of sire referencing schemes to select for improved carcass composition in sheep

Similar documents
Developments in the Genetic Improvement of a Large Commercial Population in the New Zealand Sheep Industry

Genomic selection in the Australian sheep industry

See what s on the inside can SRUC s new mobile

REALISED RESPONSES TO DIVERGENT SELECTION FOR YEARLING GROWTH RATE IN ANGUS CATTLE

Benefits of genomic selection in Merino, Terminal and Maternal indexes

Development of animal breeding strategies for the local breeds of ruminants in the French West Indies

Longhorn Cattle Performance Recording

BLUP and Genomic Selection

Improving Genetics in the Suckler Herd by Noirin McHugh & Mark McGee

Angus BREEDPLAN GETTING STARTED

OPTIMIZING SHEEP AND CATTLE BREEDING IN THE E. E. C. WITH SPECIAL REFERENCE TO FRANCE B. VISSAC* Summary

Strategy for Applying Genome-Wide Selection in Dairy Cattle

15. Breeding Program Design Principles

15. Breeding Program Design Principles

WAGYU BREEDOBJECT $INDEXES TECHNICAL UPDATE

Breeding Programs Review of approaches in Australia

THE CEFN IN HOUSE NUCLEUS PROGRAM. Rolf Sokolinski and Andrew Jones. CEFN PTY LTD, 54 King Street, Clifton, QLD 4361

LAMBPLAN: a sheep breeding strategy

11 Genetic and Environmental Impacts on Prenatal Loss H.H. Meyer

Genomic-Polygenic and Polygenic Evaluation of Multibreed Angus-Brahman Cattle for Direct and Maternal Growth Traits Under Subtropical Conditions

2018 ICBF and Sheep Ireland Genetics Conference 20 th Anniversary. Dorian Garrick

Breed Utilization and Production Efficiency

Alison Van Eenennaam, Ph.D.

France s strategy for a more profitable beef & sheep industry

Breeding practices in the Merino industry. Animal Genetics and Breeding Unit University of New England

Understanding and Using Expected Progeny Differences (EPDs)

Program or Technology? Remember: National Genetic Improvement is more than a technology. Genetic Improvement: Traditional Considerations

Mull Monitor Farm. Iain MacKay Torloisk, Isle of Mull Report from Meeting held on the 31 st January 2013 FUTURE EVENTS

THE COMBINATION OF RECORDS OF PRODUCTION, REPRODUCTION AND SUBJECTIVE TRAITS IN A PROVISIONAL SELECTION INDEX

More protifable beef cattle by genetic improvement - balancing your breeding program

Understanding Expected Progeny Differences (EPDs) Scott P. Greiner, Extension Animal Scientist, Virginia Tech

TSB Collaborative Research: Utilising i sequence data and genomics to improve novel carcass traits in beef cattle

Genetic evaluation of days to harvest in crossbred lambs

TECHNICAL BULLETIN GENEMAX ADVANTAGE IS DESIGNED FOR COMMERCIAL BEEF HERDS. August Zoetis Genetics 333 Portage Street Kalamazoo, MI

TECHNICAL BULLETIN GENEMAX ADVANTAGE IS DESIGNED FOR COMMERCIAL BEEF HERDS. August Zoetis Genetics 333 Portage Street Kalamazoo, MI

Breeding for Profit from Beef Production ( )

Farm Management Decisions in the Era of Genomics

Adoption of further traits to increase genetic gain in the $Index

Peul, Touabire and Djallonke sheep breeding programmes in Senegal

Replacement Rates in Sow Herds. Internal Multiplication: Breeding Strategies That Maximize Profit In Swine Production Systems

Replacement Rates in Sow Herds. Internal Multiplication: Breeding Strategies That Maximize Profit In Swine Production Systems

Proceedings, The Range Beef Cow Symposium XXI December 1, 2 and , Casper, WY. Integrating Information into Selection. Loren Berger.

Reliability of genetic evaluation using purebred and crossbred data from different pig farms

SDSU Sheep Day andusssa Regional Workshop

Incorporating meat quality in sheep breeding programmes: potential of non-invasive technologies

The Data Which Breeders May Collect For BREEDPLAN Analysis Includes: Flight time (from bail head to light beam)

Gene flow in a national cross-breeding beef population

The economics of using DNA markers for bull selection in the beef seedstock sector A.L. Van Eenennaam 1, J.H. van der Werf 2, M.E.

Beef cattle genetic evaluation in Australia ~ BREEDPLAN. Robert Banks AGBU

Video Image Analysis for meat yield - opportunities and challenges for value-based marketing of sheep and beef carcasses

Livestock straight-breeding system structures for the sustainable intensification of extensive grazing systems

Common Performance Recording Problems

The role and power of ultrasound in predicting marbling

Genomic selection for sheep and beef systems, dispelling the myths for farmers. Dewi Jones January 2016

The Irish Experience; DQI, breeding programs and genetic evaluations.

New Zealand Simmental Selection Indexes

BREEDPLAN EBVs The Traits Explained

Crossbreeding in Beef Cattle

Dr. Gatot Ciptadi. Fac. Of Animal Husbandry, UB. gatotciptadi.lecture.ub.ac.id. Dr.Gatot Ciptadi,Fac.Of Anim.

The benefits of genotyping at farm level & the impact across the wider dairy herd in Ireland. Kevin Downing 27 th October, 2016

Value of DNA information for beef bull selection

Agricultural Science Past Exam Questions Animal Production Higher Level

New Zealand Hereford Selection Indexes

Dr. Gatot Ciptadi. Fac. Of Animal Husbandry, UB. gatotciptadi.lecture.ub.ac.id.

New Limousin Genomic Breeding Values (GEBVS) Delivering s value for commercial producers

WHETHER dealing with a commercial

Collecting Abattoir Carcase Information

GENETICS GENETICS. for the WORLD CedarRidgeGenetics.com

11/30/2018. Introduction to Genomic Selection OUTLINE. 1. What is different between pedigree based and genomic selection? 2.

Choices in Breeding Programs to Fit Your Environment

Using EPDs in a Commercial Herd

Strategy for applying genome-wide selection in dairy cattle

Ireland s Strategy for a More Profitable Beef and Sheep Industry Dr. David Beehan B.Agr.Sc., PhD. Department of Agriculture, Food and the Marine

Angus Bull. Selecting your next

TECHNICAL BULLETIN No.43 Design and implementation of community-based sheep and goat crossbreeding schemes

SUFFOLK VS CANADIAN ARCOTT

The new infrastructure for cattle and sheep breeding in Ireland.

Introduction to Indexes

Use of New Breeding Techniques applied to cattle

2019 A utumn R am S ale

Understanding and Using Performance Data in Judging Classes

Profitable Genetic Selection: How the National Sheep Improvement Program Can Help the US Sheep and Goat Industry.

AN INTERNATIONAL COMPARISON OF THE MAIN MEAT SHEEP GENETIC SCHEMES Michel de Rancourt 1, Jérôme Raoul 2. Abstract. 1. The world sheep meat context

A systematic approach to breeding programs for game PART 1

Economic evaluations of beef bulls in an integrated supply chain 1

Trends in Swine Production Areas of Largest Pork Producers

1 This research was conducted under cooperative agreements between USDA, ARS, Montana Agric. Exp.

Sire Selection. Dr. Tim Marshall Retired UF Professor of Animal Science Retired Dean and Professor, Abraham Baldwin Agricultural College

The development of breeding strategies for the large scale commercial dairy sector in Zimbabwe

Understanding and Applying Economically Relevant Traits (ERT) and Indices for the Commercial Cattle Rancher

TECHNICAL BULLETIN GENEMAX FOCUS - EVALUATION OF GROWTH & GRADE FOR COMMERCIAL USERS OF ANGUS GENETICS. November 2016

Breeding Objectives Indicate Value of Genomics for Beef Cattle M. D. MacNeil, Delta G

Small ruminant breeding programmes in Greece

Comparison of three models to estimate breeding values for percentage of loin intramuscular fat in Duroc swine 1

Eskdalemuir A comparison of forestry and hill farming; productivity and economic impact

Optimizing Traditional and Marker Assisted Evaluation in Beef Cattle

User Guide

Reducing the costs of beef production through the genetic improvement of net feed conversion efficiency

Status as of: 01 February 2008 DESCRIPTION OF BEEF NATIONAL GENETIC EVALUATION SYSTEM DATA COLLECTION

B+LNZ Genetics for the Commercial Farmer. Max Tweedie

Transcription:

University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Faculty Papers and Publications in Animal Science Animal Science Department 2001 Use of sire referencing schemes to select for improved carcass composition in sheep G. Simm Scottish Agricultural College R. M. Lewis Scottish Agricultural College, ron.lewis@unl.edu J. E. Collins Signet, SAC G. J. Nieuwhof Meat and Livestock Commission Follow this and additional works at: http://digitalcommons.unl.edu/animalscifacpub Simm, G.; Lewis, R. M.; Collins, J. E.; and Nieuwhof, G. J., "Use of sire referencing schemes to select for improved carcass composition in sheep" (2001). Faculty Papers and Publications in Animal Science. 826. http://digitalcommons.unl.edu/animalscifacpub/826 This Article is brought to you for free and open access by the Animal Science Department at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Faculty Papers and Publications in Animal Science by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln.

Simm, Lewis, Collins & Nieuwhof in Journal of Animal Science (2001) 79 (E Supplement). Copyright 2001, American Society of Animal Science. Used by permission. Use of sire referencing schemes to select for improved carcass composition in sheep 1 G. Simm* 2, R. M. Lewis*, J. E. Collins, and G. J. Nieuwhof Scottish Agricultural College (SAC), West Mains Road, Edinburgh, EH9 3JG, U.K.; Signet, SAC, West Mains Road, Edinburgh, EH9 3JG, U.K.; and Meat and Livestock Commission, P.O. Box 44, Winterhill House, Snowdon Drive, Milton Keynes, MK6 1AX, U.K. ABSTRACT: Objective genetic improvement in specialized meat breeds of sheep in Britain is based largely on the performance recording and genetic evaluation service provided by Signet and the Meat and Livestock Commission. This includes the use of ultrasonic scanning and a selection index to identify animals with high genetic merit for lean growth. More than 20 sire referencing schemes (SRS) have been established in Britain during the last 12 yr. About half of the performance-recorded flocks in Britain now belong to SRS. Sire referencing schemes create genetic links between flocks and years through the shared use of elite rams (reference sires), often via AI. Multitrait animal model BLUP is then used to provide across-flock genetic evaluations. These in turn allow increased selection intensities and increased response to selection. High responses to index selection for lean growth (about 1.75% per annum in the specialized meat breeds) and other measures of performance are being achieved. Key Words: Carcass Composition, Genetic Improvement, Sheep 2001 American Society of Animal Science. All rights reserved. J. Anim. Sci. 79(E. Suppl.):E255 E259 Introduction Lamb carcasses are often fatter than desired. Management and nutritional measures may influence carcass fatness, but genetic improvements offer a permanent, and usually cost-effective, means of matching carcass quality with consumer demand (Simm, 1992, 1994). Although using several measures in combination may be effective, genetic improvement is often one of the most practical routes for improving carcass composition in extensive systems. National or regional performance-recording schemes are now available to sheep breeders in many countries. In Britain, performance-recording schemes were operated initially by the Meat and Livestock Commission 1 We are grateful to the Meat and Livestock Commission, the Scottish Executive Rural Affairs Department, the Ministry of Agriculture, Fisheries and Food, and the Biotechnology and Biological Sciences Research Council for funding the SAC research mentioned here. We are also grateful to the many colleagues, breeders, and industry organisations involved in this research, and to Centurian (Polled Dorset) SRS Ltd., Charollais Sire Referencing Ltd., Elite Texel Sires Ltd., The Meatlinc Sheep Co. Ltd. and Suffolk Sire Reference Scheme Ltd. for permission to publish data from their schemes. 2 Correspondence: SAC, ABD, Bush Estate, Penicuik, Midlothian, EH26 0PH, UK (e-mail: g.simm@ed.sac.ac.uk). Received July 26, 2000. Accepted June 26, 2001. (MLC), and more recently by Signet a joint MLC/Scottish Agricultural College (SAC) company. As in other countries, genetic improvement of sheep in Britain is based on on-farm performance recording. Sheep improvement programs are often hampered by relatively low use of performance recording, relatively small size of recorded flocks, and frequent lack of acrossflock genetic evaluations. In several countries, cooperative breeding schemes have been formed to surmount some of these problems. Of the best known are group breeding schemes, originally widely used in New Zealand and Australia (James, 1977; Parker and Rae, 1982). Another type of cooperative breeding scheme, sire referencing, has gained popularity in Britain. Sire referencing schemes (SRS) have been formed for over 20 sheep breeds in Britain since the late 1980s, including all of the major specialized meat breeds. About half of performance-recorded flocks in Britain, and about two thirds of performance-recorded sheep, now belong to these schemes. Most of the schemes are achieving substantial rates of genetic progress. This article describes the role of SRS in selecting for improved carcass composition, their design and operation, the results achieved by some schemes, the benefits for participants and their clients, and possible future developments. The Role of Sire Referencing Schemes Over the last 20 yr or so, BLUP has become the preferred method of predicting breeding values for farm E255

E256 Simm et al. animals (Henderson, 1984). The BLUP approach disentangles genetics from management and feeding in the best possible way, and so predicts breeding values more accurately. Related animals in different herds or flocks (e.g., the progeny of the same sires) provide genetic links between them. When these links are sufficiently strong and BLUP is used, the EBV of animals can be compared fairly across herds or flocks. This has a positive effect on the number of animals that can be compared fairly, and thus on the selection intensity and genetic gain that can be achieved. These benefits are augmented when reproductive techniques such as AI are used to increase the use of elite parents. Because related animals are recorded in successive years, it is also possible to compare BLUP EBV across years, to estimate genetic trends in evaluated traits and associated indexes. This is valuable for breeders to monitor progress in their improvement programs, and for commercial producers to identify individual stud flocks or breeding schemes making most progress. BLUP has begun to be used in genetic evaluation of sheep. However, the low use of AI in sheep has often resulted in weak genetic links among flocks. Consequently, BLUP evaluations are often performed within flocks, which means that EBV produced can only be compared fairly among animals in the same flock. Sire referencing schemes are cooperative breeding schemes creating genetic links among flocks, usually through the use of AI sires. Sire referencing schemes have been in operation in sheep or beef cattle in several countries for about 20 yr now (e.g., Willham, 1979; Ménissier et al., 1982; Morris and Baker, 1982). Interest in these schemes in Britain began in the late 1980s to enable across-flock genetic evaluations and so to accelerate rates of genetic improvement. Four key factors stimulated this interest: 1) national availability of relevant performance-recording services and selection criteria, especially the widespread use of ultrasonic scanning and the use of index selection for lean growth in performance-recorded terminal sire flocks; 2) improved success rates of laparoscopic AI in sheep using frozenthawed semen, and access to specialist sheep AI services; 3) wider availability of computer software to perform BLUP evaluations and the lower relative cost of powerful computers to run this software; 4) research and interaction with breeders on the optimal design and operation of schemes. Details of some of the SRS in specialized meat (terminal sire) breeds in Britain are shown in Table 1. Multitrait animal model BLUP evaluations have been used routinely in these schemes from the outset. Signet/ MLC have also introduced within-flock BLUP evaluations for flocks not involved in SRS. Breeding Objectives, Performance Recording and Genetic Evaluation The U.K. sheep industry has a stratified structure. In the hills and mountains, ewes of hardy breeds, such as the Scottish Blackface, Welsh Mountain, and Swaledale, are usually bred to a ram of the same breed for four or five lamb crops. Ewes are then moved to lower ground, for crossing with a longwool or crossing breed such as the Bluefaced Leicester or Border Leicester. The F1 females resulting from these matings form the core of the commercial sheep industry in the uplands and lowlands. These F1 females are mated to rams of specialized meat breeds, or terminal sire breeds, such as the Suffolk, Texel and Charollais, to produce the slaughter generation of lambs. Meat production is the primary objective in each sector of the U.K. sheep industry, with all three breed types making important contributions to the genetic makeup of lambs slaughtered (39% terminal sire breed genes, 34% hill breed genes, 26% crossing breed genes; Maniatis and Pollot, 1998). However, breeding objectives vary among sectors, with growth and carcass traits being the most important traits in terminal sire breeds, while maternal characteristics are also important in the hill and crossing breeds. Performance records collected by Signet include litter size at birth and weaning, live weights at a range of ages from weaning to breeding as measures of both the lamb s own merit for growth and its dam s milking and mothering ability, and ultrasonic measurements of fat and muscle depths in the loin region. Multitrait animal model BLUP EBV are produced for most of these individual traits, and these EBV are also used to calculate selection indexes relevant to each of the sectors of the industry. In terminal sire breeds, a lean growth index is derived, which combines information on live weight, ultrasonic fat depth and ultrasonic muscle depth, all measured at about 20 wk of age (Simm and Dingwall, 1989). The breeding goal of this index comprises carcass lean weight and carcass fat weight, with relative economic values of +3 and 1, respectively. These relative economic values were chosen to achieve desired gains in the traits in the breeding goal, rather than being based on actual market returns. This approach was chosen because of the weak relationship between carcass price and fatness in Britain at the time the index was derived. Optimal Design of Sire Referencing Schemes The main goal of most SRS is to create a structure that accelerates the rate of genetic improvement, for an agreed objective, in members flocks. To do this, genetic links are created across members flocks by the use of AI rams on a portion of the ewes in each flock, or by sharing rams for natural service. Genetic links among flocks permit the use of across-flock BLUP methods to produce EBV for across-flock comparison. In a sense, SRS are a means to an end; they create the genetic links that would occur naturally if there was wider use of AI in purebred sheep flocks. However, if they are organized properly they can also result in faster rates

Sheep sire referencing schemes E257 Table 1. Details of some sheep sire referencing schemes in meat breeds in Britain No. member Year scheme started flocks evaluated No. lambs born Breed (year of first lambing) in 1999 in 1999 Reference sire use a Suffolk 1990 66 10,148 AI Charollais 1990 39 4,267 AI Meatlinc 1991 4 1,001 AI/NS Texel 1992 58 10,801 AI Polled Dorset 1995 11 5,787 AI/NS a AI = artificial insemination; NS = natural service. of progress than would be achieved with the ad hoc use of AI. Computer simulation has been used to study three factors in the design of SRS that affect rates of genetic response and inbreeding: the number of reference sires used (1, 2, or 3), the number of ewes per flock mated to reference sires (a total of 10, 15, or 30 ewes), and the selection intensity for reference sires in the scheme (highest ranking, or from the top sixth or top third available). Genetic progress increases with increasing intensity of selection and with increasing number of ewes per flock mated to reference sires (Lewis and Simm, 2000). However, this greater genetic gain can be achieved at acceptable levels of inbreeding because of the larger population size in SRS. The SRS rely for their success on good genetic links between flocks. Recent research at SAC and the Roslin Institute in Edinburgh has produced a method of measuring the strength of genetic links (or connectedness ) between existing or potential new member flocks in SRS, in order to identify where reference sires need to be used more widely to allow reliable comparisons across all flocks (Lewis et al., 1999). Practical Operation of Sire Referencing Schemes The operation of SRS in Britain usually involves: 1) Selection of a panel of reference sires for use across members flocks. To qualify as potential reference sires, in most schemes, animals must have high EBV or index scores and must be functionally sound. Qualifying animals are often brought to a central location where all members gather to view them and vote for their choice, based on their own preferred combination of EBV, index score, pedigree, conformation, and breed type. Depending on the scheme, semen may be purchased from the owner of the selected reference sire without transfer of ownership, or the scheme may purchase the ram, or a share in him. 2) Use of two or three reference sires from this panel, by AI or natural mating, on a proportion of the ewes in each member s flock. In schemes with a wide geographic spread of members, insemination with fresh semen is impractical, so laparoscopic AI with frozen-thawed semen is often used. In terminal sire breeds, a total of 30 ewes per flock is usually recommended for mating to reference sires, based on the simulation work described above. 3) Recording performance in appropriate traits via the Signet recording scheme outlined earlier. In terminal sire breeds, most emphasis is usually on growth and ultrasonic measurements, which are then used to calculate the lean index described earlier. In the hill and crossing breeds maternal performance is also important. 4) Evaluation of performance records using across-flock, multitrait animal model BLUP. This produces EBV that can be compared fairly across flocks and across years. 5) Use of these results to select the next generation of potential reference sires and to select sires and replacement females for the individual members flocks. The key participants in the operation of SRS are the individual breeder members, the agency responsible for performance recording and genetic evaluation, and the AI company. In some cases there is active involvement of the relevant breed society. Even though SRS can undoubtedly help to accelerate genetic improvement, there are additional costs associated with membership, especially relating to the purchase of reference sires or semen and the use of AI. Also, members have less flexibility in mating decisions as a result of matings to reference sires. However, the level of cooperation and the financial and legal commitment required to make SRS work are less than in some other cooperative breeding schemes. Evidence of Improvement Estimated genetic trends in several of the SRS in meat breeds in Britain are shown in Figure 1. It is perhaps easiest to gauge the magnitude of the changes made by comparing them to those achieved in selection experiments. In most experiments, rates of genetic change in excess of 2% per annum have been achieved in fat depth or index score (Simm, 1994). These responses are close to the maximum expected values for the traits and flock sizes concerned. One of these experiments was carried out at SAC, in Suffolk sheep, where selection was on the index now used in SRS. Annual rates of change in (unscaled) index score of around 2% per annum were achieved. Annual responses in lean index score in SRS in most specialized meat breeds are only slightly less than this (i.e., rates of change of about 1.75% per annum in most schemes though higher rates are being achieved in the Meatlinc breed). Because of the much larger size of the industry schemes,

E258 Simm et al. Figure 1. Genetic trends in lean growth index scores (SD of index = 40 points) in five sire referencing schemes in Britain. The graph shows the average index score of lambs born in the year concerned (mean in start year = 100). they can achieve these similar responses in the index of objectively-measured traits, while taking account of visually assessed breed characteristics and conformation. Also, some breeders use the individual trait EBV to put additional selection emphasis on a component of the index. In many industry flocks, and in several of the experiments mentioned, animals are tested under intensive feeding, whereas in the U.K., the majority of lambs are produced off grass. Two experiments have been conducted at SAC to test the effect of selection under intensive feeding on the response in an extensive regimen. The first of these experiments involved high- or lowindex Suffolk rams, from the SAC selection experiment mentioned earlier, mated to Scottish Mule (Bluefaced Leicester Scottish Blackface) ewes. Their lambs were reared at grass to produce carcasses at target weights of 16.5, 20.0, or 23.5 kg. Sample joint dissections on these carcasses showed that the progeny of high-index sires had about 1.0% more lean and about 3.5% less fat than the progeny of low-index sires (sires differed by 100 index points, or 2.5 standard deviations in index score; Lewis et al., 1996). A second experiment involved mating selection or control line Suffolk rams from the SAC experiment to Scottish Mule ewes, with lambs slaughtered at a target live weight of 42 kg (Simm and Murphy, 1996). Selection line progeny had significantly greater carcass saleable meat yield than control line progeny, both at an adjusted constant carcass weight (+0.10 kg) and an adjusted constant visually appraised subcutaneous-fat level (+0.25 kg; unpublished SAC result). On average, lamb carcasses from selection line sires achieved prices about $2.40 higher than those from control sires, and were slaughtered 11 d sooner; this earlier slaughter date would save about $0.96 in grazing costs. This financial advantage is worth up to $960 over the working life of a ram. In both these experiments, the progeny of high index sires had poorer visually appraised carcass conformation than the progeny of low index sires, at an adjusted constant carcass weight. However, this difference in conformation was largely explained by differences in carcass fatness at this fixed weight. Possible Future Developments Because SRS rely on the widespread use of a few elite rams, they have the ideal structure to exploit new technologies more cost-effectively than most individual breeders can. For example, techniques such as computer tomography (CT) have the potential to dramatically increase rates of genetic improvement in leanmeat production in sheep (e.g., allowing up to 50% faster progress in lean growth than that possible from selection on ultrasonic measurements; Simm and Dingwall, 1989). The use of CT also allows selection for additional carcass attributes (e.g., selection for increased muscularity and altered fat or muscle distribution). Following early experimental work in Norway, CT facilities for farm animals have been established in Australia, New Zealand, and Hungary, and more recently in Edinburgh, U.K. Recent SAC studies have shown that carcass lean and fat weights can be predicted with very high precision from two or three CT scans together with live weight (Young et al., 1999). Research is now in progress to design optimum twostage selection programs that involve screening of large numbers of sheep using current ultrasonic methods, followed by more detailed CT measurements on a small proportion of these sheep. Two-stage selection schemes have begun in the five SRS mentioned in Table 1, plus the Hampshire Down SRS, with the top 10 to 20% of rams being identified in the field, based on ultrasonic measurements, for further CT measurements.

Similarly, it is likely that new molecular genetic or reproductive technologies will be helpful for identifying elite animals and then increasing their influence in future breeding programs. Already there has been a rapid uptake in the U.K., especially in SRS, of DNAbased genotyping to identify sheep that are genetically resistant to scrapie (Dawson et al., 1998). Marker-assisted selection for resistance to other diseases, or for other traits which are difficult to measure, such as meat quality, may follow. Research is in progress in several countries to identify potentially useful markers for sheep breeding. A study of this type began recently in the Roslin Institute, SAC, and the University of Edinburgh, in SRS in the Suffolk, Texel, and Charollais breeds. In the decade or so over which SRS have existed in the U.K. sheep industry, they have contributed greatly to rates of genetic improvement in lean growth. The developments outlined above should ensure that they make an even greater contribution over the decades to come. Implications Sire referencing schemes are cooperative breeding schemes that create genetic links among participating flocks (or herds). These links are usually created through the use of artificial insemination from elite sires. In theory, sire referencing schemes permit acrossflock genetic evaluation, increased selection intensity and, ultimately, increased rates of genetic gain. These schemes have had an important role in genetic improvement of several specialized meat breeds of sheep in Britain. Rates of improvement in lean growth being achieved in these industry schemes are close to the rates of gain achieved in experimental flocks. Selection for lean growth in seedstock flocks improves physical and economic performance of progeny in commercial flocks. Sheep sire referencing schemes Literature Cited E259 Dawson, M, L. J. Hoinville, B. D. Hosie, and N. Hunter. 1998. Guidance on the use of PrP genotyping as an aid to the control of clinical scrapie. Vet. Rec. 142:623 625. Henderson, C. R. 1984. Application of Linear Models in Animal Breeding. University of Guelph, Guelph, Canada. James, J. W. 1977. Open nucleus breeding schemes. Anim. Prod. 24:287 305. Lewis, R. M., R. E. Crump, G. Simm and R. Thompson. 1999. Assessing connectedness in across-flock genetic evaluations. In: Proc. Brit. Soc. Anim. Sci., Scarborough, U.K. p 121 (Abstr.). Lewis, R. M., and G. Simm. 2000. Selection strategies in sire referencing schemes in sheep. Livest. Prod. Sci. 67:129 141. Lewis, R. M., G. Simm, W. S. Dingwall, and S. V. Murphy. 1996. Selection for lean growth in terminal sire sheep to produce leaner crossbred progeny. Anim. Sci. 63:133 142. Maniatis, N., and G. E. Pollot. 1998. The dynamics of genetic resources at a national level the British sheep industry as a case study. In: Proc. 6 th World. Cong. Genet. Appl. Livest. Prod., Armidale, NSW, Australia. Vol. 27, p 219. Ménissier, F., J. L. Foulley, and J. Sapa. 1982. Selection of French beef breeds for purebreeding. In: Proc. 2nd World Cong. Genet. Appl. Livest. Prod., Madrid, Spain. Vol. VIII, p 314. Morris, C. A., and R. L. Baker. 1982. The Angus sire reference scheme in New Zealand. In: Proc. 2nd World Cong. Genet. Appl. Livest. Prod., Madrid, Spain. Vol. VIII, p 305. Parker, A. G. H., and A. L. Rae. 1982. Underlying principles of cooperative group breeding schemes. In: Proc. World Cong. Sheep and Beef Cattle Breeding, Vol. II, pp 95 101. Simm, G. 1992. Selection for lean meat production in sheep. In: A. W. Speedy (ed.) Recent Advances in Sheep and Goat Research. p 193. C. A. B. International, Wallingford, U.K. Simm, G. 1994. Developments in improvement of meat sheep. In: Proc. 5th World Cong. Genet. Appl. Livest. Prod., Guelph, Canada. Vol 18, p 3. Simm, G., and W. S. Dingwall. 1989. Selection indices for lean meat production in sheep. Livest. Prod. Sci. 21: 223 233. Simm, G., and S. V. Murphy. 1996. The effects of selection for lean growth in Suffolk sires on the saleable meat yield of their crossbred progeny. Anim. Sci. 62: 255 263. Willham, R. L. 1979. Evaluation and direction of beef sire evaluation programmes. J. Anim. Sci. 49: 592 599. Young, M. J., R. M. Lewis, K. A. McLean, N. A. A. Robson, J. Fraser, J. FitzSimons, J. Donbavand, and G. Simm. 1999. Prediction of carcass composition in meat breeds of sheep using computer tomography. In: Proc. Brit. Soc. Anim. Sci., Scarborough, U.K. p 43 (Abstr.).