Selection for AI Stud Traits

M. Todd See

North Carolina State University

 

Introduction

The adoption of artificial insemination (AI) has had a significant impact on the structure of the swine genetics industry.  It has been reported that AI now accounts for more than 50 percent of the total swine matings in the United States.  This effectively reduces the number of boars required in the U.S. swine breeding herd and at the same time increases the importance of high fertility and genetic merit for each boar.  While genetic evaluation procedures (BLUP) to select the top boars for AI are commonplace, attention still needs to be addressed on levels of inbreeding in boar populations and the cost of boar production relative to desired selection intensity. In addition, the genetic control of semen traits has not been extensively studied. Currently boars selected as "AI quality" are indexed and selected strictly on performance and carcass characteristics.  The following is a review of the genetic control of male reproductive traits with discussion towards the opportunity of selecting boars that would be optimal for semen production and quality, as well as, carcass and production traits.

 

AI Stud Traits

A complete semen evaluation includes determining the volume of the ejaculate, the total number of sperms cells and estimating the viability of sperm cells.  Semen should be evaluated promptly after it is collected.   A boar will usually ejaculate 150 to 250 ml of semen, but the volume can range from 50 to 500 ml (Almond et al., 1998).  Sperm count or concentration is usually reported in millions of sperm cells per ml of ejaculate.  Number of services per ejaculate can also be evaluated if the number of sperm cells per service is standardized.  Motility is a measure of the viability of the semen, or the percentage of sperm showing progressive forward motion.   Motility is a subjective test that requires training and practice by the AI technician.  Motility can be reported as both undiluted semen motility or extended semen motility.  Extended semen motility may also be evaluated over days of storage.  Assessing sperm cell morphology is another way to assess semen viability.  Morphology assessment is a very time consuming process that requires training, practice and patience.  Morphology assessments in practice will often be denoted as acceptable or unacceptable.  Because of the subjective nature of many motility and morphology evaluations a good collective measure of overall semen quality may be the percentage of acceptable collections produced by a boar.

           

A recent study (Flowers, 1998) examined the relationships between microscopic estimates of semen quality and fertility for boar semen.  This data represents weekly ejaculates from 12 mature boars for a 26-week period.  Evaluations for motility, morphology and acrosome integrity were conducted on each ejaculate.  Each ejaculate was extended and used to inseminate at least 5 sows. 

               

The most important conclusion from this study is that, motility, at best, can be used to establish the lower limit of acceptability for semen used for insemination.  Flowers concluded that motility is of little analytical value for ejaculates above the 60% level.  This is evident in that farrowing rates and number of pigs born alive were not different among ejaculates estimated to contain more than 60% motile spermatozoa.   As motility increased beyond 60% reproductive performance remained constant.  In contrast, for ejaculates with less than 60% motility, there was a highly correlated, positive linear relationship between the percentage of motile spermatozoa and reproductive performance. 

 

Unfortunately, the same general relationship between estimates of motility and fertility was present when morphology and acrosome integrity were considered individually or collectively with motility.  It would appear that none of the commonly used visual estimates of semen quality has strong correlations with farrowing rates and number of pigs born alive.  However, Flowers concludes that in practice morphology probably is a more appropriate characteristic to routinely monitor rather than motility.

 

Genetics of Male Reproduction

Estimates of heritability for several male reproductive traits are summarized in Table 1.  Testes and accessory gland measurements have moderate to high heritabilities while testosterone level and libido traits are slightly less heritable.  Testes measurements have a desirable genetic correlation with total sperm production or percent spermatogenesis (Wilson et al., 1977; Toelle et al., 1984; Young et al., 1986). Selection lines developed for increased weight of testes have been show to result in decreased age at which boars begin producing sperm cells (Rathje et al., 1995), increased daily sperm production (Huang and Johnson, 1996; Rathje et al., 1995) and increased concentration of sperm cells (Huang and Johnson, 1996).  Boars from lines selected for increased weight of testes did not differ from controls for percentage of abnormal sperm cells (Huang and Johnson, 1996). The service sire has also been reported to have a rather limited effect on litter size, embryonic survival and litter weight at 21 days.

 

Table 1. Heritability estimates from male reproductive traits.1

 

Trait

Number of estimates

Mean h2

Range

Testis width

8

.37

.02-.61

Testis length

6

.33

.30 - .39

Testis weight

5

.44

.24 -.73

Epididymis weight

4

.33

.15 - .55

Size of Cowper's gland

2

.61

.56 - .66

Basal testosterone level

2

.25

.14 - .37

Libido

13

.15

.03 - .47

Litter size

4

.014

.01 - .05

Embryonic survival

1

.04

.04

Litter weight at 21 days

1

06

.06

1Updated from Rothschild and Bidanel, 1998

 

 

Heritability estimates for semen traits are summarized in Table 2.  Sperm quantity and number of services produced per ejaculate have moderate to high heritabilities and would therefore be expected to respond to selection.  Sperm cell motility, morphology and concentration (count) are moderate in heritability.  However, the mean heritability estimates for sperm cell quality in Table 2 may be biased downward due to the subjective nature of the semen evaluations conducted in some of the studies (Oh et al., 2000).  Genetic control of sperm cell morphology is supported by Wekerle (1982) who reported that when sires had an increased incidence of morphological abnormalities (> 30%) their sons also had an incidence of abnormalities greater than 30%. While of increasingly less importance, halothane positive boars have been reported to have significantly lower sperm cells per ejaculate (Hillbrand and Glodek, 1984 and Schlenker et al., 1984), lower sperm volume (Schlenker et al., 1984), reduced forward motility (Schlenker et al., 1984) and increased percentage of abnormal sperm cells (Hillbrand and Glodek, 1984 and Schlenker et al., 1984). 

 

Table 2. Heritability estimates for semen traits

 

Trait

Number of estimates

(References)

Mean h2

Range

Sperm quantity

3               (12)

.37

.31 - .42

Sperm cell motility

      7        (2,10,12,17)

.20

.05 - .55

Sperm cell volume

       4              (2,17)

.21

.14 -.29

Sperm cell count

 4              (2,17)

.19

.01-.26

Sperm cell morphology

   3           (2,10,17)

.31

.05-.62

Number of services/ejaculate

1               (10)

.41

 

 

Brandt and Grandjot (1998) reported genetic correlations between semen traits and production traits (Table 3) for two lines of boars in the German hybrid-breeding scheme.  They reported high negative genetic correlations between volume and density and between density and motility the first relationship is expected and the second correlation could be explained in part by the subjective nature of motility scores.  A desirable relationship between density and daily gain and backfat depth was found, whereas, motility showed an undesirable relationship to both daily gain and backfat. These results are supported by Hillbrand and Glodek (1983) who also reported that sperm cell motility had desirable genetic correlation with ham conformation score and that number of abnormal sperm cells (sperm cell morphology) had a desirable genetic correlation with sperm cell concentration and an undesirable relationship with motility.  Brandt and Grandjot (1998) also reported that genetic correlations between semen quality traits and litter size were all below .04, which could be explained in part by standardization of services to a constant number of sperm cells and sperm cell concentration.

 

Table 3. Genetic correlations (pooled SE) between semen traits and production traits

 

Trait

Sperm cell volume

Sperm cell density

Sperm cell motility

Sperm cell density

-.49 (.08)

 

 

Sperm cell motility

.18 (.14)

-.43 (.13)

 

Daily Gain

-.19 (.12)

.14 (.11)

-.47 (.17)

Backfat

-.10 (.12)

-.18 (.10)

.24 (.17)

Source: Brandt and Grandjot, 1998

 

Oh et al. (2000) evaluated semen collection records for 253 AI boars using the DxMrr random regression routines developed by Meyer (1998).  For this analysis the mean number of services/ejaculate produced during each month of age was determined.  Mean observations were then limited to those from 6 to 27 months of age on 3-month intervals.  Genetic parameters where then estimated for average number of services/ejaculate by age of boar classification using a model that included season and year as fixed effects, additive genetic effect of the boar, permanent environmental effect of the boar and random error.  Heritability estimates for number of services/ejaculate by age of AI boar and genetic correlations between ages for number of services/ejaculate are presented in Table 4.  These results indicate that the heritability for number of services/ejaculate is quite similar across age of boar classification and is similar to previously reported literature (Rothschild and Bidanel, 1998).  Genetic correlations between ages for number of services/ejaculate were close to one for adjacent observations but decreased as the period between observations increased, especially after 12 months.  Permanent environmental effects on number of services/ejaculate would appear to be negligible (Table 5) but highly correlated between ages.

 

Table 4. Heritabilities (diagonal) and additive genetic correlations (off-diagonal) for number of services/ejaculate by age of AI boar

 

Age (Months)

6

9

12

15

18

21

24

27

6

.45

 

 

 

 

 

 

 

9

.99

.42

 

 

 

 

 

 

12

.95

.99

.41

 

 

 

 

 

15

.89

.95

.99

.40

 

 

 

 

18

.81

.88

.95

.99

.41

 

 

 

21

.71

.80

.89

.95

.99

.43

 

 

24

.61

.71

.82

.90

.96

.99

.46

 

27

.51

.63

.74

.84

.92

.97

.99

.50

Source: Oh et al., 2000

 

Table 5. Permanent environmental effects (diagonal) and correlations (off-diagonal) for number of services/ejaculate by age of AI boar

 

Age (Months)

6

9

12

15

18

21

24

27

6

.002

 

 

 

 

 

 

 

9

1.00

.003

 

 

 

 

 

 

12

.99

1.00

.005

 

 

 

 

 

15

.99

1.00

1.00

.008

 

 

 

 

18

.98

1.00

1.00

1.00

.011

 

 

 

21

.98

.99

1.00

1.00

1.00

.014

 

 

24

.98

.99

1.00

1.00

1.00

1.00

.017

 

27

.98

.99

1.00

1.00

1.00

1.00

1.00

.020

Source: Oh et al., 2000

 

Buchanan (1987) reviewed experiments that compared crossbred boars. He reported that crossbred boars exhibit a substantial advantage in testis size and weight over purebred boars and that ejaculate volume of crossbred boars was on average 14% larger than that of purebreds.  Concentration of sperm cells was greater in some studies but smaller in others.  Sperm cell motility and sperm cell morphology evaluations generally showed a small advantage for crossbred boars.

 

Economic Value

Methods to determine and compare the cost of semen production have been previously reported (See, 1996; Levis, 1999; Rutten et al., 2000).  Using conservative assumptions on cost of operating a 200 boar stud, semen production of 30 doses per boar per week, and 8.5 pigs marketed per litter estimates of economic value for number of services/ejaculate and sperm cell quality were determined.  An increase of one service/ejaculate would result in a $.27 savings in cost to produce a service or $.08 per pig marketed.  If under the same set of assumptions semen quality could be improved with a corresponding one percent improvement in acceptable ejaculates with no change in number of doses this would reduce cost per service by $.05 or $.015 per pig marketed.  These estimates do not take into account any potential improvements in conception rate, farrowing rate or litter size but only the cost associated with semen collection and processing.

 

Summary

While further investigation is warranted the available literature would indicate that the opportunity does exist to evaluate and select AI boars for semen production and sperm quality. However, substantial variation in reported heritabilities for semen quality measures would suggest that objective measures and/or more stringent standards for subjective measures might need to considered and collected if these traits are to be evaluated.

 

References

Almond, G., J. Britt, B. Flowers, C. Glossop, D. Levis, M. Morrow, and T. See. 1998. The SWINE AI Book: A field and laboratory technicians’ guide to artificial insemination in swine 2nd ed. Southern Cross Publishing, Raleigh, NC. ISBN 0-9640737-3-0.

 

Brandt, H. and G. Grandjot. 1998. Genetic and environmental effects on male fertility of AI boars. Proc. 6th World Congress on Genetics Applied to Livestock Production, Armidale, Australia. 23:527-530.

 

Buchanan, D.S. 1987. The crossbred sire: Experimental results for swine. J. Anim. Sci. 65:117-1127.

 

Flowers, W.L. 1998. Boar Fertility and artificial insemination.  Proc. 15th IPVS Congress, Brimingham England. 1:45-52.

 

Hillbrand, F.W. and P. Glodek. 1983. Genetic correlations between performance and semen traits of AI boars. In 34th Annual Meeting of the EAAP. Volume 2.

 

Hillbrand, F.W. and P. Glodek. 1984. Halothane sensitivity and semen quality of boars in 3 lines of pigs. In 35th Annual Meeting of the EAAP.2 (5):11-12.

 

Huang, Y.T. and R.K. Johnson. 1996. Effect of selection for size of testes in boars on semen and testis traits. J. Anim. Sci. 74:750-760.

 

Levis, D.G. 1999. Boar stud spreadsheet. University of Nebraska, Lincoln.

 

Meyer, K. 1998. DFREML user notes. Ver. 3.0b.

 

Oh, S.H., M.T. See, and R. Nugent. 2000. Estimation of genetic effects for semen quality and quantity in AI boars. J. Anim. Sci. 78, Suppl. 1, p. 67.

 

Rathje, T.A., R.K. Johnson and D.D. Lunstra. 1995. Sperm production in boars after nine generations of selection for increased weight of testis. J. Anim. Sci. 73:2177-2185.

 

Rothschild, M.F., and J.P. Bidanel. 1998. Biology and genetics of reproduction. In Genetics of the Pig, CAB International. New York, NY.  313-343.

 

Rutten, S.C., R.B. Morrison, and D. Reicks. 2000. Boar stud production analysis. Swine Health Prod. 8(1):11-14.

 

Schlenker, G., L. Jugert, K. Mudra, M. Pohle, and C. Heinze. 1984 Semen quality of boars with differing halothane susceptibility. Monatshefte für Veterinärmedizin. 39(22):760-763.

See. M.T. 1996.  A cost comparison of AI and natural service.  Animal Science Facts, North Carolina State Univ., ANS 96-809S.

 

Toelle, V.D. and O.W. Robison. 1984. Genetic parameters for testes trait in swine. J. Animal Sci. 59:967-973.

 

van der Steen, H.A.M. and B.A. Molenaar. Relation between boar fertility and fertility of daughters. In 34th Annual Meeting of the EAAP. Volume 1.

 

Wekerle, L. 1982. The inheritance of some boar semen anomalies.  In: Allattenyésztési és takarmányozási kutatóközpont közleményei. 25-28.

 

Wilson, E.R., R.K. Johnson, and R.P. Wettemann. 1977. Reproductive and testicular characteristics of purebred and crossbred boars. J. Anim. Sci. 44:939.

 

Young, L.D., K.A. Leymaster, and D.D. Lunstra. 1986. Genetic variation in testicular development and its relationship to female reproductive traits in swine. J. Anim. Sci. 63:17-26.

2000 NSIF Proceedings