DNA

FINGERPRINTS

AS PREDICTORS

OF HETEROSIS

Jan S. Gavora, R. Wayne Fairfull, Bernhard Benkel, William J. Cantwell and James R. Chambers, Centre for Food and Animal Research Ottawa, Ontario Canada K1A 0C6. Summary Retrospective analyses of DNA fingerprints from three crossbreeding experiments were conducted using two minisatellite and one middle-repetitive DNA probes. Genetic distances were expressed as band sharing ratios based on pooled DNA samples of 10 to 15 individuals per parental genetic group. It was concluded that: 1. 2. 3. 4.

Heterosis in chickens can be predicted from fingerprints of pooled DNA samples. Predictability of heterosis increases with the number of DNA fingerprint bands assessed. Probes vary in their predictiv e value for individual traits and prediction is generally better for traits with sizeable than those with small heterosis. Further research on refining the technique for prediction of heterosis is justified. It can be expected that as understanding of the molecular basis of production traits progresses, the use of single locus probes, detecting quantitative trait loci or their markers, will increase relative to multi-locus probes for production of DNA fingerprints. Progress in mapping the chicken genome is expected to result in improved accuracy in predictions of heterosis. Introduction

Hybrid animals and birds are widely used intoday's livestock production. With the possible exception of dairy cattle, commercially used livestock are generally produced by crossing breeds, strains_ or lines selected to various degrees for performance in economically important traits. In some instances, particularly in egg chickens, breeders may practice selection for combining ability, usually in combination with selection for purebred performance. Poultry breeders continuously test crossbred performance of various lines so that field testing of hybrids constitutes a substantial part of production costs for primary breeding companies. Therefore, a technique allowing a reasonably accurate preselection of strains or lines for crossing would constitute a welcome improvement to the present system. DNA fingerprints (DFP) with multi-locus probes detecting several types of repeats, provide a tool to assess the genome as a whole. Such probes could be divided into three general types: (1) micro-satellite probes, detecting DNA repeats, usually consisting of 2-8 bp, (2) mini-satellite probes detecting DNA repeats 9-65 bp in length, and (3) middle-repetitive DNA probes that detect DNA elements several kbp in length. The first two categories are sometimes referred to as variable number tandem repeats. The use of middle repetitive DNA probes is believed to be introduced in this study for the first time to generate DNA fingerprints. DNA fingerprints have been shown to be a useful tool for assessment of genetic distances between genetic groups of poultry (Kuhnlein et al. 1989, Dunnington 1991, Haberfeld et al. 1992). DFP could also be used to estimate genetic distance between individuals -- inbreeding (Kuhnlein et al. 1990). A recent review of uses of DFP in poultry breeding and genetics was published by Hillel et al. (1993).

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It is commonly accepted that, in general terms, heterosis increases with genetic distance between populations. As DFP can provide an estimate of genetic distances, it was considered possible that heterosis or some portion of it may be predicted on the basis of genetic distances estimated from DFP. Charcosset et al. (1991) theoretically evaluated the relationship between heterosis and heterozygosity at marker loci and concluded that prediction of heterosis would be improved if markers could be selected for their relationship to the alleles implicated in the heterosis of the trait considered. Unfortunately, sufficient molecular markers of quantitive trait loci for economically important characters of poultry are not, at present, available. Therefore, for purposes of the present study, it was hypothesized that DFP will contain loci related to the quantitative traits and may, therefore, predict heterosis. To make the approach more feasible in practical applications, DFP of a combined sample from several individuals, rather than DFP of the individuals were used in the study. The objective of the present study was to assess, on the basis of retrospective analysis of crossbreeding data in chickens, the value of DFP in prediction of heterosis for economically important traits of egg and meat chickens. Materials and methods Crossbreeding experiments and sampling of parental strains Data from three different crossbreeding experiments were used in this study (Table I)_ A large crossbreeding experiment conducted in the late 1970s used six Ottawa Leghorn strains selected for high egg production and related economic traits. The strains were tested along with their 15 reciprocal crosses from which production data for the evaluation were available. Both first year egg production (Fairfull et al. 1983) and second year data (Fairfull 1982) were used in the evaluation. For each one-way cross or a parent entry, 57 pullets were tested in the experiment. A second large crossbreeding experiment was performed in 1987 (J.S. Gavora, unpublished). The ten parental groups used in the crossbreeding experiment were inbred lines of Leghorns, outbred Leghorn strains or a commercial stock and outbred meat-type experimental strains or a commercial stock. Results from 14 such reciprocal crosses were evaluated. The numbers of pullets tested were 7 to 55 per one-way cross, 35 to 101 per reciprocal cross, 23 to 50 pet parent outbred strain and 7 to 35 per parent inbred line. The third set of data originated from a crossbreeding experiment (J.R. Chambers, unpublished) in which one-way or reciprocal crosses were produced from eight experimental meat-type selected or control strains and a total of 13 crosses were available for evaluation. There were 56 males and 56 females tested for each cross or strain. In 1989 or 1990, blood were pedigree mated. sampling of families. breeding, the numberof

samples were obtained from females from each parental stock. All the strains The 15 females were chosen in a random, stratified manner to maximize the In a few instances, where inbred lines were too small in size at the time of birds bled was less than 15 but never less than 10 per genetic group.

63

DNA analyses For each genetic group a composite sample was prepared by mixing a 50 #L sample of blood from each of the birds bled in a sterile test tube. From the composite sample, or from a single bird, a 25/zL aliquot was used for DNA extraction (Benkel et al. 1992). Twelve/zg of DNA was digested with 120 units of Msp I (Pharmacia) according to the supplier's directions. Before loading onto the gel (10 #g/sample) 500 pg of ;k phage DNA fragments were added to each sample of chicken DNA. Samples were separated on a 1% agarose gel (20 x 20 cm) in TPE buffer at 2 volts/cm overnight. Transfer was performed by the capillary method as described by Maniatis et al. (1982) and DNA was fixed to HybondN membranes (Amersham) by UV irradiation. The DNA probes described below were labelled to high specific activity using 32pdCTP 3000 Ci/mmole and the Oligo labelling kit (Pharmacia) and 25ng of probe was used per membrane. The sequence of probing and reprobing was as follows: M13, YNZ, EAV, and pCla I with ;k phage. _The first and second probings were at low stringency, in the absence of DNA blocker in the hybridization solution as described by Vassart et al. (1987). The third and fourth probings were at normal stringency, using standard hybridization buffers (Maniatis et all 1982). After the probing, membranes were exposed to Kodak X-OmatAR X-ray film with Kodak X-Omatic intensifying screens for 24 to 70 hours at -70°C. DNA Probes Three DNA probes were used in the prediction of heterosis. Probe YNZ detects repeats of a 15 bp motif related to the human zeta-globin (Nakamura et al. 1987). The M13 Probe detects repeats of a 15 bp motif related to the bacteriophage M13 protein III (Vassart et al. 1987). Hence these two probes detected mini-satellite repeats. The third probe, designated EAV is a middle-repet!tive DNA sequence, approximately 6.5 kbp in length that represents an endogenous avian retrovirus present in up to 50 copies in chicken genomes (B. Benkel and J.S. Gavora, in preparation). A fourth probe, designated pCla, was 850 bp fragment of the chicken c_d-Globin gene (Fischer et al. 1984). Evaluation of autoradiograms Autoradiograms were produced from gels for each of the three above crossbreeding experiments separately. They were scanned by a digital scanner interfaced to a Macintosh computer and the scans were analyzed using a Shareware Program Image 132. Examination of autoradiograms showing the bands produced by the pCla I and X probes indicated that band migrations within each membrane were sufficiently similar as not to require any correction for differences in the migration distance of DNA fragments of equal size. Therefore, after correcting for the general background of the autoradiogram, the optical densities of bands on the DFP were digitalized so that each point on the autoradiogram was characterized by its distance from the origin and optical density. Such data sets were then examined to determine the identity of bands within an autoradiogram. A maximum tolerance of 2% of the distance from the origin was allowed for bands in different lanes to be considered identical.

64

Measures of genetic distance Genetic distance between any two populations was expressed as band-sharing ratio: BR = Number of common bands/Total number of bands. Alternatively, Modified Rogers Distance (MRD) (Lee et al. 1989) was also used to express genetic distances as follows:

rl

1

where p_, Pjk = Frequencies of the k_hbands for the i_ and j_hstrains, 1 = total no. of bands, n = total no. of bands for the pair of strains. For calculations of MRD, it was assumed that the optical density of a band reflected the frequency of that DNA fragment in the group of birds evaluated in the pooled DNA. To arrive at relative frequencies, optical densities of bands considered to have the same distance from origin within an experiment (autoradiogram) were compared. The band with the highest optical density was then assigned the value of 1 and the densities of the remaining bands were expressed relative to that band, thus obtaining values between 0 and 1. Statistical analyses Heterosis for each cross was calculated as the deviation of the performance of the cross from midparent value. Product-moment correlations between heterosis and genetic distances obtained from different probes and between those from the same probes, expressed by BR or by MRD were evaluated to assess the relationships among the DNA fragments detected by individual probes and between the two measures of genetic distance, respectively. Product-moment correlations between heterosis and genetic distance measures for the parental genetic groups were also used to assess predictability. As probes YNZ and M13 tended to give similar results, data from evaluation of the autoradiograms were combined for these two probes or for all three probes, including EAV, to calculate such correlations. To arrive at prediction equations, linear or multiple regressions were fitted to the data and goodness of fit was assessed by R_ values. Results All three DNA probes gave similar results with respect to numbers of bands and between 20 and 44 bands were available, per probe, for evaluation per each single cross of genetic groups while the total number of bands evaluated with one probe per each experiment ranged from 45 to 67. The total number of bands available for analysis in individual crosses from probing with all three probes ranged from 71 to 124. Based on data from all three experiments, average percent correlations between genetic distance expressed on the basis of BR and on the basis of MRD ranged between -65 and -78. All correlations between band sharing and MRD within each of the three experiments were highly significant. The correlation coefficients indicated the change introduced into the expression of genetic distance by considering the optical density of bands in the calculation MRD as opposed to the consideration of presence or absence of the band in the BR. In subsequent analyses of relationships between genetic distances and heterosis,

65

the correlations of MRD with heterosis were generally lower than those between heterosis and BR. Therefore, in the remainder of this communication only data from BR, as an expression of genetic distance, will be shown. Usefulness of individual DNA probes might be assumed to increase if each probe marks different regions of DNA. Correlations between sharing of bands by individual pairs of parental groups that resulted from probing with different probes is indicative of such a relationship. In Leghorns, the two minisatellite probes, YNZ and M13, appeared to detect similar DNA fragments or fragments in similar DNA locations while fragments detected by probe EAV seemed to differ from the preceding two (Table 2). Surprisingly, in meat chickens there was a greater similarity among the DNA fragments detected by all three DNA probes used. The overall egg production performance of birds in the two experiments evaluated in this study for the first production cycle (housing to 496 d) was comparable to their contemporary commercial stocks, particularly since both parental stocks and their crosses were included (Table 3). The second production cycle data (546-797 d) cover a period of over 8 months and indicate the usual decrease in egg production rate with increased egg and body weight. Similar to egg production data, the broiler performance needs to be viewed while keeping in mind that both selected strains and control strains of meat-type chickens were included in the experiment. The coefficients of Variation for heterosis were generally high, particularly in traits where the size of heterosis was small (egg weight, egg specific gravity, Haugh units, and blood spots). Correlation coefficients between genetic distance of the parental populations, expressed as band sharing, and the size of heterosis were generally low and inconsistent for the above-mentioned egg productionrelated traits in which the average size of heterosis was small. Therefore, only data from traits in which a sizable heterosis was observed are shown in Table 4 for probes YNZ and MI3 combined and for all three probes combined. For both the first and second egg production cycles the M13 probe resulted in highest correlations, followed by the YNZ probe. In most instances, the predictability of heterosis was improved when data from the autoradiograms produced by the two probes were combined. In some instances, the combination of probes YNZ and M13 provided a better prediction of heterosis than the use of data from all three probes combined. In the first egg production cycle, the highest correlation between band sharing and heterosis was found in age-at-first-egg, followed by mature body weight, hen-housed egg production and egg production rate. Similarly, in the second production cycle, heterosis was best predicted for the onset of egg production after forced moult, followed by hen-housed egg production, egg production rate, and •body weight. For broiler traits, only 13 estimates of heterosis were available. Average heterosis was generally low and highly variable (Table 3). The M13 probe (not shown) again provided better estimates, some of which reached the 10% significance level. The EAV probe provided generally better correlations with heterosis in broiler performance than with heterosis in egg production performance. To obtain prediction equations for heterosis, both linear and multiple regressions using the band sharing and their transformed values were tested. For age-at-first-egg, hen-housed egg production in the first 66

production cycle and mature body weight in which we observed the highest correlations between heterosis and band sharing, the highest proportions of variation in heterosis explained by the regressions (R2) were obtained from quadratic regressions. The best prediction of heterosis for age-at-first-egg was obtained from the quadratic regression using band sharing based on the YNZ and M13 probes. For mature body weight, the highest proportion of variation in heterosis was explained by the same type of regression using band sharing based on all three probes combined. In both of these instances, a substantial improvement of predictability was obtained from inclusion of both the band sharing and its square in the regression. The relationship between heterosis in hen-housed egg production and band sharing tended to be more linear and only a negligible improvement was obtained from the quadratic, compared to linear, regression. For this trait, the prediction by the quadratic regression based on band sharing from all three DNA probes was substantially better than that using only the YNZ and M13 probes. Discussion A disadvantage of the retrospective analysis performed within this study was the time period between the crossbreeding experiments and sampling of the parental stocks to assess their genetic distances. This delay was particularly large in the case of the 1977 study (Table 1) where the blood samples for DNA extractions were taken only in 1989. Over the last eight generations included in this time period the selected strains tested in 1977 were reproduced by random breeding without selection. It is likely that many linkage disequilibria created by the selection had returned to an equilibrium by the time the samples were taken. The situation was less problematic wi_ the 1987 experiment (Table 1) in which both the selected and control strains used were under several generations of random breeding without selection prior to the crossbreeding experiment. For inbred lines that were also part of that experiment, mild inbreeding (half-sib matings) was practised before the crossbreeding experiment and in the period between the experiment and the blood sampling. Because of the above-mentioned reasons, results of this study haveto be considered preliminary. Further experimental verification of predictabilityof heterosis from DNA fingerprints is required before routine use of this method by the breeding industry is recommended. Based on the results of this preliminary study, it appears that pooling of DNA samples from parental stocks, candidates for crossbreeding, is feasible for assessment of heterosis. A simple expression of band sharing between parental stocks was a better predictor of heterosis than the more complicated measure, Modified Rogers Distance. This observation indicated that the optical density of individual bands on autoradiograms does not reflect the frequency of the various DNA fragments in the population. There are several factors that may influence optical density. Optical density depends on homology between the DNA probe used and the DNA fragment detected. Also, it is well known that sequences within the motifs of tandem repeats could be quite variable and, therefore, may have varied homology with the probe. Such variability in the sequences would be expected to be more pronounced in the minisatellite DNA fragments than in the EAV elements. Furthermore, optical density is not necessarily directly proportional to the amount of the DNA fragment detected on the band. Another source of errors may be that DFP bands detected by the individual probes, particularly the minisatellite probes YNZ and M13, are identified only by their size. Therefore, within a band there may be fragments from more than one location within the genome. Finally, with regards to MRD, the arbitrary setting of

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the darkest band within a group of bands equidistant from origin to 1 we may have introduced an additional bias into the data. The results of this study indicated that different DNA probes may have varying predictive values for heterosis. For example, the EAV probe predicted heterosis better in broiler traits than in egg production traits. However, no clearly discernable differences were detected in the suitability of the three probes used for prediction of heterosis in individual traits. For future work on prediction of heterosis from DNA fingerprints it seems advisable to use multiple probes and, as information becomes available in the future, to include also single locus probes detecting important quantitative trait loci or their DNA markers in the analysis. The use of such single locus probes can be expected to simplify the interpretation of the DNA data. With such probes the complexity of the DNA data will be reduced but heterosis would be predicted at a much greater cost than with the multi-locus probes. As expected, heterosis was better predicted for traits such as hen-housed egg production, with average heterosis approximately 20 %, age-at-first-egg, egg production rate, and mature body weight with heterosis around 10% of mean performance than in low heter0sis traits such as egg weight where average heterosis is only 2% of the mean. Predictability of traits with heterosis of 1% or less of the mean, such as egg quality, or broiler traits, was much lower or negligible, compared with traits exhibiting higher heterosis. The three DNA probes used in this study provided between 71 and 124 bands per cross for evaluation. Assuming the size of the chicken genome of 1 billion bp and an equidistant distribution of the marker fragments, the average distance between markers--bands was between 8 and 14 million bp. Considering this distance, which in many instances is likely increased by clustering of the markers, and taking into consideration the weaknesses associated with the retrospective nature of the analysis in this study, the predictability results can be considered encouraging. As availability of suitable probes, QTL genes and markers increases with the progress of analysis and mapping of the chicken genome, it is likely that heterosis would become more predictable in the future.

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Table 1 CROSSBREEDING EXPERIMENTS

Year of Hatch Blood Sampling

Production types

Genetic group types

1977

1989a

Leghorns

Selected

6

15

1987

1990b

Control, Selected, and Inbred

10

14

8

13

1990

1990

- Leghorn & Meat

Meat

Control, and Selected

Total number of Parental Crosses groups evaluated °

aSelection terminated 1980, random bred since bRandom bred since 1987 CReciprocal for 1977 and 1987 data, reciprocal or one-way for 1990 data

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Table 2 SIMILARITY

OF DNA REGIONS

DETECTED BY VARIOUS PROBES: CORRELATIONSBETWEEN BAND SHARING BASED ON THE INDIVIDUAL

DNA PROBES

Correlation Types of birds

Probes

(%)

Leghorns

YNZ-M 13 YNZ-EAV M13-EAV

55" * 16 15

Meat birds

YNZ-M13 YNZ-EAV

77** 82**

M13-EAV

87**

**P_
7O

Table 3 OVERALL MEANS OF PRODUCTION EGG PRODUCTION

TRAITS

PERFORMANCE

Leghorn Crosses Trait

1st Year

2nd Year

(1977 and 1987 data) performance heterosis

(1977 data only) performance heterosis

Age at first egg (d) Hen-housed egg production

148 262

-17 +45

143

+23

Egg production rate (%)

74.5

+ 8.5

59.8

+ 7.0

Egg weight (g)

57

+ 1.9

67 (690 d)

+ 5.5

Body weight (kg)

1.88

+

.18

2.13 (725 d)

BROILER PERFORMANCE

Trait

1990 Meat Chickens performance

heterosis

Body weight at 27 days (g)

883

+5

Body weight at 46 days (g)

1,968

+5

Dressing percentage Abdominal fat percentage

67.3 3.2

71

+ .04 + .02

+

.06

Table 4 CORRELATIONS

(%) OF HETEROSIS WITH GENETIC DISTANCE (BAND SHARING) BETWEEN PARENTAL POPULATIONS

DNA PROBES Trait

YNZ + M13

ALL

63**

60**

- hen-housed egg production - egg production rate

-57** -46*

-56** -47*

- mature body weight

-58**

-62**

- onset of egg production after molt

-58*

-61"

- hen-housed egg production

-52*

-38

- egg production rate

-41

-26

- body weight

-34

-37

- 27 d body weight

-27

-35

- 46 d body weight

-37

-40

- carcass weight

-42

-44

- fat weight

-49 °

-42

- fat %

-50 °

-41

- dressing %

-34

-34

COMB.

.Leghorns - first production year (N = 25) - age-at-first-egg

Leghorns - second production year (N = 15)

Broilers (N = 13)

** P-<.O1 * P-<.05 ° P-<.IO

72

Bibliography

1.

Benkel, B., J. Mucha, and J. S. Gavora. 1992. A new diagnostic method for the detection of endogenous Rous-associated virus-type provirus in chickens. Poult. Sci. 71: 1520-1526.

2.

Charcosset, A., M. Lefort-Buson, and A. Gallais. 1991. Relationship between heterosis and heterozygosisty at marker loci: a theoretical Computation. Theor. Appl. Genet. 81: 571-575.

3. Dunnington, E. A., O. Gal, P. B. Siegel, A. Haberfeld, A. Cahaner, U. Lavi, Y. Plotsky, and J. Hillel. 1991. Deoxyribonucleic acid fingerprint comparisons btween selected populations of chickens. Poult. Sci. 70: 463-467. 4. Fairfull, R. W. 1982. Combining ability, heterosis and reciprocal effects for first and second year performance in six selected Leghorn strains in a complete diallel . Proceedings 31st Anual Narional Breeders' Rundtable, St. Louis, MO 5. Fairfull, R. W., R. S. Gowe, and J. A. B. Emsley. 1983. Diallel cross of six long-term selected leghorn strains with emphasis on heterosis and reciprocal effects. Brit. Poult. Sci. 24: 133-158. 6. Fischer, H. D., J. B. Dodgson, S. Hughes, and J. D. Engel. 1984. An unusual 5' splice sequence is efficiently utilized in vivo. Proc. Natl. Acad. Sci. USA 81: 2733-2737. 7. Haberfeld, A., E. A. Dunnington, and P. B. Siegel. 1992. Genetic distances estimated from DNA fingerprints in crosses of White Plymouth Rock chickens. Anim. Genet. 23: 167-173. 8. Hillel, J., E. A. Dunnington, A. Habrfeld, U. Lavi, A. Cahaner, O. Gal, Y. Plotsky, H. L. Marks, and P. B. Siegel. 1993. Multilocus DNA markers: Application in poultry breeding and genetic analyses. Manipulation of the avian genome, Etches, R. J., Gibbins, A. M. V. ed 243-256. CRC Press. 9.

Kuhnlein, U., Y. Dawe, D. Zadworny, and J. S. Gavora. 1989. DNA fingerprinting: A tool for determining genetic distances between strains of poultry. Theor. Appl. Genet. 77: 669-672.

10. Kuhnlein, U., D. Zadworny, Y. Dawe, R. W. Fairfull, and J. S. Gavora. 1990. Assessment of inbreeding by DNA fingerprinting: Development of a calibration curve using defined strains of chickens. Theor. Appl. Genet. 125: 161-165. 11. Lee, M., E. B. Godshalk, K. R. Lamkey, and W. W. Woodman. 1989. Association of restriction fragment length polymorphisms among maize inbreds with agronomic performance of their crosses. Crop Science 29: 1067-1071. 12. Maniatis, T., E. F. Fritsch, and E. Sambrook. 1982. Molecular cloning. Cold Spring Harbour Laboratory, Cold Spring Harbour, New York.

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13. Nakamura, Y., M. Leppert, P. O'Connell, R. Wolff, T. Holm, M. Culver, C. Martin, E. Fujimoto, M. Hoff, E. Kumlin, and R. White. 1987. Variable number tandem repeat (VNTR) markers for human gene mapping. Science 235: 1616-1622. 14. Vassart, A., M. Georges, R. Monsieur, H. Brocas, A. S. Lequarre, and D. Christophe. 1987. Sequence in M13 phage detects hypervariable minisatelites in human and animal DNA. Science 235: 683-684.

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Questions

Question genomic each of heterosis?

(Dr. I.Levin): distribution the multilocus

of

to

Dr.

Jan

Gavora

How could linkage analysis and the polymorphic bands generated probes improve the prediction of

by

Answer: The hypothetical model presented in my talk assumes that the polymorphic fragments of DNA detected by DNA fingerprints may be located near quantitative trait loci and thus serve as DNA markers for such loci in the prediction of heterosis. In the study, the predictive value of DNA fingerprints was only evaluated globally, on the basis of correlations of band sharing between two parental populations and the heterosis in their progeny. The contribution of individual bands on the fingerprints to the prediction of heterosis was not analyzed. Such analysis may be attempted at a later stage of the study.

Question (Dr. Jim Arthur): Since minisatelite genetic sequences which occur in portions of which contain few functional genes, does this usefulness as markers?

sequences are the genome affect their

Answer: It would seem likely that the location of the minisatelite fragments of DNA affects their predictive value for heterosis. From what is known about minisatelites, their location would not appear favorable for this purpose. However, the data presented show good predictability. The endogenous avian viral elements that were also used to produce DNA fingerprints in the study may be more evenly distributed throughout the genome and could, therefore, be expected to be of more value in predicting heterosis than the minisatelite DNA fragments. Nevertheless, as was shown in my presentation, at least one of the minisatelites DNA probes, M 13 exceeded in its predictive value the probe detecting endogenous avian viral elements.

Question (Dr. C.M. Turk): There are the environment. Would selection for possibly select away from resistance

multiple any one to another

pathogens pathogen pathogen?

in

Answer: The question reduces to the size and sign of genetic correlations between resistance to various diseases. Generally, there is not much known about such correlations and their estimation was only seldom, if at all attempted. From our unpublished work in which we used 23 genetic groups of chickens, produced from them consecutive hatches of populations and exposed each population to a different pathogen, it seems that no severe negative correlation 75

t

between apparent,

the at

resistance least at

to the

the diseases strain mean

we tested basis.

were

It is believed that for each disease, there is one aspect of immune response that is most important for resistance. Research by the Biozzi group in laboratory mice and that by Gross and Siegel in chickens points out that selection for high immune response in one type of immune mechanisms may be favorable for resistance to one disease and unfavorable for others.

Question (Dr. M.K. Akbar)" If some level of disease resistance is established in a commercial company at the pure line level, is this resistance expected to be carried out through the GGP, GP and parent generations and in the commercial birds? And if so, what would be the level of it compared to what was established at the pure line level? AnswerIt is verydifficult, if now impossible, to provide a generally valid answer to this question. The transmission of disease resistance from primary breeding lines to great grandparent, grandparent, parent, and commercial hybrid stock would depend on the genetic basis of resistance mechanisms. To a degree that resistance to diseases is inherited, it would be expected to be carried from generation to generation. Generally, heritability of resistance to total mortality is considered low. However, h2 values are usually higher for resistance to specific diseases. In most instances, genetic resistance to infectious diseases behaves as a quantitative character and exhibits, to a substantial degree, additive genetic variation. As a rule, resistance selection is practiced in experimental and also commercial populations primarily within purebred lines and is well transmitted to progeny,

Question (Dr. John Gibson): Given that heterosis is estimated, not know without error, even if the correlation between band sharing and heterosis was -1.0, the expected correlation between band sharing and estimated heterosis would be considerably less than -1.0. It would be interesting to know what is the expected value for your correlations. Answer: We calculated the standard errors heterosis for the traits examined but did errors in heterosis estimation would affect values of the correlations.

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of the means Of not evaluate how the expected