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Genetic improvement in layer chickens vis a vis genetic variability and future prospects

Gurvinder Singh Brah
Department of Animal Breeding & Genetics
Punjab Agricultural university, Ludhiana - 141004
Email: [email protected]

Introduction

Genetic improvement of livestock depends on access to genetic variation and effective methods for exploiting this variation. Genetic diversity constitutes a buffer against changes in the environment and is a key in selection and breeding for adaptability and production on a range of environments. Commercial chickens available in much of the world are produced by a relatively small number of breeding organizations. This structure has been effective during the last 50 years in providing superior stocks. However the extent to which domestication and subsequent selection for particular traits of economic importance have reduced genetic variability in commercial poultry is not known. In this paper an overview of the genetic changes achieved in layer chickens is made, the current status of genetic diversity is examined and the potentialities of the new technologies evaluated.

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General Breeding Goals 

All breeding plans for commercial breeding companies have one major objective in common: to increase the genetic potential of the stock to produce a maximum of saleable, high quality products at minimum cost in a given production system. Breeders of egg-type chickens concentrate on four major objectives:

  • Low mortality and high adaptability to different environments
  • maximum number of saleable eggs per hen housed
  • low feed cost per egg or per kg egg mass
  • optimal external and internal egg quality

Rates of Genetic Progress

A number of selection experiments in layer chickens conducted in experimental population s maintained in public sector institutions through the world have reported continued genetic progress .However , historical data of German random sample tests as given in tables 1 provide insight into the genetic gains attained for one commercial stock , the Lohmann LSL .

Table 1: Historical trend for Lohmann LSL layers in German random sample tests

Years ending Egg mass (kg/Hen housed) Body Weight (kg) FCR (kg/kg) IOFC* DM

1980 – 82

17.70

1.94

2.46

10.90

1983 – 85

18.50

1.87

2.39

11.91

1986 – 88

18.67

1.83

2.35

12.32

1989 – 91

18.80

1.88

2.32

12.63

1992 – 94

19.77

1.96

2.25

13.84

1995 – 97

19.93

1.80

2.10

15.15

* Egg income over feed cost: 1.60 * EM – 0.40 * EM * FCR

Apparently the egg mass output has been improved by more than 2 kg within 15 years, with no major changes in body weight but a significant improvement in feed efficiency. Income over feed cost has been improved by about 4DM per hen if constant feed and egg prices are assumed.

Methods to measure genetic trends are an essential part of animal improvement schemes. Several methods can be used, such as comparison with control lines, overlapping use of sires in the population over time and repeated matings of the same sires and dams. Such estimates may be biased and are only useful for internal purposes to predict genetic changes per trait in each line. On an individual farm, genetic and environmental effects can usually not be separated. The most commonly used basis for strain comparisons are random sample tests, from which data from several years can be used to calculate rates of progress for different strain crosses. The estimates per strain are not free of environmental trends, but the differences between strains in rate of progress are mainly genetic. Data from five German random sample testing stations have been used to estimate changes in egg production and feed efficiency over11 years. Trends are calculated as pooled linear regressions for five white-egg and five brown-egg strains over the 11-year period 1984/85 to 1994/95 (Hartmann and Heil, 1985; Heil and Hartmann, 1995), using a linear model including strains, stations and years. Table 2 shows the strain means and the average regression coefficients (per10 years) for the white- and brown-egg layers.

Table 2: Means of five brown-egg and five white-egg strains and linear changes in German random sample tests 1984/85 - 1994/95

White egg strains

Mort. %

Egg No. HH

Egg Wt. g

Egg Mass Kg/HH

Feed g/d

FCR kg/kg

Body wt. g

IOFC**

DM

Lohmann

3.8

304

63.1

19.19

120

2.29

1896

13.13

Hisex

5.2

298

62.3

18.60

118

2.31

1839

12.57

Dekalb

3.7

299

61.3

18.29

115

2.30

1879

12.44

Shaver

3 .8

294

62.6

18.42

118

2.34

1944

12.23

Babcock

3.8

290

61.4

17.81

113

2.32

1853

11.97

Average

4.0

299

62.5

18.69

117

2.30

1882

12.55

1/ 10 years

+ 0.6

+14

+ 2.5

+1.70

– 2

–.2 4

– 10

+ 3.62


Brown egg strains

Mort. %

Egg No.

HH

Egg Wt. g

Egg Mass Kg/HH

Feed g/d

FCR kg/kg

Body wt. g

IOFC**

DM

ISA

5.4

296

65.2

19.33

121

2.30

2180

13.14

Lohmann

5.6

296

65.4

19.33

121

2.30

2217

13.14

Hisex

5.1

291

65.6

19.11

123

2.35

2281

12.61

Tetra

4.9

292

65.1

19.03

124

2.38

2272

12.33

Dekalb

5.1

290

64.1

18.59

124

2.44

2292

11.60

Average

5.2

295

65.0

19.17

122

2.33

2219

12.59

1/ 10 years

+ 3.2

+11

+1.2

+1.11

– 8

– .28

– 280

+3.11

* White-egg strains 309 entries, brown-egg strains 368 entries in total

** Egg income over feed cost: 1.60 * EM – 0.40 * EM * FCR

During this 11-year period, the white-egg strains have made more progress in egg output and the brown-egg strains have improved more 0.24 in feed efficiency. Progress in egg mass and feed efficiency during the decade from 1985 to 1995 was lower than during the previous decade. This may be due mainly to decreasing response as stocks approach physiological limits (1 egg in a 24-hour day). Egg weight cannot be increased beyond market needs. Most breeders have also increased their selection pressure for traits such as shell strength and shell colour in brown-egg strains, which would account for slower progress in egg mass and feed efficiency but a higher percentage of marketable eggs. The increase in mortality can be attributed to ‘animal welfare’: most stations are no longer beak trimming and experience more cannibalism, especially in brown-egg strains.

Genetic Diversity in Layer Chickens

It is widely accepted that all populations of domesticated chickens descend from a single ancestor, the Red Jungle Fowl (RJF) (Gallus gallus), originating in Southeast Asia. Although it has been claimed that other wild species of Gallus might have contributed to the domesticated chicken, the more widely accepted view is that Gallus gallus gallus alone is sufficient to account for the maternal ancestry of the domesticated chicken. At the present time, the improved Mediterranean type populations are the most closely related to the RJF, which were the first chickens brought into Europe. Much later, with the massive use of selection and crossbreeding, local breeds and lines in different parts of Europe were developed, and Asian breeds of the Chinese and Malay types were introduced. All of these sources contributed to the modern biodiversity of chicken populations. Inter-crossing, however, may have partly extinguished differences among groups or breeds, with the result that genetic relationships between chicken populations are not always definitive. Furthermore, only some of these sources were used to develop the populations which currently dominate the world's poultry industry. Since the start of commercial poultry breeding in the middle of the 20th century, chicken genetic diversity has become partitioned among relatively few highly specialized lines. As a consequence, many dual-purpose breeds, resulting from centuries of domestication and breeding, are now at the risk of being lost. These breeds may, however, represent a resource of genes for future breeding and research purposes. Therefore, it is necessary to assess the diversity at the molecular level in a wide range of chicken populations, including commercial lines, traditional breeds, experimental lines and the red jungle fowl, in order to provide recommendations regarding future management. Molecular markers may serve as an important initial guide foe assessment of the genetic diversity. Recent advances in molecular technology have provided new opportunities to assess genetic variability at the DNA level. I will discuss the two most documented studies on assessing the genetic variability using molecular genetic techniques.

European Collaborative Study

The results of the AVIANDIV EC-funded research project is one of the most authentic study of genetic diversity in which the gene-pool of 52 chicken populations from a wide range of origins to represent as many European countries as possible and to cover a wide range of populations differing by selection history and current management has been examined. This study used microsattelite based criterion foe examining the genetic variability. Micro satellites are widely used since they are numerous, randomly distributed in the genome, highly polymorphic, and show co-dominant inheritance. Many micro satellites have recently become available in chickens, and have been mapped in reference populations. These markers provide a powerful tool for QTL research, and have also been successfully used to study the genetic relationship between and within chicken populations.

Genotyping at micro satellite loci: A set of 22 (CA) n di-nucleotide micro satellite markers, which are as uniformly distributed as possible throughout the chicken genome, was tested for their use in DNA pools. Three genetic distances based on allele frequencies were used: the Nei genetic distance, Cavalli-Sforza chord measure and Reynolds genetic distance. Additionally, the delta-mu-squared distance, based on allele size, was applied. Pair wise distances between each pair of the 52 populations (1326 estimates) were calculated for each measure. A total of 3760 allele frequencies were obtained. Amongst the 1144 possible typings (22 markers_52 populations), 77 (6.7%) were missing due to technical difficulties, mainly for three loci: ADL278, MCW14, and MCW330, with missing data on 27, 15, and 15 populations, respectively. For the remaining 19 markers, only 20 (2.0%) genotyping data points were missing.

Polymorphism of markers: All 22 markers were polymorphic in at least 69% of the populations, and 91% of the populations were polymorphic. The mean number of alleles was 9.6 across populations and 3.5 within populations, and average gene diversity was 0.47. Among the 22 tested markers, the most polymorphic was MCW34 with 16 alleles across populations and, on average, 6.5 alleles per population. The gene diversity of MCW34 was 0.68 and 98% of the populations were polymorphic for this marker. At the other extreme, marker MCW98 was the least polymorphic, with four alleles across populations, 1.8 alleles per population, and a gene diversity of 0.29; in addition it was polymorphic in 69% of the populations.

Diversity of populations: Average gene diversity (H) within the 52 populations across all 22 loci was 0.47 and the average number of alleles was 3.5. The least polymorphic population was the inbred _C line_, with a gene diversity (H) of 0.05 and 1.3 alleles per locus across all markers. The next to lowest was Padovana, a fancy breed with a narrow base in Northern Italy, with H D 0:17, and 1.8 alleles. The most polymorphic population was the Gallus gallus spadiceus, with H D 0:64 and an average of 5.2 alleles, followed by the population of Yurlov Crower in Russia, with H D 0:62 and 4.8 alleles. Within these extreme populations, there was variation across marker loci. In the inbred C line, the polymorphism ranged from H D 0:39 and two alleles for marker ADL268 to H D 0 at 15 of the remaining loci. Similarly, in Gallus gallus spadiceus, polymorphism varied between H D 0:88 and 11 alleles (MCW69), to H D 0:20 and 2 alleles (MCW222).

Population-specific (private) alleles: In total, 213 different alleles were scored across the 52 populations and the 22 marker loci. Most of these alleles (181) were found in more than one population. For the 52 populations, the 32 private alleles are indicated. The majority of the populations had either no private alleles (33 populations) or a single one (14 populations) and only one population, the Yurlov crower (in Russia) had eight private alleles. The RJF subspecies: Gallus gallus gallus and Gallus gallus spadiceus with two and three private alleles respectively are worth mentioning. Taken together, the 50 domesticated populations had 91 alleles which are missing in the two RJF populations. In turn, RJF had eight private alleles which were absent in the domesticated gene pool. Among the 32 private alleles, only 14 had frequencies higher than 10%.

Diversity between and within types of populations The following points are of significance: types 1 (wild type) and 2 (unselected breeds) were the most polymorphic populations (H D 0:62 and 0.56, and number of alleles per locus, na, are 4.8 and 4.1 respectively). Type 6 (inbred) was the least polymorphic (H D 0:05 and na D 1:3). On average, layers (type 4; H D 0:45 and na D 3:4) were slightly less polymorphic than broilers (type 5; H D 0:57 and na D 3:6). Among layers, Brown-egg & (')'+*_')*_,.-_*_/0')1_2_3_,layers were the most polymorphic, while White Leghorn breeds (sub-types 4.3 and 4.10) were less polymorphic than non-Leghorn white-egg layer breeds. In recent years, breeders of commercial white-egg layers have been concerned about reduced genetic variability and future response to selection. The results reported in the present article support this concern, particularly for White Leghorn breeds. The massive merging of breeding companies in recent years should call for attention to the need for conservation of genetic variation among breeds and lines. Appropriate strategies for conservation of populations is out of the scope of the present report but is an important and controversial issue.

American Study

Another study conducted at VPI in USA assessed the level of genetic diversity in elite pure lines of commercial broilers and layers along with a control and wild progenitor populations using DNA finger prints (DFA, Jeffery’s). A summary of the sources, lines, probes, blots and bands in this study is given below:

Sources : Parental lines of White egg layers of four sources
Number of lines : 16
Control : Athens random bred and Jungle fowl
Probes : 33.6
Number of blots : 3
Mean no. of DNA fingerprint bands : 34

Of the 120 comparisons among Leghorn lines , band sharing exceeded 30% in 30 cases with 8 above 40% and 2 above 50%.Mean levels of band sharing of Jungle fowl with layer lines was 7 whereas the corresponding value with the control was 15 thus reflecting greater similarity of the commercial lines with the control than with the jungle fowl .

Newer Biotechnological Approaches to Genetic Improvement

Biotechnology can be defined as any technique that uses living organisms or substances from such organisms to make or modify a product, to improve plants or animals or to develop micro-organisms for specific purposes. Biotechnology is not new. Man has used it for thousands of years to manufacture products such as beer, wine and bread. Conventional plant and animal breeding which involves selection and mating of phenotypically preferred individuals is a good example of age-old application of biotechnology. What is new about biotechnology comes from more recent breakthroughs such as recombinant DNA technology and associated techniques, monoclonal antibody techniques, embryo manipulation technology etc. These have enhanced possibilities for manipulating biological systems for the benefit of mankind. Of the various aspects molecular markers (or genes) have potential utility in poultry breeding. Markers have many important and useful applications in poultry improvement. DNA-based technologies like DNA fingerprints (DFP) are powerful tools for identification and pedigree determination viz; preventing or correcting pedigree errors; recovering pedigrees; retrospective genetic analysis. In the study of inbreeding, genetic drift or mutation, DNA-based methods provide an unparalleled tool to follow changes at the DNA level .

Heterosis is substantial for most commercial traits in chickens. Almost all commercial male and female parent lines and virtually all commercial broilers or layers are crosses. There could be a substantial advantage to predicting the heterosis expected from crosses at all levels. Preliminary results in laying hens show promise for the prediction of heterosis using DNA fingerprint information. Occasionally, genes must quickly and economically be introduced into poultry populations (introgression). Undesirable genes in the donor genome must be excluded as far as possible. Theoretically, DNA-based markers can enhance the efficiency of introgression). Ideal introgression would employ equally spaced markers in the host genome and tightly linked flanking markers for the donor gene. The gene of interest could then be introgressed with the highest recovery of the host genome. However, suitable markers must be found and unless database with suitable cloned DNA, this may be no trivial problem. They can be located in a Marker assissed selection. Use of MAS in any form requires linkage disequilibrium, either at the family or population level. In the case of a randomly mating population, different individuals will tend to be in equilibrium with QTL alleles segregating in proportion to the relative frequencies of the alleles. Alternative marker genotypes will include both positive and negative alleles at any linked QTL, and the mean quantitative value of the alternate marker genotypes will not differ even when a linked segregating QTL is present in the population. Therefore, specific linkage arrangements must be determined for each individual by progeny testing numerous offspring. Theoretically, generalized mixed model (BLUP) approaches for incorporating markers into breeding programs reduce the erosion of marker information from one generation to the next and maximizes expected response of MAS, but require abundant QTL’s with large effects to be effective assuming all alleles are traceable. However, finding loci with large effects in a population which has undergone long term selection would be unexpected unless the gene has a negative plieotropic effect on fitness.

Evaluating expression of QTL’s in different dams, Dunnington et al. (1993) concluded that associations between DFP band patterns and quantitative traits may not be consistent in different genetic backgrounds Fairfull et al. (1987) found that epistatic effects (AXA, AXD, and DxD) were significant for egg production traits. All of this suggests problems in the application of MAS. In an economic study of MAS, De Gatori and Muir (unpublished) using the efficiencies of Zhang and Smith (1993) and costs from Beckmann and Soiler (1983) with an assumed 100 fold decrease due to technology advances by 1994, concluded that in most realistic animal breeding operations use of MAS will not be profitable. Zhang and Smith (1993) concluded that MAS will have limited value until close linkages or the QTL’s themselves are identified From numerous other theoretical evaluations of MAS and the results discussed above, it can be generally concluded that MAS will only be advantageous for traits which cannot be measured on the individual and in species which allow for large family sizes. Thus, MAS appears to be of little importance in genetic improvement of poultry. To date, MAS has not been used or tested on a wide scale. The only reported attempt to actually use MAS was that of Dunnington et al. (1992) who used within family MAS by tail analysis. Birds were bi-directionally selected based on two markers which had a significant effect on body weight. Offspring of those matings were not significantly merent. The authors attributed the lack of response on BW to false positives. Nevertheless, the authors examined the most favorable case for MAS, i.e. intermediate gene frequencies for the QTLs by crossing bidirectionally selected populations, and it failed. All theoretical studies of MAS assume an existing gene pool. MAS only changes frequencies of existing alleles (Tank&y 1997). A more beneficial use of this technology is to search for alleles in wild ancestors of domesticated species which have become lost. In every instance where this was used new alleles that outperformed the elite parents by as much as 20% were found. Thus, the real value of MAS in most species may be to look for lost alleles in distant ancestors (Muir 1994) Marker assisted selection is already part of commercial breeding programmes. In the past blood typing has been used to improve specific disease resistance. For example Marek’s resistance and general livability have been improved by eliminating birds with blood groups which are known to be a marker for high susceptibility to diseases. These breeding efforts have been accompanied by eradication of vertically transmitted diseases from pure-line populations. Today a lot of money is spent in searching for DNA based markers, mainly anonymous micro satellites, which are linked to traits of economic interest. Special matings and testing schemes have to be set up to search successfully for markers. If in one population a marker for an important trait has been found there is no guarantee that this marker can be used in other lines or products. Based on the assumption that most of the important traits are determined by a very large number of genes or loci, a single marker can only determine a small part of the genetic variation for a trait in a given population.

Based on preliminary results from the collaboration with different research institutes in Europe there is a high probability that classical selection can be improved and rate of progress enhanced by using DNA-based micro satellite markers for selection. In particular, selection between full sib males can give a major improvement because, at the time of selection, only parental breeding values and pure line and cross line sister information is available. As the performance test is sex-limited, all full sib males have the same breeding values for economically important traits. If markers are available, the best male out of a set of full-brothers can be selected for reproduction to generate the next generation. With lower rate of inbreeding more genetic progress can be achieved if only the best male from each full-sib family is used for reproduction. In figure 3 different steps of an enhanced breeding programme using marker assisted selection or even gene transfers are demonstrated.

Conclusions

  • After more than 40 years of intensive selection, the available pure-lines still show enough variation for further improvements. Accuracy and efficiency of data recording can be further improved by electronic equipment. More sophisticated statistical procedures will help to extract a maximum of information from pure-line and cross-line data from different environments. The highly integrated commercial poultry industry is dependent on a small number of organizations that control a large proportion of breeding stock through the world. The studies so far reported indicate that a considerable reservoir of genetic diversity exists. A factor that may have been responsible in maintaining such levels of diversity is that exceptionally large numbers of individuals are produced commercially throughout the world.
  • Continuous selection will be enhanced by using micro satellite markers and expressed sequence tags to estimate genetic merit at the DNA level. But the traditional quantitative genetic approaches will continue to occupy the central stage.
Source : IPSACON-2005