Chemistry: molecular biology and microbiology – Measuring or testing process involving enzymes or... – Involving nucleic acid
Reexamination Certificate
1999-08-25
2002-08-27
Jones, W. Gary (Department: 1655)
Chemistry: molecular biology and microbiology
Measuring or testing process involving enzymes or...
Involving nucleic acid
C435S005000, C435S091100, C435S091200, C435S440000, C435S455000, C435S349000, C536S024310, C536S023100, C514S04400A, C800S022000
Reexamination Certificate
active
06440666
ABSTRACT:
BACKGROUND OF THE INVENTION
The present invention relates to the field of agriculture, in particular to animal breeding, more specifically to the breeding of poultry. In breeding poultry selection of animals to breed with is a very important aspect. Traditional selection methods have been applied for centuries.It is therefore quite difficult to improve breeding stocks of poultry in important phenotypic characteristics using traditional selection methods.
Modern biotechnology has provided a number of novel tools for localizing traits on the genetic level, together with means of detecting the different alleles of such traits and thus providing the ability to select animals having the right allele. One of the novel ways of identifying a gene related to a useful trait involves so-called microsatellite markers.
Microsatellites are direct repeats of di, tri or tetra nucleotides such as (TG)
n
, (TA)
n
(CAC)
n
or (GGAT)
n
where n can vary from 4 to over 30. (Crooijmans et al, 1993). There repeating DNA elements are found almost randomly throughout the vertebrate genome. Their number, over 10
4
in a vertebrate genome, and their extreme polymorphism makes them useful for linkage analysis. It is possible to detect different alleles, resulting from variation in the number of repeats, by PCR using locus specific oligo-nucleotides. From 1993, different laboratories have been working on the construction of a chicken genetic map using these microsatellite markers.
This genetic map facilitates linking of Quantitative Trait Loci (QTLs), single gene traits and non-single gene traits, with microsatellite data in order to identify their chromosomal location(s) (Crooijmans et al., 1993; 1994; 1995; 1996a; Cheng and Crittenden, 1994; Burt et al., 1995).
Today, the chicken genetic map covers about 90% of the genome. In order to be useful for linkage studies, a genetic map should have a marker at every 20 centi Morgans (“cM”) of the linkage map, which is still approximately 1.10
7
basepair. Then a QTL will always be within ten percent recombination from a microsatellite marker, the maximum crossover percentage where usage of markers is still useful (Van der Beek and Van Arendonk, 1993).
In a recent study, Ruyter-Spira et al. (Poultry Science, in press) mapped the Dominant White locus in chicken using microsatellite markers. This gene was successfully mapped on linkage group 22 of the East Lansing International reference family near MCW188. This study proves that it is now possible to successfully map monogenic traits (i.e. the Dominant White trait) by means of a so-called total genome scan. For this purpose, microsatellite markers of high quality (many alleles, almost evenly spread performance of the PCR product) covering the major part of the chicken genome can be used.
Bulked Segregant Analysis in Combination with Microsatellite Markers
In a linkage study, a large number of animals from segregating populations have to be genotyped. When a cross is set up to study a single locus trait with a dominant or a recessive phenotype, it is possible to sample the DNA of the animals with the same phenotype. These two pools will only differ for the region that is closely linked to the phenotype on which the pools were selected, and they will be similar to all other non-linked regions. Therefore, the distribution of the different alleles of an informative marker will only show a difference between these two pools if the marker is closely linked to the gene causing the different phenotype. Identification of the chromosomal region of interest is possible when a microsatellite map covering the whole genome is available, because linkage between the gene of interest and the microsatellite marker(s) can be detected. Using this so-called bulked segregant analysis, it is possible to carry out a ‘total genome scan’ on pooled samples, which greatly reduces the amount of genotypings that have to be carried out. Today, over 600 chicken microsatellite markers are available, covering over 90% of the chicken genome. This makes it possible to make a selection of approximately 150 well-working markers that efficiently can be used for a total genome scan. In a recent experiment, Ruyter-Spira et al. (Poultry Science, in press) successfully mapped the Dominant White locus using pooled samples. A limited number of possibly linked microsatellite markers (4 out of 68 informative markers) was tested on individual samples, finally resulting in the identification of the chromosomal region of the gene. Thus pooling of DNA proved to greatly reduce the amount of PCRs and analyses to perform.
In the study of Ruyter-Spira et al., a dominant trait was successfully mapped on the chicken chromosome. However, many traits are not regulated by single genes. When segregating populations for complex traits are available, it would be theoretically possible to identify the chromosomal regions of interest using a bulked segregant approach. Puel et al. (1995) used mouse microsatellite markers to identify chromosomal regions endowed with antibody production in Biozzi mice, mice selected for High and Low antibody responses to Sheep Red Blood Cells. They carried out a total genome scan using 90 polymorphic microsatellite markers on 60 individual F
2
animals, selected for their extreme phenotype from a total F
2
population of 240 animals.
However, though it may be possible to localize dominant traits which can be attributed to a single gene to a region of a chromosome, or even regions where different parts of complex traits may be found, it is by no means clear that every complex trait can be localized using this approach, nor that for instance recessive traits can be localized using microsatellite markers. Moreover, even though a trait has been localized to the extent that it has been found associated with some microsatellite markers, this in no way means that a responsible gene for the trait has been identified. Usually the distance between two microsatellite markers is still in the order of about 400-600 Kb, which is much larger than any usual gene sequence. Furthermore, when contemplating how to localize the regions on one or more chromosomes associated with a certain phenotype, one does not know whether this will be a single gene trait or a complex one.
The present invention in one embodiment provides the localization of a trait on a chicken chromosome, as well as a gene associated with said trait.
The trait to which the present invention relates is so called autosomal dwarfism. Hereunder a short introduction into dwarfism in chicken is presented for explanatory purposes.
Crawford (1990) lists three sex-linked forms and one autosomal form of dwarfism in chicken: dominant sex-linked dwarfism (Z), recessive sex-linked dwarfism (rg), sex-linked dwarfism (dw) and autosomal dwarfism (adw). Of the first three, the sex-linked dwarfing allele (dw) is the most studied one. This recessive sex-linked dwarfism is caused by a dysfunctional Growth Hormone receptor (GHR) which causes absence of Growth Hormone (GH)-dependent gene expression in the chicken liver. This defect seems to be the chicken equivalent of Laron dwarfism in humans: despite high circulating GH concentrations, plasma Insulin-like Growth Factor-I (IGF-I) levels are extremely low (Huybrechts et al., 1985; Bowen et al., 1987; Duriez et al., 1993). A point mutation located within the part of the gene encoding the extracellular domain of the GH receptor is responsible for the dysfunctional receptor (Duriez et al., 1993). The sexlinked dwarfism chicken is now being used as an animal model for Laron Dwarfism in humans and these animals are also used to study genes regulated by Growth Hormone (Agarwal et al., 1995; Tanaka et al., 1996). Recent research revealed that IGF-I mRNA is expressed in the liver in a GH-dependent manner after hatching. In extrahepatic tissues, mRNA expression is independent of GH and GHR before and after hatching, except for the testis, where GH seems to inhibit IGF-I mRNA expression. In dwarf chickens, hepatic IGF-I expression is completely abolished (Tanaka et al., 1996).
Albers Gerardus Antonius Arnoldus
Groenen Martinus Antonius Mathilda
Jones W. Gary
Nutreco Nederland B.V.
Roberts & Merchanti, LLP
Taylor Janell E.
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