Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-19T20:43:46.604Z Has data issue: false hasContentIssue false
  • English
  • Français

Molecular markers for the assessment of chicken biodiversity

Published online by Cambridge University Press:  14 March 2007

J. HILLEL ,
Z. GRANEVITZE ,
T. TWITO ,
D. BEN-AVRAHAM ,
S. BLUM ,
U. LAVI ,
L. DAVID ,
M.W. FELDMAN ,
H. CHENG  and
S. WEIGEND
J. HILLEL*
Affiliation:
The Hebrew University of Jerusalem, Faculty of Agriculture, Rehovot 76100, Israel
Z. GRANEVITZE
Affiliation:
The Hebrew University of Jerusalem, Faculty of Agriculture, Rehovot 76100, Israel
T. TWITO
Affiliation:
ARO-Volcani Center, P.O.B.6 Bet Dagan 50250Israel
D. BEN-AVRAHAM
Affiliation:
The Hebrew University of Jerusalem, Faculty of Agriculture, Rehovot 76100, Israel
S. BLUM
Affiliation:
The Hebrew University of Jerusalem, Faculty of Agriculture, Rehovot 76100, Israel
U. LAVI
Affiliation:
ARO-Volcani Center, P.O.B.6 Bet Dagan 50250Israel
L. DAVID
Affiliation:
Stanford Genome Technology Center, Stanford University, California, 94304, USA
M.W. FELDMAN
Affiliation:
Department of Biological Sciences, Stanford University, California, 94305, USA
H. CHENG
Affiliation:
USDA-ARS, Avian Disease and Oncology Laboratory, 3606 E. Mount Hope Rd. East Lansing, MI 48823, USA
S. WEIGEND
Affiliation:
Institute for Animal Breeding Mariensee, Federal Agricultural Research Centre (FAL); 31535 Neustadt; Germany
*
*Corresponding author: [email protected]
Get access

Abstract

Three main aspects of chicken biodiversity are dealt within this report: (a) cluster analysis based on autosomal microsatellites, (b) microsatellites on the sex chromosomes, and (c) SNP-based biodiversity.

(a) Cluster analysis of autosomal microsatellites: We used 29 microsatellites to genotype 2000 chickens randomly selected from 65 different populations representing various chicken types and various geographical regions. The computer program Structure placed the 65 populations into clusters that are in agreement with their geographic origin and breed history. Only at two predefined clusters, there is little admixture between non-commercial populations originating from Asia and those from Europe. In contrast, commercial broilers and brown egg layers appeared as admixed populations of these two main gene pools. Increasing the number of clusters resulted in generation of specific clusters of commercial lines, having very low admixture with other clusters. In addition, we identified seven mixed populations, each of which shared portions of their genome with several other genetic clusters.

(b) Microsatellites on the sex chromosomes: We predicted 173 potential microsatellites on chromosome W by in-silico analysis of the chicken genome assembly (version WASHUC1). Twenty five microsatellites of the highest sequence quality were tested in the lab for gender specificity. Unexpectedly, PCR products were generated in both sexes. Moreover, 14 selected microsatellites were mapped (using the East Lansing reference panel) and in all cases, the “W specific” microsatellites were mapped to chromosome Z and except for one locus, to the same ∼6 cM region. We conclude that the draft assembly for chromosome W is quite inaccurate.

(c) SNP-based biodiversity: Ten distinct chicken breeds were genotyped at 145 single nucleotide polymorphisms (SNPs) located at 14 random DNA fragments and twenty five, each from different and unlinked genes. Microsatellite genotypes of the same ten breeds were used for comparison. Applying bootstrap values as the criterion for tree's reliability, we found that: (1) increasing the number of SNPs had a higher impact on the reliability of the analysis than increasing the number of individuals per population, and (2) the bootstrap values of phylogenetic un-rooted trees based on microsatellites were relatively low.

Keywords

biodiversitybioinformaticschickenmicrosatellitesphylogenypoultrySNPW-chromosome
Type
Review Article
Information
World's Poultry Science Journal , Volume 63 , Issue 1 , March 2007 , pp. 33 - 45
Copyright
Copyright © World's Poultry Science Association 2007

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

ALTSCHUL, S.F., GISH, W., MILLER, W., MYERS, E.W. and LIPMAN, D.J. (1990) Basic local alignment search tool. Journal of Molecular Biology 215: 403–410.Google Scholar
BEN-AVRAHAM, D., BLUM, S., GRANEVITZE, Z., WEIGEND, S., CHENG, H. and HILLEL, J. (2006) W-specific microsatellite loci detected by in silico analysis map to chromosome Z of the chicken genome. Animal Genetics 37:180–181.Google Scholar
BENSON, G. (1999) Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acid Research 27(2): 573–580.CrossRefGoogle Scholar
CRAWFORD, R.D. (1990) Origin and history of poultry species. In: Poultry Breeding and Genetics. Crawford, R.D. Ed. Elsevier, New York, NY. p1–41.Google Scholar
DELACOUR, J. (1977) The Pheasants of the world, 2nd edition.Spur Publication, Hindhead, Surrey. UK.Google Scholar
ELLEGREN, H. and CARMICHAEL, A. (2001) Multiple and independent cessation of recombination between avian sex chromosomes. Genetics 158(1): 325–331.Google Scholar
FELSENSTEIN, J. (1992) Estimating effective population size from samples of sequences: a bootstrap Monte Carlo integration method. Genetical Research 60(3): 209–220.Google Scholar
GAINES, C.A., HARE, M.P., BECK, S.E. and ROSENBAUM, H.C. (2005) Nuclear markers confirm taxonomic status and relationships among highly endangered and closely related right whale species. Proceedings. Biological Sciences 272: 533–542.Google ScholarPubMed
HANDLEY, L.J., CEPLITIS, H. and ELLEGREN, H. (2004) Evolutionary strata on the chicken Z chromosome: implications for sex chromosome evolution. Genetics 167(1): 367–376.Google Scholar
HAWARD, R. and MOORE, A. (1984) Acomplete checklist of birds of the world, revised edition. Macmillian, London, UK.Google Scholar
HILLEL, J., GROENEN, M.A., TIXIER-BOICHARD, M., KOROL, A.B., DAVID, L., KIRZHNER, V.M., BURKE, T., BARRE-DIRIE, A., CROOIJMANS, R.P., ELO, K., FELDMAN, M.W., FREIDLIN, P.J., MAKI-TANILA, A., OORTWIJN, M., THOMSON, P., VIGNAL, A., WIMMERS, K. and WEIGEND, S. (2003) Biodiversity of 52 chicken populations assessed by microsatellite typing of DNA pools. Genetics, Selection, Evolution 35: 533–557.Google Scholar
INTERNATIONAL CHICKEN POLYMORPHISM MAP CONSORTIUM (2004) A genetic variation map for chicken with 2.8 million single-nucleotide polymorphisms. Nature 432: 717–722.Google Scholar
JOHNSGARD, P.A. (1986) The Pheasants of the world. Oxford University Press, New York USA.Google Scholar
MARTINEZ-ARIAS, R., MATEU, E., BERTRANPETIT, J. and CALAFELL, F. (2001) Profiles of accepted mutation: from neutrality in a pseudogene to disease-causing mutation on its homologous gene. Human Genetics 109(1): 7–10.Google Scholar
PLOTSKY, Y., KAISER, M.G. and LAMONT, S.J. (1995) Genetic characterization of highly inbred chicken lines by two DNA methods: DNA fingerprinting and polymerase chain reaction using arbitrary primers. Animal Genetics 26: 163–170.Google Scholar
PRITCHARD, J.K., STEPHENS, M. and DONNELLY, P.J. (2000) Inference of population structure using multilocus genotype data. Genetics 155: 945–959.Google Scholar
ROMANOV, M.N. and WEIGEND, S. (2001) Analysis of genetic relationships between various populations of domestic and jungle fowl using microsatellite markers. Poultry Science 80: 1057–1063.Google Scholar
ROZEN, S. and SKALETSKY, H. (2000) Primer3 on the WWW for general users and for biologist programmers. pages In: Krawetz, S, and Misener, S. eds. Bioinformatics Methods and Protocols: Methods in Molecular Biology p. 365–386. Humana Press, NJ.Google Scholar
ROSENBERG, N.A., PRITCHARD, J.K., WEBER, J.L., CANN, H.M., KIDD, K.K., ZHIVOTOVSKY, L.A. and FELDMAN, M.W. (2002) Genetic structure of human populations. Science 298: 2381–2385.Google Scholar
SHARMA, D., APPA RAO, K.B., SINGH, R.V. and TOTEY, S.M. (2001) Genetic diversity among chicken breeds estimated through randomly amplified polymorphic DNA. Animal Biotechnology 12: 111–120.Google Scholar
SHEN, P., LAVI, T., KIVISILD, T., CHOU, V., SENGUN, D., GEFEL, D., SHPIRER, I., WOOLF, E., HILLEL, J., FELDMAN, M. and OEFNER, P.J. (2004) Reconstruction of patri- and matri-lineages of Samaritans and other Israeli populations from Y-chromosome and mitochondrial DNA sequence variation. Human Mutation 24: 248–260.Google Scholar
VANHALA, T., TUISKULA-HAAVISTO, M., ELO, K., VILKKI, J. and MAKI-TANILA, A. (1998) Evaluation of genetic variability and genetic distances between eight chicken lines using microsatellite markers. Poultry Science 77: 783–790.Google Scholar
VISHWANATHAN, H., DEEPA, E., CORDAUX, R., STONEKING, M., USHA RANI, M.V. and MAJUMDER, P.P. (2004) Genetic structure and affinities among tribal populations of southern India: a study of 24 autosomal DNA markers. Annals of Human Genetics 68: 128–138.CrossRefGoogle ScholarPubMed
WEIGEND, S., GROENEN, M.A.M., TIXIER-BOICHARD, M.VIGNAL, A., HILLEL, J., WIMMERS, K., BURKE, T. and MÄKI-TANILA, A. (1998) Development of Strategy and Application of Molecular Tools to Assess Biodiversity in Chicken Genetic Resources. AVIandIV; EC Contract No. BIO4-CT98-0342.Google Scholar
WEIGEND, S. and ROMANOV, M.N. (2001). Current strategies for the assessment and evaluation of genetic diversity in chicken resources. World's Poultry Science Journal 57: 275–287.Google Scholar
ZHOU, H. and LAMONT, S.J. (1999) Genetic characterization of biodiversity in highly inbred chicken lines by microsatellite markers. Animal Genetics 30: 256–264.CrossRefGoogle ScholarPubMed