Search results

Filters

  • Journals
  • Authors
  • Keywords
  • Date
  • Type

Search results

Number of results: 2
items per page: 25 50 75
Sort by:
Download PDF Download RIS Download Bibtex

Abstract

Local adaptation is a key concept in biology: shift of genetic structures of populations due to differential survival of genotypes is expected to lead to phenotypes providing an advantage in the local environment. Variation of sequences of twelve candidate genes was investigated in 13 Norway spruce (Picea abies (L.) Karst.) provenances originating from sites distributed along an altitudinal gradient from 550 to 1300 m a.s.l. Signals of selection were assessed in 103 single nucleotide polymorphisms (SNP). The Bayesian FST-outlier identification methods as implemented in the programs BayeScan and Arlequin did not identify any SNP with a clear evidence of selection. The approaches relying on SNP-climate associations (spatial analysis method based on logistic regression of allele frequencies with environmental variables, Bayesian method applied in BayEnv2) identified several relationships but none of them remained significant after correction for multiple testing. Gene flow, epigenetic inheritance and former management of the studied populations are discussed as potential reasons for this weak evidence of selection signals.

Go to article

Authors and Affiliations

Matúš Hrivnák
Diana Krajmerová
Dušan Gömöry
Download PDF Download RIS Download Bibtex

Abstract

Blood samples from forty-six roe deer ( Capreolus capreolus) acquired during officially approved hunting in six hunting divisions throughout Poland were used to isolate the genomic DNA. All individuals were genotyped by MD_Bovine BeadChip (Illumina) for 46.750 Single Nucleotide Polymorphism (SNP) markers. SNPs of inappropriate clusters, with a marker call rate lower than 90% and with a minor allele frequency (MAF) lower than 0.01, located on sex chromosomes and mitochondrial DNA, were removed. Altogether, 21.033 SNP markers were included for further analysis. Observed and expected heterozygosity amounted to 0.098 and 0.119, respectively. Among 21.033 markers, a panel of 148 SNPs were selected for relationship analysis. They were unlinked and had a MAF higher than 0.2. This set of SNPs showed a probability of parentage exclusion of 1.29x10 -6 and 2.37x10 -19 for one, and two known parents, respectively. The probability of identity was estimated at 1.8x10 -40. The probabilities obtained in this study are sufficient for the monitoring and effective management of the genetic diversity of roe deer in Poland and is a cost-effective complementary tool for forensic applications.
Go to article

Bibliography

References:

Apollonio M, Andersen R, Putman R (2010) European ungulates and their management in the 21st century. Cambridge University Press, Cambridge, UK.
Bartos L, Bubenik G (2011) Relationships between rank-related behaviour, antler cycle timing and antler growth in deer behavioural aspects. Anim Prod Sci 51: 303-310.
Baruch E, Weller JI (2008) Estimation of the number of SNP genetic markers required for parentage verification. Anim Genet 39: 474-479.
Bertolini F, Elbeltagy A, Rothschild M (2017) Evaluation of the application of bovine, ovine and caprine SNP chips to dromedary genotyping. Livest Res Rural Dev 29: 31-38.
Fernández ME, Goszczynski DE, Lirón JP, Villegas-Castagnasso EE, Carino MH, Ripoli MV, Rogberg-Muñoz A, Posik DM, Peral-García P, Giovambattista G (2013) Comparison of the effectiveness of microsatellites and SNP panels for genetic identification, traceability and as-sessment of parentage in an inbred Angus herd. Genet Mol Biol 36: 185-191.
Fisher PJ, Malthus B, Walker MC, Corbett G, Spelman RJ (2009) The number of single nucleotide polymorphisms and on-farm data required for whole-herd parentage testing in dairy cattle breeds. J Dairy Sci 92: 369-374.
Glowatzki-Mullis ML, Gaillard C, Wigger G, Fries R (1995) Microsatellite-based parentage control in cattle. Anim Genet 26: 7-12.
Haynes GD, Latch EK (2012) Identification of Novel Single Nucleotide Polymorphisms (SNPs) in Deer (Odocoileus spp.) Using the Bo-vineSNP50 BeadChip. PLoS One 7: e36536.
Heaton MP, Harhay GP, Bennett GL, Stone RT, Grosse WM, Casas E, Keele JW, Smith TP, Chitko-McKown CG, Laegreid WW (2002) Selection and use of SNP markers for animal identification and paternity analysis in U.S. beef cattle. Mamm Genome 13: 272-281.
Jamieson A, Taylor SC (1997) Comparison of three proba- bility formulae for parentage exclusion. Anim Genet 28: 397-400.
Kaltenbrunner M, Hochegger R, Cichna-Markl M (2018) Sika deer (Cervus nippon)-specific real-time PCR method to detect fraudulent label-ling of meat and meat products. Sci Rep 8: 7236.
Li C, Yang F, Sheppard A (2009) Adult stem cells and mammalian epimorphic regeneration-insights from studying annual renewal of deer antlers. Curr Stem Cell Res Ther 4: 237-251.
McClure MC, McCarthy J, Flynn P, McClure JC, Dair E, O’Connell DK, Kearney JF (2018) SNP Data Quality Control in a National Beef and Dairy Cattle System and Highly Accurate SNP Based parentage verification and Identification. Front Genet. 15: 84.
Miller JM, Poissant J, Kijas JW, Coltman DW (2011) International Sheep Genomics Consortium. A genome-wide set of SNPs detects popu-lation substructure and long range linkage disequilibrium in wild sheep. Mol Ecol Resour 11: 314-322
More M, Gutiérrez G, Rothschild M, Bertolini F, Ponce de León FA (2019) Evaluation of SNP genotyping in alpacas using the Bovine HD Genotyping BeadChip. Front Genet 10: 361.
Morf NV, Kopps AM, Nater A, Lendvay B, Vasilievic N, Webster LMI, Fautley RG, Ogden R, Kratzer A (2021) STRoe deer: A validated forensic STR profiling system for the European roe deer (Capreolus capreolus). Forensic Sci Int Anim Environ 1: 100023
Pertoldi C, Wójcik JM, Tokarska M, Kawałko A, Kristensen TN, Loeschcke V, Gregersen VR, Coltman D, Wilson GA, Randi E, Henryon M, Bendixen C (2010) Genome variability in European and American bison detected using BovineSNP50 BeadChip. Conserv Genet 11: 627-634.
Plis K, Niedziałkowska M, Borowik T, Lang J, Heddergott M, Tiainen J, Bunevich A, Šprem N, Paule L, Danilkin A, Kholodova M, Zvy-chaynaya E, Kashinina N, Pokorny B, Flajšman K, Paulauskas A, Djan M, Ristić Z, Novák L, Kusza S, Miller C, Tsaparis D, Stoyanov S, Shkvyria M, Suchentrunk F, Kutal M, Lavadinović V, Šnjegota D, Krapal AM, Dănilă G, Veeroja R, Dulko E, Jędrzejewska B (2022) Pan-European phylogeography of the European roe deer (Capreolus capreolus). Ecol Evol 12: e8931.
Poetsch M, Seefeldt S, Maschke M, Ignitz E (2001) Analysis of microsatellite polymorphism in red deer, roe deer, and fallow deer – possible employment in forensic applications. Forensic Sci Int 116: 1-8.
Waits LP, Luikart G, Taberlet P (2001) Estimating the probability of identity among genotypes in natural populations: cautions and guidelines. Mol Ecol 10: 249-256.
Weller JI, Seroussi E, Ron M (2006) Estimation of the number of genetic markers required for individual animal identification accounting for genotyping errors. Anim Genet 37: 387-389.
Werner FA, Durstewitz G, Habermann FA, Thaller G, Krämer W, Kollers S, Buitkamp J, Georges M, Brem G, Mosner J, Fries R (2004) Detection and characterization of SNPs useful for identity control and parentage testing in major European dairy breeds. Anim Genet 35: 44-9.
Go to article

Authors and Affiliations

K. Oleński
1
D. Zalewski
2
S. Kamiński
1

  1. University of Warmia and Mazury, Department of Animal Genetics, M. Oczapowskiego 5, 10-718 Olsztyn, Poland
  2. University of Warmia and Mazury, Department of Fur-bearing Animal Breeding and Game Management, M. Oczapowskiego 5, 10-718 Olsztyn, Poland

This page uses 'cookies'. Learn more