Certificação genealógica em Bovinos Gir Leiteiro por meio de exame de paternidade pelo DNA

• Ano de defesa: 2010
• Autor(a) principal: Pinto, Isabella Silvestre Barreto
• Orientador(a): Euclydes, Ricardo Frederico
• Banca de defesa: Carneiro, Antônio Policarpo Souza , Souza, Gustavo Henrique de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Viçosa
• Programa de Pós-Graduação: Mestrado em Genética e Melhoramento
• Departamento: Genética animal; Genética molecular e de microrganismos; Genética quantitativa; Genética vegetal; Me
• País: BR
• Palavras-chave em Português: Endogamia; Avaliação; Paternidade
• Palavras-chave em Inglês: Endogamy; Evaluation; Paternity
• Área do conhecimento CNPq: CNPQ::CIENCIAS AGRARIAS::ZOOTECNIA::GENETICA E MELHORAMENTO DOS ANIMAIS DOMESTICOS
• Link de acesso: http://locus.ufv.br/handle/123456789/4731

Embrapa Dairy has been developing for 25 years the National Program for Improvement of Dairy Gir - PNMGIL - which aims to promote the breeding Gir through the selection of top bulls. The program uses information from progeny of bulls on test, it is important to have information on paternity, since misidentification of membership can affect the genetic gain. This work used molecular markers to verify the pedigree of animals belonging to PNMGIL, check the frequency of paternity errors by farms and bull tested, verify the frequency of alleles in the analyzed population and the efficiency of markers used. Blood samples from 303 daughters were collected of 55 bulls from 74 different farms, 15 farms Gir pure and 59 of Gir x Holstein. 11 markers belonging to Kit StockMarks for Cattle® Bovine Paternity PCR Typing and five additional markers recommended by ISAG (International Society of Animal Genetics) were used. PCR products were analyzed on DNA sequencer MegaBACE 1000. The analysis of the fragments was done in the Fragment Profiler software and the application software POPGENE 1.32 was used to calculate observed and expected heterozygosity, allelic frequency and number of alleles. PIC values were calculated in the program PowerStats v1.2 and SAS ® software was used to estimate errors frequencies per farms. Paternity exclusion was seen when two or more markers were not shared between father and daughter. We found a total of 18.15% of paternity errors in all cases analyzed. Errors of 19.28% and 17.73% were found on Gir cattle farms and Gir x Holstein, respectively. The 55 tested bulls, in 22 were not errors observed and 33 presented at least one error of paternity. The bulls with semen for insemination of more widespread cows had a greater number of errors when compared to bulls with semen less widespread. The markers with highest number of alleles were ETH3, 11-3 and 28-2 with 17 alleles each and a marker with the lowest was the BM1824 with 9 alleles. The mean expected and observed heterozygosity of the markers were 0.7682 and 0.7136, respectively. The average PIC for all markers was 0.78, ranging from 0.59 (ETH3) to 0.86 (28-2), values which show high polymorphisms rate to markers. Combined power of exclusion for the markers used in this study was higher than 99.99%, showing that they were efficient to perform the paternity test while not specific to the population studied. Using the most informative markers for the population tested can reduce the number of markers used, which could reduce the cost of paternity testing. For this, a specific panel for zebu must be prepared.