YAKUT GEVREKÇİ, Yavuz AKBAŞ, KADİR KIZILKAYA

Comparison of different models in genetic analysis of dystocia

Bu çalışmanın amacı, buzağılama güçlüğünün genetik analizinde eşikli baba (TS), eşikli baba-ana tarafından büyükbaba (TS-MGS) ve doğrusal baba-ana tarafından büyükbaba (L) modellerini karşılaştırmaktır. Eşikli modeller Bayes yaklaşımına dayanmaktadır. Çalışmada, Amerika’daki Siyah Alacalara ait 19439 adet buzağılama güçlüğü kaydı kullanılmıştır. İstatistiksel modeller buzağılama yılı-mevsimi, buzağı cinsiyeti, annenin laktasyon sırası, buzağının babası ve sürü etkilerini içerirken, baba-ana tarafından büyükbaba modelinde, buzağının ana tarafından büyükbaba etkisi de bulunmaktadır. Buzağılama güçlüğü için eşikli modellerle tahminlenen varyans-kovaryanslar, doğrusal modelden tahminlenen değerlerden daha yüksek bulunmuştur. Doğrudan genetik etkiler (h2D) ile anaya ait genetik etkiler (h2M) kullanılarak elde edilen kalıtım derecesi tahminleri ve standart hataları TS-MGS ile sırasıyla 0.18±0.004 ve 0.14±0.004; doğrusal model ile 0.12±0.003 ve 0.09±0.003 olarak bulunmuştur. Doğrudan genetik etkilere ait kalıtım derecesi TS ile 0.20±0.009 olarak tahminlenmiştir. Ayrıca doğrudan ve anaya ait genetik etkiler arasındaki genetik korelasyon TS-MGS ile -0.087±0.006 bulunurken, doğrusal model ile -0.253±0.010 düzeyinde tahminlenmiştir. Sonuç olarak, buzağılama güçlüğünün analizinde eşikli model, doğrusal modele göre daha iyi kabul edilebilir. Doğrusal modelle karşılaştırıldığında eşikli modelle elde edilen daha yüksek kalıtım derecesi, daha yüksek genetik ilerleme sağlamaktadır.

Anahtar Kelimeler:

inek, baba eşikli model, istatistiksel analizler, risk faktörleri, doğrusal modeller, kalıtsallık, genetic ıslah, genetik etkiler, genetik korelasyon, genetik analizler, çevresel faktörler, zor doğum, süt ineği, süt sığırı, buzağı, Bayesian teorisi

Buzağılama güçlüğünün genetik analizinde farklı modellerin karşılaştırılması

The aim of this study was to compare threshold sire model (TS), threshold sire-maternal grandsire model (TS-MGS) and linear sire-maternal grandsire model (L) for genetic analysis of dystocia. Threshold models were based on Bayesian approach. In the study, a total of 19439 dystocia records from Holsteins in USA were used. The eff ects of calving year-season, sex of calf, parity of dam, sire of calf and herd eff ects were included in all models and also maternal grandsire eff ect of calf was included in only sire-maternal grandsire models. Variance-covariance estimates were greater in threshold models than in linear model. Estimates of heritability (±SE) of dystocia based on direct genetic eff ects (h2D) and maternal genetic eff ects (h2M) were 0.18±0.004 and 0.14±0.004 from TS-MGS and 0.12±0.003 and 0.09±0.003 from L, respectively. Heritability estimates based on direct genetic eff ects from TS was 0.20±0.009. Genetic correlation between direct and maternal genetic eff ect were -0.087±0.006 from the TS-MGS and -0.253±0.010 from L. It was concluded that the threshold models were better than the linear model in the analysis of dystocia. The higher heritability estimates on the underlying scale from threshold models should allow greater genetic improvement than those using linear model estimations.

Keywords:

cows, threshold models, statistical analysis, risk factors, linear models, heritability, genetic improvement, genetic effects, genetic correlation, genetic analysis, environmental factors, dystocia, dairy cows, dairy cattle, calves, Bayesian theory,

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