Behrouz Mohammad Nazari; Ardeshir Nejati Javaremi; Mohammad Moradi Shahre Babak; Rostam AbdolahiArpanahi
Volume 22, Issue 4 , December 2020, , Pages 515-527
Abstract
In order to evaluate the effect of genotype by environment interaction on production traits of Holstein cattle of Iran, first lactation test day records of 344170, 135000 and 156840 of milk, fat and protein yield on 34417, 13500 and 15684 cows and SNP markers of 1935 genotyped bulls were used. The ...
Read More
In order to evaluate the effect of genotype by environment interaction on production traits of Holstein cattle of Iran, first lactation test day records of 344170, 135000 and 156840 of milk, fat and protein yield on 34417, 13500 and 15684 cows and SNP markers of 1935 genotyped bulls were used. The production data were retrieved from the Animal Breeding Center and Productions Improvement of Iran’s database which were collected from 2013 to 2018. To consider the interaction of genotype and environment, mean of temperature-humidity index (THI) in three days before each test day records as continuous environmental effect were retrieved from the 35 closest meteorological stations in the vicinity of 139 Holstein herds from 13 provinces. Variance and covariance components were estimated through a single-trait random regression model with orthogonal Legendre polynomials of second order for days in milk and THI using AIREMLF90 software. The results showed that changes in THI across lactation led tofluctuations in additive genetic variance over time. The change in heritability of milk production traits over lactation followed the same trend as additive genetic variance. The results from cross-validation analysis showed that including genomic information into the predictive model, increased prediction accuracy and including THI information increased unbiasedness. Due to the changes in milk production of daughters of bulls across days and THI , genotype by environment interaction should be considered when selecting bulls under different conditions.
Abdollah Rezagholivand Lahrud; Mohammad Moradi Shahre Babak; Hossein Moradi Shahrbabak; Morteza Sattaei Mokhtari
Volume 20, Issue 4 , February 2019, , Pages 499-511
Abstract
The objective of the present study was the genetic evaluation of retained placenta (RP), metritis (MET), number of inseminations to conception (INS), and days open (DO) in Holstein cows using standard (SMMs) and recursive (RMMs) mixed models. Data on 50230 first-lactation Holstein dairy cattle, collected ...
Read More
The objective of the present study was the genetic evaluation of retained placenta (RP), metritis (MET), number of inseminations to conception (INS), and days open (DO) in Holstein cows using standard (SMMs) and recursive (RMMs) mixed models. Data on 50230 first-lactation Holstein dairy cattle, collected during 2008 to 2017 in 17 large dairy herds were used. The data was analyzed using four-variate animal Threshold-Gaussian models under SMMs and RMMs. The existence of causal effects from RP on MET, INS and DO, from MET on INS and DO and from INS to DO were considered in RMMs. The causal effects of RP and MET on INS were 0.19 and 0.09 services, respectively; and those on DO were 4.74 and 5.38 days, respectively. Also, causal effect of INS on DO was obtained as 33 days. The considered causal relationships except that of RP on MET, phenotypic and residual correlations among the disorders and fertility traits were statistically significant and different under two models. Posterior means of heritability for RP, MET, INS and DO were 0.15, 0.17, 0.07 and 0.09 under SMMs, respectively; and 0.16, 0.17, 0.07 and 0.1 under RMMs, respectively. The difference between the corresponding heritability estimates under SMMs and RMMs were not statistically significant. Therefore; RMMs may be an alternative for SMMs in genetic evaluation of studied traits in first -lactation Holstein cows.
hamid marzbani; Hossein Moradi Shahrbabak; Mohammad Moradi Shahre Babak
Volume 20, Issue 1 , May 2018, , Pages 29-41
Abstract
This study was conducted to estimate the linkage disequilibrium (LD) and determine haplotype blocks structure in 93 Sarabi cow using SNP-chip 40k of Illumina company. After genotyping and quality control, 27386 SNP markers on autosomal chromosomes remained for analyzing. The LD was measured by r2 and ...
Read More
This study was conducted to estimate the linkage disequilibrium (LD) and determine haplotype blocks structure in 93 Sarabi cow using SNP-chip 40k of Illumina company. After genotyping and quality control, 27386 SNP markers on autosomal chromosomes remained for analyzing. The LD was measured by r2 and D' statistics. In this study the average of r2 and D' for range less than of 2.5 kb were maximum with 0.505 and 0.927, respectively. The average of r2 and D' were minimum with 0.064 and 0.486, respectively in range of 2-5 Mb. 582 haplotype blocks were observed in the genome of Sarabi cow. 6.73% SNP from all of the SNPs were covered and 0.83% (21.43 Mb) of the autosomal genome were covered by the blocks haplotype. Population effective size was estimated about 40 that refer to four generations ago. The low number of haplotype block and also low LD level in Sarabi cow population showed high variation. In refer to the result and the number of haplotype blocks in this breed, applying the haplotype blocks could be improve results and high precision on genomic selection study so it was recommended that in study of genomic selection applying the haplotype blocks really useful than single SNP study
Rostam Abdollahi-Arpanahi; Abas Pakdel; Ardeshir Nejati-Javaremi; Mohammad Moradi Shahrbabak
Volume 15, Issue 1 , July 2014, , Pages 65-77
Abstract
The objective of this study was to compare six statistical methods for prediction of genomic breedingvalues for traits with different genetic architecture in term of gene effects distributions and number ofQuantitative Traits Loci (QTLs). A genome consisted of 500 bi-allelic single nucleotide polymorphism(SNP) ...
Read More
The objective of this study was to compare six statistical methods for prediction of genomic breedingvalues for traits with different genetic architecture in term of gene effects distributions and number ofQuantitative Traits Loci (QTLs). A genome consisted of 500 bi-allelic single nucleotide polymorphism(SNP) markers distributed over a chromosomes with 100 cm length was simulated. Three different geneeffects distributions (uniform, normal and gamma) were considered. Number of QTLs varied from 50 to200. Finally, nine quantitative traits with different genetic architecture were generated. The performanceof six statistical methods of genomic prediction that differ with respect to assumptions regardingdistribution of marker effects, including i) Genomic Best Linear Unbiased Prediction (GBLUP), ii) RidgeRegression Best Linear Unbiased Prediction (RRBLUP), iii) Bayes A, iv) Bayes B, v) Bayes C, and vi)Bayesian least absolute shrinkage and selection operator (Bayes L) are presented. The accuracy ofprediction declined significantly over generations (P< 0.05) but Bayesian methods outperformed GBLUPand RRBLUP in persistence of accuracy of genomic estimated breeding values over generations.Bayesian methods were superior to GBLUP and RRBLUP when the gene effects distribution generatedfrom gamma distribution. The highest accuracy of genomic breeding values was observed when the geneeffects come from normal distribution. In all statistical evaluation methods with increasing the number ofQTLs towards 200, the accuracy of predicted genomic values has been decreased. In general, Bayesianand GBLUP methods performed better in prediction than RRBLUP method. These results gave someevidences that when the genetic architecture of quantitative traits deviated from infinitesimal modelassumptions, Bayesian methods usually perform better than GBLUP and RR-BLUP.