This study aimed to develop a methodology for using ultrasonic technology (USG) to record eggshell thickness for selection of layers. Genetic correla

The objectives of this study were to determine if sires perform consistently across altitude and to quantify the genetic relationship between growth and survival at differing altitudes. Data from the American Angus Association included weaning weight (WW) adjusted to 205 (n = 77,771) and yearling weight adjusted to 365 (n = 39,450) d of age from 77,771 purebred Angus cattle born in Colorado between 1972 and 2007. Postweaning gain (PWG) was calculated by subtracting adjusted WW from adjusted yearling weight. Altitude was assigned to each record based upon the zip code of each herd in the database. Records for WW and PWG were each split into 2 traits measured at low and high altitude, with the records from medium altitude removed from the data due to inconsistencies between growth performance and apparent culling rate. A binary trait, survival (SV), was defined to account for censored records at yearling for each altitude. It was assumed that, at high altitude, individuals missing a yearling weight either died or required relocation to a lower altitude predominantly due to brisket disease, a condition common at high altitude. Model 1 considered each WW and PWG measured at 2 altitudes as separate traits. Model 2 treated PWG and SV measured as separate traits due to altitude. Models included the effects of weaning contemporary group, age of dam, animal additive genetic effects, and residual. Maternal genetic and maternal permanent environmental effects were included for WW. Heritability estimates for WW in Model 1 were 0.28 and 0.26 and for PWG were 0.26 and 0.19 with greater values in low altitude. Genetic correlations between growth traits measured at different altitude were moderate in magnitude: 0.74 for WW and 0.76 for PWG and indicate possibility of reranking of sires across altitude. Maternal genetic correlation between WW at varying altitude of 0.75 also indicates these may be different traits. In Model 2, heritabilities were 0.14 and 0.27 for PWG and 0.36 and 0.47 for SV. Genetic correlation between PWG measured at low and high altitude was 0.68. Favorable genetic correlations were estimated between SV and PWG within and between altitudes, suggesting that calves with genetics for increased growth from weaning to yearling also have increased genetic potential for SV. Genetic evaluations of PWG in different altitudes should consider preselection of the data, by using a censoring trait, like survivability to yearling. Copyright © 2012. American Society of Animal Science .

A genetic analysis was performed on Polish ostriches from the 3 principal ostrich breeds: red-, blue-, and black-necks. The analysis was based on 2 molecular methods: DNA fingerprinting and microsatellites. The DNA fingerprinting patterns were obtained using the restriction enzyme HinfI and Jeffrey’s 33.15 probe. The second method consisted of a PCR procedure, for which 5 VIAS-OS primers specific to the ostrich were used. The PCR products were separated on polyacrylamide gel using ALFexpress (Authomated Laser Fluorescent DNA Sequencer). The study aimed at assessing the genetic variability within and among the 3 ostrich breeds as well as evaluating the genetic distance between them, and represents the first report on the genetic characteristics of the ostrich breeds. The results obtained by both methods showed considerable compatibility, especially with regard to the relationship among the breeds analyzed. The diversity within breeds, obtained on the basis of the DNA fingerprinting analysis, proved to be low. Among the ostrich populations analyzed, the highest variability potential was observed for black-necked ostriches (the mean diversity of patterns amounted to 29.04%, whereas the mean heterozygosity was 0.30) and the lowest was observed for the red-necks. The largest genetic similarity was recorded between red- and blue-necked ostriches, but the greatest genetic distance was between the red- and black-necks. This means that the use of birds of those breeds in crosses should result in the highest heterotic effect. Both of these methods measured the genetic distance between the analyzed ostrich breeds that was expected from the geographic origin of these birds. The results obtained in the present study showed that both analytic methods used can be successfully applied when elaborating on the genetic characteristics of the ostrich.

The aim of this study was to estimate genetic parameters for BW of Angus cattle up to 5 yr of age and to discuss options for including mature weight (MW) in their genetic evaluation. Data were obtained from the American Angus Association. Only records from herds with at least 500 animals and with >10% of animals with BW at ≥2 yr of age were considered. Traits were weaning weight (WW, n = 81,525), yearling weight (YW, n = 62,721), and BW measured from 2 to 5 yr of age (MW2, n = 15,927; MW3, n = 12,404; MW4, n = 9,805; MW5, n = 7,546). Genetic parameters were estimated using an AIREML algorithm with a multiple-trait animal model. Fixed effects were contemporary group and departure of the actual age from standard age (205, 365, 730, 1,095, 1,460, and 1,825 d of age for WW, YW, MW2, MW3, MW4, and MW5, respectively). Random effects were animal direct additive genetic, maternal additive genetic, maternal permanent environment, and residual. Estimates of direct genetic variances (kg²) were 298 ± 71.8, 563 ± 15.1, 925 ± 52.1, 1,221 ± 65.8, 1,406 ± 80.4, and 1,402 ± 66.9; maternal genetic variances were 167 ± 4.8, 153 ± 6.1, 123 ± 9.1, 136 ± 12.25, 167 ± 18.0, and 110 ± 14.0; maternal permanent environment variances were 124 ± 2.9, 120 ± 4.3, 61 ± 7.5, 69 ± 11.9, 103 ± 15.9, and 134 ± 35.2; and residual variances were 258 ± 3.8, 608 ± 8.6, 829 ± 34.2, 1,016 ± 38.8, 1,017 ± 52.1, and 1,202 ± 63.22 for WW, YW, MW2, MW3, MW4, and MW5, respectively. The direct genetic correlation between WW and YW was 0.84 ± 0.14 and between WW and MW ranged from 0.66 ± 0.06 (WW and MW4) to 0.72 ± 0.11 (WW and MW2). Direct genetic correlations ranged from 0.77 ± 0.08 (YW and MW5) to 0.85 ± 0.07 (YW and MW2) between YW and MW, and they were ≥0.95 among MW2, MW3, MW4, and MW5. Maternal genetic correlations between WW and YW and MW ranged from 0.52 ± 0.05 (WW and MW4) to 0.95 ± 0.07 (WW and YW), and among MW they ranged from 0.54 ± 0.14 (MW4 and MW5) to 0.94 ± 0.07 (MW2 and MW3). Genetic correlations suggest that a genetic evaluation for MW may be MW2-based and that including BW from older ages could be accomplished by adjusting records to the scale of MW2. Copyright © 2011. American Society of Animal Science .