Seasonal evolution of faecal egg output by gastrointestinal worms in goats on communal farms in eastern Namibia.

As a more detailed continuation of a previous study, faecal samples for worm egg counts were collected per rectum from ten marked adult animals in selected flocks of goats, in each of six villages evenly spread out in the communal farming district of Okakarara in eastern Namibia. The study was conducted on a monthly basis from August 1999 to July 2000. Average faecal worm egg counts (FECs) were highest during the warm-wet season, much lower during the cold-dry months and moderate during the hot-dry season. Least square means of FECs were 2140, 430 and 653 per gram of faeces for the three seasons, respectively. Seasonal variation in egg counts was significant (P < 0.0001). Gastrointestinal strongyles, and to a lesser extent Strongyloides species, were the predominant parasite groups identified in goats. Kidding rates peaked in the cold-dry season and mortality rates in the hot-dry season. Results of this study suggest that gastrointestinal parasitism may be a problem that accentuates the effect of poor nutrition on small ruminants during the season of food shortages in the east of Namibia and that the use of FECs per se to assess the severity of gastrointestinal parasitic infection in goats followed by chemoprophylactic strategic and/or tactical treatment, may not be the best approach to addressing the worm problem under resource-poor conditions. The use of the FAMACHA system that identifies severely affected animals for treatment is technically a better option for communal farmers.

Joint evaluation of purebreds and crossbreds in swine.

Data from two purebred swine lines A (n = 6,022) and B (n = 24,170), and their reciprocal, cross C (n = 6,135), were used to examine gains in reliability of combined purebred and crossbred evaluation over conventional within-line evaluations using crossbred and pureline models. Random effects in the pureline model included additive, parental dominance, and litter. In the crossbred model, effects were as in the pureline model except traits of each line were treated as separate traits and two additive effects were present. The approximate model was the same as the pureline except it was used for all lines disregarding breed differences. The traits in the evaluation were lifetime daily gain (LDG) and backfat. When separate line evaluations were replaced by evaluations with crossbreds, mean reliabilities of predicted breeding values increased by 2 to 9% for purebreds and by 21 to 72% for crossbreds. Rank correlations between these breeding values were > 0.99 for purebreds but 0.85 to 0.87 for crossbreds. Rank correlations between predicted breeding values obtained from crossbred and approximate models were 0.98 to 0.99 for purebreds and 0.96 to 0.98 for crossbreds. When the number of crossbreds was small in comparison to purebreds, the increase in reliability by using the crossbred data and the crossbred model as opposed to purebred models was small for purebreds but large for crossbreds. The approximate model provided very similar rankings to the crossbred model for purebreds but rankings were less consistent for crossbreds.

Genetic parameter estimates from joint evaluation of purebreds and crossbreds in swine using the crossbred model.

Records on lifetime daily gain and backfat from two purebred lines A (n = 6,022), B (n = 24,170), and their reciprocal crosses C (n = 6,135) were used to estimate genetic parameters using within-line and terminal-cross models. The models that were fitted included fixed (contemporary group and sex), random additive A and(or) random additive B, random dominance, and random litter effects. Model for purebreds included only one additive effect, whereas the model for crossbreds included two additive effects. End weight was included as a covariable for backfat. Heritability estimates for lifetime daily gain were 0.26, 0.28, and 0.23 with within-line models for lines A, B, and C, respectively, and 0.26, 0.30, and 0.27 with the crossbred model, respectively. Heritability estimates for backfat were 0.52, 0.35, and 0.29 with within-line models for lines A, B, and C, respectively, and 0.51, 0.38, and 0.29 with the crossbred model, respectively. The genetic correlations between purebreds and crossbreds (r(pc)) for lifetime daily gain were 0.99 (A-C) and 0.62 (B-C); for backfat the correlations were 0.32 (A-C) and 0.70 (B-C). The amount of dominance variance from the crossbred model expressed as a proportion of phenotypic variance for lifetime daily gain was 0.39, 0.16, and 0.29 for lines A, B, and C respectively. Dominance variance for backfat was estimated as 0. A joint evaluation of purebreds and crossbreds would be most efficient with the crossbred model. The dominance variation should be accounted for lifetime daily gain.

A medium density microsatellite map of BTA10: reassignment of INRA69.

We have developed a genetic map of BTA10 based on 8952 informative meioses for 13 microsatellite markers and the erythrocyte antigen Z. With the exception of OarAE64, the support for the order of all loci in the map exceeded a LOD > 3.0. The length of the BTA10 genetic map was 87.0 centimorgans (cM). The 14-marker, sex-average map in Kosambi cM was: CSSM38-8.9-BM1237-5.2-HH8A-2.6- INRA69-10.6-TGLA378-0.8-BM6305-17.2- TGLA102-17.9-INRA96-0.3-CSRM60-9.2- DIK20-3.0-EAZ-6.7-CSSM46-3.7-SRCRSP3-1.0-OarA E64 with an average interval of 6.70 cM. The microsatellite INRA69 was recently assigned to the pseudoautosomal region of the bovine X chromosome by linkage analysis. However, we found that twopoint support for linkage between INRA69 and 15 X-linked bovine microsatellites was LOD < 0.50 in 529 reciprocal backcross and F2 fullsib progeny. We performed twopoint analyses of INRA69 against 275 markers distributed throughout the bovine genome and found significant associations with a LOD > 3.0 only between INRA69 and eight BTA10 microsatellite loci. Consequently, we excluded INRA69 from the genetic map of the X chromosome and reassign this microsatellite to BTA10.