Single nucleotide polymorphisms of growth hormone gene in cattle and their association with growth traits: a systematic review.

Growth traits in livestock animals are quantitative parameters, which are often controlled by many genes including growth hormone (GH) gene. However, the evidence of effect of GH gene on growth traits of cattle is poorly understood. Hence, the objective of the study was to systematically investigate the literature on single nucleotide polymorphisms (SNPs) of GH gene and their association with growth traits in cattle from four databases Google Scholar, PubMed, ScienceDirect, and Web of Science. The results indicated that fifteen (n = 15) articles with 27% of them from Indonesia qualified to be used in this study after screening. The results revealed five SNPs (1047T > C, 1180 C > T, 86,273,136 A/G, 3338 A > G and 4251 C > T) occurred across multiple investigated breeds with no common identified SNPs. Six articles observed a significant difference (p < 0.05) between growth traits and genotypes of identified SNPs. The findings showed that 7 articles (47%) investigated body weight (BW) with 6 (40%) of them found non-significant and 1 (7%) found a significant association with genotypes of the identified SNPs (3338 A > G). While 7 articles (47%) investigated weaning weight (WW) with 5 (33%) of them revealed a non-significant and 2 (13%) found a significant association with genotypes of identified SNPs (3338 A > G and 4251 C > T). This study shows that there is a lack of evidence on effect of growth hormone gene on growth traits in cattle. However, more studies are recommended for further validation of the identified SNPs and effect of growth hormone gene on growth traits in cattle.

A systematic review of estimation of growth curve in goats.

Growth is an economically important trait in animal production industry and is one of the subjects that can be justified mathematically. The literature recommends different non-linear model to estimate the growth of goats. The objective of this study was to systematically review the literature published on estimation of growth using non-linear models in goats. Databases such as Google Scholar, PubMed, ScienceDirect, and Web of Science were evaluated systematically using the combination of the following key terms: Non-linear growth curve models such as Brody, Richards, Gompertz, Von Bertalanffy, Logistic models. A total of 25 eligible articles were found published between 2008 and 2022 in Bangladesh, Brazil, China, Egypt, Germany, India, Indonesia, Iran, Pakistan, South Africa, Turkey, Tunisia, and Vietnam. The results showed that out of 25 articles, Gompertz growth curve model was the most used (n = 10), followed by Logistic (n = 8), then Brody growth curve model (n = 6). The findings further indicated that Janoscheck growth curve model was the least used model (n = 1) for estimation of growth in goats. One of the limitations is that some of the reviewed articles did not indicate the sex of the animals which make it difficult to draw the conclude for sexes. The systematic review concludes that Gompertz growth curve model is the most recommended for estimation of growth parameters of goats, followed by Logistic, and then Brody. Therefore, researchers should consider using these models when studying growth parameters of goats.

Morphological characterization of Sussex cattle at Huntersvlei farm, Free State Province, South Africa.

Sussex cattle breed is characterized by their distinctive solid red coat colour and white tail switch. Sussex cattle are known for being easy to handle and manage, making them an ideal choice for cattle farmers. The phenotypic characterization of this cattle breed in South Africa is unknown. Hence, the objective of this study was to characterize the morphological structure, phenotypic and body indices traits of Sussex cattle in South Africa at Huntersvlei farm, Frere State province of South Africa. One hundred and one weaners (n = 101) between 6 and 8 months old (female = 57 and male = 44) and fifty yearlings between 12 and 15 months old (female = 15 and male = 35) were used in this study. Body weight at weaning, yearling and linear body measurements such as head length (HL), head width (HW), ear length (EL), ear width (EW), sternum height (SH), withers height (WH), heart girth (HG), hip height (HH), body length (BL), rump length (RL), and rump width (RW) were measured. Moreover, the animals were assessed for coat colour and horn presence. Descriptive statistics, Pearson's correlation and Principal Component Analysis (PCA) were used to describe the Sussex cattle breed. The results indicated that male Sussex cattle had highly significant (p < 0.01) mean numeric values for the BW and morphometric traits. The results further showed that Sussex cattle had highly significant (p < 0.01) increase for the BW and morphometric traits as age advances in all sexes. Interaction effect of sex and age showed a highly significant (p < 0.01) effect with BW and measured morphometric traits, while moderately significant (p < 0.05) with EW. Male Sussex cattle showed highly significant (p < 0.01) higher mean numeric values for the body index (BI), length index (LI) and compact index (CI) indices. While female Sussex animals showed highly significant (p < 0.01) mean numeric values for area index (AI) and proportionality (PR). Body weight showed a positive highly significant (p < 0.01) correlation with the measured morphometric traits except for the moderate significant (p < 0.05) correlation with EL. Coat colour traits ranged from 15 (9.93%), 103 (68.21%) to 33 (21.85%) for light, moderate and dark colours, respectively. While horn presence traits ranged from 48 (31.79%), 42 (27.81%) to 61 (40.40%) for polled, scur and horned respectively. The PCA results extracted only two components in both sexes of the animals. The morphological variations obtained in this study could be complemented by performance data and molecular markers of single nucleotide polymorphism (SNP) to guide the overall breed characterization, conservation and development of appropriate breeding and selection strategies.

Comparison of the data mining and machine learning algorithms for predicting the final body weight for Romane sheep breed.

The current study aimed to predict final body weight (weight of fourth months of age to select the future reproducers) by using birth weight, birth type, sex, suckling weight, age at suckling weight, weaning weight, age at weaning weight, and age of final body weight for the Romane sheep breed. For this purpose, classification and regression tree (CART), multivariate adaptive regression splines (MARS), and support vector machine regression (SVR) algorithms were used for training (80%) and testing (20%) sets. Different data mining and machine learning algorithms were used to predict final body weight of 393 Romane sheep (238 female and 155 male animals) were used with different artificial intelligence algorithms. The best prediction model was obtained by CART model, both training and testing set. Constructed CART models indicated that sex, suckling weight, weaning weight, age of weaning weight, and age of final weight could be used as an indirect selection measure to get a superior sheep flock on the final body weight of Romane sheep. If genetically established, the Romane sheep whose sex is female, age of final weight is over 142 days, and weaning weight is over 28 kg could be chosen for affording genetic improvement in final body weight. In conclusion, the usage of CART procedure may be worthy of reflection for identifying breed standards and choosing superior sheep for meat yield in France.

Predicting live weight using body volume formula in lactating water buffalo.

Live weight (LW) is an important piece of information within production systems, as it is related to several other economic characteristics. However, in the main buffalo-producing regions in the world, it is not common to periodically weigh the animals. We develop and evaluate linear, quadratic, and allometric mathematical models to predict LW using the body volume (BV) formula in lactating water buffalo (Bubalus bubalis) reared in southeastern Mexico. The LW (391.5 ± 138.9 kg) and BV (333.62 ± 58.51 dm3) were measured in 165 lactating Murrah buffalo aged between 3 and 10 years. The goodness-of-fit of the models was evaluated using the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), coefficient of determination (R2), mean-squared error (MSE) and root MSE (RMSE). In addition, the developed models were evaluated through cross-validation (k-folds). The ability of the fitted models to predict the observed values was evaluated based on the RMSEP, R2, and mean absolute error (MAE). LW and BV were significantly positively and strongly correlated (r = 0.81; P < 0.001). The quadratic model had the lowest values of MSE (2788.12) and RMSE (52.80). On the other hand, the allometric model showed the lowest values of BIC (1319.24) and AIC (1313.07). The Quadratic and allometric models had lower values of MSEP and MAE. We recommend the quadratic and allometric models to predict the LW of lactating Murrah buffalo using BV as a predictor.

Using Multivariate Adaptive Regression Splines to Estimate the Body Weight of Savanna Goats.

The Savanna goat breed is an indigenous goat breed in South Africa that is reared for meat production. Live body weight is an important tool for livestock management, selection and feeding. The use of multivariate adaptive regression splines (MARS) to predict the live body weight of Savanna goats remains poorly understood. The study was conducted to investigate the influence of linear body measurements on the body weight of Savanna goats using MARS. In total, 173 Savanna goats between the ages of two and five years were used to collect body weight (BW), body length (BL), heart girth (HG), rump height (RH) and withers height (WH). MARS was used as a data mining algorithm for data analysis. The best predictive model was achieved from the training dataset with the highest coefficient of determination and Pearson's correlation coefficient (0.959 and 0.961), respectively. BW was influenced positively when WH > 63 cm and HG >100 cm with a coefficient of 0.51 and 2.71, respectively. The interaction of WH > 63 cm and BL < 75 cm, WH < 68 cm and HG < 100 cm with a coefficient of 0.28 and 0.02 had a positive influence on Savanna goat BW, while male goats had a negative influence (-4.57). The findings of the study suggest that MARS can be used to estimate the BW in Savanna goats. This finding will be helpful to farmers in the selection of breeding stock and precision in the day-to-day activities such as feeding, marketing and veterinary services.

Estimation of body weight using body measurements in female water buffaloes reared in southeastern Mexico.

Buffalo farming is an important livestock activity in Mexico. However, the low technological level of the farms makes it difficult to monitor the growth rates of the animals. The objectives of this study were to analyse the body measurements of 107 adult female Murrah buffaloes, to estimate the interrelationships between those measurements and body weight, and to develop equations to predict body weight (BW) using body measurements including withers at height (WH), rump height (RH), body height (BH), heart girth (HG), abdominal girth (AG), pelvic girth (PG), body length (BL), girth circumference (GC), diagonal body length (DBL), pelvic circumference (PC), and abdomen circumference (AC). The study was conducted on two commercial farms in southern Mexico. Pearson correlation and stepwise regression techniques were used for the data analysis. To find out the best regression models, we used model quality criteria such as coefficient of determination (R2), adjusted R2 (Adj.R2), root mean square error (RMSE), Mallow's Cp, Akaike's information criteria (AIC), Bayesian information criteria (BIC), and coefficient of variation (CV). Correlation results indicated that BW had a positive high correlation (P < 0.01) of all the measured traits. Model 4 (-780.56 + 311.76GC + 383.51DBL + 51.82PC + 47.65AC-106.78BL) was the best regression model with a higher R2 (0.87), Adj. R2 (0.86) smaller Cp (4.24), AIC (749.19), BIC (752.16), and RMSE (36.91). The current study suggests that GC, DBL, PC, AC, and BL might be used in combination to estimate BW of adult female Murrah buffaloes.

Evaluation of breeding practices and morphological characterization of donkeys in Blouberg Local Municipality, Limpopo province: Implication for the design of community-based breeding programme.

Identification of livestock farmers' breeding practices and morphological characterization of livestock are the important first steps to the successful implementation of any breeding programme. Community-based breeding programme (CBBP) has gained attention as a promising method for the genetic improvement of livestock but lacks information on donkey breeding. The study was conducted to identify donkey farmers' breeding practices and donkey morphological characterization in three purposely selected villages (Thorne, Archibalt and Genau) located in Blouberg Local Municipality, Limpopo province of South Africa. Questionnaire survey method was used to collect the data from twenty-one donkey farmers while body weight and seventeen morphological traits were measured for the morphological characterization from seventy-four donkeys. Descriptive statistics and index values were computed to describe donkey breeding practices. Chi-square statistics were used to compare categorical variables among villages. General Linear Model procedure was used to compare morphological characteristics of donkeys among villages. The results revealed that there was no statistical different (P>0.05) observed on socio-economic characteristics of donkey farmers except on education level (P<0.05) among villages. Purpose of keeping donkeys, type of donkey breed kept, donkey coat colours, mating systems, reasons for culling, mating seasons and selection criterions were not significantly different (P>0.05) among villages. The most common trait preferences of donkey farmers among the surveyed villages were body size and growth rate in breeding males while in breeding females were body size, twining ability and mothering ability. The results indicated that in all the eighteen measured traits only four showed a significant difference (P<0.05) among the villages and some were significantly correlated with body weight (P<0.05). The results of this study will serves as basis for the development and implementation of CBBPs for donkey farmers at Blouberg Local Municipality of South Africa.

Predicting body weight of Kalahari Red goats from linear body measurements using data mining algorithms.

Background and Aim: The Kalahari Red goat breed is the finest meat-producing species in South Africa, and its coat color ranges from light to dark red-brown. A practical approach to estimating their body weight (BW) using linear body measurements is still scarce. Therefore, this study aimed to determine the best data mining technique among classification and regression trees (CART), Chi-square automatic interaction detection (CHAID), and exhaustive CHAID (Ex-CHAID) for predicting the BW of Kalahari Red goats. Materials and Methods: This study included 50 Kalahari Red goats (does = 42 and bucks = 8) aged 3-5 years. Body length (BL), heart girth (HG), rump height (RH), height at withers (WH), sex, and age were the essential indicators to estimate BW. The best model was chosen based on the goodness of fit, such as adjusted coefficient of determination (Adj. R2), coefficient of determination (R2), root mean square error (RMSE), standard deviation ratio (SD ratio), mean absolute percentage error, Akaike information criteria, relative approximation error, and coefficient of variation. Results: The SD values of the ratio ranged from 0.32 (CART) to 0.40 (Ex-CHAID). The greatest R2 (%) was established for CART (89.23), followed by CHAID (81.99), and the lowest was established for Ex-CHAID (81.70). CART was established as the preferred algorithm with BL, HG, and WH as critical predictors. The heaviest BW (73.50 kg) was established in four goats with BL higher than 92.5 cm. Conclusion: This study reveals that CART is the optimum model with BL, HG, and WH as the essential linear body measurements for estimating BW for Kalahari Red goats. The updated records will assist the rural farmers in making precise judgments for various objectives, such as marketing, breeding, feeding, and veterinary services in remote areas where weighing scales are unavailable.

A community-based intervention approach to control disease outbreaks and climate-related deaths in communally raised goat kids in the Eastern Cape Province, South Africa.

A community-based intervention project was conducted, from April 2017 to March 2019, on 512 kids born from flocks of 30 purposively selected households located in ten villages within Alice district of the Eastern Cape Province, South Africa. The study aimed to examine the effectiveness of combined efforts from the research team and farmers to control disease outbreaks and climate change-related deaths. A systematic dosing and fortnight dipping schedule was part of the intervention efforts made by the research team as well as supplying feed to pregnant and lactating does. Proper housing shelters were constructed and practicing hygiene measures were implemented. Veterinary assistance and medication were availed whenever there was a sick kid. Diseases and climate-related deaths were diagnosed based on clinical signs, laboratory results and relevant necropsy records. The current intervention program resulted to a decline in kid mortality rate (56.17% to 22.38%). Consistent access to veterinary services reduced the prevalence of Infectious diseases in year-2 (6.38%) as opposed to year-1 (14.89%). Climatic factors (11.92 vs 2.89%) became less prevalent due to better housing infrastructure while parasitic-related health problems showed a similar trend (9.79% vs 1.81%) after implementing a systematic dosing plan and fortnight dipping schedule. Death due to mechanical (7.66% vs 3.97%), reproductive (5.53% vs 3.25%) and nutritional (6.38% vs 2.53%)-related health problems also showed a slight decline. Even though the mortality rate was still above 20%, the documented improvement in kids' survival rate implies that the approach was a moderate success. An in-depth analysis with regard to affordability and effectiveness should be conducted to ensure consistent support.

Prediction of body weight from morphological traits of South African non-descript indigenous goats of Lepelle-Nkumbi Local Municipality using different data mining algorithm.

Body weight is a vital trait which can assist farmers on selecting animals to use during breeding season. Therefore, the study was conducted to develop the best model to predict body weight from morphological traits through classification and regression tree (CART) and chi-square automatic interaction detector (CHAID) and to determine the relationship between body weight and some morphological traits. A total of 700 South African non-descript indigenous goats (female = 417 and male = 283) between the age of 1 and 5 years old were used in the study. Body weight and some morphological traits viz. body length (BL), heart girth (HG), withers height (WH), rump height (RH), and rump length (RL) were measured in the study. CART, CHAID, and Pearson's correlation were used for data analysis. CART and CHAID algorithms indicated that predictor factors such as BL, HG, age, and villages had statistical influence on body weight of goats. The study suggests that BL can be used to estimate body weight of South African non-descript indigenous goats. Goodness of fit test suggests that CHAID is a suitable algorithm for prediction of body weight of South African non-descript indigenous goats. Correlation findings indicated that BW had positive highly statistical correlation (P < 0.01) with BL in male and female goats with correlation values of r = 0.65 and r = 0.65, respectively. Findings suggest that improving BL of South African non-descript indigenous goats might improve body weight.

Breeding practices and trait preferences of goat keepers at Lepelle-Nkumpi Local Municipality, South Africa: implication for the design of breeding programmes.

Identification of breeding practices and trait preferences by livestock keepers for the selection of breeding animals to be parents of the next generations is the crucial step to the successful implementation of community-based breeding program (CBBPs). The study aimed to detect breeding practices and trait preferences by farmers at Lepelle-Nkumpi Local Municipality, South Africa to determine their relevance in establishing a CBBP. A well-structured questionnaire was designed and administered to 183 randomly selected goat keepers from four villages. Chi-square statistics were used to compare categorical variables among villages. Socio-economic factors and reasons for keeping goats were not significantly different (P > 0.05) between the four villages. Methods of controlling mating, reasons for not controlling mating, keeping breeding bucks, source of breeding bucks, reasons for culling, and culling methods were significantly different (P < 0.05) among villages. The most common trait preferences of goat keepers among the surveyed villages were twinning ability, mothering ability, and body size in breeding does, while in breeding bucks were mating ability, growth rate, and body size. The results from this study are useful for designing CBBPs for goat production in the communal areas of Lepelle-Nkumpi Local Municipality.

Classification and regression tree analysis to predict calving ease in Sussex heifers using pelvic area dimensions and morphological traits.

OBJECTIVES: The objective of this study was to assess the relationship between pelvic measurements, namely pelvic height (PH), pelvic area (PA), and pelvic width, and linear body measurement traits, such as hindquarters width, rump length (RL), hip height (HH), body weight (BW), shoulder height, chest depth (CD), body length, and also calve birth weight (CBW) under different calving ease scores, namely no assistance, gently pull, and hard pull. MATERIAL AND METHODS: A total of 51 first calf Sussex heifers at 24 months old, weighing approximately 440 ± 40.26 kg, were used for this study. Two-year-old bulls (n = 2), weighing approximately 800 kg, were used for mating the 51 heifers with a bull to cow ratio of 1:30 and 1:21. The fertility of bulls was assessed by a private veterinarian before the mating season. Calving ease was scored as follows: 1 = no assistance during parturition (normal), 2 = heifer assistance as gently pull, 3 = heifer assistance as hard pull, 4 = heifer cannot calf, 5 = heifer calved a dead calf, and 6 = heifer calf with the abnormal position. RESULTS: Descriptive statistics indicated that PH (p < 0.01) and RL (p < 0.05) were positively remarkable and different among calving ease scores. Correlation results of the no assistance Sussex heifers group revealed that CBW was positively correlated (p < 0.05) with PH. Classification and regression tree CART results demonstrated that PH, BW, CD, and HH play an important role in predicting calving ease in Sussex heifers. CONCLUSION: The findings suggest that there is an association among PAs and biometric traits. The present study might help farmers select animals with higher PH, BW, CD, and HH during breeding to lower dystocia incidents during parturition. However, further studies need to be carried out in CART modeling to reduce dystocia in a larger sample size of Sussex heifers or other cattle breeds.

Comparison of tree-based regression tree methods for predicting live body weight from morphological traits in Hy-line silver brown commercial layer and indigenous Potchefstroom Koekoek breeds raised in South Africa.

In animal breeding, more considerable attention is drawn to reveal the relationship between live body weight and morphological traits in identifying breed and species standards. The aim of this study was to predict live body weight from morphological characteristics in the Hy-line silver brown commercial layer and indigenous Potchefstroom Koekoek breed, native to South African. In the prediction of live body weight, eleven morphological measurements, i.e., wing length, back length, beak length, shank length, shank circumference, chest circumference, wingspan, keel length, body girth, toe length, and body length, were taken. As tree-based regression tree methods, predictive performances of CART, CHAID, and exhaustive CHAID algorithms were measured for body weight prediction. Among those, CART was found to be the best decision tree algorithm that gave the highest predictive accuracy. CART visual results reflected that the heaviest body weight mean (2.000 kg) was obtained from the chickens with 10.250 cm < WL ≤ 10.500 cm. As a result, it could be suggested that the CART decision tree might help to determine breed standards of the Hy-line silver brown commercial layer and, especially, indigenous Potchefstroom Koekoek breeds for breeding programs.

Effects of RAC1 on Proliferation of Hen Ovarian Prehierarchical Follicle Granulosa Cells.

RAC1 belongs to the small G protein Rho subfamily and is implicated in regulating gene expression, cell proliferation and differentiation in mammals and humans; nevertheless, the function of RAC1 in growth and development of hen ovarian follicles is still unclear. This study sought to understand the biological effects of RAC1 on granulosa cell (GC) proliferation and differentiation of hen ovarian prehierarchical follicles. Firstly, our results showed expression levels of RAC1 mRNA in the follicles with diameters of 7.0-8.0 mm, 6.0-6.9 mm and 1.0-3.9 mm were greater than other follicles (p < 0.05). The RAC1 protein was mainly expressed in oocyte and its around GCs and stromal tissues of the prehierarchical follicles by immunohistochemistry. Further investigation revealed the RAC1 gene remarkably enhanced the mRNA and protein expression levels of FSHR (a marker of follicle selection), CCND2 (a marker of cell-cycle progression and GC differentiation), PCNA (a marker of GC proliferation), StAR and CYP11A1 (markers of GC differentiation and steroidogenesis) (p < 0.05). Furthermore, our data demonstrated siRNA interference of RAC1 significantly reduced GC proliferation (p < 0.05), while RAC1 gene overexpression enhanced GC proliferation in vitro (p < 0.05). Collectively, this study provided new evidence that the biological effects of RAC1 on GC proliferation, differentiation and steroidogenesis of chicken ovary follicles.

Effect of Dietary Fiber Sources on In-Vitro Fermentation and Microbiota in Monogastrics.

Feed fiber composition is usually considered as one of the factors that have an impact on digestive tract microbiota composition. The investigations on the level of fermentation and in-vitro digestibility of different fibers are not well understood. The aim of the current study is to determine the effect of different fiber sources on intestinal nutrient digestibility, hindgut fermentation, and microbial community composition under in vitro conditions using pigs' hindgut as a model. The experimental treatment diets contained alfalfa hay, cornstalk, and rice straw. Cornstalk treatment displayed higher digestibility compared to alfalfa hay and rice straw; similar results were observed with in-vitro digestibility using intestinal digesta. Firmicutes were the most abundant phyla (Firmicutes = 89.2%), and Lactobacillus were the prominent genera (75.2%) in response to alfalfa compared to rice straw and cornstalk treatments. In simulated in-vitro digestion, corn stalk fiber improved dry matter digestibility; rice straw fiber improved volatile fatty acid content and fermentation efficiency. Alfalfa fiber improved the thickness of deposited Firmicutes and Lactobacillus.

Determination of the roles of GREM1 gene in granulosa cell proliferation and steroidogenesis of hen ovarian prehierarchical follicles.

Gremlin genes are known members of the DAN family of bone morphogenetic protein (BMP) antagonists, but their functions and regulatory mechanisms in ovarian follicular development of chicken remain unknown. The current study was designed to investigate the mRNA expression patterns of gremlin1 gene (GREM1) and its protein location in the follicles sampled, and to explore the biological effect of GREM1 on the prehierarchical follicular development. This work revealed that chicken GREM1 mRNA exhibits a constant expression level across all the prehierarchical follicles (PFs) from 1-4 mm to 7-8 mm in diameter, and the preovulatory follicles (from F6 to F1) by using RT-qPCR (P > 0.05). The GREM1 protein is predominantly expressed in the oocytes and granulosa cells (GCs) of the PFs by immunohistochemistry. Furthermore, our data demonstrated that siRNA-mediated knockdown of GREM1 in the GCs resulted in a significant reduction in cell proliferation (P < 0.001); conversely, overexpression of GREM1 in the GCs led to a remarkable increase in cell proliferation (P < 0.001). Interestingly, the expression levels of proliferating cell nuclear antigen (PCNA) and cyclin D2 (CCND2) mRNA and proteins were notably increased when GREM1 expression was upregulated in the GCs (P < 0.01), however, the expression levels of CYP11A1 and StAR were markedly downregulated (P < 0.01). The current results showed that GREM1 gene plays a stimulatory role in GC proliferation during growth and development of the prehierarchical follicles in vitro but an inhibitory role in GC differentiation and steroidogenesis of the hen ovary follicles.

Correlation and path analysis of body weight and biometric traits of Nguni cattle breed.

OBJECTIVE: This work was conducted to examine the association between body weight (BW) and biometric traits viz. head width (HW), head length (HL), ear length (EL), body length (BL), rump height (RH), withers height (WH), sternum height (SH), rump width (RW), and heart girth (HG) and to determine the direct and indirect effects of biometric traits on BW. MATERIALS AND METHODS: Sixty female and twenty male Nguni cattle between the ages of one to four years were used. Pearson correlation and path analysis were used for data analysis. RESULTS: Correlation results recognized that BW had a positive highly significant correlation with RW (r = 0.70**), RH (r = 0.90**), HG (r = 0.90**), SH (r = 0.90**), and WH (r = 0.93**) in male, whereas SH (r = 0.34**), WH (r = 0.55**), RH (r = 0.70**), and HG (r = 0.76**) had a positive highly significant correlation with BW of female Nguni cattle. Path analysis showed that RW (13.35) had the highest direct effect, whereas SH had an indirect effect on BW of male Nguni cattle. In female Nguni cattle, RH (4.87) had the highest direct effect, whereas HL had an indirect effect on BW. CONCLUSION: Association findings suggest that improvement of RW, RH, HG, SH, HG, and WH might result in the increase in BW of Nguni cattle. Path analysis results suggest that RW and RH might be used as a selection criterion during breeding to increase BW of Nguni cattle. The results of the current study might be used by cattle farmers to estimate BW using biometric traits.

Genetic effects of the transcription factors-sal-like 1 and spalt-like transcription factor 3 on egg production-related traits in Chinese Dagu hens.

Transcription factors (TFs) encoded by SALL1 and SALL3 genes play central roles in the regulation of ovarian development in hens. The present study aimed to examine polymorphisms of these two genes in Chinese Dagu chickens, and to identify the effects of TFs on the laying performance. Among the population, two novel single-nucleotide polymorphisms (SNPs) were identified by single-strand conformation polymorphism (SSCP) in the amplicons of the candidate genes. The effect of the SNP (729C > A) in exon 2 of SALL1 gene on egg production at 43, 57, and 66 weeks and EW at 30 and 43 weeks were the most significant in the 360 samples (P < 0.05). Moreover, for the SNP 1014T > A (in exon 2 of SALL3), the TT genotype was significantly correlated with higher egg production and EW (P < 0.05). Furthermore, four combined genotypes were reconstructed based on the two SNPs. The combined genotype TATT was correlated with the highest egg production at 43-66 weeks and with higher EW at 30, 43 weeks (P < 0.05). The polymorphisms of the two TFs studied are potential molecular genetic markers for chicken breeding, which might help in understanding the genetic structure of laying performance and improving these traits directly by marker-assisted selection (MAS).

Sequence variations in estrogen receptor 1 and 2 genes and their association with egg production traits in Chinese Dagu chickens.

Estrogen receptors α (ESR1) and ß (ESR2) play central roles in folliculogenesis and therefore in reproductive biology. In the present study, two single nucleotide polymorphisms (SNPs) were identified in the ESR1 and ESR2 genes using PCR-single strand conformation polymorphism (PCR-SSCP) and DNA sequencing. One of the identified SNPs, a T1101C transition located within exon 4 of the ESR1 gene, was significantly associated with hen-housed egg production (HHEP) at 30, 43, 57 and 66 weeks of age (P<0.05), and egg weight (EW) at 30 weeks (P<0.05). Another SNP, a G1755A transition leading to a non-synonymous substitution (valine 459-to-isoleucine) located within exon 8 of the ESR2 gene, was also markedly correlated with the HHEP at 30, 43, 57 and 66 weeks of age (P<0.05), and EW at 30 weeks (P<0.05). A greater proportion of the additive variance was explained by the SNPs for most of the associated egg production traits (>1%). Furthermore, the results of the combined genotype-based association analysis supported the finding that the two SNPs were associated with the traits under a study. Taken together, our findings suggest that the two sequence variations in the ESR1 and ESR2 genes may provide promising genetic markers for the early selection and prediction of advantageous phenotypes in chicken breeding.