Quantitative trait loci mapping in dairy cattle: review and meta-analysis

From an extensive review of public domain information on dairy cattle quantitative trait loci (QTL), we have prepared a draft online QTL map for dairy production traits. Most publications (45 out of 55 reviewed) reported QTL for the major milk production traits (milk, fat and protein yield, and fat and protein concentration (%)) and somatic cell score. Relatively few QTL studies have been reported for more complex traits such as mastitis, fertility and health. The collated QTL map shows some chromosomal regions with a high density of QTL, as well as a substantial number of QTL at single chromosomal locations. To extract the most information from these published records, a meta-analysis was conducted to obtain consensus on QTL location and allelic substitution effect of these QTL. This required modification and development of statistical methodologies. The meta-analysis indicated a number of consensus regions, the most striking being two distinct regions affecting milk yield on chromosome 6 at 49 cM and 87 cM explaining 4.2 and 3.6 percent of the genetic variance of milk yield, respectively. The first of these regions (near marker BM143) affects five separate milk production traits (protein yield, protein percent, fat yield, fat percent, as well as milk yield)

Prawn Morphometrics and Weight Estimation from Images using Deep Learning for Landmark Localization

Accurate morphometric analyses and weight estimation are useful in aquaculture for optimizing feeding, predicting harvest yields, identifying desirable traits for selective breeding, grading processes, and monitoring the health status of production animals. However, the collection of phenotypic data through traditional manual approaches at industrial scales and in real-time is time-consuming, labour-intensive, and prone to errors. Digital imaging of individuals and subsequent training of prediction models using Deep Learning (DL) has the potential to rapidly and accurately acquire phenotypic data from aquaculture species. In this study, we applied a novel DL approach to automate morphometric analysis and weight estimation using the black tiger prawn (Penaeus monodon) as a model crustacean. The DL approach comprises two main components: a feature extraction module that efficiently combines low-level and high-level features using the Kronecker product operation; followed by a landmark localization module that then uses these features to predict the coordinates of key morphological points (landmarks) on the prawn body. Once these landmarks were extracted, weight was estimated using a weight regression module based on the extracted landmarks using a fully connected network. For morphometric analyses, we utilized the detected landmarks to derive five important prawn traits. Principal Component Analysis (PCA) was also used to identify landmark-derived distances, which were found to be highly correlated with shape features such as body length, and width. We evaluated our approach on a large dataset of 8164 images of the Black tiger prawn (Penaeus monodon) collected from Australian farms. Our experimental results demonstrate that the novel DL approach outperforms existing DL methods in terms of accuracy, robustness, and efficiency

Software Tools 288 QTL-MLE: A MAXIMUM LIKELIHOOD QTL MAPPING PROGRAM FOR FLEXIBLE MODELLING USING THE R COMPUTING ENVIRONMENT

SUMMARY In this paper, a maximum likelihood-based procedure is described for mapping QTL in non-inbred line crosses and specifically half-sib families such as commonly found in sheep. The algorithms developed here address limitations of currently available procedures, to ensure that the most reliable information is extracted. A key feature is the use of the E-M algorithm for likelihood maximisation, as this allows standard algorithms (e.g. linear and generalised linear models) to be used, in an iterative process. A suite of programs written in R (QTL-MLE) has been developed, making use of the flexible and integrated modelling environment of that package. INTRODUCTION A large resource flock has been developed at The University of Sydney for mapping of QTL in sheep, derived between two breeds, Merino and Awassi. This is an extreme cross for many traits, including milk production, wool characteristics, and parasite resistanc

The effect of the liver fluke Fasciola gigantica infestation on the leucocyte eosinophil cell profile on sheep

Eosinophil is one of the major leucocyte cell in the blood which specifically reacted on parasite infection, thus it is important to determine its profile against the F. gigantica infection. The aims of this study is to determine the differences of the eosinophil count profiles on the different breed of sheep infected with F. gigantica and its relation with the resistance of sheep bred against parasitic disease. Four groups of sheep consist of Indonesian Thin Tail (ITT) sheep, Merino sheep, backcross sheep (10 families) and F2 sheep were infected with 300 metacercariae of Fasciola gigantica. The total sheep used in this trial is 621. Those sheep were observed for 12 weeks and the blood samples were collected every 2 weeks after infection. The results showed that total eosinophil counts in all infected sheep increased after two weeks post infection and ITT sheep showed the highest counts. On the other hand, the mean fluke counts on ITT sheep is the lowest compared with the other groups of sheep. Merino and F2 sheep had the highest mean fluke counts. Three families of backcross sheep had the mean flukes count similar to ITT sheep and the other 7 families were similar to the Merino sheep. In conclusion, the highest total eosinophil count at the early stage of infection on ITT sheep might be related with the genetic resistance, which was showed by the lowest flukes count, and the resistance was inherited to some of the backcross sheep, which had similar flukes count with ITT sheep.   Key words: Fasciola gigantica, eosinophil, shee

In vitro studies: The role of immunological cells in Indonesian thin tail sheep in the killing of the liver fluke, Fasciola gigantica

Previous studies have shown that Indonesian Thin Tail (ET) sheep exhibit high resistance to challenge with Fasciola gigantica when compared with Merino sheep, and this resistance is expressed in early infection. In order to study the role of the immune system in this resistance to ET sheep, in vitro studies were undertaken in the laboratory. In vitro study to confirm the ability of immune cells from ET sheep in the killing of F. gigantica larvae has been done by incubating immune cells and F. gigantica larvae together with immune sera or normal sera. The viability of the larvae was observed over a period 3 days incubation by observing their motility. The results showed that the cells isolated from F. gigantica- challenged ET sheep in the presence of immune sera from ET were able to kill 70% of the larvae. In contrast, cells from infected Merino were unable to kill a significant number of F. gigantica using the same sera source. It seems that the cytotoxicity was dependent on the presence of immune sera and ET peritoneal cells, suggesting the potential role of an antibody-dependent cell cytotoxic (ADCC) mechanism in the resistant ET sheep.Key words: In vitro, Fasciola gigantica, peritoneal cell, sheep gigantica

Genomic selection in aquaculture: application, limitations and opportunities with special reference to marine shrimp and pearl oysters

Within aquaculture industries, selection based on genomic information (genomic selection) has the profound potential to change genetic improvement programs and production systems. Genomic selection exploits the use of realized genomic relationships among individuals and information from genome-wide markers in close linkage disequilibrium with genes of biological and economic importance. We discuss the technical advances, practical requirements, and commercial applications that have made genomic selection feasible in a range of aquaculture industries, with a particular focus on molluscs (pearl oysters, Pinctada maxima) and marine shrimp (Litopenaeus vannamei and Penaeus monodon). The use of low-cost genome sequencing has enabled cost-effective genotyping on a large scale and is of particular value for species without a reference genome or access to commercial genotyping arrays. We highlight the pitfalls and offer the solutions to the genotyping by sequencing approach and the building of appropriate genetic resources to undertake genomic selection from first-hand experience. We describe the potential to capture large-scale commercial phenotypes based on image analysis and artificial intelligence through machine learning, as inputs for calculation of genomic breeding values. The application of genomic selection over traditional aquatic breeding programs offers significant advantages through being able to accurately predict complex polygenic traits including disease resistance; increasing rates of genetic gain; minimizing inbreeding; and negating potential limiting effects of genotype by environment interactions. Further practical advantages of genomic selection through the use of large-scale communal mating and rearing systems are highlighted, as well as presenting rate-limiting steps that impact on attaining maximum benefits from adopting genomic selection. Genomic selection is now at the tipping point where commercial applications can be readily adopted and offer significant short- and long-term solutions to sustainable and profitable aquaculture industries

Linkage disequilibrium on chromosome 6 in Australian Holstein-Friesian cattle

We analysed linkage disequilibrium (LD) in Australian Holstein-Friesian cattle by genotyping a sample of 45 bulls for 15 closely-spaced microsatellites on two regions of BTA6 reported to carry important QTL for dairy traits. The order and distance of markers were based on the USDA-MARC linkage map. Frequencies of haplotypes were estimated using the E-M approach and a more computationally-intensive Bayesian approach as implemented in PHASE. LD was then estimated using the Hedrick multiallelic extension of Lewontin normalised coefficient D'. Estimates of D' from the two approaches were in close agreement (r = 0.91). The mean estimates of D' for marker pairs with an inter-marker distance of less than 5 cM (n = 13) are 0.57 and 0.51, and for distances more than 20 cM (n = 44) are 0.29 and 0.17, estimated from the E-M and Bayesian approaches, respectively. The Malecot model was fitted for the exponential decline of LD with map distance between markers. The swept radii (the distance at which LD has declined to 1/e (~37%) of its initial value) are 11.6 and 13.7 cM for the above two methods, respectively. The Malecot model was also fitted using map distance in Mb from the bovine integrated map (bovine location database, bLDB) in addition to cM from the MARC map. Overall, the results indicate a high level of LD on chromosome 6 in Australian dairy cattle

Genetic parameters of color phenotypes of black tiger shrimp (Penaeus monodon)

Black tiger shrimp (Penaeus monodon) is the second most important aquaculture species of shrimp in the world. In addition to growth traits, uncooked and cooked body color of shrimp are traits of significance for profitability and consumer acceptance. This study investigated for the first time, the phenotypic and genetic variances and relationships for body weight and body color traits, obtained from image analyses of 838 shrimp, representing the progeny from 55 sires and 52 dams. The color of uncooked shrimp was subjectively scored on a scale from 1 to 4, with “1” being the lightest/pale color and “4” being the darkest color. For cooked shrimp color, shrimp were graded firstly by subjective scoring using a commercial grading score card, where the score ranged from 1 to 12 representing light to deep coloration which was subsequently found to not be sufficiently reliable with poor repeatability of measurement (r = 0.68–0.78) Therefore, all images of cooked color were regraded on a three-point scale from brightest and lightest colored cooked shrimp, to darkest and most color-intense, with a high repeatability (r = 0.80–0.92). Objective color of both cooked and uncooked color was obtained by measurement of RGB intensities (values range from 0 to 255) for each pixel from each shrimp. Using the “convertColor” function in “R”, the RGB values were converted to L*a*b* (CIE Lab) systems of color properties. This system of color space was established in 1976, by the International Commission of Illumination (CIE) where “L*” represents the measure of degree of lightness, values range from 0 to 100, where 0 = pure black and 100 = pure white. The value “a*” represents red to green coloration, where a positive value represents the color progression towards red and a negative value towards green. The value “b*” represents blue to yellow coloration, where a positive value refers to more yellowish and negative towards the blue coloration. In total, eight color-related traits were investigated. An ordinal mixed (threshold) model was adopted for manually (subjectively) scored color phenotypes, whereas all other traits were analyzed by linear mixed models using ASReml software to derive variance components and estimated breeding values (EBVs). Moderate to low heritability estimates (0.05–0.35) were obtained for body color traits. For subjectively scored cooked and uncooked color, EBV-based selection would result in substantial genetic improvement in these traits. The genetic correlations among cooked, uncooked and body weight traits were high and ranged from −0.88 to 0.81. These suggest for the first time that 1) cooked color can be improved indirectly by genetic selection based on color of uncooked/live shrimp, and 2) intensity of coloration is positively correlated with body weight traits and hence selection for body weight will also improve color traits in this population

The responses of eosinophil and packed cell volume (PCV) on sheep infected with Fasciola gigantica

The responses of eosinophil and packed cell volume (PCV) values were verified in infected sheep, in order to identify whether these parameters could be used to predict the flukes burden and their correlation with breed resistance. Fifteen Indonesian thin tail sheep (ET), 9 Merino sheep and 148 backcross sheep generated from mating of Merino sheep and F1 sheep (Merino X ET cross) were infected with 300 metacercariae of Fasciola gigantica. The blood samples were collected every 2 weeks by using EDTA venoject tubes in order to determine the amount of eosinophils and the PCV value. After 14 weeks of infection all of sheep were killed and the liver was collected in order to determine the number of flukes. The results showed that the amount of eosinophils increased 2 weeks after infection and reached the peak at week 4 after infection. The average of eosinophils in ET appeared higher than the other 2 breeds (Merino was the lowest and the backcross was in between). The correlation between the number of flukes recovered from the liver and the eosinophil counts were positive in ET and Merino, but negative in the backcross sheep. The PCV values remained constant along the trial, except at week 14 after infection; the PCV values were slightly decreased in backcross sheep and Merino sheep, but not in ET sheep. The correlation between number of flukes in the liver and the PCV values were negative in all breeds of sheep. These results suggested that the eosinophilic and PCV’s response of ET were higher compared to backcross and Merino sheep, thus that responses were thought to be associated with the resistant phenomenon.   Key words: Fasciolosis, eosinophil, PCV, shee