Identification of Monoallelically Expressed Genes Associated with Economic Traits in Hanwoo (Korean Native Cattle)

Hanwoo, an indigenous Korean cattle breed, has been genetically improved by selecting superior sires called Korean-proven bulls. However, cows still contribute half of the genetic stock of their offspring, and allelic-specific expressed genes have potential, as selective targets of cows, to enhance genetic gain. The aim of this study is to identify genes that have MAEs based on both the genome and transcriptome and to estimate their effects on breeding values (BVs) for economically important traits in Hanwoo. We generated resequencing data for the parents and RNA-sequencing data for the muscle, fat, and brain tissues of the offspring. A total of 3801 heterozygous single nucleotide polymorphisms (SNPs) in offspring were identified and they were located in 1569 genes. Only 14 genes showed MAE (seven expressing maternal alleles and seven expressing paternal alleles). Tissue-specific MAE was observed, and LANCL1 showed maternal allele expression across all tissues. MAE genes were enriched for the biological process of cell death and angiogenesis, which included ACKR3 and PDCL3 genes, whose SNPs were significantly associated with BVs of lean meat production-related traits, such as weight at 12 months of age, carcass weight, and loin eye area. In the current study, monoallelically expressed genes were identified in various adult tissues and these genes were associated with genetic capacity in Hanwoo.

Use of a Graph Neural Network to the Weighted Gene Co-expression Network Analysis of Korean Native Cattle

In the general framework of the weighted gene co-expression network analysis (WGCNA), a hierarchical clustering algorithm is commonly used to module definition. However, hierarchical clustering depends strongly on the topological overlap measure. In other words, this algorithm may assign two genes with low topological overlap to different modules even though their expression patterns are similar. Here, a novel gene module clustering algorithm for WGCNA is proposed. We develop a gene module clustering network (gmcNet), which simultaneously addresses single-level expression and topological overlap measure. The proposed gmcNet includes a “co-expression pattern recognizer" (CEPR) and “module classifier". The CEPR incorporates expression features of single genes into the topological features of co-expressed ones. Given this CEPR-embedded feature, the module classifier computes module assignment probabilities. We validated gmcNet performance using 4,976 genes from 20 native Korean cattle. We observed that the CEPR generates more robust features than single-level expression or topological overlap measure. Given the CEPR-embedded feature, gmcNet achieved the best performance in terms of modularity (0.261) and the differentially expressed signal (27.739) compared with other clustering methods tested. Furthermore, gmcNet detected some interesting biological functionalities for carcass weight, backfat thickness, intramuscular fat, and beef tenderness of Korean native cattle. Therefore, gmcNet is a useful framework for WGCNA module clustering.

Financial loss due to foot and mouth disease outbreak in cattle in some affected areas of Bangladesh

Foot and mouth disease (FMD) is a severe and highly contagious disease that causes immense financial losses due to mortality, reduced milk production, treatment cost of affected cattle, weight loss of fattening cattle and manpower loss for taking care of affected cattle, which occurs in Bangladesh almost every year. Outbreak of this disease causes financial loss to the farmers as well as the national economy of Bangladesh. Therefore, an attempt was made to assess the morbidity and mortality by FMD and to estimate financial loss incurred therein. For this study, data were collected from 850 affected households of Dhaka, Rajshahi, Rangpur, Khulna and Chattogram divisions of Bangladesh during July 2017 to June 2018 using a pre-tested interview schedule responding to the study objectives. In total, there were 4857 crossbred and 2138 native cattle in the affected household. The study revealed that the overall morbidity and mortality rates were 55.43% and 5.15%, respectively in crossbred cattle and 77.83% and 12.39%, respectively in native cattle and it differed significantly (p<0.01) with areas and category of cattle. Infection period for an FMD affected crossbred cattle were an average of 18.46±0.27 days and for native cattle were an average of 19.56±0.40 days. The total financial loss due to the FMD outbreak was calculated as Taka 53172067 (Tk. 53.17 million or US$ 0.63 million) for 850 affected households. The percentage of loss incurred was the highest for the death of affected cattle (63.47%) followed by veterinary cost (10.71%), weight loss of fattening cattle (10.68%), reduction in milk yield (9.17%) and manpower loss for taking care of affected cattle (5.98%). Based on this calculation the projected financial loss due to the FMD outbreak would be Taka 18856.96 crore (Tk. 188.57 billion or US$ 2.22 billion) per year in Bangladesh. Bang. J. Livs. Res. Vol. 27 (1&2), 2020: P. 82-94

Market weight, slaughter age, and yield grade to determine economic carcass traits and primal cuts yield of Hanwoo beef

ObjectiveThis study was conducted to evaluate the relationship between market weight, slaughter age, yield grade, and primal cut yield in Hanwoo. MethodsA total of 403 Hanwoo (Korean native cattle) was assessed for carcass traits such as carcass cold weight, backfat thickness, ribeye area, dressing percentage, yield index, and marbling score. The production yield of the individual major primal cuts of Hanwoo beef was also measured. FindingsCarcass cold weight, ribeye area, and backfat thickness, which affect meat quality increased with increased market weight (p<0.05). The production yield of the ten major primal cuts also increased with increased market weight (p<0.05). In terms of slaughter age, carcass cold weight, ribeye area, and backfat thickness all increased from 25 months to 28-29 months, and the production yield of all prime cuts also increased with increasing slaughter age. According to the meat yield grade, carcass cold weight and backfat thickness increased from grade A to grade C, although the ribeye area was not affected. The combined findings of the study suggest that slaughtering Hanwoo at the weight of 651-700 kg and 701-750 and age of 28.23 and 29.83 months might be desirable to achieve the best quality and quantity grade of Hanwoo beef. However, the positive correlation of carcass cold weight and backfat thickness, and the negative correlation of the yield index according to primal cuts yield indicated that it is necessary to couple the slaughtering management of cattle with improved genetic and breeding method of Hanwoo to increase the production yield of the major prime cuts of Hanwoo beef.

Use of a graph neural network to the weighted gene co-expression network analysis of Korean native cattle

In the general framework of the weighted gene co-expression network analysis (WGCNA), a hierarchical clustering algorithm is commonly used to module definition. However, hierarchical clustering depends strongly on the topological overlap measure. In other words, this algorithm may assign two genes with low topological overlap to different modules even though their expression patterns are similar. Here, a novel gene module clustering algorithm for WGCNA is proposed. We develop a gene module clustering network (gmcNet), which simultaneously addresses single-level expression and topological overlap measure. The proposed gmcNet includes a “co-expression pattern recognizer” (CEPR) and “module classifier”. The CEPR incorporates expression features of single genes into the topological features of co-expressed ones. Given this CEPR-embedded feature, the module classifier computes module assignment probabilities. We validated gmcNet performance using 4,976 genes from 20 native Korean cattle. We observed that the CEPR generates more robust features than single-level expression or topological overlap measure. Given the CEPR-embedded feature, gmcNet achieved the best performance in terms of modularity (0.261) and the differentially expressed signal (27.739) compared with other clustering methods tested. Furthermore, gmcNet detected some interesting biological functionalities for carcass weight, backfat thickness, intramuscular fat, and beef tenderness of Korean native cattle. Therefore, gmcNet is a useful framework for WGCNA module clustering.Author summaryA graph neural network is a good alternative algorithm for WGCNA module clustering. Even though the graph-based learning methods have been widely applied in bioinformatics, most studies on WGCNA did not use graph neural network for module clustering. In addition, existing methods depend on topological overlap measure of gene pairs. This can degrade similarity of expression not only between modules, but also within module. On the other hand, the proposed gmcNet, which works similar to message-passing operation of graph neural network, simultaneously addresses single-level expression and topological overlap measure. We observed the higher performance of gmcNet comparing to existing methods for WGCNA module clustering. To adopt gmcNet as clustering algorithm of WGCNA, it remains future research issues to add noise filtering and optimal k search on gmcNet. This further research will extend our proposed method to be a useful module clustering algorithm in WGCNA. Furthermore, our findings will be of interest to computational biologists since the studies using graph neural networks to WGCNA are still rare.

Astrovirus Infection in Cattle with Nonsuppurative Meningoencephalitis in South Korea

Neurological diseases in cattle can be caused by several infectious agents. Astroviruses are increasingly recognized as the causative agent of encephalitis in various animals, including humans. In this study, a neuroinvasive astrovirus (BoAstV 20B05) was discovered in the brain tissues of an 81-month-old Korean native cattle with neurological symptoms. Lymphocyte infiltration and multifocal perivascular cuffing were observed in the cerebrum and brain stem, and viral antigens were also detected in the meninges. In particular, the concentration of the astroviral genome was high in the brain tissues. Korean BoAstV 20B05 was classified into the CH13/NeuroS1 clade and was closely related to the Neuro-Uy and KagoshimaSR28-462 strains. Our evolutionary analysis showed that Korean BoAstV 20B05 belongs to the sub-lineage NeuroS1 and evolved independently of BoAstV KagoshimaSR28-462. These results suggest that neuroinvasive astroviruses were first introduced in Korea. However, analysis is limited by the lack of reference astrovirus sequences reported in various countries within Asia, and further analysis should be performed using more strains. In this study, we identified a neuroinvasive astrovirus infection with neurological symptoms for the first time in South Korea and confirmed that BoAstV 20B05 may have been introduced in South Korea a long time ago.

Naturally Occurring Glycosidases in Milk from Native Cattle Breeds: Activity and Consequences on Free and Protein Bound-Glycans

Little is known about the extent of variation and activity of naturally occurring milk glycosidases and their potential to degrade milk glycans. A multi-omics approach was used to investigate the relationship between glycosidases and important bioactive compounds such as free oligosaccharides and O-linked glycans in bovine milk. Using 4-methylumbelliferone (4-MU) assays activities of eight indigenous glycosidases were determined, and by mass spectrometry and 1H NMR spectroscopy various substrates and metabolite products were quantified in a subset of milk samples from eight native North European cattle breeds. The results showed a clear variation in glycosidase activities among the native breeds. Interestingly, negative correlations between some glycosidases including β-galactosidase, N-acetyl-β-d-glucosaminidase, certain oligosaccharide isomers as well as O-linked glycans of κ-casein were revealed. Further, a positive correlation was found for free fucose content and α-fucosidase activity (r = 0.37, p-value < 0.001) indicating cleavage of fucosylated glycans in milk at room temperature. The results obtained suggest that milk glycosidases might partially degrade valuable glycans, which would result in lower recovery of glycans and thus represent a loss for the dairy ingredients industry if these activities are pronounced.