Genetic background of hematological parameters in Holstein cattle based on genome-wide association and RNA sequencing analyses.

Hematological parameters refer to the assessment of changes in the number and distribution of blood cells, including leukocytes (LES), erythrocytes (ERS), and platelets (PLS), which are essential for the early diagnosis of hematological system disorders and other systemic diseases in livestock. In this context, the primary objectives of this study were to investigate the genomic background of 19 hematological parameters in Holstein cattle, focusing on LES, ERS, and PLS blood components. Genetic and phenotypic (co)variances of hematological parameters were calculated based on the average information restricted maximum likelihood method and 1,610 genotyped individuals and 5,499 hematological parameter records from 4,543 cows. Furthermore, we assessed the genetic relationship between these hematological parameters and other economically important traits in dairy cattle breeding programs. We also carried out genome-wide association studies and candidate gene analyses. Blood samples from 21 primiparous cows were used to identify candidate genes further through RNA sequencing (RNA-seq) analyses. Hematological parameters generally exhibited low-to-moderate heritabilities ranging from 0.01 to 0.29, with genetic correlations between them ranging from -0.88 ± 0.09 (between mononuclear cell ratio and lymphocyte cell ratio) to 0.99 ± 0.01 (between white blood cell count and granulocyte cell count). Furthermore, low-to-moderate approximate genetic correlations between hematological parameters with one longevity, 4 fertility, and 5 health traits were observed. One hundred ninety-nine significant SNP located primarily on the Bos taurus autosomes (BTA) BTA4, BTA6, and BTA8 were associated with 16 hematological parameters. Based on the RNA-seq analyses, 6,687 genes were significantly downregulated and 4,119 genes were upregulated when comparing 2 groups of cows with high and low phenotypic values. By integrating genome-wide association studies (GWAS), RNA-seq, and previously published results, the main candidate genes associated with hematological parameters in Holstein cattle were ACRBP, ADAMTS3, CANT1, CCM2L, CNN3, CPLANE1, GPAT3, GRIP2, PLAGL2, RTL6, SOX4, WDFY3, and ZNF614. Hematological parameters are heritable and moderately to highly genetically correlated among themselves. The large number of candidate genes identified based on GWAS and RNA-seq indicate the polygenic nature and complex genetic determinism of hematological parameters in Holstein cattle.

Estimation of genetic parameters and single-step genome-wide association studies for milk urea nitrogen in Holstein cattle.

The main objectives of this study were to estimate genetic parameters for milk urea nitrogen (MUN) in Holstein cattle and to conduct a single-step (ss)GWAS to identify candidate genes associated with MUN. Phenotypic measurements from 24,435 Holstein cows were collected from March 2013 to July 2019 in 9 dairy farms located in the Beijing area, China. A total of 2,029 cows were genotyped using the Illumina 150K Bovine Bead Chip, containing 121,188 SNP. A single-trait repeatability model was used to evaluate the genetic background of MUN. We found that MUN is a trait with low heritability (0.06 ± 0.004) and repeatability (0.12). Considering similar milk production levels, a lower MUN concentration indicates higher nitrogen digestibility. The genetic correlations between MUN and milk yield, net energy concentration, fat percentage, protein percentage, and lactose percentage were positive and ranged from 0.02 to 0.26. The genetic correlation between MUN and somatic cell score (SCS) was negative (-0.18), indicating that animals with higher MUN levels tend to have lower SCS. Both ssGWAS and pathway enrichment analyses were used to explore the genetic mechanisms underlying MUN. A total of 18 SNP (located on BTA11, BTA12, BTA14, BTA17, and BTA18) were found to be significantly associated with MUN. The genes CFAP77, CAMSAP1, CACNA1B, ADGRB1, FARP1, and INTU are considered to be candidate genes for MUN. These candidate genes are associated with important biological processes such as protein and lipid metabolism and binding to specific proteins. This set of candidate genes, metabolic pathways, and their functions provide a better understanding of the genomic architecture and physiological mechanisms underlying MUN in Holstein cattle.

Epigenomics of rats' liver and its cross-species functional annotation reveals key regulatory genes underlying short term heat-stress response.

Molecular responses to heat stress are multifaceted and under a complex cellular post-transcriptional control. This study explores the epigenetic and transcriptional alterations induced by heat stress (42 °C for 120 min) in the liver of rats, by integrating ATAC-seq, RNA-Seq, and WGBS information. Out of 2586 differential ATAC-seq peaks induced by heat stress, 36 up-regulated and 22 down-regulated transcript factors (TFs) are predicted, such as Cebpα, Foxa2, Foxo4, Nfya and Sp3. Furthermore, 150,189 differentially methylated regions represent 2571 differentially expressed genes (DEGs). By integrating all data, 45 DEGs are concluded as potential heat stress response markers in rats. To comprehensively annotate and narrow down predicted markers, they are integrated with GWAS results of heat stress parameters in cows, and PheWAS data in humans. Besides better understanding of heat stress responses in mammals, INSR, MAPK8, RHPN2 and BTBD7 are proposed as candidate markers for heat stress in mammals.

Genetic parameters for dairy calf and replacement heifer wellness traits and their association with cow longevity and health indicators in Holstein cattle.

High mortality and involuntary culling rates cause great economic losses to the worldwide dairy cattle industry. However, there is low emphasis on wellness traits in replacement animals (dairy calves and replacement heifers) during their development stages in modern dairy cattle breeding programs. Therefore, the main objectives of this study were to estimate genetic parameters of wellness traits in replacement cattle (replacement wellness traits) and obtain their genetic correlations with 12 cow health and longevity traits in the Chinese Holstein population. Seven replacement wellness traits were analyzed, including birth weight, survival from 3 to 60 d (Sur1), survival from 61 to 365 d (Sur2), survival from 366 d to the first calving (Sur3), calf diarrhea, calf pneumonia, and calf serum total protein (STP). Single and bivariate animal models were employed to estimate (co)variance components using the data from 189,980 Holstein cattle. The genetic correlations between replacement wellness traits and cow longevity, health traits were calculated by employing bivariate models, including 6 longevity traits and 6 health traits (clinical mastitis, metritis, ketosis, displaced abomasum, milk fever, and hoof health or hoof disease). The estimated heritabilities (± SE) were 0.335 (± 0.008), 0.088 (± 0.005), 0.166 (± 0.006), 0.102 (±0 .006), 0.048 (± 0.003), 0.063 (± 0.004), and 0.170 (± 0.019) for birth weight, Sur1, Sur2, Sur3, pneumonia, diarrhea, and STP, respectively. The majority of the genetic correlations among the 7 replacement wellness traits were negligible. The genetic correlations among Sur1, Sur2, and Sur3 ranged from 0.112 (Sur1 and Sur3) to 0.445 (Sur1 and Sur2) when fitting a linear model (estimates in the observed scale), and from 0.560 (Sur1 and Sur3) to 0.773 (Sur1 and Sur2) when fitting a threshold model (estimates in the liability scale). The genetic correlations between replacement wellness and cow longevity were low (absolute value lower than 0.30), but some of them were significantly different from zero. Compared with other replacement wellness traits, Sur3 and STP had relatively high genetic correlations with cow longevity. Replacement wellness traits are heritable and can be improved through direct genetic and genomic selection. The results from the current study will contribute for better balancing dairy cattle breeding goals to genetically improve dairy cattle wellness in the period from birth to first calving.

Predicting nitrogen use efficiency, nitrogen loss and dry matter intake of individual dairy cows in late lactation by including mid-infrared spectra of milk samples.

BACKGROUND: Nitrate leaching to groundwater and surface water and ammonia volatilization from dairy farms have negative impacts on the environment. Meanwhile, the increasing demand for dairy products will result in more pollution if N losses are not controlled. Therefore, a more efficient, and environmentally friendly production system is needed, in which nitrogen use efficiency (NUE) of dairy cows plays a key role. To genetically improve NUE, extensively recorded and cost-effective proxies are essential, which can be obtained by including mid-infrared (MIR) spectra of milk in prediction models for NUE. This study aimed to develop and validate the best prediction model of NUE, nitrogen loss (NL) and dry matter intake (DMI) for individual dairy cows in China. RESULTS: A total of 86 lactating Chinese Holstein cows were used in this study. After data editing, 704 records were obtained for calibration and validation. Six prediction models with three different machine learning algorithms and three kinds of pre-processed MIR spectra were developed for each trait. Results showed that the coefficient of determination (R2) of the best model in within-herd validation was 0.66 for NUE, 0.58 for NL and 0.63 for DMI. For external validation, reasonable prediction results were only observed for NUE, with R2 ranging from 0.58 to 0.63, while the R2 of the other two traits was below 0.50. The infrared waves from 973.54 to 988.46 cm-1 and daily milk yield were the most important variables for prediction. CONCLUSION: The results showed that individual NUE can be predicted with a moderate accuracy in both within-herd and external validations. The model of NUE could be used for the datasets that are similar to the calibration dataset. The prediction models for NL and 3-day moving average of DMI (DMI_a) generated lower accuracies in within-herd validation. Results also indicated that information of MIR spectra variables increased the predictive ability of models. Additionally, pre-processed MIR spectra do not result in higher accuracy than original MIR spectra in the external validation. These models will be applied to large-scale data to further investigate the genetic architecture of N efficiency and further reduce the adverse impacts on the environment after more data is collected.

Light-Addressable Nanoclusters of Ultrasmall Iron Oxide Nanoparticles for Enhanced and Dynamic Magnetic Resonance Imaging of Arthritis.

Design of novel nanoplatforms with single imaging elements for dynamic and enhanced T 1/T 2-weighted magnetic resonance (MR) imaging of diseases still remains significantly challenging. Here, a facile strategy to synthesize light-addressable ultrasmall Fe3O4 nanoparticles (NPs) that can form nanoclusters (NCs) under laser irradiation for enhanced and dynamic T 1/T 2-weighted MR imaging of inflammatory arthritis is reported. Citric acid-stabilized ultrasmall Fe3O4 NPs synthesized via a solvothermal approach are linked with both the arthritis targeting ligand folic acid (FA) and light-addressable unit diazirine (DA) via polyethylene glycol (PEG) spacer. The formed ultrasmall Fe3O4-PEG-(DA)-FA NPs are cytocompatible, display FA-mediated targeting specificity to arthritis-associated macrophage cells, and can form NCs upon laser irradiation to have tunable r 1 and r 2 relaxivities by varying the laser irradiation duration. With these properties owned, the designed Fe3O4-PEG-(DA)-FA NPs can be used for T 1-weighted MR imaging of arthritis without lasers and enhanced dual-mode T 1/T 2-weighted MR imaging of arthritis under laser irradiation due to the formation of NCs that have extended accumulation within the arthritis region and limited intravasation back to the blood circulation. The designed light-addressable Fe3O4-PEG-(DA)-FA NPs may be used as a promising platform for dynamic and precision T 1/T 2-weighted MR imaging of other diseases.