Genome-wide association study for residual concentrate intake using different approaches in Italian Brown Swiss

Genetic evaluations and genome-wide association studies for specific digital dermatitis diagnoses in dairy cows considering genotype × housing system interactions

The present study aimed to use detailed phenotyping for the claw disorder digital dermatitis (DD) considering specific DD stages in 2 housing systems (conventional cubicle barns [CON] and compost-bedded pack barns [CBPB]) to infer possible genotype × housing system interactions. The DD stages included 2,980 observations for the 3 traits DD-sick, DD-acute, and DD-chronic from 1,311 Holstein-Friesian and 399 Fleckvieh-Simmental cows. Selection of the 5 CBPB and 5 CON herds was based on a specific protocol to achieve a high level of herd similarity with regard to climate, feeding, milking system, and location, but with pronounced housing-system differences. Five other farms had a "mixed system" with 2 subherds, one representing CBPB and the other one CON. The CBPB system was represented by 899 cows (1,530 observations), and 811 cows (1,450 observations) represented the CON system. The average disease prevalence was 20.47% for DD-sick, 13.88% for DD-acute, and 5.34% for DD-chronic, with a higher prevalence in CON than in CBPB. After quality control of 50K genotypes, 38,495 SNPs from 926 cows remained for the ongoing genomic analyses. Genetic parameters for DD-sick, DD-acute, and DD-chronic were estimated by applying single-step approaches for single-trait repeatability animal models considering the whole dataset, and separately for the CON and CBPB subsets. Genetic correlations between same DD traits from different housing systems, and between DD-sick, DD-chronic, and DD-acute, were estimated via bivariate animal models. Heritabilities based on the whole dataset were 0.16 for DD-sick, 0.14 for DD-acute, and 0.11 for DD-chronic. A slight increase of heritabilities and genetic variances was observed in CON compared with the "well-being" CBPB system, indicating a stronger genetic differentiation of diseases in a more challenging environment. Genetic correlations between same DD traits recorded in CON or CBPB were close to 0.80, disproving obvious genotype × housing system interactions. Genetic correlations among DD-sick, DD-acute and DD-chronic ranged from 0.58 to 0.81. SNP main effects and SNP × housing system interaction effects were estimated simultaneously via GWAS, considering only the phenotypes from genotyped cows. Ongoing annotations of potential candidate genes focused on chromosomal segments 100 kb upstream and downstream from the significantly associated candidate SNP. GWAS for main effects indicated heterogeneous Manhattan plots especially for DD-acute and DD-chronic, indicating particularities in disease pathogenesis. Nevertheless, a few shared annotated potential candidate genes, that is, METTL25, AFF3, PRKG1, and TENM4 for DD-sick and DD-acute, were identified. These genes have direct or indirect effects on disease resistance or immunology. For the SNP × housing system interaction, the annotated genes ASXL1 and NOL4L on BTA 13 were relevant for DD-sick and DD-acute. Overall, the very similar genetic parameters for the same traits in different environments and negligible genotype × housing system interactions indicate only minor effects on genetic evaluations for DD due to housing-system particularities.

Genes involved in the cholecystokinin receptor signaling map were differentially expressed in the jejunum of steers with variation in residual feed intake

The jejunum is a critical site for nutrient digestion and absorption, and variation in its ability to take up nutrients within the jejunum is likely to affect feed efficiency. The purpose of this study was to determine differences in gene expression in the jejunum of beef steers divergent for residual feed intake (RFI) in one cohort of steers (Year 1), and to validate those genes in animals from a second study (Year 2). Steers from Year 1 (n = 16) were selected for high and low RFI. Jejunum mucosal tissue was obtained for RNA-seq. Thirty-two genes were differentially expressed (PFDR≤0.15), and five were over-represented in pathways including inflammatory mediator, cholecystokinin receptor (CCKR) signaling, and p38 MAPK pathways. Several differentially expressed genes (ALOX12, ALPI, FABP6, FABP7, FLT1, GSTA2, MEF2B, PDK4, SPP1, and TTF2) have been previously associated with RFI in other studies. Real-time qPCR was used to validate nine differentially expressed genes in the Year 1 steers used for RNA-seq, and in the Year 2 validation cohort. Six genes were validated as differentially expressed (P < 0.1) using RT-qPCR in the Year 1 population. In the Year 2 population, five genes displayed the same direction of expression as the Year 1 population and 3 were differentially expressed (P < 0.1). The CCKR pathway is involved in digestion, appetite control, and regulation of body weight making it a compelling candidate for feed efficiency in cattle, and the validation of these genes in a second population of cattle is suggestive of a role in feed efficiency.

Whole-genome resequencing of major populations revealed domestication-related genes in yaks

BACKGROUND

The yak is a symbol of the Qinghai-Tibet Plateau and provides important basic resources for human life on the plateau. Domestic yaks have been subjected to strong artificial selection and environmental pressures over the long-term. Understanding the molecular mechanisms of phenotypic differences in yak populations can reveal key functional genes involved in the domestication process and improve genetic breeding.

MATERIAL AND METHOD

Here, we re-sequenced 80 yaks (Maiwa, Yushu, and Huanhu populations) to identify single-nucleotide polymorphisms (SNPs) as genetic variants. After filtering and quality control, remaining SNPs were kept to identify the genome-wide regions of selective sweeps associated with domestic traits. The four methods (π, XPEHH, iHS, and XP-nSL) were used to detect the population genetic separation.

RESULTS

By comparing the differences in the population stratification, linkage disequilibrium decay rate, and characteristic selective sweep signals, we identified 203 putative selective regions of domestic traits, 45 of which were mapped to 27 known genes. They were clustered into 4 major GO biological process terms. All known genes were associated with seven major domestication traits, such as dwarfism (ANKRD28), milk (HECW1, HECW2, and OSBPL2), meat (SPATA5 and GRHL2), fertility (BTBD11 and ARFIP1), adaptation (NCKAP5, ANTXR1, LAMA5, OSBPL2, AOC2, and RYR2), growth (GRHL2, GRID2, SMARCAL1, and EPHB2), and the immune system (INPP5D and ADCYAP1R1).

CONCLUSIONS

We provided there is an obvious genetic different among domestic progress in these three yak populations. Our findings improve the understanding of the major genetic switches and domestic processes among yak populations.

GWAS and genetic and phenotypic correlations of plasma metabolites with complete blood count traits in healthy young pigs reveal implications for pig immune response

Introduction: In this study estimated genetic and phenotypic correlations between fifteen complete blood count (CBC) traits and thirty-three heritable plasma metabolites in young healthy nursery pigs. In addition, it provided an opportunity to identify candidate genes associated with variation in metabolite concentration and their potential association with immune response, disease resilience, and production traits.

Methods: The blood samples were collected from healthy young pigs and Nuclear Magnetic Resonance (NMR) was used to quantify plasma metabolites. CBC was determined using the ADVIA® 2120i Hematology System. Genetic correlations of metabolite with CBC traits and single step genome-wide association study (ssGWAS) were estimated using the BLUPF90 programs.

Results: Results showed low phenotypic correlation estimates between plasma metabolites and CBC traits. The highest phenotypic correlation was observed between lactic acid and plasma basophil concentration (0.36 ± 0.04; p &lt; 0.05). Several significant genetic correlations were found between metabolites and CBC traits. The plasma concentration of proline was genetically positively correlated with hemoglobin concentration (0.94 ± 0.03; p &lt; 0.05) and L-tyrosine was negatively correlated with mean corpuscular hemoglobin (MCH; −0.92 ± 0.74; p &lt; 0.05). The genomic regions identified in this study only explained a small percentage of the genetic variance of metabolites levels that were genetically correlated with CBC, resilience, and production traits.

Discussion: The results of this systems approach suggest that several plasma metabolite phenotypes are phenotypically and genetically correlated with CBC traits, suggesting that they may be potential genetic indicators of immune response following disease challenge. Genomic analysis revealed genes and pathways that might interact to modulate CBC, resilience, and production traits.

Runs of Homozygosity Analysis Reveals Genomic Diversity and Population Structure of an Indigenous Cattle Breed in Southwest China

In aiming to achieve sustainable development goals in the livestock industry, it is becoming increasingly necessary and important for the effective conservation of genetic resources. There are some indigenous cattle breeds in Sichuan, southwest China, for which, however, the genetic diversity and population structures still remain unknown because of the unavailability of systematic breeding programs and pedigree information. Xieka cattle are an indigenous breed locally distributed in southeastern Sichuan and have a long-term evolutionary adaptation to local environments and climates. In this study, we obtained 796,828 single nucleotide polymorphisms (SNPs) through sequencing the genomes of 30 Xieka cattle and used them for analyzing the genetic diversity and runs of homozygosity (ROH). The mean nucleotide diversity was 0.28 and 72% of SNPs were found to be in the heterozygous states. A total of 4377 ROH were detected with even distribution among all autosomes, and 74% of them were lower than 1 Mb in length. Meanwhile, only five ROH were found longer than 5 Mb. We further determined 19 significant genomic regions that were obviously enriched by ROH, in which 35 positional candidate genes were found. Some of these genes have been previously reported to be significantly associated with various production traits in cattle, such as meat quality, carcass performances, and diseases. In conclusion, the relatively high degree of genetic diversity of Xieka cattle was revealed using the genomic information, and the proposed candidate genes will help us optimize the breeding programs regarding this indigenous breed.

Multivariate and Genome-Wide Analysis of Mid-Infrared Spectra of Non-Coagulating Milk of Sarda Sheep Breed

Milk coagulation ability is crucial for the dairy sheep industry since the whole amount of milk is processed into cheese. Non-coagulating milk (NCM) is defined as milk not forming a curd within the testing time. In sheep milk, it has been reported in literature that up to 20% of milk is NCM. Although the clotting properties of individual milk have been widely studied, little attention has been given to NCM and genomic dissection of this trait. Mid-infrared (MIR) spectra can be exploited both to predict cheese-making aptitude and to discriminate between coagulating milk and NCM. The main goals of this work were (i) to assess the predictivity of MIR spectra for NCM classification and (ii) to conduct a genome-wide association study on coagulation ability. Milk samples from 949 Sarda ewes genotyped and phenotyped for milk coagulation properties (MCPs) served as the training dataset. The validation dataset included 662 ewes. Three classical MCPs were measured: rennet coagulation time (RCT), curd firmness (a30), and curd firming time (k20). Moreover, MIR spectra were acquired and stored in the region between 925.92 and 5,011.54 cm−1. The probability of a sample to be NCM was modeled by step-wise logistic regression on milk spectral information (LR-W), logistic regression on principal component (LR-PC), and canonical discriminant analysis of spectral wave number (DA-W). About 9% of the samples did not coagulate at 30 min. The use of LR-W gave a poorer classification of NCM. The use of LR-PC improved the percentage of correct assignment (45 ± 9%). The DA-W method allows us to reach 75.1 ± 10.3 and 76.5 ± 18.4% of correct assignments of the inner and external validation datasets, respectively. As far as GWA of NCM, 458 SNP associations and 45 candidate genes were detected. The genes retrieved from public databases were mostly linked to mammary gland metabolism, udder health status, and a milk compound also known to affect the ability of milk to coagulate. In particular, the potential involvement of CAPNs deserves further investigation.

Individual Feed Efficiency Monitoring of Charolaise Candidate Young Bulls in Relation to Feeding Behavior and Self-Performance Test Results

This study evaluated the effect of differences in residual feed intake (RFI) of Charolaise candidate young bulls on feeding behavior and self-performance test results. Bulls were classified into high and low RFI (H-RFI, L-RFI) groups. Bulls were fed in a HOKOFARM system to measure individual animal intake and behavior. L-RFI bulls had significantly lower feed intakes (p = 0.002) and higher gain to feed ratio (p = 0.001), lower intake per day/kg DM (dry matter) (p = 0.002) and lower intake g/body weight/day (p < 0.001). L-RFI animals had lower visits number per day (p = 0.02), but spent longer time per visit (p = 0.02), and tended to have higher intake g/visit (p = 0.06) on feeders. The correlation between RFI and DMI (dry matter intake)/bodyweight/day as well as intake per day/kg were large and positive. Back-loin length and rump length, and moreover muzzle width and frame, showed negative correlations with RFI value. However, bulls with better RFI values associated with lower legs score. Results reveal that RFI was shown beneficial correlations with economically relevant self-performance traits. Further investigations are needed to seek additional indicator traits that are predictive for RFI.