Molecular regulation of high muscle mass in developing Blonde d'Aquitaine cattle foetuses

Mining of chicken muscle growth genes and the function of important candidate gene RPL3L in muscle development

The birth weight of chickens does not significantly affect the weight at slaughter, while the different growth rate after birth was one of the important reasons for the difference in slaughter weight. Also, the increase in chickens' postnatal skeletal muscle weight is the main cause of the slaughter weight gain, but which genes are involved in this biological process is still unclear. In this study, by integrating four transcriptome datasets containing chicken muscles at different developmental times or different chicken tissues in public databases, a total of nine candidate genes that may be related to postnatal muscle development in chickens were obtained, including RPL3L, FBP2, ASB4, ASB15, CKMT2, PGAM1, YIPF7, PFKM, and LDHA. One of these candidate genes is RPL3L, whose 42 bp insertion/deletion (indel) mutation significantly correlated with multiple carcass traits in the F2 resource population from Xinghua chickens crossing with White Recessive Rock (WRR) chickens, including live weight, carcass weight, half eviscerated weight, eviscerated weight, breast meat weight, wing weight, leg muscle shear force, and breast muscle shear force. Also, there was a very significant difference between different genotypes of the RPL3L 42 bp indel mutation in these trains. Further experiments showed that RPL3L was highly expressed in chicken skeletal muscle, and its overexpression could promote the proliferation and inhibit the differentiation of chicken myoblasts by regulating ASB4 and ASB15 expression. Our findings demonstrated that the RPL3L 42 bp indel may be one of the molecular markers of chicken weight-related traits.

Identification of candidate genes on the basis of SNP by time-lagged heat stress interactions for milk production traits in German Holstein cattle

The aim of this study was to estimate genotype by time-lagged heat stress (HS) variance components as well as main and interaction SNP-marker effects for maternal HS during the last eight weeks of cow pregnancy, considering milk production traits recorded in the offspring generation. The HS indicator was the temperature humidity index (THI) for each week. A dummy variable with the code = 1 for the respective week for THI ≥ 60 indicated HS, otherwise, for no HS, the code = 0 was assigned. The dataset included test-day and lactation production traits from 14,188 genotyped first parity Holstein cows. After genotype quality control, 41,139 SNP markers remained for the genomic analyses. Genomic animal models without (model VC_nHS) and with in-utero HS effects (model VC_wHS) were applied to estimate variance components. Accordingly, for genome-wide associations, models GWA_nHS and GWA_wHS, respectively, were applied to estimate main and interaction SNP effects. Common genomic and residual variances for the same traits were very similar from models VC_nHS and VC_wHS. Genotype by HS interaction variances varied, depending on the week with in-utero HS. Among all traits, lactation milk yield with HS from week 5 displayed the largest proportion for interaction variances (0.07). For main effects from model GWA_wHS, 380 SNPs were suggestively associated with all production traits. For the SNP interaction effects from model GWA_wHS, we identified 31 suggestive SNPs, which were located in close distance to 62 potential candidate genes. The inferred candidate genes have various biological functions, including mechanisms of immune response, growth processes and disease resistance. Two biological processes excessively represented in the overrepresentation tests addressed lymphocyte and monocyte chemotaxis, ultimately affecting immune response. The modelling approach considering time-lagged genotype by HS interactions for production traits inferred physiological mechanisms being associated with health and immunity, enabling improvements in selection of robust animals.

The Blonde d'Aquitaine T3811>G3811 mutation in the myostatin gene: association with growth, carcass, and muscle phenotypes in veal calves

The mutation T3811 → G3811 (TG3811) discovered in the myostatin gene of the Blonde d'Aquitaine breed is suspected of contributing to the outstanding muscularity of this breed. An experiment was designed to estimate the effect of this mutation in an F2 and back-cross Blonde d'Aquitaine × Holstein population. By genotyping all known mutations in the myostatin gene, it was ensured that the TG3811 mutation was indeed the only known mutation segregating in this population. Fifty-six calves (43 F2, 13 back-cross) were intensively fattened and slaughtered at 24.0 ± 1.4 wk of age. The effects of the mutation were estimated by comparing the calves with the [T/T] (n = 18), [T/G] (n = 30), and [G/G] (n = 8) genotypes. Highly significant substitution effects (P < 0.001), above + 1.2 phenotypic SD, were shown on carcass yield and muscularity scores. Birth weight (P < 0.001) was positively affected by the mutation (+0.8 SD) but not growth rate (P = 0.97), while carcass length (P = 0.03), and fatness (P ≤ 0.03) were negatively affected (-0.5 to -0.7 SD). The characteristics of the Triceps brachii muscle were affected by the mutation (P < 0.001), with lower ICDH activity (oxidative) and a higher proportion of myosin type 2X muscle fibers (fast twitch). The effects of the TG3811 mutation were similar to those of other known myostatin mutations, although the Blonde d'Aquitaine animals, which are predominantly [G/G] homozygous, do not exhibit extreme double muscling.

Comparative Transcriptome Profile Analysis of Longissimus dorsi Muscle Tissues From Two Goat Breeds With Different Meat Production Performance Using RNA-Seq

Carcass weight, meat quality and muscle components are important traits economically and they underpin most of the commercial return to goat producers. In this study, the Longissimus dorsi muscle tissues were collected from five Liaoning cashmere (LC) goats and five Ziwuling black (ZB) goats with phenotypic difference in carcass weight, some meat quality traits and muscle components. The histological quantitative of collagen fibers and the transcriptome profiles in the Longissimus dorsi muscle tissues were investigated using Masson-trichrome staining and RNA-Seq, respectively. The percentage of total collagen fibers in the Longissimus dorsi muscle tissues from ZB goats was less than those from LC goats, suggesting that these ZB goats had more tender meat. An average of 15,919 and 15,582 genes were found to be expressed in Longissimus dorsi muscle tissues from LC and ZB goats, respectively. Compared to LC goats, the expression levels of 78 genes were up-regulated in ZB goats, while 133 genes were down-regulated. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that the differentially expressed genes (DEGs) were significantly enriched in GO terms related to the muscle growth and development and the deposition of intramuscular fat and lipid metabolism, hippo signaling pathway and Jak-STAT signaling pathway. The results provide an improved understanding of the genetic mechanisms regulating meat production performance in goats, and will help us improve the accuracy of selection for meat traits in goats using marker-assisted selection based on these differentially expressed genes obtained.

Uncovering Sub-Structure and Genomic Profiles in Across-Countries Subpopulations of Angus Cattle

Highlighting genomic profiles for geographically distinct subpopulations of the same breed may provide insights into adaptation mechanisms to different environments, reveal genomic regions divergently selected, and offer initial guidance to joint genomic analysis. Here, we characterized similarities and differences between the genomic patterns of Angus subpopulations, born and raised in Canada (N = 382) and Brazil (N = 566). Furthermore, we systematically scanned for selection signatures based on the detection of autozygosity islands common between the two subpopulations, and signals of divergent selection, via FST and varLD tests. The principal component analysis revealed a sub-structure with a close connection between the two subpopulations. The averages of genomic relationships, inbreeding coefficients, and linkage disequilibrium at varying genomic distances were rather similar across them, suggesting non-accentuated differences in overall genomic diversity. Autozygosity islands revealed selection signatures common to both subpopulations at chromosomes 13 (63.77-65.25 Mb) and 14 (22.81-23.57 Mb), which are notably known regions affecting growth traits. Nevertheless, further autozygosity islands along with FST and varLD tests unravel particular sites with accentuated population subdivision at BTAs 7 and 18 overlapping with known QTL and candidate genes of reproductive performance, thermoregulation, and resistance to infectious diseases. Our findings indicate overall genomic similarity between Angus subpopulations, with noticeable signals of divergent selection in genomic regions associated with the adaptation in different environments.

Combining information from genome-wide association and multi-tissue gene expression studies to elucidate factors underlying genetic variation for residual feed intake in Australian Angus cattle

BACKGROUND

Genome-wide association studies (GWAS) are extensively used to identify single nucleotide polymorphisms (SNP) underlying the genetic variation of complex traits. However, much uncertainly often still exists about the causal variants and genes at quantitative trait loci (QTL). The aim of this study was to identify QTL associated with residual feed intake (RFI) and genes in these regions whose expression is also associated with this trait. Angus cattle (2190 steers) with RFI records were genotyped and imputed to high density arrays (770 K) and used for a GWAS approach to identify QTL associated with RFI. RNA sequences from 126 Angus divergently selected for RFI were analyzed to identify the genes whose expression was significantly associated this trait with special attention to those genes residing in the QTL regions.

RESULTS

The heritability for RFI estimated for this Angus population was 0.3. In a GWAS, we identified 78 SNPs associated with RFI on six QTL (on BTA1, BTA6, BTA14, BTA17, BTA20 and BTA26). The most significant SNP was found on chromosome BTA20 (rs42662073) and explained 4% of the genetic variance. The minor allele frequencies of significant SNPs ranged from 0.05 to 0.49. All regions, except on BTA17, showed a significant dominance effect. In 1 Mb windows surrounding the six significant QTL, we found 149 genes from which OAS2, STC2, SHOX, XKR4, and SGMS1 were the closest to the most significant QTL on BTA17, BTA20, BTA1, BTA14, and BTA26, respectively. In a 2 Mb windows around the six significant QTL, we identified 15 genes whose expression was significantly associated with RFI: BTA20) NEURL1B and CPEB4; BTA17) RITA1, CCDC42B, OAS2, RPL6, and ERP29; BTA26) A1CF, SGMS1, PAPSS2, and PTEN; BTA1) MFSD1 and RARRES1; BTA14) ATP6V1H and MRPL15.

CONCLUSIONS

Our results showed six QTL regions associated with RFI in a beef Angus population where five of these QTL contained genes that have expression associated with this trait. Therefore, here we show that integrating information from gene expression and GWAS studies can help to better understand the genetic mechanisms that determine variation in complex traits.

Gene Co-expression Analysis Indicates Potential Pathways and Regulators of Beef Tenderness in Nellore Cattle

Beef tenderness, a complex trait affected by many factors, is economically important to beef quality, industry, and consumer’s palatability. In this study, RNA-Seq was used in network analysis to better understand the biological processes that lead to differences in beef tenderness. Skeletal muscle transcriptional profiles from 24 Nellore steers, selected by extreme estimated breeding values (EBVs) for shear force after 14 days of aging, were analyzed and 22 differentially expressed transcripts were identified. Among these were genes encoding ribosomal proteins, glutathione transporter ATP-binding cassette, sub-family C (CFTR/MRP), member 4 (ABCC4), and synaptotagmin IV (SYT4). Complementary co-expression analyses using Partial Correlation with Information Theory (PCIT), Phenotypic Impact Factor (PIF) and the Regulatory Impact Factor (RIF) methods identified candidate regulators and related pathways. The PCIT analysis identified ubiquitin specific peptidase 2 (USP2), growth factor receptor-bound protein 10 (GBR10), anoctamin 1 (ANO1), and transmembrane BAX inhibitor motif containing 4 (TMBIM4) as the most differentially hubbed (DH) transcripts. The transcripts that had a significant correlation with USP2, GBR10, ANO1, and TMBIM4 enriched for proteasome KEGG pathway. RIF analysis identified microRNAs as candidate regulators of variation in tenderness, including bta-mir-133a-2 and bta-mir-22. Both microRNAs have target genes present in the calcium signaling pathway and apoptosis. PIF analysis identified myoglobin (MB), enolase 3 (ENO3), and carbonic anhydrase 3 (CA3) as potentially having fundamental roles in tenderness. Pathways identified in our study impacted in beef tenderness included: calcium signaling, apoptosis, and proteolysis. These findings underscore some of the complex molecular mechanisms that control beef tenderness in Nellore cattle.