Genome-wide copy number variation (CNV) detection in Nelore cattle reveals highly frequent variants in genome regions harboring QTLs affecting production traits.

Background: Copy number variations (CNVs) have been shown to account for substantial portions of observed genomic variation and have been associated with qualitative and quantitative traits and the onset of disease in a number of species. Information from high-resolution studies to detect, characterize and estimate population-specific variant frequencies will facilitate the incorporation of CNVs in genomic studies to identify genes affecting traits of importance. Results: Genome-wide CNVs were detected in high-density single nucleotide polymorphism (SNP) genotyping data from 1,717 Nelore (Bos indicus) cattle, and in NGS data from eight key ancestral bulls. A total of 68,007 and 12,786 distinct CNVs were observed, respectively. Cross-comparisons of results obtained for the eight resequenced animals revealed that 92 % of the CNVs were observed in both datasets, while 62 % of all detected CNVs were observed to overlap with previously validated cattle copy number variant regions (CNVRs). Observed CNVs were used for obtaining breed-specific CNV frequencies and identification of CNVRs, which were subsequently used for gene annotation. A total of 688 of the detected CNVRs were observed to overlap with 286 non-redundant QTLs associated with important production traits in cattle. All of 34 CNVs previously reported to be associated with milk production traits in Holsteins were also observed in Nelore cattle. Comparisons of estimated frequencies of these CNVs in the two breeds revealed 14, 13, 6 and 14 regions in high (>20 %), low (<20 %) and divergent (NEL > HOL, NEL < HOL) frequencies, respectively. Conclusions: Obtained results significantly enriched the bovine CNV map and enabled the identification of variants that are potentially associated with traits under selection in Nelore cattle, particularly in genome regions harboring QTLs affecting production traits.

A single nucleotide polymorphism in NEUROD1 is associated with production traits in nelore beef cattle.

Feed efficiency and carcass characteristics are late-measured traits. The detection of molecular markers associated with them can help breeding programs to select animals early in life, and to predict breeding values with high accuracy. The objective of this study was to identify polymorphisms in the functional and positional candidate gene NEUROD1 (neurogenic differentiation 1), and investigate their associations with production traits in reference families of Nelore cattle. A total of 585 steers were used, from 34 sires chosen to represent the variability of this breed. By sequencing 14 animals with extreme residual feed intake (RFI) values, seven single nucleotide polymorphisms (SNPs) in NEUROD1 were identified. The investigation of marker effects on the target traits RFI, backfat thickness (BFT), ribeye area (REA), average body weight (ABW), and metabolic body weight (MBW) was performed with a mixed model using the restricted maximum likelihood method. SNP1062, which changes cytosine for guanine, had no significant association with RFI or REA. However, we found an additive effect on ABW (P ≤ 0.05) and MBW (P ≤ 0.05), with an estimated allele substitution effect of -1.59 and -0.93 kg0.75, respectively. A dominant effect of this SNP for BFT was also found (P ≤ 0.010). Our results are the first that identify NEUROD1 as a candidate that affects BFT, ABW, and MBW. Once confirmed, the inclusion of this SNP in dense panels may improve the accuracy of genomic selection for these traits in Nelore beef cattle as this SNP is not currently represented on SNP chips.

Genes diferencialmente expressos no músculo Longissimus dorsi de novilhos nelore divergentes para eficiência bruta.

2016

Variation in myogenic differentiation 1 mRNA abundance is associated with beef tenderness in Nelore cattle.

The myogenic differentiation 1 gene (MYOD1) has a key role in skeletal muscle differentiation and composition through its regulation of the expression of several muscle-specific genes. We first used a general linear mixed model approach to evaluate the association of MYOD1 expression levels on individual beef tenderness phenotypes. MYOD1 mRNA levels measured by quantitative polymerase chain reactions in 136 Nelore steers were significantly associated (P ? 0.01) with Warner?Bratzler shear force, measured on the longissimus dorsi muscle after 7 and 14 days of beef aging. Transcript abundance for the muscle regulatory gene MYOD1 was lower in animals with more tender beef. We also performed a coexpression network analysis using whole transcriptome sequence data generated from 30 samples of longissimus muscle tissue to identify genes that are potentially regulated by MYOD1. The effect of MYOD1 gene expression on beef tenderness may emerge from its function as an activator of muscle-specific gene transcription such as for the serum response factor (C-fos serum response element-binding transcription factor) gene (SRF), which determines muscle tissue development, composition, growth and maturation.

Identificação raças bovinas criadas no Brasil por meio de morfometria cuticular de pelos guarda.

A análise tricológica é um método não invasivo com potencial para a identificação de mamíferos por meio das características microscópicas de seus pelos. Permite identificar e diferenciar amostras ao nível de Ordem, Família, Gênero, Espécie e até mesmo Subespécies em alguns grupos zoológicos. A caracterização morfométrica de estruturas da cutícula em pelos de animais de raças bovinas criadas no Brasil poderia indicar a possibilidade de uso desta técnica como marcador racial. Um total de 120 animais (machos e fêmeas), pertencentes às raças Caracu, Curraleiro Pé-Duro e Nelore, provenientes de rebanhos de diferentes regiões geográficas foi amostrado. Os dados de área e perímetro das escamas cuticulares foram submetidos à análise de variância, sendo o efeito de raça significativo (P<0,001) e as médias das variáveis estudadas significativamente diferentes entre as raças (P<0,05). A técnica tricológica apresentou elevada acurácia na diferenciação das raças bovinas estudadas. O método, que tem como característica baixo custo de execução, se mostrou como uma ferramenta de grande utilidade para identificação não invasiva de bovinos, com potencial de uso e aplicação para outras espécies de interesse para a pecuária.

Genome-wide detection of CNVs and their association with meat tenderness in Nelore cattle.

Brazil is one of the largest beef producers and exporters in the world with the Nelore breed representing the vast majority of Brazilian cattle (Bos taurus indicus). Despite the great adaptability of the Nelore breed to tropical climate, meat tenderness (MT) remains to be improved. Several factors including genetic composition can influence MT. In this article, we report a genome-wide analysis of copy number variation (CNV) inferred from Illumina1 High Density SNP-chip data for a Nelore population of 723 males. We detected >2,600 CNV regions (CNVRs) representing 6.5% of the genome. Comparing our results with previous studies revealed an overlap in 1400 CNVRs (>50%). A total of 1,155 CNVRs (43.6%) overlapped 2,750 genes. They were enriched for processes involving guanosine triphosphate (GTP), previously reported to influence skeletal muscle physiology and morphology. Nelore CNVRs also overlapped QTLs for MT reported in other breeds (8.9%, 236 CNVRs) and from a previous study with this population (4.1%, 109 CNVRs). Two CNVRs were also proximal to glutathione metabolism genes that were previously associated with MT. Genome-wide association study of CN state with estimated breeding values derived from meat shear force identified 6 regions, including a region on BTA3 that contains genes of the cAMP and cGMP pathway. Ten CNVRs that overlapped regions associated with MT were successfully validated by qPCR. Our results represent the first comprehensive CNV study in Bos taurus indicus cattle and identify regions in which copy number changes are potentially of importance for the MT phenotype.