Genomic structure and marker-derived gene networks for growth and meat quality traits of Brazilian Nelore beef cattle.

BACKGROUND: Nelore is the major beef cattle breed in Brazil with more than 130 million heads. Genome-wide association studies (GWAS) are often used to associate markers and genomic regions to growth and meat quality traits that can be used to assist selection programs. An alternative methodology to traditional GWAS that involves the construction of gene network interactions, derived from results of several GWAS is the AWM (Association Weight Matrices)/PCIT (Partial Correlation and Information Theory). With the aim of evaluating the genetic architecture of Brazilian Nelore cattle, we used high-density SNP genotyping data (~770,000 SNP) from 780 Nelore animals comprising 34 half-sibling families derived from highly disseminated and unrelated sires from across Brazil. The AWM/PCIT methodology was employed to evaluate the genes that participate in a series of eight phenotypes related to growth and meat quality obtained from this Nelore sample. RESULTS: Our results indicate a lack of structuring between the individuals studied since principal component analyses were not able to differentiate families by its sires or by its ancestral lineages. The application of the AWM/PCIT methodology revealed a trio of transcription factors (comprising VDR, LHX9 and ZEB1) which in combination connected 66 genes through 359 edges and whose biological functions were inspected, some revealing to participate in biological growth processes in literature searches. CONCLUSIONS: The diversity of the Nelore sample studied is not high enough to differentiate among families neither by sires nor by using the available ancestral lineage information. The gene networks constructed from the AWM/PCIT methodology were a useful alternative in characterizing genes and gene networks that were allegedly influential in growth and meat quality traits in Nelore cattle.

Detecção de Brucella abortus em tecidos bovinos utilizando ensaios de PCR e qPCR / Detection of Brucella abortus in bovine tissue using PCR and qPCR

Objetivou-se no presente estudo avaliar as técnicas reação em cadeia da polimerase (PCR) e PCR em Tempo Real (qPCR) para detectar Brucella abortus, a partir de tecidos bovinos com lesões sugestivas de brucelose. Para isto, 21 fragmentos de tecidos bovinos coletados em abatedouros de Mato Grosso do Sul foram processados e submetidos ao cultivo microbiológico e extração do DNA genômico para realização das reações de PCR e qPCR. No cultivo microbiológico, oito amostras apresentaram crescimento bacteriano e cinco foram confirmadas como B. abortus por PCR. Diretamente das amostras de tecido, DNA do gênero Brucella (oligonucleotídeos IS711) foi detectado em 13 (61,9 por cento) amostras de tecido e 17 (81 por cento) amostras de homogeneizado. Já com os oligonucleotídeos espécie-específicos BruAb2_0168F e BruAb2_0168R, 14 (66 por cento) amostras de tecido e 18 (85,7 por cento) amostras de homogeneizado foram amplificadas. Seis amostras positivas na PCR espécie-específica foram sequenciadas e o best hit na análise BLASTn foi B. abortus. Na qPCR, 21 (100 por cento) amostras de tecidos e 19 (90,5 por cento) amostras de homogeneizado foram positivas para B. abortus. Dez amostras de DNA de sangue bovino de rebanho certificado livre foram utilizadas como controle negativo nas análises de PCR e qPCR utilizando-se os oligonucleotídeos BruAb2_0168F e BruAb2_0168R. Na PCR nenhuma amostra amplificou, enquanto que na qPCR 2 (20 por cento) amplificaram. Conclui-se que as duas técnicas detectam a presença de B. abortus diretamente de tecidos e homogeneizados, porém a qPCR apresentou maior sensibilidade. Os resultados obtidos indicam que a qPCR pode representar uma alternativa rápida e precisa para a detecção de B. abortus diretamente de tecidos, e ser utilizada em programas de vigilância sanitária, por apresentar sensibilidade e especificidade satisfatórias.

The aim of the study was to evaluate the technical polymerase chain reaction (PCR) and Real-Time PCR (qPCR) to detect Brucella abortus from bovine tissues with suggestive lesions of brucellosis. For this, 21 fragments of bovine tissues collected at abattoirs of Mato Grosso do Sul were processed and subjected to microbiological culture and extraction of genomic DNA to perform the PCR reactions and qPCR. Eight samples of microbiological culture showed bacterial growth and five samples were confirmed as B. abortus by PCR. DNA of Brucella (IS711 primers) was detected in 13 (61.9 percent) directly from tissue samples and 17 (81 percent) from tissue homogenate samples. With the species-specific set of primers BruAb2_0168F and BruAb2_0168R, 14 (66 percent) tissue samples and 18 (85.7 percent) tissue homogenate samples were positive. Six positive samples in the species-specific PCR were sequenced and the best hit in the BLASTn analysis was B. abortus. By qPCR, 21 (100 percent) tissue samples and 19 (90.5 percent) tissue homogenate samples were positive for B. abortus. Ten samples of DNA from bovine blood from an accredited-free herd were used as negative control in PCR and qPCR analysis using the primers BruAb2_0168F and BruAb2_0168R, and no one amplified by PCR, whereas two samples were amplified by qPCR (20 percent). In conclusion, both techniques detect the presence of B. abortus directly from tissues and homogenized, but the qPCR showed high sensitivity. The results indicate that qPCR can represent an alternative tool for faster and more accurate detection of B. abortus directly from tissues, and use in health surveillance programs by presenting satisfactory sensitivity and specificity.

Impact of breed and sex on porcine endocrine transcriptome: a bayesian biometrical analysis.

BACKGROUND: Transcriptome variability is due to genetic and environmental causes, much like any other complex phenotype. Ascertaining the transcriptome differences between individuals is an important step to understand how selection and genetic drift may affect gene expression. To that end, extant divergent livestock breeds offer an ideal genetic material. RESULTS: We have analyzed with microarrays five tissues from the endocrine axis (hypothalamus, adenohypophysis, thyroid gland, gonads and fat tissue) of 16 pigs from both sexes pertaining to four extreme breeds (Duroc, Large White, Iberian and a cross with SinoEuropean hybrid line). Using a Bayesian linear model approach, we observed that the largest breed variability corresponded to the male gonads, and was larger than at the remaining tissues, including ovaries. Measurement of sex hormones in peripheral blood at slaughter did not detect any breed-related differences. Not unexpectedly, the gonads were the tissue with the largest number of sex biased genes. There was a strong correlation between sex and breed bias expression, although the most breed biased genes were not the most sex biased genes. A combined analysis of connectivity and differential expression suggested three biological processes as being primarily different between breeds: spermatogenesis, muscle differentiation and several metabolic processes. CONCLUSION: These results suggest that differences across breeds in gene expression of the male gonads are larger than in other endocrine tissues in the pig. Nevertheless, the strong presence of breed biased genes in the male gonads cannot be explained solely by changes in spermatogenesis nor by differences in the reproductive tract development.

Transcriptome architecture across tissues in the pig.

BACKGROUND: Artificial selection has resulted in animal breeds with extreme phenotypes. As an organism is made up of many different tissues and organs, each with its own genetic programme, it is pertinent to ask: How relevant is tissue in terms of total transcriptome variability? Which are the genes most distinctly expressed between tissues? Does breed or sex equally affect the transcriptome across tissues? RESULTS: In order to gain insight on these issues, we conducted microarray expression profiling of 16 different tissues from four animals of two extreme pig breeds, Large White and Iberian, two males and two females. Mixed model analysis and neighbor - joining trees showed that tissues with similar developmental origin clustered closer than those with different embryonic origins. Often a sound biological interpretation was possible for overrepresented gene ontology categories within differentially expressed genes between groups of tissues. For instance, an excess of nervous system or muscle development genes were found among tissues of ectoderm or mesoderm origins, respectively. Tissue accounted for ~11 times more variability than sex or breed. Nevertheless, we were able to confidently identify genes with differential expression across tissues between breeds (33 genes) and between sexes (19 genes). The genes primarily affected by sex were overall different than those affected by breed or tissue. Interaction with tissue can be important for differentially expressed genes between breeds but not so much for genes whose expression differ between sexes. CONCLUSION: Embryonic development leaves an enduring footprint on the transcriptome. The interaction in gene x tissue for differentially expressed genes between breeds suggests that animal breeding has targeted differentially each tissue's transcriptome.