L.L. Verardo

Candidate gene expression and intramuscular fat content in pigs

Seventy-two pigs of three genetic groups (Brazilian indigenous breed Piau, Commercial line and Crossbred) of both sexes were slaughtered at four live weights (30, 60, 90 and 120 kg). Intramuscular fat (IMF) content in Longissimus dorsi muscle of each animal was extracted and correlated with candidate gene mRNA expression (ATN1, EEF1A2, FABP3, LDLR, MGP, OBSCN, PDHB, TRDN and RYR1). Within slaughter weight of 120 kg, Piau and Crossbred pigs showed higher IMF content (p < 0.05) than commercial animals, with 2.48, 2.08 and 1.00% respectively. Barrows presented higher values of IMF (p < 0.05) than gilts (1.54 and 1.30% respectively). Gene expression of EEF1A2, FABP3, LDLR, OBSCN, PDHB, TRDN and RYR1 were correlated with IMF (p < 0.05) using the whole dataset. For Piau data only, expression of FABP3, LDLR, MGP, OBSCN, PDHB, TRDN and RYR1 showed correlation with IMF (p < 0.05). Genes that have important roles in lipid transportation inside the cell (FABP3) and tissues (LDLR) showed correlation with IMF of, respectively, 0.68 and 0.63 using the whole data set, and 0.90 and 0.91 using data from Piau animals. The highly positive correlation of the LDLR and FAPB3 expression with IMF content may confirm that these genes are important for fat deposition in the porcine L. dorsi muscle.

Mapeamento de locos de características quantitativas nos cromossomos 5, 7 e 8 de suínos

The aim of this experiment was to map QTL in chromosomes 5, 7 and 8 and to associate them to carcass traits, carcass cuts, meat quality, performance and internal organs of swines. An F2 offspring with 614 animals was produced from the matting of two Brazilian naturalized Piau boars with 18 commercial females (Landrace x Large White x Pietrain). The population was genotyped for 14 microsatellite markers covering chromosomes 5, 7 and 8. After that, it was built the linkage map for each chromosome. Analysis of association were done using interval mapping by regression for QTL detection. For carcass and cuts of carcass traits, 20 QTL were mapped in the three chromosomes, whereas for traits of meat quality, only three QTL were found on chromosomes 7 and 8. Among them, significant QTL at 5% in the genome were found for midline lower backfat thickness above the last lumbar vertebrae on chromosome 5; and for total length of small intestine, abdominal fat weight and brightness on chromosome 8. For carcass length by the Brazilian method and carcass length by the American method, it was found significant QTL at 1% in the genome on chromosome 7. The results found in this work will facilitate future researches as fine mapping and identification of genes that control body composition and meat quality and that will be able to be incorporated in marker-assisted selection programs to accelerate genetic improvement in swine populations, in addition to help a better understanding of the physiology of traits in swine production.

After genome-wide association studies: Gene networks elucidating candidate genes divergences for number of teats across two pig populations.

Number of teats (NT) is an important trait affecting both piglets welfare and the production level of pig farms. Biologically, embryonic mammary gland development requires the coordination of many signaling pathways necessary for the proper development of teats. Several QTL for NT have been identified; however, further analysis is still lacking. Therefore, gene networks derived from genomewide association study (GWAS) results can be used to examine shared pathways and functions of putative candidate genes. Besides, such analyses may also be helpful to understand the genetic diversity between populations for the same trait or traits. In this study, we identified significant SNP for Landrace-based (line C) and Large White-based (line D) dam lines. Besides, gene-transcription factor (TF) networks were constructed aiming to obtain the most likely candidate genes for NT in each line followed by a comparative analysis between both lines to access similarities or dissimilarities at the marker and gene level. We identified 24 and 19 significant SNP (Bayes factor ≥ 100) for lines C and D, respectively. Only 1 significant SNP overlapped both lines. Network analysis illustrated gene interactions consistent with known mammals breast biology and captured known TF. We observed different sets of putative candidate genes for NT in each line evaluated that may have common effects on the phenotype. Based on these results, we demonstrated the importance of post-GWAS analyses increasing the biological understanding of relevant genes for a complex trait. Moreover, we believe that this genomic diversity across lines should be taken into account, considering breed-specific reference populations for genomic selection.

Genome‐wide association study and annotating candidate gene networks affecting age at first calving in Nellore cattle

We performed a genome-wide mapping for the age at first calving (AFC) with the goal of annotating candidate genes that regulate fertility in Nellore cattle. Phenotypic data from 762 cows and 777k SNP genotypes from 2,992 bulls and cows were used. Single nucleotide polymorphism (SNP) effects based on the single-step GBLUP methodology were blocked into adjacent windows of 1 Megabase (Mb) to explain the genetic variance. SNP windows explaining more than 0.40% of the AFC genetic variance were identified on chromosomes 2, 8, 9, 14, 16 and 17. From these windows, we identified 123 coding protein genes that were used to build gene networks. From the association study and derived gene networks, putative candidate genes (e.g., PAPPA, PREP, FER1L6, TPR, NMNAT1, ACAD10, PCMTD1, CRH, OPKR1, NPBWR1 and NCOA2) and transcription factors (TF) (STAT1, STAT3, RELA, E2F1 and EGR1) were strongly associated with female fertility (e.g., negative regulation of luteinizing hormone secretion, folliculogenesis and establishment of uterine receptivity). Evidence suggests that AFC inheritance is complex and controlled by multiple loci across the genome. As several windows explaining higher proportion of the genetic variance were identified on chromosome 14, further studies investigating the interaction across haplotypes to better understand the molecular architecture behind AFC in Nellore cattle should be undertaken.

Review: Animal model and the current understanding of molecule dynamics of adipogenesis.

Among several potential animal models that can be used for adipogenic studies, Wagyu cattle is the one that presents unique molecular mechanisms underlying the deposit of substantial amounts of intramuscular fat. As such, this review is focused on current knowledge of such mechanisms related to adipose tissue deposition using Wagyu cattle as model. So abundant is the lipid accumulation in the skeletal muscles of these animals that in many cases, the muscle cross-sectional area appears more white (adipose tissue) than red (muscle fibers). This enhanced marbling accumulation is morphologically similar to that seen in numerous skeletal muscle dysfunctions, disease states and myopathies; this might indicate cross-similar mechanisms between such dysfunctions and fat deposition in Wagyu breed. Animal models can be used not only for a better understanding of fat deposition in livestock, but also as models to an increased comprehension on molecular mechanisms behind human conditions. This revision underlies some of the complex molecular processes of fat deposition in animals.

Transcript profiling of expressed sequence tags from semimembranosus muscle of commercial and naturalized pig breeds.

In general, genetic differences across different breeds of pig lead to variation in mature body size and slaughter age. The Commercial breeds Duroc and Large White and the local Brazilian breed Piau are ostensibly distinct in terms of growth and muscularity, commercial breeds are much leaner while local breeds grow much slower and are fat type pigs. However, the genetic factors that underlie such distinctions remain unclear. We used expressed sequence tags (ESTs) to characterize and compare transcript profiles in the semimembranosus muscle of these pig breeds. Our aim was to identify differences in breed-related gene expression that might influence growth performance and meat quality. We constructed three non-normalized cDNA libraries from semimembranosus muscle, using two samples from each one, of these three breeds; 6902 high-quality ESTs were obtained. Cluster analysis was performed and these sequences were clustered into 3670 unique sequences; 24.7% of the sequences were categorized as contigs and 75.3% of the sequences were singletons. Based on homology searches against the SwissProt protein database, we were able to assign a putative protein identity to only 1050 unique sequences. Among these, 58.5% were full-length protein sequences and 17.2% were pig-specific sequences. Muscle structural and cytoskeletal proteins, such as actin, and myosin, were the most abundant transcripts (16.7%) followed by those related to mitochondrial function (12.9%), and ribosomal proteins (12.4%). Furthermore, ESTs generated in this study provide a rich source for identification of novel genes and for the comparative analysis of gene expression patterns in divergent pig breeds.

Mapeamento de QTL nos cromossomos 1, 2, 3, 12, 14, 15 e X em suínos: características de carcaça e qualidade de carne

The accomplishment of the present study had as objective to map Quantitative Trait Loci (QTL) associated to carcass and quality traits in a F2 pig population developed by mating two Brazilian Piau breed sires with 18 dams from a commercial line (Landrace × Large White × Pietrain). The linkage map for this population was constructed after genotyping the 684 animals for 35 microsatellite markers. Data were analyzed by interval mapping using sex, batch and halothane genotype as fixed effects and carcass weight at slaughter, direct carcass weight and slaugher age as covariables. A total of 18 QTL were identified, the QTL for higher backfat thickness on the shoulder region and cooking loss was significant at 5% genome-wise level. The backfat thickness trait was mainly associated with the Piau breed allele, known as a fat pig. The information of the significant QTL detected in this study is useful for future fine-mapping studies for identification of genes and might be used together with traditional selection methods to improve the efficiency of breeding programs, moreover, this information can also provide new insights to the understanding of the physiology of the quantatiative traits in pigs.

Detecção de locos de características quantitativas nos cromossomos 1, 2, 3, 12, 14, 15 e X de suínos: características de desempenho

The accomplishment of the present study had the objective of mapping Quantitative Trait Loci (QTL) related to performance traits in a F2 pig population developed by mating two Brazilian Piau breed sires with 18 dams from a commercial line (Landrace × Large White × Pietrain). The linkage map for this population was constructed after genotyping the animals for 35 microsatellite markers. Estimates of polymorphic information content indicated that the microsatellite markers were appropriate for QTL analyses. The genotypes were analyzed by interval mapping using the GridQTL program. A total of six QTL were found, of which the QTL for slaughter age (days) was significant at the 5% genome-wise level. The information of the significant QTL detected in this study is useful for future fine-mapping studies for the identification of genes. Such information can be used together with traditional methods in breeding programs or even for a better understanding of the phenotypes of swine production.

Gene networks for total number born in pigs across divergent environments

For reproductive traits such as total number born (TNB), variance due to different environments is highly relevant in animal breeding. In this study, we aimed to perform a gene-network analysis for TNB in pigs across different environments using genomic reaction norm models. Thus, based on relevant single-nucleotide polymorphisms and linkage disequilibrium blocks across environments obtained from GWAS, different sets of candidate genes having biological roles linked to TNB were identified. Network analysis across environment levels resulted in gene interactions consistent with known mammal’s fertility biology, captured relevant transcription factors for TNB biology and pointing out different sets of candidate genes for TNB in different environments. These findings may have important implication for animal production, as optimal breeding may vary depending on later environments. Based on these results, genomic diversity was identified and inferred across environments highlighting differential genetic control in each scenario.

Multiple-trait genomewide mapping and gene network analysis for scrotal circumference growth curves in Brahman cattle1

Fertility traits are economically important in cattle breeding programs. Scrotal circumference (SC) measures are repeatable, easily obtained, highly heritable, and positively correlated with female fertility traits and sperm quality traits in males. A useful approach to summarize SC measures over time is using nonlinear models, which summarize specific measures of SC in a few parameters with biological interpretation. This approach facilitates the selection of bulls with larger SC and maturity index (K), that is, early maturing animals. Because SC is a sex-limited trait, identifying the underlying genomics of growth curve parameters will allow selection across both males and females. We reported the first multitrait genomewide association study (GWAS) of estimated growth curve parameters for SC data in Brahman cattle. Five widely used nonlinear models were tested to fit a total of 3,612 SC records, measured at 6, 12, 18, and 24 mo of age. The von Bertalanffy model, individually fitted for each animal, best fit this SC data. Parameter estimates SC at maturity (A) and K as well as SC at all ages were jointly analyzed in a GWAS to identify 1-Mb regions most strongly associated with each trait. Heritabilities were 0.25 for K and 0.32 for A and ranged from 0.51 to 0.72 for SC at 6 (SC6), 12 (SC12), 18 (SC18), and 24 mo of age (SC24). An overlapping window on chromosome 14 explaining around 0.8% of genetic variance for K, SC12, SC18, and SC24 was observed. The major positional candidate genes within 1 Mb upstream and downstream of this overlapping window were , , , and . Windows of 1 Mb explaining more than 0.4% of each trait on chromosomes 1, 3, 6, 7, 14, 17, 18, 24, 25, and 26 were identified. Pathways and net-work analyses were indicated through transcription factors playing a role on fertility traits: , , , , , , and . Further validation studies on larger populations or other breeds are required to validate these findings and to improve our understanding of the biology and complex genetic architecture of traits associated with scrotal growth and male fertility in cattle.