Search

Background: Understanding the molecular underpinnings of phenotypic variations is critical for enhancing poultry breeding programs. The Brazilian broiler (TT) and laying hen (CC) lines exhibit striking differences in body weight, growth potential, and muscle mass. Our work aimed to compare the global transcriptome of wing and pectoral tissues during the early development (days 2.5 to 3.5) of these chicken lines, unveiling disparities in gene expression and regulation., Results: Different and bona-fide transcriptomic profiles were identified for the compared lines. A similar number of up- and downregulated differentially expressed genes (DEGs) were identified, considering the broiler line as a reference. Upregulated DEGs displayed an enrichment of protease-encoding genes, whereas downregulated DEGs exhibited a prevalence of receptors and ligands. Gene Ontology analysis revealed that upregulated DEGs were mainly associated with hormone response, mitotic cell cycle, and different metabolic and biosynthetic processes. In contrast, downregulated DEGs were primarily linked to communication, signal transduction, cell differentiation, and nervous system development. Regulatory networks were constructed for the mitotic cell cycle and cell differentiation biological processes, as their contrasting roles may impact the development of distinct postnatal traits. Within the mitotic cell cycle network, key upregulated DEGs included CCND1 and HSP90, with central regulators being NF-κB subunits (RELA and REL) and NFATC2. The cell differentiation network comprises numerous DEGs encoding transcription factors (e.g., HOX genes), receptors, ligands, and histones, while the main regulatory hubs are CREB, AR and epigenetic modifiers. Clustering analyses highlighted PIK3CD as a central player within the differentiation network., Conclusions: Our study revealed distinct developmental transcriptomes between Brazilian broiler and layer lines. The gene expression profile of broiler embryos seems to favour increased cell proliferation and delayed differentiation, which may contribute to the subsequent enlargement of pectoral tissues during foetal and postnatal development. Our findings pave the way for future functional studies and improvement of targeted traits of economic interest in poultry., (© 2024. The Author(s).)

Introduction: White Striping (WS) and Wooden Breast (WB) pectoral myopathies are relevant disorders for contemporary broiler production worldwide. Several studies aimed to elucidate the genetic components associated with the occurrence of these myopathies. However, epigenetic factors that trigger or differentiate these two conditions are still unclear. The aim of this study was to identify miRNAs differentially expressed (DE) between normal and WS and WB-affected broilers, and to verify the possible role of these miRNAs in metabolic pathways related to the manifestation of these pectoral myopathies in 28-day-old broilers., Results: Five miRNAs were DE in the WS vs control (gga-miR-375, gga-miR-200b-3p, gga-miR-429-3p, gga-miR-1769-5p, gga-miR-200a-3p), 82 between WB vs control and 62 between WB vs WS. Several known miRNAs were associated with WB, such as gga-miR-155, gga-miR-146b, gga-miR-222, gga-miR-146-5p, gga-miR- 29, gga-miR-21-5p, gga-miR-133a-3p and gga-miR-133b. Most of them had not previously been associated with the development of this myopathy in broilers. We also have predicted 17 new miRNAs expressed in the broilers pectoral muscle. DE miRNA target gene ontology analysis enriched 6 common pathways for WS and WB compared to control: autophagy, insulin signaling, FoxO signaling, endocytosis, and metabolic pathways. The WS vs control contrast had two unique pathways, ERBB signaling and the mTOR signaling, while WB vs control had 14 unique pathways, with ubiquitin-mediated proteolysis and endoplasmic reticulum protein processing being the most significant., Conclusions: We found miRNAs DE between normal broilers and those affected with breast myopathies at 28 days of age. Our results also provide novel evidence of the miRNAs role on the regulation of WS and in the differentiation of both WS and WB myopathies. Overall, our study provides insights into miRNA-mediated and pathways involved in the occurrence of WS and WB helping to better understand these chicken growth disorders in an early age. These findings can help developing new approaches to reduce these complex issues in poultry production possibly by adjustments in nutrition and management conditions. Moreover, the miRNAs and target genes associated with the initial stages of WS and WB development could be potential biomarkers to be used in selection to reduce the occurrence of these myopathies in broiler production., (© 2024. The Author(s).)

Background: Umbilical Hernia (UH) is characterized by the passage of part of the intestine through the umbilical canal forming the herniary sac. There are several potential causes that can lead to the umbilical hernia such as bacterial infections, management conditions and genetic factors. Since the genetic components involved with UH are poorly understood, this study aimed to identify polymorphisms and genes associated with the manifestation of umbilical hernia in pigs using exome and transcriptome sequencing in a case and control design., Results: In the exome sequencing, 119 variants located in 58 genes were identified differing between normal and UH-affected pigs, and in the umbilical ring transcriptome, 46 variants were identified, located in 27 genes. Comparing the two methodologies, we obtained 34 concordant variants between the exome and transcriptome analyses, which were located in 17 genes, distributed in 64 biological processes (BP). Among the BP involved with UH it is possible to highlight cell adhesion, cell junction regulation, embryonic morphogenesis, ion transport, muscle contraction, within others., Conclusions: We have generated the first exome sequencing related to normal and umbilical hernia-affected pigs, which allowed us to identify several variants possibly involved with this disorder. Many of those variants present in the DNA were confirmed with the RNA-Seq results. The combination of both exome and transcriptome sequencing approaches allowed us to better understand the complex molecular mechanisms underlying UH in pigs and possibly in other mammals, including humans. Some variants found in genes and other regulatory regions are highlighted as strong candidates to the development of UH in pigs and should be further investigated., (© 2021. The Author(s).)

Background: Copy number variations (CNVs) are a major type of structural genomic variants that underlie genetic architecture and phenotypic variation of complex traits, not only in humans, but also in livestock animals. We identified CNVs along the chicken genome and analyzed their association with performance traits. Genome-wide CNVs were inferred from Affymetrix® high density SNP-chip data for a broiler population. CNVs were concatenated into segments and association analyses were performed with linear mixed models considering a genomic relationship matrix, for birth weight, body weight at 21, 35, 41 and 42 days, feed intake from 35 to 41 days, feed conversion ratio from 35 to 41 days and, body weight gain from 35 to 41 days of age., Results: We identified 23,214 autosomal CNVs, merged into 5042 distinct CNV regions (CNVRs), covering 12.84% of the chicken autosomal genome. One significant CNV segment was associated with BWG on GGA3 (q-value = 0.00443); one significant CNV segment was associated with BW35 (q-value = 0.00571), BW41 (q-value = 0.00180) and BW42 (q-value = 0.00130) on GGA3, and one significant CNV segment was associated with BW on GGA5 (q-value = 0.00432). All significant CNV segments were verified by qPCR, and a validation rate of 92.59% was observed. These CNV segments are located nearby genes, such as KCNJ11, MyoD1 and SOX6, known to underlie growth and development. Moreover, gene-set analyses revealed terms linked with muscle physiology, cellular processes regulation and potassium channels., Conclusions: Overall, this CNV-based GWAS study unravels potential candidate genes that may regulate performance traits in chickens. Our findings provide a foundation for future functional studies on the role of specific genes in regulating performance in chickens.

Background: Bacterial chondronecrosis with osteomyelitis (BCO) develops in the growth plate (GP) of the proximal femur and tibia and is initiated by damage to the less mineralized chondrocytes followed by colonization of opportunistic bacteria. This condition affects approximately 1% of all birds housed, being considered one of the major causes of lameness in fast growing broilers. Although several studies have been previously performed aiming to understand its pathogenesis, the molecular mechanisms involved with BCO remains to be elucidated. Therefore, this study aimed to generate a profile of global differential gene expression involved with BCO in the tibia of commercial broilers, through RNA sequencing analysis to identity genes and molecular pathways involved with BCO in chickens., Results: Our data showed 192 differentially expressed (DE) genes: 63 upregulated and 129 downregulated in the GP of the tibia proximal epiphysis of BCO-affected broilers. Using all DE genes, six Biological Processes (BP) were associated with bone development (connective tissue development, cartilage development, skeletal system development, organ morphogenesis, system development and skeletal system morphogenesis). The analyses of the upregulated genes did not indicate any significant BP (FDR < 0.05). However, with the downregulated genes, the same BP were identified when using all DE genes in the analysis, with a total of 26 coding genes explaining BCO in the tibia: ACAN, ALDH1A2, CDH7, CHAD, CHADL, COL11A1, COMP, CSGALNACT1, CYR61, FRZB, GAL3ST1, HAPLN1, IHH, KIF26B, LECT1, LPPR1, PDE6B, RBP4A, SERINC5, SFRP1, SOX8, SOX9, TENM2, THBS1, UCHL1 and WFIKKN2. In addition, seven transcription factors were also associated to BCO: NFATC2, MAFB, HIF1A-ARNT, EWSR1-FLI1, NFIC, TCF3 and NF-KAPPAB., Conclusions: Our data show that osteochondral downregulated genes are potential molecular causes of BCO in broilers, and the bacterial process seems to be, in fact, a secondary condition. Sixteen genes responsible for bone and cartilage formation were downregulated in BCO-affected broilers being strong candidate genes to trigger this disorder.

Background: The proximal femoral head separation (FHS) or epiphysiolysis is a prevalent disorder affecting the chicken femur epiphysis, being considered a risk factor to infection which can cause bacterial chondronecrosis with osteomyelitis in broilers. To identify the genetic mechanisms involved in epiphysiolysis, differentially expressed (DE) genes in the femur of normal and FHS-affected broilers were identified using RNA-Seq technology. Femoral growth plate (GP) samples from 35-day-old commercial male broilers were collected from 4 healthy and 4 FHS-affected broilers. Sequencing was performed using an Illumina paired-end protocol. Differentially expressed genes were obtained using the edgeR package based on the False Discovery Rate (FDR < 0.05)., Results: Approximately 16 million reads/sample were generated with 2 × 100 bp paired-end reads. After data quality control, approximately 12 million reads/sample were mapped to the reference chicken genome (Galgal5). A total of 12,645 genes were expressed in the femur GP. Out of those, 314 were DE between groups, being 154 upregulated and 160 downregulated in FHS-affected broilers. In the functional analyses, several biological processes (BP) were overrepresented. Among them, those related to cell adhesion, extracellular matrix (ECM), bone development, blood circulation and lipid metabolism, which are more related to chicken growth, are possibly involved with the onset of FHS. On the other hand, BP associated to apoptosis or cell death and immune response, which were also found in our study, could be related to the consequence of the FHS., Conclusions: Genes with potential role in the epiphysiolysis were identified through the femur head transcriptome analysis, providing a better understanding of the mechanisms that regulate bone development in fast-growing chickens. In this study, we highlighted the importance of cell adhesion and extracellular matrix related genes in triggering FHS. Furthermore, we have shown new insights on the involvement of lipidemia and immune response/inflammation with FHS in broilers. Understanding the changes in the GP transcriptome might support breeding strategies to address poultry robustness and to obtain more resilient broilers.

Background: Feed efficiency and growth rate have been targets for selection to improve chicken production. The incorporation of genomic tools may help to accelerate selection. We genotyped 529 individuals using a high-density SNP chip (600 K, Affymetrix®) to estimate genomic heritability of performance traits and to identify genomic regions and their positional candidate genes associated with performance traits in a Brazilian F 2 Chicken Resource population. Regions exhibiting selection signatures and a SNP dataset from resequencing were integrated with the genomic regions identified using the chip to refine the list of positional candidate genes and identify potential causative mutations., Results: Feed intake (FI), feed conversion ratio (FC), feed efficiency (FE) and weight gain (WG) exhibited low genomic heritability values (i.e. from 0.0002 to 0.13), while body weight at hatch (BW1), 35 days-of-age (BW35), and 41 days-of-age (BW41) exhibited high genomic heritability values (i.e. from 0.60 to 0.73) in this F 2 population. Twenty unique 1-Mb genomic windows were associated with BW1, BW35 or BW41, located on GGA1-4, 6-7, 10, 14, 24, 27 and 28. Thirty-eight positional candidate genes were identified within these windows, and three of them overlapped with selection signature regions. Thirteen predicted deleterious and three high impact sequence SNPs in these QTL regions were annotated in 11 positional candidate genes related to osteogenesis, skeletal muscle development, growth, energy metabolism and lipid metabolism, which may be associated with body weight in chickens., Conclusions: The use of a high-density SNP array to identify QTL which were integrated with whole genome sequence signatures of selection allowed the identification of candidate genes and candidate causal variants. One novel QTL was detected providing additional information to understand the genetic architecture of body weight traits. We identified QTL for body weight traits, which were also associated with fatness in the same population. Our findings form a basis for further functional studies to elucidate the role of specific genes in regulating body weight and fat deposition in chickens, generating useful information for poultry breeding programs.

Background: Poultry breeding programs have been focused on improvement of growth and carcass traits, however, this has resulted in correlated changes in internal organ weights and increased incidence of metabolic disorders. These disorders can affect feed efficiency or even cause death. We used a high density SNP array (600 K, Affymetrix) to estimate genomic heritability, perform genome-wide association analysis, and identify genomic regions and positional candidate genes (PCGs) associated with internal organ traits in an F2 chicken population. We integrated knowledge of haplotype blocks, selection signature regions and sequencing data to refine the list of PCGs., Results: Estimated genomic heritability for internal organ traits in chickens ranged from low (LUNGWT, 0.06) to high (GIZZWT, 0.45). A total of 20 unique 1 Mb windows identified on GGA1, 2, 4, 7, 12, 15, 18, 19, 21, 27 and 28 were significantly associated with intestine length, and weights or percentages of liver, gizzard or lungs. Within these windows, 14 PCGs were identified based on their biological functions: TNFSF11, GTF2F2, SPERT, KCTD4, HTR2A, RB1, PCDH7, LCORL, LDB2, NR4A2, GPD2, PTPN11, ITGB4 and SLC6A4. From those genes, two were located within haplotype blocks and three overlapped with selection signature regions. A total of 13,748 annotated sequence SNPs were in the 14 PCGs, including 156 SNPs in coding regions (124 synonymous, 26 non-synonymous, and 6 splice variants). Seven deleterious SNPs were identified in TNFSF11, NR4A2 or ITGB4 genes., Conclusions: The results from this study provide novel insights to understand the genetic architecture of internal organ traits in chickens. The QTL detection performed using a high density SNP array covered the whole genome allowing the discovery of novel QTL associated with organ traits. We identified PCGs within the QTL involved in biological processes that may regulate internal organ growth and development. Potential functional genetic variations were identified generating crucial information that, after validation, might be used in poultry breeding programs to reduce the occurrence of metabolic disorders.

Background: Natural and artificial selection leads to changes in certain regions of the genome resulting in selection signatures that can reveal genes associated with the selected traits. Selection signatures may be identified using different methodologies, of which some are based on detecting contiguous sequences of homozygous identical-by-descent haplotypes, called runs of homozygosity (ROH), or estimating fixation index (F ST ) of genomic windows that indicates genetic differentiation. This study aimed to identify selection signatures in a paternal broiler TT line at generations 7th and 16th of selection and to investigate the genes annotated in these regions as well as the biological pathways involved. For such purpose, ROH and F ST -based analysis were performed using whole genome sequence of twenty-eight chickens from two different generations., Results: ROH analysis identified homozygous regions of short and moderate size. Analysis of ROH patterns revealed regions commonly shared among animals and changes in ROH abundance and size between the two generations. Results also suggest that whole genome sequencing (WGS) outperforms SNPchip data avoiding overestimation of ROH size and underestimation of ROH number; however, sequencing costs can limited the number of animals analyzed. F ST -based analysis revealed genetic differentiation in several genomic windows. Annotation of the consensus regions of ROH and F ST windows revealed new and previously identified genes associated with traits of economic interest, such as APOB, IGF1, IGFBP2, POMC, PPARG, and ZNF423. Over-representation analysis of the genes resulted in biological terms of skeletal muscle, matrilin proteins, adipose tissue, hyperglycemia, diabetes, Salmonella infections and tyrosine., Conclusions: Identification of ROH and F ST -based analyses revealed selection signatures in TT line and genes that have important role in traits of economic interest. Changes in the genome of the chickens were observed between the 7th and 16th generations showing that ancient and recent selection in TT line may have acted over genomic regions affecting diseases and performance traits.

Background: Excess fat content in chickens has a negative impact on poultry production. The discovery of QTL associated with fat deposition in the carcass allows the identification of positional candidate genes (PCGs) that might regulate fat deposition and be useful for selection against excess fat content in chicken's carcass. This study aimed to estimate genomic heritability coefficients and to identify QTLs and PCGs for abdominal fat (ABF) and skin (SKIN) traits in a broiler chicken population, originated from the White Plymouth Rock and White Cornish breeds., Results: ABF and SKIN are moderately heritable traits in our broiler population with estimates ranging from 0.23 to 0.33. Using a high density SNP panel (355,027 informative SNPs), we detected nine unique QTLs that were associated with these fat traits. Among these, four QTL were novel, while five have been previously reported in the literature. Thirteen PCGs were identified that might regulate fat deposition in these QTL regions: JDP2, PLCG1, HNF4A, FITM2, ADIPOR1, PTPN11, MVK, APOA1, APOA4, APOA5, ENSGALG00000000477, ENSGALG00000000483, and ENSGALG00000005043. We used sequence information from founder animals to detect 4843 SNPs in the 13 PCGs. Among those, two were classified as potentially deleterious and two as high impact SNPs., Conclusions: This study generated novel results that can contribute to a better understanding of fat deposition in chickens. The use of high density array of SNPs increases genome coverage and improves QTL resolution than would have been achieved with low density. The identified PCGs were involved in many biological processes that regulate lipid storage. The SNPs identified in the PCGs, especially those predicted as potentially deleterious and high impact, may affect fat deposition. Validation should be undertaken before using these SNPs for selection against carcass fat accumulation and to improve feed efficiency in broiler chicken production.

Background: Meat and egg-type chickens have been selected for several generations for different traits. Artificial and natural selection for different phenotypes can change frequency of genetic variants, leaving particular genomic footprints throghtout the genome. Thus, the aims of this study were to sequence 28 chickens from two Brazilian lines (meat and white egg-type) and use this information to characterize genome-wide genetic variations, identify putative regions under selection using Fst method, and find putative pathways under selection., Results: A total of 13.93 million SNPs and 1.36 million INDELs were identified, with more variants detected from the broiler (meat-type) line. Although most were located in non-coding regions, we identified 7255 intolerant non-synonymous SNPs, 512 stopgain/loss SNPs, 1381 frameshift and 1094 non-frameshift INDELs that may alter protein functions. Genes harboring intolerant non-synonymous SNPs affected metabolic pathways related mainly to reproduction and endocrine systems in the white-egg layer line, and lipid metabolism and metabolic diseases in the broiler line. Fst analysis in sliding windows, using SNPs and INDELs separately, identified over 300 putative regions of selection overlapping with more than 250 genes. For the first time in chicken, INDEL variants were considered for selection signature analysis, showing high level of correlation in results between SNP and INDEL data. The putative regions of selection signatures revealed interesting candidate genes and pathways related to important phenotypic traits in chicken, such as lipid metabolism, growth, reproduction, and cardiac development., Conclusions: In this study, Fst method was applied to identify high confidence putative regions under selection, providing novel insights into selection footprints that can help elucidate the functional mechanisms underlying different phenotypic traits relevant to meat and egg-type chicken lines. In addition, we generated a large catalog of line-specific and common genetic variants from a Brazilian broiler and a white egg layer line that can be used for genomic studies involving association analysis with phenotypes of economic interest to the poultry industry.

Background: Genetic improvement in livestock populations can be achieved without significantly affecting genetic diversity if mating systems and selection decisions take genetic relationships among individuals into consideration. The objective of this study was to examine the genetic diversity of two commercial breeds of pigs. Genotypes from 1168 Landrace (LA) and 1094 Large White (LW) animals from a commercial breeding program in Brazil were obtained using the Illumina PorcineSNP60 Beadchip. Inbreeding estimates based on pedigree (F x) and genomic information using runs of homozygosity (F ROH) and the single nucleotide polymorphisms (SNP) by SNP inbreeding coefficient (F SNP) were obtained. Linkage disequilibrium (LD), correlation of linkage phase (r) and effective population size (N e ) were also estimated., Results: Estimates of inbreeding obtained with pedigree information were lower than those obtained with genomic data in both breeds. We observed that the extent of LD was slightly larger at shorter distances between SNPs in the LW population than in the LA population, which indicates that the LW population was derived from a smaller N e . Estimates of N e based on genomic data were equal to 53 and 40 for the current populations of LA and LW, respectively. The correlation of linkage phase between the two breeds was equal to 0.77 at distances up to 50 kb, which suggests that genome-wide association and selection should be performed within breed. Although selection intensities have been stronger in the LA breed than in the LW breed, levels of genomic and pedigree inbreeding were lower for the LA than for the LW breed., Conclusions: The use of genomic data to evaluate population diversity in livestock animals can provide new and more precise insights about the effects of intense selection for production traits. Resulting information and knowledge can be used to effectively increase response to selection by appropriately managing the rate of inbreeding, minimizing negative effects of inbreeding depression and therefore maintaining desirable levels of genetic diversity.

Background: Genome-wide association studies have successfully identified several loci underlying complex diseases in humans. The development of high density SNP maps in domestic animal species should allow the detection of QTLs for economically important traits through association studies with much higher accuracy than traditional linkage analysis. Here we report the association analysis of the dataset simulated for the XII QTL-MAS meeting (Uppsala). We used two strategies, single marker association and haplotype-based association (Blossoc) that were applied to i) the raw data, and ii) the data corrected for infinitesimal, sex and generation effects., Results: Both methods performed similarly in detecting the most strongly associated SNPs, about ten loci in total. The most significant ones were located in chromosomes 1, 4 and 5. Overall, the largest differences were found between corrected and raw data, rather than between single and multiple marker analysis. The use of raw data increased greatly the number of significant loci, but possibly also the rate of false positives. Bootstrap model aggregation removed most of discrepancies between adjusted and raw data when SMA was employed., Conclusion: Model choice should be carefully considered in genome-wide association studies.