RESUMEN

Chicken is an important source of protein for human nutrition and a model system for growth and developmental biology. Although the genetic architecture of quantitative traits in meat-type chickens has been the subject of ongoing investigation, the identification of mutations associated with carcass traits of economic interest remains challenging. Therefore, our aim was to identify predicted deleterious mutation, which potentially affects protein function, and test if they were associated with carcass traits in chickens. For that, we performed a genome-wide association analysis (GWAS) for breast, thigh and drumstick traits in meat-type chickens and detected 19 unique quantitative trait loci (QTL). We then used: (1) the identified windows; (2) QTL for abdominal fat detected in a previous study with the same population and (3) previously obtained whole genome sequence data, to identify 18 predicted deleterious single nucleotide polymorphisms (SNPs) in those QTL for further association with breast, thigh, drumstick and abdominal fat traits. Using the additive model, a predicted deleterious SNP c.482C > T (SIFT score of 0.4) was associated (p-value < 0.05) with abdominal fat weight and percentage. This SNP is in the second exon of the MYBPH gene, and its allele frequency deviates from Hardy-Weinberg equilibrium. In conclusion, our study provides evidence that the c.482C > T SNP in the MYBPH gene is a putative causal mutation for fat deposition in meat-type chickens.

RESUMEN

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 F2 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 F2 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.

Asunto(s)

RESUMEN

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.

Asunto(s)

RESUMEN

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 (FST) 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 FST-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. FST-based analysis revealed genetic differentiation in several genomic windows. Annotation of the consensus regions of ROH and FST 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 FST-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.

Asunto(s)

RESUMEN

Excessive fat deposition is a negative factor for poultry production because it reduces feed efficiency, increases the cost of meat production and is a health concern for consumers. We genotyped 497 birds from a Brazilian F2 Chicken Resource Population, using a high-density SNP array (600 K), to estimate the genomic heritability of fat deposition related traits and to identify genomic regions and positional candidate genes (PCGs) associated with these traits. Selection signature regions, haplotype blocks and SNP data from a previous whole genome sequencing study in the founders of this chicken F2 population were used to refine the list of PCGs and to identify potential causative SNPs. We obtained high genomic heritabilities (0.43-0.56) and identified 22 unique QTLs for abdominal fat and carcass fat content traits. These QTLs harbored 26 PCGs involved in biological processes such as fat cell differentiation, insulin and triglyceride levels, and lipid biosynthetic process. Three of these 26 PCGs were located within haplotype blocks there were associated with fat traits, five overlapped with selection signature regions, and 12 contained predicted deleterious variants. The identified QTLs, PCGs and potentially causative SNPs provide new insights into the genetic control of fat deposition and can lead to improved accuracy of selection to reduce excessive fat deposition in chickens.

Asunto(s)

RESUMEN

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.

Asunto(s)

RESUMEN

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.

Asunto(s)

RESUMEN

Performance traits are economically important and are targets for selection in breeding programs, especially in the poultry industry. To identify regions on the chicken genome associated with performance traits, different genomic approaches have been applied in the last years. The aim of this study was the application of CornellGBS approach (134,528 SNPs generated from a PstI restriction enzyme) on Genome-Wide Association Studies (GWAS) in an outbred F2 chicken population. We have validated 91.7% of these 134,528 SNPs after imputation of missed genotypes. Out of those, 20 SNPs were associated with feed conversion, one was associated with body weight at 35 days of age (P < 7.86E-07) and 93 were suggestively associated with a variety of performance traits (P < 1.57E-05). The majority of these SNPs (86.2%) overlapped with previously mapped QTL for the same performance traits and some of the SNPs also showed novel potential QTL regions. The results obtained in this study suggests future searches for candidate genes and QTL refinements as well as potential use of the SNPs described here in breeding programs.

Asunto(s)

RESUMEN

Chicken genotyping is becoming common practice in conventional animal breeding improvement. Despite the power of high-throughput methods for genotyping, their high cost limits large scale use in animal breeding and selection. In the present paper we optimized the CornellGBS, an efficient and cost-effective genotyping by sequence approach developed in plants, for its application in chickens. Here we describe the successful genotyping of a large number of chickens (462) using CornellGBS approach. Genomic DNA was cleaved with the PstI enzyme, ligated to adapters with barcodes identifying individual animals, and then sequenced on Illumina platform. After filtering parameters were applied, 134,528 SNPs were identified in our experimental population of chickens. Of these SNPs, 67,096 had a minimum taxon call rate of 90% and were considered 'unique tags'. Interestingly, 20.7% of these unique tags have not been previously reported in the dbSNP. Moreover, 92.6% of these SNPs were concordant with a previous Whole Chicken-genome re-sequencing dataset used for validation purposes. The application of CornellGBS in chickens showed high performance to infer SNPs, particularly in exonic regions and microchromosomes. This approach represents a cost-effective (~US$50/sample) and powerful alternative to current genotyping methods, which has the potential to improve whole-genome selection (WGS), and genome-wide association studies (GWAS) in chicken production.

Asunto(s)

RESUMEN

Two functional and positional candidate genes were selected in a region of chicken chromosome 1 (GGA1), based on their biological roles, and also where several quantitative trait loci (QTL) have been mapped and associated with performance, fatness and carcass traits in chickens. The insulin-like growth factor 1 (IGF1) gene has been associated with several physiological functions related to growth. The lysine (K)-specific demethylase 5A (KDM5A) gene participates in the epigenetic regulation of genes involved with the cell cycle. Our objective was to find associations of selected single-nucleotide polymorphisms (SNPs) in these genes with performance, fatness and carcass traits in 165 F(2) chickens from a resource population. In the IGF1 gene, 17 SNPs were detected, and in the KDM5A gene, nine SNPs were detected. IGF1 SNP c.47673G > A was associated with body weight and haematocrit percentage, and also with feed intake and percentages of abdominal fat and gizzard genotype × sex interactions. KDM5A SNP c.34208C > T genotype × sex interaction affected body weight, feed intake, percentages of abdominal fat (p = 0.0001), carcass, gizzard and haematocrit. A strong association of the diplotype × sex interaction (p < 0.0001) with abdominal fat was observed, and also associations with body weight, feed intake, percentages of carcass, drums and thighs, gizzard and haematocrit. Our findings suggest that the KDM5A gene might play an important role in the abdominal fat deposition in chickens. The IGF1 and KDM5A genes are strong candidates to explain the QTL mapped in this region of GGA1.

Asunto(s)

RESUMEN

A linkage map is essential not only for quantitative trait loci (QTL) mapping, but also for the organization and location of genes along the chromosomes. The present study is part of a project whose major objective is, besides from construction the linkage maps, the whole genome scan for mapping QTL for performance traits in the Brazilian experimental chicken population. Linkage maps of chicken chromosomes 6 to 8, 11 and 13 were constructed based on this population. The population was developed from two generations of crossbreeding between a broiler and a layer line. Fifty-one microsatellite markers were tested, from which 28 were informative: 4, 8, 7, 4 and 5 for chromosomes 6, 7, 8, 11 and 13, respectively. A SNP located in the leptin receptor gene was included for chromosome 8. Ten parental, 8 F1 and 459 F2 chickens from five full-sib families were genotyped with these markers. The number of total informative meioses per locus varied from 232 to 862, and the number of phase-known informative meioses from 0 to 764. Marker orders in the chromosomes coincided with those of the chicken consensus map, except for markers ADL0147 and MCW0213, on chromosome 13, which were inverted. The reduced number of phase-known informative meioses for ADL0147 (150) may be pointed out as a possible cause for this inversion, apart from the relative short distance between the two markers involved in the inversion (10.5 cM).

O mapa de ligação além de ser fundamental no mapeamento de locos de características quantitativas (QTLs) é importante na organização e localização de genes distribuídos ao longo dos cromossomos. O presente estudo é parte de um trabalho cujo objetivo maior, é a análise de mapeamento de QTLs para características de desempenho no genoma de uma população experimental desenvolvida no Brasil. Com base nesta população foram construídos os mapas de ligação dos cromossomos 6 a 8, 11 e 13 da galinha. A população foi desenvolvida a partir de duas gerações de cruzamentos entre uma linhagem de corte e uma de postura. Foram testados 51 marcadores microssatélites, dos quais 28 foram informativos: 4, 8, 7, 4 e 5 dos cromossomos 6, 7, 8, 11 e 13, respectivamente. Um SNP localizado no gene do receptor da leptina foi incluído no cromossomo 8. Os 10 parentais, 8 F1 e um total de 459 aves F2 de cinco famílias de irmãos completos foram genotipados com estes marcadores. O número de meioses informativas totais por loco variou de 232 a 862 e o de meioses informativas de fase conhecida de 0 a 764. A ordem dos marcadores nos cromossomos coincidiu com a do mapa consenso da galinha, com exceção dos marcadores ADL0147 e MCW0213 do cromossomo 13 que tiveram sua ordem invertida. O número reduzido de meioses informativas de fase conhecida para o marcador ADL0147 (150) pode ser apontado como uma possível causa para a inversão, além da relativa proximidade entre os dois marcadores envolvidos na inversão (10,5 cM).

RESUMEN

A linkage map is essential not only for quantitative trait loci (QTL) mapping, but also for the organization and location of genes along the chromosomes. The present study is part of a project whose major objective is, besides from construction the linkage maps, the whole genome scan for mapping QTL for performance traits in the Brazilian experimental chicken population. Linkage maps of chicken chromosomes 6 to 8, 11 and 13 were constructed based on this population. The population was developed from two generations of crossbreeding between a broiler and a layer line. Fifty-one microsatellite markers were tested, from which 28 were informative: 4, 8, 7, 4 and 5 for chromosomes 6, 7, 8, 11 and 13, respectively. A SNP located in the leptin receptor gene was included for chromosome 8. Ten parental, 8 F1 and 459 F2 chickens from five full-sib families were genotyped with these markers. The number of total informative meioses per locus varied from 232 to 862, and the number of phase-known informative meioses from 0 to 764. Marker orders in the chromosomes coincided with those of the chicken consensus map, except for markers ADL0147 and MCW0213, on chromosome 13, which were inverted. The reduced number of phase-known informative meioses for ADL0147 (150) may be pointed out as a possible cause for this inversion, apart from the relative short distance between the two markers involved in the inversion (10.5 cM).

O mapa de ligação além de ser fundamental no mapeamento de locos de características quantitativas (QTLs) é importante na organização e localização de genes distribuídos ao longo dos cromossomos. O presente estudo é parte de um trabalho cujo objetivo maior, é a análise de mapeamento de QTLs para características de desempenho no genoma de uma população experimental desenvolvida no Brasil. Com base nesta população foram construídos os mapas de ligação dos cromossomos 6 a 8, 11 e 13 da galinha. A população foi desenvolvida a partir de duas gerações de cruzamentos entre uma linhagem de corte e uma de postura. Foram testados 51 marcadores microssatélites, dos quais 28 foram informativos: 4, 8, 7, 4 e 5 dos cromossomos 6, 7, 8, 11 e 13, respectivamente. Um SNP localizado no gene do receptor da leptina foi incluído no cromossomo 8. Os 10 parentais, 8 F1 e um total de 459 aves F2 de cinco famílias de irmãos completos foram genotipados com estes marcadores. O número de meioses informativas totais por loco variou de 232 a 862 e o de meioses informativas de fase conhecida de 0 a 764. A ordem dos marcadores nos cromossomos coincidiu com a do mapa consenso da galinha, com exceção dos marcadores ADL0147 e MCW0213 do cromossomo 13 que tiveram sua ordem invertida. O número reduzido de meioses informativas de fase conhecida para o marcador ADL0147 (150) pode ser apontado como uma possível causa para a inversão, além da relativa proximidade entre os dois marcadores envolvidos na inversão (10,5 cM).