Quantitative trait loci associated with fatness in a broiler–layer cross

Campos, Rita; Nones, Kátia; Ledur, Mônica Corrêa; Moura, Ana Silvia Alves Meira Tavares; Pinto, L. F. B.; Ambo, M.; Boschiero, Clarissa; Ruy, Deborah Clea; Baron, Erica Elias; Ninov, Kerli; Altenhofen, C. A. B.; Silva, R. A. M. S.; Rosário, Millor Fernandes do; Burt, David W.; Coutinho, Luiz Lehmann

doi:10.1111/j.1365-2052.2009.01910.x

Cited by 49 publications

(77 citation statements)

References 38 publications

(54 reference statements)

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“…This may be the QTL that was detected in the present study at 115 cM, although with a significant additive effect and explaining approximately 2.33% phenotypic variance. These differences may result from adjustment in the infinitesimal genetic effect used in the present study and not considered in the work by Campos et al (2009).…”

Section: Resultsmentioning

confidence: 88%

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Mapping quantitative trait loci in Gallus gallus using principal components

Pinto¹,

Packer²,

Ledur

et al. 2010

R. Bras. Zootec.

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-This study aimed at mapping QTL (quantitative trait loci) using linear combinations of characteristics of economical interest in Gallus gallus. A total of 350 F2 chickens from an initial crossing among males from a broiler line (TT) with females from a layer line (CC) were used. It was conducted a QTL mapping in chromosomes of Gallus gallus (GGA1, GGA3, GGA5, GGA8, GGA11, and GGA13) for 20 performance and carcass traits. For detecting QTL, it was used the likelihood ratio test between a reduced model (including fixed effects of sex, hatch and random effect of infinitesimal genetic value) and a full model (including all the previous effects plus QTL effects). When original characterists were analyzed, that is, before the formation of linear combinations, six significant QTLs were mapped at 1% in the genome, four in the GGA1 (live weight at 35 days of age and at 42 days of age, abdominal fat and heart weight); and two on GGA3 (live weight at 35 and 42 days of age); three significant QTLs at 5% in the genome, one on GGA1 (head weight), one on GGA3 (wings weight), and one on GGA8 (gizzard weight); besides seven suggestive linkages for several traits. When QTLs were mapped for principal components, many mapped QTLs were confirmed for original traits, in addition to finding three QTLs and eight suggestive linkages not mapped for the original traits. cromossomos Gallus gallus (GGA1, GGA3, GGA5, GGA8, GGA11 e GGA13), para 20 características de desempenho e de carcaça. Para detectar QTL foi utilizado o teste da razão de verossimilhanças entre um modelo reduzido (incluindo efeitos fixos de sexo, incubação e o efeito aleatório de valor genético infinitesimal) e um completo (incluindo todos os efeitos anteriores mais os efeitos de QTL). Ao analisar as características originais, ou seja, antes da formação das combinações lineares, foram mapeados seis QTLs significativos a 1% no genoma, quatro no GGA1 (peso vivo aos 35 dias, peso vivo aos 42 dias, gordura abdominal e peso do coração) e dois no GGA3 (peso vivo aos 35 e aos 42 dias de idade); três QTLs significativos a 5% no genoma, sendo um no GGA1 (peso da cabeça), um no GGA3 (peso das asas), e um no GGA8 (peso da moela); além de sete ligações sugestivas para diversas características. Ao mapear QTLs para os componentes principais, foram confirmados vários QTLs mapeados para as características originais, além de encontrar três QTLs e oito ligações sugestivas não mapeadas para as características originais.Palavras-chave: frangos, galinha, genoma, variáveis canônicas Revista Brasileira de Zootecnia

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Section: Resultsmentioning

confidence: 88%

“…Some QTLs mapped in this population have been described by Nones et al (2006), Ambo et al (2009) and Campos et al (2009). Procedures seeking to reduce the occurrence of false positives or negatives were not employed in these studies, except of course to adjust the level of type I error to an acceptable level.…”

Section: Introductionmentioning

confidence: 99%

Mapping quantitative trait loci in Gallus gallus using principal components

Pinto¹,

Packer²,

Ledur

et al. 2010

R. Bras. Zootec.

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“…Therefore, genetic studies have been performed to map genes and genomic loci that affect growth, body composition (MCELROY et al 2006, CAMPOS et al 2009, and reproduction traits (TUISKULA-HAAVISTO et al 2002, SASAKI et al 2004, HANSEN et al 2005, SCHREIWEIS et al 2006. If inbred lines of diverse selection lines are used for gene mapping experiments, the probability is very high that different alleles contributing to different traits segregate in the mapping population, and thus these genetic differences can be identified.…”

Section: Introductionmentioning

confidence: 99%

Phenotypic characterization of chicken inbred lines that differ extremely in growth, body composition and egg production traits

et al. 2010

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The development of phenotypically and genetically divergent inbred chicken lines as simplified genetic models facilitates the identification of genes and contributes to the elucidation of gene functions. In this study, we characterized a New Hampshire (NH) population with its partial inbred derivative, New Hampshire inbred (NHI), and a White Leghorn inbred line (WL77). Both NHI and WL77 lines were inbred after selection for high meat yield or low egg weight, respectively. The inbreeding levels in NHI and WL77 are about 86 % and 100 %, respectively. Animals of the NHI line grew twice as fast, were about two times as heavy at 20 weeks, and deposited 9.3 times as much fat as WL77. NHI females reached sexual maturity, indicated by age at first egg, earlier, had a 35 % higher egg production ratio, and their eggs were on average 6 g heavier compared to WL77 females. The NHI and WL77 lines were extremely different for most traits, which makes them suitable for cross-bred experiments to map quantitative trait loci and identify genes contributing to the observed differences.

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“…A total of 649 animals were genotyped using 127 microsatellite markers, as previously described (Nones et al, 2006;Campos et al, 2009). Genotyping was carried out using a MegaBACE automated sequencer, and fragment size analysis was performed using the Genetic Profiler software (both GE HealthCare, Little Chalfont, BKM, UK).…”

Section: Phenotypes and Genotypingmentioning

confidence: 99%

“…Without adjusting BW42 as a covariate, many QTL regions were mapped for these traits nearby regions associated with BW42 in the same population used in this study (Nones et al, 2006;Ambo et al, 2009;Campos et al, 2009;Baron et al, 2011;Nones et al, 2012). When BW42 was included as a covariate in the model, only three QTL were mapped: two for tibia weight and another for tibia width (Table 3).…”

Section: Quantitative Trait Loci Mappingmentioning

confidence: 99%

Genetic parameters and mapping quantitative trait loci associated with tibia traits in broilers

Ragognetti¹,

Stafuzza²,

Silva³

et al. 2015

Genet. Mol. Res.

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ABSTRACT. Selection among broilers for performance traits is resulting in locomotion problems and bone disorders, once skeletal structure is not strong enough to support body weight in broilers with high growth rates. In this study, genetic parameters were estimated for body weight at 42 days of age (BW42), and tibia traits (length, width, and weight) in a population of broiler chickens. Quantitative trait loci (QTL) were identified for tibia traits to expand our knowledge of the genetic architecture of the broiler population. Genetic correlations ranged from 0.56 ± 0.18 (between tibia length and BW42) to 0.89 ± 0.06 (between tibia width and weight), suggesting that these traits are either controlled by pleiotropic genes or by genes that are in linkage disequilibrium. For QTL mapping, the genome was scanned with 127 microsatellites, representing a coverage of 2630 cM. Eight QTL were mapped on Gallus gallus chromosomes (GGA): GGA1, GGA4, GGA6, GGA13, and GGA24. The QTL regions for tibia length and weight were mapped on GGA1, between LEI0079 and MCW145 markers. The gene 17545 Genetic parameters and QTL mapping in broilers ©FUNPEC-RP www.funpecrp.com.br Genetics and Molecular Research 14 (4): 17544-17554 (2015) DACH1 is located in this region; this gene acts to form the apical ectodermal ridge, responsible for limb development. Body weight at 42 days of age was included in the model as a covariate for selection effect of bone traits. Two QTL were found for tibia weight on GGA2 and GGA4, and one for tibia width on GGA3. Information originating from these QTL will assist in the search for candidate genes for these bone traits in future studies.

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Quantitative trait loci associated with fatness in a broiler–layer cross

Cited by 49 publications

References 38 publications

Mapping quantitative trait loci in Gallus gallus using principal components

Mapping quantitative trait loci in Gallus gallus using principal components

Phenotypic characterization of chicken inbred lines that differ extremely in growth, body composition and egg production traits

Genetic parameters and mapping quantitative trait loci associated with tibia traits in broilers

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