Associação e seleção genômica para eficiência alimentar em bovinos Nelore
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2021-02-22
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Universidade Federal de Goiás
Resumo
The aim of this study was to estimate genetic parameters for feed efficiency, growth,
reproductive and carcass traits in commercial Nelore cattle herds, and the correlated response
between them. It was also aimed perform a study of genomic selection evaluating prediction
methods, validation approaches and pseudo-phenotypes, and conduct a weighted single-step
genome-wide association study and an enrichment analysis for feed efficiency of feed
efficiency related traits. Residual feed intake (RFI), dry matter intake (DMI), feed conversion
ratio (FCR), feed efficiency (FE), residual live weight gain (RG), residual intake and live weight
gain (RIG), birth weight (BW), weight at 120 (W120), 240 (W240), 365 (W365), and 450
(W450) days of age, scrotal circumference at 365 (SC365) and 450 (SC450) days of age, rib
eye area (REA), backfat thickness (BF) and rump fat thickness (RF) were evaluated. The
growth, reproductive and carcass traits records from 15,639 Nelore cattle were used. Data from feed efficiency tests carried out between 2011 and 2018, with phenotypic and genotypic
information of 4,329 and 3,594 animals, respectively, were considered. The genetic
parameters were estimated in a single step approach (ssGBLUP). Six prediction methods of
genomic breeding values (GEBVs) were used: ssGBLUP, Bayes A, Bayes B, Bayes Cπ,
BLASSO, and Bayes R. Three validation approaches were used: 1) random: the data set was
randomly divided into ten subsets and the validation was done in each subset at a time; 2)
age: the population was divided into training and validation set based on the year of birth,
with the first group consisting of animals born between 2010 and 2016 and the second group
born in 2017; 3) genetic breeding value (EBV) accuracy: were divided into two groups, with
animals with accuracy above 0.45 considered as the training population, and below 0.45 the
validation set. We checked the accuracy and bias of GEBV. The percentage of variance
explained by windows of 10 adjacent SNPs was used to identify regions that explained more
than 0.5% of the additive genetic variance on each trait. The feed efficiency related traits
showed low to moderate heritabilities, ranging from 0.07 to 0.20. Feed efficiency related traits
showed low genetic correlations with growth (-0.19 to 0.24), reproductive (-0.24 to 0.27) and
carcass (-0.17 to 0.27) traits, except for growth with DMI (0.32 to 0.56) and FE (-0.40). The
results showed that the prediction ability were similar between the prediction methods. The
low heritability obtained, mainly for FE (0.07±0.03) and FCR (0.09±0.03), limited the GEBVs
accuracy, which ranged from low to moderate. The regression coefficient estimates were close
to 1, and similar between the prediction methods, validation approaches, and pseudophenotypes.
On average and despite low variation (0.0331), the random cross-validation
presented the most accurate predictions, ranging from 0.07 to 0.037, than EBV accuracy and
age. The prediction ability was higher for phenotype adjusted for fixed effects than for EBV
and EBV deregressed (30.0 and 34.3%, respectively). Enrichment analysis by The Database
for Annotation, Visualization and Integrated Discovery (DAVID) revealed several functional
vias such as neuropeptide signaling pathway (GO:0007218), negative regulation of canonical
Wnt signaling pathway (GO:0090090), detection of chemical stimulus involved in sensory
perception of bitter taste (GO:0001580), bitter taste receptor activity (GO:0033038),
neuropeptide hormone activity (GO:0005184), bile secretion (bta04976), taste transduction
(bta0742), and glucagon signaling pathway (bta04922). The selection to improve growth,
reproductive and carcass traits would not change RFI, RG, and RIG. On the other hand, DMI,
FE and FCR may lead to an increase in body weight, in addition to the selection for FCR may
lead to a reduction in carcass yield. The genetic background of feed efficiency related traits
are different, which would lead to different genetic responses. The choice of the most
adequate selection criterion depends on the production system and goals. Genomic prediction
methods can provide a reliable estimate of genomic breeding values for RFI, DMI, RG and
RGI, traits that may have higher genetic gain and selection viability than FE and FCR.
Enrichment analyzes showed genes associated with in insulin, leptin, glucose, protein and lipid
metabolism, energy balance, heat and oxidative stress, zinc finger system, bile secretion,
satiety, feed behavior, salivation, digestion and absorption of nutrients. The identification of
these genomic regions and their respective genes provide information about genetic basis and
biologic regulation for Nelore feed efficiency related traits.
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Citação
BRUNES, L. C. Associação e seleção genômica para eficiência alimentar em bovinos Nelore. 2021. 221 f. Tese (Doutorado em Zootecnia) - Universidade Federal de Goiás, Goiânia, 2021.