Capturing resilience from phenotypic deviations: a case study using feed consumption and whole genome data in pigs

Abstract Background In recent years, interest has grown in quantifying resilience in livestock by examining deviations in target phenotypes. This method is based on the idea that variability in these phenotypes reflects an animal’s ability to adapt to external factors. By utilizing routinely collect...

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Main Authors: Enrico Mancin, Christian Maltecca, Jicaj Jiang, Yi Jian Huang, Francesco Tiezzi
Format: Article
Language:English
Published: BMC 2024-11-01
Series:BMC Genomics
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Online Access:https://doi.org/10.1186/s12864-024-11052-0
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author Enrico Mancin
Christian Maltecca
Jicaj Jiang
Yi Jian Huang
Francesco Tiezzi
author_facet Enrico Mancin
Christian Maltecca
Jicaj Jiang
Yi Jian Huang
Francesco Tiezzi
author_sort Enrico Mancin
collection DOAJ
description Abstract Background In recent years, interest has grown in quantifying resilience in livestock by examining deviations in target phenotypes. This method is based on the idea that variability in these phenotypes reflects an animal’s ability to adapt to external factors. By utilizing routinely collected time-series feed intake data in pigs, researchers can obtain a broad measure of resilience. This measure extends beyond specific conditions, capturing the impact of various unknown external factors that influence phenotype variations. Importantly, this method does not require additional phenotyping investments. Despite growing interest, the relationship between resilience indicators—calculated as deviations from longitudinally recorded target traits—and the mean of those traits remains largely unexplored. This gap raises the risk of inadvertently selecting for the mean rather than accurately capturing true resilience. Additionally, distinguishing between random phenotype fluctuations (white noise) and structural variations linked to resilience poses a challenge. With the aim of developing general resilience indicators applicable to commercial swine populations, we devised four resilience indicators utilizing daily feed consumption as the target trait. These include a canonical resilience indicator (BALnVar) and three novel ones (BAMaxArea, SPLnVar, and SPMaxArea), designed to minimize noise and ensure independence from daily feed consumption. We subsequently integrated these indicators with Whole Genome Sequencing using SLEMM algorithm, data from 1,250 animals to assess their efficacy in capturing resilience and their independence from the mean of daily feed consumption. Results Our findings revealed that conventional resilience indicators failed to differentiate from the mean of daily feed consumption, underscoring potential limitations in accurately capturing true resilience. Notably, significant associations involving conventional resilience indicators were identified on chromosome 1, which is commonly linked to body weight. Conclusion We observed that deviations in feed consumption can effectively serve as indicators for selecting resilience in commercial pig farming, as confirmed by the identification of genes such as PKN1 and GYPC. However, the identification of other genes, such as RNF152, related to growth, suggests that common resilience quantification methods may be more closely related to the mean of daily feed consumption rather than capturing true resilience.
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spelling doaj-art-036ddcbe0afb44b0898ab70089c81a212025-08-20T02:32:53ZengBMCBMC Genomics1471-21642024-11-0125112210.1186/s12864-024-11052-0Capturing resilience from phenotypic deviations: a case study using feed consumption and whole genome data in pigsEnrico Mancin0Christian Maltecca1Jicaj Jiang2Yi Jian Huang3Francesco Tiezzi4Department of Agronomy, Natural Resources, Animals and Environment, (DAFNAE), University of PadovaDepartment of Animal Science, North Carolina State UniversityDepartment of Animal Science, North Carolina State UniversitySmithfield Premium GeneticsDepartment of Agriculture, Food, Environment and Forestry (DAGRI), University of FlorenceAbstract Background In recent years, interest has grown in quantifying resilience in livestock by examining deviations in target phenotypes. This method is based on the idea that variability in these phenotypes reflects an animal’s ability to adapt to external factors. By utilizing routinely collected time-series feed intake data in pigs, researchers can obtain a broad measure of resilience. This measure extends beyond specific conditions, capturing the impact of various unknown external factors that influence phenotype variations. Importantly, this method does not require additional phenotyping investments. Despite growing interest, the relationship between resilience indicators—calculated as deviations from longitudinally recorded target traits—and the mean of those traits remains largely unexplored. This gap raises the risk of inadvertently selecting for the mean rather than accurately capturing true resilience. Additionally, distinguishing between random phenotype fluctuations (white noise) and structural variations linked to resilience poses a challenge. With the aim of developing general resilience indicators applicable to commercial swine populations, we devised four resilience indicators utilizing daily feed consumption as the target trait. These include a canonical resilience indicator (BALnVar) and three novel ones (BAMaxArea, SPLnVar, and SPMaxArea), designed to minimize noise and ensure independence from daily feed consumption. We subsequently integrated these indicators with Whole Genome Sequencing using SLEMM algorithm, data from 1,250 animals to assess their efficacy in capturing resilience and their independence from the mean of daily feed consumption. Results Our findings revealed that conventional resilience indicators failed to differentiate from the mean of daily feed consumption, underscoring potential limitations in accurately capturing true resilience. Notably, significant associations involving conventional resilience indicators were identified on chromosome 1, which is commonly linked to body weight. Conclusion We observed that deviations in feed consumption can effectively serve as indicators for selecting resilience in commercial pig farming, as confirmed by the identification of genes such as PKN1 and GYPC. However, the identification of other genes, such as RNF152, related to growth, suggests that common resilience quantification methods may be more closely related to the mean of daily feed consumption rather than capturing true resilience.https://doi.org/10.1186/s12864-024-11052-0Whole genome sequenceResilienceSwineFeed consumptionEnvironmental varianceLnVar
spellingShingle Enrico Mancin
Christian Maltecca
Jicaj Jiang
Yi Jian Huang
Francesco Tiezzi
Capturing resilience from phenotypic deviations: a case study using feed consumption and whole genome data in pigs
BMC Genomics
Whole genome sequence
Resilience
Swine
Feed consumption
Environmental variance
LnVar
title Capturing resilience from phenotypic deviations: a case study using feed consumption and whole genome data in pigs
title_full Capturing resilience from phenotypic deviations: a case study using feed consumption and whole genome data in pigs
title_fullStr Capturing resilience from phenotypic deviations: a case study using feed consumption and whole genome data in pigs
title_full_unstemmed Capturing resilience from phenotypic deviations: a case study using feed consumption and whole genome data in pigs
title_short Capturing resilience from phenotypic deviations: a case study using feed consumption and whole genome data in pigs
title_sort capturing resilience from phenotypic deviations a case study using feed consumption and whole genome data in pigs
topic Whole genome sequence
Resilience
Swine
Feed consumption
Environmental variance
LnVar
url https://doi.org/10.1186/s12864-024-11052-0
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