Assessment of the Genetic Diversity of a Local Pig Breed Using Pedigree and SNP Data

Abstract

Herein, the genetic diversity of the local Přeštice Black-Pied pig breed was assessed by the simultaneous analysis of the pedigree and single nucleotide polymorphism (SNP) data. The information about sire line, dam, date of birth, sex, breeding line, and herd for 1971 individuals was considered in the pedigree analysis. The SNP analysis (n = 181) was performed using the Illumina PorcineSNP60 BeadChip kit. The quality of pedigree and SNPs and the inbreeding coefficients (F) and effective population size (Ne) were evaluated. The correlations between inbreeding based on the runs of homozygosity (FROH) and pedigree (FPED) were also calculated. The average FPED for all animals was 3.44%, while the FROH varied from 10.81% for a minimum size of 1 Mbp to 3.98% for a minimum size of 16 Mbp. The average minor allele frequency was 0.28 ± 0.11. The observed and expected within breed heterozygosities were 0.38 ± 0.13 and 0.37 ± 0.12, respectively. The Ne, obtained using both the data sources, reached values around 50 animals. Moderate correlation coefficients (0.49–0.54) were observed between FPED and FROH. It is necessary to make decisions that stabilize the inbreeding rate in the long-term using optimal contribution selection based on the available SNP data.

An empirical test of the estimation of historical effective population size using Drosophila melanogaster

“…The method of Santiago et al (2020) has now been applied to different species, particularly in the last year, including insects, such as honeybees (Sang et al, 2022); birds, such as Black Robin (von Seth et al, 2022); fishes, such as turbot, seabream and seabass (Saura et al, 2021), Baltic herring (Atmore et al, 2022), pikeperch (De Los Ríos-Pérez et al, 2022, coho salmon (Martinez et al, 2022), catfish (Coimbra et al, 2023) and sailfish (Ferrette et al, 2023); wild mammals, such as grey wolf (Pacheco et al, 2022), killer whales (Kardos et al, 2023), sika deer (Iijima et al, 2023), scimitar-horned oryx (Humble et al, 2023) and gorilla (Alvarez-Estape et al, 2023); humans (Bird et al, 2023); domestic species, such as pigs (Krupa et al, 2022), cattle (Jin et al, 2022;Magnier et al, 2022), sheep (Djokic et al, 2023;Drzaic et al, 2022), horse (Criscione et al, 2022) and chicken (Gao et al, 2023;Liu et al, 2023); plants, such as walnut (Ding et al, 2022); crustaceans, such as Daphnia (Wersebe & Weider, 2023) and fungi (Singh et al, 2021). As suggested by Santiago et al (2020), the method is generally reliable for about 200 generations in the past, although…”

Expression and Genetic Effects of GLI Pathogenesis-Related 1 Gene on Backfat Thickness in Pigs

“…SNPs are genetic variations of single base pairs occurring in the genomic sequence impacting gene expression activities, amino-acid substitution, and dysfunction [ 28 ]. The occurrence and frequency of SNPs have contributed greatly to the assessment of genetic diversity and the genetic variation of complex quantitative traits [ 29 , 30 ]. Therefore, we detected the polymorphism of the GLIPR1 gene and analyzed the association between the mutations and 6–7 rib BFT.…”

Impact of population structure in the estimation of recent historical effective population size by the software GONE

“…The possibility of estimating changes in population size in the recent past is particularly useful in livestock species, for which the start of breeding programs may imply substantial changes in N e . To date, this software has been applied to various breeds of pigs [ 20 ], cattle [ 21 , 22 ], sheep [ 23 , 24 ], horses [ 25 ] and chickens [ 26 , 27 ], and fish species such as turbot, seabream and seabass [ 16 ], Baltic herring [ 28 ], pikeperch [ 29 ], coho salmon [ 30 ], catfish [ 31 ] and sailfish [ 32 ].…”