TY - JOUR
T1 - Penalized classification for optimal statistical selection of markers from high-throughput genotyping: application in sheep breeds
AU - Mastrangelo, Salvatore
AU - Chiodi, Marcello
AU - Sardina, Maria Teresa
AU - Portolano, Baldassare
AU - Di Gerlando, Rosalia
AU - Sottile, Gianluca
AU - Tolone, Marco
PY - 2018
Y1 - 2018
N2 - The identification of individuals’ breed of origin has several practical applications in livestock and is useful in different biological contexts such as conservation genetics, breeding and authentication of animal products. In this paper, penalized multinomial regression was applied to identify the minimum number of single nucleotide polymorphisms (SNPs) from high-throughput genotyping data for individual assignment to dairy sheep breeds reared in Sicily. The combined use of penalized multinomial regression and stability selection reduced the number of SNPs required to 48. A final validation step on an independent population was carried out obtaining 100% correctly classified individuals. The results using independent analysis, such as admixture, Fst, principal component analysis and random forest, confirmed the ability of these methods in selecting distinctive markers. The identified SNPs may constitute a starting point for the development of a SNP based identification test as a tool for breed assignment and traceability of animal products.
AB - The identification of individuals’ breed of origin has several practical applications in livestock and is useful in different biological contexts such as conservation genetics, breeding and authentication of animal products. In this paper, penalized multinomial regression was applied to identify the minimum number of single nucleotide polymorphisms (SNPs) from high-throughput genotyping data for individual assignment to dairy sheep breeds reared in Sicily. The combined use of penalized multinomial regression and stability selection reduced the number of SNPs required to 48. A final validation step on an independent population was carried out obtaining 100% correctly classified individuals. The results using independent analysis, such as admixture, Fst, principal component analysis and random forest, confirmed the ability of these methods in selecting distinctive markers. The identified SNPs may constitute a starting point for the development of a SNP based identification test as a tool for breed assignment and traceability of animal products.
UR - http://hdl.handle.net/10447/243784
UR - https://www.cambridge.org/core/journals/animal/article/penalized-classification-for-optimal-statistical-selection-of-markers-from-highthroughput-genotyping-application-in-sheep-breeds/FBD2534AD5F3A7D3E50B8B269048D5A8
M3 - Article
VL - 12
SP - 1118
EP - 1125
JO - Animal
JF - Animal
SN - 1751-7311
ER -