Small ruminants are one of the first species that have been domesticated and since then environmental and anthropogenic pressures have shaped the genome of population and breeds. Initially bred for a triple productive attitude (wool/leather, meat, milk), centuries of different breeding strategies led to the evolution of more specialised breeds. Adaptation to the local environmental conditions also contributed to breeds’ formation making them able to survive to harsh environments and developing specific traits. The growing need for increased animal productivity emerged with a strong pressure, due to human demographic expansions. These new exigencies drove the research of genetic tools more and more precise with the aim of improving the efficiency of the livestock productions. Traditional and indigenous breeds, characterised by a lower production compared to commercial breeds, have been often affected by an uncontrolled crossbreed, leading to the genetic erosion and the loss of allelic variants that conferred advantageous characteristics. A correct balance between selection of important traits and the preservation of the genetic diversity should be the objective of the management plans of animal genetic resources (AnGR).
To maintain the balance between conservation status and selection of local and transboundary breeds it is necessary to view both aspects in the context of global current problems like climate change and product demand. Several advances have been made in developing and implementing genomic tools and strategies for a more efficient use of AnGR and to support sustainable productivity. Genomics has an important role in addressing several research challenges for example assessing the level of inbreeding, the introgression of foreign alleles and the genomic identification of candidate genes that regulate the complex mechanism of adaptation. But predicting the population/breed viability or capacity to adapt to climate change based on genomic information will require not only the identification of relevant loci and specific variants, but also a quantitative estimate of their connection to fitness, resilience, efficiency, and demographic parameters. To incorporate several analytical approaches with the most efficient techniques for detecting DNA sequences differences and a growing list of bioinformatic tools currently available is the right way to address these challenges.
We welcome articles that contribute to the goals of this Research Topic which are:
- to better understand the mechanism involved in the process of breed formation, including the adaptation to environmental conditions, the genetic differentiation of population and breeds, to detect footprints of selection, genomic inbreeding and inbreeding depression.
- to dissect the populations history, past migrations and other demographic events that shaped the present-day breeds.
- to genetically characterise indigenous breeds for their revaluation and preservation, as source of biodiversity and genetic heritage elucidating genetic signals of origin, spread, and introgression in small landraces populations.
- to integrate novel and the state-of-the art- genomic techniques as well as bioinformatic tools and ecological analysis to get information useful to cope with these important challenges.
- to explore the field of machine learning in animal genetics, which aims at applied algorithms that improve with experience, allows to assist in the analysis of large and complex datasets through the analysis of genome sequencing datasets, including annotation of elements of sequence and epigenetic, proteomic, or metabolomic data.
Small ruminants are one of the first species that have been domesticated and since then environmental and anthropogenic pressures have shaped the genome of population and breeds. Initially bred for a triple productive attitude (wool/leather, meat, milk), centuries of different breeding strategies led to the evolution of more specialised breeds. Adaptation to the local environmental conditions also contributed to breeds’ formation making them able to survive to harsh environments and developing specific traits. The growing need for increased animal productivity emerged with a strong pressure, due to human demographic expansions. These new exigencies drove the research of genetic tools more and more precise with the aim of improving the efficiency of the livestock productions. Traditional and indigenous breeds, characterised by a lower production compared to commercial breeds, have been often affected by an uncontrolled crossbreed, leading to the genetic erosion and the loss of allelic variants that conferred advantageous characteristics. A correct balance between selection of important traits and the preservation of the genetic diversity should be the objective of the management plans of animal genetic resources (AnGR).
To maintain the balance between conservation status and selection of local and transboundary breeds it is necessary to view both aspects in the context of global current problems like climate change and product demand. Several advances have been made in developing and implementing genomic tools and strategies for a more efficient use of AnGR and to support sustainable productivity. Genomics has an important role in addressing several research challenges for example assessing the level of inbreeding, the introgression of foreign alleles and the genomic identification of candidate genes that regulate the complex mechanism of adaptation. But predicting the population/breed viability or capacity to adapt to climate change based on genomic information will require not only the identification of relevant loci and specific variants, but also a quantitative estimate of their connection to fitness, resilience, efficiency, and demographic parameters. To incorporate several analytical approaches with the most efficient techniques for detecting DNA sequences differences and a growing list of bioinformatic tools currently available is the right way to address these challenges.
We welcome articles that contribute to the goals of this Research Topic which are:
- to better understand the mechanism involved in the process of breed formation, including the adaptation to environmental conditions, the genetic differentiation of population and breeds, to detect footprints of selection, genomic inbreeding and inbreeding depression.
- to dissect the populations history, past migrations and other demographic events that shaped the present-day breeds.
- to genetically characterise indigenous breeds for their revaluation and preservation, as source of biodiversity and genetic heritage elucidating genetic signals of origin, spread, and introgression in small landraces populations.
- to integrate novel and the state-of-the art- genomic techniques as well as bioinformatic tools and ecological analysis to get information useful to cope with these important challenges.
- to explore the field of machine learning in animal genetics, which aims at applied algorithms that improve with experience, allows to assist in the analysis of large and complex datasets through the analysis of genome sequencing datasets, including annotation of elements of sequence and epigenetic, proteomic, or metabolomic data.
