The climatic and genetic heritage of Italian goat breeds with genomic SNP data

Selection signatures and landscape genomics analysis to reveal climate adaptation of goat breeds

Goats have achieved global prominence as essential livestock since their initial domestication, primarily owing to their remarkable adaptability to diverse environmental and production systems. Differential selection pressures influenced by climate have led to variations in their physical attributes, leaving genetic imprints within the genomes of goat breeds raised in diverse agroecological settings. In light of this, our study pursued a comprehensive analysis, merging environmental data with single nucleotide polymorphism (SNP) variations, to unearth indications of selection shaped by climate-mediated forces in goats. Through the examination of 43,300 SNPs from 51 indigenous goat breeds adapting to different climatic conditions using four analytical methods: latent factor mixed models (LFMM), F-statistics (Fst), Extended haplotype homozygosity across populations (XPEHH), and spatial analysis method (SAM), A total of 74 genes were revealed to display clear signs of selection, which are believed to be influenced by climatic conditions. Among these genes, 32 were consistently identified by at least two of the applied methods, and three genes (DENND1A, PLCB1, and ITPR2) were confirmed by all four approaches. Moreover, our investigation yielded 148 Gene Ontology (GO) terms based on these 74 genes, underlining pivotal biological pathways crucial for environmental adaptation. These pathways encompass functions like vascular smooth muscle contraction, cellular response to heat, GTPase regulator activity, rhythmic processes, and responses to temperature stimuli. Of significance, GO terms about endocrine regulation and energy metabolic responses, key for local adaptation were also uncovered, including biological processes, such as cell differentiation, regulation of peptide hormone secretion, and lipid metabolism. These findings contribute to our knowledge of the genetic structure of climate-triggered adaptation across the goat genome and have practical implications for marker-assisted breeding in goats.

The demographic history and adaptation of Canarian goat breeds to environmental conditions through the use of genome-wide SNP data

BACKGROUND

The presence of goats in the Canary Islands dates back to the late 1st millennium BC, which coincides with the colonization by the Amazigh settlers. However, the exact geographic origin of Canarian goats is uncertain since the Amazigh peoples were distributed over a wide spatial range. Nowadays, three Canarian breeds (Palmera, Majorera and Tinerfeña) are officially recognized, along with two distinct South and North Tinerfeña ecotypes, with the South Tinerfeña and Majorera goats thriving in arid and dry semi-desertic environments and the Palmera and North Tinerfeña goats are adapted to humid and temperate areas that are influenced by trade winds. Genotypes for 224 Canarian goats were generated using the Illumina Goat single nucleotide polymorphism (SNP)50 BeadChip. By merging these data with the genotypes from 1007 individuals of African and Southern European ancestry, our aim was to ascertain the geographic origin of the Canarian goats and identify genes associated with adaptation to diverse environmental conditions.

RESULTS

The diversity indices of the Canarian breeds align with most of those of the analyzed local breeds from Africa and Europe, except for the Palmera goats that showed lower levels of genetic variation. The Canarian breeds demonstrate a significant genetic differentiation compared to other populations, which indicates a history of prolonged geographic isolation. Moreover, the phylogenetic reconstruction indicated that the ancestry of the Canarian goats is fundamentally North African rather than West African. The ADMIXTURE and the TreeMix analyses showed no evidence of gene flow between Canarian goats and other continental breeds. The analysis of runs of homozygosity (ROH) identified 13 ROH islands while the window-based FST method detected 25 genomic regions under selection. Major signals of selection were found on Capra hircus (CHI) chromosomes 6, 7, and 10 using various comparisons and methods.

CONCLUSIONS

This genome-wide analysis sheds new light on the evolutionary history of the four breeds that inhabit the Canary Islands. Our findings suggest a North African origin of the Canarian goats. In addition, within the genomic regions highlighted by the ROH and FST approaches, several genes related to body size and heat tolerance were identified.

Characterization of heterozygosity-rich regions in Italian and worldwide goat breeds

Heterozygosity-rich regions (HRR) are genomic regions of high heterozygosity, which may harbor loci related to key functional traits such as immune response, survival rate, fertility, and other fitness traits. This study considered 30 Italian and 19 worldwide goat breeds genotyped with the Illumina GoatSNP50k BeadChip. The aim of the work was to study inter-breed relationships and HRR patterns using Sliding Window (SW) and Consecutive Runs (CR) detection methods. Genetic relationships highlighted a clear separation between non-European and European breeds, as well as the north-south geographic cline within the latter. The Pearson correlation coefficients between the descriptive HRR parameters obtained with the SW and CR methods were higher than 0.9. A total of 166 HRR islands were detected. CHI1, CHI11, CHI12 and CHI18 were the chromosomes harboring the highest number of HRR islands. The genes annotated in the islands were linked to various factors such as productive, reproductive, immune, and environmental adaptation mechanisms. Notably, the Montecristo feral goat showed the highest number of HRR islands despite the high level of inbreeding, underlining potential balancing selection events characterizing its evolutionary history. Identifying a species-specific HRR pattern could provide a clearer view of the mechanisms regulating the genome modelling following anthropogenic selection combined with environmental interaction.

Individual-based landscape genomics for conservation: An analysis pipeline

Landscape genomics can harness environmental and genetic data to inform conservation decisions by providing essential insights into how landscapes shape biodiversity. The massive increase in genetic data afforded by the genomic era provides exceptional resolution for answering critical conservation genetics questions. The accessibility of genomic data for non-model systems has also enabled a shift away from population-based sampling to individual-based sampling, which now provides accurate and robust estimates of genetic variation that can be used to examine the spatial structure of genomic diversity, population connectivity and the nature of environmental adaptation. Nevertheless, the adoption of individual-based sampling in conservation genetics has been slowed due, in large part, to concerns over how to apply methods developed for population-based sampling to individual-based sampling schemes. Here, we discuss the benefits of individual-based sampling for conservation and describe how landscape genomic methods, paired with individual-based sampling, can answer fundamental conservation questions. We have curated key landscape genomic methods into a user-friendly, open-source workflow, which we provide as a new R package, A Landscape Genomics Analysis Toolkit in R (algatr). The algatr package includes novel added functionality for all of the included methods and extensive vignettes designed with the primary goal of making landscape genomic approaches more accessible and explicitly applicable to conservation biology.

Phenotypic and Genomic Characterization of the Comune di Sicilia Goat: Towards the Conservation of an Endangered Local Breed

The Comune di Sicilia, a local goat breed from Sicily (Italy), is currently undergoing recognition as a distinct breed. This study aims to characterize the population both phenotypically and genomically to advance its recognition process. A total of 78 subjects from two locations were enrolled, and their phenotypic data, including qualitative traits and morphometric measurements of adult animals, were recorded and statistically analyzed. The goats were genotyped using the Illumina 50 k Goat SNPchip, comparing them with 473 goats from 15 Italian breeds. Population structure, phylogenetic relationships, admixture, and genomic inbreeding were analyzed. Additionally, subjects with different morphological traits were compared using FST and runs of homozygosity, leading to the identification of potential candidate genes associated with anotia and wattle presence in goats. The Comune di Sicilia breed exhibited distinctive genomic and phenotypic features, setting it apart from other breeds in the same region. However, moderate variability, possibly influenced by selection practices, was also observed. To ensure the breed's preservation and prevent excessive inbreeding, a comprehensive approach considering both morphology and genomic background is recommended. This study contributes valuable insights into the genetic peculiarities of the Comune di Sicilia goat, supporting its recognition as a unique and valuable breed.

Transcriptome analysis to identify candidate genes related to mammary gland development of Bactrian camel (Camelus bactrianus)

Introduction

The demand for camel milk, which has unique therapeutic properties, is increasing. The mammary gland is the organ in mammals responsible for the production and quality of milk. However, few studies have investigated the genes or pathways related to mammary gland growth and development in Bactrian camels. This study aimed to compare the morphological changes in mammary gland tissue and transcriptome expression profiles between young and adult female Bactrian camels and to explore the potential candidate genes and signaling pathways related to mammary gland development.

Methods

Three 2  years-old female camels and three 5  years-old adult female camels were maintained in the same environment. The parenchyma of the mammary gland tissue was sampled from the camels using percutaneous needle biopsy. Morphological changes were observed using hematoxylin-eosin staining. High-throughput RNA sequencing was performed using the Illumina HiSeq platform to analyze changes in the transcriptome between young and adult camels. Functional enrichment, pathway enrichment, and protein-protein interaction networks were also analyzed. Gene expression was verified using quantitative real-time polymerase chain reaction (qRT-PCR).

Results

Histomorphological analysis showed that the mammary ducts and mammary epithelial cells in adult female camels were greatly developed and differentiated from those in young camels. Transcriptome analysis showed that 2,851 differentially expressed genes were obtained in the adult camel group compared to the young camel group, of which 1,420 were upregulated, 1,431 were downregulated, and 2,419 encoded proteins. Functional enrichment analysis revealed that the upregulated genes were significantly enriched for 24 pathways, including the Hedgehog signaling pathway which is closely related to mammary gland development. The downregulated genes were significantly enriched for seven pathways, among these the Wnt signaling pathway was significantly related to mammary gland development. The protein-protein interaction network sorted the nodes according to the degree of gene interaction and identified nine candidate genes: PRKAB2, PRKAG3, PLCB4, BTRC, GLI1, WIF1, DKK2, FZD3, and WNT4. The expression of fifteen genes randomly detected by qRT-PCR showed results consistent with those of the transcriptome analysis.

Discussion

Preliminary findings indicate that the Hedgehog, Wnt, oxytocin, insulin, and steroid biosynthesis signaling pathways have important effects on mammary gland development in dairy camels. Given the importance of these pathways and the interconnections of the involved genes, the genes in these pathways should be considered potential candidate genes. This study provides a theoretical basis for elucidating the molecular mechanisms associated with mammary gland development and milk production in Bactrian camels.

Genome-wide mapping of signatures of selection using a high-density array identified candidate genes for growth traits and local adaptation in chickens

BACKGROUND

Availability of single nucleotide polymorphism (SNP) genotyping arrays and progress in statistical analyses have allowed the identification of genomic regions and genes under selection in chicken. In this study, SNP data from the 600 K Affymetrix chicken array were used to detect signatures of selection in 23 local Italian chicken populations. The populations were categorized into four groups for comparative analysis based on live weight (heavy vs light) and geographical area (Northern vs Southern Italy). Putative signatures of selection were investigated by combining three extended haplotype homozygosity (EHH) statistical approaches to quantify excess of haplotype homozygosity within (iHS) and between (Rsb and XP-EHH) groups. Presence of runs of homozygosity (ROH) islands was also analysed for each group.

RESULTS

After editing, 541 animals and 313,508 SNPs were available for statistical analyses. In total, 15 candidate genomic regions that are potentially under selection were detected among the four groups: eight within a group by iHS and seven by combining the results of Rsb and XP-EHH, which revealed divergent selection between the groups. The largest overlap between genomic regions identified to be under selection by the three approaches was on chicken chromosome 8. Twenty-one genomic regions were identified with the ROH approach but none of these overlapped with regions identified with the three EHH-derived statistics. Some of the identified regions under selection contained candidate genes with biological functions related to environmental stress, immune responses, and disease resistance, which indicate local adaptation of these chicken populations.

CONCLUSIONS

Compared to commercial lines, local populations are predominantly reared as backyard chickens, and thus, may have developed stronger resistance to environmental challenges. Our results indicate that selection can play an important role in shaping signatures of selection in local chicken populations and can be a starting point to identify gene mutations that could have a useful role with respect to climate change.

Selection Signatures in Italian Livestock Guardian and Herding Shepherd Dogs

Livestock guardian (LGD) and herding shepherd (HSD) dogs have distinct morphological and behavioural characteristics, long selected by farmers and breeders, to accomplish different tasks. This study aimed to find the genomic regions that best differentiate and characterise Italian LGD and HSD. Genomic data of 158 dogs of four LGD and five HSD breeds, obtained with the 170K canine SNPchip, were collected. The two groups were compared using F_ST and XP-EHH analyses, identifying regions containing 29 genes. Moreover, 16 islands of runs of homozygosity were found in LGD, and 15 in HSD; 4 of them were partially shared. Among the genes found that better differentiated HSD and LGD, several were associated with dog domestication and behavioural aspects; particularly, MSRB3 and LLPH were linked to herding behaviour in previous studies. Others, DYSK, MAP2K5, and RYR, were related to body size and muscle development. Prick ears prevailed in sampled HSD, and drop ears in LGD; this explains the identification of WIF1 and MSRB3 genes. Unexpectedly, a number of genes were also associated with eye development and functionality. These results shed further light on the differences that human selection introduced in dogs aimed at different duties, even in a limited geographic area such as Italy.

Genomic Tools for the Characterization of Local Animal Genetic Resources: Application in Mascaruna Goat

Italy contains a large number of local goat populations, some of which do not have a recognized genetic structure. The "Mascaruna" is a goat population reared for milk production in Sicily. In this study, a total of 72 individuals were genotyped with the Illumina Goat_IGGC_65K_v2 BeadChip with the aim to characterize the genetic diversity, population structure and relatedness with another 31 Italian goat populations. The results displayed a moderate level of genetic variability for Mascaruna, in concordance with the estimated values for Italian goats. Runs of homozygosity islands are linked to genes involved in milk production, immune response and local adaptation. Population structure analyses separated Mascaruna from the other goat populations, indicating a clear genetic differentiation. Although they are not conclusive, our current results represent a starting point for the creation of monitoring and conservation plans. Additional analyses and a wider sampling would contribute to refine and validate these results. Finally, our study describing the diversity and structure of Mascaruna confirms the usefulness of applied genomic analyses as valid tools for the study of the local uncharacterized genetic resources.

Analysis of the Association of Two SNPs in the Promoter Regions of the PPP2R5C and SLC39A5 Genes with Litter Size in Yunshang Black Goats

Screening for candidate genes and genetic variants associated with litter size is important for goat breeding. The aim of this study was to analyze the relationship between single nucleotide polymorphisms (SNPs) in PPP2R5C and SLC39A5 and litter size in Yunshang black goats. KASP genotyping was used to detect the SNP genetic markers in the PPP2R5C and SLC39A5 in a population of 569 Yunshang black goats. The results show that there were two SNPs in the PPP2R5C and SLC39A5 promoter regions. Association analysis revealed that the polymorphisms PPP2R5C g.65977743C>T and SLC39A5 g.50676693T>C were significantly associated with the litter size of the third parity of Yunshang black goats (p < 0.05). To further explore the regulatory mechanism of the two genes, the expression of different genotypes of PPP2R5C and SLC39A5 was validated by RT-qPCR and Western blotting. The expression of PPP2R5C was significantly higher in individuals with the TT genotype than in those with the TC and CC genotypes (p < 0.05). The expression of SLC39A5 was also significantly higher in individuals with the TT genotype than in TC and CC genotypes (p < 0.05). Dual luciferase reporter analysis showed that the luciferase activity of PPP2R5C-C variant was significantly higher than that of PPP2R5C-T variant (p < 0.05). The luciferase activity of SLC39A5-T variant was significantly higher than that of SLC39A5-C variant (p < 0.05). Software was used to predict the binding of transcription factors to the polymorphic sites, and the results show that SOX18, ZNF418, and ZNF667 and NKX2-4 and TBX6 might bind to PPP2R5C g.65977743C>T and SLC39A5 g.50676693T>C, respectively. These results provide new insights into the identification of candidate genes for marker-assisted selection (MAS) in goats.

How Geography and Climate Shaped the Genomic Diversity of Italian Local Cattle and Sheep Breeds

Simple Summary

In this paper, we study the inter-relationships among geography, climate, and genetics in Italian local cattle and sheep breeds. In terms of genetic diversity, geography (latitude and longitude) appears to play a larger role in sheep (26.4%) than that in cattle (13.8%). Once geography is accounted for, 10.1% of cattle genomic diversity and 13.3% of that of sheep are attributable to climatic effects. Stronger geographic effects in sheep can be related to a combination of higher predomestication genetic variability together with biological and productive specializations. The climate alone seems to have had less impact on the current genetic diversity in both species even if climate and geography are greatly confounded. Results confirm that both species are the result of complex evolutionary histories triggered by interactions between human needs and environmental conditions.

Abstract

Understanding the relationships among geography, climate, and genetics is increasingly important for animal farming and breeding. In this study, we examine these inter-relationships in the context of local cattle and sheep breeds distributed along the Italian territory. To this aim, we used redundancy analysis on genomic data from previous projects combined with geographical coordinates and corresponding climatic data. The effect of geographic factors (latitude and longitude) was more important in sheep (26.4%) than that in cattle (13.8%). Once geography had been partialled out of analysis, 10.1% of cattle genomic diversity and 13.3% of that of sheep could be ascribed to climatic effects. Stronger geographic effects in sheep can be related to a combination of higher pre-domestication genetic variability together with biological and productive specificities. Climate alone seems to have had less impact on current genetic diversity in both species, even if climate and geography are greatly confounded. Results confirm that both species are the result of complex evolutionary histories triggered by interactions between human needs and environmental conditions.

Genetic Differentiation among Livestock Breeds—Values for Fst

Simple Summary

The degree of relationship among livestock breeds can be quantified by the F_st statistic, which measures the extent of genetic differentiation between them. An F_st value of 0.1 has often been taken as indicating that two breeds are indeed genetically distinct, but this concept has not been evaluated critically. Here, F_st values have been collated for the six major livestock species: cattle, sheep, goats, pigs, horses, and chickens. These values are remarkably variable both within and between species, demonstrating that F_st > 0.1 is not a reliable criterion for breed distinctiveness. However, the large body of F_st data accumulated in the last 20–30 years represents an untapped database that could contribute to the development of interdisciplinary research involving livestock breeds.

Abstract

(1) Background: The F_st statistic is widely used to characterize between-breed relationships. F_st = 0.1 has frequently been taken as indicating genetic distinctiveness between breeds. This study investigates whether this is justified. (2) Methods: A database was created of 35,080 breed pairs and their corresponding F_st values, deduced from microsatellite and SNP studies covering cattle, sheep, goats, pigs, horses, and chickens. Overall, 6560 (19%) of breed pairs were between breeds located in the same country, 7395 (21%) between breeds of different countries within the same region, 20,563 (59%) between breeds located far apart, and 562 (1%) between a breed and the supposed wild ancestor of the species. (3) Results: General values for between-breed F_st were as follows, cattle: microsatellite 0.06–0.12, SNP 0.08–0.15; sheep: microsatellite 0.06–0.10, SNP 0.06–0.17; horses: microsatellite 0.04–0.11, SNP 0.08–0.12; goats: microsatellite 0.04–0.14, SNP 0.08–0.16; pigs: microsatellite 0.06–0.27, SNP 0.15–0.22; chickens: microsatellite 0.05–0.28, SNP 0.08–0.26. (4) Conclusions: (1) Large amounts of F_st data are available for a substantial proportion of the world’s livestock breeds, (2) the value for between-breed F_st of 0.1 is not appropriate owing to its considerable variability, and (3) accumulated F_st data may have value for interdisciplinary research.

The SNP-Based Profiling of Montecristo Feral Goat Populations Reveals a History of Isolation, Bottlenecks, and the Effects of Management

The Montecristo wild goat is an endangered feral population that has been on the homonymous island in the Tuscan Archipelago since ancient times. The origins of Montecristo goats are still debated, with authors dating their introduction either back to Neolithic times or between the 6th and 13th century of the Common Era. To investigate the evolutionary history and relationships of this population we assembled a 50K SNP dataset including 55 Mediterranean breeds and two nuclei of Montecristo goats sampled on the island and from an ex situ conservation project. Diversity levels, gene flow, population structure, and genetic relationships were assessed through multiple approaches. The insular population scored the lowest values of both observed and expected heterozygosity, highlighting reduced genetic variation, while the ex situ nucleus highlighted a less severe reduction. Multivariate statistics, network, and population structure analyses clearly separated the insular nucleus from all other breeds, including the population of Montecristo goats from the mainland. Moreover, admixture and gene flow analyses pinpointed possible genetic inputs received by the two Montecristo goat nuclei from different sources, while Runs of Homozygosity (ROHs) indicated an ancient bottleneck/founder effect in the insular population and recent extensive inbreeding in the ex situ one. Overall, our results suggest that Montecristo goats experienced several demographic fluctuations combined with admixture events over time and highlighted a noticeable differentiation between the two nuclei.

Genetic Diversity, Population Structure and Phylogeny of Indigenous Goats of Mongolia Revealed by SNP Genotyping

Simple Summary

We performed SNP genotyping of indigenous goats of Mongolia to explore their demographic history in the global context and to estimate their genetic risks. Recently, these risks have become a subject of concern due to recent climatic disasters and uncontrolled massive breeding. Various clustering methods demonstrated close genetic relations among Mongolian, Russian, Chinese, and West Asian breeds. Mongolian goats themselves exhibited low to moderate estimates of genetic differentiation. We identified genetic features highlighting the distinct origin and breeding history of Mongolian goat breeds, as well as traces of artificial selection and geographic isolation. However, none of them met formal criteria to be considered as endangered.

Abstract

Mongolian goats are of great interest for studying ancient migration routes and domestication, and also represent a good model of adaptability to harsh environments. Recent climatic disasters and uncontrolled massive breeding endangered the valuable genetic resources of Mongolian goats and raised the question of their conservation status. Meanwhile, Mongolian goats have never been studied on genomic scale. We used Illumina Goat SNP50 to estimate genetic risks in five Mongolian goat breeds (Buural, Ulgii Red, Gobi GS, Erchim, Dorgon) and explored phylogenic relationships among these populations and in the context of other breeds. Various clustering methods showed that Mongolian goats grouped with other Asian breeds and were especially close to some neighboring Russian and Chinese breeds. The Buural breed showed the lowest estimates of inbreeding and exhibited the shortest genetic distances within the other Mongolian breeds, especially, to Ulgii Red and Gobi GS. These three breeds formed a single core group, being weakly differentiated from each other. Among them, Gobi GS displayed obvious signs of inbreeding probably resulted from artificial selection pressure. Dorgon and especially Erchim goats stand apart from the other Mongolian breeds according to various types of analyses, and bear unique features pointing to different breeding histories or distinct origins of these breeds. All populations showed strong decline in effective population size. However, none of them met formal criteria to be considered as endangered breeds. The SNP data obtained in this study improved the knowledge of Mongolian goat breeds and could be used in future management decisions in order to preserve their genetic diversity.

Runs of homozygosity in the Italian goat breeds: impact of management practices in low-input systems

Background

Climate and farming systems, several of which are considered as low-input agricultural systems, vary between goat populations from Northern and Southern Italy and have led to different management practices. These processes have impacted genome shaping in terms of inbreeding and regions under selection and resulted in differences between the northern and southern populations. Both inbreeding and signatures of selection can be pinpointed by the analysis of runs of homozygosity (ROH), which provides useful information to assist the management of this species in different rural areas.

Results

We analyzed the ROH distribution and inbreeding (F_ROH) in 902 goats from the Italian Goat Consortium2 dataset. We evaluated the differences in individual ROH number and length between goat breeds from Northern (NRD) and Central-southern (CSD) Italy. Then, we identified the signatures of selection that differentiate these two groups using three methods: ROH, ΔROH, and averaged F_ST. ROH analyses showed that some Italian goat breeds have a lower inbreeding coefficient, which is attributable to their management and history. ROH are longer in breeds that are undergoing non-optimal management or with small population size. In several small breeds, the ROH length classes are balanced, reflecting more accurate mating planning. The differences in climate and management between the NRD and CSD groups have resulted in different ROH lengths and numbers: the NRD populations bred in isolated valleys present more and shorter ROH segments, while the CSD populations have fewer and longer ROH, which is likely due to the fact that they have undergone more admixture events during the horizontal transhumance practice followed by a more recent standardization. We identified four genes within signatures of selection on chromosome 11 related to fertility in the NRD group, and 23 genes on chromosomes 5 and 6 related to growth in the CSD group. Finally, we identified 17 genes on chromosome 12 related to environmental adaptation and body size with high homozygosity in both groups.

Conclusions

These results show how different management practices have impacted the level of genomic inbreeding in two Italian goat groups and could be useful to assist management in a low-input system while safeguarding the diversity of small populations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00685-4.

The Quest for Genes Involved in Adaptation to Climate Change in Ruminant Livestock

Livestock radiated out from domestication centres to most regions of the world, gradually adapting to diverse environments, from very hot to sub-zero temperatures and from wet and humid conditions to deserts. The climate is changing; generally global temperature is increasing, although there are also more extreme cold periods, storms, and higher solar radiation. These changes impact livestock welfare and productivity. This review describes advances in the methodology for studying livestock genomes and the impact of the environment on animal production, giving examples of discoveries made. Sequencing livestock genomes has facilitated genome-wide association studies to localize genes controlling many traits, and population genetics has identified genomic regions under selection or introgressed from one breed into another to improve production or facilitate adaptation. Landscape genomics, which combines global positioning and genomics, has identified genomic features that enable animals to adapt to local environments. Combining the advances in genomics and methods for predicting changes in climate is generating an explosion of data which calls for innovations in the way big data sets are treated. Artificial intelligence and machine learning are now being used to study the interactions between the genome and the environment to identify historic effects on the genome and to model future scenarios.