Background: Sheep were among the first animals to be domesticated. They are raised all over the world and produce a major scale of animal-based protein for human consumption and play an important role in agricultural economy. Iran is one of the important locations for sheep genetic resources in the world. Here, we compared the Illumina Ovine SNP50 BeadChip data of three Iranian local breeds (Moghani, Afshari and Gezel), as a population that does not undergone artificial breeding programs as yet, and five other sheep breeds namely East Friesian white, East Friesian brown, Lacaune, DorsetHorn and Texel to detect genetic mechanisms underlying economical traits and daptation to harsh environments in sheep. Results: To identify genomic regions that have been targeted by positive selection, we used fixation index (Fst) and nucleotide diversity (Pi) statistics. Further analysis indicated candidate genes involved in different important traits such as; wool production included crimp of wool (PTPN3, NBEA and KRTAP20–2 genes), fiber diameter (PIK3R4 gene), hair follicle development (LHX2 gene), the growth and development of fiber (COL17A1 gene)), adaptation to hot arid environments (CORIN gene), adaptive in deficit water status (CPQ gene), heat stress (PLCB4, FAM107B, NBEA, PIK3C2B and USP43 genes) in sheep. Conclusions: We detected several candidate genes related to wool production traits and adaptation to hot arid environments in sheep that can be applicable for inbreeding goals. Our findings not only include the results of previous researches, but also identify a number of novel candidate genes related to studied traits. However, more works will be essential to acknowledge phenotype- genotype relationships of the identified genes in our study.

Background: Goat, one of the first domesticated livestock, is a worldwide important species both culturally and economically. The current goat reference genome, known as ARS1, is reported as the first nonhuman genome assembly using 69× PacBio sequencing. However, ARS1 suffers from incomplete X chromosome and highly fragmented Y chromosome scaffolds. Results: Here, we present a very high-quality de novo genome assembly, Saanen_v1, from a male Saanen dairy goat, with the first goat Y chromosome scaffold based on 117× PacBio long-read sequencing and 118× Hi-C data. Saanen_v1 displays a high level of completeness thanks to the presence of centromeric and telomeric repeats at the proximal and distal ends of two-thirds of the autosomes, and a much reduced number of gaps (169 vs. 773). The completeness and accuracy of the Saanen_v1 genome assembly are also evidenced by more assembled sequences on the chromosomes (2.63 Gb for Saanen_v1 vs. 2.58 Gb for ARS1), a slightly increased mapping ratio for transcriptomic data, and more genes anchored to chromosomes. The eight putative large assembly errors (1 to ~ 7 Mb each) found in ARS1 were amended, and for the first time, the substitution rate of this ruminant Y chromosome was estimated. Furthermore, sequence improvement in Saanen_v1, compared with ARS1, enables us to assign the likely correct positions for 4.4% of the single nucleotide polymorphism (SNP) probes in the widely used GoatSNP50 chip. Conclusions: The updated goat genome assembly including both sex chromosomes (X and Y) and the autosomes with high-resolution quality will serve as a valuable resource for goat genetic research and applications.

Background: Understanding how evolutionary forces relating to climate have shaped the patterns of genetic variation within and between species is a fundamental pursuit in biology. Iranian indigenous chickens have evolved genetic adaptations to their local environmental conditions, such as hot and arid regions. In the present study, we provide a population genome landscape of genetic variations in 72 chickens representing nine Iranian indigenous ecotypes (Creeper, Isfahan, Lari, Marand, Mashhad, Naked neck, Sari, Shiraz and Yazd) and two commercial lines (White Leghorn and Arian). We further performed comparative population genomics to evaluate the genetic basis underlying variation in the adaptation to hot climate and immune response in indigenous chicken ecotypes. To detect genomic signatures of adaptation, we applied nucleotide diversity (θπ) and F_ST statistical measurements, and further analyzed the results to find genomic regions under selection for hot adaptation and immune response-related traits. Results: We assessed the relationship between the genetic diversity of indigenous chicken ecotypes and their genetic distances to two different commercial lines. The results of genetic structure analysis revealed clustering of indigenous chickens in agreement with their geographic origin. Among all studied chicken groups, the highest level of linkage disequilibrium (LD) (~ 0.70) was observed in White Leghorn group at marker pairs distance of 1 Kb. The results from admixture analysis demonstrated evidence of shared ancestry between Arian individuals and indigenous chickens, especially those from the north of the country. Our search for potential genomic regions under selection in indigenous chicken ecotypes revealed several immune response and heat shock protein-related genes, such as HSP70, HSPA9, HSPH1, HSP90AB1 and PLCB4 that have been previously unknown to be involved in environmental-adaptive traits. In addition, we found some other candidate loci on different chromosomes probably related with hot adaptation and immune response-related traits. Conclusions: The work provides crucial insights into the structural variation in the genome of Iranian indigenous chicken ecotypes, which up to now has not been genetically investigated. Several genes were identified as candidates for drought, heat tolerance, immune response and other phenotypic traits. These candidate genes may be helpful targets for understanding of the molecular basis of adaptation to hot environmental climate and as such they should be used in chicken breeding programs to select more efficient breeds for desert climate.

Background: Artificial and natural selection for important economic traits and genetic adaptation of the populations to specific environments have led to the changes on the sheep genome. Recent advances in genome sequencing methods have made it possible to use comparative genomics tools to identify genes under selection for traits of economic interest in domestic animals.Objectives: In this study, we compared the genomes of Assaf and Awassi sheep breeds with those of the Cambridge, Romanov and British du cher sheep breeds to explore positive selection signatures for milk traits using nucleotide diversity (Pi) and FST statistical methods.Methods: Genome sequences from fourteen sheep with a mean sequence depth of 9.32X per sample were analysed, and a total of 23 million single nucleotide polymorphisms (SNPs) were called and applied for this study. Genomic clustering of breeds was identified using ADMIXTURE software. The FST and Pi values for each SNP were computed between population A (Assaf and Awassi) and population B (Cambridge, British du cher, and Romanov).Results: The results of the PCA grouped two classes for these five dairy sheep breeds. The selection signatures analysis displayed 735 and 515 genes from FST and nucleotide diversity (Pi) statistical methods, respectively. Among all these, 12 genes were shared between the two approaches. The most conspicuous genes were related to milk traits, including ST3GAL1 (the synthesis of oligosacáridos), CSN1S1 (milk protein), CSN2 (milk protein), OSBPL8 (fatty acid traits), SLC35A3 (milk fat and protein percentage), VPS13B (total milk production, fat yield, and protein yield), DPY19L1 (peak yield), CCDC152 (lactation persistency and somatic cell count), NT5DC1 (lactation persistency), P4HTM (test day protein), CYTH4 (FAT Production) and METRNL (somatic cell), U1 (milk traits), U6 (milk traits) and 5S_RRNA (milk traits).Conclusions: The findings provide new insight into the genetic basis of sheep milk properties and can play a role in designing sheep breeding programs incorporating genomic information.

Background: Since domestication, both evolutionary forces and human selection have played crucial roles in producing adaptive and economic traits, resulting in animal breeds that have been selected for specific climates and different breeding goals. Pakistani goat breeds have acquired genomic adaptations to their native climate conditions, such as tropical and hot climates. In this study, using next-generation sequencing data, we aimed to assess the signatures of positive selection in three native Pakistani goats, known as milk production breeds, that have been well adapted to their local climate. Results: To explore the genomic relationship between studied goat populations and their population structure, whole genome sequence data from native goat populations in Pakistan (n = 26) was merged with available worldwide goat genomic data (n = 184), resulting in a total dataset of 210 individuals. The results showed a high genetic correlation between Pakistani goats and samples from North-East Asia. Across all populations analyzed, a higher linkage disequilibrium (LD) level (– 0.59) was found in the Pakistani goat group at a genomic distance of 1 Kb. Our findings from admixture analysis (K = 5 and K = 6) showed no evidence of shared genomic ancestry between Pakistani goats and other goat populations from Asia. The results from genomic selection analysis revealed several candidate genes related to adaptation to tropical/hot climates (such as; KITLG, HSPB9, HSP70, HSPA12B, and HSPA12B) and milk production related-traits (such as IGFBP3, LPL, LEPR, TSHR, and ACACA) in Pakistani native goat breeds. Conclusions: The results from this study shed light on the structural variation in the DNA of the three native Pakistani goat breeds. Several candidate genes were discovered for adaptation to tropical/hot climates, immune responses, and milk production traits. The identified genes could be exploited in goat breeding programs to select efficient breeds for tropical/hot climate regions.