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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: By generating whole-genome data, 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., (© 2022. The Author(s).)

Background: Various regions of the chicken genome have been under natural and artificial selection for thousands of years. The substantial diversity that exits among chickens from different geographic regions provides an excellent opportunity to investigate the genomic regions under selection which, in turn, will increase our knowledge about the mechanisms that underlie chicken diversity and adaptation. Several statistics have been developed to detect genomic regions that are under selection. In this study, we applied approaches based on differences in allele or haplotype frequencies (F ST and hapFLK, respectively) between populations, differences in long stretches of consecutive homozygous sequences (ROH), and differences in allele frequencies within populations (composite likelihood ratio (CLR)) to identify inter- and intra-populations traces of selection in two Iranian indigenous chicken ecotypes, the Lari fighting chicken and the Khazak or creeper (short-leg) chicken., Results: Using whole-genome resequencing data of 32 individuals from the two chicken ecotypes, approximately 11.9 million single nucleotide polymorphisms (SNPs) were detected and used in genomic analyses after quality processing. Examination of the distribution of ROH in the two populations indicated short to long ROH, ranging from 0.3 to 5.4 Mb. We found 90 genes that were detected by at least two of the four applied methods. Gene annotation of the detected putative regions under selection revealed candidate genes associated with growth (DCN, MEOX2 and CACNB1), reproduction (ESR1 and CALCR), disease resistance (S1PR1, ALPK1 and MHC-B), behavior pattern (AGMO, GNAO1 and PSEN1), and morphological traits (IHH and NHEJ1)., Conclusions: Our findings show that these two phenotypically different indigenous chicken populations have been under selection for reproduction, immune, behavioral, and morphology traits. The results illustrate that selection can play an important role in shaping signatures of differentiation across the genomic landscape of two chicken populations., (© 2021. The Author(s).)

Background: Species domestication is generally characterized by the exploitation of high-impact mutations through processes that involve complex shifting demographics of domesticated species. These include not only inbreeding and artificial selection that may lead to the emergence of evolutionary bottlenecks, but also post-divergence gene flow and introgression. Although domestication potentially affects the occurrence of both desired and undesired mutations, the way wild relatives of domesticated species evolve and how expensive the genetic cost underlying domestication is remain poorly understood. Here, we investigated the demographic history and genetic load of chicken domestication., Results: We analyzed a dataset comprising over 800 whole genomes from both indigenous chickens and wild jungle fowls. We show that despite having a higher genetic diversity than their wild counterparts (average π, 0.00326 vs. 0.00316), the red jungle fowls, the present-day domestic chickens experienced a dramatic population size decline during their early domestication. Our analyses suggest that the concomitant bottleneck induced 2.95% more deleterious mutations across chicken genomes compared with red jungle fowls, supporting the "cost of domestication" hypothesis. Particularly, we find that 62.4% of deleterious SNPs in domestic chickens are maintained in heterozygous states and masked as recessive alleles, challenging the power of modern breeding programs to effectively eliminate these genetic loads. Finally, we suggest that positive selection decreases the incidence but increases the frequency of deleterious SNPs in domestic chicken genomes., Conclusion: This study reveals a new landscape of demographic history and genomic changes associated with chicken domestication and provides insight into the evolutionary genomic profiles of domesticated animals managed under modern human selection.

Despite the substantial role that chickens have played in human societies across the world, both the geographic and temporal origins of their domestication remain controversial. To address this issue, we analyzed 863 genomes from a worldwide sampling of chickens and representatives of all four species of wild jungle fowl and each of the five subspecies of red jungle fowl (RJF). Our study suggests that domestic chickens were initially derived from the RJF subspecies Gallus gallus spadiceus whose present-day distribution is predominantly in southwestern China, northern Thailand and Myanmar. Following their domestication, chickens were translocated across Southeast and South Asia where they interbred locally with both RJF subspecies and other jungle fowl species. In addition, our results show that the White Leghorn chicken breed possesses a mosaic of divergent ancestries inherited from other subspecies of RJF. Despite the strong episodic gene flow from geographically divergent lineages of jungle fowls, our analyses show that domestic chickens undergo genetic adaptations that underlie their unique behavioral, morphological and reproductive traits. Our study provides novel insights into the evolutionary history of domestic chickens and a valuable resource to facilitate ongoing genetic and functional investigations of the world's most numerous domestic animal.

Native chickens are endangered genetic resources that are kept by farmers for different purposes. Native chickens distributed in a wide range of altitudes, have developed adaptive mechanisms to deal with hypoxia. For the first time, we report variants associated with high-altitude adaptation in Iranian native chickens by whole genome sequencing of lowland and highland chickens. We found that these adaptive variants are involved in DNA repair, organs development, immune response and histone binding. Amazingly, signature selection analysis demonstrated that differential variants are adaptive in response to hypoxia and are not due to other evolutionary pressures. Cellular component analysis of variants showed that mitochondrion is the most important organelle for hypoxia adaptation. A total of 50 variants was detected in mtDNA for highland and lowland chickens. High-altitude associated with variant discovery highlighted the importance of COX3, a gene involved in cell respiration, in hypoxia adaptation. The results of study suggest that MIR6644-2 is involved in hypoxia and high-altitude adaptations by regulation of embryo development. Finally, 3877 novel SNVs including the mtDNA ones, were submitted to EBI (PRJEB24944). Whole-genome sequencing and variant discovery of native chickens provided novel insights about adaptation mechanisms and highlights the importance of valuable genomic variants in chickens.

Copy number variations (CNVs) are important large-scale variants. They are widespread in the genome and may contribute to phenotypic variation. Detection and characterization of CNVs can provide new insights into the genetic basis of important traits. Here, we perform whole-genome short read sequence analysis to identify CNVs in two indigenous and commercial chicken breeds to evaluate the impact of the identified CNVs on breed-specific traits. After filtration, a total of 12 955 CNVs spanning (on average) about 9.42% of the chicken genome were found that made up 5467 CNV regions (CNVRs). Chicken quantitative trait loci (QTL) datasets and Ensembl gene annotations were used as resources for the estimation of potential phenotypic effects of our CNVRs on breed-specific traits. In total, 34% of our detected CNVRs were also detected in earlier CNV studies. These CNVRs partly overlap several previously reported QTL and gene ontology terms associated with some important traits, including shank length QTL in Creeper-specific CNVRs and body weight and egg production characteristics, as well as muscle and body organ growth, in the Arian commercial breed. Our findings provide new insights into the genomic structure of the chicken genome for an improved understanding of the potential roles of CNVRs in differentiating between breeds or lines.

Background: Genomic selection has been successfully implemented in plant and animal breeding programs to shorten generation intervals and accelerate genetic progress per unit of time. In practice, genomic selection can be used to improve several correlated traits simultaneously via multiple-trait prediction, which exploits correlations between traits. However, few studies have explored multiple-trait genomic selection. Our aim was to infer genetic correlations between three traits measured in broiler chickens by exploring kinship matrices based on a linear combination of measures of pedigree and marker-based relatedness. A predictive assessment was used to gauge genetic correlations., Methods: A multivariate genomic best linear unbiased prediction model was designed to combine information from pedigree and genome-wide markers in order to assess genetic correlations between three complex traits in chickens, i.e. body weight at 35 days of age (BW), ultrasound area of breast meat (BM) and hen-house egg production (HHP). A dataset with 1351 birds that were genotyped with the 600 K Affymetrix platform was used. A kinship kernel (K) was constructed as K = λ G + (1 - λ)A, where A is the numerator relationship matrix, measuring pedigree-based relatedness, and G is a genomic relationship matrix. The weight (λ) assigned to each source of information varied over the grid λ = (0, 0.2, 0.4, 0.6, 0.8, 1). Maximum likelihood estimates of heritability and genetic correlations were obtained at each λ, and the "optimum" λ was determined using cross-validation., Results: Estimates of genetic correlations were affected by the weight placed on the source of information used to build K. For example, the genetic correlation between BW-HHP and BM-HHP changed markedly when λ varied from 0 (only A used for measuring relatedness) to 1 (only genomic information used). As λ increased, predictive correlations (correlation between observed phenotypes and predicted breeding values) increased and mean-squared predictive error decreased. However, the improvement in predictive ability was not monotonic, with an optimum found at some 0 < λ < 1, i.e., when both sources of information were used together., Conclusions: Our findings indicate that multiple-trait prediction may benefit from combining pedigree and marker information. Also, it appeared that expected correlated responses to selection computed from standard theory may differ from realized responses. The predictive assessment provided a metric for performance evaluation as well as a means for expressing uncertainty of outcomes of multiple-trait selection.

B Whole-genome sequencing of the samples using the next-generation sequencing technique was conducted within the framework of the Global Chicken Genome Project ( b http://chicken.ynau.edu.cn/index/about/index.html B ) led by Kunming Institute of Zoology, Chinese Academy of Sciences (KIZ-CAS) and described by Wang et al. b [[2]]." Furthermore, the whole genome sequencing data, BAM files, and genotypes (VCF) have been submitted in the ChickenSD database (http://bigd.big.ac.cn/chickensd/)." The original declaration stated: "The whole genome sequencing data for all chicken individuals generated in this study have been deposited at NCBI SRA Database with accession code: PRJNA807738 or accessible through https://www.ncbi.nlm.nih.gov/bioproject/ PRJNA807738. [Extracted from the article]

10.1186/s12711-021-00664-9 2 Wang MS, Thakur M, Peng MS, Jiang Y, Frantz LAF, Li M. 863 genomes reveal the origin and domestication of chicken. Methods Sampling and genome sequencing Page '3', first paragraph, line '10' where we described the preparation of DNA samples, the following sentence is missing: "Whole-genome sequencing of the samples using the next-generation sequencing technique was conducted within the framework of the Global Chicken Genome Project (http://chicken.ynau.edu.cn/index/about/index.html) led by the Kunming Institute of Zoology, Chinese Academy of Sciences (KIZ-CAS) and described by Wang et al. [[2]-[5]]". [Extracted from the article]