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Novel genetic variants data for adaptation to hypoxia in native chickens

Abstract

Objective

The genomic response and the role of genetic variants in hypoxia condition are always interesting issues about adaption pathways at genomic level. Herein, we carried out a comparative genomic study between highland and lowland native chickens, in order to identify the adaptive variants in hypoxia condition. We generated more than 20 million genetic variants in highland and lowland chickens. Finally, 3877 SNVs including the mtDNA ones, were discovered as novel adaptive genetic variants. The generated data set can provide new insight about mechanism of adaptation to hypoxia at genomic level.

Data description

To investigate the role of genetic variants in adaptation to hypoxia, 10 whole-genome sequencing data sets associated to highland and lowland native chickens were provided. DNA was extracted by salting-out protocol. Paired-end 125 bp short reads were sequenced by Illumina Hiseq 2000. Variants calling of highland and lowland native chickens were performed by fix ploidy algorithm in CLC Genomic Workbench. Total genetic variants of highland chickens were compared to lowland chickens in order to identify the differential genetic variants (DGVs) between highland and lowland chickens. In this way, 3877 novel SNVs (VCF format) including the mtDNA ones, were deposited at EBI database (https://identifiers.org/ena.embl:ERZ491574) for the first time.

Peer Review reports

Objective

Chicken (Gallus gallus demesticus) is one of the widespread domestic bird in the world. Origin of chicken’s domestication has always been a challenge. However, the outcomes of investigations showed chickens have been domesticated more than 10,000 years ago from Red Jungle Flow subspecies Gallus gallus spadiceus that is distributed in northern Thailand, China, and Myanmar [1]. Food production, religions ideas and cock fighting are the most important reasons for the beginning of chicken domestications [2]. It is believed, genome is dynamic and it responses to environmental conditions. Alterations of genetic variants as genome response play a critical role in domestication and adaptation of chickens [3]. Altitude is distance above sea level and areas that are above 2,400 m of sea level are usually considered as high-altitude condition. Hypoxia is the most important risk factor in high-altitude areas that organisms must adapt to this harsh environment in order to increase the probability of viability [4]. Hypoxia means low oxygen and adaptation to hypoxia is a complex process that includes some biological pathways and gene networks [5]. Therefore, understanding the genetics factors associated with adaptation to high-altitude conditions in domestic animals provide new science for finding the adaptation process [6].

There are studies carried out in order to identify the genetic factors related to high-altitude conditions. Results of these studies show that hypoxia is involved in cerebral edema, tumorigenesis, myocardial ischemia and some genes including Endothelin 1 (EDN1), Erythropoietin (EPO) and Aldosterone synthase (CYP11B2) are reported as the key genes of hypoxia adaptation [7,8,9]. Investigations indicated that highland chickens are adapted based on factors including the small body size, the ability to outstand foraging, high hatchability, large organs (liver, heart and lungs), and higher hemoglobin concentration [8].

Due to different climates and altitudes, there is considerable genetic diversity among indigenous chickens in Iran [10]. Historical evidence shows that Iran is one of the oldest poultry breeding centers in the world. Chicken have been kept since many years ago by farmers and consequently they have adapted to local environment conditions by genetic changes [11]. Previously, we performed a comparative genomic study by whole genome sequencing data between highland and lowland native chickens in order to identify the adaptive genetic variants in hypoxia condition [5].

Our founding indicated that adaptive variants are involved in DNA repair, organs development, immune response and histone binding. Cellular component analysis of variants showed that mitochondrion is the most important organelle for hypoxia adaptation. High-altitude associated with variant discovery highlighted the importance of COX3, a gene involved in cell respiration, in hypoxia adaptation [5]. Finally, 3877 novel SNVs including the mtDNA ones, were submitted to EBI (PRJEB24944). The submitted genetic variants of native chickens provided new insights about adaptation mechanisms and highlights the importance of valuable genomic variants in chickens.

Data description

The current data set and additional methods details were published previously in Scientific Report journal [5]. In order to identify adaptive genetic variants five blood samples were collected from Mazandraran province (Altitude = 54 m) as lowland chickens and five blood samples were obtained from Isfahan province (Altitude = 2087 m) as highland chickens. DNA was extracted by salting-out protocol. Nanodrop (ratio 260/280 (nm)) and agarose gel (1%) electrophoresis was applied to quantity and quality controls of the provided DNA [12]. Paired-end 125 bp short reads were sequenced by Illumina Hiseq 2000 [1]. Around 0.94 Gbp and 22.1 Gb data were provided [5]. Reference genome and annotations were downloaded from the Ensembl database (fp://fp.ensembl.org/pub/relase-84/fasta/gallus_gallus). CLC Genomics Workbench (version:8.5.1) [13] was applied to adaptors trimming, quality control and mapping short reads against reference genome. Variants calling of highland and lowland native chickens were carried out by fix ploidy algorithm in CLC Genomic Workbench (version:8.5) under default parameters and more than 20 million genetic variants were generated. Total genetic variants of highland chickens were compared to lowland chickens in order to identify the differential genetic variants (DGVs). In this way, a total 114,634 DGVs was reported between highland and lowland chickens. Known variants annotation was utilized to identify the novel genetic variants that have not been reported previously in database of single nucleotide polymorphisms dbSNPs (www.ncbi.nlm.nih.gov/snp). Finally, 3877 novel SNVs (VCF format) were submitted to EBI database (https://www.ebi.ac.uk/). The submitted data is available in the following link (https://identifiers.org/ena.embl:ERZ491574) [14]. Table 1 shows the details of submitted data and direct download link. Variants discovery projects produce numerous variations. Thereby, validating the variants is highly required. Here, validations were carried out for two groups of detected variants. First, novel differential SNVs between highland and lowland chickens, and second, mtDNA variations in highland chickens. The whole genome sequencing and genetic variants calling of other five whole genomes of highland samples (Isfahan) was carried out, separately. Finally, in order to validate the reported novel genetic variants, each novel SNV’s regions and chromosomes were evaluated in the new five samples by R program (https://www.r-project.org) [5].”

Table 1 The novel genetic variants data sets for adaptation to hypoxia in native chickens at ENA (European Nucleotide Archive) database

Limitations

In the current investigation, 10 native chickens were studied to describe the adaptive variants in hypoxia condition. Therefore, the generated genetic variants could not present a comprehensive information of adaptation process in native chickens.

Data Availability

The genetic variant data described herein have been deposited in EBI database (European Nucleotide Variation) as novel genetic variants in (VCF) format (https://identifiers.org/ena.embl:ERZ491574) under the accession number of PRJNA532674.

Abbreviations

Gb:

Giga byte

Gbp:

Giga base pair

DNA:

Deoxyribonucleic acid

SNP:

single nucleotide polymorphism

SNV:

single nucleotide variation

DGVs:

differential genetic variants

VCF:

variant call format

References

  1. Wang MS, Thakur M, Peng MS, Jiang YU, Frantz LA, Li M, Zhang JJ, Wang S, Peters J, Otecko NO, Suwannapoom C. 863 genomes reveal the origin and domestication of chicken. Cell Res. 2020;30(8):693–701.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Esfandiari P, Dadpasand M, Kharrati-Koopaee H, Atashi H, Gharghi A, Niazi A. Bioinformatics, phylogenetic and variant association analysis of Ovocalyxin-32 gene reveals its contribution to egg production traits in native chickens. Anim Gene. 2020;1(17):200108.

    Article  Google Scholar 

  3. Snyder-Mackler N, Lea AJ. Functional genomic insights into the environmental determinants of mammalian fitness. Curr Opin Genet Dev 2018;1(53)105–12.

  4. Kharrati-Koopaee H, Ebrahimie E, Dadpasand M, Niazi A, Tian R, Esmailizadeh A. Gene network analysis to determine the effect of hypoxia-associated genes on brain damages and tumorigenesis using an avian model. J Genet Eng Biotechnol. 2021;19(1):1–24.

    Article  Google Scholar 

  5. Kharrati-Koopaee H, Ebrahimie E, Dadpasand M, Niazi A, Esmailizadeh A. Genomic analysis reveals variant association with high altitude adaptation in native chickens. Scientific Rep. 2019;25;9(1):1–22.

  6. Friedrich J, Wiener P. Selection signatures for high-altitude adaptation in ruminants. Anim Genet. 2020;51(2):157–65.

    Article  CAS  PubMed  Google Scholar 

  7. Haron A, Ruzal M, Shinder D, Druyan S. Hypoxia during incubation and its effects on broiler’s embryonic development. Poult Sci. 2021;100(3):100951.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Zhang Q, Gou W, Wang X, Zhang Y, Ma J, Zhang H, Zhang Y, Zhang H. Genome resequencing identifies unique adaptations of tibetan chickens to hypoxia and high-dose ultraviolet radiation in high-altitude environments. Genome Biol Evol. 2016;8(3):765–76.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Zhao X, Wu N, Zhu Q, Gaur U, Gu T, Li D. High-altitude adaptation of tibetan chicken from MT-COI and ATP-6 perspective. Mitochondrial DNA Part A. 2016;27(5):3280–8.

    Article  CAS  Google Scholar 

  10. Kharrati-kooppae H, Esmaeelizadeh A, Pournanaei H. Evaluation of genetic potential of iranian native chicken ecotypes; insights for conservation. Agri Biotechnol J. 2022;14(2):119–32.

    Google Scholar 

  11. Mohammadabadi MR, Nikbakhti M, Mirzaee HR, et al. Genetic variability in three native iranian chicken populations of the Khorasan province based on microsatellite markers. Russ J Genet. 2010;46:505–9.

    Article  CAS  Google Scholar 

  12. Jamalpour M, Dadpasand M, Atashi H, Niazi A, Kharrati H, Hashemi SM. Bioinformatics and phylogenetic analysis for 5′ UTR region of neuropeptide Y gene and its association with body weight and egg production traits in Fars native chickens. Iran J Anim Sci. 2018;49(3):453–8.

    Google Scholar 

  13. Genomics CLC. Workbench 8.5.1, https://www.qiagenbioinformatics.com/.

  14. https://identifiers.org/ena.embl:ERZ491574.

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Acknowledgements

The authors are thankful of the chicken holders in Iran for their contribution to collecting chicken samples.

Funding

Tis project was supported financially by Kunming Institute of Zoology in China. The authors are thankful to Chinese colleagues for providing the raw NGS data.

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Authors

Contributions

Sampling and data analysis were done by HKK and AM. MFZ, MF and FT prepared the manuscript. All authors have read and approved the final version of the manuscript.

Corresponding author

Correspondence to Hamed Kharrati-Koopaee.

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The procedure of blood sampling was approved by the Department of Animal Science at Shiraz University (Permit number: 94–193).

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Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Moradi, A., Kharrati-Koopaee, H., Fardi, M. et al. Novel genetic variants data for adaptation to hypoxia in native chickens. BMC Res Notes 16, 225 (2023). https://doi.org/10.1186/s13104-023-06493-x

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