Genomic Analyses Reveal Potential Independent Adaptation to High Altitude in Tibetan Chickens

Wang, Mingshan; Li, Yan; Peng, Min‐Sheng; Zhong, Li; Wang, Zongji; Li, Qiye; Tu, Xiaolong; Dong, Yang; Zhu, Chun-Ling; Wang, Lu; Yang, Minmin; Wu, Shi-Fang; Miao, Yongwang; Liu, Jianping; Irwin, David M.; Wang, Wen; Wu, Dong‐Dong; Zhang, Yaping

doi:10.1093/molbev/msv071

Cited by 179 publications

(209 citation statements)

References 45 publications

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“…2B). Different from a previous report on the two independent origins of Tibetan chickens [8], we revealed the presence of at least three distinct clusters among the six geographically representative populations of Tibetan fowls: the fowls inhabiting Tibet and Qinghai (in cluster 1) were genetically closer to RJF, while the Tibetan chickens inhabiting Yunnan and Sichuan (clusters 2 and 3) were closer to the domestic populations (Fig. 1).…”

Section: Resultscontrasting

confidence: 99%

Genomic data for 78 chickens from 14 populations

Che

Chen

et al. 2017

GigaScience

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Background: Since the domestication of the red jungle fowls (Gallus gallus; dating back to ∼10 000 B.P.) in Asia, domestic chickens (Gallus gallus domesticus) have been subjected to the combined effects of natural selection and human-driven artificial selection; this has resulted in marked phenotypic diversity in a number of traits, including behavior, body composition, egg production, and skin color. Population genomic variations through diversifying selection have not been fully investigated. Findings: The whole genomes of 78 domestic chickens were sequenced to an average of 18-fold coverage for each bird. By combining this data with publicly available genomes of five wild red jungle fowls and eight Xishuangbanna game fowls, we conducted a comprehensive comparative genomics analysis of 91 chickens from 17 populations. After aligning ∼21.30 gigabases (Gb) of high-quality data from each individual to the reference chicken genome, we identified ∼6.44 million (M) single nucleotide polymorphisms (SNPs) for each population. These SNPs included 1.10 M novel SNPs in 17 populations that were absent in the current chicken dbSNP (Build 145) entries. Conclusions: The current data is important for population genetics and further studies in chickens and will serve as a valuable resource for investigating diversifying selection and candidate genes for selective breeding in chickens.

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Section: Resultscontrasting

confidence: 99%

Genomic data for 78 chickens from 14 populations

Che

Chen

et al. 2017

GigaScience

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“…3b, Supplementary Dataset S1 & S2). Several genes within these regions were previously implicated in the adaptation of Tibetan dwellers, including HMOX2 and HBB in Tibetans48, AK9 in Tibetan chickens49, GLDC and RHOG in Tibetan pigs10, ATP12A , PIK3C2A, ADORA2A , and ENG in Tibetan antelope50, GNB1 in Tibetan dogs51. In addition, a total of 53 regions were within the top 1% of the distribution (di > 12.79), which included highland adaptation related genes such as ANGPTL4 in Tibetans48 , ENO3 and KIF1C in Tibetan dogs51, and PKLR in Tibetan antelope50.…”

Section: Resultsmentioning

confidence: 99%

Whole-genome sequencing of eight goat populations for the detection of selection signatures underlying production and adaptive traits

Wang

Liu

Zhou

et al. 2016

Sci Rep

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The goat (Capra hircus) is one of the first farm animals that have undergone domestication and extensive natural and artificial selection by adapting to various environments, which in turn has resulted in its high level of phenotypic diversity. Here, we generated medium-coverage (9–13×) sequences from eight domesticated goat breeds, representing morphologically or geographically specific populations, to identify genomic regions representing selection signatures. We discovered ~10 million single nucleotide polymorphisms (SNPs) for each breed. By combining two approaches, ZHp and di values, we identified 22 genomic regions that may have contributed to the phenotypes in coat color patterns, body size, cashmere traits, as well as high altitude adaptation in goat populations. Candidate genes underlying strong selection signatures including coloration (ASIP, KITLG, HTT, GNA11, and OSTM1), body size (TBX15, DGCR8, CDC25A, and RDH16), cashmere traits (LHX2, FGF9, and WNT2), and hypoxia adaptation (CDK2, SOCS2, NOXA1, and ENPEP) were identified. We also identified candidate functional SNPs within selected genes that may be important for each trait. Our results demonstrated the potential of using sequence data in identifying genomic regions that are responsible for agriculturally significant phenotypes in goats, which in turn can be used in the selection of goat breeds for environmental adaptation and domestication.

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“…Details about the sequenced samples and method of sequencing are in [11, 12]. As mentioned in these two papers, individual DNA libraries with an insert size of 500 bp were constructed and sequenced by using the Illumina HiSeq 2000 platform.…”

Section: Methodsmentioning

confidence: 99%

Whole-genome resequencing of Xishuangbanna fighting chicken to identify signatures of selection

Guo

Fang

et al. 2016

Genet Sel Evol

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BackgroundSelective breeding for genetic improvement is expected to leave distinctive selection signatures within genomes. The identification of selection signatures can help to elucidate the mechanisms of selection and accelerate genetic improvement. Fighting chickens have undergone extensive artificial selection, resulting in modifications to their morphology, physiology and behavior compared to wild species. Comparing the genomes of fighting chickens and wild species offers a unique opportunity for identifying signatures of artificial selection.ResultsWe identified selection signals in 100-kb windows sliding in 10-kb steps by using two approaches: the pooled heterozygosity and the fixation index between Xishuangbanna fighting chicken (YNLC) and Red Jungle Fowl. A total of 413 candidate genes were found to be putatively under selection in YNLC. These genes were related to traits such as growth, disease resistance, aggressive behavior and energy metabolism, as well as the morphogenesis and homeostasis of many tissues and organs.ConclusionsThis study reveals mechanisms and targets of artificial selection, which will contribute to improve our knowledge about the evolution of fighting chickens and facilitate future quantitative trait loci mapping.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-016-0239-4) contains supplementary material, which is available to authorized users.

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Genomic Analyses Reveal Potential Independent Adaptation to High Altitude in Tibetan Chickens

Cited by 179 publications

References 45 publications

Genomic data for 78 chickens from 14 populations

Genomic data for 78 chickens from 14 populations

Whole-genome sequencing of eight goat populations for the detection of selection signatures underlying production and adaptive traits

Whole-genome resequencing of Xishuangbanna fighting chicken to identify signatures of selection

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