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Record W2531463945 · doi:10.1093/jmcb/mjw044

Comparative population genomics reveals genetic basis underlying body size of domestic chickens

2016· article· en· W2531463945 on OpenAlexaff
Mingshan Wang, Yongxia Huo, Yán Li, Newton O. Otecko, Ling‐Yan Su, Haibo Xu, Shi‐Fang Wu, Min‐Sheng Peng, Hequn Liu, Lin Zeng, David M. Irwin, Yong‐Gang Yao, Dong‐Dong Wu, Ya‐Ping Zhang

Bibliographic record

VenueJournal of Molecular Cell Biology · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsUniversity of Toronto
FundersYouth Innovation Promotion AssociationNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsBiologyGenomicsGeneticsFunctional genomicsTraitComparative genomicsZebrafishQuantitative trait locusPopulationGeneGenetic architectureGenomeEvolutionary biologyEffective population sizeGenetic variationComputational biology

Abstract

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Domestic animals are excellent biological models widely used in developmental biology, phenotypic evolution, and medical research studies. They have been developed as different breeds exhibiting remarkable differences in morphology, physiology, behavior, and adaptations (Darwin, 1868; Roots, 2007; Sutter et al., 2007; Menheniott et al., 2013; Gou et al., 2014; Yoon et al., 2014; Wang et al., 2015a, 2016). As an economic character, body size of domestic animals is extremely important for humans and the development of human civilization. An amazing amount of body size variation is seen within domestic animals, which is much higher than that seen in their wild ancestors (Roots, 2007). In addition to breeders, both evolutionary and developmental biologists are interested in discovering and characterizing the mechanisms that underlie the genetic control of variation in body size of domestic animals (Sutter et al., 2007; Makvandi-Nejad et al., 2012; Gou et al., 2014). Domestic chickens are the most phenotypically variable bird (Darwin, 1868). For instance, bantam and cochin are amazing chicken breeds with adult body sizes at ~0.5 and ~5 kg, respectively, on the two extremes. As the farm animal with the widest distribution globally and raised in the largest number, domestic chickens have also been used in genetic and medical studies (Lawler, 2014). Genetic variants of specific traits, especially for body size, have been characterized, as they have major implications in both research and breeding (Sutter et al., 2007; Makvandi-Nejad et al., 2012; Gou et al., 2014). Several hundreds of quantitative trait loci (QTL) have been mapped and reported to be associated with growth and body weight of chickens (http://www.animalgenome.org/cgi-bin/QTLdb/GG/index). Despite these achievements, most of these QTLs are mapped to large genomic regions due to the low resolution of low-density loci and limited number of microsatellite and SNP panel markers. Thus, only a limited number of causative loci have been identified. For example, some genes, including IGF1, TBC1D1, FOXO1A, KPNA3, INTS6, and HNF4G, have been associated with growth and body weight in chickens (Rubin et al., 2010; Gu et al., 2011; Elferink et al., 2012; Xie et al., 2012; Wang et al., 2015b). These studies were mostly based on commercial chickens with very limited variations, and most of the variants controlling body size could have likely been missed. Genome-wide association studies (GWAS) hold a promise for elucidating the quantitative genetic basis of this complex trait (Gu et al., 2011; Elferink et al., 2012; Xie et al., 2012; Wang et al., 2015b), although the difficulty of the methods and the high expense of collecting phenotypic data hamper its wide application. In addition, the great phenotypic diversity among the diverse breeds and their complicated demographic histories (Miao et al., 2013) have also impeded the study for genetic mechanisms underlying the variation of body size in chickens. Fortunately, next-generation genome sequencing data supplemented by comparative population genomics have revolutionized the fields of quantitative genetics and evolution, and thus have proved to be a powerful tool for interpreting the genetic underpinnings of complex traits in domestic animals, e.g. the head crest in the rock pigeon (Shapiro et al., 2013), cold adaptation of high latitude Chinese pigs (Ai et al., 2015), and adaptation to starch-rich foods by dogs (Axelsson et al., 2013). Yuanbao chicken, a famous Chinese ornamental chicken breed, is known for its miniature body size, with adult male weight ~800 g and adult female ~500 g. It has a long breeding history that can be traced back to the Tang dynasty (Supplementary Figure S1). Both the small body size that makes it easily handled in the palm and the appearance similar to ‘Yuanbao’, a metallic ingot used in ancient China as money, made Yuanbao chicken be treated as a symbol of wealth at-hand in ancient times (Supplementary Figure S1). To date, Yuanbao chicken is indisputably one of the most esteemed chicken breeds in China. Here, we employed comparative population genomics to study the genetic basis underlying the small body size of Yuanbao chicken. We identified four novel loci that potentially control the variation in body size of domestic chickens. In this study, 89 genomes were obtained representing 7 Red Junglefowls, 24 Yuanbao chickens (Supplementary Figure S1), and 58 other domestic chickens, with ~12.2× sequence coverage for each individual (Supplementary Figure S2 and Table S1). Comparisons among the genome sequences identified a total of 21286312 SNPs, with 51.8% of them mapping to intergenic regions, 42.6% to intronic regions, and only a small proportion (1.5%) mapping to exonic regions of the genome (Supplementary Table S2). Functional annotation of the SNPs assigned to protein-coding regions identified 101999 SNPs that produce non-synonymous amino acid substitutions and 226713 SNPs that were synonymous, with 704 genes having SNPs that cause gain or loss of a stop codon (Supplementary Table S3). Further comparisons indicated that 88% and 90% of the SNPs used in the 60 K Illumina BeadChip genotyping array and the 600 K Affymetrix® Axiom® HD genotyping array, respectively, were contained in our new dataset. Our dataset of SNPs is much larger than those available in the chicken SNP database: 14353694 and 8670333 of our SNPs were not reported in BUILD 138 and BUILD 145 of the chicken dbSNP databases (ftp://ftp.ncbi.nih.gov/snp/organisms/chicken_9031), respectively. These novel SNPs potentially supplement the catalog of chicken variants. Compared with other birds, Yuanbao chicken showed a lower level of nucleotide diversity (mean value: 4.56E-03) (Supplementary Figure S3). A phylogenetic tree of all individuals was constructed using weighted neighbour-joining method (Bruno et al., 2000), which revealed that Yuanbao chicken formed a relatively homogeneous ancestral cluster (Figure 1A). Principle component analysis (PCA) (Figure 1B), admixture (Supplementary Figure S4), and haplotype-based structure analyses (Supplementary Figure S5) indicated that several Yuanbao chickens had mixed ancestry with other chicken breeds. Phylogenetic and positive selection analyses. (A) Neighbour-joining tree of 89 chicken genomes. (B) PCA. (C and D) Genomic landscape of population differentiation by FST (C) and LSBL (D). Four significant clusters are marked and presented. YB, Yuanbao chicken; RJF, Red Junglefowl; DWS, Daweishan chicken. Comparative analysis of population variants is a powerful tool that has enabled successful investigation into genetic mechanisms underlying complex traits (Axelsson et al., 2013; Kamberov et al., 2013; Shapiro et al., 2013; Ai et al., 2015; Lamichhaney et al., 2015). Since Yuanbao chicken has a remarkably smaller body size compared to the average body size of chickens, comparative genome analysis of Yuanbao and other chickens would be an effective strategy to identify the genetic basis underlying the variation in body size among chickens. Here, we employed FST and LSBL (Shriver et al., 2004) to evaluate the population differentiation of Yuanbao chicken from other chickens (Figure 1C and D). First, a sliding window analysis was performed, with 50 kb window size and 25 kb step size, identifying 268 and 275 genes from the empirical data with FST and LSBL, respectively, as candidates based on the outlier approach (99th percentile cutoff). Functional enrichment analysis of these candidate genes did not reveal any pathway specifically associated with the development of body size (Supplementary Tables S4 and S5). By combining the signals of FST and LSBL, we identified four regions of the genome (chr22:0.25Mb–0.33Mb, chr1:147.55Mb–147.82Mb, chr2:57.05Mb–57.22Mb, and chr24:6.1Mb–6.3Mb) that exhibited extreme population differentiation, likely as the result of artificial selection. The genomic region chr22:0.25Mb–0.33Mb stands out as the most extremely candidate selective sweep with the highest level of population differentiation (Figure 1C). There are three genes GKN1, GKN2, and BMP10 located in this region (Figure 2A). GKN1 and GKN2 are paralogues abundantly and uniquely expressed in the stomach (Menheniott et al., 2013). Both genes have documented functional importance in maintaining integrity and normal function of gastric mucosa, and their anomaly is associated with gastric cancer (Kim et al., 2014; Yoon et al., 2014). In Yuanbao and other chickens, both GKN1 and GKN2 exhibited no or extremely low expression levels in the heat, kidney, spleen, muscle, liver, and lung (Supplementary Figure S6). Population differentiation in chr22:0.25 Mb–0.33 Mb between Yuanbao and other chickens. (A−C) Landscape of FST (A), LSBL (B), and ΔAF (C). (D) Haplotype comparison between Yuanbao and other chickens. Alternative alleles are labelled in blue. BMP10, a member of the transforming growth factor β (TGFβ) family, showed consistently higher values in FST and LSBL analyses and high differences in allele frequencies (Figure 2A−C). A haplotype comparison analysis revealed a consistent differentiation of BMP10 for Yuanbao chicken from other chickens (Figure 2D). Until now, a role of BMP10 in body size has not been reported in chickens. In addition, no QTL associated with body size in chickens was mapped to this genomic region. Further investigation showed that BMP10 had a high expression in the heart (Supplementary Figure S7), and the expression level was significantly upregulated in Yuanbao chicken compared to other chickens (Figure 3A). Phylogenetic network analysis based on the Sanger resequencing verified data also supported the conclusion that the promoter region of BMP10 has become highly differentiated in Yuanbao chicken compared to other chickens (Figure 3B). To examine promoter activity, we performed luciferase reporter gene assays with BMP10 promoter sequence from Yuanbao chicken and the reference sequence. Consistently, we observed an increased reporter activity driven by the BMP10 promoter of Yuanbao chicken compared to the reference promoter (Figure 3C and D). Next, based on our phylogenetic network, we identified 21 SNPs that were located upstream of BMP10 and showed high differentiation between Yuanbao and other chickens. These SNPs were further examined to investigate differences in DNA−protein interactions by electrophoretic mobility shift assays (EMSA) with nuclear extracts from chicken hearts. Probes for five of these SNPs showed differences in gel shift between Yuanbao and other chickens (Figure 3E and Supplementary Figure S8). Mutations in Yuanbao chicken at chr22:274606(T→C) and chr22:274758(C→deletion) led to decrease or loss of interactions between DNA and protein. On the other hand, mutations in Yuanbao chicken at chr22:274670(A→G), chr22:276118(A→G), and chr22:276140(C→T) increased the DNA−protein interaction. From these observations, we inferred that the differences in protein binding, due to the underlying SNPs, likely contribute to the upregulation of BMP10 expression in the heart of Yuanbao chicken (Figure 3A). We further genotyped one SNP within this strong linkage region, which showed a significant association with body weight (Figure 3F, P = 3.249E-18). The SNP could of the weight in five chicken chicken, chicken, Yuanbao chicken, and ornamental chicken. and association analysis of the gene (A) of the expression of BMP10 in heart between and other chickens. (B) network of the BMP10 promoter (C) structure of luciferase reporter with different (D) of luciferase activity of the between and other chickens. SNPs mobility by and to with the allele and reference respectively. analysis of BMP10 and is the reference is by YB, Yuanbao chicken. of BMP10 a decrease in body weight in et al., To examine it is a function of BMP10 to control body size in we performed an of BMP10 in from the were with BMP10 respectively. of BMP10 in in a body and a body compared to control (Figure and Supplementary Figure These that BMP10 has an important role in body is a normal and in growth and development and To study the phenotypic of BMP10 on in we with and the number of at with of BMP10 showed a larger number of and only of compared with the control (Figure and Supplementary Figure These that of BMP10 growth in which would growth and result in a these data that upregulation of BMP10 likely to a smaller body size of Yuanbao chicken. of BMP10 developmental in (A−C) at Compared with control with BMP10 exhibited a body by the and a body by the Supplementary Figure for and that the BMP10 higher of with developmental and body of BMP10 in and of at Red in the Compared to the with BMP10 and with of the The regions in are in higher to the a cluster of selective sweep SNPs, significantly higher levels of population differentiation as revealed by FST (Figure and LSBL (Figure gene is located in this region. this region is located within a reported QTL associated with and et al., Gu et al., The gene which a role in the control of and growth et al., 2013), is to this mapped analysis showed that expression of was in the heart of Yuanbao chicken (Supplementary Figure P to that in chr1:147.55Mb–147.82Mb, no protein-coding gene is located in the genomic region, although it also strong signals of selection with high levels of population differentiation as revealed by FST (Figure and LSBL (Figure QTL mapping has that this region is associated with and in chickens et al., et al., et al., is upstream of the gene factor a factor that a role in animal development and We observed an upregulated expression of in of Yuanbao chicken compared to domestic chicken = and Red = (Supplementary Figure The mapped region protein-coding genes (Supplementary Table S6). There is no QTL associated with body weight or growth in this region. These genes are in biological (Supplementary Table S6). For example, is associated with in chickens et al., and are in et al., 2007; et al., a protein is highly expressed in the heart and muscle, which is in maintaining integrity in some of in of in et al., In our study, the expression of was in the of Yuanbao chicken compared to domestic chicken = and Red = (Supplementary Figure are of importance and in They are also raised for other biological research and For the of and economic have made great to chickens with a large body size and growth for (Lawler, 2014). Our study four loci that potentially control body size, important and candidate genetic for chicken Our study also a strategy with comparative population genomics to identify candidate for the variation in the body size of chickens. strategy is much and than methods as QTL mapping and A great variation in body size has been observed in several animals, including and chickens (Roots, 2007). size is not only an important commercial trait for also a for evolutionary and developmental studies (Sutter et al., 2007; Makvandi-Nejad et al., 2012; et al., 2012; et al., 2013; et al., 2014). The investigation in variants controlling variation in body size has from animal breeders, evolutionary and developmental and medical (Sutter et al., 2007; Makvandi-Nejad et al., 2012; Gou et al., 2014). size, of complex traits, is to be by genes in similar functional et al., For example, in a study of loci associated with body were these loci only for of variation et al., 2015). In very genes have been reported to be in the of body size in domestic For example, variants at genes of the size seen in some breeds et al., 2013). In a similar was four loci of the variation in body size et al., Here, we also that BMP10 could of body size variation in five chicken including chicken, chicken, Yuanbao chicken, and ornamental chicken. These between humans and domestic animals are likely by the differences in artificial selection. In the genetic basis underlying the small body size of Yuanbao chicken, we identified several genomic regions associated with A region was identified on sequence is upstream of the protein-coding gene and showed of positive expression was in the heart of Yuanbao chicken. The human has been reported to be associated with et al., 2015). A based on the Illumina 60 K SNP also for a association of with body weight in domestic chickens et al., et al., Gu et al., no protein-coding gene was in the region of which is located upstream of gene in et al., et al., 2013). The expression of was upregulated in of Yuanbao chicken. has a function in controlling body size is protein to DNA and et al., is for the control of body weight and et al., and is associated with in humans et al., In addition, expression of can be by et al., a protein that an important role in the development of the with exhibited in et al., In a selective sweep region in 24 were protein-coding genes with diverse biological a gene for was in Yuanbao chicken, likely an association with the growth of Yuanbao chicken. protein-coding genes GKN1, GKN2, and BMP10 were in the region of Both GKN1 and GKN2 are highly and uniquely expressed in the with important in maintaining its normal BMP10 is specifically expressed in the heart and a role in the development of the heart in et al., and due to development and function et al., of BMP10 in to and in et al., with of BMP10 in the a in the heart size and a in body weight and size at the of et al., BMP10 is also reported to have a role in and growth of et al., et al., 2014). For example, BMP10 expression was observed to be or in and BMP10 in and of cancer et al., Further showed that BMP10 expression was upregulated in the heart of Yuanbao chicken, as a result of five mutations upstream of BMP10 that likely increased the promoter to that in et al., an of BMP10 a decrease in body in a function of BMP10 in controlling body size in The four loci identified in our study, with high population differentiation between Yuanbao and other chickens, potentially gene expression than protein-coding sequence. potentially a that of gene expression contribute significantly to the of body size, a consistent with the that in gene expression are important in et al., 2015). There are some in our First, we that five mutations could have likely the promoter activity of BMP10 to higher expression of BMP10 in Yuanbao chicken. mutations chr22:274606(T→C) and chr22:274758(C→deletion) to decrease or loss of DNA−protein the other three mutations chr22:274670(A→G), chr22:276118(A→G), and chr22:276140(C→T) increased DNA−protein Our study could not out which were in these all or only some of these to the promoter of In addition, some miniature domestic chicken breeds have similar body size as Yuanbao chicken, we only Yuanbao chicken as a small chicken in our the region BMP10 gene in Daweishan chicken was in the as in Red and other domestic chicken we that BMP10 has a in other domestic chicken especially due to the complex and demographic history of domestic chickens (Miao et al., 2013). to chicken breeds with small body size and these in the animal were performed to the by the of of to including 24 Yuanbao chickens Daweishan chickens a and miniature Red chickens, and chickens were in this study (Supplementary Table S1). DNA was using the method and the was by and on a DNA was used for the of genome sequencing to the Illumina genome was performed on an Illumina with a of for chickens from our study et al., chickens from the study by et and chickens from the study by et were into our study (Supplementary Table S1). 89 genomes for 7 Red and domestic chickens were sequence were by and using and were the chicken reference genome using with the A of were employed to the including and which were out using the and in the and and in the et al., SNPs and were and using and in with mapping and for which with mapping of all at this were with alleles and within clusters SNPs in a were SNPs were assigned to specific genomic regions and genes using based on the chicken et al., SNPs with were and for each were by and 2007). Genome-wide genetic diversity was for Yuanbao chicken, Red Daweishan chicken, and other chicken using et al., using a sliding window with Several methods were to the population structure of Yuanbao chicken. First, we constructed a neighbour-joining tree using the (Bruno et al., based on the from the for all SNP The tree was using et al., to the of SNPs by regions of strong linkage we the SNPs to the observed using et al., with the 50 and was performed using et al., admixture analysis was performed to the population structure by using et al., with an population size from to based on the we used a haplotype-based and to population structure et al., We employed three to investigate the genomic regions of positive selection in Yuanbao chicken. FST values for each SNP were between Yuanbao and other chickens as et al., LSBL were for each SNP based on the FST values between the three (Shriver et al., we Yuanbao chicken as Red and Daweishan chicken as Daweishan chicken similar to Red and domestic chicken were assigned LSBL for each was using the LSBL = window analysis was performed for FST and LSBL in each window with In addition, we the allele SNP between Yuanbao and other chickens to the of positive selection et al., 2014). candidate selective by methods were using the available at Functional of protein-coding genes including and were using et al., Sanger resequencing on an Genetic was used to SNPs in the region upstream and in the of the BMP10 A total of chickens, including Yuanbao chicken and chickens, were used for used for and sequencing are in Supplementary Table were using and A network was constructed using et al., To further variation at BMP10 to the body size, we genotyped one SNP in chickens from five chicken chicken, chicken, Yuanbao chicken, and ornamental with available body weight using Sanger resequencing The proportion of weight variation was using with the et al., 2007). was from liver, spleen, muscle, kidney, and of adult chickens using and using The and integrity of the was using and was used to using the in a of 25 to the expression levels of BMP10 in the chicken heart were using quantitative with the method and to the gene used for BMP10 are in Supplementary Table was performed on the with was used to the For we from muscle, spleen, liver, and of Yuanbao chicken, domestic chicken, and Red which were using in one of our Supplementary Table were out using et al., with to were chicken reference genome using (Kim et al., with to et al., 2015). et al., were used to new and the with the reference to a annotation et al., was used to the of the gene expression for each between Red and Yuanbao chicken, as as between domestic chicken and Yuanbao chicken. was based on the by et al., To the highly differentiated SNPs in the upstream of BMP10 in Yuanbao chicken increased the BMP10 promoter activity, we performed a luciferase reporter upstream of the BMP10 a long and a respectively, were by and into the and were used to the in 24 were at with the reporter and of luciferase in each using activity was at 24 using the of were with the as the were was used to the between Yuanbao and other chickens. A total of 21 SNPs within upstream region from of the BMP10 which were also verified by Sanger were for a functional using to reveal differences in DNA−protein A total of of at and one were DNA from chickens one Yuanbao chicken and three Chinese domestic were the chickens were and at further extracts were from the heart using The nuclear extracts were to the and for on For the of were to the of the were to the and for at DNA−protein were by on gel at for in were to at for in cold DNA−protein were using and were using A and were at on a Four to five of were for for On were were at in in were and to et The and of the has been and The at the is by the for and of For the were with BMP10 and were examined with a and with A of were for levels of and with to the expression analyses were using analysis animals were for each data are as analysis and of the data were performed using was performed using a or as is indicated by P and P Supplementary is available at of study was supported by from the of China the of and of and the Chinese of of

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.278
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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