Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Chungang Feng is active.

Publication


Featured researches published by Chungang Feng.


PLOS ONE | 2011

Genome-wide association study of body weight in chicken F2 resource population.

Xiaorong Gu; Chungang Feng; Li Ma; Chi Song; Yanqiang Wang; Yang Da; Huifang Li; Kuanwei Chen; Shaohui Ye; Changrong Ge; Xiaoxiang Hu; Ning Li

Chicken body weight is an economically important trait and great genetic progress has been accomplished in genetic selective for body weight. To identify genes and chromosome regions associated with body weight, we performed a genome-wide association study using the chicken 60 k SNP panel in a chicken F2 resource population derived from the cross between Silky Fowl and White Plymouth Rock. A total of 26 SNP effects involving 9 different SNP markers reached 5% Bonferroni genome-wide significance. A chicken chromosome 4 (GGA4) region approximately 8.6 Mb in length (71.6–80.2 Mb) had a large number of significant SNP effects for late growth during weeks 7–12. The LIM domain-binding factor 2 (LDB2) gene in this region had the strongest association with body weight for weeks 7–12 and with average daily gain for weeks 6–12. This GGA4 region was previously reported to contain body weight QTL. GGA1 and GGA18 had three SNP effects on body weight with genome-wide significance. Some of the SNP effects with the significance of “suggestive linkage” overlapped with previously reported results.


PLOS Genetics | 2012

The Rose-comb Mutation in Chickens Constitutes a Structural Rearrangement Causing Both Altered Comb Morphology and Defective Sperm Motility

Freyja Imsland; Chungang Feng; Henrik Boije; Bertrand Bed'Hom; Valerie Fillon; Ben Dorshorst; Carl-Johan Rubin; Ranran Liu; Yu Gao; Xiaorong Gu; Yanqiang Wang; David Gourichon; Michael C. Zody; William Zecchin; Agathe Vieaud; Michèle Tixier-Boichard; Xiaoxiang Hu; Finn Hallböök; Ning Li; Leif Andersson

Rose-comb, a classical monogenic trait of chickens, is characterized by a drastically altered comb morphology compared to the single-combed wild-type. Here we show that Rose-comb is caused by a 7.4 Mb inversion on chromosome 7 and that a second Rose-comb allele arose by unequal crossing over between a Rose-comb and wild-type chromosome. The comb phenotype is caused by the relocalization of the MNR2 homeodomain protein gene leading to transient ectopic expression of MNR2 during comb development. We also provide a molecular explanation for the first example of epistatic interaction reported by Bateson and Punnett 104 years ago, namely that walnut-comb is caused by the combined effects of the Rose-comb and Pea-comb alleles. Transient ectopic expression of MNR2 and SOX5 (causing the Pea-comb phenotype) occurs in the same population of mesenchymal cells and with at least partially overlapping expression in individual cells in the comb primordium. Rose-comb has pleiotropic effects, as homozygosity in males has been associated with poor sperm motility. We postulate that this is caused by the disruption of the CCDC108 gene located at one of the inversion breakpoints. CCDC108 is a poorly characterized protein, but it contains a MSP (major sperm protein) domain and is expressed in testis. The study illustrates several characteristic features of the genetic diversity present in domestic animals, including the evolution of alleles by two or more consecutive mutations and the fact that structural changes have contributed to fast phenotypic evolution.


eLife | 2016

The genetic basis for ecological adaptation of the Atlantic herring revealed by genome sequencing

Alvaro Martinez Barrio; Sangeet Lamichhaney; Guangyi Fan; Nima Rafati; Mats Pettersson; He Zhang; Jacques Dainat; Diana Ekman; Marc P. Höppner; Patric Jern; Marcel Martin; Björn Nystedt; Xin Liu; Wenbin Chen; Xinming Liang; Chengcheng Shi; Yuanyuan Fu; Kailong Ma; Xiao Zhan; Chungang Feng; Ulla Gustafson; Carl-Johan Rubin; Markus Sällman Almén; Martina Blass; Michele Casini; Arild Folkvord; Linda Laikre; Nils Ryman; Simon Ming-Yuen Lee Lee; Xun Xu

Ecological adaptation is of major relevance to speciation and sustainable population management, but the underlying genetic factors are typically hard to study in natural populations due to genetic differentiation caused by natural selection being confounded with genetic drift in subdivided populations. Here, we use whole genome population sequencing of Atlantic and Baltic herring to reveal the underlying genetic architecture at an unprecedented detailed resolution for both adaptation to a new niche environment and timing of reproduction. We identify almost 500 independent loci associated with a recent niche expansion from marine (Atlantic Ocean) to brackish waters (Baltic Sea), and more than 100 independent loci showing genetic differentiation between spring- and autumn-spawning populations irrespective of geographic origin. Our results show that both coding and non-coding changes contribute to adaptation. Haplotype blocks, often spanning multiple genes and maintained by selection, are associated with genetic differentiation. DOI: http://dx.doi.org/10.7554/eLife.12081.001


Animal Genetics | 2012

A genome-wide survey of copy number variation regions in various chicken breeds by array comparative genomic hybridization method.

Yanqiang Wang; Xiaorong Gu; Chungang Feng; Chi Song; Xiaoxiang Hu; Ning Li

The discovery of copy number variation (CNV) in the genome has provided new insight into genomic polymorphism. Studies with chickens have identified a number of large CNV segments using a 385k comparative genomic hybridization (CGH) chip (mean length >140 kb). We present a detailed CNV map for local Chinese chicken breeds and commercial chicken lines using an Agilent 400k array CGH platform with custom-designed probes. We identified a total of 130 copy number variation regions (CNVRs; mean length = 25.70 kb). Of these, 104 (80.0%) were novel segments reported for the first time in chickens. Among the 104 novel CNVRs, 56 (53.8%) of the segments were non-coding sequences, 65 (62.5%) showed the gain of DNA and 40 (38.5%) showed the loss of DNA (one locus showed both loss and gain). Overlapping with the formal selective sweep data and the quantitative trait loci data, we identified four loci that might be considered to be high-confidence selective segments that arose during the domestication of chickens. Compared with the CNVRs reported previously, genes for the positive regulation of phospholipase A2 activity were discovered to be significantly over-represented in the novel CNVRs reported here by gene ontology analysis. Availability of our results should facilitate further research in the study of the genetic variability in chicken breeds.


Genetica | 2009

Advanced technologies for genomic analysis in farm animals and its application for QTL mapping

Xiaoxiang Hu; Yu Gao; Chungang Feng; Qiuyue Liu; Xiaobo Wang; Zhuo Du; Qingsong Wang; Ning Li

Rapid progress in farm animal breeding has been made in the last few decades. Advanced technologies for genomic analysis in molecular genetics have led to the identification of genes or markers associated with genes that affect economic traits. Molecular markers, large-insert libraries and RH panels have been used to build the genetic linkage maps, physical maps and comparative maps in different farm animals. Moreover, EST sequencing, genome sequencing and SNPs maps are helping us to understand how genomes function in various organisms and further areas will be studied by DNA microarray technologies and proteomics methods. Because most economically important traits in farm animals are controlled by multiple genes and the environment, the main goal of genome research in farm animals is to map and characterize genes determining QTL. There are two main strategies to identify trait loci, candidate gene association tests and genome scan approaches. In recent years, some new concepts, such as RNAi, miRNA and eQTL, have been introduced into farm animal research, especially for QTL mapping and finding QTN. Several genes that influence important traits have already been identified or are close to being identified, and some of them have been applied in farm animal breeding programs by marker-assisted selection.


PLOS ONE | 2012

The Crest phenotype in chicken is associated with ectopic expression of HOXC8 in cranial skin

Yanqiang Wang; Yu Gao; Freyja Imsland; Xiaorong Gu; Chungang Feng; Ranran Liu; Chi Song; Michèle Tixier-Boichard; David Gourichon; Qingyuan Li; Kuanwei Chen; Huifang Li; Leif Andersson; Xiaoxiang Hu; Ning Li

The Crest phenotype is characterised by a tuft of elongated feathers atop the head. A similar phenotype is also seen in several wild bird species. Crest shows an autosomal incompletely dominant mode of inheritance and is associated with cerebral hernia. Here we show, using linkage analysis and genome-wide association, that Crest is located on the E22C19W28 linkage group and that it shows complete association to the HOXC-cluster on this chromosome. Expression analysis of tissues from Crested and non-crested chickens, representing 26 different breeds, revealed that HOXC8, but not HOXC12 or HOXC13, showed ectopic expression in cranial skin during embryonic development. We propose that Crest is caused by a cis-acting regulatory mutation underlying the ectopic expression of HOXC8. However, the identification of the causative mutation(s) has to await until a method becomes available for assembling this chromosomal region. Crest is unfortunately located in a genomic region that has so far defied all attempts to establish a contiguous sequence.


Animal Genetics | 2009

Mapping quantitative trait loci regulating chicken body composition traits

Yu Gao; Zhuo Du; Wenhua Wei; X. J. Yu; X. M. Deng; Chungang Feng; Jing Fei; J. D. Feng; Ning Li; Xiaoxiang Hu

Genome scans were conducted on an F(2) resource population derived from intercross of the White Plymouth Rock with the Silkies Fowl to detect QTL affecting chicken body composition traits. The population was genotyped with 129 microsatellite markers and phenotyped for 12 body composition traits on 238 F(2) individuals from 15 full-sib families. In total, 21 genome-wide QTL were found to be responsible for 11 traits, including two newly studied traits of proventriculus weight and shank girth. Three QTL were genome-wide significant: at 499 cm on GGA1 (explained 3.6% of phenotypic variance, P < 0.01) and 51 cm on GGA5 (explained 3.3% of phenotypic variance, P < 0.05) for the shank & claw weight and 502 cm on GGA1 (explained 1.4% of phenotypic variance, P < 0.05) for wing weight. The QTL on GGA1 seemed to have pleiotropic effects, also affecting gizzard weight at 490 cm, shank girth at 489 cm and intestine length at 481 cm. It is suggested that further efforts be made to understand the possible pleiotropic effects of the QTL on GGA1 and that on GGA5 for two shank-related traits.


BMC Genomics | 2015

Genome-wide DNA methylome variation in two genetically distinct chicken lines using MethylC-seq

Jinxiu Li; Rujiao Li; Ying Wang; Xiaoxiang Hu; Yiqiang Zhao; Lin Li; Chungang Feng; Xiaorong Gu; Fang Liang; Susan J. Lamont; Songnian Hu; Huaijun Zhou; Ning Li

BackgroundDNA cytosine methylation is an important epigenetic modification that has significant effects on a variety of biological processes in animals. Avian species hold a crucial position in evolutionary history. In this study, we used whole-genome bisulfite sequencing (MethylC-seq) to generate single base methylation profiles of lungs in two genetically distinct and highly inbred chicken lines (Fayoumi and Leghorn) that differ in genetic resistance to multiple pathogens, and we explored the potential regulatory role of DNA methylation associated with immune response differences between the two chicken lines.MethodsThe MethylC-seq was used to generate single base DNA methylation profiles of Fayoumi and Leghorn birds. In addition, transcriptome profiling using RNA–seq from the same chickens and tissues were obtained to interrogate how DNA methylation regulates gene transcription on a genome-wide scale.ResultsThe general DNA methylation pattern across different regions of genes was conserved compared to other species except for hyper-methylation of repeat elements, which was not observed in chicken. The methylation level of miRNA and pseudogene promoters was high, which indicates that silencing of these genes may be partially due to promoter hyper-methylation. Interestingly, the promoter regions of more recently evolved genes tended to be more highly methylated, whereas the gene body regions of evolutionarily conserved genes were more highly methylated than those of more recently evolved genes. Immune-related GO (Gene Ontology) terms were significantly enriched from genes within the differentially methylated regions (DMR) between Fayoumi and Leghorn, which implicates DNA methylation as one of the regulatory mechanisms modulating immune response differences between these lines.ConclusionsThis study establishes a single-base resolution DNA methylation profile of chicken lung and suggests a regulatory role of DNA methylation in controlling gene expression and maintaining genome transcription stability. Furthermore, profiling the DNA methylomes of two genetic lines that differ in disease resistance provides a unique opportunity to investigate the potential role of DNA methylation in host disease resistance. Our study provides a foundation for future studies on epigenetic modulation of host immune response to pathogens in chickens.


PLOS Genetics | 2014

A cis-regulatory mutation of PDSS2 causes silky-feather in chickens.

Chungang Feng; Yu Gao; Ben Dorshorst; Chi Song; Xiaorong Gu; Qingyuan Li; Jinxiu Li; Tongxin Liu; Carl Johan Rubin; Yiqiang Zhao; Yanqiang Wang; Jing Fei; Huifang Li; Kuanwei Chen; Hao Qu; Dingming Shu; Chris M. Ashwell; Yang Da; Leif Andersson; Xiaoxiang Hu; Ning Li

Silky-feather has been selected and fixed in some breeds due to its unique appearance. This phenotype is caused by a single recessive gene (hookless, h). Here we map the silky-feather locus to chromosome 3 by linkage analysis and subsequently fine-map it to an 18.9 kb interval using the identical by descent (IBD) method. Further analysis reveals that a C to G transversion located upstream of the prenyl (decaprenyl) diphosphate synthase, subunit 2 (PDSS2) gene is causing silky-feather. All silky-feather birds are homozygous for the G allele. The silky-feather mutation significantly decreases the expression of PDSS2 during feather development in vivo. Consistent with the regulatory effect, the C to G transversion is shown to remarkably reduce PDSS2 promoter activity in vitro. We report a new example of feather structure variation associated with a spontaneous mutation and provide new insight into the PDSS2 function.


Animal Genetics | 2011

Evaluation of SNPs in the chicken HMGA2 gene as markers for body weight gain

Chi Song; Xiaorong Gu; Chungang Feng; Yanqiang Wang; Yu Gao; Xiaoxiang Hu; Ning Li

A QTL affecting body weight in chickens has been mapped to GGA1, between the markers GCT0006 and MCW0106. The gene HMGA2, which was previously identified as a candidate gene for determining body height in humans and mice, is also conspicuously close to the MCW0106 marker in chickens. Subsequently, 14 SNP markers of HMGA2 were genotyped in CAU chicken resource populations, and the associations between body weight and those SNP markers that displayed polymorphisms were analysed. Three SNPs (rs13849241, rs15231472 and rs13849381) were found to be significantly correlated with body weight in chickens (P < 0.05). Furthermore, haplotypes constructed based on these three SNPs were also discovered to be associated with body weight in chickens at the ages of 6, 7, 9 and 12 weeks. These results suggest that the chicken HMGA2 gene is indeed involved in body weight gain.

Collaboration


Dive into the Chungang Feng's collaboration.

Top Co-Authors

Avatar

Ning Li

China Agricultural University

View shared research outputs
Top Co-Authors

Avatar

Xiaoxiang Hu

China Agricultural University

View shared research outputs
Top Co-Authors

Avatar

Yanqiang Wang

China Agricultural University

View shared research outputs
Top Co-Authors

Avatar

Yu Gao

China Agricultural University

View shared research outputs
Top Co-Authors

Avatar

Xiaorong Gu

China Agricultural University

View shared research outputs
Top Co-Authors

Avatar

Chi Song

China Agricultural University

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Zhuo Du

China Agricultural University

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Jing Fei

China Agricultural University

View shared research outputs
Researchain Logo
Decentralizing Knowledge