Guoqiang Yi

Genome-Wide Characterization of Insertion and Deletion Variation in Chicken Using Next Generation Sequencing

Insertion and deletion (INDEL) is one of the main events contributing to genetic and phenotypic diversity, which receives less attention than SNP and large structural variation. To gain a better knowledge of INDEL variation in chicken genome, we applied next generation sequencing on 12 diverse chicken breeds at an average effective depth of 8.6. Over 1.3 million non-redundant short INDELs (1–49 bp) were obtained, the vast majority (92.48%) of which were novel. Follow-up validation assays confirmed that most (88.00%) of the randomly selected INDELs represent true variations. The majority (95.76%) of INDELs were less than 10 bp. Both the detected number and affected bases were larger for deletions than insertions. In total, INDELs covered 3.8 Mbp, corresponding to 0.36% of the chicken genome. The average genomic INDEL density was estimated as 0.49 per kb. INDELs were ubiquitous and distributed in a non-uniform fashion across chromosomes, with lower INDEL density in micro-chromosomes than in others, and some functional regions like exons and UTRs were prone to less INDELs than introns and intergenic regions. Nearly 620,253 INDELs fell in genic regions, 1,765 (0.28%) of which located in exons, spanning 1,358 (7.56%) unique Ensembl genes. Many of them are associated with economically important traits and some are the homologues of human disease-related genes. We demonstrate that sequencing multiple individuals at a medium depth offers a promising way for reliable identification of INDELs. The coding INDELs are valuable candidates for further elucidation of the association between genotypes and phenotypes. The chicken INDELs revealed by our study can be useful for future studies, including development of INDEL markers, construction of high density linkage map, INDEL arrays design, and hopefully, molecular breeding programs in chicken.

Genetic parameters of feed efficiency traits in laying period of chickens

Laying records on 1,534 F2 hens, derived from a reciprocal cross between White Leghorns and Dongxiang blue-shelled chickens, were used to estimate genetic parameters for residual feed intake (RFI), feed conversion ratio (FCR), daily feed intake (FI), metabolic BW (MBW), BW gain (BWG), and daily egg mass (EM) at 37 to 40 (T1) and 57 to 60 wk age (T2), respectively. Genetic analysis was subsequently conducted with the AI-REML method using an animal model. Estimates for heritability of RFI, FCR, and FI were 0.21, 0.19, and 0.20 in T1, and 0.29, 0.13, and 0.26 in T2, respectively. In T1 and T2, RFI showed high and positive genetic correlations with FCR (0.51, 0.43) and FI (0.72, 0.84), whereas the genetic correlation between FI and FCR was very low (−0.09, 0.11). Genetically, negative correlations were found between RFI and its component traits (−0.01 to −0.47). In addition, high genetic correlations, from 0.76 to 0.94, were observed between T1 and T2 for RFI, FCR, and FI, suggesting that feed efficiency traits in the 2 stages had a similar genetic background. The results indicate that selection for low RFI could reduce FI without significant changes in EM, while selection on FCR will increase EM. The present study lays the foundation for genetic improvement of feed efficiency during the laying period of chickens.

In-Depth Duodenal Transcriptome Survey in Chickens with Divergent Feed Efficiency Using RNA-Seq

Since the feed cost is a major determinant of profitability in poultry industry, how to improve feed efficiency through genetic selection is an intriguing subject for breeders and producers. As a more suitable indicator assessing feed efficiency, residual feed intake (RFI) is defined as the difference between observed and expected feed intake based on maintenance and growth. However, the genetic mechanisms responsible for RFI in chickens are still less well appreciated. In this study, we investigated the duodenal transcriptome architecture of extreme RFI phenotypes in the six brown-egg dwarf hens (three per group) using RNA sequencing technology. Among all mapped reads, an average of 75.62% fell into annotated exons, 5.50% were located in introns, and the remaining 18.88% were assigned to intergenic regions. In total, we identified 41 promising candidate genes by differential expression analysis between the low and high RFI groups. Furthermore, qRT-PCR assays were designed for 10 randomly chosen genes, and nine (90.00%) were successfully validated. Functional annotation analyses revealed that these significant genes belong to several specific biological functions related to digestibility, metabolism and biosynthesis processes as well as energy homeostasis. We also predicted 253 intergenic coding transcripts, and these transcripts were mainly involved in fundamental biological regulation and metabolism processes. Our findings provided a pioneering exploration of biological basis underlying divergent RFI using RNA-Seq, which pinpoints promising candidate genes of functional relevance, is helpful to guide future breeding strategies to optimize feed efficiency and assists in improving the current gene annotation in chickens.

The sodium channel gene family is specifically expressed in hen uterus and associated with eggshell quality traits

BackgroundEggshell quality is important for the poultry industry. During eggshell formation a mass of inorganic minerals is deposited. The Sodium Channel (SCNN1) gene family plays an essential role in cation transportation. The objective of this study was to investigate the pattern of expression of members of the SCNN1 gene family, their variation and their effects on eggshell quality.ResultThe highest expression of SCNN1a, SCNN1b, and SCNN1g genes were in the active uterus during eggshell mineralization, while SCNN1d showed its highest expression level in the quiescent uterus (no egg present). Nineteen candidate SNPs from the four genes were genotyped in a population of 338 White Leghorn layers. Association analysis between SNPs (haplotypes/diplotypes) and eggshell traits was performed. Among seven significant SNPs, five SNPs were associated with eggshell strength, eggshell thickness, eggshell percentage or/and egg weight, while the other two SNPs within SCNN1d were only associated with eggshell percentage. These SNPs had a 0.25-6.99% contribution to phenotypic variance, depending on the trait. In haplotype analysis, SCNN1b and SCNN1d were associated with egg weight. The SCNN1b and SCNN1g were significantly associated with eggshell weight while only SCNN1g explained 2.04% of phenotypic variance. All the alleles of the members of SCNN1 gene family were associated with eggshell percentage and eggshell thickness, and others members had an association with eggshell strength except for SCNN1a. The contribution of different haplotypes of the SCNN1 gene family to eggshell phenotypic variance ranged from 0.09% to 5.74%.ConclusionsOur study indicated that the SCNN1 gene family showed tissue expression specificity and was significantly associated with eggshell traits in chicken. This study provides evidence that genetic variation in members of the sodium channel can influence eggshell quality.

Whole-genome scan for signatures of recent selection reveals loci associated with important traits in White Leghorn chickens

Chicken is considered to be an excellent model for genetic studies of phenotypic and genomic evolution, with large effective population size, specialized commercial lines, and strong human-driven selection. High-density chicken SNP chips can help to achieve a better understanding of the selection mechanisms in artificially selected populations. We performed the genome-wide tests for the selection signature in 385 White Leghorn hens and mapped positively selected regions to the genome annotations. Ten QTL related to egg production, egg quality, growth, and disease resistance traits were selected for extended haplotype homozygosity tests to give a brief overview of recent selection signatures in chicken QTL. We also reported 185 candidate genes/CDSs showing top P-values and slower decay of haplotype homozygosities. Some of these genes seemed to have significant effects on important economical traits, and most of them have not been reported in chickens. The current study provides a genome-wide map of linkage disequilibrium extents and distributions and selection footprints in the chicken genome. A panel of genes, including PRL, NCKX1, NRF1, LHX2, and SFRP1 associated with egg production, metabolism traits, and response to illumination were identified. In addition, there were more genes identified that have not yet been reported in chickens, and our results provide new clues for further study.

Identification of Promising Mutants Associated with Egg Production Traits Revealed by Genome-Wide Association Study

Egg number (EN), egg laying rate (LR) and age at first egg (AFE) are important production traits related to egg production in poultry industry. To better understand the knowledge of genetic architecture of dynamic EN during the whole laying cycle and provide the precise positions of associated variants for EN, LR and AFE, laying records from 21 to 72 weeks of age were collected individually for 1,534 F2 hens produced by reciprocal crosses between White Leghorn and Dongxiang Blue-shelled chicken, and their genotypes were assayed by chicken 600 K Affymetrix high density genotyping arrays. Subsequently, pedigree and SNP-based genetic parameters were estimated and a genome-wide association study (GWAS) was conducted on EN, LR and AFE. The heritability estimates were similar between pedigree and SNP-based estimates varying from 0.17 to 0.36. In the GWA analysis, we identified nine genome-wide significant loci associated with EN of the laying periods from 21 to 26 weeks, 27 to 36 weeks and 37 to 72 weeks. Analysis of GTF2A1 and CLSPN suggested that they influenced the function of ovary and uterus, and may be considered as relevant candidates. The identified SNP rs314448799 for accumulative EN from 21 to 40 weeks on chromosome 5 created phenotypic differences of 6.86 eggs between two homozygous genotypes, which could be potentially applied to the molecular breeding for EN selection. Moreover, our finding showed that LR was a moderate polygenic trait. The suggestive significant region on chromosome 16 for AFE suggested the relationship between sex maturity and immune in the current population. The present study comprehensively evaluates the role of genetic variants in the development of egg laying. The findings will be helpful to investigation of causative genes function and future marker-assisted selection and genomic selection in chickens.

Promising Loci and Genes for Yolk and Ovary Weight in Chickens Revealed by a Genome-Wide Association Study.

Because it serves as the cytoplasm of the oocyte and provides a large amount of reserves, the egg yolk has biological significance for developing embryos. The ovary and its hierarchy of follicles are the main reproductive organs responsible for yolk deposition in chickens. However, the genetic architecture underlying the yolk and ovarian follicle weights remains elusive. Here, we measured the yolk weight (YW) at 11 age points from onset of egg laying to 72 weeks of age and measured the follicle weight (FW) and ovary weight (OW) at 73 weeks as part of a comprehensive genome-wide association study (GWAS) in 1,534 F2 hens derived from reciprocal crosses between White Leghorn (WL) and Dongxiang chickens (DX). For all ages, YWs exhibited moderate single nucleotide polymorphism (SNP)-based heritability estimates (0.25–0.38), while the estimates for FW (0.16) and OW (0.20) were relatively low. Independent univariate genome-wide screens for each trait identified 12, 3, and 31 novel significant associations with YW, FW, and OW, respectively. A list of candidate genes such as ZAR1, STARD13, ACER1b, ACSBG2, and DHRS12 were identified for having a plausible function in yolk and follicle development. These genes are important to the initiation of embryogenesis, lipid transport, lipoprotein synthesis, lipid droplet promotion, and steroid hormone metabolism, respectively. Our study provides for the first time a genome-wide association (GWA) analysis for follicle and ovary weight. Identification of the promising loci as well as potential candidate genes will greatly advance our understanding of the genetic basis underlying dynamic yolk weight and ovarian follicle development and has practical significance in breeding programs for the alteration of yolk weight at different age points.

Genome‐wide copy number profiling using high‐density SNP array in chickens

Phenotypic diversity is a direct consequence resulting mainly from the impact of underlying genetic variation, and recent studies have shown that copy number variation (CNV) is emerging as an important contributor to both phenotypic variability and disease susceptibility. Herein, we performed a genome-wide CNV scan in 96 chickens from 12 diversified breeds, benefiting from the high-density Affymetrix 600 K SNP arrays. We identified a total of 231 autosomal CNV regions (CNVRs) encompassing 5.41 Mb of the chicken genome and corresponding to 0.59% of the autosomal sequence. The length of these CNVRs ranged from 2.6 to 586.2 kb with an average of 23.4 kb, including 130 gain, 93 loss and eight both gain and loss events. These CNVRs, especially deletions, had lower GC content and were located particularly in gene deserts. In particular, 102 CNVRs harbored 128 chicken genes, most of which were enriched in immune responses. We obtained 221 autosomal CNVRs after converting probe coordinates to Galgal3, and comparative analysis with previous studies illustrated that 153 of these CNVRs were regarded as novel events. Furthermore, qPCR assays were designed for 11 novel CNVRs, and eight (72.73%) were validated successfully. In this study, we demonstrated that the high-density 600 K SNP array can capture CNVs with higher efficiency and accuracy and highlighted the necessity of integrating multiple technologies and algorithms. Our findings provide a pioneering exploration of chicken CNVs based on a high-density SNP array, which contributes to a more comprehensive understanding of genetic variation in the chicken genome and is beneficial to unearthing potential CNVs underlying important traits of chickens.

Genome-Wide Association Studies for Comb Traits in Chickens

The comb, as a secondary sexual character, is an important trait in chicken. Indicators of comb length (CL), comb height (CH), and comb weight (CW) are often selected in production. DNA-based marker-assisted selection could help chicken breeders to accelerate genetic improvement for comb or related economic characters by early selection. Although a number of quantitative trait loci (QTL) and candidate genes have been identified with advances in molecular genetics, candidate genes underlying comb traits are limited. The aim of the study was to use genome-wide association (GWA) studies by 600 K Affymetrix chicken SNP arrays to detect genes that are related to comb, using an F2 resource population. For all comb characters, comb exhibited high SNP-based heritability estimates (0.61–0.69). Chromosome 1 explained 20.80% genetic variance, while chromosome 4 explained 6.89%. Independent univariate genome-wide screens for each character identified 127, 197, and 268 novel significant SNPs with CL, CH, and CW, respectively. Three candidate genes, VPS36, AR, and WNT11B, were determined to have a plausible function in all comb characters. These genes are important to the initiation of follicle development, gonadal growth, and dermal development, respectively. The current study provides the first GWA analysis for comb traits. Identification of the genetic basis as well as promising candidate genes will help us understand the underlying genetic architecture of comb development and has practical significance in breeding programs for the selection of comb as an index for sexual maturity or reproduction.

Genetic analysis for dynamic changes of egg weight in 2 chicken lines

One of the main concerns for poultry producers is how to maintain egg uniformity and stability in size and weight following the rapid growth during the early laying period. In this study, we aimed to investigate the increase in egg weight with advancing hen age, and to estimate genetic parameters of these increment traits in 2 pure lines of chickens (i.e., 2,010 White Leghorn and 1,200 brown-egg dwarf hens), using the restricted maximum likelihood method with the DMU procedure. We collected age at first egg (AFE), first egg weight (FEW) and kept records of egg weight per 10 wk from 30 to 60 wk of age. Meanwhile, the increments of egg weight were calculated for the evaluation of age-dependent dynamic changes. The increment of egg weight gained dramatically before 30 wk of age and became slower with the advance of age. Heritability estimates of AFE were larger than 0.32, and the low to moderate genetic correlations between AFE and FEW were observed in the 2 lines. The FEW showed high variation level compared with egg weights at later ages in the 2 lines, and had moderate heritability estimates in White Leghorns (0.20) and dwarf hens (0.33). Egg weights at different ages were highly heritable in the 2 lines (h(2) ≥ 0.35), and had strong genetic and phenotypic correlations among different ages. The estimates of heritability for most increment traits were low to moderate, especially those increments for 10-wk intervals ranging from 0.00 to 0.14. The genetic correlations among 3 consecutive egg weight increments for 10-wk intervals were low to moderate. Our results in the 2 lines should provide important insights into the genetic architecture of increment traits and offer some suggestions for producing uniform and stable eggs in response to advancing age.