An Efficient Genotyping Method in Chicken Based on Genome Reducing and Sequencing

The Identification of Functional Genes Affecting Fat-Related Meat Traits in Meat-Type Pigeons Using Double-Digest Restriction-Associated DNA Sequencing and Molecular Docking Analysis

The Chinese indigenous Shiqi (SQ) pigeon and the imported White King (WK) pigeon are two meat-type pigeon breeds of economical and nutritional importance in China. They displayed significant differences in such meat quality traits as intramuscular fat (IMF) content and fatty acid (FA) compositions in the breast muscles. In this study, we aimed to screen candidate genes that could affect fat-related meat quality traits in meat-type pigeons. We investigated the polymorphic variations at the genomic level using double-digest restriction-associated DNA (ddRAD) sequencing in 12 squabs of SQ and WK pigeons that exhibited significant inter-breed differences in IMF content as well as FA and amino acid compositions in the breast muscles, and screened candidate genes influencing fat-related traits in squabs through gene ontology analysis and pathway analysis. By focusing on 6019 SNPs, which were located in genes with correct annotations and had the potential to induce changes in the encoded proteins, we identified 19 genes (ACAA1, ACAA2, ACACB, ACADS, ACAT1, ACOX3, ACSBG1, ACSBG2, ACSL1, ACSL4, ELOVL6, FADS1, FADS2, HACD4, HADH, HADHA, HADHB, MECR, OXSM) as candidate genes that could affect fat-related traits in squabs. They were significantly enriched in the pathways of FA metabolism, degradation, and biosynthesis (p < 0.05). Results from molecular docking analysis further revealed that three non-synonymous amino acid alterations, ACAA1(S357N), ACAA2(T234I), and ACACB(H1418N), could alter the non-bonding interactions between the enzymatic proteins and their substrates. Since ACAA1, ACAA2, and ACACB encode rate-limiting enzymes in FA synthesis and degradation, alterations in the enzyme-substrate binding affinity may subsequently affect the catalytic efficiency of enzymes. We suggested that SNPs in these three genes were worthy of further investigation into their roles in explaining the disparities in fat-related traits in squabs.

Restriction site-associated DNA sequencing technologies as an alternative to low-density SNP chips for genomic selection: a simulation study in layer chickens

BACKGROUND

To reduce the cost of genomic selection, a low-density (LD) single nucleotide polymorphism (SNP) chip can be used in combination with imputation for genotyping selection candidates instead of using a high-density (HD) SNP chip. Next-generation sequencing (NGS) techniques have been increasingly used in livestock species but remain expensive for routine use for genomic selection. An alternative and cost-efficient solution is to use restriction site-associated DNA sequencing (RADseq) techniques to sequence only a fraction of the genome using restriction enzymes. From this perspective, use of RADseq techniques followed by an imputation step on HD chip as alternatives to LD chips for genomic selection was studied in a pure layer line.

RESULTS

Genome reduction and sequencing fragments were identified on reference genome using four restriction enzymes (EcoRI, TaqI, AvaII and PstI) and a double-digest RADseq (ddRADseq) method (TaqI-PstI). The SNPs contained in these fragments were detected from the 20X sequence data of the individuals in our population. Imputation accuracy on HD chip with these genotypes was assessed as the mean correlation between true and imputed genotypes. Several production traits were evaluated using single-step GBLUP methodology. The impact of imputation errors on the ranking of the selection candidates was assessed by comparing a genomic evaluation based on ancestry using true HD or imputed HD genotyping. The relative accuracy of genomic estimated breeding values (GEBVs) was investigated by considering the GEBVs estimated on offspring as a reference. With AvaII or PstI and ddRADseq with TaqI and PstI, more than 10 K SNPs were detected in common with the HD SNP chip, resulting in an imputation accuracy greater than 0.97. The impact of imputation errors on genomic evaluation of the breeders was reduced, with a Spearman correlation greater than 0.99. Finally, the relative accuracy of GEBVs was equivalent.

CONCLUSIONS

RADseq approaches can be interesting alternatives to low-density SNP chips for genomic selection. With more than 10 K SNPs in common with the SNPs of the HD SNP chip, good imputation and genomic evaluation results can be obtained. However, with real data, heterogeneity between individuals with missing data must be considered.

Genomic analysis of GBS data reveals genes associated with facial pigmentation in Xinyang blue-shelled layers

Facial pigmentation is an important economic trait of chickens, especially for laying hens, which will affect the carcass appearance of eliminated layers. Therefore, identifying the genomic regions and exploring the function of this region that contributes to understanding the variation of skin color traits is significant for breeding. In the study, 291 pure-line Xinyang blue-shelled laying hens were selected, of which 75 were dark-faced chickens and 216 were white-faced chickens. The population was sequenced and typed by GBS genotyping technology. The obtained high-quality SNPs and pigmentation phenotypes were analyzed by a genome-wide association study (GWAS) and a F ST scan. Based on the two analytical methods, we identified a same genomic region (10.70-11.60 Mb) on chromosome 20 with 68 significant SNPs ( - log⁡ 10 ( P ) > 6 ), mapped to 10 known genes, including NPEPL1, EDN3, GNAS, C20orf85, VAPB, BMP7, TUBB1, ELMO2, DDX27, and NCOA5, which are associated with dermal hyperpigmentation.

A high-resolution genetic linkage map and QTL fine mapping for growth-related traits and sex in the Yangtze River common carp (Cyprinus carpio haematopterus)

Background

A high-density genetic linkage map is essential for QTL fine mapping, comparative genome analysis, identification of candidate genes and marker-assisted selection for economic traits in aquaculture species. The Yangtze River common carp (Cyprinus carpio haematopterus) is one of the most important aquacultured strains in China. However, quite limited genetics and genomics resources have been developed for genetic improvement of economic traits in such strain.

Results

A high-resolution genetic linkage map was constructed by using 7820 2b-RAD (2b-restriction site-associated DNA) and 295 microsatellite markers in a F2 family of the Yangtze River common carp (C. c. haematopterus). The length of the map was 4586.56 cM with an average marker interval of 0.57 cM. Comparative genome mapping revealed that a high proportion (70%) of markers with disagreed chromosome location was observed between C. c. haematopterus and another common carp strain (subspecies) C. c. carpio. A clear 2:1 relationship was observed between C. c. haematopterus linkage groups (LGs) and zebrafish (Danio rerio) chromosomes. Based on the genetic map, 21 QTLs for growth-related traits were detected on 12 LGs, and contributed values of phenotypic variance explained (PVE) ranging from 16.3 to 38.6%, with LOD scores ranging from 4.02 to 11.13. A genome-wide significant QTL (LOD = 10.83) and three chromosome-wide significant QTLs (mean LOD = 4.84) for sex were mapped on LG50 and LG24, respectively. A 1.4 cM confidence interval of QTL for all growth-related traits showed conserved synteny with a 2.06 M segment on chromosome 14 of D. rerio. Five potential candidate genes were identified by blast search in this genomic region, including a well-studied multi-functional growth related gene, Apelin.

Conclusions

We mapped a set of suggestive and significant QTLs for growth-related traits and sex based on a high-density genetic linkage map using SNP and microsatellite markers for Yangtze River common carp. Several candidate growth genes were also identified from the QTL regions by comparative mapping. This genetic map would provide a basis for genome assembly and comparative genomics studies, and those QTL-derived candidate genes and genetic markers are useful genomic resources for marker-assisted selection (MAS) of growth-related traits in the Yangtze River common carp.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4613-1) contains supplementary material, which is available to authorized users.

Identifying Genetic Differences Between Dongxiang Blue-Shelled and White Leghorn Chickens Using Sequencing Data

The Dongxiang Blue-shelled chicken is one of the most valuable Chinese indigenous poultry breeds. However, compared to the Italian native White Leghorn, although this Chinese breed possesses numerous favorable characteristics, it also exhibits lower growth performance and fertility. Here, we utilized genotyping sequencing data obtained via genome reduction on a sequencing platform to detect 100,114 single nucleotide polymorphisms and perform further biological analysis and functional annotation. We employed cross-population extended haplotype homozygosity, eigenvector decomposition combined with genome-wide association studies (EigenGWAS), and efficient mixed-model association expedited methods to detect areas of the genome that are potential selected regions (PSR) in both chicken breeds, and performed gene ontology (GO) enrichment and quantitative trait loci (QTL) analyses annotating using the Kyoto Encyclopedia of Genes and Genomes. The results of this study revealed a total of 2424 outlier loci (p-value <0.01), of which 2144 occur in the White Leghorn breed and 280 occur in the Dongxiang Blue-shelled chicken. These correspond to 327 and 94 PSRs containing 297 and 54 genes, respectively. The most significantly selected genes in Blue-shelled chicken are TMEM141 and CLIC3, while the SLCO1B3 gene, related to eggshell color, was identified via EigenGWAS. We show that the White Leghorn genes JARID2, RBMS3, GPC3, TRIB2, ROBO1, SAMSN1, OSBP2, and IGFALS are involved in immunity, reproduction, and growth, and thus might represent footprints of the selection process. In contrast, we identified six significantly enriched pathways in the Dongxiang Blue-shelled chicken that are related to amino acid and lipid metabolism as well as signal transduction. Our results also reveal the presence of a GO term associated with cell metabolism that occurs mainly in the White Leghorn breed, while the most significant QTL regions mapped to the Chicken QTL Database (GG_4.0) for the Dongxiang Blue-shelled breed are predominantly related to lesions, bone mineral content, and other related traits compared to tibia length and body weight (i.e., at 14, 28, 42, and 70 d) in the White Leghorn. The results of this study highlight differences in growth, immunity, and egg quality traits between the two breeds, and provide a foundation for the exploration of their genetic mechanisms.

Optimized double-digest genotyping by sequencing (ddGBS) method with high-density SNP markers and high genotyping accuracy for chickens

High-density single nucleotide polymorphism (SNP) markers are crucial to improve the resolution and accuracy of genome-wide association study (GWAS) and genomic selection (GS). Numerous approaches, including whole genome sequencing, genome sampling sequencing, and SNP chips are able to discover or genotype markers at different densities and costs. Achieving an optimal balance between sequencing resolution and budgets, especially in large-scale population genetics research, constitutes a major challenge. Here, we performed improved double-enzyme digestion genotyping by sequencing (ddGBS) on chicken. We evaluated eight double-enzyme digestion combinations, and EcoR I- Mse I was chosen as the optimal combination for the chicken genome. We firstly proposed that two parameters, optimal read-count point (ORP) and saturated read-count point (SRP), could be utilized to determine the optimal sequencing volume. A total of 291,772 high-density SNPs from 824 animals were identified. By validation using the SNP chip, we found that the consistency between ddGBS data and the SNP chip is over 99%. The approach that we developed in chickens, which is high-quality, high-density, cost-effective (300 K, $30/sample), and time-saving (within 48 h), will have broad applications in animal breeding programs.

High-throughput and Cost-effective Chicken Genotyping Using Next-Generation Sequencing

Chicken genotyping is becoming common practice in conventional animal breeding improvement. Despite the power of high-throughput methods for genotyping, their high cost limits large scale use in animal breeding and selection. In the present paper we optimized the CornellGBS, an efficient and cost-effective genotyping by sequence approach developed in plants, for its application in chickens. Here we describe the successful genotyping of a large number of chickens (462) using CornellGBS approach. Genomic DNA was cleaved with the PstI enzyme, ligated to adapters with barcodes identifying individual animals, and then sequenced on Illumina platform. After filtering parameters were applied, 134,528 SNPs were identified in our experimental population of chickens. Of these SNPs, 67,096 had a minimum taxon call rate of 90% and were considered 'unique tags'. Interestingly, 20.7% of these unique tags have not been previously reported in the dbSNP. Moreover, 92.6% of these SNPs were concordant with a previous Whole Chicken-genome re-sequencing dataset used for validation purposes. The application of CornellGBS in chickens showed high performance to infer SNPs, particularly in exonic regions and microchromosomes. This approach represents a cost-effective (~US$50/sample) and powerful alternative to current genotyping methods, which has the potential to improve whole-genome selection (WGS), and genome-wide association studies (GWAS) in chicken production.