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

A Cost-effective, High-throughput, Highly Accurate Genotyping Method for Outbred Populations

Affordable sequencing and genotyping methods are essential for large scale genome-wide association studies. While genotyping microarrays and reference panels for imputation are available for human subjects, non-human model systems often lack such options. Our lab previously demonstrated an efficient and cost-effective method to genotype heterogeneous stock rats using double-digest genotyping-by-sequencing. However, low-coverage whole-genome sequencing offers an alternative method that has several advantages. Here, we describe a cost-effective, high-throughput, high-accuracy genotyping method for N/NIH heterogeneous stock rats that can use a combination of sequencing data previously generated by double-digest genotyping-by-sequencing and more recently generated by low-coverage whole-genome-sequencing data. Using double-digest genotyping-by-sequencing data from 5,745 heterogeneous stock rats (mean 0.21x coverage) and low-coverage whole-genome-sequencing data from 8,760 heterogeneous stock rats (mean 0.27x coverage), we can impute 7.32 million bi-allelic single-nucleotide polymorphisms with a concordance rate >99.76% compared to high-coverage (mean 33.26x coverage) whole-genome sequencing data for a subset of the same individuals. Our results demonstrate the feasibility of using sequencing data from double-digest genotyping-by-sequencing or low-coverage whole-genome-sequencing for accurate genotyping, and demonstrate techniques that may also be useful for other genetic studies in non-human subjects.

Genomic prediction and genome-wide association studies for additive and dominance effects for body composition traits using 50 K and imputed high-density SNP genotypes in Yunong-black pigs

Body composition traits are complex traits controlled by minor genes and, in hybrid populations, are impacted by additive and nonadditive effects. We aimed to identify candidate genes and increase the accuracy of genomic prediction of body composition traits in crossbred pigs by including dominance genetic effects. Genomic selection (GS) and genome-wide association studies were performed on seven body composition traits in 807 Yunong-black pigs using additive genomic models (AM) and additive-dominance genomic models (ADM) with an imputed high-density single nucleotide polymorphism (SNP) array and the Illumina Porcine SNP50 BeadChip. The results revealed that the additive heritabilities estimated for AM and ADM using the 50 K SNP data ranged from 0.20 to 0.34 and 0.11 to 0.30, respectively. However, the ranges of additive heritability for AM and ADM in the imputed data ranged from 0.20 to 0.36 and 0.12 to 0.30, respectively. The dominance variance accounted for 23% and 27% of the total variance for the 50 K and imputed data, respectively. The accuracy of genomic prediction improved by 5% on average for 50 K and imputed data when dominance effect were considered. Without the dominance effect, the accuracies for 50 K and imputed data were 0.35 and 0.38, respectively, and 0.41 and 0.43, respectively, upon considering it. A total of 12 significant SNP and 16 genomic regions were identified in the AM, and 14 significant SNP and 21 genomic regions were identified in the ADM for both the 50 K and imputed data. There were five overlapping SNP in the 50 K and imputed data. In the AM, a significant SNP (CNC10041568) was found in both body length and backfat thickness traits, which was in the PLAG1 gene strongly and significantly associated with body length and backfat thickness in pigs. Moreover, a significant SNP (CNC10031356) with a heterozygous dominant genotype was present in the ADM. Furthermore, several functionally related genes were associated with body composition traits, including MOS, RPS20, LYN, TGS1, TMEM68, XKR4, SEMA4D and ARNT2. These findings provide insights into molecular markers and GS breeding for the Yunong-black pigs.

Genome-wide diversity evaluation and core germplasm extraction in ex situ conservation: A case of golden Camellia tunghinensis

Whether ex situ populations constructed in the limited nursery resources of botanical gardens can preserve enough genetic diversity of endangered plants in the wild remains uncertain. Here, a case study was conducted with Camellia tunghinensis, which is one of the species with the lowest natural distribution area in the sect. Chrysantha (golden camellia) of the family Theaceae. We investigated the genetic diversity and population structure of 229 samples from wild and ex situ populations using genotyping by sequencing (GBS). Core germplasm was constructed from these samples. The results showed that wild C. tunghinensis exhibited high genetic diversity, with observed heterozygosity of 0.257-0.293 and expected heterozygosity of 0.247-0.262. Compared with wild populations, the genetic diversity of ex situ populations established by transplanting wild seedlings was close to or even higher. However, the genetic diversity of those established by seed or cuttings of a few superior trees was lower. The Admixture analysis revealed that the structure of the ex situ populations derived from seeds and cuttings was relatively simple compared with the ex situ populations derived from transplanted wild seedlings and wild populations. These results suggested that direct transplanting of wild seedlings was more conducive to preserving the genetic diversity of endangered plants in the wild. In addition, wild populations demonstrated a small differentiation (mean F ST = 0.044) among themselves, possibly due to long-term and frequent gene flow between the wild populations. In contrast, moderate differentiation (mean F ST > 0.05) was detected among ex situ populations and between ex situ and wild populations. This may be the combined result of the absence of gene flow pathways and strong selection pressure in various ex situ environments. Finally, 77 core germplasms were extracted from 229, likely representing the genetic diversity of C. tunghinensis. This study provides future strategies for the ex situ conservation and management of the golden camellia species and other rare and endangered plants.

Genetic architecture and key regulatory genes of fatty acid composition in Gushi chicken breast muscle determined by GWAS and WGCNA

BACKGROUND

Fatty acids composition in poultry muscle is directly related to its tenderness, flavour, and juiciness, whereas its genetic mechanisms have not been elucidated. In this study, the genetic structure and key regulatory genes of the breast muscle fatty acid composition of local Chinese chicken, Gushi-Anka F2 resource population by integrating genome-wide association study (GWAS) and weighted gene co-expression network analysis (WGCNA) strategies. GWAS was performed based on 323,306 single nucleotide polymorphisms (SNPs) obtained by genotyping by sequencing (GBS) method and 721 chickens from the Gushi-Anka F2 resource population with highly variable fatty acid composition traits in the breast muscle. And then, according to the transcriptome data of the candidate genes that were obtained and phenotypic data of fatty acid composition traits in breast muscle of Gushi chickens at 14, 22, and 30 weeks of age, we conducted a WGCNA.

RESULTS

A total of 128 suggestive significantly associated SNPs for 11 fatty acid composition traits were identified and mapped on chromosomes (Chr) 2, 3, 4, 5, 13, 17, 21, and 27. Of these, the two most significant SNPs were Chr13:5,100,140 (P = 4.56423e-10) and Chr13:5,100,173 (P = 4.56423e-10), which explained 5.6% of the phenotypic variation in polyunsaturated fatty acids (PUFA). In addition, six fatty acid composition traits, including C20:1, C22:6, saturated fatty acid (SFA), unsaturated fatty acids (UFA), PUFA, and average chain length (ACL), were located in the same QTL intervals on Chr13. We obtained 505 genes by scanning the linkage disequilibrium (LD) regions of all significant SNPs and performed a WGCNA based on the transcriptome data of the above 505 genes. Combining two strategies, 9 hub genes (ENO1, ADH1, ASAH1, ADH1C, PIK3CD, WISP1, AKT1, PANK3, and C1QTNF2) were finally identified, which could be the potential candidate genes regulating fatty acid composition traits in chicken breast muscle.

CONCLUSION

The results of this study deepen our understanding of the genetic mechanisms underlying the regulation of fatty acid composition traits, which is helpful in the design of breeding strategies for the subsequent improvement of fatty acid composition in poultry muscle.

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.

Genome-wide association study of 17 serum biochemical indicators in a chicken F2 resource population

BACKGROUND

Serum biochemical indicators are often regarded as direct reflections of animal metabolism and health. The molecular mechanisms underlying serum biochemical indicators metabolism of chicken (Gallus Gallus) have not been elucidated. Herein, we performed a genome-wide association study (GWAS) to identify the variation associated with serum biochemical indicators. The aim of this research was to broaden the understanding of the serum biochemical indicators in chickens.

RESULTS

A GWAS of serum biochemical indicators was carried out on 734 samples from an F2 Gushi× Anka chicken population. All chickens were genotyped by sequencing, 734 chickens and 321,314 variants were obtained after quality control. Based on these variants, a total of 236 single-nucleotide polymorphisms (SNPs) on 9 chicken chromosomes (GGAs) were identified to be significantly (-log₁₀(P) > 5.72) associated with eight of seventeen serum biochemical indicators. Ten novel quantitative trait locis (QTLs) were identified for the 8 serum biochemical indicator traits of the F2 population. Literature mining revealed that the ALPL, BCHE, GGT2/GGT5 genes at loci GGA24, GGA9 and GGA15 might affect the alkaline phosphatase (AKP), cholinesterase (CHE) and γ-glutamyl transpeptidase (GGT) traits, respectively.

CONCLUSION

The findings of the present study may contribute to a better understanding of the molecular mechanisms of chicken serum biochemical indicator regulation and provide a theoretical basis for chicken breeding programs.

3D-GBS: a universal genotyping-by-sequencing approach for genomic selection and other high-throughput low-cost applications in species with small to medium-sized genomes

Despite the increased efficiency of sequencing technologies and the development of reduced-representation sequencing (RRS) approaches allowing high-throughput sequencing (HTS) of multiplexed samples, the per-sample genotyping cost remains the most limiting factor in the context of large-scale studies. For example, in the context of genomic selection (GS), breeders need genome-wide markers to predict the breeding value of large cohorts of progenies, requiring the genotyping of thousands candidates. Here, we introduce 3D-GBS, an optimized GBS procedure, to provide an ultra-high-throughput and ultra-low-cost genotyping solution for species with small to medium-sized genome and illustrate its use in soybean. Using a combination of three restriction enzymes (PstI/NsiI/MspI), the portion of the genome that is captured was reduced fourfold (compared to a "standard" ApeKI-based protocol) while reducing the number of markers by only 40%. By better focusing the sequencing effort on limited set of restriction fragments, fourfold more samples can be genotyped at the same minimal depth of coverage. This GBS protocol also resulted in a lower proportion of missing data and provided a more uniform distribution of SNPs across the genome. Moreover, we investigated the optimal number of reads per sample needed to obtain an adequate number of markers for GS and QTL mapping (500-1000 markers per biparental cross). This optimization allows sequencing costs to be decreased by ~ 92% and ~ 86% for GS and QTL mapping studies, respectively, compared to previously published work. Overall, 3D-GBS represents a unique and affordable solution for applications requiring extremely high-throughput genotyping where cost remains the most limiting factor.

Genome-wide association study for the primary feather color trait in a native Chinese duck

Background: To reveal candidate genes and the molecular genetic mechanism underlying primary feather color trait in ducks, a genome-wide association study (GWAS) for the primary feather color trait was performed based on the genotyping-by-sequencing (GBS) technology for a native Chinese female duck, Longyan Shan-ma ducks. Methods: Blood genomic DNA from 314 female Longyan Shan-ma duck were genotyped using GBS technology. A GWAS for the primary feather color trait with genome variations was performed using an univariate linear mixed model based on all SNPs in autosomes. Results: Seven genome-wide significant single nucleotide polymorphisms (SNPs, Bonferroni-adjusted p-value <8.03 × 10^-7) within the introns of the genes STARD9, ZNF106, SLC7A5, and BANP genes were associated with the primary feather color trait. Twenty-two genome-wide suggestive SNPs (Bonferroni-adjusted p-value <1.61 × 10^-5) of 17 genes (besides ZNF106 and SLC7A5) were also identified. Seven SNPs were located at one 0.22 Mb region (38.65-38.87 Mb) on chromosome 5, and six SNPs were located at one 0.31 Mb region (19.53-19.84 Mb) on chromosome 11. The functions of STARD9, SLC7A5, BANP, LOC101798015, and IPMK were involved pigmentation and follicle development, especially, STARD9 upregulated expression in black feather (haplotype-CCCC) bulb tissue compared with in pockmarked feather (haplotype-TGTT) bulb tissue, implicating these genes as candidate genes for primary feather color trait. Conclusion: The preliminarily findings suggested candidate genes and regions, and the genetic basis of primary feather color trait in a female duck.

Genome-wide association study identifies SNPs for growth performance and serum indicators in Valgus-varus deformity broilers (Gallus gallus) using ddGBS sequencing

Background

Valgus-varus deformity (VVD) is a lateral or middle deviation of the tibiotarsus or tarsometatarsus, which is associated with compromised growth, worse bone quality and abnormal changes in serum indicators in broilers. To investigate the genetic basis of VVD, a genome wide association study (GWAS) was performed to identify candidate genes and pathways that are responsible for VVD leg disease, serum indicators and growth performance in broilers.

Results

In total, VVD phenotype, seven serum indicators and three growth traits were measured for 126 VVD broilers (case group) and 122 sound broilers (control group) based on a high throughput genome wide genotyping-by-sequencing (GBS) method. After quality control 233 samples (113 sound broilers and 120 VVD birds) and 256,599 single nucleotide polymorphisms (SNPs) markers were used for further analysis. As a result, a total of 5 SNPs were detected suggestively significantly associated with VVD and 70 candidate genes were identified that included or adjacent to these significant SNPs. In addition, 43 SNPs located on Chr24 (0.22 Mb - 1.79 Mb) were genome-wide significantly associated with serum alkaline phosphatase (ALP) and 38 candidate genes were identified. Functional enrichment analysis showed that these genes are involved in two Gene Ontology (GO) terms related to bone development (cartilage development and cartilage condensation) and two pathways related to skeletal development (Toll−like receptor signaling pathway and p53 signaling pathway). BARX2 (BARX homeobox 2) and Panx3 (Pannexin 3) related to skeleton diseases and bone quality were obtained according to functional analysis. According to the integration of GWAS with transcriptome analysis, HYLS1 (HYLS1 centriolar and ciliogenesis associated) was an important susceptibility gene.

Conclusions

The results provide some reference for understanding the relationship between metabolic mechanism of ALP and pathogenesis of VVD, which will provide a theoretical basis for disease-resistant breeding of chicken leg soundness.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08236-3.

High-density genetic linkage mapping reveals low stability of QTLs across environments for economic traits in Eucalyptus

Introduction

Eucalyptus urophylla, E. tereticornis and their hybrids are the most important commercial forest tree species in South China where they are grown for pulpwood and solid wood production. Construction of a fine-scale genetic linkage map and detecting quantitative trait loci (QTL) for economically important traits linked to these end-uses will facilitate identification of the main candidate genes and elucidate the regulatory mechanisms.

Method

A high-density consensus map (a total of 2754 SNPs with 1359.18 cM) was constructed using genotyping by sequencing (GBS) on clonal progenies of E. urophylla × tereticornis hybrids. QTL mapping of growth and wood property traits were conducted in three common garden experiments, resulting in a total of 108 QTLs. A total of 1052 candidate genes were screened by the efficient combination of QTL mapping and transcriptome analysis.

Results

Only ten QTLs were found to be stable across two environments, and only one (qSG10Stable mapped on chromosome 10, and associated with lignin syringyl-to-guaiacyl ratio) was stable across all three environments. Compared to other QTLs, qSG10Stable explained a very high level of phenotypic variation (18.4-23.6%), perhaps suggesting that QTLs with strong effects may be more stably inherited across multiple environments. Screened candidate genes were associated with some transcription factor families, such as TALE, which play an important role in the secondary growth of plant cell walls and the regulation of wood formation.

Discussion

While QTLs such as qSG10Stable, found to be stable across three sites, appear to be comparatively uncommon, their identification is likely to be a key to practical QTL-based breeding. Further research involving clonally-replicated populations, deployed across multiple target planting sites, will be required to further elucidate QTL-by-environment interactions.

Genome‑wide association study and genomic prediction for growth traits in yellow-plumage chicken using genotyping-by-sequencing

Background

Growth traits are of great importance for poultry breeding and production and have been the topic of extensive investigation, with many quantitative trait loci (QTL) detected. However, due to their complex genetic background, few causative genes have been confirmed and the underlying molecular mechanisms remain unclear, thus limiting our understanding of QTL and their potential use for the genetic improvement of poultry. Therefore, deciphering the genetic architecture is a promising avenue for optimising genomic prediction strategies and exploiting genomic information for commercial breeding. The objectives of this study were to: (1) conduct a genome-wide association study to identify key genetic factors and explore the polygenicity of chicken growth traits; (2) investigate the efficiency of genomic prediction in broilers; and (3) evaluate genomic predictions that harness genomic features.

Results

We identified five significant QTL, including one on chromosome 4 with major effects and four on chromosomes 1, 2, 17, and 27 with minor effects, accounting for 14.5 to 34.1% and 0.2 to 2.6% of the genomic additive genetic variance, respectively, and 23.3 to 46.7% and 0.6 to 4.5% of the observed predictive accuracy of breeding values, respectively. Further analysis showed that the QTL with minor effects collectively had a considerable influence, reflecting the polygenicity of the genetic background. The accuracy of genomic best linear unbiased predictions (BLUP) was improved by 22.0 to 70.3% compared to that of the conventional pedigree-based BLUP model. The genomic feature BLUP model further improved the observed prediction accuracy by 13.8 to 15.2% compared to the genomic BLUP model.

Conclusions

A major QTL and four minor QTL were identified for growth traits; the remaining variance was due to QTL effects that were too small to be detected. The genomic BLUP and genomic feature BLUP models yielded considerably higher prediction accuracy compared to the pedigree-based BLUP model. This study revealed the polygenicity of growth traits in yellow-plumage chickens and demonstrated that the predictive ability can be greatly improved by using genomic information and related features.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00672-9.

In Search of Species-Specific SNPs in a Non-Model Animal (European Bison (Bison bonasus))-Comparison of De Novo and Reference-Based Integrated Pipeline of STACKS Using Genotyping-by-Sequencing (GBS) Data

The European bison is a non-model organism; thus, most of its genetic and genomic analyses have been performed using cattle-specific resources, such as BovineSNP50 BeadChip or Illumina Bovine 800 K HD Bead Chip. The problem with non-specific tools is the potential loss of evolutionary diversified information (ascertainment bias) and species-specific markers. Here, we have used a genotyping-by-sequencing (GBS) approach for genotyping 256 samples from the European bison population in Bialowieza Forest (Poland) and performed an analysis using two integrated pipelines of the STACKS software: one is de novo (without reference genome) and the other is a reference pipeline (with reference genome). Moreover, we used a reference pipeline with two different genomes, i.e., Bos taurus and European bison. Genotyping by sequencing (GBS) is a useful tool for SNP genotyping in non-model organisms due to its cost effectiveness. Our results support GBS with a reference pipeline without PCR duplicates as a powerful approach for studying the population structure and genotyping data of non-model organisms. We found more polymorphic markers in the reference pipeline in comparison to the de novo pipeline. The decreased number of SNPs from the de novo pipeline could be due to the extremely low level of heterozygosity in European bison. It has been confirmed that all the de novo/Bos taurus and Bos taurus reference pipeline obtained SNPs were unique and not included in 800 K BovineHD BeadChip.

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.

Genome-wide association study reveals the genetic determinism of growth traits in a Gushi-Anka F2 chicken population

Chicken growth traits are economically important, but the relevant genetic mechanisms have not yet been elucidated. Herein, we performed a genome-wide association study to identify the variants associated with growth traits. In total, 860 chickens from a Gushi-Anka F₂ resource population were phenotyped for 68 growth and carcass traits, and 768 samples were genotyped based on the genotyping-by-sequencing (GBS) method. Finally, 734 chickens and 321,314 SNPs remained after quality control and removal of the sex chromosomes, and these data were used to carry out a GWAS analysis. A total of 470 significant single-nucleotide polymorphisms (SNPs) for 43 of the 68 traits were detected and mapped on chromosomes (Chr) 1-6, -9, -10, -16, -18, -23, and -27. Of these, the significant SNPs in Chr1, -4, and -27 were found to be associated with more than 10 traits. Multiple traits shared significant SNPs, indicating that the same mutation in the region might have a large effect on multiple growth or carcass traits. Haplotype analysis revealed that SNPs within the candidate region of Chr1 presented a mosaic pattern. The significant SNPs and pathway enrichment analysis revealed that the MLNR, MED4, CAB39L, LDB2, and IGF2BP1 genes could be putative candidate genes for growth and carcass traits. The findings of this study improve our understanding of the genetic mechanisms regulating chicken growth and carcass traits and provide a theoretical basis for chicken breeding programs.

Genetic Dissection of Growth Traits in a Unique Chicken Advanced Intercross Line

The advanced intercross line (AIL) that is created by successive generations of pseudo-random mating after the F₂ generation is a valuable resource, especially in agricultural livestock and poultry species, because it improves the precision of quantitative trait loci (QTL) mapping compared with traditional association populations by introducing more recombination events. The growth traits of broilers have significant economic value in the chicken industry, and many QTLs affecting growth traits have been identified, especially on chromosomes 1, 4, and 27, albeit with large confidence intervals that potentially contain dozens of genes. To promote a better understanding of the underlying genetic architecture of growth trait differences, specifically body weight and bone development, in this study, we report a nine-generation AIL derived from two divergent outbred lines: High Quality chicken Line A (HQLA) and Huiyang Bearded (HB) chicken. We evaluate the genetic architecture of the F₀, F₂, F₈, and F₉ generations of AIL and demonstrate that the population of the F₉ generation sufficiently randomized the founder genomes and has the characteristics of rapid linkage disequilibrium decay, limited allele frequency decline, and abundant nucleotide diversity. This AIL yielded a much narrower QTL than the F₂ generations, especially the QTL on chromosome 27, which was reduced to 120 Kb. An ancestral haplotype association analysis showed that most of the dominant haplotypes are inherited from HQLA but with fluctuation of the effects between them. We highlight the important role of four candidate genes (PHOSPHO1, IGF2BP1, ZNF652, and GIP) in bone growth. We also retrieved a missing QTL from AIL on chromosome 4 by identifying the founder selection signatures, which are explained by the loss of association power that results from rare alleles. Our study provides a reasonable resource for detecting quantitative trait genes and tracking ancestor history and will facilitate our understanding of the genetic mechanisms underlying chicken bone growth.

DepthFinder: a tool to determine the optimal read depth for reduced-representation sequencing

MOTIVATION

Identification of DNA sequence variations such as single nucleotide polymorphisms (SNPs) is a fundamental step toward genetic studies. Reduced-representation sequencing methods have been developed as alternatives to whole genome sequencing to reduce costs and enable the analysis of many more individual. Amongst these methods, restriction site associated sequencing (RSAS) methodologies have been widely used for rapid and cost-effective discovery of SNPs and for high-throughput genotyping in a wide range of species. Despite the extensive improvements of the RSAS methods in the last decade, the estimation of the number of reads (i.e. read depth) required per sample for an efficient and effective genotyping remains mostly based on trial and error.

RESULTS

Herein we describe a bioinformatics tool, DepthFinder, designed to estimate the required read counts for RSAS methods. To illustrate its performance, we estimated required read counts in six different species (human, cattle, spruce budworm, salmon, barley and soybean) that cover a range of different biological (genome size, level of genome complexity, level of DNA methylation and ploidy) and technical (library preparation protocol and sequencing platform) factors. To assess the prediction accuracy of DepthFinder, we compared DepthFinder-derived results with independent datasets obtained from an RSAS experiment. This analysis yielded estimated accuracies of nearly 94%. Moreover, we present DepthFinder as a powerful tool to predict the most effective size selection interval in RSAS work. We conclude that DepthFinder constitutes an efficient, reliable and useful tool for a broad array of users in different research communities.

AVAILABILITY AND IMPLEMENTATION

https://bitbucket.org/jerlar73/DepthFinder.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Multiple ancestral haplotypes harboring regulatory mutations cumulatively contribute to a QTL affecting chicken growth traits

In depth studies of quantitative trait loci (QTL) can provide insights to the genetic architectures of complex traits. A major effect QTL at the distal end of chicken chromosome 1 has been associated with growth traits in multiple populations. This locus was fine-mapped in a fifteen-generation chicken advanced intercross population including 1119 birds and explored in further detail using 222 sequenced genomes from 10 high/low body weight chicken stocks. We detected this QTL that, in total, contributed 14.4% of the genetic variance for growth. Further, nine mosaic precise intervals (Kb level) which contain ancestral regulatory variants were fine-mapped and we chose one of them to demonstrate the key regulatory role in the duodenum. This is the first study to break down the detail genetic architectures for the well-known QTL in chicken and provides a good example of the fine-mapping of various of quantitative traits in any species.

Adapting Genotyping-by-Sequencing and Variant Calling for Heterogeneous Stock Rats

The heterogeneous stock (HS) is an outbred rat population derived from eight inbred rat strains. HS rats are ideally suited for genome wide association studies; however, only a few genotyping microarrays have ever been designed for rats and none of them are currently in production. To address the need for an efficient and cost effective method of genotyping HS rats, we have adapted genotype-by-sequencing (GBS) to obtain genotype information at large numbers of single nucleotide polymorphisms (SNPs). In this paper, we have outlined the laboratory and computational steps we took to optimize double digest genotype-by-sequencing (ddGBS) for use in rats. We evaluated multiple existing computational tools and explain the workflow we have used to call and impute over 3.7 million SNPs. We have also compared various rat genetic maps, which are necessary for imputation, including a recently developed map specific to the HS. Using our approach, we obtained concordance rates of 99% with data obtained using data from a genotyping array. The principles and computational pipeline that we describe could easily be adapted for use in other species for which reliable reference genome sets are available.

Genome-wide association study of bone mineral density trait among three pig breeds

Leg weakness (LW) issues are a great concern for pig breeding industry. And it also has a serious impact on animal welfare. To dissect the genetic architecture of limb-and-hoof firmness in commercial pigs, a genome-wide association study was conducted on bone mineral density (BMD) in three sow populations, including Duroc, Landrace and Yorkshire. The BMD data were obtained by ultrasound technology from 812 pigs (including Duroc 115, Landrace 243 and Yorkshire 454). In addition, all pigs were genotyped using genome-by-sequencing and a total of 224 162 single-nucleotide polymorphisms (SNPs) were obtained. After quality control, 218 141 SNPs were used for subsequent genome-wide association analysis. Nine significant associations were identified on chromosomes 3, 5, 6, 7, 9, 10, 12 and 18 that passed Bonferroni correction threshold of 0.05/(total SNP numbers). The most significant locus that associated with BMD (P value = 1.92e-14) was detected at approximately 41.7 Mb on SSC6 (SSC stands for Sus scrofa chromosome). CUL7, PTK7, SRF, VEGFA, RHEB, PRKAR1A and TPO that are located near the lead SNP of significant loci were highlighted as functionally plausible candidate genes for sow limb-and-hoof firmness. Moreover, we also applied a new method to measure the BMD data of pigs by ultrasound technology. The results provide an insight into the genetic architecture of LW and can also help to improve animal welfare in pigs.

High-Throughput Sequencing With the Preselection of Markers Is a Good Alternative to SNP Chips for Genomic Prediction in Broilers

The choice of a genetic marker genotyping platform is important for genomic prediction in livestock and poultry. High-throughput sequencing can produce more genetic markers, but the genotype quality is lower than that obtained with single nucleotide polymorphism (SNP) chips. The aim of this study was to compare the accuracy of genomic prediction between high-throughput sequencing and SNP chips in broilers. In this study, we developed a new SNP marker screening method, the pre-marker-selection (PMS) method, to determine whether an SNP marker can be used for genomic prediction. We also compared a method which preselection marker based results from genome-wide association studies (GWAS). With the two methods, we analysed body weight at the12^th week (BW) and feed conversion ratio (FCR) in a local broiler population. A total of 395 birds were selected from the F2 generation of the population, and 10X specific-locus amplified fragment sequencing (SLAF-seq) and the Illumina Chicken 60K SNP Beadchip were used for genotyping. The genomic best linear unbiased prediction method (GBLUP) was used to predict the genomic breeding values. The accuracy of genomic prediction was validated by the leave-one-out cross-validation method. Without SNP marker screening, the accuracies of the genomic estimated breeding value (GEBV) of BW and FCR were 0.509 and 0.249, respectively, when using SLAF-seq, and the accuracies were 0.516 and 0.232, respectively, when using the SNP chip. With SNP marker screening by the PMS method, the accuracies of GEBV of the two traits were 0.671 and 0.499, respectively, when using SLAF-seq, and 0.605 and 0.422, respectively, when using the SNP chip. Our SNP marker screening method led to an increase of prediction accuracy by 0.089-0.250. With SNP marker screening by the GWAS method, the accuracies of genomic prediction for the two traits were also improved, but the gains of accuracy were less than the gains with PMS method for all traits. The results from this study indicate that our PMS method can improve the accuracy of GEBV, and that more accurate genomic prediction can be obtained from an increased number of genomic markers when using high-throughput sequencing in local broiler populations. Due to its lower genotyping cost, high-throughput sequencing could be a good alternative to SNP chips for genomic prediction in breeding programmes of local broiler populations.

NanoGBS: A Miniaturized Procedure for GBS Library Preparation

High-throughput reduced-representation sequencing (RRS)-based genotyping methods, such as genotyping-by-sequencing (GBS), have provided attractive genotyping solutions in numerous species. Here, we present NanoGBS, a miniaturized and eco-friendly method for GBS library construction. Using acoustic droplet ejection (ADE) technology, NanoGBS libraries were constructed in tenfold smaller volumes compared to standard methods (StdGBS) and leading to a reduced use of plastics of up to 90%. A high-quality DNA library and SNP catalogue were obtained with extensive overlap (96%) in SNP loci and 100% agreement in genotype calls compared to the StdGBS dataset with a high level of accuracy (98.5%). A highly multiplexed pool of GBS libraries (768-plex) was sequenced on a single Ion Proton PI chip and yielded enough SNPs (~4K SNPs; 1.5 SNP per cM, on average) for many high-volume applications. Combining NanoGBS library preparation and increased multiplexing can dramatically reduce (72%) genotyping cost per sample. We believe that this approach will greatly facilitate the adoption of marker applications where extremely high throughputs are required and cost is still currently limiting.

Optimizing ddRADseq in Non-Model Species: A Case Study in Eucalyptus dunnii Maiden

Restriction site-associated DNA sequencing (RADseq) and its derived protocols, such as double digest RADseq (ddRADseq), offer a flexible and highly cost-effective strategy for efficient plant genome sampling. This has become one of the most popular genotyping approaches for breeding, conservation, and evolution studies in model and non-model plant species. However, universal protocols do not always adapt well to non-model species. Herein, this study reports the development of an optimized and detailed ddRADseq protocol in Eucalyptus dunnii, a non-model species, which combines different aspects of published methodologies. The initial protocol was established using only two samples by selecting the best combination of enzymes and through optimal size selection and simplifying lab procedures. Both single nucleotide polymorphisms (SNPs) and simple sequence repeats (SSRs) were determined with high accuracy after applying stringent bioinformatics settings and quality filters, with and without a reference genome. To scale it up to 24 samples, we added barcoded adapters. We also applied automatic size selection, and therefore obtained an optimal number of loci, the expected SNP locus density, and genome-wide distribution. Reliability and cross-sequencing platform compatibility were verified through dissimilarity coefficients of 0.05 between replicates. To our knowledge, this optimized ddRADseq protocol will allow users to go from the DNA sample to genotyping data in a highly accessible and reproducible way.

Invited review: Reproductive and genomic technologies to optimize breeding strategies for genetic progress in dairy cattle

Abstract. Dairy cattle breeders have exploited technological advances that have emerged in the past in regards to reproduction and genomics. The implementation of such technologies in routine breeding programs has permitted genetic gains in traditional milk production traits as well as, more recently, in low-heritability traits like health and fertility. As demand for dairy products increases, it is important for dairy breeders to optimize the use of available technologies and to consider the many emerging technologies that are currently being investigated in various fields. Here we review a number of technologies that have helped shape dairy breeding programs in the past and present, along with those potentially forthcoming. These tools have materialized in the areas of reproduction, genotyping and sequencing, genetic modification, and epigenetics. Although many of these technologies bring encouraging opportunities for genetic improvement of dairy cattle populations, their applications and benefits need to be weighed with their impacts on economics, genetic diversity, and society.