Body size is one of the main selection indices in chicken breeding. Although often investigated, knowledge of the underlying genetic mechanisms is incomplete. The aim of the current study was to identify genomic regions associated with body size differences between Asian Game and Asian Bantam type chickens. In this study, 94 and 107 chickens from 4 Asian Game and 5 Asian Bantam type breeds, respectively, were genotyped using the chicken 580K single nucleotide polymorphism (SNP) array. A genome-wide association study (GWAS) and principal component analyses (PCA) were performed to identify genomic regions associated with body size related-traits such as wing length, shank length, shank thickness, keel length, and body weight. Hierarchical clustering of genotype data showed a clear genetic difference between the investigated Asian Game and Asian Bantam chicken types. GWAS identified 16 genomic regions associated with wing length (2, FDR ≤ 0.018), shank thickness (6, FDR ≤ 0.008), keel length (5, FDR ≤ 0.023), and body weight (3, FDR ≤ 0.041). PCA showed that the first principal component (PC1) separated the 2 chicken types and significantly correlated with the measured body size related-traits (P ≤ 2.24e-40). SNPs contributing significantly to PC1 were subjected to a more detailed investigation. This analysis identified 11 regions potentially associated with differences in body size related-traits. A region on chromosome 4 (GGA4) (17.3-21.3 Mb) was detected in both analyses GWAS and PCA. This region harbors 60 genes. Among them are myotubularin 1 (MTM1) and secreted frizzled-related protein 2 (SFPR2) which can be considered as potential candidate genes for body size related-traits. Our results clearly show that the investigated Asian Game type chicken breeds are genetically different from the Asian Bantam breeds. A region on GGA4 between 17.3 and 21.3 Mb was identified which contributes to the phenotypic difference, though further validation of candidate genes is necessary.

Structural variants (SV) have gained increasing interest within the last years. However, calling SVs from array genotypes or short-read data is known to suffer from high false-positive rates and low specificity at the same time. In contrast, long-read technologies promise to derive accurate and sensitive SV callsets. We hereby present the first study that uses PacBio and Nanopore long-reads to derive quantitative estimates of the amount of SVs in chicken, based on four trios. We estimated the mean size of the reference genome affected by at least heterozygous SV calls to range from 0.2% for insertions to 0.7% for deletions. We further compared the results to a short-read based calling approach. This revealed more than 2/3 of short-read based initial SV calls not being backed by long-read based calls, while more than 50% of the long-read based calls would have been missed by the short-read approach.

Several PCR-based methods are known for sexing of chickens and other birds (Çakmak et al., 2017; Eiras et al., 2018; Gruszczyńska & Grzegrzółka, 2021; Morinha et al., 2012). While some methods for bird sexing are suitable for large-scale analyses (Chen et al., 2012; Clinton et al., 2016; He et al., 2019; Margulis & Danielli, 2019; Morinha et al., 2013; Rosenthal et al., 2010), research is still ongoing because most of these methods are costly and time consuming. Here we report a newly developed, easy to use competitive allele-specific PCR (KASP) assay that is suitable for large-scale sexing in chickens and other birds. The KASP assay is based on an A/G difference in exon 17 between the W- and Z-chromosomal variants of the conserved chromodomain helicase DNA binding protein 1 (CHD1) in exon 17 (Figure S1). Sex-specific primers were designed up- and downstream of this variant in CHD1 genes to amplify a product of 46 bp (Figure 1; Table S1, Figure S1). The amplicon overlaps with the PCR product for sex genotyping of the method of Fridolfsson and Ellegren (1999) (Figure S1). Furthermore, similar sequences were obtained from NCBI databases using blast (https://blast.ncbi.nlm.nih.gov/Blast.cgi) for duck, goose, quail and turkey and were aligned with the chicken sequence (Figure 1). In total, 734 chicken samples with known sex were analysed (Table S2). In addition, 55 samples of other species of the orders Galliformes and Anseriformes were analysed (Table S2). If the sex of non-chicken samples was unknown it was verified by multiplex PCR modified from Fridolfsson and Ellegren (1999) (Table S1, Figure S1). Samples were mainly taken from an extensive DNA collection, which was set up within the framework of the projects AVIANDIV (Lyimo et al., 2014) and SYNBREED (www.synbreed.tum.de). Each KASP reaction contained 20–50 ng of template DNA, KASP v. 4.0 2× Master mix standard ROX and the KASP-by-Design assay mix (LGC Genomics). The standard KASP thermal cycling conditions according to LGC protocols were performed in an Eppendorf Mastercycler (Eppendorf). After amplification, microplates were analysed with FLUOstar Omega (BMG Labtech) using excitation and emission values of 485/520 nm for the FAM-labelled-FRET cassette, 530/560 nm for the HEX-labelled-FRET cassette and 584/620 nm for the ROX standard. All chickens, ducks, geese, quails and turkeys were correctly assigned to their sex using the newly developed KASP assay (Table S2). This newly developed KASP assay is well suited to chicken, duck, goose, quail and turkey for efficient sex determination on a larger scale. The research leading to these results has received funding from the European Union's Horizon 2020 Research and Innovation Programme under the grant agreement no. 677353 IMAGE. The authors thank Alina Kirchhoff, Kim Köhler, Christin Moelders and Katrin Zimmermann for technical assistance. Open access funding was enabled and organised by ProjektDEAL. Open access funding enabled and organized by ProjektDEAL. The authors declare no potential conflicts of interest. The data supporting the findings of the present study are available from the corresponding author upon reasonable request. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Skeletal disorders, including fractures and osteoporosis, in laying hens cause major welfare and economic problems. Although genetics have been shown to play a key role in bone integrity, little is yet known about the underlying genetic architecture of the traits. This study aimed to identify genes associated with bone breaking strength and bone mineral density of the tibiotarsus and the humerus in laying hens. Potentially informative single nucleotide polymorphisms (SNP) were identified using Random Forests classification. We then searched for genes known to be related to bone stability in close proximity to the SNPs and identified 16 potential candidates. Some of them had human orthologues. Based on our findings, we can support the assumption that multiple genes determine bone strength, with each of them having a rather small effect, as illustrated by our SNP effect estimates. Furthermore, the enrichment analysis showed that some of these candidates are involved in metabolic pathways critical for bone integrity. In conclusion, the identified candidates represent genes that may play a role in the bone integrity of chickens. Although further studies are needed to determine causality, the genes reported here are promising in terms of alleviating bone disorders in laying hens.

BACKGROUND:Migration of a population from its founder population is expected to cause a reduction of its genetic diversity and facilitates differentiation between the population and its founder population, as predicted by the theory of genetic isolation by distance. Consistent with that theory, a model of expansion from a single founder predicts that patterns of genetic diversity in populations can be explained well by their geographic expansion from their founders, which is correlated with genetic differentiation.METHODS:To investigate this in chicken, we estimated the relationship between the genetic diversity of 160 domesticated chicken populations and their genetic distances to wild chicken populations.RESULTS:Our results show a strong inverse relationship, i.e. 88.6% of the variation in the overall genetic diversity of domesticated chicken populations was explained by their genetic distance to the wild populations. We also investigated whether the patterns of genetic diversity of different types of single nucleotide polymorphisms (SNPs) and genes are similar to that of the overall genome. Among the SNP classes, the non-synonymous SNPs deviated most from the overall genome. However, genetic distance to the wild chicken still explained more variation in domesticated chicken diversity across all SNP classes, which ranged from 83.0 to 89.3%.CONCLUSIONS:Genetic distance between domesticated chicken populations and their wild relatives can predict the genetic diversity of the domesticated populations. On the one hand, genes with little genetic variation across populations, regardless of the genetic distance to the wild population, are associated with major functions such as brain development. Changes in such genes may be detrimental to the species. On the other hand, genetic diversity seems to change at a faster rate within genes that are associated with e.g. protein transport and protein and lipid metabolic processes. In general, such genes may be flexible to changes according to the populations' needs. These results contribute to the knowledge of the evolutionary patterns of different functional genomic regions in the chicken.

Single nucleotide polymorphisms (SNPs), genotyped with arrays, have become a widely used marker type in population genetic analyses over the last 10 years. However, compared to whole genome re-sequencing data, arrays are known to lack a substantial proportion of globally rare variants and tend to be biased towards variants present in populations involved in the development process of the respective array. This affects population genetic estimators and is known as SNP ascertainment bias. We investigated factors contributing to ascertainment bias in array development by redesigning the Axiom™ Genome-Wide Chicken Array in silico and evaluating changes in allele frequency spectra and heterozygosity estimates in a stepwise manner. A sequential reduction of rare alleles during the development process was shown. This was mainly caused by the identification of SNPs in a limited set of populations and a within-population selection of common SNPs when aiming for equidistant spacing. These effects were shown to be less severe with a larger discovery panel. Additionally, a generally massive overestimation of expected heterozygosity for the ascertained SNP sets was shown. This overestimation was 24% higher for populations involved in the discovery process than not involved populations in case of the original array. The same was observed after the SNP discovery step in the redesign. However, an unequal contribution of populations during the SNP selection can mask this effect but also adds uncertainty. Finally, we make suggestions for the design of specialized arrays for large scale projects where whole genome re-sequencing techniques are still too expensive.

The high laying performance of today’s laying hens places enormous demands on their mineral metabolism. While up-to-date data are rare, the present study aimed to describe blood parameters associated with egg laying and bone metabolism during the pre-laying period, in the course of the laying period and the daily egg laying cycle. Ten to 15 laying hens of two high-performing, phylogenetically divergent lines (BLA: brown-egg layer; WLA: white-egg layer), kept in single cages were blood sampled at 17, 25, 29, 49, and 69 weeks of age. Sampling was made at 6 a.m., 10 a.m., 2 p.m. and, with the exception of week 17, 6 p.m. Blood samples were analyzed for concentrations of total and ionized calcium, inorganic phosphate (PO4), markers of bone formation (osteocalcin) and resorption [carboxyterminal crosslinked telopeptide of type I collagen (CTX-I)], 25-hydroxycholecalciferol (25(OH)D 3 ) and estradiol-17β. In the pre-laying period (17 week), the estradiol-17β level calculated for WLA was more than twice as high as the level calculated for BLA, while no significant difference could be observed in the laying period (25 to 69 weeks). BLA hens had significantly higher total calcium concentrations at 49 weeks of age as well as up to twice as high levels of osteocalcin and 25(OH)D 3 than WLA at any time of the day from 25 to 69 weeks of age. While osteocalcin, CTX-I and 25(OH)D 3 concentrations were significantly higher before the onset of lay, total calcium and estradiol-17β levels significantly increased from 17 to 69 weeks of age. In contrast, PO4 values varied only slightly during the experimental period and ionized calcium was highest at 17 and 49 weeks of age and lowest around peak production (29 week). In the course of the daily egg laying cycle blood concentrations clearly reflected the stage of egg formation. Our results provide up-to-date data of bone- and egg laying-associated blood parameters of two contemporary purebred layer lines over the course of the pre- and egg-laying period and the daily egg laying cycle. Differences between brown- and white-egg layers raise questions, whether phylogenetic background determines their efficiency to cope with high calcium demands relating to egg production.

Abstract Background Population genetic studies based on genotyped single nucleotide polymorphisms (SNPs) are influenced by a non-random selection of the SNPs included in the used genotyping arrays. The resulting bias in the estimation of allele frequency spectra and population genetics parameters like heterozygosity and genetic distances relative to whole genome sequencing (WGS) data is known as SNP ascertainment bias. Full correction for this bias requires detailed knowledge of the array design process, which is often not available in practice. This study suggests an alternative approach to mitigate ascertainment bias of a large set of genotyped individuals by using information of a small set of sequenced individuals via imputation without the need for prior knowledge on the array design. Results The strategy was first tested by simulating additional ascertainment bias with a set of 1566 chickens from 74 populations that were genotyped for the positions of the Affymetrix Axiom™ 580 k Genome-Wide Chicken Array. Imputation accuracy was shown to be consistently higher for populations used for SNP discovery during the simulated array design process. Reference sets of at least one individual per population in the study set led to a strong correction of ascertainment bias for estimates of expected and observed heterozygosity, Wright’s Fixation Index and Nei’s Standard Genetic Distance. In contrast, unbalanced reference sets (overrepresentation of populations compared to the study set) introduced a new bias towards the reference populations. Finally, the array genotypes were imputed to WGS by utilization of reference sets of 74 individuals (one per population) to 98 individuals (additional commercial chickens) and compared with a mixture of individually and pooled sequenced populations. The imputation reduced the slope between heterozygosity estimates of array data and WGS data from 1.94 to 1.26 when using the smaller balanced reference panel and to 1.44 when using the larger but unbalanced reference panel. This generally supported the results from simulation but was less favorable, advocating for a larger reference panel when imputing to WGS. Conclusions The results highlight the potential of using imputation for mitigation of SNP ascertainment bias but also underline the need for unbiased reference sets.

The authors wish to make the following corrections to this paper [...]

The repository contains the raw SNP data in vcf format for the publication "How Array Design Creates SNP Ascertainment Bias". Note that the variants are not filtered at this timepoint. Samples starting with pl_ are pooled sequences of ~10 individuals while samples starting with i_ were individually sequenced. Please find detailed information about samples, raw sequencing data and SNP calling pipeline in the linked preprint (https://doi.org/10.1101/833541)/ publication (https://doi.org/10.1371/journal.pone.0245178). In case you need additional information, please contact johannes.geibel@uni-goettingen.de

The authors wish to make the following corrections to this paper [...].

In modern laying hybrids, calcium (Ca) homeostasis is immensely challenged by daily eggshell calcification. However, excessive mobilization of Ca from bones may lead to osteoporosis, which then manifests in a high incidence of poor bone quality. The aim of this study was to characterize the hens’ adaptation response to an alternating dietary Ca restriction. The animal model consisted of four purebred layer lines, differing in laying performance (high vs. moderately performing lines) and phylogenetic origin (white- vs. brown-egg lines). According to the resource allocation theory, hens selected for high egg production were assumed to show a different response pattern to cope with this nutritive challenge compared to moderately performing lines. Data collected included egg number, egg quality traits, body weight and bone characteristics. The Ca depletion led to a temporary drop in egg production and shell quality and a loss of bone stability due to Ca mobilization. The white-egg lines response was more pronounced, whereas the brown-egg lines were less sensitive towards reduced Ca supply. Our study shows that the hens’ responsiveness to coping with a nutritive Ca depletion is not ultimately linked to genetic selection for increased egg production but rather to phylogenetic origin.

Impaired animal welfare due to skeletal disorders is likely one of the greatest issues currently facing the egg production industry. Reduced bone stability in laying hens is frequently attributed to long-term selection for increased egg production. The present study sought to analyse the relationship between bone stability traits and egg production. The study comprised four purebred layer lines, differing in their phylogenetic origin and performance level, providing extended insight into the phenotypic variability in bone characteristics in laying hens. Data collection included basic production parameters, bone morphometry, bone mineral density (BMD) and bone breaking strength (BBS) of the tibiotarsus and humerus. Using a multifactorial model and regression analyses, BMD proved to be of outstanding importance for bone stability. Only for the tibiotarsus were morphometric parameters and the bone weight associated with BBS. Within the chicken lines, no effect of total eggshell production on BBS or BMD could be detected, suggesting that a high egg yield itself is not necessarily a risk for poor bone health. Considering the complexity of osteoporosis, the estimated genetic parameters confirmed the importance of genetics in addressing the challenge of improving bone strength in layers.

We carried out whole genome resequencing of 127 chicken including red jungle fowl and multiple populations of commercial broilers and layers to perform a systematic screening of adaptive changes in modern chicken (Gallus gallus domesticus). We uncovered >21 million high quality SNPs of which 34% are newly detected variants. This panel comprises >115,000 predicted amino-acid altering substitutions as well as 1,100 SNPs predicted to be stop-gain or -loss, several of which reach high frequencies. Signatures of selection were investigated both through analyses of fixation and differentiation to reveal selective sweeps that may have had prominent roles during domestication and breed development. Contrasting wild and domestic chicken we confirmed selection at the BCO2 and TSHR loci and identified 34 putative sweeps co-localized with ALX1, KITLG, EPGR, IGF1, DLK1, JPT2, CRAMP1, and GLI3, among others. Analysis of enrichment between groups of wild vs. commercials and broilers vs. layers revealed a further panel of candidate genes including CORIN, SKIV2L2 implicated in pigmentation and LEPR, MEGF10 and SPEF2, suggestive of production-oriented selection. SNPs with marked allele frequency differences between wild and domestic chicken showed a highly significant deficiency in the proportion of amino-acid altering mutations (P<2.5×10−6). The results contribute to the understanding of major genetic changes that took place during the evolution of modern chickens and in poultry breeding.

In our previous research, we identified a QTL with an interval of 3.4 Mb for growth on chicken chromosome (GGA) 4 in an advanced intercross population of an initial cross between the New Hampshire inbred line (NHI) and the White Leghorn inbred line (WL77). In the current study, an association analysis was performed in a population of purebred white layers (WLA) with White Leghorn origin. Genotypic data of 130 SNPs within the previously identified 3.4-Mb region were obtained using a 60K SNP chip. In total, 24 significant SNPs (LOD ≥ 4.44) on GGA4 were detected for daily weigh gain from 8 to 14 weeks and two SNPs (LOD ≥ 4.80) for body weight at 14 weeks. The QTL interval was reduced by 1.9 Mb to an interval of 1.5 Mb (74.6-76.1 Mb) that harbors 15 genes. Furthermore, to identify additional loci for chicken growth, a genome-wide association study (GWAS) was carried out in a WLA population. The GWAS identified an additional QTL on GGA6 for body weight at six weeks (19.8-21.2 Mb). Our findings showed that by using a WLA population we were able to further reduce the QTL confidence interval previously detected using a NHI × WL77 advanced intercross population.

BACKGROUND:Single nucleotide polymorphism (SNP) panels have been widely used to study genomic variations within and between populations. Methods of SNP discovery have been a matter of debate for their potential of introducing ascertainment bias, and genetic diversity results obtained from the SNP genotype data can be misleading. We used a total of 42 chicken populations where both individual genotyped array data and pool whole genome resequencing (WGS) data were available. We compared allele frequency distributions and genetic diversity measures (expected heterozygosity (H e ), fixation index (F ST ) values, genetic distances and principal components analysis (PCA)) between the two data types. With the array data, we applied different filtering options (SNPs polymorphic in samples of two Gallus gallus wild populations, linkage disequilibrium (LD) based pruning and minor allele frequency (MAF) filtering, and combinations thereof) to assess their potential to mitigate the ascertainment bias. RESULTS:Rare SNPs were underrepresented in the array data. Array data consistently overestimated H e compared to WGS data, however, with a similar ranking of the breeds, as demonstrated by Spearman's rank correlations ranging between 0.956 and 0.985. LD based pruning resulted in a reduced overestimation of H e compared to the other filters and slightly improved the relationship with the WGS results. The raw array data and those with polymorphic SNPs in the wild samples underestimated pairwise F ST values between breeds which had low F ST (<0.15) in the WGS, and overestimated this parameter for high WGS F ST (>0.15). LD based pruned data underestimated F ST in a consistent manner. The genetic distance matrix from LD pruned data was more closely related to that of WGS than the other array versions. PCA was rather robust in all array versions, since the population structure on the PCA plot was generally well captured in comparison to the WGS data. CONCLUSIONS:Among the tested filtering strategies, LD based pruning was found to account for the effects of ascertainment bias in the relatively best way, producing results which are most comparable to those obtained from WGS data and therefore is recommended for practical use.