A high-density SNP panel reveals extensive diversity, frequent recombination and multiple recombination hotspots within the chicken major histocompatibility complex B region between BG2 and CD1A1

Effective population sizes and adaptive genetic variation in a captive bird population

Captive populations are considered a key component of ex situ conservation programs. Research on multiple taxa has shown the differential success of maintaining demographic versus genetic stability and viability in captive populations. In typical captive populations, usually founded by few or related individuals, genetic diversity can be lost and inbreeding can accumulate rapidly, calling into question their ultimate utility for release into the wild. Furthermore, domestication selection for survival in captive conditions is another concern. Therefore, it is crucial to understand the dynamics of population sizes, particularly the effective population size, and genetic diversity at non-neutral and adaptive loci in captive populations. In this study, we assessed effective population sizes and genetic variation at both neutral microsatellite markers, as well as SNP variants from the MHC-B locus of a captive Red Junglefowl population. This population represents a rare instance of a population with a well-documented history in captivity, following a realistic scenario of chain-of-custody, unlike many captive lab populations. Our analyses, which included 27 individuals comprising the entirety of one captive population show very low neutral and adaptive genetic variation, as well as low effective sizes, which correspond with the known demographic history. Finally, our study also shows the divergent impacts of small effective size and inbreeding in captive populations on microsatellite versus adaptive genetic variation in the MHC-B locus. Our study provides insights into the difficulties of maintaining adaptive genetic variation in small captive populations.

Genomic Prediction of Complex Phenotypes Using Genic Similarity Based Relatedness Matrix

In the last years, a series of methods for genomic prediction (GP) have been established, and the advantages of GP over pedigree best linear unbiased prediction (BLUP) have been reported. However, the majority of previously proposed GP models are purely based on mathematical considerations while seldom take the abundant biological knowledge into account. Prediction ability of those models largely depends on the consistency between the statistical assumptions and the underlying genetic architectures of traits of interest. In this study, gene annotation information was incorporated into GP models by constructing haplotypes with SNPs mapped to genic regions. Haplotype allele similarity between pairs of individuals was measured through different approaches at single gene level and then converted into whole genome level, which was then treated as a special kernel and used in kernel based GP models. Results shown that the gene annotation guided methods gave higher or at least comparable predictive ability in some traits, especially in the Arabidopsis dataset and the rice breeding population. Compared to SNP models and haplotype models without gene annotation, the gene annotation based models improved the predictive ability by 0.56~26.67% in the Arabidopsis and 1.62~16.53% in the rice breeding population, respectively. However, incorporating gene annotation slightly improved the predictive ability for several traits but did not show any extra gain for the rest traits in a chicken population. In conclusion, integrating gene annotation into GP models could be beneficial for some traits, species, and populations compared to SNP models and haplotype models without gene annotation. However, more studies are yet to be conducted to implicitly investigate the characteristics of these gene annotation guided models.

Variation in recombination frequency and distribution across eukaryotes: patterns and processes

Recombination, the exchange of DNA between maternal and paternal chromosomes during meiosis, is an essential feature of sexual reproduction in nearly all multicellular organisms. While the role of recombination in the evolution of sex has received theoretical and empirical attention, less is known about how recombination rate itself evolves and what influence this has on evolutionary processes within sexually reproducing organisms. Here, we explore the patterns of, and processes governing recombination in eukaryotes. We summarize patterns of variation, integrating current knowledge with an analysis of linkage map data in 353 organisms. We then discuss proximate and ultimate processes governing recombination rate variation and consider how these influence evolutionary processes. Genome-wide recombination rates (cM/Mb) can vary more than tenfold across eukaryotes, and there is large variation in the distribution of recombination events across closely related taxa, populations and individuals. We discuss how variation in rate and distribution relates to genome architecture, genetic and epigenetic mechanisms, sex, environmental perturbations and variable selective pressures. There has been great progress in determining the molecular mechanisms governing recombination, and with the continued development of new modelling and empirical approaches, there is now also great opportunity to further our understanding of how and why recombination rate varies.This article is part of the themed issue 'Evolutionary causes and consequences of recombination rate variation in sexual organisms'.

MHC-B variability within the Finnish Landrace chicken conservation program

The major histocompatibility complex (MHC) is a cluster of genes involved with immune responses. The chicken MHC has been shown to influence resistance to viruses, bacteria, and infections from both internal and external parasites. The highly variable chicken MHC haplotypes were initially identified by the use of haplotype-specific serological reagents. A novel SNP-based panel encompassing 210,000 bp of the MHC-B locus was developed to allow fine scale genetic analyses including rapid identification of novel haplotypes for which serological reagents are not available. The Finnish Landrace breed of chickens traces its origins to almost 1,000 years ago, with multiple lineages maintained as small populations in isolated villages. The breed is well adapted to the cooler Finnish climate and is considered to be an infrequent egg layer. Conservation efforts to protect this endangered breed were initiated by a hobby breeder in the 1960s. An official conservation program was established in 1998 and now 12 different populations are currently maintained by a network of volunteer hobbyist breeders. Variation in the MHC-B region in these populations was examined using a panel of 90 selected SNP. A total of 195 samples from 12 distinct populations (average of 15 individuals sampled per population) were genotyped with the 90 SNP panel specific for the MHC-B region, spanning 210,000 bp. There were 36 haplotypes found, 16 of which are a subset of 78 that had been previously identified in either commercially utilized or heritage breeds from North America with the remaining 20 haplotypes being novel. The average number of MHC-B haplotypes found within each Finnish Landrace population was 5.9, and ranged from one to 13. While haplotypes common to multiple populations were found, population-specific haplotypes were also identified. This study shows that substantial MHC-B region diversity exists in the Finnish Landrace breed and exemplifies the significance tied to conserving multiple populations of rare breeds.

Generalists and Specialists: A New View of How MHC Class I Molecules Fight Infectious Pathogens

In comparison with the major histocompatibility complexes (MHCs) of typical mammals, the chicken MHC is simple and compact with a single dominantly expressed class I molecule that can determine the immune response. In addition to providing useful information for the poultry industry and allowing insights into the evolution of the adaptive immune system, the simplicity of the chicken MHC has allowed the discovery of phenomena that are more difficult to discern in the more complicated mammalian systems. This review discusses the new concept that poorly expressed promiscuous class I alleles act as generalists to protect against a wide variety of infectious pathogens, while highly expressed fastidious class I alleles can act as specialists to protect against new and dangerous pathogens.

A broad overview of classical MHC I expression and bound peptides reveals an inverse correlation between repertoire breadth and cell-surface expression in some chicken and human alleles.

Several chicken class I alleles with wide peptide-binding repertoires (promiscuity) are associated with resistance to a variety of common diseases.

Conversely, a narrow peptide-binding repertoire (fastidiousness) in some human HLA-B alleles is associated with resistance to HIV progression.

Cell-surface expression of some classical class I alleles depends on the regulation of translocation to the cell surface rather than of transcription or translation. MHC translocation is influenced by peptide translocation in chickens and by tapasin interaction in humans.

Genomic regions associated with host response to porcine reproductive and respiratory syndrome vaccination and co-infection in nursery pigs

BACKGROUND

The WUR1000125 (WUR) single nucleotide polymorphism (SNP) can be used as a genetic marker for host response to porcine reproductive and respiratory syndrome (PRRS), PRRS vaccination, and co-infection with porcine circovirus type 2b (PCV2b). Objectives of this study were to identify genomic regions other than WUR associated with host response to PRRS vaccination and PRRSV/PCV2b co-infection and regions with a different effect on host response to co-infection, depending on previous vaccination for PRRS.

METHODS

Commercial crossbred nursery pigs were pre-selected for WUR genotype (n = 171 AA and 198 AB pigs) where B is the dominant and favorable allele. Half of the pigs were vaccinated for PRRS and 4 weeks later, all pigs were co-infected with PRRS virus and PCV2b. Average daily gain (ADG) and viral load (VL) were quantified post vaccination (Post Vx) and post co-infection (Post Co-X). Single-SNP genome-wide association analyses were then conducted to identify genomic regions associated with response to vaccination and co-infection.

RESULTS

Multiple SNPs near the major histocompatibility complex were significantly associated with PCV2b VL (-log ₁₀ P ≥ 5.5), regardless of prior vaccination for PRRS. Several SNPs were also significantly associated with ADG Post Vx and Post Co-X. SNPs with a different effect on ADG, depending on prior vaccination for PRRS, were identified Post Vx (-log ₁₀ P = 5.6) and Post Co-X (-log ₁₀ P = 5.5). No SNPs were significantly associated with vaccination VL (-log₁₀ P ≤ 4.7) or PRRS VL (-log₁₀ P ≤ 4.3). Genes near SNPs associated with vaccination VL, PRRS VL, and PCV2b VL were enriched (P ≤ 0.01) for immune-related pathways and genes near SNPs associated with ADG were enriched for metabolism pathways (P ≤ 0.04). SNPs associated with vaccination VL, PRRS VL, and PCV2b VL showed overrepresentation of health QTL identified in previous studies and SNPs associated with ADG Post Vx of Non-Vx pigs showed overrepresentation of growth QTL.

CONCLUSIONS

Multiple genomic regions were associated with PCV2b VL and ADG Post Vx and Post Co-X. Different SNPs were associated with ADG, depending on previous vaccination for PRRS. Results of functional annotation analyses and novel approaches of using previously-reported QTL support the identified regions.

Genomic variability in Mexican chicken population using copy number variants

BACKGROUND

Copy number variations are genome polymorphism that influence phenotypic variation and are an important source of genetic variation in populations. The aim of this study was to investigate genetic variability in the Mexican Creole chicken population using CNVs.

RESULTS

The Hidden Markov Model of the PennCNV software detected a total of 1924 CNVs in the genome of the 256 samples processed with Axiom® Genome-Wide Chicken Genotyping Array (Affymetrix). The mapped CNVs comprised 1538 gains and 386 losses, resulting at population level in 1216 CNV regions (CNVRs), of which 959 gains, 226 losses and 31 complex (i.e. containing both losses and gains). The CNVRs covered a total of 47 Mb of the whole genome sequence length, corresponding to 5.12% of the chicken galGal4 autosome assembly.

CONCLUSIONS

This study allowed a deep insight into the structural variation in the genome of unselected Mexican chicken population, which up to now has not been genetically characterized. The genomic study disclosed that the population, even if presenting extreme morphological variation, cannot be organized in differentiated genetic subpopulations. Finally this study provides a chicken CNV map based on the 600 K SNP chip array jointly with a genome-wide gene copy number estimates in a native unselected for more than 500 years chicken population.

What chickens might tell us about the MHC class II system

Almost all knowledge about the structure and function of MHC class II molecules outside of mammals comes from work with chickens. Most of the genes implicated in the class II system are present in chickens, so it is likely that the machinery of antigen processing and peptide-loading is similar to mammals. However, there is only one isotype (lineage) of classical class II genes, with one monomorphic DR-like BLA gene and two polymorphic BLB genes, located near one DMA and two DMB genes. The DMB2 and BLB2 genes are widely expressed at high levels, whereas the DMB1 and BLB1 genes are only expressed at highest levels in spleen and intestine, suggesting the possibility of two class II systems in chickens.

Prediction of genomic breeding values for growth, carcass and meat quality traits in a multi-breed sheep population using a HD SNP chip

Background

New Zealand has some unique Terminal Sire composite sheep breeds, which were developed in the last three decades to meet commercial needs. These composite breeds were developed based on crossing various Terminal Sire and Maternal breeds and, therefore, present high genetic diversity compared to other sheep breeds. Their breeding programs are focused on improving carcass and meat quality traits. There is an interest from the industry to implement genomic selection in this population to increase the rates of genetic gain. Therefore, the main objectives of this study were to determine the accuracy of predicted genomic breeding values for various growth, carcass and meat quality traits using a HD SNP chip and to evaluate alternative genomic relationship matrices, validation designs and genomic prediction scenarios. A large multi-breed population (n = 14,845) was genotyped with the HD SNP chip (600 K) and phenotypes were collected for a variety of traits.

Results

The average observed accuracies (± SD) for traits measured in the live animal, carcass, and, meat quality traits ranged from 0.18 ± 0.07 to 0.33 ± 0.10, 0.28 ± 0.09 to 0.55 ± 0.05 and 0.21 ± 0.07 to 0.36 ± 0.08, respectively, depending on the scenario/method used in the genomic predictions. When accounting for population stratification by adjusting for 2, 4 or 6 principal components (PCs) the observed accuracies of molecular breeding values (mBVs) decreased or kept constant for all traits. The mBVs observed accuracies when fitting both G and A matrices were similar to fitting only G matrix. The lowest accuracies were observed for k-means cross-validation and forward validation performed within each k-means cluster.

Conclusions

The accuracies observed in this study support the feasibility of genomic selection for growth, carcass and meat quality traits in New Zealand Terminal Sire breeds using the Ovine HD SNP chip. There was a clear advantage on using a mixed training population instead of performing analyzes per genomic clusters. In order to perform genomic predictions per breed group, genotyping more animals is recommended to increase the size of the training population within each group and the genetic relationship between training and validation populations. The different scenarios evaluated in this study will help geneticists and breeders to make wiser decisions in their breeding programs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-017-0476-8) contains supplementary material, which is available to authorized users.

A New Chicken Genome Assembly Provides Insight into Avian Genome Structure

The importance of the Gallus gallus (chicken) as a model organism and agricultural animal merits a continuation of sequence assembly improvement efforts. We present a new version of the chicken genome assembly (Gallus_gallus-5.0; GCA_000002315.3), built from combined long single molecule sequencing technology, finished BACs, and improved physical maps. In overall assembled bases, we see a gain of 183 Mb, including 16.4 Mb in placed chromosomes with a corresponding gain in the percentage of intact repeat elements characterized. Of the 1.21 Gb genome, we include three previously missing autosomes, GGA30, 31, and 33, and improve sequence contig length 10-fold over the previous Gallus_gallus-4.0. Despite the significant base representation improvements made, 138 Mb of sequence is not yet located to chromosomes. When annotated for gene content, Gallus_gallus-5.0 shows an increase of 4679 annotated genes (2768 noncoding and 1911 protein-coding) over those in Gallus_gallus-4.0. We also revisited the question of what genes are missing in the avian lineage, as assessed by the highest quality avian genome assembly to date, and found that a large fraction of the original set of missing genes are still absent in sequenced bird species. Finally, our new data support a detailed map of MHC-B, encompassing two segments: one with a highly stable gene copy number and another in which the gene copy number is highly variable. The chicken model has been a critical resource for many other fields of study, and this new reference assembly will substantially further these efforts.

Genetic variation of major histocompatibility complex (MHC) in wild Red Junglefowl (Gallus gallus)

The major histocompatibility complex (MHC) is a multi-family gene cluster that encodes proteins with immuno-responsive function. While studies of MHC in domesticated poultry are relatively common, very little is known about this highly polymorphic locus in wild Red Junglefowl (Gallus gallus), the natural progenitor of domestic chickens. We investigated the diversity of MHC within and among four wild Red Junglefowl populations across diversified natural habitats in South Central Vietnam. Based on a SNP panel of 84 sites spanning 210 Kb of the MHC-B locus, we identified 310 unique haplotypes in 398 chromosomes. None of these haplotypes have been described before and we did not observe any of the wild Red Junglefowl haplotypes in domesticated chickens. Analysis of molecular variance (AMOVA) revealed that 94.51% of observed haplotype variation was accounted for at the within individual level. Little genetic variance was apportioned within and among populations, the latter accounting only for 0.83%. We also found evidence of increased recombination, including numerous hotspots, and limited linkage disequilibrium among the 84 SNP sites. Compared to an average haplotype diversity of 3.55% among seventeen lines of domestic chickens, our results suggest extraordinarily high haplotype diversity remains in wild Red Junglefowl and is consistent with a pattern of balancing selection. Wild Red Junglefowl in Vietnam, therefore, represent a rich resource of natural genomic variation independent from artificial selection.

MHC variability in heritage breeds of chickens

The chicken Major Histocompatibility Complex (MHC) is very strongly associated with disease resistance and thus is a very important region of the chicken genome. Historically, MHC (B locus) has been identified by the use of serology with haplotype specific alloantisera. These antisera can be difficult to produce and frequently cross-react with multiple haplotypes and hence their application is generally limited to inbred and MHC-defined lines. As a consequence, very little information about MHC variability in heritage chicken breeds is available. DNA-based methods are now available for examining MHC variability in these previously uncharacterized populations. A high density SNP panel consisting of 101 SNP that span a 230,000 bp region of the chicken MHC was used to examine MHC variability in 17 heritage populations of chickens from five universities from Canada and the United States. The breeds included 6 heritage broiler lines, 3 Barred Plymouth Rock, 2 New Hampshire and one each of Rhode Island Red, Light Sussex, White Leghorn, Dark Brown Leghorn, and 2 synthetic lines. These heritage breeds contained from one to 11 haplotypes per line. A total of 52 unique MHC haplotypes were found with only 10 of them identical to serologically defined haplotypes. Furthermore, nine MHC recombinants with their respective parental haplotypes were identified. This survey confirms the value of these non-commercially utilized lines in maintaining genetic diversity. The identification of multiple MHC haplotypes and novel MHC recombinants indicates that diversity is being generated and maintained within these heritage populations.