SNP Chip Genotyping Research Articles

Genetic architecture of body weight, carcass, and internal organs traits of Ghanaian local chickens.

Information on the genetic architecture of the production traits of indigenous African chicken is limited. We performed a genome-wide association study using imputed Affymetrix Axiom® 600K SNP-chip genotypes on 1,113 chickens from three agroecological zones of Ghana. After quality control, a total of 382,240 SNPs remained. Variance components and heritabilities for some growth, carcass and internal organ traits were estimated. The genetic and phenotypic correlations among these traits were also estimated. The estimated heritabilities of body weight at week 22 (BW22), average daily gain (ADG), dressed weight, breast weight, thigh weight, wing weight, drumstick weight, and neck weight were high and ranged from 0.50 to 0.69. Estimates of heritabilities for head weight, shank weight, and gizzard weight were moderate (0.31-0.35) while those of liver weight, back weight, dressing percentage, and heart weight were low (0.13-0.21). The estimated heritabilities of dressed weight, breast weight, wing weight, drumstick weight, neck weight, shank weight, and gizzard weight, corrected for BW22, were moderate (0.29-0.38), while the remaining traits had low heritability estimates (0.13-0.21). A total of 58 1-Mb SNP windows on chromosomes 1, 2, 4, 5, 6, 7, 8, 9, 13, 18, and 33 each explained more than 1% of the genetic variance for at least one of these traits. These genomic regions contained many genes previously reported to have effects on growth, carcass, and internal organ traits of chickens, including EMX2, CALCUL1, ACVR1B, CACNB1, RB1, MLNR, FOXO1, NCARPG, LCORL, LAP3, LDB2, KPNA3, and CAB39L. The moderate to high heritability estimates and high positive genetic correlations suggest that BW22, ADG, dressed weight, breast weight, thigh weight, wing weight, drumstick weight, and neck weight could be improved through selective breeding.

Use of DNA pools of a reference population for genomic selection of a binary trait in Atlantic salmon.

Genomic selection has a great potential in aquaculture breeding since many important traits are not directly measured on the candidates themselves. However, its implementation has been hindered by staggering genotyping costs because of many individual genotypes. In this study, we explored the potential of DNA pooling for creating a reference population as a tool for genomic selection of a binary trait. Two datasets from the SalmoBreed population challenged with salmonid alphavirus, which causes pancreas disease, were used. Dataset-1, that includes 855 individuals (478 survivors and 377 dead), was used to develop four DNA pool samples (i.e., 2 pools each for dead and survival). Dataset-2 includes 914 individuals (435 survivors and 479 dead) belonging to 65 full-sibling families and was used to develop in-silico DNA pools. SNP effects from the pool data were calculated based on allele frequencies estimated from the pools and used to calculate genomic breeding values (GEBVs). The correlation between SNP effects estimated based on individual genotypes and pooled data increased from 0.3 to 0.912 when the number of pools increased from 1 to 200. A similar trend was also observed for the correlation between GEBVs, which increased from 0.84 to 0.976, as the number of pools per phenotype increased from 1 to 200. For dataset-1, the accuracy of prediction was 0.71 and 0.70 when the DNA pools were sequenced in 40× and 20×, respectively, compared to an accuracy of 0.73 for the SNP chip genotypes. For dataset-2, the accuracy of prediction increased from 0.574 to 0.691 when the number of in-silico DNA pools increased from 1 to 200. For this dataset, the accuracy of prediction using individual genotypes was 0.712. A limited effect of sequencing depth on the correlation of GEBVs and prediction accuracy was observed. Results showed that a large number of pools are required to achieve as good prediction as individual genotypes; however, alternative effective pooling strategies should be studied to reduce the number of pools without reducing the prediction power. Nevertheless, it is demonstrated that pooling of a reference population can be used as a tool to optimize between cost and accuracy of selection.

Capturing Genetic Diversity and Selection Signatures of the Endangered Kosovar Balusha Sheep Breed.

There is a growing concern about the loss of animal genetic resources. The aim of this study was to analyze the genetic diversity and potential peculiarity of the endangered Kosovar sheep breed Balusha. For this purpose, a dataset consisting of medium-density SNP chip genotypes (39,879 SNPs) from 45 Balusha sheep was generated and compared with SNP chip genotypes from 29 individuals of a second Kosovar breed, Bardhoka. Publicly available SNP genotypes from 39 individuals of the relatively closely located sheep breeds Istrian Pramenka and Ruda were additionally included in the analyses. Analysis of heterozygosity, allelic richness and effective population size was used to assess the genetic diversity. Inbreeding was evaluated using two different methods (FIS, FROH). The standardized FST (di) and cross-population extended haplotype homozygosity (XPEHH) methods were used to detect signatures of selection. We observed the lowest heterozygosity (HO = 0.351) and effective population size (Ne5 = 25, Ne50 = 228) for the Balusha breed. The mean allelic richness levels (1.780–1.876) across all analyzed breeds were similar and also comparable with those in worldwide breeds. FROH estimates (0.023–0.077) were highest for the Balusha population, although evidence of decreased inbreeding was observed in FIS results for the Balusha breed. Two Gene Ontology (GO) TERMs were strongly enriched for Balusha, and involved genes belonging to the melanogenesis and T cell receptor signaling pathways, respectively. This could result from selection for the special coat color pattern of Balusha (black head) and resistance to certain infectious diseases. The analyzed diversity parameters highlight the urgency to preserve the local Kosovar Balusha sheep as it is clearly distinguished from other sheep of Southeastern Europe, has the lowest diversity level and may harbor valuable genetic variants, e.g., for resistance to infectious diseases.

Quantitative trait loci for yellow rust resistance in spring wheat doubled haploid populations developed from the German Federal ex situ genebank genetic resources.

Novel resistance sources to the pathogen Puccinia striiformis f. sp. tritici, which causes yellow rust (stripe rust), a widespread devastating foliar disease in wheat (Triticum aestivum L.), are in demand. Here, we tested two doubled haploid (DH) spring wheat populations derived from the genetic resources for resistance to yellow rust in field trials in Germany and Egypt. Additionally, we performed tests for all-stage resistance (seedling resistance). We performed linkage mapping based on 15k Infinium SNP chip genotyping data that resulted in 3,567 and 3,457 polymorphic markers for DH Population 1 (103 genotypes) and DH Population 2 (148 genotypes), respectively. In DH Population 1, we identified a major and consistent quantitative trait locus (QTL) on chromosome 1B that explained up to 28 and 39% of the phenotypic variation in the field and seedling tests, respectively. The favorable allele was contributed by the line 'TRI-5645', a landrace from Iran, and is most probably the yellow rust resistance (Yr) gene Yr10. In DH Population 2, the favorable allele of a major QTL on chromosome 6B was contributed by the line 'TRI-5310', representing the variety 'Eureke' from France. This QTL was mainly effective in the German environments and explained up to 36% of the phenotypic variation. In Egypt, however, only a moderate resistance QTL was identified in the field tests and no resistance QTL was observed in the seedling tests. Our results demonstrate the usefulness of genetic resources to identify novel sources of resistance to yellow rust, including the "Warrior" race PstS10.

Implementing a genomic rotational crossbreeding scheme to promote local dairy cattle breeds—A simulation study

In dairy cattle breeding, there is a clear trend toward the use of only a few high-yielding breeds. One main reason is that efficient breeding programs require a certain population size. Since some numerically small breeds are well known for their functional traits, they might be an interesting crossing partner for high-yielding breeds with the aim to utilize heterosis. This simulation study investigated the transition period of a small cattle population for the implementation of genomic selection and rotational crossbreeding with a high-yielding breed. Real SNP chip genotype data from the numerically small red dairy breed Angler and the high-yielding breed Holstein Friesian were used to simulate the base generations, from which rotational crossbreeding was conducted for 10 generations. A polygenic trait with many quantitative trait loci with additive and directional dominance effects was simulated. Different selection methods for Angler sires (purebred performance, crossbred performance, and weighted purebred-crossbred performance) and different sizes and structures of the reference population (Angler, crossbred animals, and Angler plus crossbred animals) were considered. The results showed that the implementation of a genomic rotational crossbreeding scheme is an appealing option to promote the numerically small Angler breed. The growing reference population consisting of Angler and crossbred individuals maximized the genetic gain for Angler and the performance level for the crossbred individuals. Selection for purebred performance, crossbred performance, or a weighted combination of both hardly affected the results, and differences between selection scenarios were observed only in the long term with decreasing purebred-crossbred correlations.

Genetic mapping and transcriptomic characterization of a new fuzzless-tufted cottonseed mutant.

Fiber mutants are unique and valuable resources for understanding the genetic and molecular mechanisms controlling initiation and development of cotton fibers that are extremely elongated single epidermal cells protruding from the seed coat of cottonseeds. In this study, we reported a new fuzzless-tufted cotton mutant (Gossypium hirsutum) and showed that fuzzless-tufted near-isogenic lines (NILs) had similar agronomic traits and a higher ginning efficiency compared to their recurrent parents with normal fuzzy seeds. Genetic analysis revealed that the mutant phenotype is determined by a single incomplete dominant locus, designated N5. The mutation was fine mapped to an approximately 250-kb interval containing 33 annotated genes using a combination of bulked segregant sequencing, SNP chip genotyping, and fine mapping. Comparative transcriptomic analysis using 0–6 days post-anthesis (dpa) ovules from NILs segregating for the phenotypes of fuzzless-tufted (mutant) and normal fuzzy cottonseeds (wild-type) uncovered candidate genes responsible for the mutant phenotype. It also revealed that the flanking region of the N5 locus is enriched with differentially expressed genes (DEGs) between the mutant and wild-type. Several of those DEGs are members of the gene families with demonstrated roles in cell initiation and elongation, such as calcium-dependent protein kinase and expansin. The transcriptome landscape of the mutant was significantly reprogrammed in the 6 dpa ovules and, to a less extent, in the 0 dpa ovules, but not in the 2 and 4 dpa ovules. At both 0 and 6 dpa, the reprogrammed mutant transcriptome was mainly associated with cell wall modifications and transmembrane transportation, while transcription factor activity was significantly altered in the 6 dpa mutant ovules. These results imply a similar molecular basis for initiation of lint and fuzz fibers despite certain differences.

Tracing selection signatures in the pig genome gives evidence for selective pressures on a unique curly hair phenotype in Mangalitza

Selection for desirable traits and breed-specific phenotypes has left distinctive footprints in the genome of pigs. As representative of a breed with strong selective traces aiming for robustness, health and performance, the Mangalitza pig, a native curly-haired pig breed from Hungary, was investigated in this study. Whole genome sequencing and SNP chip genotyping was performed to detect runs of homozygosity (ROH) in Mangalitza and Mangalitza-crossbreeds. We identified breed specific ROH regions harboring genes associated with the development of the curly hair type and further characteristics of this breed. Further analysis of two matings of Mangalitza with straight-coated pig breeds confirmed an autosomal dominant inheritance of curly hair. Subsequent scanning of the genome for variant effects on this trait revealed two variants potentially affecting hair follicle development and differentiation. Validation in a large sample set as well as in imputed SNP data confirmed these variants to be Mangalitza-specific. Herein, we demonstrated how strong artificial selection has shaped the genome in Mangalitza pigs and left traces in the form of selection signatures. This knowledge on genomic variation promoting unique phenotypes like curly hair provides an important resource for futures studies unraveling genetic effects for special characteristics in livestock.

A 63-bp insertion in exon 2 of the porcine KIF21A gene is associated with arthrogryposis multiplex congenita.

A recessive form of arthrogryposis multiplex congenita (AMC) was detected 20years ago in the Swiss Large White (SLW) pig population. A diagnostic marker test enabled the identification of carrier animals, but the underlying causal mutation remains unknown. To identify the mutation underlying AMC, we collected SNP chip genotyping data for 11 affected piglets and 23 healthy pigs. Association testing using 47829 SNPs confirmed that AMC maps to SSC5 (P=9.4×10-13 ). Subsequent autozygosity mapping revealed a common 6.06Mb region (from 66 757970 to 72815151bp) of extended homozygosity in 11 piglets affected by AMC. Using WGS data, we detected a 63-bp insertion compatible with the recessive inheritance of AMC in the second exon of KIF21A gene encoding Kinesin Family Member 21A. The 63-bp insertion is predicted to introduce a premature stop codon in KIF21A gene (p.Val41_Phe42insTer) that truncates 1614 amino acids (~97%) from the protein. We found that this deleterious allele still segregates at a frequency of 0.1% in the SLW pig population. Carrier animals can now be detected unambiguously and excluded from breeding.

Genome-Wide Identification of a Regulatory Mutation in BMP15 Controlling Prolificacy in Sheep.

The search for the genetic determinism of prolificacy variability in sheep has evidenced several major mutations in genes playing a crucial role in the control of ovulation rate. In the Noire du Velay (NV) sheep population, a recent genetic study has evidenced the segregation of such a mutation named FecLL. However, based on litter size (LS) records of FecLL non-carrier ewes, the segregation of a second prolificacy major mutation was suspected in this population. In order to identify this mutation, we have combined a case/control genome-wide association study with ovine 50k SNP chip genotyping, whole genome sequencing, and functional analyses. A new single nucleotide polymorphism (OARX:50977717T > A, NC_019484) located on the X chromosome upstream of the BMP15 gene was evidenced to be highly associated with the prolificacy variability (P = 1.93E-11). The variant allele was called FecXN and shown to segregate also in the Blanche du Massif Central (BMC) sheep population. In both NV and BMC, the FecXN allele frequency was estimated close to 0.10, and its effect on LS was estimated at +0.20 lamb per lambing at the heterozygous state. Homozygous FecXN carrier ewes were fertile with increased prolificacy in contrast to numerous mutations affecting BMP15. At the molecular level, FecXN was shown to decrease BMP15 promoter activity and supposed to impact BMP15 expression in the oocyte. This regulatory action was proposed as the causal mechanism for the FecXN mutation to control ovulation rate and prolificacy in sheep.

Unraveling the genetic diversity of Belgian Milk Sheep using medium‐density SNP genotypes

SummaryThe present study focuses on the Belgian Milk Sheep in Flanders (Belgium) and compares its genetic diversity and relationship with the Flemish Sheep, the Friesian Milk Sheep, the French Lacaune dairy sheep and other Northern European breeds. For this study, 94 Belgian Milk Sheep, 23 Flemish Sheep and 22 Friesian Milk Sheep were genotyped with the OvineSNP50 array. In addition, 29 unregistered animals phenotypically similar to Belgian Milk Sheep were genotyped using the 15K ISGC chip. Both Belgian and Friesian Milk Sheep as well as the East Friesian Sheep were found to be less diverse than the other seven breeds included in this study. Genomic inbreeding coefficients based on runs of homozygosity (ROH) were estimated at 14.5, 12.4 and 10.2% for Belgian Milk Sheep, Flemish Sheep and Friesian Milk Sheep respectively. Out of 29 unregistered Belgian Milk Sheep, 28 mapped in the registered Belgian Milk Sheep population. Ancestry analysis, PCA and F ST calculations showed that Belgian Milk Sheep are more related to Friesian Milk Sheep than to Flemish Sheep, which was contrary to the breeders' expectations. Consequently, breeders may prefer to crossbreed Belgian Milk Sheep with Friesian sheep populations (Friesian Milk Sheep or East Friesian Sheep) in order to increase diversity. This research underlines the usefulness of SNP chip genotyping and ROH analyses for monitoring genetic diversity and studying genetic links in small livestock populations, profiting from internationally available genotypes. As assessment of genetic diversity is vital for long‐term breed survival, these results will aid flockbooks to preserve genetic diversity.

Detection of Autosomal Hemizygous Regions in the Fleckvieh Population Based on SNP-chip Data and Parent Offspring Pairs

A Copy Number Variation (CNV) is a loss or a gain in the DNA sequence, ranging from 50 basepairs to a few megabasepairs. Most studies use whole genome sequencing data to detect deletions. Due to the fact that SNP-chip data is more commonly used in livestock, especially in cattle, the detection of deletions based on SNP-chip data is of interest. In the present study an approach based on SNP chip data and the analysis of Mendelian mismatches in parent-offspring-pairs was developed. Use was made of the fact that deletions appear as homozygous after SNP Chip genotyping. For some SNPs with high number of mismatches, the inheritance of the mismatches could be traced back to one or a few bulls and thereby regions of possible deletions were defined. The study has shown that an approach based on Mendelian mismatches and SNP-chip data is a promising way of detecting deletions.

Runs of homozygosity and signatures of selection: a comparison among eight local Swiss sheep breeds

A dataset consisting of 787 animals with high-density SNP chip genotypes (346774 SNPs) and 939 animals with medium-density SNP chip genotypes (33828 SNPs) from eight indigenous Swiss sheep breeds was analyzed to characterize population structure, quantify genomic inbreeding based on runs of homozygosity and identify selection signatures. In concordance with the recent known history of these breeds, the highest genetic diversity was observed in Engadine Red sheep and the lowest in Valais Blacknose sheep. Correlation between FPED and FROH was around 0.50 and thereby lower than that found in similar studies in cattle. Mean FROH estimates from medium-density data and HD data were highly correlated (0.95). Signatures of selection and candidate gene analysis revealed that the most prominent signatures of selection were found in the proximity of genes associated with body size (NCAPG, LCORL, LAP3, SPP1, PLAG1, ALOX12, TP53), litter size (SPP1), milk production (ABCG2, SPP1), coat color (KIT, ASIP, TBX3) and horn status (RXFP2). For the Valais Blacknose sheep, the private signatures in proximity of genes/QTL influencing body size, coat color and fatty acid composition were confirmed based on runs of homozygosity analysis. These private signatures underline the genetic uniqueness of the Valais Blacknose sheep breed. In conclusion, we identified differences in the genetic make-up of Swiss sheep breeds, and we present relevant candidate genes responsible for breed differentiation in locally adapted breeds.

Finding the Optimal Imputation Strategy for Small Cattle Populations.

The imputation from lower density SNP chip genotypes to whole-genome sequence level is an established approach to generate high density genotypes for many individuals. Imputation accuracy is dependent on many factors and for small cattle populations such as the endangered German Black Pied cattle (DSN), determining the optimal imputation strategy is especially challenging since only a low number of high density genotypes is available. In this paper, the accuracy of imputation was explored with regard to (1) phasing of the target population and the reference panel for imputation, (2) comparison of a 1-step imputation approach, where 50 k genotypes are directly imputed to sequence level, to a 2-step imputation approach that used an intermediate step imputing first to 700 k and subsequently to sequence level, (3) the software tools Beagle and Minimac, and (4) the size and composition of the reference panel for imputation. Analyses were performed for 30 DSN and 30 Holstein Frisian cattle available from the 1000 Bull Genomes Project. Imputation accuracy was assessed using a leave-one-out cross validation procedure. We observed that phasing of the target populations and the reference panels affects the imputation accuracy significantly. Minimac reached higher accuracy when imputing using small reference panels, while Beagle performed better with larger reference panels. In contrast to previous research, we found that when a low number of animals is available at the intermediate imputation step, the 1-step imputation approach yielded higher imputation accuracy compared to a 2-step imputation. Overall, the size of the reference panel for imputation is the most important factor leading to higher imputation accuracy, although using a larger reference panel consisting of a related but different breed (Holstein Frisian) significantly reduced imputation accuracy. Our findings provide specific recommendations for populations with a limited number of high density genotyped or sequenced animals available such as DSN. The overall recommendation when imputing a small population are to (1) use a large reference panel of the same breed, (2) use a large reference panel consisting of diverse breeds, or (3) when a large reference panel is not available, we recommend using a smaller same breed reference panel without including a different related breed.

Short communication: Identification of the pseudoautosomal region in the Hereford bovine reference genome assembly ARS-UCD1.2

In cattle, the X chromosome accounts for approximately 3 and 6% of the genome in bulls and cows, respectively. In spite of the large size of this chromosome, very few studies report analysis of the X chromosome in genome-wide association studies and genomic selection. This lack of genetic interrogation is likely due to the complexities of undertaking these studies given the hemizygous state of some, but not all, of the X chromosome in males. The first step in facilitating analysis of this gene-rich chromosome is to accurately identify coordinates for the pseudoautosomal boundary (PAB) to split the chromosome into a region that may be treated as autosomal sequence (pseudoautosomal region) and a region that requires more complex statistical models. With the recent release of ARS-UCD1.2, a more complete and accurate assembly of the cattle genome than was previously available, it is timely to fine map the PAB for the first time. Here we report the use of SNP chip genotypes, short-read sequences, and long-read sequences to fine map the PAB (X chromosome:133,300,518) and simultaneously determine the neighboring regions of reduced homology and true pseudoautosomal region. These results greatly facilitate the inclusion of the X chromosome in genome-wide association studies, genomic selection, and other genetic analysis undertaken on this reference genome.

In vivo haploid induction leads to increased frequency of twin-embryo and abnormal fertilization in maize

BackgroundIn vivo haploid induction (HI) based on Stock6-derived inducer lines has been the most prevalent means of producing haploids. Nevertheless, the biological mechanism of HI is not fully understood, the twin-embryo kernels had been found during haploid induction, which may provide potential evidence for the abnormal double fertilization during HI.ResultsWe investigated twin-embryo frequency in progenies of different haploid inducers. Results reveal that increasing the HI potential significantly improved the frequency of twin-embryo kernels. Compared with the average twin-embryo kernel frequency (average frequency = 0.07%) among progenies pollinated by the haploid inducer line CAUHOI, the frequency of twin-embryo was improved to 0.16% in progenies pollinated by the haploid inducer line CAU5. This result was further confirmed by pollinating single hybrid ND5598 with four haploid inducers possessing differentiated HIRs, where twin-embryo frequency was highly correlated with HIR. Among 237 twin-embryo kernels, we identified 30 haploid twin-embryo kernels (12.66%), a frequency which was much greater than the average HI rate for three other inducer lines (frequency range 2–10%). In addition, aneuploids, occurred at high frequency (8 in 41 twin plants). This level of aneuploidy provides new insight into the abnormal double fertilization during HI. Moreover, we observed differences in growth rate between twin plants in the field, as 4.22% of the twin plants grew at a significantly different rate. Both simple sequence repeats markers (SSR) and 3072 SNP-chip genotyping results revealed that > 90% of the twin plants shared the same origin, and the growth difference could be attributed to aneuploidy, competition for nutrients, and possible hormone regulation.ConclusionThese results demonstrate that an enhanced HI ability can increase twin-embryo kernel frequency, and high frequency of both haploid twin-embryo kernels and aneuploidy observed in this research give us new insights to understand the mechanism of both HI and abnormal embryogenesis.

A heuristic method for fast and accurate phasing and imputation of single-nucleotide polymorphism data in bi-parental plant populations

Key messageNew fast and accurate method for phasing and imputation of SNP chip genotypes within diploid bi-parental plant populations.This paper presents a new heuristic method for phasing and imputation of genomic data in diploid plant species. Our method, called AlphaPlantImpute, explicitly leverages features of plant breeding programmes to maximise the accuracy of imputation. The features are a small number of parents, which can be inbred and usually have high-density genomic data, and few recombinations separating parents and focal individuals genotyped at low density (i.e. descendants that are the imputation targets). AlphaPlantImpute works roughly in three steps. First, it identifies informative low-density genotype markers in parents. Second, it tracks the inheritance of parental alleles and haplotypes to focal individuals at informative markers. Finally, it uses this low-density information as anchor points to impute focal individuals to high density. We tested the imputation accuracy of AlphaPlantImpute in simulated bi-parental populations across different scenarios. We also compared its accuracy to existing software called PlantImpute. In general, AlphaPlantImpute had better or equal imputation accuracy as PlantImpute. The computational time and memory requirements of AlphaPlantImpute were tiny compared to PlantImpute. For example, accuracy of imputation was 0.96 for a scenario where both parents were inbred and genotyped at 25,000 markers per chromosome and a focal F2 individual was genotyped with 50 markers per chromosome. The maximum memory requirement for this scenario was 0.08 GB and took 37 s to complete.

Which Individuals To Choose To Update the Reference Population? Minimizing the Loss of Genetic Diversity in Animal Genomic Selection Programs.

Genomic selection (GS) is commonly used in livestock and increasingly in plant breeding. Relying on phenotypes and genotypes of a reference population, GS allows performance prediction for young individuals having only genotypes. This is expected to achieve fast high genetic gain but with a potential loss of genetic diversity. Existing methods to conserve genetic diversity depend mostly on the choice of the breeding individuals. In this study, we propose a modification of the reference population composition to mitigate diversity loss. Since the high cost of phenotyping is the limiting factor for GS, our findings are of major economic interest. This study aims to answer the following questions: how would decisions on the reference population affect the breeding population, and how to best select individuals to update the reference population and balance maximizing genetic gain and minimizing loss of genetic diversity? We investigated three updating strategies for the reference population: random, truncation, and optimal contribution (OC) strategies. OC maximizes genetic merit for a fixed loss of genetic diversity. A French Montbéliarde dairy cattle population with 50K SNP chip genotypes and simulations over 10 generations were used to compare these different strategies using milk production as the trait of interest. Candidates were selected to update the reference population. Prediction bias and both genetic merit and diversity were measured. Changes in the reference population composition slightly affected the breeding population. Optimal contribution strategy appeared to be an acceptable compromise to maintain both genetic gain and diversity in the reference and the breeding populations.

A systematic survey to identify lethal recessive variation in highly managed pig populations

BackgroundLethal recessive variation can cause prenatal death of homozygous offspring. Although usually present at low-frequency in populations, the impact on individual fitness can be substantial. Until recently, the presence of recessive embryonic lethal variation could only be measured indirectly through reduced fertility. In this study, we estimate the presence of genetic loci associated with both early and late termination of development during gestation in pigs from the wealth of genome data routinely generated by a commercial breeding company.ResultsWe examined three commercial pig (Sus scrofa) populations for potentially deleterious genetic variation based on 80 K SNP-chip genotypes, and estimate the effects on reproductive traits. 24,000 pigs from three populations were analyzed for missing or depletion of homozygous haplotypes. We identified 145 haplotypes (ranging from 0.5–4 Mb in size) in the genome with complete absence or depletion of homozygous animals. Thirty-five haplotypes show a negative effect on at least one of the analysed reproductive traits (total number born, number of stillborn, and number of mummified piglets). One variant in particular appeared to result in relative late termination of development of fetuses, responsible for a significant fraction of observed stillborn piglets (‘mummies’), as they die mid-gestation. Moreover, we identified the BMPER gene as a likely candidate underlying this phenomenon.ConclusionsOur study shows that although lethal recessive variation is present, the frequency of these alleles is invariably low in these highly managed populations. Nevertheless, due to cumulative effects of deleterious variants, large numbers of affected offspring are produced. Furthermore, our study demonstrates the use of a large-scale commercial genetic experiment to systematically screen for ‘natural knockouts’ that can increase understanding of gene function.

Rapid Discovery of De Novo Deleterious Mutations in Cattle Enhances the Value of Livestock as Model Species

In humans, the clinical and molecular characterization of sporadic syndromes is often hindered by the small number of patients and the difficulty in developing animal models for severe dominant conditions. Here we show that the availability of large data sets of whole-genome sequences, high-density SNP chip genotypes and extensive recording of phenotype offers an unprecedented opportunity to quickly dissect the genetic architecture of severe dominant conditions in livestock. We report on the identification of seven dominant de novo mutations in CHD7, COL1A1, COL2A1, COPA, and MITF and exploit the structure of cattle populations to describe their clinical consequences and map modifier loci. Moreover, we demonstrate that the emergence of recessive genetic defects can be monitored by detecting de novo deleterious mutations in the genome of bulls used for artificial insemination. These results demonstrate the attractiveness of cattle as a model species in the post genomic era, particularly to confirm the genetic aetiology of isolated clinical case reports in humans.

RNF213 Is Associated with Intracranial Aneurysms in the French-Canadian Population

Intracranial aneurysms (IAs) are the result of focal weakness in the artery wall and have a complex genetic makeup. To date, genome-wide association and sequencing studies have had limited success in identifying IA risk factors. Distinct populations, such as the French-Canadian (FC) population, have increased IA prevalence. In our study, we used exome sequencing to prioritize risk variants in a discovery cohort of six FC families affected by IA, and the analysis revealed an increased variation burden for ring finger protein 213 (RNF213). We resequenced RNF213 in a larger FC validation cohort, and association tests on further identified variants supported our findings (SKAT-O, p = 0.006). RNF213 belongs to the AAA+ protein family, and two variants (p.Arg2438Cys and p.Ala2826Thr) unique to affected FC individuals were found to have increased ATPase activity, which could lead to increased risk of IA by elevating angiogenic activities. Common SNPs in RNF213 were also extracted from the NeuroX SNP-chip genotype data, comprising 257 FC IA-affected and 1,988 control individuals. We discovered that the non-ancestral allele of rs6565666 was significantly associated with the affected individuals (p = 0.03), and it appeared as though the frequency of the risk allele had changed through genetic drift. Although RNF213 is a risk factor for moyamoya disease in East Asians, we demonstrated that it might also be a risk factor for IA inthe FC population. It therefore appears that the function of RNF213 can be differently altered to predispose distinct populations to dissimilar neurovascular conditions, highlighting the importance of a population's background in genetic studies of heterogeneous disease.