Development and validation of a 5K low-density SNP chip for Hainan cattle.

BACKGROUND: This study aimed to design and develop a 5K low-density liquid chip for Hainan cattle utilizing targeted capture sequencing technology. The chip incorporates a substantial number of functional single nucleotide polymorphism (SNP) loci derived from public literature, including SNP loci significantly associated with immunity, heat stress, meat quality, reproduction, and other traits. Additionally, SNPs located in the coding regions of immune-related genes from the Bovine Genome Variation Database (BGVD) and Hainan cattle-specific SNP loci were included. RESULTS: A total of 5,293 SNPs were selected, resulting in 9,837 DNA probes with a coverage rate of 85.69%, thereby creating a Hainan cattle-specific 5K Genotyping by Target Sequencing (GBTS) liquid chip. Evaluation with 152 cattle samples demonstrated excellent clustering performance and a detection rate ranging from 96.60 to 99.07%, with 94.5% of SNP sites exhibiting polymorphism. The chip achieved 100% gender coverage and displayed a heterozygosity rate between 14.20% and 29.65%, with a repeatability rate of 99.65-99.85%. Analyses using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed the potential regulatory roles of exonic SNPs in immune response pathways. CONCLUSION: The development and validation of the 5K GBTS liquid chip for Hainan cattle represent a valuable tool for genome analysis and genetic diversity assessment. Furthermore, it facilitates breed identification, gender determination, and kinship analysis, providing a foundation for the efficient utilization and development of local cattle genetic resources.

Review on camel genetic diversity: ecological and economic perspectives.

Camels, known as the "Ship of the Desert," play a vital role in the ecosystems and economies of arid and semi-arid regions. They provide meat, milk, transportation, and other essential services, and their resilience to harsh environments makes them invaluable. Despite their similarities, camel breeds exhibit notable differences in size, color, and structure, with over 40 million camels worldwide. This number is projected to increase, underscoring their growing significance. Economically, camels are crucial for food production, tourism, and trade, with camel racing being particularly significant in Arab countries. Their unique physiological traits, such as low disease susceptibility and efficient water conservation, further enhance their value. Camel products, especially meat and milk, offer substantial nutritional and therapeutic benefits, contributing to their high demand. Genetic diversity studies have advanced our understanding of camels' adaptation to extreme environments. Functional genomics and whole-genome sequencing have identified genes responsible for these adaptations, aiding breeding programs and conservation efforts. High-throughput sequencing has revealed genetic markers linked to traits like milk production and disease resistance. The development of SNP chips has revolutionized genetic studies by providing a cost-effective alternative to whole-genome sequencing. These tools facilitate large-scale genotyping, essential for conserving genetic diversity and improving breeding strategies. To prevent the depletion of camel genetic diversity, it is crucial to streamline in situ and ex situ conservation efforts to maintain their ecological and economic value. A comprehensive approach to camel conservation and genetic preservation, involving advanced genomic technologies, reproductive biotechniques, and sustainable management practices, will ensure their continued contribution to human societies.

Analysis of genetic diversity and structure of endangered Dengchuan cattle population using a single-nucleotide polymorphism chip.

This study aimed to evaluate the genetic diversity and structure within the Dengchuan cattle population and effectively protect and utilize their germplasm resources. Herein, the single-nucleotide polymorphisms (SNPs) of 100 Dengchuan cattle (46 bulls and 54 cows) were determined using the GGP Bovine 100K SNP Beadchip. The results showed that among the Dengchuan cattle, a total of 101,220 SNPs were detected, and there were 83,534 SNPs that passed quality control, of which 85.7% were polymorphic. The average genetic distance based on identity-by-state (IBS) within the conservation population of Dengchuan cattle was 0.26 ± 0.02. A total of 3,999 genome-length runs of homozygosity (ROHs) were detected in the Dengchuan cattle, with ROH lengths primarily concentrated in the range of 1-5 Mb, accounting for 87.02% of the total. The average inbreeding coefficient based on ROHs was 4.6%, within the conservation population of Dengchuan cattle, whereas it was 4.9% for bulls, and the Wright inbreeding coefficient (FIS) value was 2.4%, demonstrating a low level of inbreeding within the Dengchuan cattle population. Based on neighbor-joining tree analysis, the Dengchuan cattle could be divided into 16 families. In summary, the conservation population of Dengchuan cattle displays relatively abundant diversity and a moderate genetic relationship. Inbreeding was observed among a few individuals, but the overall inbreeding level of the population remained low. It is important to maintain this low level of inbreeding when introducing purebred bloodlines to expand the core group. This approach will ensure the long-term conservation of Dengchuan cattle germplasm resources and prevent loss of genetic diversity.

Imputation accuracy from low- to medium-density SNP chips for US crossbred dairy cattle.

This study aimed at evaluating the quality of imputation accuracy (IA) by marker (IAm) and by individual (IAi) in US crossbred dairy cattle. Holstein × Jersey crossbreds were used to evaluate IA from a low- (7K) to a medium-density (50K) SNP chip. Crossbred animals, as well as their sires (53), dams (77), and maternal grandsires (63), were all genotyped with a 78K SNP chip. Seven different scenarios of reference populations were tested, in which some scenarios used different family relationships and others added random unrelated purebred and crossbred individuals to those different family relationship scenarios. The same scenarios were tested on Holstein and Jersey purebred animals to compare these outcomes against those attained in crossbred animals. The genotype imputation was performed with findhap (version 4) software (VanRaden, 2015). There were no significant differences in IA results depending on whether the sire of imputed individuals was Holstein and the dam was Jersey, or vice versa. The IA increased significantly with the addition of related individuals in the reference population, from 86.70 ± 0.06% when only sires or dams were included in the reference population to 90.09 ± 0.06% when sire (S), dam (D), and maternal grandsire genomic data were combined in the reference population. In all scenarios including related individuals in the reference population, IAm and IAi were significantly superior in purebred Jersey and Holstein animals than in crossbreds, ranging from 90.75 ± 0.06 to 94.02 ± 0.06%, and from 90.88 ± 0.11 to 94.04 ± 0.10%, respectively. Additionally, a scenario called SPB+DLD(where PB indicates purebread and LD indicates low density), similar to the genomic evaluations performed on US crossbred dairy, was tested. In this scenario, the information from the 5 evaluated breeds (Ayrshire, Brown Swiss, Guernsey, Holstein, and Jersey) genotyped with a 50K SNP chip and genomic information from the dams genotyped with a 7K SNP chip were combined in the reference population, and the IAm and IAi were 80.87 ± 0.06% and 80.85 ± 0.08%, respectively. Adding randomly nonrelated genotyped individuals in the reference population reduced IA for both purebred and crossbred cows, except for scenario SPB+DLD, where adding crossbreds to the reference population increased IA values. Our findings demonstrate that IA for US Holstein × Jersey crossbred ranged from 85 to 90%, and emphasize the significance of designing and defining the reference population for improved IA.

Genomic inbreeding coefficients using imputation genotypes: Assessing the effect of ancestral genotyping in Holstein-Friesian dairy cows.

The objective of this study was to assess the effect of using or not using the genotypes of the parents of a cow for imputing SNPs on the estimation of genomic inbreeding coefficients of cows. Imputation (i.e., genotyped plus imputed) genotypes from 68,127 Italian Holstein dairy cows registered in the Italian National Association of Holstein, Brown, and Jersey Breeders were analyzed. Cows were genotyped with the high-density (HD) Illumina Infinium BovineHD BeadChip and GeneSeek Genomic Profiler HD-150K, and the medium-density (MD) GeneSeek Genomic Profiler 3, GeneSeek Genomic Profiler 4, GeneSeek MD, and the Labogena MD. To assess differences among estimators, genomic inbreeding coefficients were estimated with 4 PLINK v1.9 estimators (F, Fhat1,Fhat2, andFhat3), 2 genomic relationship matrix- (grm) based estimators (Fgrm and Fgrm2, with the latter including also pedigree information), and one estimator of runs of homozygosity (ROH; FROH). Assuming that the correct genomic inbreeding coefficients should be those estimated from genotyped SNPs, a comparison of the genomic inbreeding coefficients estimated either with the genotyped SNPs or the SNPs after imputation was made. Information on the presence or absence of genotypic information from sire, dam, and maternal grandsire during the imputation was investigated. Genomic inbreeding coefficients estimated with genotyped SNPs or SNPs after imputation were consistent for F, Fhat3, Fgrm2, and FROH, when at least one of the parents was genotyped. Biased (mainly higher) genomic inbreeding coefficients of imputation SNPs were observed in cows that were genotyped with MD SNP panels whose SNPs were poorly represented in the selected imputation SNP dataset and also did not have their parents genotyped, when compared with what would be expected based on actual genotype data. For cows genotyped with MD the estimators Fhat1, Fhat2, and Fgrm provided higher genomic inbreeding coefficients of imputation SNPs even with both parents and the maternal grandsire genotyped. Overall, FROH was the most robust estimator, followed by F and Fhat3. Our findings suggest that SNPs selection, parental genotyping and estimator should be considered for designing imputation strategies in dairy cattle for estimating genomic inbreeding with imputation SNPs. For computing genomic inbreeding coefficients, it is recommendable to have at least one parent genotyped and use an ROH-based estimator.

Application effectiveness of "Youxin-1" in genetic diversity and structure analysis of local chickens.

China's local chicken breeds are rich in resources, and have formed different germplasm characteristics in the process of long-term selection and evolution. Scientific assessment of population genetic diversity and identification of inter-breed genetic structure are of great value to the protection and innovative utilization of local chicken breed resource. In order to evaluate the application effectiveness of 23K SNP chip "Youxin-1" in the analysis of genetic diversity and genetic structure of local chickens, we used RADseq to identify genomic genetic variation of 21 local chicken breeds and developed 23K chip "Youxin-1". The genetic statistics of each variety were calculated based on two sets of SNP data, and correlation, fitting and phylogenetic analysis were carried out to evaluate the application effectiveness of the chip. The results showed that the observed heterozygosity (Ho), polymorphism information content (PIC), inbred coefficient (FROH) and genetic differentiation coefficient (Fst) calculated based on the two SNP data sets were basically consistent in the 21 local chicken breeds. The genetic diversity of Langya chicken (LA), Piao chicken (PJ) and Wenchang chicken (WC) was relatively rich. The genetic diversity of Bian chickens (BJ), Langshan chickens (LS), Gushi chickens (GS), Dongxiang blue-eggshell chickens (DX) and Beijing fatty chickens (BY) was relatively poor, and the correlation coefficients of Ho, PIC, FROH and average Fst in the two groups were 0.794, 0.901, 0.926 and 0.984, respectively, all reaching extremely significant levels (P<0.01) with a high degree of fit (P<0.001) and R2 were 0.644, 0.827, 0.916 and 0.927. For the two sets of SNP data, the evolutionary tree constructed by neighbor-joining (NJ) method and maximum likelihood (ML) method was reasonable, and the 21 local chicken breeds were generally divided into six categories, which was consistent with the formation history and geographical distribution of the varieties. The 23K chip also realized reasonable clustering of the five new varieties without individual deviation. There are some differences in the estimation of genetic statistics using SNP with different densities, and data standardization is needed. 23K chip has good efficacy in the analysis of genetic diversity and structure of local chickens.

Genome-wide identification of SNPs associated with body weight in yak.

BACKGROUND: The yak is the most important livestock in the Qinghai-Tibet Plateau, and body weight directly affects the economic values of yak. Up to date, the genome-wide profiling of single-nucleotide polymorphisms (SNPs) associating with body weight has not been reported in yak. In the present study, the SNPs in 480 yaks from three breeds were analyzed using the commercial high-density (600 K) yak SNP chips. RESULTS: The results identified 12 and 4 SNPs potentially associated with body weight in male and female yaks, respectively. Among them, 9 and 2 SNPs showed significant difference in yak body weight between different genotypes at each locus in male and female yaks, respectively. Further exploration found 33 coding genes within the 100 kbp upstream or downstream to the SNP loci, which might be potentially affected by the variation of SNPs. Among them, G protein-coupled receptor kinase 4 (GRK4) might be potentially affected by the SNP AX-174555047, which has been reported to affect the functioning of two body-weight associated hormones (parathyroid hormone, PTH, and adrenomedullin, ADM). Determination of PTH and ADM levels in yak revealed positive relationship between PTH level and body weight, negative relationship between ADM level and body weight along with the variation of AX-174555047 mutation. CONCLUSIONS: These results suggested that the SNP AX-174555047 might potentially affect body weight through mediating GRK4 expression and then PTH and ADM functioning. Thus, the SNP AX-174555047 might be used as a biomarker for molecular breeding of yak. More investigations are required to validate this point.

Design and validation of a 63K genome-wide SNP-genotyping platform for caribou/reindeer (Rangifer tarandus).

BACKGROUND: Development of large single nucleotide polymorphism (SNP) arrays can make genomic data promptly available for conservation problematic. Medium and high-density panels can be designed with sufficient coverage to offer a genome-wide perspective and the generated genotypes can be used to assess different genetic metrics related to population structure, relatedness, or inbreeding. SNP genotyping could also permit sexing samples with unknown associated metadata as it is often the case when using non-invasive sampling methods favored for endangered species. Genome sequencing of wild species provides the necessary information to design such SNP arrays. We report here the development of a SNP-array for endangered Rangifer tarandus using a multi-platform sequencing approach from animals found in diverse populations representing the entire circumpolar distribution of the species. RESULTS: From a very large comprehensive catalog of SNPs detected over the entire sample set (N = 894), a total of 63,336 SNPs were selected. SNP selection accounted for SNPs evenly distributed across the entire genome (~ every 50Kb) with known minor alleles across populations world-wide. In addition, a subset of SNPs was selected to represent rare and local alleles found in Eastern Canada which could be used for ecotype and population assignments - information urgently needed for conservation planning. In addition, heterozygosity from SNPs located in the X-chromosome and genotyping call-rate of SNPs located into the SRY gene of the Y-chromosome yielded an accurate and robust sexing assessment. All SNPs were validated using a high-throughput SNP-genotyping chip. CONCLUSION: This design is now integrated into the first genome-wide commercially available genotyping platform for Rangifer tarandus. This platform would pave the way to future genomic investigation of populations for this endangered species, including estimation of genetic diversity parameters, population assignments, as well as animal sexing from genetic SNP data for non-invasive samples.

Assessing the Pathogenicity, Penetrance, and Expressivity of Putative Disease-Causing Variants in a Population Setting.

More than 100,000 genetic variants are classified as disease causing in public databases. However, the true penetrance of many of these rare alleles is uncertain and might be over-estimated by clinical ascertainment. Here, we use data from 379,768 UK Biobank (UKB) participants of European ancestry to assess the pathogenicity and penetrance of putatively clinically important rare variants. Although rare variants are harder to genotype accurately than common variants, we were able to classify as high quality 1,244 of 4,585 (27%) putatively clinically relevant rare (MAF < 1%) variants genotyped on the UKB microarray. We defined as "clinically relevant" variants that were classified as either pathogenic or likely pathogenic in ClinVar or are in genes known to cause two specific monogenic diseases: maturity-onset diabetes of the young (MODY) and severe developmental disorders (DDs). We assessed the penetrance and pathogenicity of these high-quality variants by testing their association with 401 clinically relevant traits. 27 of the variants were associated with a UKB trait, and we were able to refine the penetrance estimate for some of the variants. For example, the HNF4A c.340C>T (p.Arg114Trp) (GenBank: NM_175914.4) variant associated with diabetes is <10% penetrant by the time an individual is 40 years old. We also observed associations with relevant traits for heterozygous carriers of some rare recessive conditions, e.g., heterozygous carriers of the ERCC4 c.2395C>T (p.Arg799Trp) variant that causes Xeroderma pigmentosum were more susceptible to sunburn. Finally, we refute the previous disease association of RNF135 in developmental disorders. In conclusion, this study shows that very large population-based studies will help refine our understanding of the pathogenicity of rare genetic variants.

Genome-wide association studies for egg quality traits in White Leghorn layers using low-pass sequencing and SNP chip data.

Low-pass sequencing data have been proposed as an alternative to single nucleotide polymorphism (SNP) chips in genome-wide association studies (GWAS) of several species. However, it has not been used in layer chickens yet. This study aims at comparing the GWAS results of White Leghorn chickens using low-pass sequencing data (1×) and 54 k SNP chip data. Ten commercially relevant egg quality traits including albumen height, shell strength, shell colour, egg weight and yolk weight collected from up to 1,420 White Leghorn chickens were analysed. The results showed that the genomic heritability estimates based on low-pass sequencing data were higher than those based on SNP chip data. Although two GWAS analyses showed similar overall landscape for most traits, low-pass sequencing captured some significant SNPs that were not on the SNP chip. In GWAS analysis using 54 k SNP chip data, after including more individuals (up to 5,700), additional significant SNPs not detected by low-pass sequencing data were found. In conclusion, GWAS using low-pass sequencing data showed similar results to those with SNP chip data and may require much larger sample sizes to show measurable advantages.

Genome-wide association study of yield and related traits in common wheat under salt-stress conditions.

BACKGROUND: Soil salinization is a major threat to wheat production. It is essential to understand the genetic basis of salt tolerance for breeding and selecting new salt-tolerant cultivars that have the potential to increase wheat yield. RESULT: In this study, a panel of 191 wheat accessions was subjected to genome wide association study (GWAS) to identify SNP markers linked with adult-stage characters. The population was genotyped by Wheat660K SNP array and eight phenotype traits were investigated under low and high salinity environments for three consecutive years. A total of 389 SNPs representing 11 QTLs were significantly associated with plant height, spike number, spike length, grain number, thousand kernels weight, yield and biological mass under different salt treatments, with the phenotypic explanation rate (R2) ranging from 9.14 to 50.45%. Of these, repetitive and pleiotropic loci on chromosomes 4A, 5A, 5B and 7A were significantly linked to yield and yield related traits such as thousand kernels weight, spike number, spike length, grain number and so on under low salinity conditions. Spike length-related loci were mainly located on chromosomes 1B, 3B, 5B and 7A under different salt treatments. Two loci on chromosome 4D and 5A were related with plant height in low and high salinity environment, respectively. Three salt-tolerant related loci were confirmed to be important in two bi-parental populations. Distribution of favorable haplotypes indicated that superior haplotypes of pleiotropic loci on group-5 chromosomes were strongly selected and had potential for increasing wheat salt tolerance. A total of 14 KASP markers were developed for nine loci associating with yield and related traits to improve the selection efficiency of wheat salt-tolerance breeding. CONCLUSION: Utilizing a Wheat660K SNPs chip, QTLs for yield and its related traits were detected under salt treatment in a natural wheat population. Important salt-tolerant related loci were validated in RIL and DH populations. This study provided reliable molecular markers that could be crucial for marker-assisted selection in wheat salt tolerance breeding programs.

Exploring genetic diversity and population structure of Punjab goat breeds using Illumina 50 K SNP bead chip.

Pakistan has 35 goat breeds. Moreover, the province of Punjab has highest goat population constituting 37% of country's total population with seven goat breeds including Beetal, Daira Deen Panah, Nachi, Barbari, Teddi, Pahari, and Pothwari. The diversity study of breeds warrants the documentation of breeds particularly using genome wide panel of markers, i.e., SNP chip. The objective of the current study was to fill this gap of information. Therefore, in current study we collected total of 879 unrelated goat blood samples along with data on body weight measurements; genomic DNA was extracted, and genotyping was carried out using 50 K SNP bead chip. Quality control measures were performed in Plink 1.07. Genetic diversity was observed among studied populations using heterozygosity and pairwise FST estimates, principal component analysis, admixture analysis in Plink software with visualization in Clumpak, and constructing phylogenetic tree in Mega 7 software. Moderate to high level of heterozygosity was observed among the studied populations. Coefficient of inbreeding varied from 0.0186 ± 0.0327 in Pahari to 0.183 ± 0.0715 in Barbari. Barbari and Daira Deen Panah had quite higher level of inbreeding coefficient as compared to all other breeds with value of 0.183 ± 0.0715 and 0.1378 ± 0.0741, respectively. PCA identified three steps of subdividing the seven goat breeds at various levels of K. All the seven breeds made independent clusters at various levels of PCA. Admixture analysis revealed the distinctness of Teddi and Barbari breeds. Genetic sub-structuring was observed in the admixture patterns of Beetal breed. Moreover, high level of genetic admixture was observed in Nachi, Pahari, Pothwari, and Daira Deen Panah breeds. Admixture results were further interpreted by calculating pairwise FST values. Our results provided first insights about genetic diversity of Pakistani goat breeds based on genomic data. To conclude, the enriched goat breed diversity in Pakistan could provide valuable genetic reservoir for national breeding schemes.

Single nucleotide polymorphism associated with disease resistance in Penaeus vannamei.

Despite the considerable number of genetic markers published for Penaeus vannamei, the classification of these markers and their standardization in specific databases is still insufficient. As a consequence, access to these markers is difficult, hampering their application in genetic association studies. In this study, all previously described single nucleotide polymorphisms (SNPs) related to resistance for P. vannamei were revised, and 512 SNPs were identified and classified in detail. We observed that most of the SNPs occurred in the proteins including Toll like receptors 1 and 3, hemocyanin large and small subunits, and anti-lipopolysaccharide factors 1 and 2, allowing to propose to use them as targets in association studies involving resistance in P. vannamei. Additionally, the potential effects of the most frequent non-synonymous coding SNPs in the secondary structure of the main target proteins were evaluated using an in silico approach. These data can serve as the starting point for the development of new genetic and computational tools as well as for the design of new association studies that involve resistance in P. vannamei.

Identification of genomic regions regulating sex determination in Atlantic salmon using high density SNP data.

BACKGROUND: A complete understanding of the genetic basis for sexual determination and differentiation is necessary in order to implement efficient breeding schemes at early stages of development. Atlantic salmon belongs to the family Salmonidae of fishes and represents a species of great commercial value. Although the species is assumed to be male heterogametic with XY sex determination, the precise genetic basis of sexual development remains unclear. The complexity is likely associated to the relatively recent salmonid specific whole genome duplication that may be responsible for certain genome instability. This instability together with the capacity of the sex-determining gene to move across the genome as reported by previous studies, may explain that sexual development genes are not circumscribed to the same chromosomes in all members of the species. In this study, we have used a 220 K SNP panel developed for Atlantic salmon to identify the chromosomes explaining the highest proportion of the genetic variance for sex as well as candidate regions and genes associated to sexual development in this species. RESULTS: Results from regional heritability analysis showed that the chromosomes explaining the highest proportion of variance in these populations were Ssa02 (heritability = 0.42, SE = 0.12) and Ssa21 (heritability = 0.26, SE = 0.11). After pruning by linkage disequilibrium, genome-wide association analyses revealed 114 SNPs that were significantly associated with sex, being Ssa02 the chromosome containing a greatest number of regions. Close examination of the candidate regions evidenced important genes related to sex in other species of Class Actinopterygii, including SDY, genes from family SOX, RSPO1, ESR1, U2AF2A, LMO7, GNRH-R, DND and FIGLA. CONCLUSIONS: The combined results from regional heritability analysis and genome-wide association have provided new advances in the knowledge of the genetic regulation of sex determination in Atlantic salmon, supporting that Ssa02 is the candidate chromosome for sex in this species and suggesting an alternative population lineage in Spanish wild populations according to the results from Ssa21.

WITHDRAWN:Investigating population structure and genetic diversity of some Iranian native cattle breeds using SNP markers.

Ahead of Print article withdrawn by publisher.

Genome-wide detection of CNVs associated with beak deformity in chickens using high-density 600K SNP arrays.

Beak deformity (crossed beaks) is found in several indigenous chicken breeds including Beijing-You studied here. Birds with deformed beaks have reduced feed intake and poor production performance. Recently, copy number variation (CNV) has been examined in many species and is recognized as a source of genetic variation, especially for disease phenotypes. In this study, to unravel the genetic mechanisms underlying beak deformity, we performed genome-wide CNV detection using Affymetrix chicken high-density 600K data on 48 deformed-beak and 48 normal birds using penncnv. As a result, two and eight CNV regions (CNVRs) covering 0.32 and 2.45 Mb respectively on autosomes were identified in deformed-beak and normal birds respectively. Further RT-qPCR studies validated nine of the 10 CNVRs. The ratios of six CNVRs were significantly different between deformed-beak and normal birds (P < 0.01). Within these six regions, three and 21 known genes were identified in deformed-beak and normal birds respectively. Bioinformatics analysis showed that these genes were enriched in six GO terms and one KEGG pathway. Five candidate genes in the CNVRs were further validated using RT-qPCR. The expression of LRIG2 (leucine rich repeats and immunoglobulin like domains 2) was lower in birds with deformed beaks (P < 0.01). Therefore, the LRIG2 gene could be considered a key factor in view of its known functions and its potential roles in beak deformity. Overall, our results will be helpful for future investigations of the genomic structural variations underlying beak deformity in chickens.

Variations on a Chip: Technologies of Difference in Human Genetics Research.

In this article we examine the history of the production of microarray technologies and their role in constructing and operationalizing views of human genetic difference in contemporary genomics. Rather than the "turn to difference" emerging as a post-Human Genome Project (HGP) phenomenon, interest in individual and group differences was a central, motivating concept in human genetics throughout the twentieth century. This interest was entwined with efforts to develop polymorphic "genetic markers" for studying human traits and diseases. We trace the technological, methodological and conceptual strategies in the late twentieth century that established single nucleotide polymorphisms (SNPs) as key focal points for locating difference in the genome. By embedding SNPs in microarrays, researchers created a technology that they used to catalog and assess human genetic variation. In the process of making genetic markers and array-based technologies to track variation, scientists also made commitments to ways of describing, cataloging and "knowing" human genetic differences that refracted difference through a continental geographic lens. We show how difference came to matter in both senses of the term: difference was made salient to, and inscribed on, genetic matter(s), as a result of the decisions, assessments and choices of collaborative and hybrid research collectives in medical genomics research.

Development and validation of the Axiom(®) Apple480K SNP genotyping array.

Cultivated apple (Malus × domestica Borkh.) is one of the most important fruit crops in temperate regions, and has great economic and cultural value. The apple genome is highly heterozygous and has undergone a recent duplication which, combined with a rapid linkage disequilibrium decay, makes it difficult to perform genome-wide association (GWA) studies. Single nucleotide polymorphism arrays offer highly multiplexed assays at a relatively low cost per data point and can be a valid tool for the identification of the markers associated with traits of interest. Here, we describe the development and validation of a 487K SNP Affymetrix Axiom(®) genotyping array for apple and discuss its potential applications. The array has been built from the high-depth resequencing of 63 different cultivars covering most of the genetic diversity in cultivated apple. The SNPs were chosen by applying a focal points approach to enrich genic regions, but also to reach a uniform coverage of non-genic regions. A total of 1324 apple accessions, including the 92 progenies of two mapping populations, have been genotyped with the Axiom(®) Apple480K to assess the effectiveness of the array. A large majority of SNPs (359 994 or 74%) fell in the stringent class of poly high resolution polymorphisms. We also devised a filtering procedure to identify a subset of 275K very robust markers that can be safely used for germplasm surveys in apple. The Axiom(®) Apple480K has now been commercially released both for public and proprietary use and will likely be a reference tool for GWA studies in apple.

Developing a 670k genotyping array to tag ~2M SNPs across 24 horse breeds.

BACKGROUND: To date, genome-scale analyses in the domestic horse have been limited by suboptimal single nucleotide polymorphism (SNP) density and uneven genomic coverage of the current SNP genotyping arrays. The recent availability of whole genome sequences has created the opportunity to develop a next generation, high-density equine SNP array. RESULTS: Using whole genome sequence from 153 individuals representing 24 distinct breeds collated by the equine genomics community, we cataloged over 23 million de novo discovered genetic variants. Leveraging genotype data from individuals with both whole genome sequence, and genotypes from lower-density, legacy SNP arrays, a subset of ~5 million high-quality, high-density array candidate SNPs were selected based on breed representation and uniform spacing across the genome. Considering probe design recommendations from a commercial vendor (Affymetrix, now Thermo Fisher Scientific) a set of ~2 million SNPs were selected for a next-generation high-density SNP chip (MNEc2M). Genotype data were generated using the MNEc2M array from a cohort of 332 horses from 20 breeds and a lower-density array, consisting of ~670 thousand SNPs (MNEc670k), was designed for genotype imputation. CONCLUSIONS: Here, we document the steps taken to design both the MNEc2M and MNEc670k arrays, report genomic and technical properties of these genotyping platforms, and demonstrate the imputation capabilities of these tools for the domestic horse.

Evaluating the accuracy of genomic prediction of growth and wood traits in two Eucalyptus species and their F1 hybrids.

BACKGROUND: Genomic prediction is a genomics assisted breeding methodology that can increase genetic gains by accelerating the breeding cycle and potentially improving the accuracy of breeding values. In this study, we use 41,304 informative SNPs genotyped in a Eucalyptus breeding population involving 90 E.grandis and 78 E.urophylla parents and their 949 F1 hybrids to develop genomic prediction models for eight phenotypic traits - basic density and pulp yield, circumference at breast height and height and tree volume scored at age three and six years. We assessed the impact of different genomic prediction methods, the composition and size of the training and validation set and the number and genomic location of SNPs on the predictive ability (PA). RESULTS: Heritabilities estimated using the realized genomic relationship matrix (GRM) were considerably higher than estimates based on the expected pedigree, mainly due to inconsistencies in the expected pedigree that were readily corrected by the GRM. Moreover, the GRM more precisely capture Mendelian sampling among related individuals, such that the genetic covariance was based on the true proportion of the genome shared between individuals. PA improved considerably when increasing the size of the training set and by enhancing relatedness to the validation set. Prediction models trained on pure species parents could not predict well in F1 hybrids, indicating that model training has to be carried out in hybrid populations if one is to predict in hybrid selection candidates. The different genomic prediction methods provided similar results for all traits, therefore either GBLUP or rrBLUP represents better compromises between computational time and prediction efficiency. Only slight improvement was observed in PA when more than 5000 SNPs were used for all traits. Using SNPs in intergenic regions provided slightly better PA than using SNPs sampled exclusively in genic regions. CONCLUSIONS: The size and composition of the training set and number of SNPs used are the two most important factors for model prediction, compared to the statistical methods and the genomic location of SNPs. Furthermore, training the prediction model based on pure parental species only provide limited ability to predict traits in interspecific hybrids. Our results provide additional promising perspectives for the implementation of genomic prediction in Eucalyptus breeding programs by the selection of interspecific hybrids.