Estimates of linkage disequilibrium and effective population sizes in Chinese Merino (Xinjiang type) sheep by genome-wide SNPs

Knowledge of linkage disequilibrium (LD) is important for effective genome-wide association studies and accurate genomic prediction. Chinese Merino (Xinjiang type) is well-known fine wool sheep breed. However, the extent of LD across the genome remains unexplored. In this study, we calculated autosomal LD based on genome-wide SNPs of 635 Chinese Merino (Xinjiang type) sheep by Illumina Ovine SNP50 BeadChip. A moderate level of LD (r ²?≥?0.25) across the whole genome was observed at short distances of 0–10 kb. Further, the ancestral effective population size (N _e ) was analyzed by extent of LD and found that N _e increased with the increase of generations and declined rapidly within the most recent 50 generations, which is consistent with the history of Chinese Merino sheep breeding, initiated in 1971. We also noted that even when the effective population size was estimated across different single chromosomes, N _e only ranged from 140.36 to 183.33 at five generations in the past, exhibiting a rapid decrease compared with that at ten generations in the past. These results indicated that the genetic diversity in Chinese Merino sheep recently decreased and proper protective measures should be taken to maintain the diversity. Our datasets provided essential genetic information to track molecular variations which potentially contribute to phenotypic variation in Chinese Merino sheep.     

Genome-wide association study of body weight in Australian Merino sheep reveals an orthologous region on OAR6 to human and bovine genomic regions affecting height and weight

Background

Body weight (BW) is an important trait for meat production in sheep. Although over the past few years, numerous quantitative trait loci (QTL) have been detected for production traits in cattle, few QTL studies have been reported for sheep, with even fewer on meat production traits. Our objective was to perform a genome-wide association study (GWAS) with the medium-density Illumina Ovine SNP50 BeadChip to identify genomic regions and corresponding haplotypes associated with BW in Australian Merino sheep.

Methods

A total of 1781 Australian Merino sheep were genotyped using the medium-density Illumina Ovine SNP50 BeadChip. Among the 53 862 single nucleotide polymorphisms (SNPs) on this array, 48 640 were used to perform a GWAS using a linear mixed model approach. Genotypes were phased with hsphase; to estimate SNP haplotype effects, linkage disequilibrium blocks were identified in the detected QTL region.

Results

Thirty-nine SNPs were associated with BW at a Bonferroni-corrected genome-wide significance threshold of 1 %. One region on sheep (Ovis aries) chromosome 6 (OAR6) between 36.15 and 38.56 Mb, included 13 significant SNPs that were associated with BW; the most significant SNP was OAR6_41936490.1 (P = 2.37 × 10⁻¹⁶) at 37.69 Mb with an allele substitution effect of 2.12 kg, which corresponds to 0.248 phenotypic standard deviations for BW. The region that surrounds this association signal on OAR6 contains three genes: leucine aminopeptidase 3 (LAP3), which is involved in the processing of the oxytocin precursor; NCAPG non-SMC condensin I complex, subunit G (NCAPG), which is associated with foetal growth and carcass size in cattle; and ligand dependent nuclear receptor corepressor-like (LCORL), which is associated with height in humans and cattle.

Conclusions

The GWAS analysis detected 39 SNPs associated with BW in sheep and a major QTL region was identified on OAR6. In several other mammalian species, regions that are syntenic with this region have been found to be associated with body size traits, which may reflect that the underlying biological mechanisms share a common ancestry. These findings should facilitate the discovery of causative variants for BW and contribute to marker-assisted selection.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0142-4) contains supplementary material, which is available to authorized users.     

Merino sheep: a further look at quantitative trait loci for wool production

A quantitative trait loci (QTL) analysis of wool traits from experimental half-sib data of Merino sheep is presented. A total of 617 animals distributed in 10 families were genotyped for 36 microsatellite markers on four ovine chromosomes OAR1, OAR3, OAR4 and OAR11. The markers covering OAR3 and OAR11 were densely spaced, at an average distance of 2.8 and 1.2 cM, respectively. Body weight and wool traits were measured at first and second shearing. Analyses were conducted under three hypotheses: (i) a single QTL controlling a single trait (for multimarker regression models); (ii) two linked QTLs controlling a single trait (using maximum likelihood techniques) and (iii) a single QTL controlling more than one trait (also using maximum likelihood techniques). One QTL was identified for several wool traits on OAR1 (average curvature of fibre at first and second shearing, and clean wool yield measured at second shearing) and on OAR11 (weight and staple strength at first shearing, and coefficient of variation of fibre diameter at second shearing). In addition, one QTL was detected on OAR4 affecting weight measured at second shearing. The results of the single trait method and the two-QTL hypotheses showed an additional QTL segregating on OAR11 (for greasy fleece weight at first shearing and clean wool yield trait at second shearing). Pleiotropic QTLs (controlling more than one trait) were found on OAR1 (clean wool yield, average curvature of fibre, clean and greasy fleece weightand staple length, all measured at second shearing).     

Genome-wide association study of birth weight in sheep

Birth weight is the earliest available growth trait with considerable impacts on lamb survivability and growth performance traits. This study was conducted to perform a genome-wide association study of birth weight in a meat-type sheep. A total of 132 Lori-Bakhtiari sheep were selected based on estimated of breeding values (EBVs) for BW analyses. The selected animals were genotyped using Illumina Ovine SNP50 Bead Chip. After quality control, a total of 41 323 single-nucleotide polymorphisms (SNPs) and 130 sheep were used for subsequent analyses. Plink 1.90 beta software was used for the analyses. Seven SNPs on chromosomes 1, 16, 19 and 22 were detected based on genome-wide unadjusted P-values (P <10⁻⁶), which jointly accounted for 1.2% of total genetic variation. However, based on Bonferroni-adjusted P-values, only three SNPs on chromosome 1 had significant associations with EBVs for birth weight (P <0.05), which jointly explained 0.8% of total genetic variation. A total of seven genes were found in 50 kb intervals from the three significant SNPs on chromosome 1, but only three genes, including RAB6B (a member of RAS oncogene family), Tf serotransferrin and GIGYF2 (a GRB10 interacting GYF protein 2), could be considered as candidate genes for birth weight in future studies. The results of this study may facilitate potential use of the genes involving in growth and production traits for genetic improvement of productivity in sheep.     

Association between Expression Quantitative Trait Loci and Metabolic Traits in Two Korean Populations

Most genome-wide association studies consider genes that are located closest to single nucleotide polymorphisms (SNPs) that are highly significant for those studies. However, the significance of the associations between SNPs and candidate genes has not been fully determined. An alternative approach that used SNPs in expression quantitative trait loci (eQTL) was reported previously for Crohn’s disease; it was shown that eQTL-based preselection for follow-up studies was a useful approach for identifying risk loci from the results of moderately sized GWAS. In this study, we propose an approach that uses eQTL SNPs to support the functional relationships between an SNP and a candidate gene in a genome-wide association study. The genome-wide SNP genotypes and 10 biochemical measures (fasting glucose levels, BUN, serum albumin levels, AST, ALT, gamma GTP, total cholesterol, HDL cholesterol, triglycerides, and LDL cholesterol) were obtained from the Korean Association Resource (KARE) consortium. The eQTL SNPs were isolated from the SNP dataset based on the RegulomeDB eQTL-SNP data from the ENCODE projects and two recent eQTL reports. A total of 25,658 eQTL SNPs were tested for their association with the 10 metabolic traits in 2 Korean populations (Ansung and Ansan). The proportion of phenotypic variance explained by eQTL and non-eQTL SNPs showed that eQTL SNPs were more likely to be associated with the metabolic traits genetically compared with non-eQTL SNPs. Finally, via a meta-analysis of the two Korean populations, we identified 14 eQTL SNPs that were significantly associated with metabolic traits. These results suggest that our approach can be expanded to other genome-wide association studies.     

Genomic variants associated with the number and diameter of muscle fibers in pigs as revealed by a genome-wide association study

Muscle fiber characteristics comprise a set of complex traits that influence the mea quality and lean meat production of livestock. However, the genetic and biological mechanisms regulating muscle fiber characteristics are largely unknown in pigs. Based on a genome-wide association study (GWAS) performed on 421 Large White × Min pig F2 individuals presenting well-characterized phenotypes, this work aimed to detect genome variations and candidate genes for five muscle fiber characteristics: percentage of type I fibers (FIB1P), percentage of type IIA fibers (FIB2AP), percentage of type IIB fibers (FIB2BP), diameter of muscle fibers (DIAMF) and number of muscle fibers per unit area (NUMMF). The GWAS used the Illumina Porcine SNP60K genotypic data, which were analyzed by a mixed model. Seven and 10 single nucleotide polymorphisms (SNPs) were significantly associated with DIAMF and NUMMF, respectively (P < 1.10E-06); no SNP was significantly associated with FIB1P, FIB2AP or FIB2B. For DIAMF, the significant SNPs on chromosome 4 were located in the previously reported quantitative trait loci (QTL) interval. Because the significant SNPs on chromosome 6 were not mapped in the previously reported QTL interval, a putative novel QTL was suggested for this locus. None of the previously reported QTL intervals on chromosomes 6 and 14 harbored significant SNPs for NUMMF; thus, new potential QTLs on these two chromosomes are suggested in the present work. The most significant SNPs associated with DIAMF (ALGA0025682) and NUMMF (MARC0046984) explained 12.02% and 11.59% of the phenotypic variation of these traits, respectively. In addition, both SNPs were validated as associated with DIAMF and NUMMF in Beijing Black pigs (P < 0.01). Some candidate genes or non-coding RNAs, such as solute carrier family 44 member 5 and miR-124a-1 for DIAMF, and coiled-coil serine rich protein 2 for NUMMF, were identified based on their close location to the significant SNPs. This study revealed some genome-wide association variants for muscle fiber characteristics, and it provides valuable information to discover the genetic mechanisms controlling these traits in pigs.     

Genome-wide association study of milk production traits in a crossbred dairy sheep population using three statistical models

Milk production is one of the most important characteristics of dairy sheep, and the identification of genes affecting milk production traits is critical to understanding the genetics and improve milk production in future generations. Three statistical techniques, namely GWAS, ridge-regression BLUP and BayesC , were used to identify SNPs in significant association with three milk production traits (milk yield, fat yield and protein yield) in a crossbred dairy sheep population. The results suggested that chromosomes 1, 3, 4, 5, 7 and 11 were likely to harbor genes important to milk production because these chromosomes had the greatest top-100-SNP variance contributions on the three milk production traits. The GWAS analysis identified between 74 and 288 genome-wide significant SNP (P < 0.05) whereas the BayesCπ model revealed between six and 63 SNPs, each with >95% posterior probability of inclusion as having a non-zero association effect on at least one of the three milk production traits. Positional candidate genes for milk production in sheep were searched, based on the sheep genomic assembly OAR version 3.1, such as those which map position coincided with or was located within 0.1 Mbp of a genome-wide suggestive or significant SNP. These identified SNPs and candidate genes supported some previous findings and also added new information about genetic markers for genetic improvement of lactation in dairy sheep, but keeping in mind that the majority of these positional candidate genes are not necessarily true causative loci for these traits and future validations are thus necessary.     

Evidence of linkage between high-glycine-tyrosine keratin gene loci and wool fibre diameter in a Merino half-sib family

Candidate genes for quantitative trait loci have been studied in a Medium Peppin Merino flock. Obvious candidates for effects on wool production traits are genes for the major proteins expressed in the wool fibre, the keratin and keratin-associated protein genes. Two keratin-associated protein loci, KRTAP6 and KRTAP8, have previously been shown to be linked. The results of analyses between these two loci and production traits gave significant evidence of linkage with wool fibre diameter in one out of eight halfsib groups tested. High-glycine-tyrosine proteins (KRTAP6, 7 and 8) are known to vary considerably in abundance in wool fibres and it is possible that a gene for major effect on fibre diameter is located within the same chromosomal region as KRTAP6 and KRTAP8.     

Association Mapping for Fruit,Plant and Leaf Morphology Traits in Eggplant

An eggplant (Solanum melongena) association panel of 191 accessions, comprising a mixture of breeding lines, old varieties and landrace selections was SNP genotyped and phenotyped for key breeding fruit and plant traits at two locations over two seasons. A genome-wide association (GWA) analysis was performed using the mixed linear model, which takes into account both a kinship matrix and the sub-population membership of the accessions. Overall, 194 phenotype/genotype associations were uncovered, relating to 30 of the 33 measured traits. These associations involved 79 SNP loci mapping to 39 distinct chromosomal regions distributed over all 12 eggplant chromosomes. A comparison of the map positions of these SNPs with those of loci derived from conventional linkage mapping showed that GWA analysis both validated many of the known controlling loci and detected a large number of new marker/trait associations. Exploiting established syntenic relationships between eggplant chromosomes and those of tomato and pepper recognized orthologous regions in ten eggplant chromosomes harbouring genes influencing breeders’ traits.     

Genetic Control of Individual Differences in Gene-Specific Methylation in Human Brain

We have observed extensive interindividual differences in DNA methylation of 8590 CpG sites of 6229 genes in 153 human adult cerebellum samples, enriched in CpG island “shores” and at further distances from CpG islands. To search for genetic factors that regulate this variation, we performed a genome-wide association study (GWAS) mapping of methylation quantitative trait loci (mQTLs) for the 8590 testable CpG sites. cis association refers to correlation of methylation with SNPs within 1 Mb of a CpG site. 736 CpG sites showed phenotype-wide significant cis association with 2878 SNPs (after permutation correction for all tested markers and methylation phenotypes). In trans analysis of methylation, which tests for distant regulation effects, associations of 12 CpG sites and 38 SNPs remained significant after phenotype-wide correction. To examine the functional effects of mQTLs, we analyzed 85 genes that were with genetically regulated methylation we observed and for which we had quality gene expression data. Ten genes showed SNP-methylation-expression three-way associations—the same SNP simultaneously showed significant association with both DNA methylation and gene expression, while DNA methylation was significantly correlated with gene expression. Thus, we demonstrated that DNA methylation is frequently a heritable continuous quantitatively variable trait in human brain. Unlike allele-specific methylation, genetic polymorphisms mark both cis- and trans-regulatory genetic sites at measurable distances from their CpG sites. Some of the genetically regulated DNA methylation is directly connected with genetically regulated gene expression variation.     

Genome-wide association mapping of salinity tolerance in rice (Oryza sativa)

Salinity tolerance in rice is highly desirable to sustain production in areas rendered saline due to various reasons. It is a complex quantitative trait having different components, which can be dissected effectively by genome-wide association study (GWAS). Here, we implemented GWAS to identify loci controlling salinity tolerance in rice. A custom-designed array based on 6,000 single nucleotide polymorphisms (SNPs) in as many stress-responsive genes, distributed at an average physical interval of <100 kb on 12 rice chromosomes, was used to genotype 220 rice accessions using Infinium high-throughput assay. Genetic association was analysed with 12 different traits recorded on these accessions under field conditions at reproductive stage. We identified 20 SNPs (loci) significantly associated with Na⁺/K⁺ ratio, and 44 SNPs with other traits observed under stress condition. The loci identified for various salinity indices through GWAS explained 5–18% of the phenotypic variance. The region harbouring Saltol, a major quantitative trait loci (QTLs) on chromosome 1 in rice, which is known to control salinity tolerance at seedling stage, was detected as a major association with Na⁺/K⁺ ratio measured at reproductive stage in our study. In addition to Saltol, we also found GWAS peaks representing new QTLs on chromosomes 4, 6 and 7. The current association mapping panel contained mostly indica accessions that can serve as source of novel salt tolerance genes and alleles. The gene-based SNP array used in this study was found cost-effective and efficient in unveiling genomic regions/candidate genes regulating salinity stress tolerance in rice.     

Genomic selection and complex trait prediction using a fast EM algorithm applied to genome-wide markers

Background  

The information provided by dense genome-wide markers using high throughput technology is of considerable potential in human disease studies and livestock breeding programs. Genome-wide association studies relate individual single nucleotide polymorphisms (SNP) from dense SNP panels to individual measurements of complex traits, with the underlying assumption being that any association is caused by linkage disequilibrium (LD) between SNP and quantitative trait loci (QTL) affecting the trait. Often SNP are in genomic regions of no trait variation. Whole genome Bayesian models are an effective way of incorporating this and other important prior information into modelling. However a full Bayesian analysis is often not feasible due to the large computational time involved.     

High-resolution melting analysis for SNP genotyping and mapping in tetraploid alfalfa (Medicago sativa L.)

Single nucleotide polymorphisms (SNPs) represent the most abundant type of genetic polymorphism in plant genomes. SNP markers are valuable tools for genetic analysis of complex traits of agronomic importance, linkage and association mapping, genome-wide selection, map-based cloning, and marker-assisted selection. Current challenges for SNP genotyping in polyploid outcrossing species include multiple alleles per loci and lack of high-throughput methods suitable for variant detection. In this study, we report on a high-resolution melting (HRM) analysis system for SNP genotyping and mapping in outcrossing tetraploid genotypes. The sensitivity and utility of this technology is demonstrated by identification of the parental genotypes and segregating progeny in six alfalfa populations based on unique melting curve profiles due to differences in allelic composition at one or multiple loci. HRM using a 384-well format is a fast, consistent, and efficient approach for SNP discovery and genotyping, useful in polyploid species with uncharacterized genomes. Possible applications of this method include variation discovery, analysis of candidate genes, genotyping for comparative and association mapping, and integration of genome-wide selection in breeding programs.     

Genome Wide Analysis of Flowering Time Trait in Multiple Environments via High-Throughput Genotyping Technique in Brassica napus L.

The prediction of the flowering time (FT) trait in Brassica napus based on genome-wide markers and the detection of underlying genetic factors is important not only for oilseed producers around the world but also for the other crop industry in the rotation system in China. In previous studies the low density and mixture of biomarkers used obstructed genomic selection in B. napus and comprehensive mapping of FT related loci. In this study, a high-density genome-wide SNP set was genotyped from a double-haploid population of B. napus. We first performed genomic prediction of FT traits in B. napus using SNPs across the genome under ten environments of three geographic regions via eight existing genomic predictive models. The results showed that all the models achieved comparably high accuracies, verifying the feasibility of genomic prediction in B. napus. Next, we performed a large-scale mapping of FT related loci among three regions, and found 437 associated SNPs, some of which represented known FT genes, such as AP1 and PHYE. The genes tagged by the associated SNPs were enriched in biological processes involved in the formation of flowers. Epistasis analysis showed that significant interactions were found between detected loci, even among some known FT related genes. All the results showed that our large scale and high-density genotype data are of great practical and scientific values for B. napus. To our best knowledge, this is the first evaluation of genomic selection models in B. napus based on a high-density SNP dataset and large-scale mapping of FT loci.     

IGFBP-3基因多态性及其与中国美利奴羊部分羊毛性状的关联性分析

采用PCR-SSCP方法对中国美利奴羊和哈萨克羊中IGFBP-3基因的多态性进行了检测, 并对不同基因型与中国美利奴羊部分羊毛性状间的关联性进行了分析。结果在位于内含子1区的一段178 bp的扩增产物经SSCP分析后出现了3种基因型, 基因型AA、AB和BB及等位基因A、B在中国美利奴羊中的频率分别为0.70、0.24、0.06和0.82、0.18; 在哈萨克羊中的频率分别为0.87、0.13、0.00和0.93、0.07。序列分析发现: 在该序列的122位碱基表现多态性 (g.122 G>T)。所研究的两个群体在该位点上均处于Hardy-Weinberg不平衡状态(P<0.01)。不同基因型对部分羊毛性状有一定的影响: 不同基因型个体在剪毛后体重和净毛率上没有明显差异。AA、AB及BB基因型个体的羊毛伸直长度逐渐变短, 其中AA与AB基因型之间差异极显著(P<0.01)。AA型个体的剪毛量和羊毛密度要明显低于AB型(P<0.01)和BB型个体(P<0.05); 羊毛纤维直径则明显高于AB型(P<0.01)和BB型(P<0.05)个体。     

Confirmation and fine‐mapping of clinical mastitis and somatic cell score QTL in Nordic Holstein cattle

A genome‐wide association study of 2098 progeny‐tested Nordic Holstein bulls genotyped for 36 387 SNPs on 29 autosomes was conducted to confirm and fine‐map quantitative trait loci (QTL) for mastitis traits identified earlier using linkage analysis with sparse microsatellite markers in the same population. We used linear mixed model analysis where a polygenic genetic effect was fitted as a random effect and single SNPs were successively included as fixed effects in the model. We detected 143 SNP‐by‐trait significant associations (P < 0.0001) on 20 chromosomes affecting mastitis‐related traits. Among them, 21 SNP‐by‐trait combinations exceeded the genome‐wide significant threshold. For 12 chromosomes, both the present association study and the previous linkage study detected QTL, and of these, six were in the same chromosomal locations. Strong associations of SNPs with mastitis traits were observed on bovine autosomes 6, 13, 14 and 20. Possible candidate genes for these QTL were identified. Identification of SNPs in linkage disequilibrium with QTL will enable marker‐based selection for mastitis resistance. The candidate genes identified should be further studied to detect candidate polymorphisms underlying these QTL.     

Identification of favorable SNP alleles and candidate genes responsible for inflorescence-related traits via GWAS in chrysanthemum

Key message

81 SNPs were identified for three inflorescence-related traits, in which 15 were highly favorable. Two dCAPS markers were developed for future MAS breeding, and six candidate genes were predicted.

Abstract

Chrysanthemum is a leading ornamental species worldwide and demonstrates a wealth of morphological variation. Knowledge about the genetic basis of its phenotypic variation for key horticultural traits can contribute to its effective management and genetic improvement. In this study, we conducted a genome-wide association study (GWAS) based on two years of phenotype data and a set of 92,617 single nucleotide polymorphisms (SNPs) using a panel of 107 diverse cut chrysanthemums to dissect the genetic control of three inflorescence-related traits. A total of 81 SNPs were significantly associated with the three inflorescence-related traits (capitulum diameter, number of ray florets and flowering time) in at least one environment, with an individual allele explaining 22.72–38.67% of the phenotypic variation. Fifteen highly favorable alleles were identified for the three target traits by computing the phenotypic effect values for the stable associations detected in 2 year-long trials at each locus. Dosage pyramiding effects of the highly favorable SNP alleles and significant linear correlations between highly favorable allele numbers and corresponding phenotypic performance were observed. Two highly favorable SNP alleles correlating to flowering time and capitulum diameter were converted to derived cleaved amplified polymorphic sequence (dCAPS) markers to facilitate future breeding. Finally, six putative candidate genes were identified that contribute to flowering time and capitulum diameter. These results serve as a foundation for analyzing the genetic mechanisms underlying important horticultural traits and provide valuable insights into molecular marker-assisted selection (MAS) in chrysanthemum breeding programs.

     

小麦根部耐盐性状全基因组关联分析

为了解小麦耐盐相关性状的遗传机理,挖掘与小麦耐盐性显著相关的SNP位点及候选基因,本研究利用浓度200 mmol/L的NaCl溶液和正常营养液对全国300份小麦品种(系)进行耐盐性试验,并利用小麦90 K芯片对分布于小麦全基因组的16650个SNP,采用Q+K关联混合模型对小麦最长根长、根干重、根鲜重、根平均直径、根尖...