An imputation‐based genome‐wide association study on traits related to male reproduction in a White Duroc × Erhualian F2 population

Boar reproductive traits are economically important for the pig industry. Here we conducted a genome‐wide association study (GWAS) for 13 reproductive traits measured on 205 F₂ boars at day 300 using 60 K single nucleotide polymorphism (SNP) data imputed from a reference panel of 1200 pigs in a White Duroc × Erhualian F₂ intercross population. We identified 10 significant loci for seven traits on eight pig chromosomes (SSC). Two loci surpassed the genome‐wide significance level, including one for epididymal weight around 60.25 Mb on SSC7 and one for semen temperature around 43.69 Mb on SSC4. Four of the 10 significant loci that we identified were consistent with previously reported quantitative trait loci for boar reproduction traits. We highlighted several interesting candidate genes at these loci, including APN, TEP1, PARP2, SPINK1 and PDE1C. To evaluate the imputation accuracy, we further genotyped nine GWAS top SNPs using PCR restriction fragment length polymorphism or Sanger sequencing. We found an average of 91.44% of genotype concordance, 95.36% of allelic concordance and 0.85 of r² correlation between imputed and real genotype data. This indicates that our GWAS mapping results based on imputed SNP data are reliable, providing insights into the genetic basis of boar reproductive traits.     

Genetic and genomic analyses for predicted methane‐related traits in Japanese Black steers

The objectives of this study were to estimate genetic parameters and to perform a genome‐wide association study (GWAS) for predicted methane‐related traits in Japanese Black steers. The methane production and yield traits were predicted using on‐farm measurable traits, such as dry matter intake and average daily gain. A total of 4,578 Japanese Black steers, which were progenies of 362 sires genotyped with imputed 551,995 single nucleotide polymorphisms (SNPs), had phenotypes of predicted methane‐related traits during the total fattening period (52 weeks). For the estimation of genetic parameters, the estimated heritabilities were moderate (ranged from 0.57 to 0.60). In addition, the estimated genetic correlations of methane production traits with most of carcass traits and feed‐efficiency traits were unfavorable, but those of methane yield traits were favorable or low. For the GWAS, no genome‐wide significant SNP was detected, but a total of four quantitative trait locus (QTL) regions that explained more than 5.0% of genetic variance were localized on the genome, and some candidate genes associated with growth and feed‐efficiency traits were located on the regions. Our results suggest that the predicted methane‐related traits are heritable and some QTL regions for the traits are localized on the genome in Japanese Black steers.     

Genome‐wide association study for feedlot average daily gain in Nellore cattle (Bos indicus)

The genome‐wide association study (GWAS) results are presented for average daily gain (ADG) in Nellore cattle. Phenotype of 720 male Bos indicus animals with information of ADG in feedlots and 354 147 single‐nucleotide polymorphisms (SNPs) obtained from a database added by information from Illumina Bovine HD (777 962 SNPs) and Illumina BovineSNP50 (54 609) by imputation were used. After quality control and imputation, 290 620 SNPs remained in the association analysis, using R package Genome‐wide Rapid Association using Mixed Model and Regression method GRAMMAR‐Gamma. A genomic region with six significant SNPs, at Bonferroni‐corrected significance, was found on chromosome 3. The most significant SNP (rs42518459, BTA3: 85849977, p = 9.49 × 10^?8) explained 5.62% of the phenotypic variance and had the allele substitution effect of ?0.269 kg/day. Important genes such as PDE4B, LEPR, CYP2J2 and FGGY are located near this region, which is overlapped by 12 quantitative trait locus (QTLs) described for several production traits. Other regions with markers with suggestive effects were identified in BTA6 and BTA10. This study showed regions with major effects on ADG in Bos indicus in feedlots. This information may be useful to increase the efficiency of selecting this trait and to understand the physiological processes involved in its regulation.     

Pool‐based genome‐wide association study identified novel candidate regions on BTA9 and 14 for oleic acid percentage in Japanese Black cattle

Fatty acid composition is an important indicator of beef quality. The objective of this study was to search the potential candidate region for fatty acid composition. We performed pool‐based genome‐wide association studies (GWAS) for oleic acid percentage (C18:1) in a Japanese Black cattle population from the Hyogo prefecture. GWAS analysis revealed two novel candidate regions on BTA9 and BTA14. The most significant single nucleotide polymorphisms (SNPs) in each region were genotyped in a population (n = 899) to verify their effect on C18:1. Statistical analysis revealed that both SNPs were significantly associated with C18:1 (p = .0080 and .0003), validating the quantitative trait loci (QTLs) detected in GWAS. We subsequently selected VNN1 and LYPLA1 genes as candidate genes from each region on BTA9 and BTA14, respectively. We sequenced full‐length coding sequence (CDS) of these genes in eight individuals and identified a nonsynonymous SNP T66M on VNN1 gene as a putative candidate polymorphism. The polymorphism was also significantly associated with C18:1, but the p value (p = .0162) was higher than the most significant SNP on BTA9, suggesting that it would not be responsible for the QTL. Although further investigation will be needed to determine the responsible gene and polymorphism, our findings would contribute to development of selective markers for fatty acid composition in the Japanese Black cattle of Hyogo.     

Genome‐wide association studies reveal additional related loci for fatty acid composition in a Duroc pig multigenerational population

The aim of the present study was to detect quantitative trait loci affecting fatty acid composition in back fat and intramuscular fat in a Duroc pig population comprising seventh‐generation pedigrees using genome‐wide association studies (GWAS). In total, 305 animals were genotyped using single nucleotide polymorphisms (SNPs) array and five selected SNPs from regions containing known candidate genes related to fatty acid synthesis or metabolism. In total, 24 genome‐wide significant SNP regions were detected in 12 traits, and 76 genome‐wide suggestive SNP regions were detected in 33 traits. The Sus scrofa chromosome (SSC) 7 at 10.3 Mb was significantly associated with C17:0 in intramuscular fat, while the SSC9 at 13.6 Mb was significantly associated with C14:0 in intramuscular fat. The SSC12 at 1.0 Mb was significantly associated with C14:0 in back fat and the SSC14 at 121.0 Mb was significantly associated with C18:0 in intramuscular fat. These regions not only replicated previously reported loci containing some candidate genes involved in fatty acid composition (fatty acid synthase and stearoyl‐CoA desaturase) but also included several additional related loci.     

Detection of candidate polymorphisms around the QTL for fat area ratio to rib eye area on BTA7 using whole‐genome resequencing in Japanese Black cattle

In our previous study, we performed genome‐wide association study (GWAS) to identify the genomic region associated with Fat area ratio to rib eye area (FAR) and detected a candidate in BTA7 at 10–30 Mbp. The present study aims to comprehensively detect all polymorphisms in the candidate region using whole‐genome resequencing data. Based on whole‐genome resequencing of eight animals, we detected 127,090 polymorphisms within the region. Of these, 31,945 were located within the genes. We further narrowed the polymorphisms to 6,044 with more than five allele differences between the high and low FAR groups that were located within 179 genes. We subsequently investigated the functions of these genes and selected 170 polymorphisms in eight genes as possible candidate polymorphisms. We focused on SLC27A6 K81M as a putative candidate polymorphism. We genotyped the SNP in a Japanese Black population (n = 904) to investigate the effect on FAR. Analysis of variance revealed that SLC27A6 K81M had a lower p‐value (p = .0009) than the most significant SNP in GWAS (p = .0049). Although only SLC27A6 K81M was verified in the present study, subsequent verification of the remaining candidate genes and polymorphisms could lead to the identification of genes and polymorphisms responsible for FAR.     

Significance testing and genomic inflation factor using high‐density genotypes or whole‐genome sequence data

Significance testing for genome‐wide association study (GWAS) with increasing SNP density up to whole‐genome sequence data (WGS) is not straightforward, because of strong LD between SNP and population stratification. Therefore, the objective of this study was to investigate genomic control and different significance testing procedures using data from a commercial pig breeding scheme. A GWAS was performed in GCTA with data of 4,964 Large White pigs using medium density, high density or imputed whole‐genome sequence data, fitting a genomic relationship matrix based on a leave‐one–chromosome‐out approach to account for population structure. Subsequently, genomic inflation factors were assessed on whole‐genome level and the chromosome level. To establish a significance threshold, permutation testing, Bonferroni corrections using either the total number of SNPs or the number of independent chromosome fragments, and false discovery rates (FDR) using either the Benjamini–Hochberg procedure or the Benjamini and Yekutieli procedure were evaluated. We found that genomic inflation factors did not differ between different density genotypes but do differ between chromosomes. Also, the leave‐one‐chromosome‐out approach for GWAS or using the pedigree relationships did not account appropriately for population stratification and gave strong genomic inflation. Regarding different procedures for significance testing, when the aim is to find QTL regions that are associated with a trait of interest, we recommend applying the FDR following the Benjamini and Yekutieli approach to establish a significance threshold that is adjusted for multiple testing. When the aim is to pinpoint a specific mutation, the more conservative Bonferroni correction based on the total number of SNPs is more appropriate, till an appropriate method is established to adjust for the number of independent tests.     

Genome‐wide association study for egg production and quality in layer chickens

Discovery of genes with large effects on economically important traits has for many years been of interest to breeders. The development of SNP panels which cover the whole genome with high density and, more importantly, that can be genotyped on large numbers of individuals at relatively low cost, has opened new opportunities for genome‐wide association studies (GWAS). The objective of this study was to find genomic regions associated with egg production and quality traits in layers using analysis methods developed for the purpose of whole genome prediction. Genotypes on over 4500 birds and phenotypes on over 13 000 hens from eight generations of a brown egg layer line were used. Birds were genotyped with a custom 42K Illumina SNP chip. Recorded traits included two egg production and 11 egg quality traits (puncture score, albumen height, yolk weight and shell colour) at early and late stages of production, as well as body weight and age at first egg. Egg weight was previously analysed by Wolc et al. ( 2012 ). The Bayesian whole genome prediction model – BayesB (Meuwissen et al. 2001 ) was used to locate 1 Mb regions that were most strongly associated with each trait. The posterior probability of a 1 Mb window contributing to genetic variation was used as the criterion for suggesting the presence of a quantitative trait locus (QTL) in that window. Depending upon the trait, from 1 to 7 significant (posterior probability >0.9) 1 Mb regions were found. The largest QTL, a region explaining 32% of genetic variance, was found on chr4 at 78 Mb for body weight but had pleiotropic effects on other traits. For the other traits, the largest effects were much smaller, explaining <7% of genetic variance, with regions on chromosomes 2, 12 and 17 explaining above 5% of genetic variance for albumen height, shell colour and egg production, respectively. In total, 45 of 1043 1 Mb windows were estimated to have a non‐zero effect with posterior probability > 0.9 for one or more traits.     

Genome‐wide association study for carcass traits,fatty acid composition,chemical composition,sugar, and the effects of related candidate genes in Japanese Black cattle

We performed a genome‐wide association study (GWAS) and candidate gene analysis to: (i) evaluate the effectiveness of the GWAS in our small population by performing GWAS for carcass weight (CW) and fatty acid composition; (ii) detect novel candidate regions affecting non‐CW carcass traits, chemical composition and sugar; and (iii) evaluate the association of the candidate genes previously detected in CW and fatty acid composition with other economically important traits. A total of 574 Japanese Black cattle and 40 657 Single nucleotide polymorphisms were used. In addition, candidate gene analyses were performed to evaluate the association of three CW‐related genes and two fatty acid‐related genes with carcass traits, fatty acid composition, chemical composition and sugar. The significant regions with the candidate genes were detected for CW and fatty acid composition, and these results showed that a significant region would be detectable despite the small sample size. The novel candidate regions were detected on BTA23 for crude protein and on BTA19 for fructose. CW‐related genes associated with the rib‐eye area and fatty acid composition were identified, and fatty acid‐related genes had no relationship with other traits. Moreover, the favorable allele of CW‐related genes had an unfavorable effect on fatty acid composition.     

Genome‐wide association studies for two exterior traits in Chinese Dongxiang spotted pigs

Pigs show extensive variation in exterior appearance. This variation has been explored as one of the selection targets to form breeding features in the pig industry. In this study, a customized Affymetrix Axiom Pig1.4M array plate was used to conduct genome‐wide association studies (GWAS) for two exterior traits—spotted coat color (SC) and facial type (FT)—in Chinese Dongxiang spotted pigs. Two and 12 single nucleotide polymorphisms (SNPs) were identified to be associated with SC and FT at the 5% genome‐wide significant level, respectively. Of these SNPs, two associated with SC were located around the DACH1 gene on Sus Scrofa chromosome (SSC)11. Eleven SNPs associated with FT were located within a 7.68 Mb region (29.03–36.71 Mb) on SSC7. Based on the GWAS results and the biological functions of genes, we highlight EDNRB as a candidate gene for SC and HMGA1 and RPS10 as the potential genes affecting facial variation. The findings contribute to the final characterization of causative genes and mutations underlying the effects of the SSC7 and SSC11 loci and improve our understanding of the genetic basis of phenotypic variation in Chinese indigenous pigs.     

A genome‐wide SNP scan in a porcine Large White × Minzhu intercross population reveals a locus influencing muscle mass on chromosome 2

A high‐density single nucleotide polymorphism (SNP) array containing 62 163 markers was employed for a genome‐wide association study (GWAS) to identify variants associated with lean meat in ham (LMH, %) and lean meat percentage (LMP, %) within a porcine Large White × Minzhu intercross population. For each individual, LMH and LMP were measured after slaughter at the age of 240 ± 7 days. A total of 557 F2 animals were genotyped. The GWAS revealed that 21 SNPs showed significant genome‐wide or chromosome‐wide associations with LMH and LMP by the Genome‐wide Rapid Association using Mixed Model and Regression‐Genomic Control approach. Nineteen significant genome‐wide SNPs were mapped to the distal end of Sus Scrofa Chromosome (SSC) 2, where a major known gene responsible for muscle mass, IGF2 is located. A conditioned analysis, in which the genotype of the strongest associated SNP is included as a fixed effect in the model, showed that those significant SNPs on SSC2 were derived from a single quantitative trait locus. The two chromosome‐wide association SNPs on SSC1 disappeared after conditioned analysis suggested the association signal is a false association derived from using a F2 population. The present result is expected to lead to novel insights into muscle mass in different pig breeds and lays a preliminary foundation for follow‐up studies for identification of causal mutations for subsequent application in marker‐assisted selection programs for improving muscle mass in pigs.     

基于单倍型肉牛屠宰性状全基因组关联分析研究

单倍型标记与数量性状基因座(quantitative trait loci，QTL)之间具有较强的连锁不平衡(linkage disequilibrium，LD)关系，在基因定位和因果突变鉴定方面具有较高的应用价值。为了评估单倍型标记在基因组研究中的作用，本研究在华西牛资源群体中，选取该群体于2008—2021年间屠宰的共计1 478头平均月龄为24个月的个体进行研究，其中公牛1 333头，母牛145头。利用770K高密度芯片数据，基于LD阈值(r²>0.3)及固定单核苷酸多态(single nucleotide polymorphism,SNP)个数(5个连续SNP)两种方法进行单倍型构建，分别采用单位点SNP标记和两种单倍型标记共3种标记，基于GCTA的混合线性模型(mixed linear model,MLM)，开展宰前活重(LW)和屠宰率(DP)等屠宰性状的全基因组关联分析(genome-wide association study，GWAS)，定位影响屠宰性状的显著(P<0.05) SNPs、单倍型块和候选基因，同时比较3种标记的GWAS结果，评估3种标记的优劣。结果显示，3种标记在全基因组范围内共找到16个的显著SNPs及单倍型区域，主要分布于1、5、6、14、16、17和28号染色体上，同时鉴定到FAM184B、PPM1K、LCORL、RIMS2等10个与屠宰性状相关的候选基因，其中，基于SNP标记方法鉴定到的3个候选基因，在利用基于单倍型标记的方法中也鉴定到，且单倍型鉴定到的显著性位点或区域大多位于基因内部。在两种单倍型构建方法中，与基于固定SNP个数构建单倍型进行GWAS相比，基于LD阈值的构建方法鉴定到了更多候选基因。本研究结果表明，以单倍型开展GWAS可以综合考虑SNP位点间连锁关系，能较好地揭示复杂性状的遗传结构。     

Genome‐wide association studies revealed candidate genes for tail fat deposition and body size in the Hulun Buir sheep

Fat‐tailed sheep have a unique characteristic of depositing fat in their tails. In the present study, we conducted genome‐wide association studies (GWAS) on traits related to tail fat deposition and body size in the Hulun Buir sheep. A total number of 300 individuals belonging to two fat‐tailed lines of the Hulun Buir sheep breed genotyped with the Ovine Infinium HD SNP BeadChip were included in the current study. Two mixed models, one for continuous and one for binary phenotypic traits, were employed to analyse ten traits, that is, body length (BL), body height (BH), chest girth (CG), tail length (TL), tail width (TW), tail circumference (TC), carcass weight (CW), tail fat weight (TF), ratio of CW to TF (RCT) and tail type (TT). We identified 7, 6, 7, 2, 10 and 1 SNPs significantly associated with traits TF, CW, RCT, TW, TT and CG, respectively. Their associated genomic regions harboured 42 positional candidate genes. Out of them, 13 candidate genes including SMURF2, FBF1, DTNBP1, SETD7 and RBM11 have been associated with fat metabolism in sheep. The RBM11 gene has already been identified in a previous study on signatures of selection in this specific sheep population. Two more genes, that is, SMARCA5 and GAB1 were associated with body size in sheep. The present study has identified candidate genes that might be implicated in tail fat deposition and body size in sheep.     

Genome-wide linkage and QTL mapping in porcine F2 families generated from Pietrain, Meishan and Wild Boar crosses

Three informative pig F₂ families based on European Wild Boar (W), Meishan (M) and Pietrain (P) crosses have been used for genome‐wide linkage and quantitative trait loci (QTL) analysis. Altogether 129 microsatellites, 56 type I loci and 46 trait definitions (specific to growth, fattening, fat deposition, muscling, meat quality, stress resistance and body conformation) were included in the study. In the linkage maps of M × P, W × P and W × M families, average spacing of markers were 18.4, 19.7 and 18.8 cM, the numbers of informative meioses were 582, 534 and 625, and the total lengths of autosomes measured were 27.3, 26.0 and 26.2 Morgan units, respectively. Maternal maps were on average 1.3 times longer than paternal maps. QTLs contributing more than 3% of F₂ phenotypic variance could be identified at p < 0.05 chromosome‐wide level. Differences in the numbers and positions of QTLs were observed between families. Genome‐wide significant QTL effects were mapped for growth and fattening traits on eight chromosomes (1, 2, 4, 13, 14, 17, 18 and X), for fat deposition traits on seven chromosomes (1, 2, 3, 4, 6, 7 and X), for muscling traits on 11 chromosomes (1, 2, 3, 4, 6, 7, 8, 12, 14, 15 and X), for meat quality and stress resistance traits on seven chromosomes (2, 3, 6, 13, 16, 18 and X), and QTLs for body‐conformation traits were detected on 14 chromosomes. Closely correlated traits showed similar QTL profiles within families. Major QTL effects for meat quality and stress resistance traits were found on SSC6 in the interval RYR1‐A1BG in the W × P and M × P families, and could be attributed to segregation of the RYR1 allele T derived from Pietrain, whereas no effect in the corresponding SSC6 interval was found in family W × M, where Wild Boar and Meishan both contributed the RYR1 allele C. QTL positions were mostly similar in two of the three families for body conformation traits and for growth, fattening, fat deposition and muscling traits, especially on SSC4 (interval SW1073‐NGFB). QTLs with large effects were also mapped on SSC7 in the major histocompatibility complex (MHC) (interval CYP21A2‐S0102) and affected body length, weight of head and many other traits. The identification of DNA variants in genes causative for the QTLs requires further fine mapping of QTL intervals and a positional cloning. However, for these subsequent steps, the genome‐wide QTL mapping in F₂ families represents an essential starting point and is therefore significant for animal breeding.     

Whole‐genome resequencing to identify candidate genes for the QTL for oleic acid percentage in Japanese Black cattle

In our previous study, we detected a QTL for the oleic acid percentage (C18:1) on BTA9 in Japanese Black cattle through a genome‐wide association study (GWAS). In this study, we performed whole‐genome resequencing on eight animals with higher and lower C18:1 to identify candidate polymorphisms for the QTL. A total of 39,658 polymorphisms were detected in the candidate region, which were narrowed to 1993 polymorphisms within 23 genes based on allele differences between the high and low C18:1 groups. We subsequently selected three candidate genes, that is, CYB5R4, MED23, and VNN1, among the 23 genes based on their function in fatty acid metabolism. In each candidate gene, three SNPs, that is, CYB5R4 c.*349G > T, MED23 c.3700G > A, and VNN1 c.197C > T, were selected as candidate SNPs to verify their effect on C18:1 in a Japanese Black cattle population (n = 889). The statistical analysis showed that these SNPs were significantly associated with C18:1 (p < 0.05), suggesting that they were candidates for the QTL. In conclusion, we successfully narrowed the candidates for the QTL by detecting possible polymorphisms located within the candidate region. It is expected that the responsible polymorphism can be identified by demonstrating their effect on the gene's function.     

Weighted single‐step genome‐wide association study and pathway analyses for feed efficiency traits in Nellore cattle

The aim was to conduct a weighted single‐step genome‐wide association study to detect genomic regions and putative candidate genes related to residual feed intake, dry matter intake, feed efficiency (FE), feed conversion ratio, residual body weight gain, residual intake and weight gain in Nellore cattle. Several protein‐coding genes were identified within the genomic regions that explain more than 0.5% of the additive genetic variance for these traits. These genes were associated with insulin, leptin, glucose, protein and lipid metabolisms; energy balance; heat and oxidative stress; bile secretion; satiety; feed behaviour; salivation; digestion; and nutrient absorption. Enrichment analysis revealed functional pathways (p‐value < .05) such as neuropeptide signalling (GO:0007218), negative regulation of canonical Wingless/Int‐1 (Wnt) signalling (GO:0090090), bitter taste receptor activity (GO:0033038), neuropeptide hormone activity (GO:0005184), bile secretion (bta04976), taste transduction (bta0742) and glucagon signalling pathway (bta04922). The identification of these genes, pathways and their respective functions should contribute to a better understanding of the genetic and physiological mechanisms regulating Nellore FE‐related traits.     

Combined approaches to identify genomic regions involved in phenotypic differentiation between low divergent breeds: Application in Sardinian sheep populations

Selective breeding has led to modifications in the genome of many livestock breeds. In this study, we identified the genomic regions that may explain some of the phenotypic differences between two closely related breeds from Sardinia. A total of 44 animals, 20 Sardinian Ancestral Black (SAB) and 24 Sardinian White (SW), were genotyped using the Illumina Ovine 50K array. A total of 68, 38 and 15 significant markers were identified using the case–control genome‐wide association study (GWAS), the Bayesian population differentiation analysis (F_ST) and the Rsb metric, respectively. Comparisons among the approaches revealed a total of 22 overlapping markers between GWAS and F_ST and one marker between GWAS and Rsb. Three markers detected by Rsb were also located near (<2 Mb) to highly significant regions identified by GWAS and F_ST analyses. Moreover, one candidate marker identified by GWAS and F_ST approaches was located in a run of homozygosity island that was shared by both breeds. We identified several genes involved in many phenotypic differences (such as stature and growth, reproduction, ear size, coat colour, behaviour) between the two analysed breeds. This study shows that combining several genome‐wide approaches could improve discovery of regions involved in the variability of breeding traits and responsible for the phenotypic diversity even between closely related breeds. Overall, the combination of such genome‐wide methods can be extended to other livestock breeds that share between them a similar genetic background, to understand the process that shapes the patterns of genetic variability between closely related populations.     

Genome‐wide study on intramuscular fat in Italian Large White pig breed using the PorcineSNP60 BeadChip

Genome‐wide association study results are presented for intramuscular fat in Italian Large White pig breed. A total of 886 individuals were genotyped with PorcineSNP60 BeadChip. After quality control performed with plink software and in R environment, 49 208 markers remained for the association analysis. The genome‐wide association studies was conducted using linear mixed model implemented in GenABEL. We detected seven new SNPs of genes till now not found associated to intramuscular fat (IMF). Three markers map in a wide intergenic region rich of QTL linked to fat traits, one map 388 kb upstream the gene SDK1, one map inside PPP3CA gene, one inside SCPEP1 gene and the last is not mapped in the porcine genome yet. Associations here presented indicate a moderate effect of these genes on IMF. In particular, PPP3CA, that is involved in the oxidative metabolism of skeletal muscle, could be considerated as an interesting candidate gene for IMF content in pigs. However, further studies are needed to clarify the role of these genes on the physiological processes involved in IMF regulation. These results may be useful to control this trait that is important in terms of nutritional, technological and organoleptic characteristics of fresh meat and processed products.     

A genome‐wide association study for fat‐related traits computed by image analysis in Japanese Black cattle

The objective of this study was to identify genomic regions associated with fat‐related traits using a Japanese Black cattle population in Hyogo. From 1836 animals, those with high or low values were selected on the basis of corrected phenotype and then pooled into high and low groups (n = 100 each), respectively. DNA pool‐based genome‐wide association study (GWAS) was performed using Illumina BovineSNP50 BeadChip v2 with three replicate assays for each pooled sample. GWAS detected that two single nucleotide polymorphisms (SNPs) on BTA7 (ARS‐BFGL‐NGS‐35463 and Hapmap23838‐BTA‐163815) and one SNP on BTA12 (ARS‐BFGL‐NGS‐2915) significantly affected fat percentage (FAR). The significance of ARS‐BFGL‐NGS‐35463 on BTA7 was confirmed by individual genotyping in all pooled samples. Moreover, association analysis between SNP and FAR in 803 Japanese Black cattle revealed a significant effect of SNP on FAR. Thus, further investigation of these regions is required to identify FAR‐associated genes and mutations, which can lead to the development of DNA markers for marker‐assisted selection for the genetic improvement of beef quality.     

Genome‐wide association study and genomic evaluation of feed efficiency traits in Japanese Black cattle using single‐step genomic best linear unbiased prediction method

The objectives of this study were to better understand the genetic architecture and the possibility of genomic evaluation for feed efficiency traits by (i) performing genome‐wide association studies (GWAS), and (ii) assessing the accuracy of genomic evaluation for feed efficiency traits, using single‐step genomic best linear unbiased prediction (ssGBLUP)‐based methods. The analyses were performed in residual feed intake (RFI), residual body weight gain (RG), and residual intake and body weight gain (RIG) during three different fattening periods. The phenotypes from 4,578 Japanese Black steers, which were progenies of 362 progeny‐tested bulls and the genotypes from the bulls were used in this study. The results of GWAS showed that a total of 16, 8, and 12 gene ontology terms were related to RFI, RG, and RIG, respectively, and the candidate genes identified in RFI and RG were involved in olfactory transduction and the phosphatidylinositol signaling system, respectively. The realized reliabilities of genomic estimated breeding values were low to moderate in the feed efficiency traits. In conclusion, ssGBLUP‐based method can lead to understand some biological functions related to feed efficiency traits, even with small population with genotypes, however, an alternative strategy will be needed to enhance the reliability of genomic evaluation.