A genomic estimated breeding value-assisted reduction method of single nucleotide polymorphism sets: a novel approach for determining the cutoff thresholds in genome-wide association studies and best linear unbiased prediction.

Traditionally, the p-value is the criterion for the cutoff threshold to determine significant markers in genome-wide association studies (GWASs). Choosing the best subset of markers for the best linear unbiased prediction (BLUP) for improved prediction ability (PA) has become an interesting issue. However, when dealing with many traits having the same marker information, the p-values' themselves cannot be used as an obvious solution for having a confidence in GWAS and BLUP. We thus suggest a genomic estimated breeding value-assisted reduction method of the single nucleotide polymorphism (SNP) set (GARS) to address these difficulties. GARS is a BLUP-based SNP set decision presentation. The samples were Landrace pigs and the traits used were back fat thickness (BF) and daily weight gain (DWG). The prediction abilities (PAs) for BF and DWG for the entire SNP set were 0.8 and 0.8, respectively. By using the correlation between genomic estimated breeding values (GEBVs) and phenotypic values, selecting the cutoff threshold in GWAS and the best SNP subsets in BLUP was plausible as defined by GARS method. 6,000 SNPs in BF and 4,000 SNPs in DWG were considered as adequate thresholds. Gene Ontology (GO) analysis using the GARS results of the BF indicated neuron projection development as the notable GO term, whereas for the DWG, the main GO terms were nervous system development and cell adhesion.

Genome-wide association studies on collagen contents trait for meat quality in Hanwoo.

Beef consumers valued meat quality traits such as texture, tenderness, juiciness, flavor, and meat color that determining consumers' purchasing decision. Most research on meat quality has focused on marbling, a key characteristic related to meat eating quality. However, other important traits such as meat texture, tenderness, and color have not much studied in cattle. Among these traits, meat tenderness and texture of cattle are among the most important factors affecting quality evaluation of consumers. Collagen is the main component of connective tissues.It greatly affects meat tenderness. The objective of this study was to determine significant variants and candidate genes associated with collagen contents trait (total collagen) through genome-wide association studies (GWAS). Phenotypic and genomic data from 135 Hanwoo were used. The BLUPF90 family program and GRAMMAR method for GWAS were applied in this study. A total of 73 potential single nucleotide polymorphisms (SNPs) showed significant associations with collagen content. They were located in or near 108 candidate genes. TMEM135 and ME3 genes were identified to have the most significant SNPs associated with collagen contents trait. Data indicated that these genes were related to collagen. Biological processes and pathways for the prediction of biological functions of candidate genes were confirmed. We found that candidate genes were involved in positive regulation of CREB transcription factor activity and actin cytoskeleton related to tenderness and texture of beef. Three genes (CRTC3, MYO1C and MYLK4) belonging to these biological functions were related to tenderness. These results provide a basis for improving genomic characteristics of Hanwoo for the production of tender beef. Furthermore, they could be used they could be used as an index to select desired traits for consumers.

Molecular modeling and dynamic simulation of chicken Mx protein with the S631N polymorphism.

Myxovirus resistance (Mx) proteins are antiviral GTPases induced by type I interferons (IFNs). In chickens, a single Mx protein variant, S631N, has been suggested to possess antiviral activity. However, the impact of this variant on chicken Mx (chMx) protein structure and conformation has not been investigated. Hence, in this study, we applied computational methods such as molecular modeling, molecular dynamic simulation, inter domain motion and residue networks to examine the structure and dynamic behavior of wild-type and mutant chMx. At first, we built 3-dimensional structural models for both wild-type and mutant chMx proteins, which revealed that the structural organization of chMx was similar to that of human Mx proteins. Subsequently, molecular dynamics simulations revealed that angle variation around the hinge1 region led to the different stalk domain conformations between the wild-type and mutant chMx proteins. Domain motion analysis further suggested that the conformational differences in the loop region surrounded by the mutant residue may lead to an inclined stalk domain conformation in the mutant compared to the wild-type protein. In addition, we performed betweenness centrality analysis from residue interaction networks, to identify the crucial residues for intramolecular signal flow in chMx. The results of this study provided information on the differences in structure and dynamics between wild-type and mutant chMx, which may aid in understanding the structural features of the S631N mutant, that may be associated with chMx protein antiviral activity.Communicated by Ramaswamy H. Sarma.

High-throughput sequencing-based metagenomic and transcriptomic analysis of intestine in piglets infected with salmonella.

Salmonella enterica serovar Typhimurium isolate HJL777 is a virulent bacterial strain in pigs. The high rate of salmonella infection are at high risk of non-typhoidal salmonella gastroenteritis development. Salmonellosis is most common in young pigs. We investigated changes in gut microbiota and biological function in piglets infected with salmonella via analysis of rectal fecal metagenome and intestinal transcriptome using 16S rRNA and RNA sequencing. We identified a decrease in Bacteroides and increase in harmful bacteria such as Spirochaetes and Proteobacteria by microbial community analysis. We predicted that reduction of Bacteroides by salmonella infection causes proliferation of salmonella and harmful bacteria that can cause an intestinal inflammatory response. Functional profiling of microbial communities in piglets with salmonella infection showed increasing lipid metabolism associated with proliferation of harmful bacteria and inflammatory responses. Transcriptome analysis identified 31 differentially expressed genes. Using gene ontology and Innate Immune Database analysis, we identified that BGN, DCN, ZFPM2 and BPI genes were involved in extracellular and immune mechanisms, specifically salmonella adhesion to host cells and inflammatory responses during infection. We confirmed alterations in gut microbiota and biological function during salmonella infection in piglets. Our findings will help prevent disease and improve productivity in the swine industry.

Antitumorigenic effect of insect-derived peptide poecilocorisin-1 in human skin cancer cells through regulation of Sp1 transcription factor.

Malignant melanoma is highly resistant to conventional treatments and is one of the most aggressive types of skin cancers. Conventional cancer treatments are limited due to drug resistance, tumor selectivity, and solubility. Therefore, new treatments with fewer side effects and excellent effects should be developed. In previous studies, we have analyzed antimicrobial peptides (AMPs), which showed antibacterial and anti-inflammatory effects in insects, and some AMPs also exhibited anticancer efficacy. Anticancer peptides (ACPs) are known to have fewer side effects and high anticancer efficacy. In this study, the insect-derived peptide poecilocorisin-1 (PCC-1) did not induce toxicity in the human epithelial cell line HaCaT, but its potential as an anticancer agent was confirmed through specific effects of antiproliferation, apoptosis, and cell cycle arrest in two melanoma cell lines, SK-MEL-28 and G361. Additionally, we discovered a novel anticancer mechanism of insect-derived peptides in melanoma through the regulation of transcription factor Sp1 protein, which is overexpressed in cancer, apoptosis, and cell cycle-related proteins. Taken together, this study aims to clarify the anticancer efficacy and safety of insect-derived peptides and to present their potential as future therapeutic agents.

Correction: Weighted Genomic Best Linear Unbiased Prediction for Carcass Traits in Hanwoo Cattle. Genes 2019, 10, 1019.

The authors wish to make the following corrections to this paper [...].

Comparative genomics of canine Lactobacillus reuteri reveals adaptation to a shared environment with humans.

BACKGROUND: Lactobacillus reuteri is a gram-positive, non-motile bacterial species that has been used as a representative microorganism model to describe the ecology and evolution of vertebrate gut symbionts. OBJECTIVE: Because the genetic features and evolutionary strategies of L. reuteri from the gastrointestinal tract of canines remain unknown, we tried to construct draft genome canine L. reuteri and investigate modified, acquired, or lost genetic features that have facilitated the evolution and adaptation of strains to specific environmental niches by this study. METHODS: To examine canine L. reuteri, we sequenced an L. reuteri strain isolated from a dog in Korea. A comparative genomic approach was used to assess genetic diversity and gain insight into the distinguishing features related to different hosts based on 27 published genomic sequences. RESULTS: The pan-genome of 28 L. reuteri strains contained 7,369 gene families, and the core genome contained 1070 gene families. The ANI tree based on the core genes in the canine L. reuteri strain (C1) was very close to those for three strains (IRT, DSM20016, JCM1112) from humans. Evolutionarily, these four strains formed one clade, which we regarded as C1-clade in this study. We could investigate a total of 32,050 amino acid substitutions among the 28 L. reuteri strain genomes. In this comparison, 283 amino acid substitutions were specific to strain C1 and four strains in C1-clade shared most of these 283 C1-strain specific amino acid substitutions, suggesting strongly similar selective pressure. In accessory genes, we could identify 127 C1-clade host-specific genes and found that several genes were closely related to replication, recombination, and repair. CONCLUSION: This study provides new insights into the adaptation of L. reuteri to the canine intestinal habitat, and suggests that the genome of L. reuteri from canines is closely associated with their living and shared environment with humans.

Conformational Changes Induced by S34Y and R98C Variants in the Death Domain of Myd88.

Myeloid differentiating factor 88 (Myd88) is a universal adaptor protein that plays a critical role in innate immunity by mediating TLR downstream signaling. Myd88 death domain (DD) forms an oligomeric complex by association with other DD-containing proteins such as IRAK4. Despite its universal role, polymorphisms in Myd88 can result in several diseases. Previous studies have suggested that, out of several non-synonymous single-nucleotide polymorphisms (nsSNPs), the variants S34Y and R98C in the DD of Myd88 disrupt the formation of the Myddosome complex. Therefore, we performed molecular dynamics (MD) simulations on wild-type (Myd88WT) and mutant (Myd88S34Y, Myd88R98C) DDs to evaluate the subtle conformational changes induced by these mutations. Our results suggest that the S34Y variant induces large structural transitions compared to the R98C variant as evidenced by residual flexibility at the variable loop regions, particularly in the H1-H2 loop, and variations in the collective modes of motion observed for wild-type and mutant Myd88 DDs. The residue interaction network strongly suggests a distortion in the interaction pattern at the location of the mutated residue between the wild type and mutants. Moreover, betweenness centrality values indicate that variations in the distribution of functionally important residues may be reflected by distinct residue signal transductions in both wild-type and mutant Myd88 DDs, which may influence the interaction with other DDs in TLR downstream signaling.

Comparison of characteristics of long noncoding RNA in Hanwoo according to sex.

OBJECTIVE: Cattle were some of the first animals domesticated by humans for the production of milk, meat, etc. Long noncoding RNA (lncRNA) is defined as longer than 200 bp in non-protein coding transcripts. lncRNA is known to function in regulating gene expression and is currently being studied in a variety of livestock including cattle. The purpose of this study is to analyze the characteristics of lncRNA according to sex in Hanwoo cattle. METHODS: This study was conducted using the skeletal muscles of 9 Hanwoo cattle include bulls, steers and cows. RNA was extracted from skeletal muscle of Hanwoo. Sequencing was conducted using Illumina HiSeq2000 and mapped to the Bovine Taurus genome. The expression levels of lncRNAs were measured by DEGseq and quantitative trait loci (QTL) data base was used to identify QTLs associated with lncRNA. The python script was used to match the nearby genes. RESULTS: In this study, the expression patterns of transcripts of bulls, steers and cows were identified. And we identified significantly differentially expressed lncRNAs in bulls, steers and cows. In addition, characteristics of lncRNA which express differentially in muscles according to the sex of Hanwoo were identified. As a result, we found differentially expressed lncRNAs according to sex were related to shear force and body weight. CONCLUSION: This study was classified and characterized lncRNA which differentially expressed by sex in Hanwoo cattle. We believe that the characterization of lncRNA by sex of Hanwoo will be helpful for future studies of the physiological mechanisms of Hanwoo cattle.

Genomic Prediction Based on SNP Functional Annotation Using Imputed Whole-Genome Sequence Data in Korean Hanwoo Cattle.

Whole-genome sequence (WGS) data are increasingly being applied into genomic predictions, offering a higher predictive ability by including causal mutations or single-nucleotide polymorphisms (SNPs) putatively in strong linkage disequilibrium with causal mutations affecting the trait. This study aimed to improve the predictive performance of the customized Hanwoo 50 k SNP panel for four carcass traits in commercial Hanwoo population by adding highly predictive variants from sequence data. A total of 16,892 Hanwoo cattle with phenotypes (i.e., backfat thickness, carcass weight, longissimus muscle area, and marbling score), 50 k genotypes, and WGS imputed genotypes were used. We partitioned imputed WGS data according to functional annotation [intergenic (IGR), intron (ITR), regulatory (REG), synonymous (SYN), and non-synonymous (NSY)] to characterize the genomic regions that will deliver higher predictive power for the traits investigated. Animals were assigned into two groups, the discovery set (7324 animals) used for predictive variant detection and the cross-validation set for genomic prediction. Genome-wide association studies were performed by trait to every genomic region and entire WGS data for the pre-selection of variants. Each set of pre-selected SNPs with different density (1000, 3000, 5000, or 10,000) were added to the 50 k genotypes separately and the predictive performance of each set of genotypes was assessed using the genomic best linear unbiased prediction (GBLUP). Results showed that the predictive performance of the customized Hanwoo 50 k SNP panel can be improved by the addition of pre-selected variants from the WGS data, particularly 3000 variants from each trait, which is then sufficient to improve the prediction accuracy for all traits. When 12,000 pre-selected variants (3000 variants from each trait) were added to the 50 k genotypes, the prediction accuracies increased by 9.9, 9.2, 6.4, and 4.7% for backfat thickness, carcass weight, longissimus muscle area, and marbling score compared to the regular 50 k SNP panel, respectively. In terms of prediction bias, regression coefficients for all sets of genotypes in all traits were close to 1, indicating an unbiased prediction. The strategy used to select variants based on functional annotation did not show a clear advantage compared to using whole-genome. Nonetheless, such pre-selected SNPs from the IGR region gave the highest improvement in prediction accuracy among genomic regions and the values were close to those obtained using the WGS data for all traits. We concluded that additional gain in prediction accuracy when using pre-selected variants appears to be trait-dependent, and using WGS data remained more accurate compared to using a specific genomic region.

Risk prediction and marker selection in nonsynonymous single nucleotide polymorphisms using whole genome sequencing data.

Despite the various existing studies about nonsynonymous single nucleotide polymorphisms (nsSNPs), genome-wide studies based on nsSNPs are rare. NsSNPs alter amino acid sequences, affect protein structure and function, and have deleterious effects. By predicting the deleterious effect of nsSNPs, we determined the total risk score per individual. Additionally, the machine learning technique was utilized to find an optimal nsSNP subset that best explains the complete nsSNP effect. A total of 16,100 nsSNPs were selected as the best representatives among 89,519 regressed nsSNPs. In the gene ontology analysis encompassing the 16,100 nsSNPs, DNA metabolic process, chemokine- and immune-related, and reproduction were the most enriched terms. We expect that our risk score prediction and nsSNP marker selection will contribute to future development of extant genome-wide association studies and breeding science more broadly.

Weighted Genomic Best Linear Unbiased Prediction for Carcass Traits in Hanwoo Cattle.

The genomic best linear unbiased prediction (GBLUP) method has been widely used in routine genomic evaluation as it assumes a common variance for all single nucleotide polymorphism (SNP). However, this is unlikely in the case of traits influenced by major SNP. Hence, the present study aimed to improve the accuracy of GBLUP by using the weighted GBLUP (WGBLUP), which gives more weight to important markers for various carcass traits of Hanwoo cattle, such as backfat thickness (BFT), carcass weight (CWT), eye muscle area (EMA), and marbling score (MS). Linear and different nonlinearA SNP weighting procedures under WGBLUP were evaluated and compared with unweighted GBLUP and traditional pedigree-based methods (PBLUP). WGBLUP methods were assessed over ten iterations. Phenotypic data from 10,215 animals from different commercial herds that were slaughtered at approximately 30-month-old of age were used. All these animals were genotyped using Illumina Bovine 50k SNP chip and were divided into a training and a validation population by birth date on 1 November 2015. Genomic prediction accuracies obtained in the nonlinearA weighting methods were higher than those of the linear weighting for all traits. Moreover, unlike with linear methods, no sudden drops in the accuracy were noted after the peak was reached in nonlinearA methods. The average accuracies using PBLUP were 0.37, 0.49, 0.40, and 0.37, and 0.62, 0.74, 0.67, and 0.65 using GBLUP for BFT, CWT, EMA, and MS, respectively. Moreover, these accuracies of genomic prediction were further increased to 4.84% and 2.70% for BFT and CWT, respectively by using the nonlinearA method under the WGBLUP model. For EMA and MS, WGBLUP was as accurate as GBLUP. Our results indicate that the WGBLUP using a nonlinearA weighting method provides improved predictions for CWT and BFT, suggesting that the ability of WGBLUP over the other models by weighting selected SNPs appears to be trait-dependent.

In silico approach to calculate the transcript capacity.

We sought the novel concept, transcript capacity (TC) and analyzed TC. Our approach to estimate TC was through an in silico method. TC refers to the capacity that a transcript exerts in a cell as enzyme or protein function after translation. We used the genome-wide association study (GWAS) beta effect and transcription level in RNA-sequencing to estimate TC. The trait was body fat percent and the transcript reads were obtained from the human protein atlas. The assumption was that the GWAS beta effect is the gene's effect and TC was related to the corresponding gene effect and transcript reads. Further, we surveyed gene ontology (GO) in the highest TC and the lowest TC genes. The most frequent GOs with the highest TC were neuronal-related and cell projection organization related. The most frequent GOs with the lowest TC were wound-healing related and embryo development related. We expect that our analysis contributes to estimating TC in the diverse species and playing a benevolent role to the new bioinformatic analysis.

Comparison of long noncoding RNA between muscles and adipose tissues in Hanwoo beef cattle.

Long noncoding RNAs (lncRNAs) regulate the expression of mRNA and can affect various biological processes and phenotypes. Currently, studies of lncRNAs in cattle are under way, but their exact function for several tissues has not yet been established. Hanwoo cattle (Bos taurus coreanae) have inhabited the Korean peninsula for about 6000 years and are one of the representative domesticated animals in Korea. As a result of intensive breeding, the meat of Hanwoo cattle is high in marbling content and is preferred by Koreans and other East Asian people. In this study, the expression of lncRNAs was identified in 36 samples from skeletal muscle and three adipose tissues (intramuscular, subcutaneous, and omental) of nine Hanwoo individuals. We identified 76 tissue-specific lncRNAs for each of the four tissues using the differences in expression levels. Through QTL information, we could identify 12 lncRNAs associated with shear force and six lncRNAs associated with body weight, which are two important traits in the Hanwoo population breeding strategy. By the physical position comparison of lncRNA and Bovine transcripts information, we could identify 11 lncRNAs that were in bovine transcripts, and four of the 11 genes related to transcripts of lncRNAs were biologically associated with muscle function. We believe this Hanwoo lncRNAs study will help reveal the lncRNA role in the physiological mechanisms of these four tissues.

Analysis of genetic characteristics of pig breeds using information on single nucleotide polymorphisms.

OBJECTIVE: This study was undertaken to investigate the genetic characteristics of Berkshire (BS), Landrace (LR), and Yorkshire (YS) pig breeds raised in the Great Grandparents pig farms using the single nucleotide polymorphisms (SNP) information. METHODS: A total of 25,921 common SNP genotype markers in three pig breeds were used to estimate the expected heterozygosity (HE), polymorphism information content, F-statistics (FST), linkage disequilibrium (LD) and effective population size (Ne). RESULTS: The chromosome-wise distribution of FST in BS, LR, and YS populations were within the range of 0-0.36, and the average FST value was estimated to be 0.07±0.06. This result indicated some level of genetic segregation. An average LD (r2) for the BS, LR, and YS breeds was estimated to be approximately 0.41. This study also found an average Ne of 19.9 (BS), 31.4 (LR), and 34.1 (YS) over the last 5th generations. The effective population size for the BS, LR, and YS breeds decreased at a consistent rate from 50th to 10th generations ago. With a relatively faster Ne decline rate in the past 10th generations, there exists possible evidence for intensive selection practices in pigs in the recent past. CONCLUSION: To develop customized chips for the genomic selection of various breeds, it is important to select and utilize SNP based on the genetic characteristics of each breed. Since the improvement efficiency of breed pigs increases sharply by the population size, it is important to increase test units for the improvement and it is desirable to establish the pig improvement network system to expand the unit of breed pig improvement through the genetic connection among breed pig farms.

In silico approaches to identify the functional and structural effects of non-synonymous SNPs in selective sweeps of the Berkshire pig genome.

OBJECTIVE: Non-synonymous single nucleotide polymorphisms (nsSNPs) were identified in Berkshire selective sweep regions and then were investigated to discover genetic nsSNP mechanisms that were potentially associated with Berkshire domestication and meat quality. We further used bioinformatics tools to predict damaging amino-acid substitutions in Berkshire-related nsSNPs. METHODS: nsSNPs were examined in whole genome resequencing data of 110 pigs, including 14 Berkshire pigs, generated using the Illumina Hiseq2000 platform to identify variations that might affect meat quality in Berkshire pigs. RESULTS: Total 65,550 nsSNPs were identified in the mapped regions; among these, 319 were found in Berkshire selective-sweep regions reported in a previous study. Genes encompassing these nsSNPs were involved in lipid metabolism, intramuscular fatty-acid deposition, and muscle development. The effects of amino acid change by nsSNPs on protein functions were predicted using sorting intolerant from tolerant and polymorphism phenotyping V2 to reveal their potential roles in biological processes that may correlate with the unique Berkshire meat-quality traits. CONCLUSION: Our nsSNP findings confirmed the history of Berkshire pigs and illustrated the effects of domestication on generic-variation patterns. Our novel findings, which are generally consistent with those of previous studies, facilitated a better understanding of Berkshire domestication. In summary, we extensively investigated the relationship between genomic composition and phenotypic traits by scanning for nsSNPs in large-scale whole-genome sequencing data.

Characterization of gene expression and genetic variation of horse ERBB receptor feedback inhibitor 1 in Thoroughbreds.

OBJECTIVE: This study aimed to test the expression patterns of ERBB receptor feedback inhibitor 1 (ERRFI1) before and after exercise and the association of non-synonymous single-nucleotide polymorphisms (nsSNPs) of horse ERRFI1 with racing traits in Thoroughbreds. METHODS: We performed bioinformatics and gene expression analyses for horse ERRFI1. Transcription factor (TF) binding sites in the 5'-regulatory region of this gene were identified through a tool for prediction of TF-binding site (PROMO). A general linear model was used to detect the association between the nsSNP (LOC42830758 A to G) and race performance. RESULTS: Quantitative polymerase chain reaction analysis showed that expression level of ERRFI1 after exercise was 1.6 times higher than that before exercise. Ten transcription factors were predicted from the ERRFI1 regulatory region. A novel nsSNP (LOC42830758 A to G) was found in ERRFI1, which was associated with three racing traits including average prize money, average racing index, and 3-year-old starts percentile ranking. CONCLUSION: Our analysis will be helpful as a basis for studying genes and SNPs that affect race performance in racehorses.

Validation of selection accuracy for the total number of piglets born in Landrace pigs using genomic selection.

OBJECTIVE: This study was to determine the relationship between estimated breeding value and phenotype information after farrowing when juvenile selection was made in candidate pigs without phenotype information. METHODS: After collecting phenotypic and genomic information for the total number of piglets born by Landrace pigs, selection accuracy between genomic breeding value estimates using genomic information and breeding value estimates of best linear unbiased prediction (BLUP) using conventional pedigree information were compared. RESULTS: Genetic standard deviation (σa ) for the total number of piglets born was 0.91. Since the total number of piglets born for candidate pigs was unknown, the accuracy of the breeding value estimated from pedigree information was 0.080. When genomic information was used, the accuracy of the breeding value was 0.216. Assuming that the replacement rate of sows per year is 100% and generation interval is 1 year, genetic gain per year is 0.346 head when genomic information is used. It is 0.128 when BLUP is used. CONCLUSION: Genetic gain estimated from single step best linear unbiased prediction (ssBLUP) method is by 2.7 times higher than that the one estimated from BLUP method, i.e., 270% more improvement in efficiency.

Comprehensive Identification of Sexual Dimorphism-Associated Differentially Expressed Genes in Two-Way Factorial Designed RNA-Seq Data on Japanese Quail (Coturnix coturnix japonica).

Japanese quail (Coturnix coturnix japonica) reach sexual maturity earlier, breed rapidly and successfully, and cost less and require less space than other birds raised commercially. Given the value of this species for food production and experimental use, more studies are necessary to determine chromosomal regions and genes associated with gender and breed-differentiation. This study employed Trinity and edgeR for transcriptome analysis of next-generation RNA-seq data, which included 4 tissues obtained from 3 different breeding lines of Japanese quail (random bred control, heavy weight, low weight). Differentially expressed genes shared between female and male tissue contrast groups were analyzed to identify genes related to sexual dimorphism as well as potential novel candidate genes for molecular sexing. Several of the genes identified in the present study as significant sex-related genes have been previously found in avian gene expression analyses (NIPBL, UBAP2), and other genes found differentially expressed in this study and not previously associated with sex-related differences may be considered potential candidates for molecular sexing (TERA, MYP0, PPR17, CASQ2). Additionally, other genes likely associated with neuronal and brain development (CHKA, NYAP), as well as body development and size differentiation (ANKRD26, GRP87) in quail were identified. Expression of homeobox protein regulating genes (HXC4, ISL1) shared between our two sex-related contrast groups (Female Brain vs. Male Brain and Ovary vs. Testis) indicates that these genes may regulate sex-specific anatomical development. Results reveal genetic features of the quail breed and could allow for more effective molecular sexing as well as selective breeding for traits important in commercial production.

Exploring evidence of positive selection reveals genetic basis of meat quality traits in Berkshire pigs through whole genome sequencing.

BACKGROUND: Natural and artificial selection following domestication has led to the existence of more than a hundred pig breeds, as well as incredible variation in phenotypic traits. Berkshire pigs are regarded as having superior meat quality compared to other breeds. As the meat production industry seeks selective breeding approaches to improve profitable traits such as meat quality, information about genetic determinants of these traits is in high demand. However, most of the studies have been performed using trained sensory panel analysis without investigating the underlying genetic factors. Here we investigate the relationship between genomic composition and this phenotypic trait by scanning for signatures of positive selection in whole-genome sequencing data. RESULTS: We generated genomes of 10 Berkshire pigs at a total of 100.6 coverage depth, using the Illumina Hiseq2000 platform. Along with the genomes of 11 Landrace and 13 Yorkshire pigs, we identified genomic variants of 18.9 million SNVs and 3.4 million Indels in the mapped regions. We identified several associated genes related to lipid metabolism, intramuscular fatty acid deposition, and muscle fiber type which attribute to pork quality (TG, FABP1, AKIRIN2, GLP2R, TGFBR3, JPH3, ICAM2, and ERN1) by applying between population statistical tests (XP-EHH and XP-CLR). A statistical enrichment test was also conducted to detect breed specific genetic variation. In addition, de novo short sequence read assembly strategy identified several candidate genes (SLC25A14, IGF1, PI4KA, CACNA1A) as also contributing to lipid metabolism. CONCLUSIONS: Results revealed several candidate genes involved in Berkshire meat quality; most of these genes are involved in lipid metabolism and intramuscular fat deposition. These results can provide a basis for future research on the genomic characteristics of Berkshire pigs.