Divergent gene expression patterns in alcohol and opioid use disorders lead to consistent alterations in functional networks within the Dorsolateral Prefrontal Cortex

Substance Use Disorders (SUDs) manifest as persistent drug-seeking behavior despite adverse consequences, with Alcohol Use Disorder (AUD) and Opioid Use Disorder (OUD) representing prevalent forms associated with significant mortality rates and economic burdens. The co-occurrence of AUD and OUD is common, necessitating a deeper comprehension of their intricate interactions. While the causal link between these disorders remains elusive, shared genetic factors are hypothesized. Leveraging public datasets, we employed genomic and transcriptomic analyses to explore conserved and distinct molecular pathways within the dorsolateral prefrontal cortex associated with AUD and OUD. Our findings unveil modest transcriptomic overlap at the gene level between the two disorders but substantial convergence on shared biological pathways. Notably, these pathways predominantly involve inflammatory processes, synaptic plasticity, and key intracellular signaling regulators. Integration of transcriptomic data with the latest genome-wide association studies (GWAS) for problematic alcohol use (PAU) and OUD not only corroborated our transcriptomic findings but also confirmed the limited shared heritability between the disorders. Overall, our study indicates that while alcohol and opioids induce diverse transcriptional alterations at the gene level, they converge on select biological pathways, offering promising avenues for novel therapeutic targets aimed at addressing both disorders simultaneously.

Assessment of milk metabolites as biomarkers for predicting feed efficiency in dairy sheep

Estimating feed efficiency (FE) in dairy sheep is challenging due to the high cost of systems that measure individual feed intake. Identifying proxies that can serve as effective predictors of FE could make it possible to introduce FE into breeding programs. Here, 39 Assaf ewes in first lactation were evaluated regarding their FE by 2 metrics, residual feed intake (RFI) and feed conversion ratio (FCR). The ewes were classified into high, medium and low groups for each metric. Milk samples of the 39 ewes were subjected to untargeted metabolomics analysis. The complete milk metabolomic signature was used to discriminate the FE groups using partial least squares discriminant analysis. A total of 41 and 26 features were selected as the most relevant features for the discrimination of RFI and FCR groups, respectively. The predictive ability when utilizing the complete milk metabolomic signature and the reduced data sets were investigated using 4 machine-learning algorithms and a multivariate regression method. The Orthogonal Partial Least Square algorithm outperformed other ML algorithms for the FCR prediction in the scenarios using the complete milk metabolite signature (r2 = 0.62 ± 0.06) and the 26 selected features (0.62 ± 0.15). Regarding RFI predictions, the scenarios using the 41 selected features outperformed the scenario with the complete milk metabolite signature, where the Multilayer feedforward artificial neural network (r2 = 0.18 ± 0.14) and extreme gradient boosting (r2 = 0.17 ± 0.15) outperformed other algorithms. The functionality of the selected metabolites implied that the metabolism of glucose, galactose, fructose, sphingolipids, amino acids, insulin, and thyroid hormones was at play. Compared with the use of traditional methods, practical applications of these biomarkers might simplify and reduce costs in selecting feed-efficient ewes.

Multi-breed host rumen epithelium transcriptome and microbiome associations and their relationship with beef cattle feed efficiency

Understanding host-microbial interactions in the rumen and its influence on desirable production traits may lead to potential microbiota manipulation or genetic selection for improved cattle feed efficiency. This study investigated the host transcriptome and its correlation with the rumen archaea and bacteria differential abundance of two pure beef cattle breeds (Angus and Charolais) and one composite beef hybrid (Kinsella) divergent for residual feed intake (RFI; low-RFI vs. high-RFI). Using RNA-Sequencing of rumen tissue and 16S rRNA gene amplicon sequencing, differentially expressed genes (FDR ≤ 0.05, |log2(Fold-change) >|2) and differentially abundant (p-value < 0.05) archaea and bacteria amplicon sequence variants (ASV) were determined. Significant correlations between gene expression and ASVs (p-value < 0.05) were determine using Spearman correlation. Interesting associations with muscle contraction and the modulation of the immune system were observed for the genes correlated with bacterial ASVs. Potential functional candidate genes for feed efficiency status were identified for Angus (CCL17, CCR3, and CXCL10), Charolais (KCNK9, GGT1 and IL6), and Kinsella breed (ESR2). The results obtained here provide more insights regarding the applicability of target host and rumen microbial traits for the selection and breeding of more feed efficient beef cattle.

Genomic screening of allelic and genotypic transmission ratio distortion in horse

The phenomenon in which the expected Mendelian inheritance is altered is known as transmission ratio distortion (TRD). The TRD analysis relies on the study of the transmission of one of the two alleles from a heterozygous parent to the offspring. These distortions are due to biological mechanisms affecting gametogenesis, embryo development and/or postnatal viability, among others. In this study, TRD phenomenon was characterized in horses using SNP-by-SNP model by TRDscan v.2.0 software. A total of 1,041 Pura Raza Español breed horses were genotyped with 554,634 SNPs. Among them, 277 horses genotyped in trios (stallion-mare-offspring) were used to perform the TRD analysis. Our results revealed 140 and 42 SNPs with allelic and genotypic patterns, respectively. Among them, 63 displayed stallion-TRD and 41 exhibited mare-TRD, while 36 SNPs showed overall TRD. In addition, 42 SNPs exhibited heterosis pattern. Functional analyses revealed that the annotated genes located within the TRD regions identified were associated with biological processes and molecular functions related to spermatogenesis, oocyte division, embryonic development, and hormonal activity. A total of 10 functional candidate genes related to fertility were found. To our knowledge, this is the most extensive study performed to evaluate the presence of alleles and functional candidate genes with transmission ratio distortion affecting reproductive performance in the domestic horse.

Unravelling transmission ratio distortion across the bovine genome: identification of candidate regions for reproduction defects

BACKGROUND

Biological mechanisms affecting gametogenesis, embryo development and postnatal viability have the potential to alter Mendelian inheritance expectations resulting in observable transmission ratio distortion (TRD). Although the discovery of TRD cases have been around for a long time, the current widespread and growing use of DNA technologies in the livestock industry provides a valuable resource of large genomic data with parent-offspring genotyped trios, enabling the implementation of TRD approach. In this research, the objective is to investigate TRD using SNP-by-SNP and sliding windows approaches on 441,802 genotyped Holstein cattle and 132,991 (or 47,910 phased) autosomal SNPs.

RESULTS

The TRD was characterized using allelic and genotypic parameterizations. Across the whole genome a total of 604 chromosomal regions showed strong significant TRD. Most (85%) of the regions presented an allelic TRD pattern with an under-representation (reduced viability) of carrier (heterozygous) offspring or with the complete or quasi-complete absence (lethality) for homozygous individuals. On the other hand, the remaining regions with genotypic TRD patterns exhibited the classical recessive inheritance or either an excess or deficiency of heterozygote offspring. Among them, the number of most relevant novel regions with strong allelic and recessive TRD patterns were 10 and 5, respectively. In addition, functional analyses revealed candidate genes regulating key biological processes associated with embryonic development and survival, DNA repair and meiotic processes, among others, providing additional biological evidence of TRD findings.

CONCLUSIONS

Our results revealed the importance of implementing different TRD parameterizations to capture all types of distortions and to determine the corresponding inheritance pattern. Novel candidate genomic regions containing lethal alleles and genes with functional and biological consequences on fertility and pre- and post-natal viability were also identified, providing opportunities for improving breeding success in cattle.

Transcriptome analysis of perirenal fat from Spanish Assaf suckling lamb carcasses showing different levels of kidney knob and channel fat

Introduction

Suckling lamb meat is highly appreciated in European Mediterranean countries because of its mild flavor and soft texture. In suckling lamb carcasses, perirenal and pelvic fat depots account for a large fraction of carcass fat accumulation, and their proportions are used as an indicator of carcass quality.

Material and Methods

This study aimed to characterize the genetic mechanisms that regulate fat deposition in suckling lambs by evaluating the transcriptomic differences between Spanish Assaf lambs with significantly different proportions of kidney knob and channel fat (KKCF) depots in their carcasses (4 High-KKCF lambs vs. 4 Low-KKCF lambs).

Results

The analyzed fat tissue showed overall dominant expression of white adipose tissue gene markers, although due to the young age of the animals (17-36 days), the expression of some brown adipose tissue gene markers (e.g., UCP1, CIDEA) was still identified. The transcriptomic comparison between the High-KKCF and Low-KKCF groups revealed a total of 80 differentially expressed genes (DEGs). The enrichment analysis of the 49 DEGs with increased expression levels in the Low-KKCF lambs identified significant terms linked to the biosynthesis of lipids and thermogenesis, which may be related to the higher expression of the UCP1 gene in this group. In contrast, the enrichment analysis of the 31 DEGs with increased expression in the High-KKCF lambs highlighted angiogenesis as a key biological process supported by the higher expression of some genes, such as VEGF-A and THBS1, which encode a major angiogenic factor and a large adhesive extracellular matrix glycoprotein, respectively.

Discussion

The increased expression of sestrins, which are negative regulators of the mTOR complex, suggests that the preadipocyte differentiation stage is being inhibited in the High-KKCF group in favor of adipose tissue expansion, in which vasculogenesis is an essential process. All of these results suggest that the fat depots of the High-KKCF animals are in a later stage of development than those of the Low-KKCF lambs. Further genomic studies based on larger sample sizes and complementary analyses, such as the identification of polymorphisms in the DEGs, should be designed to confirm these results and achieve a deeper understanding of the genetic mechanisms underlying fat deposition in suckling lambs.

Intergenerational impact of dietary protein restriction in dairy ewes on epigenetic marks in the perirenal fat of their suckling lambs

In sheep, nutrition during the prepubertal stage is essential for growth performance and mammary gland development. However, the potential effects of nutrient restriction in a prepuberal stage over the progeny still need to be better understood. Here, the intergenerational effect of maternal protein restriction at prepubertal age (2 months of age) on methylation patterns was evaluated in the perirenal fat of Assaf suckling lambs. In total, 17 lambs from ewes subjected to dietary protein restriction (NPR group, 44% less protein) and 17 lambs from control ewes (C group) were analyzed. These lambs were ranked based on their carcass proportion of perirenal and cavitary fat and classified into HighPCF and LowPCF groups. The perirenal tissue from 4 NPR-LowPCF, 4 NPR-HighPCF, 4 C-LowPCF, and 4 C-HighPCF lambs was subjected to whole-genome bisulfite sequencing and differentially methylated regions (DMRs) were identified. Among other relevant processes, these DMRs were mapped in genes responsible for regulating the transition of brown to white adipose tissue and nonshivering thermoregulation, which might be associated with better adaptation/survival of lambs in the perinatal stage. The current study provides important biological insights about the intergenerational effect on the methylation pattern of an NPR in replacement ewes.

Deviations from Mendelian Inheritance on Bovine X-Chromosome Revealing Recombination, Sex-of-Offspring Effects and Fertility-Related Candidate Genes

Transmission ratio distortion (TRD), or significant deviations from Mendelian inheritance, is a well-studied phenomenon on autosomal chromosomes, but has not yet received attention on sex chromosomes. TRD was analyzed on 3832 heterosomal single nucleotide polymorphisms (SNPs) and 400 pseudoautosomal SNPs spanning the length of the X-chromosome using 436,651 genotyped Holstein cattle. On the pseudoautosomal region, an opposite sire-TRD pattern between male and female offspring was identified for 149 SNPs. This finding revealed unique SNPs linked to a specific-sex (Y- or X-) chromosome and describes the accumulation of recombination events across the pseudoautosomal region. On the heterosomal region, 13 SNPs and 69 haplotype windows were identified with dam-TRD. Functional analyses for TRD regions highlighted relevant biological functions responsible to regulate spermatogenesis, development of Sertoli cells, homeostasis of endometrium tissue and embryonic development. This study uncovered the prevalence of different TRD patterns across both heterosomal and pseudoautosomal regions of the X-chromosome and revealed functional candidate genes for bovine reproduction.

Integrated analyses of the methylome and transcriptome to unravel sex differences in the perirenal fat from suckling lambs

In sheep, differences were observed regarding fat accumulation and fatty acid (FA) composition between males and females, which may impact the quality and organoleptic characteristics of the meat. The integration of different omics technologies is a relevant approach for investigating biological and genetic mechanisms associated with complex traits. Here, the perirenal tissue of six male and six female Assaf suckling lambs was evaluated using RNA sequencing and whole-genome bisulfite sequencing (WGBS). A multiomic discriminant analysis using multiblock (s)PLS-DA allowed the identification of 314 genes and 627 differentially methylated regions (within these genes), which perfectly discriminate between males and females. These candidate genes overlapped with previously reported QTLs for carcass fat volume and percentage of different FAs in milk and meat from sheep. Additionally, differentially coexpressed (DcoExp) modules of genes between males (nine) and females (three) were identified that harbour 22 of these selected genes. Interestingly, these DcoExp were significantly correlated with fat percentage in different deposits (renal, pelvic, subcutaneous and intramuscular) and were associated with relevant biological processes for adipogenesis, adipocyte differentiation, fat volume and FA composition. Consequently, these genes may potentially impact adiposity and meat quality traits in a sex-specific manner, such as juiciness, tenderness and flavour.

27 Evaluating the Functional Differences at Genome, Transcriptome and Methylome Level between ARS-UCD1.2 and UMD 3.1 Bovine Reference Genomes

Crossbred beef steers, n = 5,140; 352 ± 5.45 kg initial body weight (BW) were used to evaluate chromium propionate supplementation to yearling steers in a commercial feedyard. Cattle were blocked by arrival date and initial BW and assigned randomly to pen within block; pens were randomly assigned to treatment within block. Treatments, replicated in 15 pens per treatment with 130 to 250 steers per pen, included: 1) control (CTL), 0 mg supplemental Cr/kg dietary dry matter (DM); 2) chromium (CR) 0.50 mg supplemental Cr/kg dietary DM (4.9 mg/d; chromium propionate; KemTRACE Chromium 0.4%, Kemin Industries, Des Moines, IA). Final BW, average daily gain (ADG) and gain efficiency (G:F) did not differ among treatments (P ≥ 0.26). Dry matter intake was greater for CR than CTL, 8.61 kg. vs. 8.49 kg, respectively (P = 0.03). Hot carcass weight (HCW), dressing percentage, ribeye area, and 12th-rib-fat were not different for CTL or CR (P ≥ 0.12). The percentage of carcasses camera grading choice or better was greater (P = 0.04) for CR (51.2%) than CTL (48%), and the percentage of select carcasses was less (P = 0.01) for CR (41.5%) than CTL (45.5%). Yield grade distribution did not differ among treatments (P ≥ 0.26). There was no difference (P ≥ 0.36) in overall morbidity (7.75%), or total mortality (1.43%) between treatments. Steers fed CR had higher quality carcasses, and similar G:F and HCW to CTL.

Genome-wide association study using haplotype libraries and repeated measures model to identify candidate genomic regions for stillbirth in Holstein cattle

Reduced fertility is one of the main causes of economic losses on dairy farms, resulting in economic losses estimated at $938 per stillbirth case in Holstein herds. The identification of genomic regions associated with stillbirth could help to develop better management and breeding strategies aimed to reduce the frequency of undesirable gestation outcomes. Here, 10,570 cows and 50,541 birth records were used to perform a haplotype-based GWAS. A total of 41 significantly associated pseudo-SNPs (haplotypes within haplotype blocks converted to a binary classification) were identified after Bonferroni adjustment for multiple tests. A total of 117 positional candidate genes were annotated within or close (in a 200-kb interval) to significant pseudo-SNPs (haplotype blocks). The guilt-by-association functional prioritization identified 31 potential functional candidate genes for reproductive performance out of the 117 positional candidate genes annotated. These genes play crucial roles in biological processes associated with pregnancy persistence, fetus development, immune response, among others. These results helped us to better understand the genetic basis of stillbirth in dairy cattle and may be useful for the prediction of stillbirth in Holstein cattle, helping to reduce the related economic losses caused by this phenotype.

21 Unravelling Transmission Ratio Distortion Across the Genome of a Crossbreed Beef Cattle Population

Transmission ratio distortion (TRD) is a process when one allele from either parent is preferentially transmitted to the offspring. The identification of genomic regions affected by TRD might help in the detection of lethal alleles or potential genes affecting reproduction. Here, we investigated TRD in crossbreed beef cattle population aiming to identify genomic regions showing altered deviations in segregation that could be affecting reproduction performance. A total of 237 genotyped animals were used including 46 sires, 80 dams, and 111 parent-offspring (trios). The predominant breeds of these animals were Angus (61.83%), Simmental (18.99%), Gelbvieh (6.12%), Charolais (3.65%), Hereford (2.46%) and Limousin (1.57%). After excluding SNPs with minor allele frequency lower than 0.05 and call-rate lower than 0.90, a total of 369,902 autosomal SNPs were retained for further analyses. The SNP-by-SNP analysis was performed within a Bayesian framework using TRDscanv.2.0 software, using 100,000 iterations, with 10,000 iterations being discarded as burn-in. As table 1 shows, 33 SNPs were identified with TRD, considering a Bayes Factor (BF)≥100 and the approximate empirical null distribution of TRD at 0.01% margin error. Among them, 26 SNPs were parent-unspecific and 7 SNPs were parent-specific TRD. For parent-specific TRD, 214 were identified for sire- and 162 for dam-TRD (BF≥100). Among them, 4 SNPs were detected with sire- and dam-TRD in opposite direction of preference of transmission. Preliminary functional and positional analysis was performed using the list of TRD regions with BF≥100 and the approximate empirical null distribution of TRD at 0.01% margin error. For sire-TRD, 14% of the identified QTL (n = 254) were related to non-return rate. For dam-TRD, 21 regions related to conception rate were found (1.5%) and 13 regions related to stillbirth (0.93%). Haplotype analysis is in progress to identify additional candidate regions and alleles with TRD to better understand this phenomenon in a crossbreed beef population.

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27 Machine Learning Algorithms Based on Haplotype Libraries for Classification of Stillbirth Susceptibility in Holstein Cows

Reduced fertility is one of the main causes of economic losses in dairy farms. The cost of a stillbirth is estimated in US$ 938 per case in Holstein herds. Machine learning (ML) is gaining popularity in the livestock sector as a mean to identify hidden patterns and due to its potential to address dimensionality problems. Here we investigate the application of ML algorithms for the prediction of cows with higher stillbirth susceptibility in two scenarios: cows with &gt;25% and &gt;33.33% of stillbirths among birth records. These thresholds correspond to percentiles 75 (still_75) and 90 (still_90), respectively. A total of 10,570 cows and 50,541 birth records were collected to perform a haplotype-based genome-wide association study. Five-hundred significant pseudo single nucleotide polymorphisms (pseudo-SNPs) (False-Discovery Rate&lt; 0.05) were used as input features of ML-based predictions to determine if the cow is in the top-75 and top-90 percentiles. Table 1 shows the classification performance of the investigated ML and linear models. The ML models outperformed linear models for both thresholds. In general, still_75 showed higher F1 values compared to still_90, suggesting a lower misclassification ratio when a less stringent threshold is used. We observe that accuracy of the models in our study is higher when compared to ML-based prediction accuracies in other breeds, e.g. compared to the accuracies of 0.46 and 0.67 that were achieved using SNPs for body weight in Brahman and fertility traits in Nellore, respectively. Xgboost algorithm shows the highest balanced accuracy (BA; 0.625), F1-score (0.588) and area under the curve (AUC; 0.688), suggesting that xgboost can achieve the highest predictive performance and the lowest difference in misclassification ratio between classes. The ML applied over haplotype libraries is an interesting approach for the detection of animals with higher susceptibility to stillbirths due to highest predictive accuracy and relatively lower misclassification ratio.

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Detection and Visualization of Heterozygosity-Rich Regions and Runs of Homozygosity in Worldwide Sheep Populations

In this study, we chose 17 worldwide sheep populations of eight breeds, which were intensively selected for different purposes (meat, milk, or wool), or locally-adapted breeds, in order to identify and characterize factors impacting the detection of runs of homozygosity (ROH) and heterozygosity-rich regions (HRRs) in sheep. We also applied a business intelligence (BI) tool to integrate and visualize outputs from complementary analyses. We observed a prevalence of short ROH, and a clear distinction between the ROH profiles across populations. The visualizations showed a fragmentation of medium and long ROH segments. Furthermore, we tested different scenarios for the detection of HRR and evaluated the impact of the detection parameters used. Our findings suggest that HRRs are small and frequent in the sheep genome; however, further studies with higher density SNP chips and different detection methods are suggested for future research. We also defined ROH and HRR islands and identified common regions across the populations, where genes related to a variety of traits were reported, such as body size, muscle development, and brain functions. These results indicate that such regions are associated with many traits, and thus were under selective pressure in sheep breeds raised for different purposes. Interestingly, many candidate genes detected within the HRR islands were associated with brain integrity. We also observed a strong association of high linkage disequilibrium pattern with ROH compared with HRR, despite the fact that many regions in linkage disequilibrium were not located in ROH regions.

GALLO: An R package for genomic annotation and integration of multiple data sources in livestock for positional candidate loci

BACKGROUND

The development of high-throughput sequencing and genotyping methodologies has enabled the identification of thousands of genomic regions associated with several complex traits. The integration of multiple sources of biological information is a crucial step required to better understand patterns regulating the development of these traits.

FINDINGS

Genomic Annotation in Livestock for positional candidate LOci (GALLO) is an R package developed for the accurate annotation of genes and quantitative trait loci (QTLs) located in regions identified in common genomic analyses performed in livestock, such as genome-wide association studies and transcriptomics using RNA sequencing. Moreover, GALLO allows the graphical visualization of gene and QTL annotation results, data comparison among different grouping factors (e.g., methods, breeds, tissues, statistical models, studies), and QTL enrichment in different livestock species such as cattle, pigs, sheep, and chickens.

CONCLUSIONS

Consequently, GALLO is a useful package for annotation, identification of hidden patterns across datasets, and data mining previously reported associations, as well as the efficient examination of the genetic architecture of complex traits in livestock.

Identification of functional candidate variants and genes for feed efficiency in Holstein and Jersey cattle breeds using RNA-sequencing

The identification of functional genetic variants and associated candidate genes linked to feed efficiency may help improve selection for feed efficiency in dairy cattle, providing economic and environmental benefits for the dairy industry. This study used RNA-sequencing data obtained from liver tissue from 9 Holstein cows [n = 5 low residual feed intake (RFI), n = 4 high RFI] and 10 Jersey cows (n = 5 low RFI, n = 5 high RFI), which were selected from a single population of 200 animals. Using RNA-sequencing, 3 analyses were performed to identify: (1) variants within low or high RFI Holstein cattle; (2) variants within low or high RFI Jersey cattle; and (3) variants within low or high RFI groups, which are common across both Holstein and Jersey cattle breeds. From each analysis, all variants were filtered for moderate, modifier, or high functional effect, and co-localized quantitative trait loci (QTL) classes, enriched biological processes, and co-localized genes related to these variants, were identified. The overlapping of the resulting genes co-localized with functional SNP from each analysis in both breeds for low or high RFI groups were compared. For the first two analyses, the total number of candidate genes associated with moderate, modifier, or high functional effect variants fixed within low or high RFI groups were 2,810 and 3,390 for Holstein and Jersey breeds, respectively. The major QTL classes co-localized with these variants included milk and reproduction QTL for the Holstein breed, and milk, production, and reproduction QTL for the Jersey breed. For the third analysis, the common variants across both Holstein and Jersey breeds, uniquely fixed within low or high RFI groups were identified, revealing a total of 86,209 and 111,126 functional variants in low and high RFI groups, respectively. Across all 3 analyses for low and high RFI cattle, 12 and 31 co-localized genes were overlapping, respectively. Among the overlapping genes across breeds, 9 were commonly detected in both the low and high RFI groups (INSRR, CSK, DYNC1H1, GAB1, KAT2B, RXRA, SHC1, TRRAP, PIK3CB), which are known to play a key role in the regulation of biological processes that have high metabolic demand and are related to cell growth and regeneration, metabolism, and immune function. The genes identified and their associated functional variants may serve as candidate genetic markers and can be implemented into breeding programs to help improve the selection for feed efficiency in dairy cattle.

Identifying functionally relevant candidate genes for inflexible ethanol intake in mice and humans using a guilt-by-association approach

Gene prioritization approaches are useful tools to explore and select candidate genes in transcriptome studies. Knowing the importance of processes such as neuronal activity, intracellular signal transduction, and synapse plasticity to the development and maintenance of compulsive ethanol drinking, the aim of the present study was to explore and identify functional candidate genes associated with these processes in an animal model of inflexible pattern of ethanol intake. To do this, we applied a guilt-by-association approach, using the GUILDify and ToppGene software, in our previously published microarray data from the prefrontal cortex (PFC) and striatum of inflexible drinker mice. We then tested some of the prioritized genes that showed a tissue-specific pattern in postmortem brain tissue (PFC and nucleus accumbens (NAc)) from humans with alcohol use disorder (AUD). In the mouse brain, we prioritized 44 genes in PFC and 26 in striatum, which showed opposite regulation patterns in PFC and striatum. The most prioritized of them (i.e., Plcb1 and Prkcb in PFC, and Dnm2 and Lrrk2 in striatum) were associated with synaptic neuroplasticity, a neuroadaptation associated with excessive ethanol drinking. The identification of transcription factors among the prioritized genes suggests a crucial role for Irf4 in the pattern of regulation observed between PFC and striatum. Lastly, the differential transcription of IRF4 and LRRK2 in PFC and nucleus accumbens in postmortem brains from AUD compared to control highlights their involvement in compulsive ethanol drinking in humans and mice.

Genome-wide association study to identify genomic regions and positional candidate genes associated with male fertility in beef cattle

Fertility plays a key role in the success of calf production, but there is evidence that reproductive efficiency in beef cattle has decreased during the past half-century worldwide. Therefore, identifying animals with superior fertility could significantly impact cow-calf production efficiency. The objective of this research was to identify candidate regions affecting bull fertility in beef cattle and positional candidate genes annotated within these regions. A GWAS using a weighted single-step genomic BLUP approach was performed on 265 crossbred beef bulls to identify markers associated with scrotal circumference (SC) and sperm motility (SM). Eight windows containing 32 positional candidate genes and five windows containing 28 positional candidate genes explained more than 1% of the genetic variance for SC and SM, respectively. These windows were selected to perform gene annotation, QTL enrichment, and functional analyses. Functional candidate gene prioritization analysis revealed 14 prioritized candidate genes for SC of which MAP3K1 and VIP were previously found to play roles in male fertility. A different set of 14 prioritized genes were identified for SM and five were previously identified as regulators of male fertility (SOD2, TCP1, PACRG, SPEF2, PRLR). Significant enrichment results were identified for fertility and body conformation QTLs within the candidate windows. Gene ontology enrichment analysis including biological processes, molecular functions, and cellular components revealed significant GO terms associated with male fertility. The identification of these regions contributes to a better understanding of fertility associated traits and facilitates the discovery of positional candidate genes for future investigation of causal mutations and their implications.

Development and comparison of RNA-sequencing pipelines for more accurate SNP identification: practical example of functional SNP detection associated with feed efficiency in Nellore beef cattle

Background

Optimization of an RNA-Sequencing (RNA-Seq) pipeline is critical to maximize power and accuracy to identify genetic variants, including SNPs, which may serve as genetic markers to select for feed efficiency, leading to economic benefits for beef production. This study used RNA-Seq data (GEO Accession ID: PRJEB7696 and PRJEB15314) from muscle and liver tissue, respectively, from 12 Nellore beef steers selected from 585 steers with residual feed intake measures (RFI; n = 6 low-RFI, n = 6 high-RFI). Three RNA-Seq pipelines were compared including multi-sample calling from i) non-merged samples; ii) merged samples by RFI group, iii) merged samples by RFI and tissue group. The RNA-Seq reads were aligned against the UMD3.1 bovine reference genome (release 94) assembly using STAR aligner. Variants were called using BCFtools and variant effect prediction (VeP) and functional annotation (ToppGene) analyses were performed.

Results

On average, total reads detected for Approach i) non-merged samples for liver and muscle, were 18,362,086.3 and 35,645,898.7, respectively. For Approach ii), merging samples by RFI group, total reads detected for each merged group was 162,030,705, and for Approach iii), merging samples by RFI group and tissues, was 324,061,410, revealing the highest read depth for Approach iii). Additionally, Approach iii) merging samples by RFI group and tissues, revealed the highest read depth per variant coverage (572.59 ± 3993.11) and encompassed the majority of localized positional genes detected by each approach. This suggests Approach iii) had optimized detection power, read depth, and accuracy of SNP calling, therefore increasing confidence of variant detection and reducing false positive detection. Approach iii) was then used to detect unique SNPs fixed within low- (12,145) and high-RFI (14,663) groups. Functional annotation of SNPs revealed positional candidate genes, for each RFI group (2886 for low-RFI, 3075 for high-RFI), which were significantly (P < 0.05) associated with immune and metabolic pathways.

Conclusion

The most optimized RNA-Seq pipeline allowed for more accurate identification of SNPs, associated positional candidate genes, and significantly associated metabolic pathways in muscle and liver tissues, providing insight on the underlying genetic architecture of feed efficiency in beef cattle.

Weighted Gene Correlation Network Meta-Analysis Reveals Functional Candidate Genes Associated with High- and Sub-Fertile Reproductive Performance in Beef Cattle

Improved reproductive efficiency could lead to economic benefits for the beef industry, once the intensive selection pressure has led to a decreased fertility. However, several factors limit our understanding of fertility traits, including genetic differences between populations and statistical limitations. In the present study, the RNA-sequencing data from uterine samples of high-fertile (HF) and sub-fertile (SF) animals was integrated using co-expression network meta-analysis, weighted gene correlation network analysis, identification of upstream regulators, variant calling, and network topology approaches. Using this pipeline, top hub-genes harboring fixed variants (HF × SF) were identified in differentially co-expressed gene modules (DcoExp). The functional prioritization analysis identified the genes with highest potential to be key-regulators of the DcoExp modules between HF and SF animals. Consequently, 32 functional candidate genes (10 upstream regulators and 22 top hub-genes of DcoExp modules) were identified. These genes were associated with the regulation of relevant biological processes for fertility, such as embryonic development, germ cell proliferation, and ovarian hormone regulation. Additionally, 100 candidate variants (single nucleotide polymorphisms (SNPs) and insertions and deletions (INDELs)) were identified within those genes. In the long-term, the results obtained here may help to reduce the frequency of subfertility in beef herds, reducing the associated economic losses caused by this condition.

Genetic mechanisms regulating the host response during mastitis

Mastitis is a very costly and common disease in the dairy industry. The study of the transcriptome from healthy and mastitic milk somatic cell samples using RNA-Sequencing technology can provide measurements of transcript levels associated with the immune response to the infection. The objective of this study was to characterize the Holstein milk somatic cell transcriptome from 6 cows to determine host response to intramammary infections. RNA-Sequencing was performed on 2 samples from each cow from 2 separate quarters, one classified as healthy (n = 6) and one as mastitic (n = 6). In total, 449 genes were differentially expressed between the healthy and mastitic quarters (false discovery rate <0.05, fold change >±2). Among the differentially expressed genes, the most expressed genes based on reads per kilobase per million mapped reads (RPKM) in the healthy group were associated with milk components (CSN2 and CSN3), and in the mastitic group they were associated with immunity (B2M and CD74). In silico functional analysis was performed using the list of 449 differentially expressed genes, which identified 36 significantly enriched metabolic pathways (false discovery rate <0.01), some of which were associated with the immune system, such as cytokine-cytokine interaction and cell adhesion molecules. Seven functional candidate genes were selected, based on the criteria of being highly differentially expressed between healthy and mastitic groups and significantly enriched in metabolic pathways that are relevant to the inflammatory process (GLYCAM1, B2M, CD74, BoLA-DRA, FCER1G, SDS, and NFKBIA). Last, we identified the differentially expressed genes that are located in quantitative trait locus regions previously known to be associated with mastitis, specifically clinical mastitis, somatic cell count, and somatic cell score. It was concluded that multiple genes within quantitative trait locus regions could potentially affect host response to mastitis-causing agents, making some cows more susceptible to intramammary infections. The identification of potential candidate genes with functional, statistical, biological, and positional relevance associated with host defense to infection will contribute to a better understanding of the underlying genetic architecture associated with mastitis. This in turn will improve the sustainability of agricultural practices by facilitating the selection of cows with improved host defense leading to increased resistance to mastitis.

Genome-wide association for milk production traits and somatic cell score in different lactation stages of Ayrshire, Holstein, and Jersey dairy cattle

We performed genome-wide association analyses for milk, fat, and protein yields and somatic cell score based on lactation stages in the first 3 parities of Canadian Ayrshire, Holstein, and Jersey cattle. The genome-wide association analyses were performed considering 3 different lactation stages for each trait and parity: from 5 to 95, from 96 to 215, and from 216 to 305 d in milk. Effects of single nucleotide polymorphisms (SNP) for each lactation stage, trait, parity, and breed were estimated by back-solving the direct breeding values estimated using the genomic best linear unbiased predictor and single-trait random regression test-day models containing only the fixed population average curve and the random genomic curves. To identify important genomic regions related to the analyzed lactation stages, traits, parities and breeds, moving windows (SNP-by-SNP) of 20 adjacent SNP explaining more than 0.30% of total genetic variance were selected for further analyses of candidate genes. A lower number of genomic windows with a relatively higher proportion of the explained genetic variance was found in the Holstein breed compared with the Ayrshire and Jersey breeds. Genomic regions associated with the analyzed traits were located on 12, 8, and 15 chromosomes for the Ayrshire, Holstein, and Jersey breeds, respectively. Especially for the Holstein breed, many of the identified candidate genes supported previous reports in the literature. However, well-known genes with major effects on milk production traits (e.g., diacylglycerol O-acyltransferase 1) showed contrasting results among lactation stages, traits, and parities of different breeds. Therefore, our results suggest evidence of differential sets of candidate genes underlying the phenotypic expression of the analyzed traits across breeds, parities, and lactation stages. Further functional studies are needed to validate our findings in independent populations.

Implementation of Bayesian methods to identify SNP and haplotype regions with transmission ratio distortion across the whole genome: TRDscan v.1.0

Realized deviations from the expected Mendelian inheritance of alleles from heterozygous parents have been previously reported in a broad range of organisms (i.e., transmission ratio distortion; TRD). Various biological mechanisms affecting gametes, embryos, fetuses, or even postnatal offspring can produce patterns of TRD. However, knowledge about its prevalence and potential causes in livestock species is still scarce. Specific Bayesian models have been recently developed for the analyses of TRD for biallelic loci, which accommodated a wide range of population structures, enabling TRD investigation in livestock populations. The parameterization of these models is flexible and allows the study of overall (parent-unspecific) TRD and sire- and dam-specific TRD. This research aimed at deriving Bayesian models for fitting TRD on the basis of haplotypes, testing the models for both haplotype- and SNP-based methods in simulated data and actual Holstein genotypes, and developing a specific software for TRD analyses. Results obtained on simulated data sets showed that the statistical power of the analysis increased with sample size of trios (n), proportion of heterozygous parents, and the magnitude of the TRD. On the other hand, the statistical power to detect TRD decreased with the number of alleles at each loci. Bayesian analyses showed a strong Pearson correlation coefficient (≥0.97) between simulated and estimated TRD that reached the significance level of Bayes factor ≥10 for both single-marker and haplotype analyses when n ≥ 25. Moreover, the accuracy in terms of the mean absolute error decreased with the increase of the sample size and increased with the number of alleles at each loci. Using real data (55,732 genotypes of Holstein trios), SNP- and haplotype-based distortions were detected with overall TRD, sire-TRD, or dam-TRD, showing different magnitudes of TRD and statistical relevance. Additionally, the haplotype-based method showed more ability to capture TRD compared with individual SNP. To discard possible random TRD in real data, an approximate empirical null distribution of TRD was developed. The program TRDscan v.1.0 was written in Fortran 2008 language and provides a powerful statistical tool to scan for TRD regions across the whole genome. This developed program is freely available at http://www.casellas.info/files/TRDscan.zip.

Reducing cryptic relatedness in genomic data sets via a central node exclusion algorithm

Cryptic relatedness is a confounding factor in genetic diversity and genetic association studies. Development of strategies to reduce cryptic relatedness in a sample is a crucial step for downstream genetic analyses. This study uses a node selection algorithm, based on network degrees of centrality, to evaluate its applicability and impact on evaluation of genetic diversity and population stratification. 1,036 Guzerá (Bos indicus) females were genotyped using Illumina Bovine SNP50 v2 BeadChip. Four strategies were compared. The first and second strategies consist on a iterative exclusion of most related individuals based on PLINK kinship coefficient (φij) and VanRaden's φij, respectively. The third and fourth strategies were based on a node selection algorithm. The fourth strategy, Network G matrix, preserved the larger number of individuals with a better diversity and representation from the initial sample. Determining the most probable number of populations was directly affected by the kinship metric. Network G matrix was the better strategy for reducing relatedness due to producing a larger sample, with more distant individuals, a more similar distribution when compared with the full data set in the MDS plots and keeping a better representation of the population structure. Resampling strategies using VanRaden's φij as a relationship metric was better to infer the relationships among individuals. Moreover, the resampling strategies directly impact the genomic inflation values in genomewide association studies. The use of the node selection algorithm also implies better selection of the most central individuals to be removed, providing a more representative sample.

Biotinidase deficiency: Genotype-biochemical phenotype association in Brazilian patients

Introduction

The association between the BTD genotype and biochemical phenotype [profound biotinidase deficiency (BD), partial BD or heterozygous activity] is not always consistent. This study aimed to investigate the genotype-biochemical phenotype association in patients with low biotinidase activity.

Methods

All exons, the 5'UTR and the promoter of the BTD gene were sequenced in 72 Brazilian individuals who exhibited low biotinidase activity. For each patient, the expected biochemical phenotype based on the known genotype was compared with the observed biochemical phenotype. Additional non-genetic factors that could affect the biotinidase activity were also analysed.

Results

Most individuals were identified by neonatal screening (n = 66/72). When consecutive results for the same patient were compared, age, prematurity and neonatal jaundice appeared to affect the level of biotinidase activity. The biochemical phenotype at the time of the second blood collection changed in 11/22 patients compared to results from the first sample. Three novel variants were found: c.1337T>C (p.L446P), c.1466A>G (p.N489S) and c.962G>A (p.W321*). Some patients with the same genotype presented different biochemical phenotypes. The expected and observed biochemical phenotypes agreed in 68.5% of cases (concordant patients). The non-coding variants c.-183G>A, c.-315A>G and c.-514C>T were present in heterozygosis in 5/17 discordant patients. In addition, c.-183G>A and c.-514C>T were also present in 10/37 concordant patients.

Conclusions

The variants found in the promoter region do not appear to have a strong impact on biotinidase activity. Since there is a disparity between the BTD genotype and biochemical phenotype, and biotinidase activity may be affected by both genetic and non-genetic factors, we suggest that the diagnosis of BD should be based on more than one measurement of plasma biotinidase activity. DNA analysis can be of additional relevance to differentiate between partial BD and heterozygosity.

A new tetra-primer ARMS-PCR for genotyping bovine kappa-casein polymorphisms

Kappa-casein (κ-casein) is one of the most abundant milk proteins. Its main function is to avoid the aggregation of casein micelles, keeping them, and therefore calcium phosphate, in pockets in solution. In bovines, a κ-casein functional polymorphism has been associated with fat, calcium, and protein milk contents and faster curd contraction in cheese production. Quicker curd contraction reduces the loss of milk solids, enhancing cheese yield. This polymorphism induces a double amino acid substitution (Thr136Ile and Ala148Asp). The polymorphism is normally detected by PCR-RFLP, which is a laborious method. An interesting methodological alternative is the tetra-primer amplification refractory mutation system PCR (tetra-primer ARMS-PCR). A tetra-primer ARMS-PCR for the detection of this κ-casein polymorphism has been described. However, specificity was not achieved, probably due to problems with primer design. We developed a new tetra-primer ARMS-PCR for the detection of the κ-casein polymorphism. This new method was validated in a double-blind test, by comparison with the results obtained for 50 Guzerá bulls formerly genotyped by PCR-RFLP. This new method achieved 100% sensitivity and specificity. We conclude that this method is a useful, cost-efficient alternative for the detection of functional κ-casein polymorphisms.