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Context Genomic prediction is the use of genomic data in the estimation of genomic breeding values (GEBV) in animal breeding. In beef cattle breeding programs, genomic prediction increases the rates of genetic gain by increasing the accuracy of selection at earlier ages. Aims The objectives of the study were to examine the effect of single-nucleotide polymorphism (SNP) density and to evaluate the effect of using SNPs preselected from imputed whole-genome sequence for genomic prediction. Methods Genomic and phenotypic data from 2110 Hanwoo steers were used to predict GEBV for marbling score (MS), meat texture (MT), and meat colour (MC) traits. Three types of SNP densities including 50k, high-density (HD), and whole-genome sequence data and preselected SNPs from genome-wide association study (GWAS) were used for genomic prediction analyses. Two scenarios (independent and dependent discovery populations) were used to select top significant SNPs. The accuracy of GEBV was assessed using random cross-validation. Genomic best linear unbiased prediction (GBLUP) was used to predict the breeding values for each trait. Key results Our result showed that very similar prediction accuracies were observed across all SNP densities used in the study. The prediction accuracy among traits ranged from 0.29 ± 0.05 for MC to 0.46 ± 0.04 for MS. Depending on the studied traits, up to 5% of prediction accuracy improvement was obtained when the preselected SNPs from GWAS analysis were included in the prediction analysis. Conclusions High SNP density such as HD and the whole-genome sequence data yielded a similar prediction accuracy in Hanwoo beef cattle. Therefore, the 50K SNP chip panel is sufficient to capture the relationships in a breed with a small effective population size such as the Hanwoo cattle population. Preselected variants improved prediction accuracy when they were included in the genomic prediction model. Implications The estimated genomic prediction accuracies are moderately accurate in Hanwoo cattle and for searching for SNPs that are more productive could increase the accuracy of estimated breeding values for the studied traits.

Biologically informed single nucleotide polymorphisms (SNPs) impact genomic prediction accuracy of the target traits. Our previous genomics, proteomics, and transcriptomics work identified candidate genes related to puberty and fertility in Brahman heifers. We aimed to test this biological information for capturing heritability and predicting heifer fertility traits in another breed i.e., Tropical Composite. The SNP from the identified genes including 10 kilobases (kb) region on either side were selected as biologically informed SNP set. The SNP from the rest of the Bos taurus genes including 10-kb region on either side were selected as biologically uninformed SNP set. Bovine high-density (HD) complete SNP set (628,323 SNP) was used as a control. Two populations—Tropical Composites (N = 1331) and Brahman (N = 2310)—had records for three traits: pregnancy after first mating season (PREG1, binary), first conception score (FCS, score 1 to 3), and rebreeding score (REB, score 1 to 3.5). Using the best linear unbiased prediction method, effectiveness of each SNP set to predict the traits was tested in two scenarios: a 5-fold cross-validation within Tropical Composites using biological information from Brahman studies, and application of prediction equations from one breed to the other. The accuracy of prediction was calculated as the correlation between genomic estimated breeding values and adjusted phenotypes. Results show that biologically informed SNP set estimated heritabilities not significantly better than the control HD complete SNP set in Tropical Composites; however, it captured all the observed genetic variance in PREG1 and FCS when modeled together with the biologically uninformed SNP set. In 5-fold cross-validation within Tropical Composites, the biologically informed SNP set performed marginally better (statistically insignificant) in terms of prediction accuracies (PREG1: 0.20, FCS: 0.13, and REB: 0.12) as compared to HD complete SNP set (PREG1: 0.17, FCS: 0.10, and REB: 0.11), and biologically uninformed SNP set (PREG1: 0.16, FCS: 0.10, and REB: 0.11). Across-breed use of prediction equations still remained a challenge: accuracies by all SNP sets dropped to around zero for all traits. The performance of biologically informed SNP was not significantly better than other sets in Tropical Composites. However, results indicate that biological information obtained from Brahman was successful to predict the fertility traits in Tropical Composite population.

Context Studies have shown that favourable genetic correlations exist between female and male fertility traits. However, investigations regarding these correlations in Australian tropical beef cattle are limited to either pedigree or single-breed analysis. Aim The study aims to use genomic information to estimate genetic parameters of six female and seven male fertility traits measured during the first 2 years of life, in two tropical breeds. Methods Single-, bivariate and multi-trait models were used to analyse fertility data from Brahman (BB; 996 cows and 1022 bulls); and Tropical Composite (TC; 1091 cows and 998 bulls) cattle genotyped with high-density single-nucleotide polymorphism chip assay. Key results Heritability estimates in BB cows ranged from low (0.07 ± 0.04) for days to calving at the first calving opportunity (DC1, days) to high (0.57 ± 0.08) for age at first corpus luteum (AGECL, days). In BB bulls, estimates varied from low (0.09 ± 0.05) for sperm motility (score 1–5) to high (0.64 ± 0.06) for scrotal circumference (SC) measured at 24 months (SC24, cm). Similarly, heritability estimates in TC cows were low (0.04 ± 0.03) for DC1 and high (0.69 ± 0.02) for AGECL. In TC bulls, the heritability was low (0.09 ± 0.05) for sperm motility and high (0.69 ± 0.07) for SC24. Within-sex for both breeds, blood concentrations of insulin growth-factor 1 (IGF1) measured in cows at 18 months (IGF1c) were negatively correlated with female fertility phenotypes. In BB, across-sex, bulls’ blood concentration of IGF1 measured at 6 months (IGF1b) was a good indicator trait for the following four female traits: AGECL, the first postpartum anoestrus interval, age at first calving and DC1. In TC, IGF1b and percentage normal sperm were good predictors of female fertility phenotypes. Conclusions The heritability estimates and genomic correlations from the present study generally support and confirmed the earlier estimates from pedigree analyses. The findings suggest that selection for female fertility traits will benefit male fertility, and vice versa. Implications Heritability estimates and genomic correlations suggest that we can select for fertility traits measured early in life, with benefits within and across sex. Using traits available through veterinary assessment of bull fertility as selection indicators will enhance bull and cow fertility, which can lead to better breeding rates in tropical herds.

The aim of this study was to evaluate the genotype x environment interaction (GxE) for scrotal circumference (SC) measured at different ages using pedigree-based (A-1) and pedigree and genomic-based (H-1) relationship matrices. Data from 1,515 Brahman bulls, from the Cooperative Research Centre for Beef Genetic Technologies (Beef CRC) experimental dataset, were used in this study. SC was adjusted to age and body weight measured at 6 mo (SC6), 12 mo (SC12), 18 mo (SC18), and 24 mo of age (SC24). Body weight (BW) measured at 6 mo (BW6), 12 mo (BW12), 18 mo (BW18), and 24 mo of age (BW24) was used as criteria to describe the environment for SC in each age. All the animals measured were genotyped using medium-density SNP chips ("50k" or "70k" SNP) and their genotype were imputed using a reference panel with 729,068 SNP. The environment gradient (EG) was obtained by standardizing the solutions of the contemporary groups obtained by Animal Model with BW as the dependent variable. Then, the reaction norms (RN) were determined through a Random Regression Model. The breeding values (EBV) were estimated using either A-1 or H-1. The rank correlation was obtained using Spearman's correlation among the EBV estimated for the traits in analysis. For SC6 and SC24, higher estimates of heritability (h²) were obtained using A-1, when compared with those observed with H-1. In those ages, the improvement of the environment decreases the h² coefficient. On the other hand, the h² for SC12 and SC18 increased as the environment became more favorable, regardless of the matrix used. The RN for SC6 and SC24 estimated using A-1 and H-1 showed a decrease of variance from the worst to the best environment, an indication of existence of GxE. On the other hand, for SC12 and SC18, there were no significant differences between the EBV estimated in the lower and in the higher environments, regardless of the kinship matrix used, suggesting absence of GxE on those ages. Spearman's correlation among EBV estimated using A-1 and H-1 in different EG was practically equal to unity for all traits evaluated. In our study, there was weak evidence of GxE effect on SC in ages suitable for selection for sexual precocity. So, the absence of GxE at 12 and 18 mo means that these ages are advantageous for measuring SC to selection for sexual precocity. The advantage is that no changes in classification were observed when the sires were evaluated in different environments.Beef production systems rely on efficient cow-calf operations, that is, farms where the cow herd has a high level of fertility and pregnancies are common. Bull fertility also plays an important role in terms of pregnancy rates. To increase herd fertility, cattle breeders and genetic selection programs use some indicator traits that are related to fertility. A common indicator trait used is scrotal circumference (SC), which like most reproduction traits are influenced by the animal’s genetics and its environment. For some traits, when the environment has a large effect and it interacts with the genetics of the animals, selection might be less successful. Therefore, it is important to investigate genotype by environment interactions and their effect on reproduction traits used for selection. In this study, SC was measured at four different ages in Brahman cattle. We found weak evidence of genotype by environment effect on SC measured at 12 and 18 mo. In short, SC measured at these ages can be a good indicator of sexual precocity. No changes in sire rankings were observed when SC was measured at those ages, meaning that selecting the best sire is more straightforward than if the environment was playing a bigger role.

Made available in DSpace on 2020-12-12T01:35:26Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-08-12 BACKGROUND: Twenty-five phenotypes were measured as indicators of bull fertility (1099 Brahman and 1719 Tropical Composite bulls). Measurements included sperm morphology, scrotal circumference, and sperm chromatin phenotypes such as DNA fragmentation and protamine deficiency. We estimated the heritability of these phenotypes and carried out genome-wide association studies (GWAS) within breed, using the bovine high-density chip, to detect quantitative trait loci (QTL). RESULTS: Our analyses suggested that both sperm DNA fragmentation and sperm protamine deficiency are heritable (h2 from 0.10 to 0.22). To confirm these first estimates of heritability, further studies on sperm chromatin traits, with larger datasets are necessary. Our GWAS identified 12 QTL for bull fertility traits, based on at least five polymorphisms (P

Puberty is a whole‐body event, driven by the hypothalamic integration of peripheral signals such as leptin or IGF‐1. In the process of puberty, reproductive development is simultaneous to growth, including muscle growth. To enhance our understanding of muscle function related to puberty, we performed transcriptome analyses of muscle samples from six pre‐ and six post‐pubertal Brahman heifers (Bos indicus). Our aims were to perform differential expression analyses and co‐expression analyses to derive a regulatory gene network associate with puberty. As a result, we identified 431 differentially expressed (DEx) transcripts (genes and non‐coding RNAs) when comparing pre‐ to post‐pubertal average gene expression. The DEx transcripts were compared with all expressed transcripts in our samples (over 14,000 transcripts) for functional enrichment analyses. The DEx transcripts were associated with “extracellular region,” “inflammatory response” and “hormone activity” (adjusted p, Puberty is a whole‐body event. In the process of puberty, reproductive development is simultaneous to muscle growth. To enhance our understanding of muscle function related to puberty, we performed whole‐genome gene expression analyses. As a result, we identified 431 differentially expressed genes and predicted a gene network. In the derived co‐expression gene network, TCF3 was also a key regulator. In short, we described how puberty may affect muscle gene expression in cattle.

Although the genetic correlation between complex traits have been estimated for more than a century, only recently we have started to map and understand the precise localization of the genomic region(s) that underpin these correlations. Reproductive traits are often genetically correlated, and yet we don9t fully understand the complexities, synergism, or trade-offs between male and female fertility. In this study, we used reproductive traits in two cattle populations to develop a novel framework termed correlation scan. This framework was used to identify regions associated with the genetic correlations between male and female fertility traits across the bovine genome. The traits used were age at first corpus luteum (AGECL) and serum levels of insulin growth hormone (IGF1 measured in bulls, IGF1b, or cows, IGF1c). The methodology developed herein used correlations of 500-SNP (single nucleotide polymorphism) effects in a 100-SNPs sliding window in each chromosome to identify regions in the genome that either drive (i.e., SNP effects on the same direction) or antagonize (i.e., SNP effects in the opposite direction) the genetic correlations between traits. We used a permutation test to confirm which regions of the genome harboured significant correlations. Hence, this framework can also identify neutral genomic regions with no effect on the pairwise trait studied. About 40% of the total genomic regions were identified as driving and antagonizing genetic correlations between male and female fertility traits in the two population. These regions confirmed the polygenic nature of the traits being studied and pointed to genes of interest. Quantitative trait loci (QTL) and functional enrichment analysis revealed that many significant windows co-located with known QTLs related to milk production and fertility traits, especially puberty. In general, the enriched reproductive QTLs driving the genetic correlations between male and female fertility are the same for both cattle populations, while the antagonizing regions were population specific. Moreover, most of the antagonizing regions were mapped to the chromosome X. These results suggest regions of the chromosome X for further investigation into the trade-offs between male and female fertility. Although the methodology was applied to cattle phenotypes, using high-density SNP genotypes, the general framework developed can be applied to any species or traits, and it can easily accommodate genome sequence data.

Background The rate of protein accretion and growth affect amino acid requirements in young animals. Differences in amino acid metabolism contribute to individual variations in growth rate. This study aimed at determining how amino acid needs may change with growth rates in broiler chickens. Experiment 1 consisted of testing amino acid choices in two chicken groups with extreme growth rates (the slowest –SG- or fastest –FG- growing birds in a flock). Essential (EAA) (methionine, lysine and threonine) or non-essential (NEAA) (alanine, aspartic acid and asparagine) amino acids were added to a standard control feed (13.2 MJ/kg; 21.6% crude protein). The chickens were offered simultaneous access to the control feed and a feed supplemented with one of the two amino acid mixes added at 73% above standard dietary levels. Experiment 2 consisted of the selection of the bottom 5 SG and top 5 FG chickens from a flock of 580 to study differences in amino acid metabolism using the proventriculus representing gut sensing mechanism. In this experiment, transcriptomic, proteomic, and genomic analyses were used to compare the two groups of chickens. Results SG preferred NEAA, while they rejected EAA supplemented feeds (P P P > 0.05). Transcriptomic and proteomic analyses identified 909 differentially expressed genes and 146 differentially abundant proteins associated with differences in growth rate (P Conclusion Dietary preferences for NEAA in the SG group are associated with a potential cytosolic depletion of alanine following an upregulation of the catabolism into TCA cycle intermediates.

BackgroundSpatiotemporal changes in the chromatin accessibility landscape are essential to cell differentiation, development, health, and disease. The quest of identifying regulatory elements in open chromatin regions across different tissues and developmental stages is led by large international collaborative efforts mostly focusing on model organisms, such as ENCODE. Recently, the Functional Annotation of Animal Genomes (FAANG) has been established to unravel the regulatory elements in non-model organisms, including cattle. Now, we can transition from prediction to validation by experimentally identifying the regulatory elements in tropical indicine cattle. The identification of regulatory elements, their annotation and comparison with the taurine counterpart, holds high promise to link regulatory regions to adaptability traits and improve animal productivity and welfare.ResultsWe generate open chromatin profiles for liver, muscle, and hypothalamus of indicine cattle through ATAC-seq. Using robust methods for motif discovery, motif enrichment and transcription factor binding sites, we identify potential master regulators of the epigenomic profile in these three tissues, namely HNF4, MEF2, and SOX factors, respectively. Integration with transcriptomic data allows us to confirm some of their target genes. Finally, by comparing our results with Bos taurus data we identify potential indicine-specific open chromatin regions and overlaps with indicine selective sweeps.ConclusionsOur findings provide insights into the identification and analysis of regulatory elements in non-model organisms, the evolution of regulatory elements within two cattle subspecies as well as having an immediate impact on the animal genetics community in particular for a relevant productive species such as tropical cattle.

Together with their sister subspecies Bos taurus, zebu cattle (Bos indicus) have contributed to important socioeconomic changes that have shaped modern civilizations. Zebu cattle were domesticated in the Indus Valley 8000 years before present (YBP). From the domestication site, they expanded to Africa, East Asia, southwestern Asia and Europe between 4000 and 1300 YBP, intercrossing with B. taurus to form clinal variations of zebu ancestry across the landmass of Afro-Eurasia. In the past 150 years, zebu cattle reached the Americas and Oceania, where they have contributed to the prosperity of emerging economies. The zebu genome is characterized by two mitochondrial haplogroups (I1 and I2), one Y chromosome haplogroup (Y3) and three major autosomal ancestral groups (Indian-Pakistani, African and Chinese). Phenotypically, zebu animals are recognized by their hump, large ears and excess skin. They are rustic, resilient to parasites and capable of bearing the hot and humid climates of the tropics. Many resources are available to study the zebu genome, including commercial arrays of SNP, reference assemblies and publicly available genotypes and whole-genome sequences. Nevertheless, many of these resources were initially developed to support research and subsidize industrial applications in B. taurus, and therefore they can produce bias in data analysis. The combination of genomics with precision agriculture holds great promise for the identification of genetic variants affecting economically important traits such as tick resistance and heat tolerance, which were naturally selected for millennia and played a major role in the evolution of B. indicus cattle.

The aim of this study was to identify candidate regions associated with sexual precocity in Bos indicus. Nellore and Brahman were set as validation and discovery populations, respectively. SNP selected in Brahman to validate in Nellore were from gene regions affecting reproductive traits (G1) and significant SNP (p ≤ 10-3 ) from a meta-analysis (G2). In the validation population, early pregnancy (EP) and scrotal circumference (SC) were evaluated. To perform GWAS in validation population, we used regression and Bayes C. SNP with p ≤ 10-3 in regression and Bayes factor ≥3 in Bayes C were deemed significant. Significant SNP (for EP or SC) or SNP in their ±250 Kb vicinity region, which were in at least one discovery set (G1 or G2), were considered validated. SNP identified in both G1 and G2 were considered candidate. For EP, 145 SNP were validated in G1 and 41 in G2, and for SC, these numbers were 14 and 2. For EP, 21 candidate SNP were detected (G1 and G2). For SC, no candidate SNP were identified. Validated SNP and their vicinity region were located close to quantitative trait loci or genes related to reproductive traits and were enriched in gene ontology terms related to reproductive success. These are therefore strong candidate regions for sexual precocity in Nellore and Brahman.

An efficient strategy to improve QTL detection power is performing across-breed validation studies. Variants segregating across breeds are expected to be in high linkage disequilibrium (LD) with causal mutations affecting economically important traits. The aim of this study was to validate, in a Tropical Composite cattle (TC) population, QTL associations identified for sexual precocity traits in a Nellore and Brahman meta-analysis genome-wide association study. In total, 2,816 TC, 8,001 Nellore, and 2,210 Brahman animals were available for the analysis. For that, genomic regions significantly associated with puberty traits in the meta-analysis study were validated for the following sexual precocity traits in TC: age at first corpus luteum (AGECL), first postpartum anestrus interval (PPAI), and scrotal circumference at 18 months of age (SC). We considered validated QTL those underpinned by significant markers from the Nellore and Brahman meta-analysis (P ≤ 10–4) that were also significant for a TC trait, i.e., presenting a P-value of ≤10–3 for AGECL, PPAI, or SC. We also considered as validated QTL those regions where significant markers in the reference population were at ±250 kb from significant markers in the validation population. Using this criteria, 49 SNP were validated for AGECL, 4 for PPAI, and 14 for SC, from which 5 were in common with AGECL, totaling 62 validated SNP for these traits and 30 candidate genes surrounding them. Considering just candidate genes closest to the top SNP of each chromosome, for AGECL 8 candidate genes were identified: COL8A1, PENK, ENSBTAG00000047425, BPNT1, ADAMTS17, CCHCR1, SUFU, and ENSBTAG00000046374. For PPAI, 3 genes emerged as candidates (PCBP3, KCNK10, and MRPS5), and for SC 8 candidate genes were identified (SNORA70, TRAC, ASS1, BPNT1, LRRK1, PKHD1, PTPRM, and ENSBTAG00000045690). Several candidate regions presented here were previously associated with puberty traits in cattle. The majority of emerging candidate genes are related to biological processes involved in reproductive events, such as maintenance of gestation, and some are known to be expressed in reproductive tissues. Our results suggested that some QTL controlling early puberty seem to be segregating across cattle breeds adapted to tropical conditions.

Changes in brain metabolism are a hallmark of alcohol use disorder (AUD). Determining how AUD changes the brain proteome is critical for understanding the effects of alcohol consumption on biochemical processes in the brain. We used data-independent acquisition mass spectrometry proteomics to study differences in the abundance of proteins associated with AUD in prefrontal lobe and motor cortex from autopsy brain. AUD had a substantial effect on the overall brain proteome exceeding the inherent differences between brain regions. Proteins associated with glycolysis, trafficking, the cytoskeleton, and excitotoxicity were altered in abundance in AUD. We observed extensive changes in the abundance of key metabolic enzymes, consistent with a switch from glucose to acetate utilization in the AUD brain. We propose that metabolic adaptations allowing efficient acetate utilization contribute to ethanol dependence in AUD.

Pigment-associated deafness is a common hereditary condition in a range of dog breeds. The aim of this study was to perform a genome-wide association analysis to investigate the genetic architecture of deafness in Australian Cattle Dogs. Genotypes for 104 757 polymorphisms in 216 dogs were available for analyses after quality control. A genomic relationship matrix was used in the mixed model analyses to account for polygenic effects, as we tested each polymorphism for its association with deafness, in a case/control experimental design. Three approaches were used to code the genotypes and test for additive, recessive and dominant SNP effects. The genome-wide association study analyses identified a clear association peak on CFA20, with the most significant SNPs on this chromosome (1.29 × 10-4 ) in the vicinity of MITF. Variants in MITF have been associated with white pigmentation in dogs and with deafness in humans and other species, supporting the premise that canine deafness is associated with variants in or near this gene. A recessive inheritance for the peak in CFA20 is possible given the significant results in the recessive model; however, the estimated heritability was low (4.54 × 10-5 ). Further validation, identification of variants and testing in other dog breeds are needed.

Fertility traits measured early in life define the reproductive potential of heifers. Knowledge of genetics and biology can help devise genomic selection methods to improve heifer fertility. In this study, we used ~2400 Brahman cattle to perform GWAS and multi-trait meta-analysis to determine genomic regions associated with heifer fertility. Heifer traits measured were pregnancy at first mating opportunity (PREG1, a binary trait), first conception score (FCS, score 1 to 3) and rebreeding score (REB, score 1 to 3.5). The heritability estimates were 0.17 (0.03) for PREG1, 0.11 (0.05) for FCS and 0.28 (0.05) for REB. The three traits were highly genetically correlated (0.75–0.83) as expected. Meta-analysis was performed using SNP effects estimated for each of the three traits, adjusted for standard error. We identified 1359 significant SNPs (p-value &lt, 9.9 × 10−6 at FDR &lt, 0.0001) in the multi-trait meta-analysis. Genomic regions of 0.5 Mb around each significant SNP from the meta-analysis were annotated to create a list of 2560 positional candidate genes. The most significant SNP was in the vicinity of a genomic region on chromosome 8, encompassing the genes SLC44A1, FSD1L, FKTN, TAL2 and TMEM38B. The genomic region in humans that contains homologs of these genes is associated with age at puberty in girls. Top significant SNPs pointed to additional fertility-related genes, again within a 0.5 Mb region, including ESR2, ITPR1, GNG2, RGS9BP, ANKRD27, TDRD12, GRM1, MTHFD1, PTGDR and NTNG1. Functional pathway enrichment analysis resulted in many positional candidate genes relating to known fertility pathways, including GnRH signaling, estrogen signaling, progesterone mediated oocyte maturation, cAMP signaling, calcium signaling, glutamatergic signaling, focal adhesion, PI3K-AKT signaling and ovarian steroidogenesis pathway. The comparison of results from this study with previous transcriptomics and proteomics studies on puberty of the same cattle breed (Brahman) but in a different population identified 392 genes in common from which some genes—BRAF, GABRA2, GABR1B, GAD1, FSHR, CNGA3, PDE10A, SNAP25, ESR2, GRIA2, ORAI1, EGFR, CHRNA5, VDAC2, ACVR2B, ORAI3, CYP11A1, GRIN2A, ATP2B3, CAMK2A, PLA2G, CAMK2D and MAPK3—are also part of the above-mentioned pathways. The biological functions of the positional candidate genes and their annotation to known pathways allowed integrating the results into a bigger picture of molecular mechanisms related to puberty in the hypothalamus–pituitary–ovarian axis. A reasonable number of genes, common between previous puberty studies and this study on early reproductive traits, corroborates the proposed molecular mechanisms. This study identified the polymorphism associated with early reproductive traits, and candidate genes that provided a visualization of the proposed mechanisms, coordinating the hypothalamic, pituitary, and ovarian functions for reproductive performance in Brahman cattle.

Made available in DSpace on 2021-06-25T10:30:37Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-04-30 Global Change Institute, University of Queensland Institute for Molecular Bioscience, University Of Queensland Queensland Alliance for Agriculture and Food Innovation, University of Queensland Research Computing Centre, University of Queensland University of Queensland Centre for Natural Gas, University of Queensland School of Agriculture and Food Sciences, University of Queensland School of Pharmacy, University of Queensland Spermatogenesis relies on complex molecular mechanisms, essential for the genesis and differentiation of the male gamete. Germ cell differentiation starts at the testicular parenchyma and finishes in the epididymis, which has three main regions: head, body, and tail. RNA-sequencing data of the testicular parenchyma (TP), head epididymis (HE), and tail epididymis (TE) from four bulls (three biopsies per bull: 12 samples) were subjected to differential expression analyses, functional enrichment analyses, and co-expression analyses. The aim was to investigate the co-expression and infer possible regulatory roles for transcripts involved in the spermatogenesis of Bos indicus bulls. Across the three pairwise comparisons, 3,826 differentially expressed (DE) transcripts were identified, of which 384 are small RNAs. Functional enrichment analysis pointed to gene ontology (GO) terms related to ion channel activity, detoxification of copper, neuroactive receptors, and spermatogenesis. Using the regulatory impact factor (RIF) algorithm, we detected 70 DE small RNAs likely to regulate the DE transcripts considering all pairwise comparisons among tissues. The pattern of small RNA co-expression suggested that these elements are involved in spermatogenesis regulation. The 3,826 DE transcripts (mRNAs and small RNAs) were further subjected to co-expression analyses using the partial correlation and information theory (PCIT) algorithm for network prediction. Significant correlations underpinned the co-expression network, which had 2,216 transcripts connected by 158,807 predicted interactions. The larger network cluster was enriched for male gamete generation and had 15 miRNAs with significant RIF. The miRNA bta-mir-2886 showed the highest number of connections (601) and was predicted to down-regulate ELOVL3, FEZF2, and HOXA13 (negative co-expression correlations and confirmed with TargetScan). In short, we suggest that bta-mir-2886 and other small RNAs might modulate gene expression in the testis and epididymis, in Bos indicus cattle. Department of Production and Animal Health School of Veterinary Medicine São Paulo State University (UNESP) Department of Animal Science University of São Paulo/ESALQ School of Chemistry and Molecular Biosciences The University of Queensland Australian Institute for Bioengineering and Nanotechnology (AIBN) The University of Queensland CSIRO Agriculture and Food Queensland Bioscience Precinct Department of Production and Animal Health School of Veterinary Medicine São Paulo State University (UNESP)

Background: Host resilience (HR) to parasites can affect growth in pastured raised cattle. This study is a detailed investigation of the genetic mechanisms of HR to ticks (TICK), gastrointestinal nematodes (GIN), and Eimeria spp. (EIM) under natural infestation. HR was defined as the slope coefficient of random regression models of body weight (BW) when TICK, GIN, and EIM burdens were used as environmental gradients. The BW was evaluated in five measurement events (ME): when animals were 331, 385, 443, 498, and 555 days old on average. 7307 BW records were available from 1712 animals weighted at least in one ME. Out of those, 1075 animals had valid genotypic information after quality control analysis that were used in genome-wide association studies (GWAS) and GWAS meta-analyses to identify genomic regions associated with HR. Results: Both the genetic correlations between intercept and HR to each parasite, and the genetic correlations between BW measured in animals submitted to different parasite burden indicated that there was genotype x parasite burden interaction for BW, and selection for BW under environment with controlled parasite burden might be an efficient strategy to improve both, BW and HR. Furthermore, there was no impact of age of measurement on genetic variance estimates for HR to different parasites. However, genetic correlation between HR to the same parasite measured in different ages ranged from low to moderate in magnitude, with a posteriori means (high posterior density interval with 90% of samples) varying from 0.13 (-0.05; 0.35) to 0.40 (0.15; 0.63) for TICK, from 0.11 (-0.06; 0.29) to 0.52 (0.37; 0.67) for GIN and from 0.25 (0.07; 0.43) to 0.56 (0.34; 0.77) for EIM. Conclusions: These results indicate the importance of age of measurement in studies on HR. HR to GIN and EIM can be used as a complementary tool to parasitic control management, and a multiple trait selection method that combine BW and HR to parasites should be used in parasitic endemic areas to avoid economic losses due parasitic diseases.

Genome-wide gene expression is routinely used as a tool to gain a systems-level understanding of complex, biological processes. Numerical approaches that have been used to highlight influential genes include abundance, differential expression, differential variation, network connectivity and differential connectivity. Network connectivity tends to be built on a small subset of extremely high co-expression signals that are deemed significant, but this overlooks the vast majority of pairwise signals. Here, we aimed to assess a complementary strategy, namely whether the entire shape of the distribution of genome-wide co-expression values contains a meaningful biological signal that has hitherto remained hidden from view. We have developed a computational pipeline to assign one of 8 distributions (including normal, skewed, bimodal, kurtotic, inverted) to every gene. We then used a hypergeometric enrichment process to determine if particular genes (regulators versus non-regulators) and properties (differentially expressed or not) tend to be associated with particular distributions greater than would be expected by chance. Examination of several distinct data sets spanning 4 species indicates that there is indeed an additional biological signal present in the genome-wide distribution of co-expression values which would be overlooked by currently adopted approaches.Author summaryHigh-throughput technologies, such as RNA-Seq, enables access to a vast amount of data. Here, we describe a new approach to interrogate these data and extract further information to help researchers to understand complex phenotypes. Our method is based on gene-level co-expression distributions which were compared to eight possible template shapes to group genes with similar behaviours. The method was tested using five different datasets and the consistency of the results indicate it can be used as a complementary strategy to analyse transcriptomic data.

Spermatogenesis relies on complex molecular mechanisms, essential for the genesis and differentiation of the male gamete. Germ cell differentiation starts at the testicular parenchyma and finishes in the epididymis, which has three main regions: head, body, and tail. RNA-sequencing data of the testicular parenchyma (TP), head epididymis (HE), and tail epididymis (TE) from four bulls (three biopsies per bull: 12 samples) were subjected to differential expression analyses, functional enrichment analyses, and co-expression analyses. The aim was to investigate the co-expression and infer possible regulatory roles for transcripts involved in the spermatogenesis of Bos indicus bulls. Across the three pairwise comparisons, 3,826 differentially expressed (DE) transcripts were identified, of which 384 are small RNAs. Functional enrichment analysis pointed to gene ontology (GO) terms related to ion channel activity, detoxification of copper, neuroactive receptors, and spermatogenesis. Using the regulatory impact factor (RIF) algorithm, we detected 70 DE small RNAs likely to regulate the DE transcripts considering all pairwise comparisons among tissues. The pattern of small RNA co-expression suggested that these elements are involved in spermatogenesis regulation. The 3,826 DE transcripts (mRNAs and small RNAs) were further subjected to co-expression analyses using the partial correlation and information theory (PCIT) algorithm for network prediction. Significant correlations underpinned the co-expression network, which had 2,216 transcripts connected by 158,807 predicted interactions. The larger network cluster was enriched for male gamete generation and had 15 miRNAs with significant RIF. The miRNA bta-mir-2886 showed the highest number of connections (601) and was predicted to down-regulate ELOVL3, FEZF2, and HOXA13 (negative co-expression correlations and confirmed with TargetScan). In short, we suggest that bta-mir-2886 and other small RNAs might modulate gene expression in the testis and epididymis, in Bos indicus cattle.

Multitrait meta-analyses are a strategy to produce more accurate genome-wide association studies, especially for complex phenotypes. We carried out a meta-analysis study for traits related to sexual precocity in tropical beef cattle (Nellore and Brahman) aiming to identify important genomic regions affecting these traits. The traits included in the analyses were age at first calving (AFC), early pregnancy (EP), age at first corpus luteum (AGECL), first postpartum anoestrus interval (PPAI), and scrotal circumference (SC). The traits AFC, EP, and SCN were measured in Nellore cattle, while AGECL, PPAI, and SCB were measured in Brahman cattle. Meta-analysis resulted in 108 significant single-nucleotide polymorphisms (SNPs), at an empirical threshold P-value of 1.39 × 10-5 (false discovery rate [FDR] < 0.05). Within 0.5 Mb of the significant SNP, candidate genes were annotated and analyzed for functional enrichment. Most of the closest genes to the SNP with higher significance in each chromosome have been associated with important roles in reproductive function. They are TSC22D2, KLF7, ARHGAP29, 7SK, MAP3K5, TLE3, WDR5, TAF3, TMEM68, PPP1R15B, NR2F2, GALR1, SUFU, and KCNU1. We did not observe any significant SNP in BTA5, BTA12, BTA17, BTA18, BTA19, BTA20, BTA22, BTA23, BTA25, and BTA28. Although the majority of significant SNPs are in BTA14, it was identified significant associations in multiple chromosomes (19 out of 29 autosomes), which is consistent with the postulation that reproductive traits are complex polygenic phenotypes. Five proposed association regions harbor the majority of the significant SNP (76%) and were distributed over four chromosomes (P < 1.39 × 10-5, FDR < 0.05): BTA2 (5.55%) from 95 to 96 Mb, BTA4 (5.55%) from 94.1 to 94.8 Mb, BTA14 (59.26%) from 24 to 25 Mb and 29 to 30 Mb, and BTA21 (5.55%) from 6.7 Mb to 11.4 Mb. These regions harbored key genes related to reproductive function. Moreover, these genes were enriched for functional groups associated with immune response, maternal-fetal tolerance, pregnancy maintenance, embryo development, fertility, and response to stress. Further studies including other breeds and precocity traits could confirm the importance of these regions and identify new candidate regions for sexual precocity in beef cattle.

Made available in DSpace on 2018-12-11T17:38:25Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-06-01. Added 1 bitstream(s) on 2019-10-09T18:33:20Z : No. of bitstreams: 1 S0100-204X2018000600717.pdf: 678435 bytes, checksum: 176a6246ebde0a965c995d81a0311f98 (MD5) The objective of this work was to evaluate the effects of genomic information on the genetic evaluation of hip height in Brahman cattle using different matrices built from genomic and pedigree data. Hip height measurements from 1,695 animals, genotyped with high-density SNP chip or imputed from 50 K high-density SNP chip, were used. The numerator relationship matrix (NRM) was compared with the H matrix, which incorporated the NRM and genomic relationship (G) matrix simultaneously. The genotypes were used to estimate three versions of G: observed allele frequency (HGOF), average minor allele frequency (HGMF), and frequency of 0.5 for all markers (HG50). For matrix comparisons, animal data were either used in full or divided into calibration (80% older animals) and validation (20% younger animals) datasets. The accuracy values for the NRM, HGOF, and HG50 were 0.776, 0.813, and 0.594, respectively. The NRM and HGOF showed similar minor variances for diagonal and off-diagonal elements, as well as for estimated breeding values. The use of genomic information resulted in relationship estimates similar to those obtained based on pedigree; however, HGOF is the best option for estimating the genomic relationship matrix and results in a higher prediction accuracy. The ranking of the top 20% animals was very similar for all matrices, but the ranking within them varies depending on the method used. O objetivo deste trabalho foi avaliar os efeitos da informação genômica na avaliação genética para altura do quadril em bovinos da raça Brahman, por meio de diferentes matrizes construídas com dados genômicos e de pedigree. Utilizaram-se medidas de altura do quadril de 1.695 animais, genotipados com SNP chip de alta densidade ou imputados do 50 K SNP chip de alta densidade. A matriz de pedigree numerator relationship matrix (NRM) foi comparada à matriz H, a qual incorporou as matrizes NRM e de parentesco genômico (G) simultaneamente. Os genótipos foram utilizados para estimar três versões de G: frequência observada dos alelos (HGOF), média da menor frequência alélica (HGMF) e frequência de 0,5 para todos os marcadores (HG50). Para a comparação das matrizes, foram utilizadas informações completas ou divididas em conjuntos de dados de calibração (80% dos animais mais velhos) e de validação (20% dos mais jovens). Os valores de acurácia para NRM, HGOF e HG50 foram 0,776, 0,813 e 0,594, respectivamente. NRM e HGOF foram semelhantes, com menores variâncias para os elementos da diagonal e fora da diagonal, bem como para os valores genéticos estimados. O uso de informações genômicas resultou em estimativas de parentesco semelhantes às obtidas com base em pedigree; entretanto, HGOF é a melhor opção para estimar a matriz de parentesco genômico e resulta em maiores acurácias de predição. O ranking dos animais top 20% foi muito semelhante para as matrizes, mas a classificação dentro destas varia dependendo do método. Universidade Estadual Paulista (Unesp) Faculdade de Ciências Agrárias e Veterinárias Campus Jaboticabal, Via de Acesso Prof. Paulo Donato Castellane, s/no The University of Queensland School of Chemistry and Molecular Biosciences Australian Agricultural Company Corporate Office, GPO Box 587 Commonwealth Scientific and Industrial Research Organisation Queensland Bioscience Precinct St Lucia Reception, 306 Carmody Road Universidade Estadual Paulista (Unesp) Faculdade de Ciências Agrárias e Tecnológicas, Rodovia Comandante João Ribeiro de Barros, SP 294, Km 651 The University of Queensland Queensland Alliance for Agriculture and Food Innovation Centre for Animal Science Queensland Bioscience Precint, Building #80, 306 Carmody Road Universidade Estadual Paulista (Unesp) Faculdade de Ciências Agrárias e Veterinárias Campus Jaboticabal, Via de Acesso Prof. Paulo Donato Castellane, s/no Universidade Estadual Paulista (Unesp) Faculdade de Ciências Agrárias e Tecnológicas, Rodovia Comandante João Ribeiro de Barros, SP 294, Km 651

Numerical approaches to high-density single nucleotide polymorphism (SNP) data are often employed independently to address individual questions. We linked independent approaches in a bioinformatics pipeline for further insight. The pipeline driven by heterozygosity and Hardy-Weinberg equilibrium (HWE) analyses was applied to characterize Bos taurus and Bos indicus ancestry. We infer a gene co-heterozygosity network that regulates bovine fertility, from data on 18,363 cattle with genotypes for 729,068 SNP. Hierarchical clustering separated populations according to Bos taurus and Bos indicus ancestry. The weights of the first principal component were subjected to Normal mixture modelling allowing the estimation of a gene's contribution to the Bos taurus-Bos indicus axis. We used deviation from HWE, contribution to Bos indicus content and association to fertility traits to select 1,284 genes. With this set, we developed a co-heterozygosity network where the group of genes annotated as fertility-related had significantly higher Bos indicus content compared to other functional classes of genes, while the group of genes associated with milk production had significantly higher Bos taurus content. The network analysis resulted in capturing novel gene associations of relevance to bovine domestication events. We report transcription factors that are likely to regulate genes associated with cattle domestication and tropical adaptation. Our pipeline can be generalized to any scenarios where population structure requires scrutiny at the molecular level, particularly in the presence of a priori set of genes known to impact a phenotype of evolutionary interest such as fertility. Made available in DSpace on 2018-02-01T23:36:44Z (GMT). No. of bitstreams: 1 APBostaurusPlosOne.pdf: 4208873 bytes, checksum: cc037124470b280aaa27de1136e41635 (MD5) Previous issue date: 2018-02-01 Artigo e0181930. Na publicação: Mauricio A. Mudadu, Luciana Regitano.

Fertility traits are economically important in cattle breeding programs. Scrotal circumference (SC) measures are repeatable, easily obtained, highly heritable, and positively correlated with female fertility traits and sperm quality traits in males. A useful approach to summarize SC measures over time is using nonlinear models, which summarize specific measures of SC in a few parameters with biological interpretation. This approach facilitates the selection of bulls with larger SC and maturity index (K), that is, early maturing animals. Because SC is a sex-limited trait, identifying the underlying genomics of growth curve parameters will allow selection across both males and females. We reported the first multitrait genomewide association study (GWAS) of estimated growth curve parameters for SC data in Brahman cattle. Five widely used nonlinear models were tested to fit a total of 3,612 SC records, measured at 6, 12, 18, and 24 mo of age. The von Bertalanffy model, individually fitted for each animal, best fit this SC data. Parameter estimates SC at maturity (A) and K as well as SC at all ages were jointly analyzed in a GWAS to identify 1-Mb regions most strongly associated with each trait. Heritabilities were 0.25 for K and 0.32 for A and ranged from 0.51 to 0.72 for SC at 6 (SC6), 12 (SC12), 18 (SC18), and 24 mo of age (SC24). An overlapping window on chromosome 14 explaining around 0.8% of genetic variance for K, SC12, SC18, and SC24 was observed. The major positional candidate genes within 1 Mb upstream and downstream of this overlapping window were , , , and . Windows of 1 Mb explaining more than 0.4% of each trait on chromosomes 1, 3, 6, 7, 14, 17, 18, 24, 25, and 26 were identified. Pathways and net-work analyses were indicated through transcription factors playing a role on fertility traits: , , , , , , and . Further validation studies on larger populations or other breeds are required to validate these findings and to improve our understanding of the biology and complex genetic architecture of traits associated with scrotal growth and male fertility in cattle.

To understand genes, pathways, and networks related to puberty, we characterized the transcriptome of two tissues: the pituitary gland and ovaries. Samples were harvested from pre- and postpubertal Brahman heifers (same age group). Brahman heifers () are older at puberty compared with , a productivity issue. With RNA sequencing, we identified differentially expressed (DEx) genes and important transcription factors (TF) and predicted coexpression networks. The number of DEx genes detected in the pituitary gland was 284 ( < 0.05), and was the most DEx gene (fold change = 4.12, = 0.01). The gene promotes bone mineralization through transforming growth factor-β (TGFβ) signaling. Further studies of the link between bone mineralization and puberty could target . In ovaries, 3,871 genes were DEx ( < 0.05). Four highly DEx genes were noteworthy for their function: (a γ-aminobutyric acid [GABA] transporter), (), and () and its receptor . These genes had higher ovarian expression in postpubertal heifers. The GABA and its receptors and transporters were expressed in the ovaries of many mammals, suggesting a role for this pathway beyond the brain. The pathway has been known to influence the timing of puberty in rats, via modulation of GnRH. The effects of at the hypothalamus, pituitary gland, and ovaries have been documented. and its receptors are known factors in the release of GnRH, similar to and GABA, although their roles in ovarian tissue are less clear. Pathways previously related to puberty such as TGFβ signaling ( = 6.71 × 10), Wnt signaling ( = 4.1 × 10), and peroxisome proliferator-activated receptor (PPAR) signaling ( = 4.84 × 10) were enriched in our data set. Seven genes were identified as key TF in both tissues: , , , , , , and a novel gene. An ovarian subnetwork created with TF and significant ovarian DEx genes revealed five zinc fingers as regulators: , , , , and . Recent work of hypothalamic gene expression also pointed to zinc fingers as TF for bovine puberty. Although some zinc fingers may be ubiquitously expressed, the identification of DEx genes in common across tissues points to key regulators of puberty. The hypothalamus and pituitary gland had eight DEx genes in common. The hypothalamus and ovaries had 89 DEx genes in common. The pituitary gland and ovaries had 48 DEx genes in common. Our study confirmed the complexity of puberty and suggested further investigation on genes that code zinc fingers.

Traits such as sperm morphology and motility are routine in veterinarian evaluations of bull fertility. However, they rarely are included in livestock breeding programs, which typically use only scrotal circumference (SC) and some female traits for fertility selection. We studied 25 male fertility traits measured in two research populations of bulls (1,099 Brahman, and 1,719 Tropical Composite) and one commercial population (2,490 Santa Gertrude bulls). Measurements included standard semen evaluation (e.g. sperm motility and morphology) and SC. In the research data, we also measured sperm DNA fragmentation and sperm protamine deficiency for about 50% of the bulls. Using a mixture of genomic and pedigree analyses, we estimated heritabilities and genetic correlations for all traits, in each population. Our analyses suggest that bull fertility traits have a heritable component, which makes selective breeding possible. The phenotype variation in sperm DNA fragmentation and sperm protamine deficiency traits also have a heritable component (h2 ~ 0.05–0.22). These first estimates for heritability of sperm chromatin phenotypes require further studies, with larger datasets, to corroborate present results. In all three populations, we observed genetic correlations across traits that were favorable, but not high. For example, the percentage of normal sperm (PNS) from the sperm morphology evaluation was positively correlated with SC. In the research data, sperm DNA fragmentation was negatively correlated with PNS (r2 ~ 0.23–0.33), meaning that bulls with a higher PNS had less DNA fragmentation, being therefore more fertile according to both indicators. Given the favorable and yet not high genetic correlations between traits, it is possible to envision that sperm chromatin phenotypes might form a panel, together with PNS and SC, for a comprehensive bull fertility index. Selection indices that include fertility traits are being implemented in the dairy industry and could be recommended for beef cattle, too. An index that benefits from the favorable genetic correlations between traits that describe different aspects of bull fertility is a sensible approach to selective breeding. The clinical use of complementary indicators for male fertility is largely accepted, when deciding on bull fitness for the mating season. We propose extending this rationale to create a multi-trait index that captures genetic merit for bull fertility. In addition, we performed genome-wide association analyses in the research data and identified eight QTLs in the X chromosome. Correlations and shared SNP associations support the hypothesis that these phenotypes have the same underlying cause: abnormal spermatogenesis. In conclusion, it is possible to improve bull fertility through selective breeding, by measuring complementary fertility traits. Genomic selection for bull fertility might be more accurate if the X chromosome mutations that underlie the discovered QTL are included in the analyses. Polymorphisms associated with fertility in the bull accumulate in the X chromosome, as they do in humans and mice, thus suggesting specialization of this chromosome.

Mineral contents in bovine muscle can affect meat quality, growth, health, and reproductive traits. To better understand the genetic basis of this phenotype in Nelore (Bos indicus) cattle, we analysed genome-wide mRNA and miRNA expression data from 114 muscle samples. The analysis implemented a new application for two complementary algorithms: the partial correlation and information theory (PCIT) and the regulatory impact factor (RIF), in which we included the estimated genomic breeding values (GEBVs) for the phenotypes additionally to the expression levels, originally proposed for these methods. We used PCIT to determine putative regulatory relationships based on significant associations between gene expression and GEBVs for each mineral amount. Then, RIF was adopted to determine the regulatory impact of genes and miRNAs expression over the GEBVs for the mineral amounts. We also investigated over-represented pathways, as well as pieces of evidences from previous studies carried in the same population and in the literature, to determine regulatory genes for the mineral amounts. For example, NOX1 expression level was positively correlated to Zinc and has been described as Zinc-regulated in humans. Based on our approach, we were able to identify genes, miRNAs and pathways not yet described as underlying mineral amount. The results support the hypothesis that extracellular matrix interactions are the core regulator of mineral amount in muscle cells. Putative regulators described here add information to this hypothesis, expanding the knowledge on molecular relationships between gene expression and minerals. Made available in DSpace on 2020-09-09T04:37:14Z (GMT). No. of bitstreams: 1 AP-Genetic-regulators-2020.pdf: 3953162 bytes, checksum: f7f057405a94ac732a64d0f4b4788219 (MD5) Previous issue date: 2020 Article: 8436.

Made available in DSpace on 2019-10-04T12:15:56Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-09-03 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Mineral content affects the biological processes underlying beef quality. Muscle mineral concentration depends not only on intake-outtake balance and muscle type, but also on age, environment, breed, and genetic factors. To unveil the genetic factors involved in muscle mineral concentration, we applied a pairwise differential gene expression analysis in groups of Nelore steers genetically divergent for nine different mineral concentrations. Here, based on significant expression differences between contrasting groups, we presented candidate genes for the genetic regulation of mineral concentration in muscle. Functional enrichment and protein-protein interaction network analyses were carried out to search for gene regulatory processes concerning each mineral. The core genetic regulation for all minerals studied, except Zn, seems to rest on interactions between components of the extracellular matrix. Regulation of adipogenesis-related pathways was also significant in our results. Antagonistic patterns of gene expression for fatty acid metabolism-related genes may explain the Cu and Zn antagonistic effect on fatty acid accumulation. Our results shed light on the role of these minerals on cell function. Univ Fed Sao Carlos, Dept Evolutionary Genet & Mol Biol, Sao Carlos, SP, Brazil Univ Sao Paulo, Dept Anim Sci, ESALQ, Piracicaba, Brazil Embrapa Pecuaria Sudeste, Sao Carlos, SP, Brazil Univ Sao Paulo, Phys Inst Sao Carlos, Sao Carlos, SP, Brazil Sao Paulo State Univ, Anim Sci Dept, Lab Mol Genet, Jaboticabal, Brazil Bahia Fed Inst Educ Sci & Technol, Ilheus, Brazil Univ Queensland, Fac Sci, Sch Chem & Mol Biosci, Brisbane, Qld, Australia NGS Solucoes Genom, Rua Ajudante Albano 847, Piracicaba, SP, Brazil Sao Paulo State Univ, Anim Sci Dept, Lab Mol Genet, Jaboticabal, Brazil FAPESP: 2012/23638-8

Made available in DSpace on 2019-10-06T16:42:20Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-01-01 Animal breeding programs have used molecular genetic tools as an auxiliary method to identify and select animals with superior genetic merit for milk production and milk quality traits as well as disease resistance. Genes of the major histocompatibility complex (MHC) are important molecular markers for disease resistance that could be applied for genetic selection. The aim of this study was to identify single nucleotide polymorphisms (SNPs) and haplotypes in DRB2, DRB3, DMA, and DMB genes in Murrah breed and to analyze the association between molecular markers and milk, fat, protein and mozzarella production, fat and protein percentage, and somatic cell count. Two hundred DNA samples from Murrah buffaloes were used. The target regions of candidate genes were amplified by polymerase chain reaction (PCR) followed by sequencing and identification of polymorphisms. Allele and genotype frequencies, as well as linkage disequilibrium between SNPs, were calculated. Genotypes were used in association analyses with milk production and quality traits. Except for the DMA gene, identified as monomorphic, the other genes presented several polymorphisms. The DMB, DRB2, and DRB3 genes presented two, six, and seven SNPs, respectively. Fifty-seven haplotype blocks were constructed from 15 SNPs identified, which was used in association analyses. All the studied traits had at least one associated haplotype. In conclusion, it is suggested that the haplotypes found herein can be associated with important traits related to milk production and quality. Department of Animal Science School of Agricultural and Veterinarian Sciences (FCAV) São Paulo State University (UNESP) Department of Exact Sciences School of Agricultural and Veterinarian Sciences (FCAV) São Paulo State University (UNESP) School of Chemistry and Molecular Biosciences The University of Queensland, Saint Lucia Campus Department of Animal Science School of Agricultural and Veterinarian Sciences (FCAV) São Paulo State University (UNESP) Department of Exact Sciences School of Agricultural and Veterinarian Sciences (FCAV) São Paulo State University (UNESP)

We introduce an innovative approach to lowering the overall cost of obtaining genomic EBV (GEBV) and encourage their use in commercial extensive herds of Brahman beef cattle. In our approach, the DNA genotyping of cow herds from 2 independent properties was performed using a high-density bovine SNP chip on DNA from pooled blood samples, grouped according to the result of a pregnancy test following their first and second joining opportunities. For the DNA pooling strategy, 15 to 28 blood samples from the same phenotype and contemporary group were allocated to pools. Across the 2 properties, a total of 183 pools were created representing 4,164 cows. In addition, blood samples from 309 bulls from the same properties were also taken. After genotyping and quality control, 74,584 remaining SNP were used for analyses. Pools and individual DNA samples were related by means of a "hybrid" genomic relationship matrix. The pooled genotyping analysis of 2 large and independent commercial populations of tropical beef cattle was able to recover significant and plausible associations between SNP and pregnancy test outcome. We discuss 24 SNP with significant association ( < 1.0 × 10) and mapped within 40 kb of an annotated gene. We have established a method to estimate the GEBV in young herd bulls for a trait that is currently unable to be predicted at all. In summary, our novel approach allowed us to conduct genomic analyses of fertility in 2 large commercial Brahman herds managed under extensive pastoral conditions.

Puberty onset is a developmental process influenced by genetic determinants, environment, and nutrition. Mutations and regulatory gene networks constitute the molecular basis for the genetic determinants of puberty onset. The emerging knowledge of these genetic determinants presents opportunities for innovation in the breeding of early pubertal cattle. This paper presents new data on hypothalamic gene expression related to puberty in (Brahman) in age- and weight-matched heifers. Six postpubertal heifers were compared with 6 prepubertal heifers using whole-genome RNA sequencing methodology for quantification of global gene expression in the hypothalamus. Five transcription factors (TF) with potential regulatory roles in the hypothalamus were identified in this experiment: , , , , and . These TF genes were significantly differentially expressed in the hypothalamus of postpubertal versus prepubertal heifers and were also identified as significant according to the applied regulatory impact factor metric ( < 0.05). Two of these 5 TF, and , were zinc fingers, belonging to a gene family previously reported to have a central regulatory role in mammalian puberty. The gene belongs to the family of homologues of Drosophila sine oculis () genes implicated in transcriptional regulation of gonadotrope gene expression. Tumor-related genes such as and are known to affect basic cellular processes that are relevant in both cancer and developmental processes. Mutations in were associated with puberty in humans. Mutations in these TF, together with other genetic determinants previously discovered, could be used in genomic selection to predict the genetic merit of cattle (i.e., the likelihood of the offspring presenting earlier than average puberty for Brahman). Knowledge of key mutations involved in genetic traits is an advantage for genomic prediction because it can increase its accuracy.

Puberty onset is a multifactorial process influenced by genetic determinants and environmental conditions, especially nutritional status. Genes, genetic variations, and regulatory networks compose the molecular basis of achieving puberty. In this article, we reviewed the discovery of multiple polymorphisms and genes associated with heifer puberty phenotypes and discuss the opportunities to use this evolving knowledge of genetic determinants for breeding early pubertal Bos indicus-influenced cattle. The discovery of polymorphisms and genes was mainly achieved through candidate gene studies, quantitative trait loci analyses, genome-wide association studies, and recently, global gene expression studies (transcriptome). These studies are recapitulated and summarized in the current review.

Progesterone signaling and uterine function are crucial in terms of pregnancy establishment. To investigate how the uterine tissue and its secretion changes in relation to puberty, we sampled tissue and uterine fluid from six pre- and six postpubertal Brahman heifers. Post-pubertal heifers were sampled in the luteal phase. Gene expression of the uterine tissue was investigated with RNA-sequencing, whereas the uterine fluid was used for protein profiling with mass spectrometry. A total of 4034 genes were differentially expressed (DE) at a nominal P-value of 0.05, and 26 genes were significantly DE after Bonferroni correction (P < 3.1 9 10 À6 ). We also identified 79 proteins (out of 230 proteins) that were DE (P < 1 9 10 À5 ) in the uterine fluid. When we compared proteomics and transcriptome results, four DE proteins were identified as being encoded by DE genes: OVGP1, GRP, CAP1 and HBA. Except for CAP1, the other three had lower expression post-puberty. The function of these four genes hypothetically related to preparation of the uterus for a potential pregnancy is discussed in the context of puberty. All DE genes and proteins were also used in pathway and ontology enrichment analyses to investigate overall function. The DE genes were enriched for terms related to ribosomal activity. Transcription factors that were deemed key regulators of DE genes are also reported. Transcription factors ZNF567, ZNF775, RELA, PIAS2, LHX4, SOX2, MEF2C, ZNF354C, HMG20A, TCF7L2, ZNF420, HIC1, GTF3A and two novel genes had the highest regulatory impact factor scores. These data can help to understand how puberty influences uterine function.

Changes in brain metabolism are a hallmark of Alcohol Use Disorder (AUD). Determining how AUD changes the brain proteome is critical for understanding the effects of alcohol consumption on biochemical processes in the brain. We used data-independent acquisition mass spectrometry proteomics to study differences in the abundance of proteins associated with AUD in pre-frontal lobe and motor cortex from autopsy brain. AUD had a substantial effect on the overall brain proteome exceeding the inherent differences between brain regions. Proteins associated with glycolysis, trafficking, the cytoskeleton, and excitotoxicity were altered in abundance in AUD. We observed extensive changes in the abundance of key metabolic enzymes, consistent with a switch from glucose to acetate utilization in the AUD brain. We propose that metabolic adaptations allowing efficient acetate utilization contribute to ethanol dependence in AUD.

Altres ajuts: Fundação de Amparo à Pesquisa do Estado de Minas Gerais APQ APQ-01377-17. Conselho Nacional de Desenvolvimento Científico e Tecnológico CNPq 312068/2015-8 The identification of biological processes related to the regulation of complex traits is a difficult task. Commonly, complex traits are regulated through a multitude of genes contributing each to a small part of the total genetic variance. Additionally, some loci can simultaneously regulate several complex traits, a phenomenon defined as pleiotropy. The lack of understanding on the biological processes responsible for the regulation of these traits results in the decrease of selection efficiency and the selection of undesirable hitchhiking effects. The identification of pleiotropic key-regulator genes can assist in developing important tools for investigating biological processes underlying complex traits. A multi-breed and multi-OMICs approach was applied to study the pleiotropic effects of key-regulator genes using three independent beef cattle populations evaluated for fertility traits. A pleiotropic map for 32 traits related to growth, feed efficiency, carcass and meat quality, and reproduction was used to identify genes shared among the different populations and breeds in pleiotropic regions. Furthermore, data-mining analyses were performed using the Cattle QTL database (CattleQTLdb) to identify the QTL category annotated in the regions around the genes shared among breeds. This approach allowed the identification of a main gene network (composed of 38 genes) shared among breeds. This gene network was significantly associated with thyroid activity, among other biological processes, and displayed a high regulatory potential. In addition, it was possible to identify genes with pleiotropic effects related to crucial biological processes that regulate economically relevant traits associated with fertility, production and health, such as MYC, PPARG, GSK3B, TG and IYD genes. These genes will be further investigated to better understand the biological processes involved in the expression of complex traits and assist in the identification of functional variants associated with undesirable phenotypes, such as decreased fertility, poor feed efficiency and negative energetic balance.

The adipose tissue has been recognized as an active endocrine organ which can modulate numerous physiological processes such as metabolism, appetite, immunity, and reproduction. The aim of this study was to look for differentially abundant proteins and their biological functions in the abdominal adipose tissue between pre- and postpubertal Brahman heifers. Twelve Brahman heifers were divided into 2 groups and paired on slaughter day. Prepubertal heifers had never ovulated and postpubertal heifers were slaughtered on the luteal phase of their second estrous cycle. After ensuring the occurrence of puberty in postpubertal heifers, abdominal adipose tissue samples were collected. Mass spectrometry proteomic analysis identified 646 proteins and revealed that 171 proteins showed differential abundance in adipose tissue between the pre- and postpuberty groups (adjusted P-value < 0.05). Data are available via ProteomeXchange with identifier PXD009452. Using a list of 51 highly differentially abundant proteins as the target (adjusted P-value < 10(−5)), we found 14 enriched pathways. The results indicated that gluconeogenesis was enhanced when puberty approached. The metabolism of glucose, lipids, and AA in the adipose tissue mainly participated in oxidation and energy supply for heifers when puberty occurred. Our study also revealed the differentially abundant proteins were enriched for estrogen signaling and PI3K-Akt signaling pathways, which are known integrators of metabolism and reproduction. These results suggest new candidate proteins that may contribute to a better understanding of the signaling mechanisms that relate adipose tissue function to puberty. Protein–protein interaction network analysis identified 4 hub proteins that had the highest degrees of connection: PGK1, ALDH5A1, EEF2, and LDHB. Highly connected proteins are likely to influence the functions of all differentially abundant proteins identified, directly or indirectly.

Cow fertility traits are key factors that influence beef production profitability, and is particularly important in tropical environments where achieving high reproductive rates is challenging. Genomic selection (GS) has the potential to improve genetic gain rates for reproduction, if genomic estimated breeding values (GEBV) for these traits are sufficiently accurate. Several Bayesian models have already been proposed for GS, but the benchmarks used to compare them are still scarce, mainly for age at first calving (AFC) in Nellore cattle. A total of 714 AFC records of Nellore cows and 70 K SNPs were used to compare five models, Bayes A (BA), Bayes B (BB), Bayes Cπ (BCπ), Bayesian LASSO (BL) and Bayesian Ridge Regression (BRR). These models were compared by cross validation, randomly partitioning the whole population into 7 subsets (7-fold) and replicated 15 times. The prediction accuracy were 0.24 (0.11), 0.23 (0.11), 0.33 (0.13), 0.24 (0.11) and 0.38 (0.13), for BA, BB, BCπ, BL and BRR, respectively. Thus, BRR resulted in 14%, 15%, 5% and 14% additional prediction accuracy compared to BA, BB, BCπ and BL, respectively. Pearson and Spearman correlations between GEBVs obtained from BRR and BB models were, 0.97 and 0.94, respectively. It suggested that little difference in terms of animal selection would result from these methods. A more parsimonious model, such as BRR, can be successfully used in breeding programs to generate GEBVs which further enable consistent selection decisions. Although moderate accuracies of GEBV for AFC can be achieved, we found low efficiency of GS for AFC in the present population due to the small sample size and low heritability, reinforcing that GS efficiency is highly dependent upon these factors.

Multitrait meta-analyses are a strategy to produce more accurate genome-wide association studies, especially for complex phenotypes. We carried out a meta-analysis study for traits related to sexual precocity in tropical beef cattle (Nellore and Brahman) aiming to identify important genomic regions affecting these traits. The traits included in the analyses were age at first calving (AFC), early pregnancy (EP), age at first corpus luteum (AGECL), first postpartum anoestrus interval (PPAI), and scrotal circumference (SC). The traits AFC, EP, and SC(N) were measured in Nellore cattle, while AGECL, PPAI, and SC(B) were measured in Brahman cattle. Meta-analysis resulted in 108 significant single-nucleotide polymorphisms (SNPs), at an empirical threshold P-value of 1.39 × 10(−5) (false discovery rate [FDR] < 0.05). Within 0.5 Mb of the significant SNP, candidate genes were annotated and analyzed for functional enrichment. Most of the closest genes to the SNP with higher significance in each chromosome have been associated with important roles in reproductive function. They are TSC22D2, KLF7, ARHGAP29, 7SK, MAP3K5, TLE3, WDR5, TAF3, TMEM68, PPP1R15B, NR2F2, GALR1, SUFU, and KCNU1. We did not observe any significant SNP in BTA5, BTA12, BTA17, BTA18, BTA19, BTA20, BTA22, BTA23, BTA25, and BTA28. Although the majority of significant SNPs are in BTA14, it was identified significant associations in multiple chromosomes (19 out of 29 autosomes), which is consistent with the postulation that reproductive traits are complex polygenic phenotypes. Five proposed association regions harbor the majority of the significant SNP (76%) and were distributed over four chromosomes (P < 1.39 × 10(−5), FDR < 0.05): BTA2 (5.55%) from 95 to 96 Mb, BTA4 (5.55%) from 94.1 to 94.8 Mb, BTA14 (59.26%) from 24 to 25 Mb and 29 to 30 Mb, and BTA21 (5.55%) from 6.7 Mb to 11.4 Mb. These regions harbored key genes related to reproductive function. Moreover, these genes were enriched for functional groups associated with immune response, maternal–fetal tolerance, pregnancy maintenance, embryo development, fertility, and response to stress. Further studies including other breeds and precocity traits could confirm the importance of these regions and identify new candidate regions for sexual precocity in beef cattle.

In this study, we aimed to provide a wet laboratory validation for a set of single nucleotide polymorphisms (SNP), which had been identified as candidate functional variants in silico. Genotyping for candidate SNP was performed in Brahman and Tropical Composite cattle. After quality control, 29 SNP were first investigated individually for their association with female reproductive traits and then used as a panel for genomic predictions. The reproductive traits studied were age at first corpus luteum (AGECL; days), post-partum anoestrus interval (PPAI; days), and a binary trait that described if the cow had ovulated before weaning the first calf or not (PW, 0-1). Single nucleotide polymorphisms in six genes (FOXA2, TRAF4, IRF2, IRF1, BPTF, and CPEB1) were found to be significantly associated with reproduction traits . The genomic prediction method used was BayesR, to accommodate the 29 new SNP and compare their performance with predictions based on 50K genotypes (Illumina SNP chip). When new SNP and PLAG1 mutation rs109231213 were included in the genomic predictions for female reproductive traits their accuracies improved. The best predictions were obtained by combining the new SNP and the 50K SNP using BayesR analysis, with a 4% improvement in accuracy. The proportion of the genetic variance explained by the new SNP together was 0.07 for AGECL, 0.03 for PPAI, and 0.02 for PW. It would be favourable to include these new SNP in future versions of bovine SNP chips to target selection for female reproductive traits. These new SNP are likely to improve genomic predictions for female reproductive traits in tropical beef cattle breeds, with varying degrees of Bos indicus content.

Fixed-time AI (FTAI) is a powerful tool for genetic improvement of extensively managed beef cattle. A genomewide association study (GWAS) was conducted to investigate genes and genetic markers associated with the outcome (pregnant or not pregnant) of FTAI in 614 commercial Brahman heifers genotyped for 18,895 SNP and imputed to 51,588 SNP. The likelihood of Brahman heifers becoming pregnant after hormonal treatment to synchronize ovulation followed by FTAI was influenced by the content of their genomes, as determined by a principal component analysis. The principal component analysis involved comparisons between the studied heifers and populations of known and ancestry. The heritability of FTAI outcome was = 0.18, which is higher than for most other reproductive outcome traits. The number of SNP associated with FTAI outcome was 101 ( < 0.001, false discovery rate = 0.53). Compared with all SNP tested, associated SNP had a tendency for highly divergent allelic frequencies between and . Associated SNP were located in nearly all chromosomes, a result that shows a complex genetic architecture that is typical of highly complex traits with low heritability. Considering this and previous GWAS that examined Brahman heifer puberty and postpartum anestrus interval, 3 genomic regions emerge as important for overall Brahman heifer fertility, which mapped to chromosomes 1, 7, and 9. Further analyses, including improved genome annotation, are required to elucidate the link between these regions and heifer fertility. Additional studies are needed to confirm SNP and gene associations reported herein and further elucidate the genetics of FTAI outcome. Future GWAS should target other Braham populations and additional cattle breeds with FTAI records, including breeds with higher ancestry.

Inbreeding has the potential to negatively impact animal performance. Strategies to monitor and mitigate inbreeding depression require that it can be accurately estimated. Here, we used genomewide SNP data to explore 3 alternative measures of genomic inbreeding: the diagonal elements of the genomic relationship matrix (FGRM), the proportion of homozygous SNP (FHOM), and the proportion of the genome covered by runs of homozygosity (FROH). We used 2,111 Brahman (BR) and 2,550 Tropical Composite (TC) cattle with phenotypes recorded for 10 traits of relevance to tropical adaptation. We further explored 3 marker densities ranging from a high-density chip (729,068 SNP), a medium-density chip (71,726 SNP) specifically designed for cattle, and a low-density chip (18,860 SNP) associated with the measures of inbreeding. Measures of FGRM were highly correlated across the 3 SNP densities and negatively correlated with FHOM and FROH in the BR population. In both populations, there was a strong positive correlation for each measure of inbreeding across the 3 SNP panels. We found significant ( < 0.01) inbreeding depression for various traits, particularly when using the highest-density SNP chip in the BR population, where inbreeding was negatively associated with coat color and coat type such that inbred animals presented shorter, slicker, and lighter coats. Based on FGRM using the medium-density chip, we found that a 1% increase in inbreeding in the BR and TC populations was associated with a decrease of 0.514 and 0.579 kg BW, respectively, in yearlings. In the TC population, a 1% increase in FHOM was associated with a decrease in BCS of -0.636% ( < 0.001). The low-density chip, comprising SNP associated with inbreeding, captured genes, and regions with pleiotropic effects ( < 0.001). However, it did not improve our ability to identify inbreeding depression, relative to the use of higher-density panels. We conclude that where heterogeneous populations are present, such as in tropical environments where composite animals abound, measures of inbreeding that do not depend on allele frequencies, such as FHOM and FROH, are preferable for estimating genomic inbreeding. Finally, the sustainable intensification of livestock systems in tropical regions will rely on genetic safeguards to ensure that productivity is improved while also adapting animals to cope with climate change. The results of this study are a step toward achieving that goal.

The association between sperm morphology characteristics and DNA conformation and integrity is still controversial. In bulls, major morphological sperm abnormalities have been associated with reduced fertility, and morphological assessment is used to provide an indication of potential fertility of the individual. Sperm DNA fragmentation and damage has a negative effect on embryo development and subsequently fertility, with bull spermatozoa generally displaying low levels of DNA damage and tight chromatin. However, sensitive methods for detecting chromatin damage may reveal associations with morphological defects. The objective was to determine whether morphological sperm abnormalities and variables expressing sperm DNA integrity and protamination are correlated in bulls, using the sperm chromatin structure assay (SCSA) and the sperm protamine deficiency assay (SPDA). Electroejaculated samples (n = 1009) from two-year-old tropically adapted bulls were split and fixed and submitted to microscopic sperm morphology assessment, and snap-frozen for sperm nuclear integrity assessments by SPDA and SCSA. For SPDA, the variables were defective (MCB) and deprotaminated (HCB), and for SCSA, the variables were DNA fragmentation index (DFI) and high DNA stainability (HDS). HCB correlated with DFI; τKen2 = 0.317 and HDS; 0.098, and MCB correlated with DFI; 0.183 (p < 0.001). The percentage of morphological normal spermatozoa was correlated negatively to DFI; τKen2 = -0.168, MCB; -0.116 and HCB; -0.137 (p < 0.001). HCB and DFI were both positively correlated to head defects, proximal droplets, and spermatogenic immaturity, but not to distal droplets, vacuoles, or diadems. Sperm DNA integrity and protamination, using the SCSA and SPDA, respectively, in bulls show associations with morphological parameters, particularly with head shape abnormalities and indicators of spermatogenic immaturity, including proximal droplets. The vacuoles and diadem defects were not correlated with sperm nuclear integrity, and hence, these are likely physiological features that may not directly affect sperm chromatin configuration.

We performed a genome-wide mapping for the age at first calving (AFC) with the goal of annotating candidate genes that regulate fertility in Nellore cattle. Phenotypic data from 762 cows and 777k SNP genotypes from 2,992 bulls and cows were used. Single nucleotide polymorphism (SNP) effects based on the single-step GBLUP methodology were blocked into adjacent windows of 1 Megabase (Mb) to explain the genetic variance. SNP windows explaining more than 0.40% of the AFC genetic variance were identified on chromosomes 2, 8, 9, 14, 16 and 17. From these windows, we identified 123 coding protein genes that were used to build gene networks. From the association study and derived gene networks, putative candidate genes (e.g., PAPPA, PREP, FER1L6, TPR, NMNAT1, ACAD10, PCMTD1, CRH, OPKR1, NPBWR1 and NCOA2) and transcription factors (TF) (STAT1, STAT3, RELA, E2F1 and EGR1) were strongly associated with female fertility (e.g., negative regulation of luteinizing hormone secretion, folliculogenesis and establishment of uterine receptivity). Evidence suggests that AFC inheritance is complex and controlled by multiple loci across the genome. As several windows explaining higher proportion of the genetic variance were identified on chromosome 14, further studies investigating the interaction across haplotypes to better understand the molecular architecture behind AFC in Nellore cattle should be undertaken.