Stress-induced epigenetic effects driven by maternal lactation in dairy cattle: a comethylation network approach.

Epigenetic marks do not follow the Mendelian laws of inheritance. The environment can alter the epigenotype of an individual when exposed to different external stressors. In lactating cows, the first stages of gestation overlap with the lactation peak, creating a negative energy balance that is difficult to overcome with diet. This negative energy balance could affect early embryo development that must compete with the mammary tissue for nutrients. We hypothesize that the methylation profiles of calves born to nonlactating heifers are different from those of calves born to lactating cows. We found 50,277 differentially methylated cytosines and 2,281 differentially methylated regions between these two groups of animals. A comethylation network was constructed to study the correlation between the phenotypes of the mothers and the epigenome of the calves, revealing 265 regions associated with the phenotypes. Our study revealed the presence of DMCs and DMRs in calves gestated by heifers and lactating cows, which were linked to the dam's lactation and the calves' ICAP and milk EBV. Gene-specific analysis highlighted associations with vasculature and organ morphogenesis and cell communication and signalling. These finding support the hypothesis that calves gestated by nonlactating mothers have a different methylation profile than those gestated by lactating cows.

Chromosome-Scale Genome Assembly of the Sheep-Biting Louse Bovicola ovis Using Nanopore Sequencing Data and Pore-C Analysis.

Bovicola ovis, commonly known as the sheep-biting louse, is an ectoparasite that adversely affects the sheep industry. Sheep louse infestation lowers the quality of products, including wool and leather, causing a loss of approximately AUD 123M per annum in Australia alone. The lack of a high-quality genome assembly for the sheep-biting louse, as well as any closely related livestock lice, has hindered the development of louse research and management control tools. In this study, we present the assembly of B. ovis with a genome size of ~123 Mbp based on a nanopore long-read sequencing library and Illumina RNA sequencing, complemented with a chromosome-level scaffolding using the Pore-C multiway chromatin contact dataset. Combining multiple alignment and gene prediction tools, a comprehensive annotation on the assembled B. ovis genome was conducted and recalled 11,810 genes as well as other genomic features including orf, ssr, rRNA and tRNA. A manual curation using alignment with the available closely related louse species, Pediculus humanus, increased the number of annotated genes to 16,024. Overall, this study reported critical genetic resources and biological insights for the advancement of sheep louse research and the development of sustainable control strategies in the sheep industry.

Genome-wide association and expression quantitative trait loci in cattle reveals common genes regulating mammalian fertility.

Most genetic variants associated with fertility in mammals fall in non-coding regions of the genome and it is unclear how these variants affect fertility. Here we use genome-wide association summary statistics for Heifer puberty (pubertal or not at 600 days) from 27,707 Bos indicus, Bos taurus and crossbred cattle; multi-trait GWAS signals from 2119 indicine cattle for four fertility traits, including days to calving, age at first calving, pregnancy status, and foetus age in weeks (assessed by rectal palpation of the foetus); and expression quantitative trait locus for whole blood from 489 indicine cattle, to identify 87 putatively functional genes affecting cattle fertility. Our analysis reveals a significant overlap between the set of cattle and previously reported human fertility-related genes, impling the existence of a shared pool of genes that regulate fertility in mammals. These findings are crucial for developing approaches to improve fertility in cattle and potentially other mammals.

Boosting the catalytic activity of nanostructured ZnFe2O4 spinels incorporating with Cu2+ for photo-Fenton degradation under visible light.

Methylene blue (MB) is hazardous in natural water because this dye causes serious diseases that endangers public health and ecosystems. Photocatalytic degradation is a prominent technique for achieving the effective elimination of dye pollutants from wastewater and contribute vitally to ecology and environmental safety. Herein, Cu2+-substituted ZnFe2O4 nanomaterials (CuxZn1-xFe2O4; x = 0, 0.1, 0.2, 0.3, 0.4, 0.6) were synthesized, characterized, and applied for the photocatalytic degradation of MB dye beneath visible light with the assistance of hydrogen peroxide (H2O2). The feature of the photo-catalysts was determined by XRD, EDX, FTIR, DRS, BET, SEM, and TEM techniques. Incorporation of Cu2+ ions changed the crystalline phase, particle size, morphology, and surface area. The photocatalysis condition was optimized with the following major factors, the amout of doping Cu2+ ions, H2O2 concentration, adsorbent dosage, and MB concentration. As a result, the photocatalytic MB degradation efficiency by Cu0.6Zn0.4Fe2O4 catalyst was 99.83% within 90 min under LED light (λ ≥ 420 nm), which was around 4 folds higher than that of pure ZnFe2O4. The photo-Fenton kinetics were in accordance with the pseudo-first-order kinetic model (R2 = 0.981), giving the highes rate constant of 0.034 min-1. It can be, therefore, concluded that Cu2+ substitution considerably boosted the photocatalytic activity of CuxZn1-xFe2O4 ZnFe2O4, suggesting a bright prospect of Cu0.6Zn0.4Fe2O4 as a photo-catalyst in the dyes wastewater treatment.

An Approach to Semantic-Aware Heterogeneous Network Embedding for Recommender Systems.

Recent studies on heterogeneous information network (HIN) embedding-based recommendations have encountered challenges. These challenges are related to the data heterogeneity of the associated unstructured attribute or content (e.g., text-based summary/description) of users and items in the context of HIN. In order to address these challenges, in this article, we propose a novel approach of semantic-aware HIN embedding-based recommendation, called SemHE4Rec. In our proposed SemHE4Rec model, we define two embedding techniques for efficiently learning the representations of both users and items in the context of HIN. These rich-structural user and item representations are then used to facilitate the matrix factorization (MF) process. The first embedding technique is a traditional co-occurrence representation learning (CoRL) approach which aims to learn the co-occurrence of structural features of users and items. These structural features are represented for their interconnections in terms of meta-paths. In order to do that, we adopt the well-known meta-path-based random walk strategy and heterogeneous Skip-gram architecture. The second embedding approach is a semantic-aware representation learning (SRL) method. The SRL embedding technique is designed to focus on capturing the unstructured semantic relations between users and item content for the recommendation task. Finally, all the learned representations of users and items are then jointly combined and optimized while integrating with the extended MF for the recommendation task. Extensive experiments on real-world datasets demonstrate the effectiveness of the proposed SemHE4Rec in comparison with the recent state-of-the-art HIN embedding-based recommendation techniques, and reveal that the joint text-based and co-occurrence-based representation learning can help to improve the recommendation performance.

Efficient and recyclable Nd3+-doped CoFe2O4 for boosted visible light-driven photocatalytic degradation of Rhodamine B dye.

Rare earth metal doping spinel ferrites offer excellent electronic, magnetic, and photocatalytic properties, but they have not been well explored for environmental mitigation. Herein, we report the facile fabrication of novel CoNd x Fe2-x O4 (x = 0-0.05) photocatalysts based on Nd3+ incorporated into CoFe2O4 for the degradation of Rhodamine B under visible light irradiation. The Nd3+ dopant considerably increased the specific surface area (35 m2 g-1) and enhanced the degradation performance (94.7%) of CoNd x Fe2-x O4 catalysts. Nd3+-doped CoFe2O4 played a role in the formation of radicals, including ˙OH, h+, and ˙O2 -. With high recyclability and performance, CoNd0.05Fe1.95O4 nanoparticles can be efficient and reusable photocatalysts for degrading organic dyes, including Rhodamine B from wastewaters.

In it for the long run: perspectives on exploiting long-read sequencing in livestock for population scale studies of structural variants.

Studies have demonstrated that structural variants (SV) play a substantial role in the evolution of species and have an impact on Mendelian traits in the genome. However, unlike small variants (< 50 bp), it has been challenging to accurately identify and genotype SV at the population scale using short-read sequencing. Long-read sequencing technologies are becoming competitively priced and can address several of the disadvantages of short-read sequencing for the discovery and genotyping of SV. In livestock species, analysis of SV at the population scale still faces challenges due to the lack of resources, high costs, technological barriers, and computational limitations. In this review, we summarize recent progress in the characterization of SV in the major livestock species, the obstacles that still need to be overcome, as well as the future directions in this growing field. It seems timely that research communities pool resources to build global population-scale long-read sequencing consortiums for the major livestock species for which the application of genomic tools has become cost-effective.

Ce3+/Ce4+-Doped ZrO2/CuO Nanocomposite for Enhanced Photocatalytic Degradation of Methylene Blue under Visible Light.

In recent years, photocatalysis has been used as an environmentally friendly method for the degradation of organic pigments in water. In this study, Ce3+/Ce4+-doped ZrO2/CuO as a mixed semiconductor oxide was successfully prepared by a one-step hydrothermal method. The Ce3+/Ce4+-doped ZrO2/CuO has shown high degradation efficiency of methylene blue (MB), and the maximum degradation percentage was observed to be 94.5% at 180 min under irradiation visible light. The photocatalytic activity increases significantly by doping Ce3+/Ce4+ in ZrO2/CuO for MB degradation. Ce3+/Ce4+ doping is shown to reduce the (e-/h+) recombination rate and improve the charge transfer, leading to enhanced photocatalytic activity of materials. The materials were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), FTIR, EDS, BET and diffuse reflectance spectroscopy (DRS).

Toward enhanced visible-light photocatalytic dye degradation and reusability of La3+ substituted ZnFe2O4 nanostructures.

The present work focused on the synthesis of novel ZnLaxFe2-xO4 catalysts (x = 0, 0.01, 0.03, 0.05) and their utilization for the photocatalytic degradation of Rhodamine B dye. Structurally, the band gap energy of the catalysts tended to decrease (1.94-1.70 eV) with increasing the amount of La3+ dopant. ZnLa0.05Fe1.95O4 had an average particle size (40 nm), high surface area (41.07 m2 g-1) and large pore volume (0.186 cm3 g-1). Moreover, the effect of doping ratio, reaction time, H2O2 concentration, catalyst loading on the treatment performance of La3+ substituted ZnFe2O4 nanocomposites was investigated. ZnLa0.05Fe1.95O4/H2O2 system exhibited the highest degradation efficiency of 99.5% and nonlinear pseudo first-order kinetic reaction rate (14.8 × 10-3 min-1) in the presence of visible light irradiation. The key role of reactive oxygen species involving •O2- and •OH radicals was well explained through the scavenger study. A plausible mechanism of the degradation of Rhodamine B dye was also proposed. Due to two advantageous points including high recyclability (up to 4 cycles) and stability, La3+ substituted ZnFe2O4 nanocomposites can be an effective and competitive catalyst for the visible light-driven photodegradation of toxic dyes in the real wastewaters.

Extensive Variation in Gene Expression is Revealed in 13 Fertility-Related Genes Using RNA-Seq, ISO-Seq, and CAGE-Seq From Brahman Cattle.

Fertility is a key driver of economic profitability in cattle production. A number of studies have identified genes associated with fertility using genome wide association studies and differential gene expression analysis; however, the genes themselves are poorly characterized in cattle. Here, we selected 13 genes from the literature which have previously been shown to have strong evidence for an association with fertility in Brahman cattle (Bos taurus indicus) or closely related breeds. We examine the expression variation of the 13 genes that are associated with cattle fertility using RNA-seq, CAGE-seq, and ISO-seq data from 11 different tissue samples from an adult Brahman cow and a Brahman fetus. Tissues examined include blood, liver, lung, kidney, muscle, spleen, ovary, and uterus from the cow and liver and lung from the fetus. The analysis revealed several novel isoforms, including seven from SERPINA7. The use of three expression characterization methodologies (5' cap selected ISO-seq, CAGE-seq, and RNA-seq) allowed the identification of isoforms that varied in their length of 5' and 3' untranslated regions, variation otherwise undetectable (collapsed as degraded RNA) in generic isoform identification pipelines. The combinations of different sequencing technologies allowed us to overcome the limitations of relatively low sequence depth in the ISO-seq data. The lower sequence depth of the ISO-seq data was also reflected in the lack of observed expression of some genes that were observed in the CAGE-seq and RNA-seq data from the same tissue. We identified allele specific expression that was tissue-specific in AR, IGF1, SOX9, STAT3, and TAF9B. Finally, we characterized an exon of TAF9B as partially nested within the neighboring gene phosphoglycerate kinase 1. As this study only examined two animals, even more transcriptional variation may be present in a genetically diverse population. This analysis reveals the large amount of transcriptional variation within mammalian fertility genes and illuminates the fact that the transcriptional landscape cannot be fully characterized using a single technology alone.

Growth and Biochemical Responses of Green and Red Perilla Supplementally Subjected to UV-A and Deep-blue LED Lights.

This study investigated the effects of UV-A and UV-A-closed visible light (deep-blue [DB]) on the growth and bioactive compound accumulation of green and red perilla. Four-week-old seedlings were cultivated in an environment control room under visible light with red, blue and white LEDs for 4 weeks and then were continuously grown under supplemental UV-A (365 nm and 385 nm) and DB (415 nm and 430 nm) lights for 7 days. UV-A and DB treatments did not enhance the growth characteristics of green perilla compared with the control; while these treatments enhanced the growth parameters of red perilla, and the values were highest in DB 415 nm. The photosynthesis rate of both cultivars showed similar trends as the growth results of each cultivar. The electron transport rate and maximum quantum yield of both cultivars were reduced under UV-A 365 nm, while these values were maintained in DB treatments. In both cultivars, total phenolic, antioxidant capacity, rosmarinic and caffeic acids and perillaldehyde levels were enhanced in DB treatments, whereas UV-A 365 nm and DB 415 nm increased the total anthocyanin content. Overall, supplemental DB 415 nm and 430 nm was suitable for improving the growth and biochemical accumulation of both perilla cultivars.

An Epigenetic Aging Clock for Cattle Using Portable Sequencing Technology.

Extensively grazed cattle are often mustered only once a year. Therefore, birthdates are typically unknown or inaccurate. Birthdates would be useful for deriving important traits (growth rate; calving interval), breed registrations, and making management decisions. Epigenetic clocks use methylation of DNA to predict an individual's age. An epigenetic clock for cattle could provide a solution to the challenges of industry birthdate recording. Here we derived the first epigenetic clock for tropically adapted cattle using portable sequencing devices from tail hair, a tissue which is widely used in industry for genotyping. Cattle (n = 66) with ages ranging from 0.35 to 15.7 years were sequenced using Oxford Nanopore Technologies MinION and methylation was called at CpG sites across the genome. Sites were then filtered and used to calculate a covariance relationship matrix based on methylation state. Best linear unbiased prediction was used with 10-fold cross validation to predict age. A second methylation relationship matrix was also calculated that contained sites associated with genes used in the dog and human epigenetic clocks. The correlation between predicted age and actual age was 0.71 for all sites and 0.60 for dog and human gene epigenetic clock sites. The mean absolute deviation was 1.4 years for animals aged less than 3 years of age, and 1.5 years for animals aged 3-10 years. This is the first reported epigenetic clock using industry relevant samples in cattle.

Genomic prediction using low-coverage portable Nanopore sequencing.

Most traits in livestock, crops and humans are polygenic, that is, a large number of loci contribute to genetic variation. Effects at these loci lie along a continuum ranging from common low-effect to rare high-effect variants that cumulatively contribute to the overall phenotype. Statistical methods to calculate the effect of these loci have been developed and can be used to predict phenotypes in new individuals. In agriculture, these methods are used to select superior individuals using genomic breeding values; in humans these methods are used to quantitatively measure an individual's disease risk, termed polygenic risk scores. Both fields typically use SNP array genotypes for the analysis. Recently, genotyping-by-sequencing has become popular, due to lower cost and greater genome coverage (including structural variants). Oxford Nanopore Technologies' (ONT) portable sequencers have the potential to combine the benefits genotyping-by-sequencing with portability and decreased turn-around time. This introduces the potential for in-house clinical genetic disease risk screening in humans or calculating genomic breeding values on-farm in agriculture. Here we demonstrate the potential of the later by calculating genomic breeding values for four traits in cattle using low-coverage ONT sequence data and comparing these breeding values to breeding values calculated from SNP arrays. At sequencing coverages between 2X and 4X the correlation between ONT breeding values and SNP array-based breeding values was > 0.92 when imputation was used and > 0.88 when no imputation was used. With an average sequencing coverage of 0.5x the correlation between the two methods was between 0.85 and 0.92 using imputation, depending on the trait. This suggests that ONT sequencing has potential for in clinic or on-farm genomic prediction, however, further work to validate these findings in a larger population still remains.

Chromatin accessibility and regulatory vocabulary across indicine cattle tissues.

BACKGROUND: Spatiotemporal 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. RESULTS: We 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. CONCLUSIONS: Our 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.

Prowler: a novel trimming algorithm for Oxford Nanopore sequence data.

MOTIVATION: Trimming and filtering tools are useful in DNA sequencing analysis because they increase the accuracy of sequence alignments and thus the reliability of results. Oxford nanopore technologies (ONT) trimming and filtering tools are currently rudimentary, generally only filtering reads based on whole read average quality. This results in discarding reads that contain regions of high-quality sequence. Here, we propose Prowler, a trimmer that uses a window-based approach inspired by algorithms used to trim short read data. Importantly, we retain the phase and read length information by optionally replacing trimmed sections with Ns. RESULTS: Prowler was applied to mammalian and bacterial datasets, to assess its effect on alignment and assembly, respectively. Compared to data filtered with Nanofilt, alignments of data trimmed with Prowler had lower error rates and more mapped reads. Assemblies of Prowler trimmed data had a lower error rate than those filtered with Nanofilt; however, this came at some cost to assembly contiguity. AVAILABILITY AND IMPLEMENTATION: Prowler is implemented in Python and is available at https://github.com/ProwlerForNanopore/ProwlerTrimmer. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Enhanced Photocatalytic Activity of Spherical Nd3+ Substituted ZnFe2O4 Nanoparticles.

In this study, nanocrystalline ZnNdxFe2-xO4 ferrites with x = 0.0, 0.01, 0.03 and 0.05 were fabricated and used as a catalyst for dye removal potential. The effect of Nd3+ ions substitution on the structural, optical and photo-Fenton activity of ZnNdxFe2-xO4 has been investigated. The addition of Nd3+ ions caused a decrease in the grain size of ferrites, the reduction of the optical bandgap energies and thus could be well exploited for the catalytic study. The photocatalytic activity of the ferrite samples was evaluated by the degradation of Rhodamine B (RhB) in the presence of H2O2 under visible light radiation. The results indicated that the ZnNdxFe2-xO4 samples exhibited higher removal efficiencies than the pure ZnFe2O4 ferrites. The highest degradation efficiency was 98.00%, attained after 210 min using the ZnNd0.03Fe1.97O4 sample. The enhanced photocatalytic activity of the ZnFe2O4 doped with Nd3+ is explained due to the efficient separation mechanism of photoinduced electron and holes. The effect of various factors (H2O2 oxidant concentration and catalyst loading) on the degradation of RhB dye was clarified.

Improved genomic prediction of clonal performance in sugarcane by exploiting non-additive genetic effects.

KEY MESSAGE: Non-additive genetic effects seem to play a substantial role in the expression of complex traits in sugarcane. Including non-additive effects in genomic prediction models significantly improves the prediction accuracy of clonal performance. In the recent decade, genetic progress has been slow in sugarcane. One reason might be that non-additive genetic effects contribute substantially to complex traits. Dense marker information provides the opportunity to exploit non-additive effects in genomic prediction. In this study, a series of genomic best linear unbiased prediction (GBLUP) models that account for additive and non-additive effects were assessed to improve the accuracy of clonal prediction. The reproducible kernel Hilbert space model, which captures non-additive genetic effects, was also tested. The models were compared using 3,006 genotyped elite clones measured for cane per hectare (TCH), commercial cane sugar (CCS), and Fibre content. Three forward prediction scenarios were considered to investigate the robustness of genomic prediction. By using a pseudo-diploid parameterization, we found significant non-additive effects that accounted for almost two-thirds of the total genetic variance for TCH. Average heterozygosity also had a major impact on TCH, indicating that directional dominance may be an important source of phenotypic variation for this trait. The extended-GBLUP model improved the prediction accuracies by at least 17% for TCH, but no improvement was observed for CCS and Fibre. Our results imply that non-additive genetic variance is important for complex traits in sugarcane, although further work is required to better understand the variance component partitioning in a highly polyploid context. Genomics-based breeding will likely benefit from exploiting non-additive genetic effects, especially in designing crossing schemes. These findings can help to improve clonal prediction, enabling a more accurate identification of variety candidates for the sugarcane industry.

The Future of Livestock Management: A Review of Real-Time Portable Sequencing Applied to Livestock.

Oxford Nanopore Technologies' MinION has proven to be a valuable tool within human and microbial genetics. Its capacity to produce long reads in real time has opened up unique applications for portable sequencing. Examples include tracking the recent African swine fever outbreak in China and providing a diagnostic tool for disease in the cassava plant in Eastern Africa. Here we review the current applications of Oxford Nanopore sequencing in livestock, then focus on proposed applications in livestock agriculture for rapid diagnostics, base modification detection, reference genome assembly and genomic prediction. In particular, we propose a future application: 'crush-side genotyping' for real-time on-farm genotyping for extensive industries such as northern Australian beef production. An initial in silico experiment to assess the feasibility of crush-side genotyping demonstrated promising results. SNPs were called from simulated Nanopore data, that included the relatively high base call error rate that is characteristic of the data, and calling parameters were varied to understand the feasibility of SNP calling at low coverages in a heterozygous population. With optimised genotype calling parameters, over 85% of the 10,000 simulated SNPs were able to be correctly called with coverages as low as 6×. These results provide preliminary evidence that Oxford Nanopore sequencing has potential to be used for real-time SNP genotyping in extensive livestock operations.

Genome-Wide Co-Expression Distributions as a Metric to Prioritize Genes of Functional Importance.

Genome-wide gene expression analysis are routinely used to gain a systems-level understanding of complex processes, including network 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 developed a computational pipeline to assign to every gene its pair-wise genome-wide co-expression distribution to one of 8 template distributions shapes varying between unimodal, bimodal, skewed, or symmetrical, representing different proportions of positive and negative correlations. We then used a hypergeometric test to determine if specific genes (regulators versus non-regulators) and properties (differentially expressed or not) are associated with a particular distribution shape. We applied our methodology to five publicly available RNA sequencing (RNA-seq) datasets from four organisms in different physiological conditions and tissues. Our results suggest that genes can be assigned consistently to pre-defined distribution shapes, regarding the enrichment of differential expression and regulatory genes, in situations involving contrasting phenotypes, time-series, or physiological baseline data. There is indeed a striking additional biological signal present in the genome-wide distribution of co-expression values which would be overlooked by currently adopted approaches. Our method can be applied to extract further information from transcriptomic data and help uncover the molecular mechanisms involved in the regulation of complex biological process and phenotypes.