Transformation of animal genomics by next-generation sequencing technologies: a decade of challenges and their impact on genetic architecture

Nanomaterials-assisted gene editing and synthetic biology for optimizing the treatment of pulmonary diseases

The use of nanomaterials in gene editing and synthetic biology has emerged as a pivotal strategy in the pursuit of refined treatment methodologies for pulmonary disorders. This review discusses the utilization of nanomaterial-assisted gene editing tools and synthetic biology techniques to promote the development of more precise and efficient treatments for pulmonary diseases. First, we briefly outline the characterization of the respiratory system and succinctly describe the principal applications of diverse nanomaterials in lung ailment treatment. Second, we elaborate on gene-editing tools, their configurations, and assorted delivery methods, while delving into the present state of nanomaterial-facilitated gene-editing interventions for a spectrum of pulmonary diseases. Subsequently, we briefly expound on synthetic biology and its deployment in biomedicine, focusing on research advances in the diagnosis and treatment of pulmonary conditions against the backdrop of the coronavirus disease 2019 pandemic. Finally, we summarize the extant lacunae in current research and delineate prospects for advancement in this domain. This holistic approach augments the development of pioneering solutions in lung disease treatment, thereby endowing patients with more efficacious and personalized therapeutic alternatives.

Genome-wide association study identifies genetic variants underlying footrot in Portuguese Merino sheep

BACKGROUND

Ovine footrot caused by Dichelobacter nodosus (D. nodosus) is a contagious disease with serious economic and welfare impacts in sheep production systems worldwide. A better understanding of the host genetic architecture regarding footrot resistance/susceptibility is crucial to develop disease control strategies that efficiently reduce infection and its severity. A genome-wide association study was performed using a customized SNP array (47,779 SNPs in total) to identify genetic variants associated to footrot resistance/susceptibility in two Portuguese native breeds, i.e. Merino Branco and Merino Preto, and a population of crossbred animals. A cohort of 1375 sheep sampled across 17 flocks, located in the Alentejo region (southern Portugal), was included in the analyses.

RESULTS

Phenotypes were scored from 0 (healthy) to 5 (severe footrot) based on visual inspection of feet lesions, following the Modified Egerton System. Using a linear mixed model approach, three SNPs located on chromosome 24 reached genome-wide significance after a Bonferroni correction (p < 0.05). Additionally, six genome-wide suggestive SNPs were identified each on chromosomes 2, 4, 7, 8, 9 and 15. The annotation and KEGG pathway analyses showed that these SNPs are located within regions of candidate genes such as the nonsense mediated mRNA decay associated PI3K related kinase (SMG1) (chromosome 24) and the RALY RNA binding protein like (RALYL) (chromosome 9), both involved in immunity, and the heparan sulfate proteoglycan 2 (HSPG2) (chromosome 2) and the Thrombospodin 1 (THBS1) (chromosome 7) implicated in tissue repair and wound healing processes.

CONCLUSION

This is the first attempt to identify molecular markers associated with footrot in Portuguese Merino sheep. These findings provide relevant information on a likely genetic association underlying footrot resistance/susceptibility and the potential candidate genes affecting this trait. Genetic selection strategies assisted on the information obtained from this study could enhance Merino sheep-breeding programs, in combination with farm management strategies, for a more effective and sustainable long-term solution for footrot control.

A comprehensive framework for detecting copy number variants from single nucleotide polymorphism data: 'rCNV', a versatile r package for paralogue and CNV detection

Recent studies have highlighted the significant role of copy number variants (CNVs) in phenotypic diversity, environmental adaptation and species divergence across eukaryotes. The presence of CNVs also has the potential to introduce genotyping biases, which can pose challenges to accurate population and quantitative genetic analyses. However, detecting CNVs in genomes, particularly in non-model organisms, presents a formidable challenge. To address this issue, we have developed a statistical framework and an accompanying r software package that leverage allelic-read depth from single nucleotide polymorphism (SNP) data for accurate CNV detection. Our framework capitalises on two key principles. First, it exploits the distribution of allelic-read depth ratios in heterozygotes for individual SNPs by comparing it against an expected distribution based on binomial sampling. Second, it identifies SNPs exhibiting an apparent excess of heterozygotes under Hardy-Weinberg equilibrium. By employing multiple statistical tests, our method not only enhances sensitivity to sampling effects but also effectively addresses reference biases, resulting in optimised SNP classification. Our framework is compatible with various NGS technologies (e.g. RADseq, Exome-capture). This versatility enables CNV calling from genomes of diverse complexities. To streamline the analysis process, we have implemented our framework in the user-friendly r package 'rCNV', which automates the entire workflow seamlessly. We trained our models using simulated data and validated their performance on four datasets derived from different sequencing technologies, including RADseq (Chinook salmon-Oncorhynchus tshawytscha), Rapture (American lobster-Homarus americanus), Exome-capture (Norway spruce-Picea abies) and WGS (Malaria mosquito-Anopheles gambiae).

Mapinsights: deep exploration of quality issues and error profiles in high-throughput sequence data

High-throughput sequencing (HTS) has revolutionized science by enabling super-fast detection of genomic variants at base-pair resolution. Consequently, it poses the challenging problem of identification of technical artifacts, i.e. hidden non-random error patterns. Understanding the properties of sequencing artifacts holds the key in separating true variants from false positives. Here, we develop Mapinsights, a toolkit that performs quality control (QC) analysis of sequence alignment files, capable of detecting outliers based on sequencing artifacts of HTS data at a deeper resolution compared with existing methods. Mapinsights performs a cluster analysis based on novel and existing QC features derived from the sequence alignment for outlier detection. We applied Mapinsights on community standard open-source datasets and identified various quality issues including technical errors related to sequencing cycles, sequencing chemistry, sequencing libraries and across various orthogonal sequencing platforms. Mapinsights also enables identification of anomalies related to sequencing depth. A logistic regression-based model built on the features of Mapinsights shows high accuracy in detecting 'low-confidence' variant sites. Quantitative estimates and probabilistic arguments provided by Mapinsights can be utilized in identifying errors, bias and outlier samples, and also aid in improving the authenticity of variant calls.

An In Silico Functional Analysis of Non-Synonymous Single-Nucleotide Polymorphisms of Bovine CMAH Gene and Potential Implication in Pathogenesis

The sugar molecule N-glycolylneuraminic acid (Neu5Gc) is one of the most common sialic acids discovered in mammals. Cytidine monophospho-N-acetylneuraminic acid hydroxylase (CMAH) catalyses the conversion of N-acetylneuraminic acid (Neu5Ac) to Neu5Gc, and it is encoded by the CMAH gene. On the one hand, food metabolic incorporation of Neu5Gc has been linked to specific human diseases. On the other hand, Neu5Gc has been shown to be highly preferred by some pathogens linked to certain bovine diseases. We used various computational techniques to perform an in silico functional analysis of five non-synonymous single-nucleotide polymorphisms (nsSNPs) of the bovine CMAH (bCMAH) gene identified from the 1000 Bull Genomes sequence data. The c.1271C>T (P424L) nsSNP was predicted to be pathogenic based on the consensus result from different computational tools. The nsSNP was also predicted to be critical based on sequence conservation, stability, and post-translational modification site analysis. According to the molecular dynamic simulation and stability analysis, all variations promoted stability of the bCMAH protein, but mutation A210S significantly promoted CMAH stability. In conclusion, c.1271C>T (P424L) is expected to be the most harmful nsSNP among the five detected nsSNPs based on the overall studies. This research could pave the way for more research associating pathogenic nsSNPs in the bCMAH gene with diseases.

Genome-wide assessment of the population structure and genetic diversity of four Portuguese native sheep breeds

As the effects of global warming become increasingly complex and difficult to manage, the conservation and sustainable use of locally adapted sheep breeds are gaining ground. Portuguese native sheep breeds are important reservoirs of genetic diversity, highly adapted to harsh environments and reared in low input production systems. Genomic data that would describe the breeds in detail and accelerate the selection of more resilient animals to be able to cope with climatic challenges are still lacking. Here, we sequenced the genomes of 37 animals from four Portuguese native sheep breeds (Campaniça, Bordaleira Serra da Estrela, Merino Branco and Merino Preto) and 19 crossbred sheep to make inferences on their genomic diversity and population structure. Mean genomic diversities were very similar across these breeds (.30 ≤ H_o ≤ .34; .30 ≤ H_e ≤ .35; 1.7 × 10^-3 ≤ π ≤ 3.1 × 10^-3) and the levels of inbreeding were negligible (.005 ≤ F_IS ≤ .038). The Principal Components, Bayesian clustering and Treemix analyses split the Portuguese breeds in two main groups which are consistent with historical records: one comprising Campaniça and Serra da Estrela together with other European and transboundary dairy breeds; and another of the well-differentiated multi-purpose Merino and Merino-related breeds. Runs of homozygosity analyses yielded 1,690 ROH segments covering an average of 2.27 Gb across the genome in all individuals. The overall genome covered by ROH segments varied from 27,75 Mb in Serra da Estrela to 61,29 Mb in Campaniça. The phylogenetic analysis of sheep mitogenomes grouped the Portuguese native breeds within sub-haplogroup B1a along with two animals of the Akkaraman breed from Turkey. This result provides additional support to a direct influence of Southwest Asian sheep in local breeds from the Iberian Peninsula. Our study is a first step pertaining to the genomic characterization of Portuguese sheep breeds and the results emphasize the potential of genomic data as a valid tool to guide conservation efforts in locally adapted sheep breeds. In addition, the genomic data we generated can be used to identify markers for breed assignment and traceability of certified breed-products.

Unlocking Horse Y Chromosome Diversity

The present equine genetic variation mirrors the deep influence of intensive breeding programs during the last 200 years. Here, we provide a comprehensive current state of knowledge on the trends and prospects on the variation in the equine male-specific region of the Y chromosome (MSY), which was assembled for the first time in 2018. In comparison with the other 12 mammalian species, horses are now the most represented, with 56 documented MSY genes. However, in contrast to the high variability in mitochondrial DNA observed in many horse breeds from different geographic areas, modern horse populations demonstrate extremely low genetic Y-chromosome diversity. The selective pressures employed by breeders using pedigree data (which are not always error-free) as a predictive tool represent the main cause of this lack of variation in the Y-chromosome. Nevertheless, the detailed phylogenies obtained by recent fine-scaled Y-chromosomal genotyping in many horse breeds worldwide have contributed to addressing the genealogical, forensic, and population questions leading to the reappraisal of the Y-chromosome as a powerful genetic marker to avoid the loss of biodiversity as a result of selective breeding practices, and to better understand the historical development of horse breeds.

The Innovative Informatics Approaches of High-Throughput Technologies in Livestock: Spearheading the Sustainability and Resiliency of Agrigenomics Research

For more than a decade, next-generation sequencing (NGS) has been emerging as the mainstay of agrigenomics research. High-throughput technologies have made it feasible to facilitate research at the scale and cost required for using this data in livestock research. Scale frameworks of sequencing for agricultural and livestock improvement, management, and conservation are partly attributable to innovative informatics methodologies and advancements in sequencing practices. Genome-wide sequence-based investigations are often conducted worldwide, and several databases have been created to discover the connections between worldwide scientific accomplishments. Such studies are beginning to provide revolutionary insights into a new era of genomic prediction and selection capabilities of various domesticated livestock species. In this concise review, we provide selected examples of the current state of sequencing methods, many of which are already being used in animal genomic studies, and summarize the state of the positive attributes of genome-based research for cattle (Bos taurus), sheep (Ovis aries), pigs (Sus scrofa domesticus), horses (Equus caballus), chickens (Gallus gallus domesticus), and ducks (Anas platyrhyncos). This review also emphasizes the advantageous features of sequencing technologies in monitoring and detecting infectious zoonotic diseases. In the coming years, the continued advancement of sequencing technologies in livestock agrigenomics will significantly influence the sustained momentum toward regulatory approaches that encourage innovation to ensure continued access to a safe, abundant, and affordable food supplies for future generations.

Identification of the Differentially Expressed Genes in the leg muscles of Zhedong White Geese (Anser cygnoides) reared under different photoperiods

Light is a factor affecting muscle development and meat quality in poultry production. However, few studies have reported on the role of light in muscle development and meat quality in geese. In this experiment, 10 healthy 220-day-old Zhedong white geese were reared for 60 d under a long photoperiod (15L:9D, LL) and short photoperiod (9L:15D, SL). The gastrocnemius muscles were collected after slaughter to evaluate muscle fiber characteristics and meat color, and RNA-seq analysis. The results showed that compared to the LL group, the SL group had large muscle fiber diameter and cross-sectional area, few muscle fibers per unit area, high meat color a* value, and low L* value at 24 h postmortem. On comparing the 2 groups, 70 differentially expressed genes (DEGs) were identified. Compared to the SL group, the LL group had 25 upregulated and 45 downregulated genes. Gene Ontology (GO) enrichment analysis showed that these DEGs were mainly involved in cell, cell part, binding, cellular processes, and single-organism processes. Several significantly enriched athways were identified in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, such as the calcium and PI3k-Akt signaling pathways. The expression of five randomly selected DEGs was verified using quantitative real-time PCR, and the results were consistent with the RNA-seq data. This study provides a theoretical basis for studying the molecular mechanisms by which light affects muscle development and meat color in geese.

Sparse System Identification of Leptin Dynamics in Women With Obesity

The prevalence of obesity is increasing around the world at an alarming rate. The interplay of the hormone leptin with the hypothalamus-pituitary-adrenal axis plays an important role in regulating energy balance, thereby contributing to obesity. This study presents a mathematical model, which describes hormonal behavior leading to an energy abnormal equilibrium that contributes to obesity. To this end, we analyze the behavior of two neuroendocrine hormones, leptin and cortisol, in a cohort of women with obesity, with simplified minimal state-space modeling. Using a system theoretic approach, coordinate descent method, and sparse recovery, we deconvolved the serum leptin-cortisol levels. Accordingly, we estimate the secretion patterns, timings, amplitudes, number of underlying pulses, infusion, and clearance rates of hormones in eighteen premenopausal women with obesity. Our results show that minimal state-space model was able to successfully capture the leptin and cortisol sparse dynamics with the multiple correlation coefficients greater than 0.83 and 0.87, respectively. Furthermore, the Granger causality test demonstrated a negative prospective predictive relationship between leptin and cortisol, 14 of 18 women. These results indicate that increases in cortisol are prospectively associated with reductions in leptin and vice versa, suggesting a bidirectional negative inhibitory relationship. As dysregulation of leptin may result in an abnormality in satiety and thereby associated to obesity, the investigation of leptin-cortisol sparse dynamics may offer a better diagnostic methodology to improve better treatments plans for individuals with obesity.

Successful ATAC-Seq From Snap-Frozen Equine Tissues

An assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) has become an increasingly popular method to assess genome-wide chromatin accessibility in isolated nuclei from fresh tissues. However, many biobanks contain only snap-frozen tissue samples. While ATAC-seq has been applied to frozen brain tissues in human, its applicability in a wide variety of tissues in horse remains unclear. The Functional Annotation of Animal Genome (FAANG) project is an international collaboration aimed to provide high quality functional annotation of animal genomes. The equine FAANG initiative has generated a biobank of over 80 tissues from two reference female animals and experiments to begin to characterize tissue specificity of genome function for prioritized tissues have been performed. Due to the logistics of tissue collection and storage, extracting nuclei from a large number of tissues for ATAC-seq at the time of collection is not always practical. To assess the feasibility of using stored frozen tissues for ATAC-seq and to provide a guideline for the equine FAANG project, we compared ATAC-seq results from nuclei isolated from frozen tissue to cryopreserved nuclei (CN) isolated at the time of tissue harvest in liver, a highly cellular homogenous tissue, and lamina, a relatively acellular tissue unique to the horse. We identified 20,000-33,000 accessible chromatin regions in lamina and 22-61,000 in liver, with consistently more peaks identified using CN isolated at time of tissue collection. Our results suggest that frozen tissues are an acceptable substitute when CN are not available. For more challenging tissues such as lamina, nuclei extraction at the time of tissue collection is still preferred for optimal results. Therefore, tissue type and accessibility to intact nuclei should be considered when designing ATAC-seq experiments.

Validation of oral brushing as a non-invasive technique for the identification of feline oral squamous cell carcinoma by DNA methylation and TP53 mutation analysis

Feline oral squamous cell carcinoma (FOSCC) is a frequent and progressively invasive tumour. Early lesions are difficult to recognize based on the sole clinical examination and may be misinterpreted as non-neoplastic. Mutations of TP53 and epigenetic alterations of specific genes are present in FOSCC and may be early detected. Aim of this prospective study was to investigate the DNA methylation pattern of a 17-gene panel and TP53 mutational status of FOSCC cytological samples obtained by oral brushing. Results were compared with a control group, in order to validate this non-invasive procedure for the screening of FOSCC. In FOSCC, the same analyses were carried out on the corresponding histological sample, if available. Thirty-five FOSCC and 60 controls were included. Mutations of TP53 were detected in 17 FOSCC brushings (48%) and in none of the controls (P < .001). Six genes (ZAP70, FLI1, MiR124-1, KIF1A, MAGEC2 and MiR363) were differentially methylated in FOSCC and were included in a methylation score. An algorithm based on TP53 mutational status and methylation score allowed to differentiate FOSCC from controls with a 69% sensitivity and a 97% specificity (accuracy, 86%). In 19 FOSCC histological samples, TP53 mutational status was fully concordant with brushings and a positive methylation score was observed in all cases. These results are promising for the identification of FOSCC by oral brushing, although some factors may limit the accuracy of this technique and further studies are required to assess its reproducibility in clinical practice.

Computational methods and next-generation sequencing approaches to analyze epigenetics data: Profiling of methods and applications

Epigenetics is mainly comprised of features that regulate genomic interactions thereby playing a crucial role in a vast array of biological processes. Epigenetic mechanisms such as DNA methylation and histone modifications influence gene expression by modulating the packaging of DNA in the nucleus. A plethora of studies have emphasized the importance of analyzing epigenetics data through genome-wide studies and high-throughput approaches, thereby providing key insights towards epigenetics-based diseases such as cancer. Recent advancements have been made towards translating epigenetics research into a high throughput approach such as genome-scale profiling. Amongst all, bioinformatics plays a pivotal role in achieving epigenetics-related computational studies. Despite significant advancements towards epigenomic profiling, it is challenging to understand how various epigenetic modifications such as chromatin modifications and DNA methylation regulate gene expression. Next-generation sequencing (NGS) provides accurate and parallel sequencing thereby allowing researchers to comprehend epigenomic profiling. In this review, we summarize different computational methods such as machine learning and other bioinformatics tools, publicly available databases and resources to identify key modifications associated with epigenetic machinery. Additionally, the review also focuses on understanding recent methodologies related to epigenome profiling using NGS methods ranging from library preparation, different sequencing platforms and analytical techniques to evaluate various epigenetic modifications such as DNA methylation and histone modifications. We also provide detailed information on bioinformatics tools and computational strategies responsible for analyzing large scale data in epigenetics.

Full Transcriptome Analysis of Callus Suspension Culture System of Bletilla striata

Background

Bletilla striata has been widely used in the pharmacology industry. To effectively produce the secondary metabolites through suspension cultured cells of B. striata, it is important to exploring the full-length transcriptome data and the genes related to cell growth and chemical producing of all culture stages. We applied a combination of Real-Time Sequencing of Single Molecule (SMRT) and second-generation sequencing (SGS) to generate the complete and full-length transcriptome of B. striata suspension cultured cells.

Methods

The B. striata transcriptome was formed in de novo way by using PacBio isoform sequencing (Iso-Seq) on a pooled RNA sample derived from 23 samples of 10 culture stages, to explore the potential for capturing full-length transcript isoforms. All unigenes were obtained after splicing, assembling, and clustering, and corrected by the SGS results. The obtained unigenes were compared with the databases, and the functions were annotated and classified.

Results and conclusions

A total of 100,276 high-quality full-length transcripts were obtained, with an average length of 2530 bp and an N50 of 3302 bp. About 52% of total sequences were annotated against the Gene Ontology, 53,316 unigenes were hit by KOG annotations and divided into 26 functional categories, 80,020 unigenes were mapped by KEGG annotations and clustered into 363 pathways. Furthermore, 15,133 long-chain non-coding RNAs (lncRNAs) were detected. And 68,996 coding sequences were identified based on SSR analysis, among which 31 pairs of primers selected at random were amplified and obtained stable bands. In conclusion, our results provide new full-length transcriptome data and genetic resources for identifying growth and metabolism-related genes, which provide a solid foundation for further research on its growth regulation mechanisms and genetic engineering breeding mechanisms of B. striata.

Fusarium infection alters the m6A-modified transcript landscape in the cornea

N6-methyladenosine (m⁶A) is the most common post-transcriptional modification of RNA in eukaryotes that regulates the post-transcriptional expression level of genes without changing the base sequence. The role of m⁶A in fungal keratitis has not yet been elucidated. Here, we aimed to identify m⁶A modification changes and their potential roles in fungal keratitis. The murine model of fungal keratitis was established by inoculating mice with Fusarium solani (F. solani). The overall m⁶A level was detected via an m⁶A RNA methylation assay kit. The expression levels of key m⁶A modification-related genes were estimated by quantitative real-time polymerase chain reaction (PCR). The expression and localization of METTL (methyltransferase like)3, the key component of the m⁶A methyltransferase complex, was determined by immunostaining and Western blotting (WB). Immunoprecipitation methylation microarray was used to describe the changes in m⁶A modification in F. solani-infected corneal tissue. The overall m⁶A level in corneal tissue on the 5th day in the F. solani-treated group was upregulated compared with that in the control group. The demethylase levels were unaltered, but the level of the methylase METTL3 was increased significantly after fungal infection. Additionally, differences were found in m⁶A modifications in 1137 mRNAs, of which 780 were hypermethylated and 357 were hypomethylated. To the best of our knowledge, the present work is the first investigation on the m⁶A modification profiles in experimental fungal keratitis, and it may provide a potential therapeutic target.

A Comprehensive Investigation of Potential Novel Marine Psychrotolerant Actinomycetes sp. Isolated from the Bay-of-Bengal

BACKGROUND

This study was carried out to classify the diversity of the deep marine psychrotolerant actinomycetes sp. nov., in the Bay of Bengal and exploit the production of cold-active industrial and pharmaceutical biomolecules.

OBJECTIVE

1) Characterization, optimum the growth conditions and classify the diversity of the novel isolated deep marine psychrotolerant actinomycetes sp from the Bay-of-Bengal. 2) Screening for industrially important biocatalysts and determine the antimicrobial activities against the five dreadful pathogens. 3) The differential expression profiling of the candidate genes to regulate the biosynthesis of selected enzymes.

METHODS

The cold-adapted actinomycetes were isolated from the deep marine water collections at 1200 mts below the surface in Bay-of-Bengal. The phenotypic and genotypic characterizations have been carried out to understand the persistent diversity of this novel marine psychrotolerant actinomycetes species. The production of cold-active enzymes, such as amylase, cellulase, lipase, pectinase, and L-asparaginase, were screened and the expression profiling genes were determined by using qRT PCR. The antibacterial and antifungal activities have also been investigated.

RESULTS

A total number of 37 novel actinomycetes were isolated and the phenotypic and genotypic characterizations identified the genus, dominated by Streptomyces (17 distinct sub-groups) as the major group, followed by Micromonospora, Actinopolyspora, Actinosynnema, Streptoverticillium, Saccharopolyspora, Nocardiopsis, and Nocardia. The optimum growth and abundant mycelium formation are observed at 15°C to 20°C and also capability for thriving at 4°C. All the isolates exhibited a significant role in the production of biocatalysts, and the antagonistic activities were also noted against five major selected pathogens.

CONCLUSION

The Streptomyces from the Bay-of-Bengal have high biosynthetic potential and can serve as a good resource for the exploration of bioactive natural products.

Identification of Differentially Expressed Genes in Different Types of Broiler Skeletal Muscle Fibers Using the RNA-seq Technique

The difference in muscle fiber types is very important to the muscle development and meat quality of broilers. At present, the molecular regulation mechanisms of skeletal muscle fiber-type transformation in broilers are still unclear. In this study, differentially expressed genes between breast and leg muscles in broilers were analyzed using RNA-seq. A total of 767 DEGs were identified. Compared with leg muscle, there were 429 upregulated genes and 338 downregulated genes in breast muscle. Gene Ontology (GO) enrichment indicated that these DEGs were mainly involved in cellular processes, single organism processes, cells, and cellular components, as well as binding and catalytic activity. KEGG analysis shows that a total of 230 DEGs were mapped to 126 KEGG pathways and significantly enriched in the four pathways of glycolysis/gluconeogenesis, starch and sucrose metabolism, insulin signalling pathways, and the biosynthesis of amino acids. Quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) was used to verify the differential expression of 7 selected DEGs, and the results were consistent with RNA-seq data. In addition, the expression profile of MyHC isoforms in chicken skeletal muscle cells showed that with the extension of differentiation time, the expression of fast fiber subunits (types IIA and IIB) gradually increased, while slow muscle fiber subunits (type I) showed a downward trend after 4 days of differentiation. The differential genes screened in this study will provide some new ideas for further understanding the molecular mechanism of skeletal muscle fiber transformation in broilers.

Veterinary informatics: forging the future between veterinary medicine, human medicine, and One Health initiatives-a joint paper by the Association for Veterinary Informatics (AVI) and the CTSA One Health Alliance (COHA)

Objectives

This manuscript reviews the current state of veterinary medical electronic health records and the ability to aggregate and analyze large datasets from multiple organizations and clinics. We also review analytical techniques as well as research efforts into veterinary informatics with a focus on applications relevant to human and animal medicine. Our goal is to provide references and context for these resources so that researchers can identify resources of interest and translational opportunities to advance the field.

Methods and Results

This review covers various methods of veterinary informatics including natural language processing and machine learning techniques in brief and various ongoing and future projects. After detailing techniques and sources of data, we describe some of the challenges and opportunities within veterinary informatics as well as providing reviews of common One Health techniques and specific applications that affect both humans and animals.

Discussion

Current limitations in the field of veterinary informatics include limited sources of training data for developing machine learning and artificial intelligence algorithms, siloed data between academic institutions, corporate institutions, and many small private practices, and inconsistent data formats that make many integration problems difficult. Despite those limitations, there have been significant advancements in the field in the last few years and continued development of a few, key, large data resources that are available for interested clinicians and researchers. These real-world use cases and applications show current and significant future potential as veterinary informatics grows in importance. Veterinary informatics can forge new possibilities within veterinary medicine and between veterinary medicine, human medicine, and One Health initiatives.

Ten years of the horse reference genome: insights into equine biology, domestication and population dynamics in the post-genome era

The horse reference genome from the Thoroughbred mare Twilight has been available for a decade and, together with advances in genomics technologies, has led to unparalleled developments in equine genomics. At the core of this progress is the continuing improvement of the quality, contiguity and completeness of the reference genome, and its functional annotation. Recent achievements include the release of the next version of the reference genome (EquCab3.0) and generation of a reference sequence for the Y chromosome. Horse satellite‐free centromeres provide unique models for mammalian centromere research. Despite extremely low genetic diversity of the Y chromosome, it has been possible to trace patrilines of breeds and pedigrees and show that Y variation was lost in the past approximately 2300 years owing to selective breeding. The high‐quality reference genome has led to the development of three different SNP arrays and WGSs of almost 2000 modern individual horses. The collection of WGS of hundreds of ancient horses is unique and not available for any other domestic species. These tools and resources have led to global population studies dissecting the natural history of the species and genetic makeup and ancestry of modern breeds. Most importantly, the available tools and resources, together with the discovery of functional elements, are dissecting molecular causes of a growing number of Mendelian and complex traits. The improved understanding of molecular underpinnings of various traits continues to benefit the health and performance of the horse whereas also serving as a model for complex disease across species.