Long-read RNA Sequencing Improves the Annotation of the Equine Transcriptome

A high-quality reference genome assembly, a biobank of diverse equine tissues from the Functional Annotation of the Animal Genome (FAANG) initiative, and incorporation of long-read sequencing technologies, have enabled efforts to build a comprehensive and tissue-specific equine transcriptome. The equine FAANG transcriptome reported here provides up to 45% improvement in transcriptome completeness across tissue types when compared to either RefSeq or Ensembl transcriptomes. This transcriptome also provides major improvements in the identification of alternatively spliced isoforms, novel noncoding genes, and 3’ transcription termination site (TTS) annotations. The equine FAANG transcriptome will empower future functional studies of important equine traits while providing future opportunities to identify allele-specific expression and differentially expressed genes across tissues

Missense Mutation in Exon 2 of SLC36A1 Responsible for Champagne Dilution in Horses

Champagne coat color in horses is controlled by a single, autosomal-dominant gene (CH). The phenotype produced by this gene is valued by many horse breeders, but can be difficult to distinguish from the effect produced by the Cream coat color dilution gene (CR). Three sires and their families segregating for CH were tested by genome scanning with microsatellite markers. The CH gene was mapped within a 6 cM region on horse chromosome 14 (LOD = 11.74 for θ = 0.00). Four candidate genes were identified within the region, namely SPARC [Secreted protein, acidic, cysteine-rich (osteonectin)], SLC36A1 (Solute Carrier 36 family A1), SLC36A2 (Solute Carrier 36 family A2), and SLC36A3 (Solute Carrier 36 family A3). SLC36A3 was not expressed in skin tissue and therefore not considered further. The other three genes were sequenced in homozygotes for CH and homozygotes for the absence of the dilution allele (ch). SLC36A1 had a nucleotide substitution in exon 2 for horses with the champagne phenotype, which resulted in a transition from a threonine amino acid to an arginine amino acid (T63R). The association of the single nucleotide polymorphism (SNP) with the champagne dilution phenotype was complete, as determined by the presence of the nucleotide variant among all 85 horses with the champagne dilution phenotype and its absence among all 97 horses without the champagne phenotype. This is the first description of a phenotype associated with the SLC36A1 gene

Selection of diagnostic features on breast MRI to differentiate between malignant and benign lesions using computer-aided diagnosis: differences in lesions presenting as mass and non-mass-like enhancement

Purpose: To investigate methods developed for the characterisation of the morphology and enhancement kinetic features of both mass and non-mass lesions, and to determine their diagnostic performance to differentiate between malignant and benign lesions that present as mass versus non-mass types. Methods: Quantitative analysis of morphological features and enhancement kinetic parameters of breast lesions were used to differentiate among four groups of lesions: 88 malignant (43 mass, 45 non-mass) and 28 benign (19 mass, 9 non-mass). The enhancement kinetics was measured and analysed to obtain transfer constant (Ktrans) and rate constant (kep). For each mass eight shape/margin parameters and 10 enhancement texture features were obtained. For the lesions presenting as nonmass-like enhancement, only the texture parameters were obtained. An artificial neural network (ANN) was used to build the diagnostic model. Results: For lesions presenting as mass, the four selected morphological features could reach an area under the ROC curve (AUC) of 0.87 in differentiating between malignant and benign lesions. The kinetic parameter (kep) analysed from the hot spot of the tumour reached a comparable AUC of 0.88. The combined morphological and kinetic features improved the AUC to 0.93, with a sensitivity of 0.97 and a specificity of 0.80. For lesions presenting as non-mass-like enhancement, four texture features were selected by the ANN and achieved an AUC of 0.76. The kinetic parameter kepfrom the hot spot only achieved an AUC of 0.59, with a low added diagnostic value. Conclusion: The results suggest that the quantitative diagnostic features can be used for developing automated breast CAD (computer-aided diagnosis) for mass lesions to achieve a high diagnostic performance, but more advanced algorithms are needed for diagnosis of lesions presenting as non-mass-like enhancement. © The Author(s) 2009

A High Density SNP Array for the Domestic Horse and Extant Perissodactyla: Utility for Association Mapping, Genetic Diversity, and Phylogeny Studies

An equine SNP genotyping array was developed and evaluated on a panel of samples representing 14 domestic horse breeds and 18 evolutionarily related species. More than 54,000 polymorphic SNPs provided an average inter-SNP spacing of ∼43 kb. The mean minor allele frequency across domestic horse breeds was 0.23, and the number of polymorphic SNPs within breeds ranged from 43,287 to 52,085. Genome-wide linkage disequilibrium (LD) in most breeds declined rapidly over the first 50–100 kb and reached background levels within 1–2 Mb. The extent of LD and the level of inbreeding were highest in the Thoroughbred and lowest in the Mongolian and Quarter Horse. Multidimensional scaling (MDS) analyses demonstrated the tight grouping of individuals within most breeds, close proximity of related breeds, and less tight grouping in admixed breeds. The close relationship between the Przewalski's Horse and the domestic horse was demonstrated by pair-wise genetic distance and MDS. Genotyping of other Perissodactyla (zebras, asses, tapirs, and rhinoceros) was variably successful, with call rates and the number of polymorphic loci varying across taxa. Parsimony analysis placed the modern horse as sister taxa to Equus przewalski. The utility of the SNP array in genome-wide association was confirmed by mapping the known recessive chestnut coat color locus (MC1R) and defining a conserved haplotype of ∼750 kb across all breeds. These results demonstrate the high quality of this SNP genotyping resource, its usefulness in diverse genome analyses of the horse, and potential use in related species

Recombinant Mouse PAP Has pH-Dependent Ectonucleotidase Activity and Acts through A1-Adenosine Receptors to Mediate Antinociception

Prostatic acid phosphatase (PAP) is expressed in nociceptive neurons and functions as an ectonucleotidase. When injected intraspinally, the secretory isoforms of human and bovine PAP protein have potent and long-lasting antinociceptive effects that are dependent on A1-adenosine receptor (A1R) activation. In this study, we purified the secretory isoform of mouse (m)PAP using the baculovirus expression system to determine if recombinant mPAP also had antinociceptive properties. We found that mPAP dephosphorylated AMP, and to a much lesser extent, ADP at neutral pH (pH 7.0). In contrast, mPAP dephosphorylated all purine nucleotides (AMP, ADP, ATP) at an acidic pH (pH 5.6). The transmembrane isoform of mPAP had similar pH-dependent ectonucleotidase activity. A single intraspinal injection of mPAP protein had long-lasting (three day) antinociceptive properties, including antihyperalgesic and antiallodynic effects in the Complete Freund's Adjuvant (CFA) inflammatory pain model. These antinociceptive effects were transiently blocked by the A1R antagonist 8-cyclopentyl-1, 3-dipropylxanthine (CPX), suggesting mPAP dephosphorylates nucleotides to adenosine to mediate antinociception just like human and bovine PAP. Our studies indicate that PAP has species-conserved antinociceptive effects and has pH-dependent ectonucleotidase activity. The ability to metabolize nucleotides in a pH-dependent manner could be relevant to conditions like inflammation where tissue acidosis and nucleotide release occur. Lastly, our studies demonstrate that recombinant PAP protein can be used to treat chronic pain in animal models

Genetic diversity in the modern horse illustrated from genome-wide SNP data

Horses were domesticated from the Eurasian steppes 5,000-6,000 years ago. Since then, the use of horses for transportation, warfare, and agriculture, as well as selection for desired traits and fitness, has resulted in diverse populations distributed across the world, many of which have become or are in the process of becoming formally organized into closed, breeding populations (breeds). This report describes the use of a genome-wide set of autosomal SNPs and 814 horses from 36 breeds to provide the first detailed description of equine breed diversity. F(ST) calculations, parsimony, and distance analysis demonstrated relationships among the breeds that largely reflect geographic origins and known breed histories. Low levels of population divergence were observed between breeds that are relatively early on in the process of breed development, and between those with high levels of within-breed diversity, whether due to large population size, ongoing outcrossing, or large within-breed phenotypic diversity. Populations with low within-breed diversity included those which have experienced population bottlenecks, have been under intense selective pressure, or are closed populations with long breed histories. These results provide new insights into the relationships among and the diversity within breeds of horses. In addition these results will facilitate future genome-wide association studies and investigations into genomic targets of selection

How I report breast magnetic resonance imaging studies for breast cancer staging and screening

Magnetic resonance imaging (MRI) of the breast is the most sensitive imaging technique for the diagnosis and local staging of primary breast cancer and yet, despite the fact that it has been in use for 20 years, there is little evidence that its widespread uncritical adoption has had a positive impact on patient-related outcomes. This has been attributed previously to the low specificity that might be expected with such a sensitive modality, but with modern techniques and protocols, the specificity and positive predictive value for malignancy can exceed that of breast ultrasound and mammography. A more likely explanation is that historically, clinicians have acted on MRI findings and altered surgical plans without prior histological confirmation. Furthermore, modern adjuvant therapy for breast cancer has improved so much that it has become a very tall order to show a an improvement in outcomes such as local recurrence rates. In order to obtain clinically useful information, it is necessary to understand the strengths and weaknesses of the technique and the physiological processes reflected in breast MRI. An appropriate indication for the scan, proper patient preparation and good scan technique, with rigorous quality assurance, are all essential prerequisites for a diagnostically relevant study. The use of recognised descriptors from a standardised lexicon is helpful, since assessment can then dictate subsequent recommendations for management, as in the American College of Radiology BI-RADS (Breast Imaging Reporting and Data System) lexicon (Morris et al., ACR BI-RADS® Atlas, Breast Imaging Reporting and Data System, 2013). It also enables audit of the service. However, perhaps the most critical factor in the generation of a meaningful report is for the reporting radiologist to have a thorough understanding of the clinical question and of the findings that will influence management. This has never been more important than at present, when we are in the throes of a remarkable paradigm shift in the treatment of both early stage and locally advanced breast cancer. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40644-016-0078-0) contains supplementary material, which is available to authorized users

NetMets: software for quantifying and visualizing errors in biological network segmentation

One of the major goals in biomedical image processing is accurate segmentation of networks embedded in volumetric data sets. Biological networks are composed of a meshwork of thin filaments that span large volumes of tissue. Examples of these structures include neurons and microvasculature, which can take the form of both hierarchical trees and fully connected networks, depending on the imaging modality and resolution. Network function depends on both the geometric structure and connectivity. Therefore, there is considerable demand for algorithms that segment biological networks embedded in three-dimensional data. While a large number of tracking and segmentation algorithms have been published, most of these do not generalize well across data sets. One of the major reasons for the lack of general-purpose algorithms is the limited availability of metrics that can be used to quantitatively compare their effectiveness against a pre-constructed ground-truth. In this paper, we propose a robust metric for measuring and visualizing the differences between network models. Our algorithm takes into account both geometry and connectivity to measure network similarity. These metrics are then mapped back onto an explicit model for visualization

Genetic Diversity in the Modern Horse Illustrated from Genome-Wide SNP Data

Horses were domesticated from the Eurasian steppes 5,000–6,000 years ago. Since then, the use of horses for transportation, warfare, and agriculture, as well as selection for desired traits and fitness, has resulted in diverse populations distributed across the world, many of which have become or are in the process of becoming formally organized into closed, breeding populations (breeds). This report describes the use of a genome-wide set of autosomal SNPs and 814 horses from 36 breeds to provide the first detailed description of equine breed diversity. FST calculations, parsimony, and distance analysis demonstrated relationships among the breeds that largely reflect geographic origins and known breed histories. Low levels of population divergence were observed between breeds that are relatively early on in the process of breed development, and between those with high levels of within-breed diversity, whether due to large population size, ongoing outcrossing, or large within-breed phenotypic diversity. Populations with low within-breed diversity included those which have experienced population bottlenecks, have been under intense selective pressure, or are closed populations with long breed histories. These results provide new insights into the relationships among and the diversity within breeds of horses. In addition these results will facilitate future genome-wide association studies and investigations into genomic targets of selection