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The mammalian spermatozoon has a unique chromatin structure in which the majority of histones are replaced by protamines during spermatogenesis and a small fraction of nucleosomes are retained at specific locations of the genome. The sperm's chromatin structure remains unresolved in most animal species, including the pig. However, mapping the genomic locations of retained nucleosomes in sperm could help understanding the molecular basis of both sperm development and function as well as embryo development. This information could then be useful to identify molecular markers for sperm quality and fertility traits. Here, micrococcal nuclease digestion coupled with high throughput sequencing was performed on pig sperm to map the genomic location of mono- and sub-nucleosomal chromatin fractions in relation to a set of diverse functional elements of the genome, some of which were related to semen quality and early embryogenesis. In particular, the investigated elements were promoters, the different sections of the gene body, coding and non-coding RNAs present in the pig sperm, potential transcription factor binding sites, genomic regions associated to semen quality traits and repeat elements. The analysis yielded 25,293 and 4,239 peaks in the mono- and sub-nucleosomal fractions, covering 0.3% and 0.02% of the porcine genome, respectively. A cross-species comparison revealed positional conservation of the nucleosome retention in sperm between the pig data and a human dataset that found nucleosome enrichment in genomic regions of importance in development. Both gene ontology analysis of the genes mapping nearby the mono-nucleosomal peaks and the identification of putative transcription factor binding motifs within the mono- and the sub- nucleosomal peaks showed enrichment for processes related to sperm function and embryo development. There was significant motif enrichment for Znf263, which in humans was suggested to be a key regulator of genes with paternal preferential expression during early embryogenesis. Moreover, enriched positional intersection was found in the genome between the mono-nucleosomal peaks and both the RNAs present in pig sperm and the RNAs related to sperm quality. There was no co-location between GWAS hits for semen quality in swine and the nucleosomal sites. Finally, the data evidenced depletion of mono-nucleosomes in long interspersed nuclear elements and enrichment of sub-nucleosomes in short interspersed repeat elements. These results suggest that retained nucleosomes in sperm could both mark regulatory elements or genes expressed during spermatogenesis linked to semen quality and fertility and act as transcriptional guides during early embryogenesis. The results of this study support the undertaking of ambitious research using a larger number of samples to robustly assess the positional relationship between histone retention in sperm and the reproductive ability of boars. [ABSTRACT FROM AUTHOR]

Background: Reliable biomarkers to differentiate gastrointestinal cancer (GIC) from chronic inflammatory enteropathy (CIE) in dogs are needed. Fecal and serum microRNAs (miRNAs) have been proposed as diagnostic and prognostic markers of GI disease in humans and dogs. Hypothesis/Objectives: Dogs with GIC have fecal and serum miRNA profiles that differ from those of dogs with CIE. Aims: (a) identify miRNAs that differentiate GIC from CIE, (b) use high‐throughput reverse transcription quantitative real‐time PCR (RT‐qPCR) to establish fecal and serum miRNA panels to distinguish GIC from CIE in dogs. Animals: Twenty‐four dogs with GIC, 10 dogs with CIE, and 10 healthy dogs, all client‐owned. Methods: An international multicenter observational prospective case‐control study. Small RNA sequencing was used to identify fecal and serum miRNAs, and RT‐qPCR was used to establish fecal and serum miRNA panels with the potential to distinguish GIC from CIE. Results: The best diagnostic performance for distinguishing GIC from CIE was fecal miR‐451 (AUC: 0.955, sensitivity: 86.4%, specificity: 100%), miR‐223 (AUC: 0.918, sensitivity: 90.9%, specificity: 80%), and miR‐27a (AUC: 0.868, sensitivity: 81.8%, specificity: 90%) and serum miR‐20b (AUC: 0.905, sensitivity: 90.5%, specificity: 90%), miR‐148a‐3p (AUC: 0.924, sensitivity: 85.7%, specificity: 90%), and miR‐652 (AUC: 0.943, sensitivity: 90.5%, specificity: 90%). Slightly improved diagnostic performance was achieved when combining fecal miR‐451 and miR‐223 (AUC: 0.973, sensitivity: 95.5%, specificity: 90%). Conclusions and Clinical Importance: When used as part of a diagnostic RT‐qPCR panel, the abovementioned miRNAs have the potential to function as noninvasive biomarkers for the differentiation of GIC and CIE in dogs. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) are short non-coding RNAs that regulate gene expression at the post-transcriptional level. miRNAs have been found in urine and have shown diagnostic potential in human nephropathies. Here, we aimed to characterize, for the first time, the feline urinary miRNAome and explore the use of urinary miRNA profiles as non-invasive biomarkers for feline pyelonephritis (PN). Thirty-eight cats were included in a prospective case-control study and classified in five groups: healthy Control cats (n = 11), cats with PN (n = 10), cats with subclinical bacteriuria or cystitis (SB/C, n = 5), cats with ureteral obstruction (n = 7) and cats with chronic kidney disease (n = 5). By small RNA sequencing we identified 212 miRNAs in cat urine, including annotated (n = 137) and putative novel (n = 75) miRNAs. The 15 most highly abundant urinary miRNAs accounted for nearly 71% of all detected miRNAs, most of which were previously identified in feline kidney. Ninety-nine differentially abundant (DA) miRNAs were identified when comparing Control cats to cats with urological conditions and 102 DA miRNAs when comparing PN to other urological conditions. Tissue clustering analysis revealed that the majority of urine samples clustered close to kidney, which confirm the likely cellular origin of the secreted urinary miRNAs. Relevant DA miRNAs were verified by quantitative real-time PCR (qPCR). Eighteen miRNAs discriminated Control cats from cats with a urological condition. Of those, seven miRNAs were DA by both RNAseq and qPCR methods between Control and PN cats (miR-125b-5p, miR-27a-3p, miR-21-5p, miR-27b-3p, miR-125a-5p, miR-17-5p and miR-23a-3p) or DA between Control and SB/C cats (miR-125b-5p). Six additional miRNAs (miR-30b-5p, miR-30c, miR-30e-5p, miR-27a-3p, miR-27b-39 and miR-222) relevant for discriminating PN from other urological conditions were identified by qPCR alone (n = 4) or by both methods (n = 2) (P<0.05). This panel of 13 miRNAs has potential as non-invasive urinary biomarkers for diagnostic of PN and other urological conditions in cats. [ABSTRACT FROM AUTHOR]

Backfat is an important trait in pork production, and it has been included in the breeding objectives of genetic companies for decades. Although adipose tissue is a good energy storage, excessive fat results in reduced efficiency and economical losses. A large QTL for backfat thickness on chromosome 5 is still segregating in different commercial pig breeds. We fine mapped this QTL region using a genome-wide association analysis (GWAS) with 133,358 genotyped animals from five commercial populations (Landrace, Pietrain, Large White, Synthetic, and Duroc) imputed to the porcine 660K SNP chip. The lead SNP was located at 5:66103958 (G/A) within the third intron of the CCND2 gene, with the G allele associated with more backfat, while the A allele is associated with less backfat. We further phased the QTL region to discover a core haplotype of five SNPs associated with low backfat across three breeds. Linkage disequilibrium analysis using whole-genome sequence data revealed three candidate causal variants within intronic regions and downstream of the CCND2 gene, including the lead SNP. We evaluated the association of the lead SNP with the expression of the genes in the QTL region (including CCND2) in a large cohort of 100 crossbred samples, sequenced in four different tissues (lung, spleen, liver, muscle). Results show that the A allele increases the expression of CCND2 in an additive way in three out of four tissues. Our findings indicate that the causal variant for this QTL region is a regulatory variant within the third intron of the CCND2 gene affecting the expression of CCND2. [ABSTRACT FROM AUTHOR]

Understanding the cell molecular changes occurring as a results of climatic circumstances is crucial in the current days in which climate change and global warming are one of the most serious challenges that living organisms have to face. Sperm are one of the mammals' cells most sensitive to heat, therefore evaluating the impact of seasonal changes in terms of its transcriptional activity can contribute to elucidate how these cells cope with heat stress events. We sequenced the total sperm RNA from 64 ejaculates, 28 collected in summer and 36 collected in autumn, from 40 Manchega rams. A highly rich transcriptome (11,896 different transcripts) with 90 protein coding genes that exceed an average number of 5000 counts were found. Comparing transcriptome in the summer and autumn ejaculates, 236 significant differential abundance genes were assessed, most of them (228) downregulated. The main functions that these genes are related to sexual reproduction and negative regulation of protein metabolic processes and kinase activity. Sperm response to heat stress supposes a drastic decrease of the transcriptional activity, and the upregulation of only a few genes related with the basic functions to maintain the organisms' homeostasis and surviving. Rams' spermatozoids carry remnant mRNAs which are retrospectively indicators of events occurring along the spermatogenesis process, including abiotic factors such as environmental temperature. [ABSTRACT FROM AUTHOR]

Transmission Ratio Distortion (TRD), the uneven transmission of an allele from a parent to its offspring, can be caused by allelic differences affecting gametogenesis, fertilization or embryogenesis. However, TRD remains vaguely studied at a genomic scale. We sequenced the diploid and haploid genomes of three boars from leukocytes and spermatozoa at 50x to shed light into the genetic basis of spermatogenesis-caused Allelic Ratio Distortion (ARD). We first developed a Binomial model to identify ARD by simultaneously analysing all three males. This led to the identification of 55 ARD SNPs, most of which were animal-specific. We then evaluated ARD individually within each pig by a Fisher's exact test and identified two shared genes (TOP3A and UNC5B) and four shared genomic regions harbouring distinct ARD SNPs in the three boars. The shared genomic regions contained candidate genes with functions related to spermatogenesis including AK7 , ARID4B , BDKRB2 , GSK3B , NID1 , NSMCE1 , PALB2 , VRK1 and ZC3H13. Using the Fisher's test, we also identified 378 genes containing variants with protein damaging potential in at least one boar, a high proportion of which, including FAM120B , TDRD15 , JAM2 or AOX4 among others, are associated to spermatogenesis. Overall, our results show that sperm is subjected to ARD with variants associated to a wide variety of genes involved in different stages of spermatogenesis. [ABSTRACT FROM AUTHOR]

Understanding the molecular basis of cell function and ultimate phenotypes is crucial for the development of biological markers. With this aim, several RNA-seq studies have been devoted to the characterization of the transcriptome of ejaculated spermatozoa in relation to sperm quality and fertility. Semen quality follows a seasonal pattern and decays in the summer months in several animal species. The aim of this study was to deeply profile the transcriptome of the boar sperm and to evaluate its seasonal changes. We sequenced the total and the short fractions of the sperm RNA from 10 Pietrain boars, 5 collected in summer and 5 five sampled in winter, and identified a complex and rich transcriptome with 4,436 coding genes of moderate to high abundance. Transcript fragmentation was high but less obvious in genes related to spermatogenesis, chromatin compaction and fertility. Short non-coding RNAs mostly included piwi-interacting RNAs, transfer RNAs and microRNAs. We also compared the transcriptome of the summer and the winter ejaculates and identified 34 coding genes and 7 microRNAs with a significantly distinct distribution. These genes were mostly related to oxidative stress, DNA damage and autophagy. This is the deepest characterization of the boar sperm transcriptome and the first study linking the transcriptome and the seasonal variability of semen quality in animals. The annotation described here can be used as a reference for the identification of markers of sperm quality in pigs. [ABSTRACT FROM AUTHOR]

Autosomal recessive retinal degenerative diseases cause visual impairment and blindness in both humans and dogs. Currently, no standard treatment is available, but pioneering gene therapy-based canine models have been instrumental for clinical trials in humans. To study a novel form of retinal degeneration in Labrador retriever dogs with clinical signs indicating cone and rod degeneration, we used whole-genome sequencing of an affected sib-pair and their unaffected parents. A frameshift insertion in the ATP binding cassette subfamily A member 4 (ABCA4) gene (c.4176insC), leading to a premature stop codon in exon 28 (p.F1393Lfs*1395), was identified. In contrast to unaffected dogs, no full-length ABCA4 protein was detected in the retina of an affected dog. The ABCA4 gene encodes a membrane transporter protein localized in the outer segments of rod and cone photoreceptors. In humans, the ABCA4 gene is associated with Stargardt disease (STGD), an autosomal recessive retinal degeneration leading to central visual impairment. A hallmark of STGD is the accumulation of lipofuscin deposits in the retinal pigment epithelium (RPE). The discovery of a canine homozygous ABCA4 loss-of-function mutation may advance the development of dog as a large animal model for human STGD. [ABSTRACT FROM AUTHOR]

The study of the boar sperm transcriptome by RNA-seq can provide relevant information on sperm quality and fertility and might contribute to animal breeding strategies. However, the analysis of the spermatozoa RNA is challenging as these cells harbor very low amounts of highly fragmented RNA, and the ejaculates also contain other cell types with larger amounts of non-fragmented RNA. Here, we describe a strategy for a successful boar sperm purification, RNA extraction and RNA-seq library preparation. Using these approaches our objectives were: (i) to evaluate the sperm recovery rate (SRR) after boar spermatozoa purification by density centrifugation using the non-porcine-specific commercial reagent BoviPureTM; (ii) to assess the correlation between SRR and sperm quality characteristics; (iii) to evaluate the relationship between sperm cell RNA load and sperm quality traits and (iv) to compare different library preparation kits for both total RNA-seq (SMARTer Universal Low Input RNA and TruSeq RNA Library Prep kit) and small RNA-seq (NEBNext Small RNA and TailorMix miRNA Sample Prep v2) for high-throughput sequencing. Our results show that pig SRR (~22%) is lower than in other mammalian species and that it is not significantly dependent of the sperm quality parameters analyzed in our study. Moreover, no relationship between the RNA yield per sperm cell and sperm phenotypes was found. We compared a RNA-seq library preparation kit optimized for low amounts of fragmented RNA with a standard kit designed for high amount and quality of input RNA and found that for sperm, a protocol designed to work on low-quality RNA is essential. We also compared two small RNA-seq kits and did not find substantial differences in their performance. We propose the methodological workflow described for the RNA-seq screening of the boar spermatozoa transcriptome. Abbreviations: FPKM: fragments per kilobase of transcript per million mapped reads; KRT1: keratin 1; miRNA: micro-RNA; miscRNA: miscellaneous RNA; Mt rRNA: mitochondrial ribosomal RNA; Mt tRNA: mitochondrial transference RNA; OAZ3: ornithine decarboxylase antizyme 3; ORT: osmotic resistance test; piRNA: Piwi-interacting RNA; PRM1: protamine 1; PTPRC: protein tyrosine phosphatase receptor type C; rRNA: ribosomal RNA; snoRNA: small nucleolar RNA; snRNA: small nuclear RNA; SRR: sperm recovery rate; tRNA: transfer RNA [ABSTRACT FROM AUTHOR]