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Original Research
31 July 2023

Introduction: Hair follicles in Dorper sheep are characterized by seasonal cyclic growth and development, consequently resulting in hair shedding during spring. The cyclic growth and development of hair follicles are regulated by several influencing factors such as photoperiods, hormones, age of the animal, genes, long non-coding RNAs (lncRNAs), and signaling pathways.

Methods: In the present study, skin samples of five shedding sheep (S), used as experimental animals, and three non-shedding sheep (N), used as controls, were collected at three time points (September 27, 2019; January 3, 2020; and March 17, 2020) for RNA sequencing (RNA-seq) technology. Nine different groups (S1-vs-S2, S1-vs-S3, S2-vs-S3, N1- vs-N2, N1-vs-N3, N2-vs-N3, S1-vs-N1, S2-vs-N2, and S3-vs-N3) were compared using FDR < 0.05 and log 21 FC >as thresholds to assess the differences in the expression of lncRNAs.

Results and discussion: In total, 395 differentially expressed (DE) lncRNAs were screened. Cluster heatmap analysis identified two types of expression patterns, namely, high expression during the anagen phase (A pattern) and high expression during the telogen phase (T pattern). Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed that the target genes were largely enriched in the Estrogen signaling pathway, PI3K-Akt signaling pathway, Fc gamma R-mediated phagocytosis, and cell adhesion molecules (CAMs), which are associated with hair follicle cyclic growth and development-related pathways. In addition, 17 pairs of lncRNAs-target genes related to hair follicle cyclic growth and development were screened, and a regulatory network was constructed. Altogether, candidate lncRNAs and their regulated target genes were screened that contributed to sheep hair follicle cyclic growth and development. We believe these findings will provide useful insights into the underlying regulatory mechanisms.

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Original Research
03 April 2023

When necessary, RNA-sequencing data or polymerase chain reaction (PCR) assays can be used to determine the presence of the chromosome Y (ChrY) in samples. This information allows for biological variation due to sexual dimorphism to be studied. A prime example is when researchers conduct RNA-sequencing of single embryos, or conceptuses, prior to the development of gonads. A recent publication of a complete sequence of the ChrY has removed limitations for the development of these procedures in cattle, otherwise imposed by the absence of a ChrY in the reference genome. Using the sequence of the cattle ChrY and transcriptome data, we conducted a systematic search for genes in the ChrY that are exclusively expressed in male tissues. The genes ENSBIXG00000029763, ENSBIXG00000029774, ENSBIXG00000029788, and ENSBIXG00000029892 were consistently expressed across male tissues and lowly expressed or absent in female samples. We observed that the cumulative values of counts per million were 2688-fold greater in males than the equivalent values in female samples. Thus, we deemed these genes suitable for the sexing of samples using RNA-sequencing data. We successfully used this set of genes to infer the sex of 22 cattle blastocysts (8 females and 14 males). Additionally, the completed sequence of the cattle ChrY has segments in the male-specific region that are not repeated. We designed a pair of oligonucleotides that targets one of these non-repeated regions in the male-specific sequence of the ChrY. Using this pair of oligonucleotides, in a multiplexed PCR assay with oligonucleotides that anneal to an autosome chromosome, we accurately identified the sex of cattle blastocysts. We developed efficient procedures for the sexing of samples in cattle using either transcriptome data or their DNA. The procedures using RNA-sequencing will greatly benefit researchers who work with samples limited in cell numbers which are only sufficient to produce transcriptome data. The oligonucleotides used for the accurate sexing of samples using PCR are transferable to other cattle tissue samples.

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5 citations
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Frontiers in Veterinary Science

Vetinformatics: An Insight for Decoding Livestock Systems Through In Silico Biology Volume II
Edited by Jun-Mo Kim, Rajesh Kumar Pathak
Deadline
30 May 2025
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