Animal & Avian Sciences

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Start date: 2021Subject: search.filters.subject.Cattle

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    Are CD45RO+ and CD45RA- genuine markers for bovine memory T cells?
    (Springer Nature, 2022-10-11) Anmol, Kandel; Akanksha, Hada; Zhengguo, Xiao
    Effective vaccination induces memory T cells, which protect the host against pathogen re-infections. Therefore, detection of memory T cells is essential for evaluating vaccine efficacy, which was originally dependent on cytokine induction assays. Currently, two isoforms of CD45 tyrosine phosphatase, CD45RO expression and CD45RA exclusion (CD45RO+/ CD45RA-) are used extensively for detecting memory T cells in cattle. The CD45RO+/CD45RA- markers were first established in humans around three decades ago, and were adopted in cattle soon after. However, in the last two decades, some published data in humans have challenged the initial paradigm, and required multiple markers for identifying memory T cells. On the contrary, memory T cell detection in cattle still mostly relies on CD45RO+/CD45RA- despite some controversial evidence. In this review, we summarized the current literature to examine if CD45RO+/CD45RA- are valid markers for detecting memory T cells in cattle. It seems CD45RA and CD45RO (CD45RA/RO) as markers for identifying bovine memory T cells are questionable.
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    Genome-wide recombination map construction from single sperm sequencing in cattle
    (Springer Nature, 2022-03-05) Yang, Liu; Gao, Yahui; Li, Mingxun; Park, Ki-Eun; Liu, Shuli; Kang, Xiaolong; Liu, Mei; Oswalt, Adam; Fang, Lingzhao; Telugu, Bhanu P.; Sattler, Charles G.; Li, Cong-jun; Cole, John B.; Seroussi, Eyal; Xu, Lingyang; Yang, Lv; Zhou, Yang; Li, Li; Zhang, Hongping; Rosen, Benjamin D.; Van Tassell, Curtis P.; Ma, Li; Liu, George E.
    Meiotic recombination is one of the important phenomena contributing to gamete genome diversity. However, except for human and a few model organisms, it is not well studied in livestock, including cattle. To investigate their distributions in the cattle sperm genome, we sequenced 143 single sperms from two Holstein bulls. We mapped meiotic recombination events at high resolution based on phased heterozygous single nucleotide polymorphism (SNP). In the absence of evolutionary selection pressure in fertilization and survival, recombination events in sperm are enriched near distal chromosomal ends, revealing that such a pattern is intrinsic to the molecular mechanism of meiosis. Furthermore, we further validated these findings in single sperms with results derived from sequencing its family trio of diploid genomes and our previous studies of recombination in cattle. To our knowledge, this is the first large-scale single sperm whole-genome sequencing effort in livestock, which provided useful information for future studies of recombination, genome instability, and male infertility.
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    Towards the detection of copy number variation from single sperm sequencing in cattle
    (Springer Nature, 2022-03-17) Yang, Liu; Gao, Yahui; Oswalt, Adam; Fang, Lingzhao; Boschiero, Clarissa; Neupane, Mahesh; Sattler, Charles G.; Li, Cong-jun; Seroussi, Eyal; Xu, Lingyang; Yang, Lv; Li, Li; Zhang, Hongping; Rosen, Benjamin D.; Van Tassell, Curtis P.; Zhou, Yang; Ma, Li; Liu, George E.
    Copy number variation (CNV) has been routinely studied using bulk-cell sequencing. However, CNV is not well studied on the single-cell level except for humans and a few model organisms. We sequenced 143 single sperms of two Holstein bulls, from which we predicted CNV events using 14 single sperms with deep sequencing. We then compared the CNV results derived from single sperms with the bulk-cell sequencing of one bull’s family trio of diploid genomes. As a known CNV hotspot, segmental duplications were also predicted using the bovine ARS-UCD1.2 genome. Although the trio CNVs validated only some single sperm CNVs, they still showed a distal chromosomal distribution pattern and significant associations with segmental duplications and satellite repeats. Our preliminary results pointed out future research directions and highlighted the importance of uniform whole genome amplification, deep sequence coverage, and dedicated software pipelines for CNV detection using single cell sequencing data.