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不同生长速度的虹鳟鱼在季节性梯度下的转录组分析

Transcriptome profiling in fast versus slow-growing rainbow trout across seasonal gradients.

作者信息

Danzmann Roy G, Kocmarek Andrea L, Norman Joseph D, Rexroad Caird E, Palti Yniv

机构信息

Department of Integrative Biology, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada.

National Center for Cool and Cold Water Aquaculture, ARS-USDA, 11861 Leetown Road, Kearneysville, WV, 25430, USA.

出版信息

BMC Genomics. 2016 Jan 15;17:60. doi: 10.1186/s12864-016-2363-5.

DOI:10.1186/s12864-016-2363-5
PMID:26768650
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4714434/
Abstract

BACKGROUND

Circannual rhythms in vertebrates can influence a wide variety of physiological processes. Some notable examples include annual reproductive cycles and for poikilotherms, seasonal changes modulating growth. Increasing water temperature elevates growth rates in fishes, but increases in photoperiod regime can have similar influences even at constant temperature. Therefore, in order to understand the dynamics of growth in fish it is important to consider the background influence of photoperiod regime on gene expression differences. This study examined the influence of a declining photoperiod regime (winter solstice) compared to an increasing photoperiod regime (spring equinox) on white muscle transcriptome profiles in fast and slow-growing rainbow trout from a commercial aquaculture strain.

RESULTS

Slow-growing fish could be characterized as possessing transcriptome profiles that conform in many respects to an endurance training regime in humans. They have elevated mitochondrial and cytosolic creatine kinase expression levels and appear to suppress mTOR-signaling as evidenced by elevated TSC2 expression, and they also have elevated p53 levels. Large fish display a physiological repertoire that may be consistent with strength/resistance physiology having elevated cytoskeletal gene component expression and glycogen metabolism cycling along with higher PI3K levels. In many respects small vs. large fish match eccentric vs. concentric muscle expression patterns, respectively. Lipid metabolic genes are also more elevated in larger fish, the most notable being the G0S2 switch gene. M and Z-line sarcomere remodelling appears to be more prevalent in large fish. Twenty-three out of 26 gene families with previously reported significant SNP-based growth differences were detected as having significant expression differences.

CONCLUSIONS

Larger fish display a broader array of genes showing higher expression, and their profiles are more similar to those observed in December lot fish (i.e., an accelerated growth period). Conversely, small fish display gene profiles more similar to seasonal growth decline phases (i.e., September lot fish). Overall, seasonal timing was coupled to greater differences in gene expression compared to differences associated with fish size.

摘要

背景

脊椎动物的年周期节律可影响多种生理过程。一些显著的例子包括每年的生殖周期,对于变温动物而言,还有调节生长的季节性变化。水温升高会提高鱼类的生长速度,但即使在恒温条件下,光周期变化也能产生类似的影响。因此,为了理解鱼类生长的动态变化,考虑光周期变化对基因表达差异的背景影响很重要。本研究比较了光周期递减(冬至)与光周期递增(春分)对商业养殖品系中快速生长和慢速生长虹鳟鱼白肌转录组图谱的影响。

结果

慢速生长的鱼其转录组图谱在许多方面符合人类耐力训练模式的特征。它们的线粒体和胞质肌酸激酶表达水平升高,并且似乎抑制了mTOR信号传导,这从TSC2表达升高可以得到证明,它们的p53水平也升高。大型鱼表现出的生理特征可能与力量/抗性生理一致,其细胞骨架基因成分表达升高,糖原代谢循环加快,同时PI3K水平更高。在许多方面,小鱼和大鱼分别与离心肌和向心机的表达模式相匹配。大型鱼中脂质代谢基因的表达也更高,最显著的是G0S2开关基因。M线和Z线肌节重塑在大型鱼中似乎更普遍。在之前报道的基于SNP的生长差异显著的26个基因家族中,检测到23个存在显著的表达差异。

结论

大型鱼表现出更广泛的高表达基因,其图谱与12月批次的鱼(即生长加速期)中观察到的更为相似。相反,小鱼的基因图谱与季节性生长下降阶段(即9月批次的鱼)更为相似。总体而言,与鱼类大小相关的差异相比,季节性时间与基因表达的差异联系更为紧密。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3732/4714434/3007d56d82ca/12864_2016_2363_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3732/4714434/c31cf4691798/12864_2016_2363_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3732/4714434/c64315c10a63/12864_2016_2363_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3732/4714434/e531e9380dbf/12864_2016_2363_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3732/4714434/1f550e571251/12864_2016_2363_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3732/4714434/59393922f91c/12864_2016_2363_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3732/4714434/3007d56d82ca/12864_2016_2363_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3732/4714434/c31cf4691798/12864_2016_2363_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3732/4714434/c64315c10a63/12864_2016_2363_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3732/4714434/e531e9380dbf/12864_2016_2363_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3732/4714434/1f550e571251/12864_2016_2363_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3732/4714434/59393922f91c/12864_2016_2363_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3732/4714434/3007d56d82ca/12864_2016_2363_Fig6_HTML.jpg

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