Suppr超能文献

通过对16S rRNA基因扩增子进行高通量测序揭示的雅库特牛和卡尔梅克牛瘤胃及粪便微生物群谱数据。

Data on rumen and faeces microbiota profiles of Yakutian and Kalmyk cattle revealed by high-throughput sequencing of 16S rRNA gene amplicons.

作者信息

Kataev Vladimir Ya, Sleptsov Ivan I, Martynov Andrey A, Aduchiev Bator K, Khlopko Yuri A, Miroshnikov Sergey A, Cherkasov Sergey V, Plotnikov Andrey O

机构信息

Institute for Cellular and Intracellular Symbiosis of the Ural Branch of the Russian Academy of Sciences, 11 Pionerskaya St., Orenburg 460000, Russian Federation.

Arctic State Agrotechnological University, 15 Krasilnikov St., Yakutsk 677007, Russian Federation.

出版信息

Data Brief. 2020 Oct 11;33:106407. doi: 10.1016/j.dib.2020.106407. eCollection 2020 Dec.

Abstract

It is known that the rumen microbiome directly or indirectly contributes to animal production, and may be a prospective target for mitigation of greenhouse gas emissions [1]. At the same time, feed types and components of diet can influence the composition of the rumen microbiome [2,3]. Fluctuations in the composition of the digestive tract microbiota can alter the development, health, and productivity of cattle [4]. Many studies of cattle microbiomes have focussed on the rumen microbiota, whereas the faecal microbiota has received less attention [5], [6], [7]. Therefore, the features of the faecal and the ruminal microbiomes in different cattle breeds are yet to be studied. Here, we provided 16S rRNA gene amplicon data of the ruminal and the faecal microbiomes from Yakutian and Kalmyk cattle living in the Republic of Sakha, Yakutia, Russia. Total DNA was extracted from 13 faecal and 13 ruminal samples, and DNA libraries were prepared and sequenced on an Illumina MiSeq platform. Paired-end raw reads were processed, and final operational taxonomic units (OTUs) were assigned to the respective prokaryotic taxa using the RDP (Ribosomal Database Project) database. Analysis of the microbiome composition at the phylum level revealed very similar faecal microbiota between the introduced Kalmyk breed and the indigenous Yakutian breed, whereas the ruminal microbiomes of these breeds differed substantially in terms of relative abundance of some prokaryotic phyla. We believe that the data obtained may provide new insights into the dynamics of the ruminal and the faecal microbiota of cattle as well as disclose breed-specific features of ruminal microbiomes. Besides, these data will contribute to our understanding of the ruminal microbiome structure and function, and might be useful for the management of cattle feeding and ruminal methane production.

摘要

已知瘤胃微生物群直接或间接影响动物生产,并且可能是减少温室气体排放的一个潜在目标[1]。同时,饲料类型和日粮成分会影响瘤胃微生物群的组成[2,3]。消化道微生物群组成的波动会改变牛的发育、健康和生产力[4]。许多关于牛微生物群的研究都集中在瘤胃微生物群上,而粪便微生物群受到的关注较少[5,6,7]。因此,不同牛品种的粪便和瘤胃微生物群的特征尚待研究。在此,我们提供了生活在俄罗斯萨哈共和国雅库特地区的雅库特牛和卡尔梅克牛的瘤胃和粪便微生物群的16S rRNA基因扩增子数据。从13份粪便样本和13份瘤胃样本中提取总DNA,并制备DNA文库,在Illumina MiSeq平台上进行测序。对双端原始读数进行处理,并使用RDP(核糖体数据库项目)数据库将最终的操作分类单元(OTU)分配给相应的原核生物分类群。在门水平上对微生物群组成的分析表明,引入的卡尔梅克品种和本地雅库特品种之间的粪便微生物群非常相似,而这些品种的瘤胃微生物群在一些原核生物门的相对丰度方面存在很大差异。我们认为,所获得的数据可能为牛瘤胃和粪便微生物群的动态变化提供新的见解,并揭示瘤胃微生物群的品种特异性特征。此外,这些数据将有助于我们理解瘤胃微生物群的结构和功能,可能对牛的饲养管理和瘤胃甲烷产生有用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a6e/7578675/713e281aadd0/gr1.jpg

相似文献

3
The rumen microbial metagenome associated with high methane production in cattle.
BMC Genomics. 2015 Oct 23;16:839. doi: 10.1186/s12864-015-2032-0.
6
The bovine epimural microbiota displays compositional and structural heterogeneity across different ruminal locations.
J Dairy Sci. 2020 Apr;103(4):3636-3647. doi: 10.3168/jds.2019-17649. Epub 2020 Feb 11.
7
Changes in Microbiota in Rumen Digesta and Feces Due to a Grain-Based Subacute Ruminal Acidosis (SARA) Challenge.
Microb Ecol. 2017 Aug;74(2):485-495. doi: 10.1007/s00248-017-0940-z. Epub 2017 Feb 8.
10

本文引用的文献

1
The structure of microbial populations in Nelore GIT reveals inter-dependency of methanogens in feces and rumen.
J Anim Sci Biotechnol. 2020 Feb 24;11:6. doi: 10.1186/s40104-019-0422-x. eCollection 2020.
3
Taxon abundance, diversity, co-occurrence and network analysis of the ruminal microbiota in response to dietary changes in dairy cows.
PLoS One. 2017 Jul 13;12(7):e0180260. doi: 10.1371/journal.pone.0180260. eCollection 2017.
4
Variability, stability, and resilience of fecal microbiota in dairy cows fed whole crop corn silage.
Appl Microbiol Biotechnol. 2017 Aug;101(16):6355-6364. doi: 10.1007/s00253-017-8348-8. Epub 2017 Jun 10.
5
Ribosomal Database Project: data and tools for high throughput rRNA analysis.
Nucleic Acids Res. 2014 Jan;42(Database issue):D633-42. doi: 10.1093/nar/gkt1244. Epub 2013 Nov 27.
6
PEAR: a fast and accurate Illumina Paired-End reAd mergeR.
Bioinformatics. 2014 Mar 1;30(5):614-20. doi: 10.1093/bioinformatics/btt593. Epub 2013 Oct 18.
7
UPARSE: highly accurate OTU sequences from microbial amplicon reads.
Nat Methods. 2013 Oct;10(10):996-8. doi: 10.1038/nmeth.2604. Epub 2013 Aug 18.
10
UCHIME improves sensitivity and speed of chimera detection.
Bioinformatics. 2011 Aug 15;27(16):2194-200. doi: 10.1093/bioinformatics/btr381. Epub 2011 Jun 23.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验