Evidence map›Paper›PMID 32005147›Full record

ArticleBMC genomics2020

Whole-genome sequencing of wild Siberian musk deer (Moschus moschiferus) provides insights into its genetic features.

Li Yi, Menggen Dalai, Rina Su, Weili Lin, Myagmarsuren Erdenedalai, Batkhuu Luvsantseren, Chimedragchaa Chimedtseren, Zhen Wang, Surong Hasi

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.2field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Dietary supplementation withFrontiers in veterinary science · 2024
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Genomics of Adaptations in Ungulates.Animals : an open access journal from MDPI · 2021
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 4 institutions in 1 country.

Li YiInner Mongolia Agricultural University / Key Laboratory of Clinical Diagnosis and Treatment Technology in Animal Disease, Ministry of Agriculture and Rural Affairs, Hohhot, 010018, China.
Menggen DalaiAffiliated Hospital of Inner Mongolia Medical University, Hohhot, 010050, China. mengendalai@sina.com.
Rina SuInner Mongolia Agricultural University / Key Laboratory of Clinical Diagnosis and Treatment Technology in Animal Disease, Ministry of Agriculture and Rural Affairs, Hohhot, 010018, China.
Weili LinKey Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
Myagmarsuren ErdenedalaiInstitute of Traditional Medicine and Technology, Ulaanbaatar, Mongolia.
Batkhuu LuvsantserenInstitute of Traditional Medicine and Technology, Ulaanbaatar, Mongolia.
Chimedragchaa ChimedtserenInstitute of Traditional Medicine and Technology, Ulaanbaatar, Mongolia. Chi.chimedragchaa@yahoo.com.
Zhen WangKey Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, China. zwang01@sibs.ac.cn.
Surong HasiInner Mongolia Agricultural University / Key Laboratory of Clinical Diagnosis and Treatment Technology in Animal Disease, Ministry of Agriculture and Rural Affairs, Hohhot, 010018, China. surong@imau.edu.cn.
Inner Mongolia Agricultural University · CNShanghai Institutes for Biological Sciences · CNInner Mongolia Medical University · CNMinistry of Agriculture and Rural Affairs · CN

Funding

the National International Scientific and Technological Cooperation Project 2016YFE0116500
6 · The paper itself

Abstract

backgroundSiberian musk deer, one of the seven species, is distributed in coniferous forests of Asia. Worldwide, the population size of Siberian musk deer is threatened by severe illegal poaching for commercially valuable musk and meat, habitat losses, and forest fire. At present, this species is categorized as Vulnerable on the IUCN Red List. However, the genetic information of Siberian musk deer is largely unexplored.

resultsHere, we produced 3.10 Gb draft assembly of wild Siberian musk deer with a contig N50 of 29,145 bp and a scaffold N50 of 7,955,248 bp. We annotated 19,363 protein-coding genes and estimated 44.44% of the genome to be repetitive. Our phylogenetic analysis reveals that wild Siberian musk deer is closer to Bovidae than to Cervidae. Comparative analyses showed that the genetic features of Siberian musk deer adapted in cold and high-altitude environments. We sequenced two additional genomes of Siberian musk deer constructed demographic history indicated that changes in effective population size corresponded with recent glacial epochs. Finally, we identified several candidate genes that may play a role in the musk secretion based on transcriptome analysis.

conclusionsHere, we present a high-quality draft genome of wild Siberian musk deer, which will provide a valuable genetic resource for further investigations of this economically important musk deer.

Indexed as

Adaptation, BiologicalAnimalsContig MappingDeerEvolution, MolecularFemaleGene Expression ProfilingGenome SizeMolecular Sequence AnnotationPhylogenyPopulation DensitySequence Analysis, RNAWhole Genome SequencingDe novo assemblyGenetic featuresMusk secretionWild Siberian musk deer (Moschus moschiferus) genome

Identifiers

PMID32005147
PMCPMC6995116
OpenAlexW3013895579

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.