Evidence map›Paper›PMID 29846663›Full record

ArticleMolecular biology and evolution2018

Population Genomic Analysis Reveals Contrasting Demographic Changes of Two Closely Related Dolphin Species in the Last Glacial.

Nagarjun Vijay, Chungoo Park, Jooseong Oh, Soyeong Jin, Elizabeth Kern, Hyun Woo Kim, Jianzhi Zhang, Joong-Ki Park

Abstract readComparative Study
In one paragraph

Article in Molecular biology and evolution, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
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

12 citing papers in PubMed.

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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

8 authors.

Nagarjun VijayDepartment of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI.
Chungoo ParkSchool of Biological Sciences and Technology, Chonnam National University, Gwangju, Republic of Korea.
Jooseong OhSchool of Biological Sciences and Technology, Chonnam National University, Gwangju, Republic of Korea.
Soyeong JinDivision of EcoScience, Ewha Womans University, Seoul, Republic of Korea.
Elizabeth KernDivision of EcoScience, Ewha Womans University, Seoul, Republic of Korea.
Hyun Woo KimCetacean Research Institute, National Institute of Fisheries Science, Ulsan, Republic of Korea.
Jianzhi ZhangDepartment of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI.
Joong-Ki ParkDivision of EcoScience, Ewha Womans University, Seoul, Republic of Korea.

Funding

Position effects on gene expression level and noiseR01GM120093 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ZHANG, JIANZHI · 2016 to 2019
$1.2M
NIGMS NIH HHS R01 GM120093
6 · The paper itself

Abstract

Population genomic data can be used to infer historical effective population sizes (Ne), which help study the impact of past climate changes on biodiversity. Previous genome sequencing of one individual of the common bottlenose dolphin Tursiops truncatus revealed an unusual, sharp rise in Ne during the last glacial, raising questions about the reliability, generality, underlying cause, and biological implication of this finding. Here we first verify this result by additional sampling of T. truncatus. We then sequence and analyze the genomes of its close relative, the Indo-Pacific bottlenose dolphin T. aduncus. The two species exhibit contrasting demographic changes in the last glacial, likely through actual changes in population size and/or alterations in the level of gene flow among populations. Our findings suggest that even closely related species can have drastically different responses to climatic changes, making predicting the fate of individual species in the ongoing global warming a serious challenge.

Indexed as

DolphinsAnimal DistributionAnimalsGenomicsPopulation Density

Identifiers

PMID29846663
PMCPMC6063294

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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.