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Differentiated transcriptional signatures in the maize landraces of Chiapas, Mexico

Overview of attention for article published in BMC Genomics, September 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (54th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Mentioned by

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5 tweeters

Citations

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3 Dimensions

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32 Mendeley
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Title
Differentiated transcriptional signatures in the maize landraces of Chiapas, Mexico
Published in
BMC Genomics, September 2017
DOI 10.1186/s12864-017-4005-y
Pubmed ID
Authors

Matthew A. Kost, Hugo R. Perales, Saranga Wijeratne, Asela J. Wijeratne, Eric Stockinger, Kristin L. Mercer

Abstract

Landrace farmers are the keepers of crops locally adapted to the environments where they are cultivated. Patterns of diversity across the genome can provide signals of past evolution in the face of abiotic and biotic change. Understanding this rich genetic resource is imperative especially since diversity can provide agricultural security as climate continues to shift. Here we employ RNA sequencing (RNA-seq) to understand the role that conditions that vary across a landscape may have played in shaping genetic diversity in the maize landraces of Chiapas, Mexico. We collected landraces from three distinct elevational zones and planted them in a midland common garden. Early season leaf tissue was collected for RNA-seq and we performed weighted gene co-expression network analysis (WGCNA). We then used association analysis between landrace co-expression module expression values and environmental parameters of landrace origin to elucidate genes and gene networks potentially shaped by environmental factors along our study gradient. Elevation of landrace origin affected the transcriptome profiles. Two co-expression modules were highly correlated with temperature parameters of landrace origin and queries into their 'hub' genes suggested that temperature may have led to differentiation among landraces in hormone biosynthesis/signaling and abiotic and biotic stress responses. We identified several 'hub' transcription factors and kinases as candidates for the regulation of these responses. These findings indicate that natural selection may influence the transcriptomes of crop landraces along an elevational gradient in a major diversity center, and provide a foundation for exploring the genetic basis of local adaptation. While we cannot rule out the role of neutral evolutionary forces in the patterns we have identified, combining whole transcriptome sequencing technologies, established bioinformatics techniques, and common garden experimentation can powerfully elucidate structure of adaptive diversity across a varied landscape. Ultimately, gaining such understanding can facilitate the conservation and strategic utilization of crop genetic diversity in a time of climate change.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 28%
Researcher 5 16%
Student > Master 4 13%
Student > Doctoral Student 3 9%
Student > Bachelor 2 6%
Other 6 19%
Unknown 3 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 59%
Biochemistry, Genetics and Molecular Biology 4 13%
Social Sciences 2 6%
Computer Science 1 3%
Psychology 1 3%
Other 3 9%
Unknown 2 6%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 April 2018.
All research outputs
#6,960,980
of 12,860,000 outputs
Outputs from BMC Genomics
#3,483
of 7,557 outputs
Outputs of similar age
#114,947
of 265,666 outputs
Outputs of similar age from BMC Genomics
#7
of 18 outputs
Altmetric has tracked 12,860,000 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,557 research outputs from this source. They receive a mean Attention Score of 4.3. This one has gotten more attention than average, scoring higher than 50% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 265,666 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.