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A Comparison of transgenic and wild type soybean seeds: analysis of transcriptome profiles using RNA-Seq

Overview of attention for article published in BMC Biotechnology, October 2015
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Title
A Comparison of transgenic and wild type soybean seeds: analysis of transcriptome profiles using RNA-Seq
Published in
BMC Biotechnology, October 2015
DOI 10.1186/s12896-015-0207-z
Pubmed ID
Authors

Kevin C. Lambirth, Adam M. Whaley, Ivory C. Blakley, Jessica A. Schlueter, Kenneth L. Bost, Ann E. Loraine, Kenneth J. Piller

Abstract

Soybean (Glycine max) has been bred for thousands of years to produce seeds rich in protein for human and animal consumption, making them an appealing bioreactor for producing valuable recombinant proteins at high levels. However, the effects of expressing recombinant protein at high levels on bean physiology are not well understood. To address this, we investigated whether gene expression within transgenic soybean seed tissue is altered when large amounts of recombinant proteins are being produced and stored exclusively in the seeds. We used RNA-Seq to survey gene expression in three transgenic soybean lines expressing recombinant protein at levels representing up to 1.61 % of total protein in seed tissues. The three lines included: ST77, expressing human thyroglobulin protein (hTG), ST111, expressing human myelin basic protein (hMBP), and 764, expressing a mutant, nontoxic form of a staphylococcal subunit vaccine protein (mSEB). All lines selected for analysis were homozygous and contained a single copy of the transgene. Each transgenic soybean seed was screened for transgene presence and recombinant protein expression via PCR and western blotting.  Whole seed mRNA was extracted and cDNA libraries constructed for Illumina sequencing.  Following alignment to the soybean reference genome, differential gene expression analysis was conducted using edgeR and cufflinks.  Functional analysis of differentially expressed genes was carried out using the gene ontology analysis tool AgriGO. The transcriptomes of nine seeds from each transgenic line were sequenced and compared with wild type seeds. Native soybean gene expression was significantly altered in line 764 (mSEB) with more than 3000 genes being upregulated or downregulated. ST77 (hTG) and ST111 (hMBP) had significantly less differences with 52 and 307 differentially expressed genes respectively. Gene ontology enrichment analysis found that the upregulated genes in the 764 line were annotated with functions related to endopeptidase inhibitors and protein synthesis, but suppressed expression of genes annotated to the nuclear pore and to protein transport. No significant gene ontology terms were detected in ST77, and only a few genes involved in photosynthesis and thylakoid functions were downregulated in ST111. Despite these differences, transgenic plants and seeds appeared phenotypically similar to non-transgenic controls. There was no correlation between recombinant protein expression level and the quantity of differentially expressed genes detected. Measurable unscripted gene expression changes were detected in the seed transcriptomes of all three transgenic soybean lines analyzed, with line 764 being substantially altered. Differences detected at the transcript level may be due to T-DNA insert locations, random mutations following transformation or direct effects of the recombinant protein itself, or a combination of these. The physiological consequences of such changes remain unknown.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 2%
Unknown 47 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 29%
Student > Bachelor 7 15%
Researcher 7 15%
Student > Master 3 6%
Professor > Associate Professor 3 6%
Other 4 8%
Unknown 10 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 40%
Biochemistry, Genetics and Molecular Biology 14 29%
Computer Science 3 6%
Social Sciences 1 2%
Neuroscience 1 2%
Other 0 0%
Unknown 10 21%
Attention Score in Context

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 06 October 2015.
All research outputs
#14,239,245
of 22,829,683 outputs
Outputs from BMC Biotechnology
#626
of 935 outputs
Outputs of similar age
#142,183
of 274,923 outputs
Outputs of similar age from BMC Biotechnology
#16
of 24 outputs
Altmetric has tracked 22,829,683 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 935 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
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 274,923 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.