Biology subjects

Tameshige, T.

Publications and source records attributed to Tameshige, T..

4 recordsLinked to original sources

bioRxiv2024

Modeling of transcriptomic variation among subgenomes in 25 accessions of common wheat reveals cis- and trans-regulation architectures

Common wheat is an allohexaploid plant, thus making it difficult to obtain homoeolog-distinguished transcriptome data. Lasy-Seq, a type of 3 RNA-seq, is efficient for obtaining homoeolog-distinguished transcriptomes and can thus overcome this measurement difficulty. This study obtained transcriptome data from the seedlings, second leaves, and root tips of 25 lines from mainly eastern transmitted area using Lasy-Seq. Roots and seedlings exhibited similar transcriptome profiles; however, they were different from those of the leaves. We determined the effects of subgenomes, lines and their interactions with leaves, roots, and seedlings on the expression levels of each homoeolog triad. Of the 19,805 homoeolog triads, 50.9-55.4%, 24.2-29.5%, and 7.7-9.0% showed significant effects on their expression levels from subgenome, line, and interaction, respectively. 51-55% and 24-30% have genetic variation in the cis- and trans-regulation. Hierarchical clustering and co-trans regulation network analysis of homoeolog triads revealed that the patterns of expression polymorphisms among the lines were shared in different genes. The triads in which the statistical model detected as line effects imply that expression variation between lines is caused by changes in a smaller number of common trans-factors. We assigned gene ontology (GO) terms of the Arabidopsis orthologs to wheat homoeolog triads via reciprocal BLAST between common wheat and Arabidopsis, thus improving the percentage of gene-assigned GO terms to all analyzed GO terms from 19.1% to 90.6%. GO term enrichment analysis revealed that GO terms related to each tissue type function were enriched in genes expressed in the leaves and roots. Our information provides fundamental knowledge for the future breeding of plants possessing complex gene regulatory networks such as common wheat.

plant biology↗

bioRxiv2022

PlantServation: time-series phenotyping using machine learning revealed seasonal pigment fluctuation in diploid and polyploid Arabidopsis

Long-term field monitoring of leaf pigment content is informative for understanding plant responses to environments distinct from regulated chambers, but is impractical by conventional destructive measurements. We developed PlantServation, a method incorporating robust image-acquisition hardware and deep learning-based software to analyze field images, where the plant shape, color, and background vary over months. We estimated the anthocyanin contents of small individuals of four Arabidopsis species using color information and verified the results experimentally. We obtained >4 million plant images over three field seasons to study anthocyanin fluctuations. We found significant effects of past radiation, coldness, and precipitation on the anthocyanin content in the field. The synthetic allopolyploid A. kamchatica recapitulated the fluctuations of natural polyploids by integrating diploid responses. The data support a long-standing hypothesis stating that allopolyploids can inherit and combine the traits of progenitors. PlantServation pipeline facilitates the study of plant responses to complex environments termed "in natura."

plant biology↗

bioRxiv2021

The Boundary-Expressed EPIDERMAL PATTERNING FACTOR-LIKE2 Gene Encoding a Signaling Peptide Promotes Cotyledon Growth during Arabidopsis thaliana Embryogenesis

The shoot organ boundaries have important roles in plant growth and morphogenesis. It has been reported that a gene encoding a cysteine-rich secreted peptide of the EPIDERMAL PATTERNING FACTOR-LIKE (EPFL) family, EPFL2, is expressed in the boundary domain between the two cotyledon primordia of Arabidopsis thaliana embryo. However, its developmental functions remain unknown. This study aimed to analyze the role of EPFL2 during embryogenesis. We found that cotyledon growth was reduced in its loss-of-function mutants, and this phenotype was associated with the reduction of auxin response peaks at the tips of the primordia. The reduced cotyledon size of the mutant embryo recovered in germinating seedlings, indicating the presence of a factor that acted redundantly with EPFL2 to promote cotyledon growth in late embryogenesis. Our analysis indicates that the boundary domain between the cotyledon primordia acts as a signaling center that organizes auxin response peaks and promotes cotyledon growth.

plant biology↗

bioRxiv2018

Homeolog expression quantification methods for allopolyploids

Genome duplication with hybridization, or allopolyploidization, occurs in animals, fungi, and plants, and is especially common in crop plants. There is increasing interest in the study of allopolyploids due to advances in polyploid genome assembly, however the high level of sequence similarity in duplicated gene copies (homeologs) pose many challenges. Here we compared standard RNA-seq expression quantification approaches used currently for diploid species against subgenome-classification approaches which maps reads to each subgenome separately. We examined mapping error using our previous and new RNA-seq data in which a subgenome is experimentally added (synthetic allotetraploid Arabidopsis kamchatica) or reduced (allohexaploid wheat Triticum aestivum versus extracted allotetraploid) as ground truth. The error rates in the two species were very similar. The standard approaches showed higher error rates (> 10% using pseudo-alignment with Kallisto) while subgenome-classification approaches showed much lower error rates (< 1% using EAGLE-RC, < 2% using HomeoRoq). Although downstream analysis may partly mitigate mapping errors, the difference in methods was substantial in hexaploid wheat, where Kallisto appeared to have systematic differences relative to other methods. Only approximately half of the differentially expressed homeologs detected using Kallisto overlapped with those by any other method. In general, disagreement in low expression genes was responsible for most of the discordance between methods, which is consistent with known biases in Kallisto. We also observed that there exist uncertainties in genome sequences and annotation which can affect each method differently. Overall, subgenome-classification approaches tend to perform better than standard approaches with EAGLE-RC having the highest precision.

bioinformatics↗