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Transcription

Transcription

Overview
Transcription is the process of synthesizing RNA from a DNA sequence by RNA polymerase. It is the first step in producing a protein from a gene sequence. Additionally, many other proteins and regulatory sequences are involved in the proper synthesis of messenger RNA (mRNA). Regulation of transcription is responsible for the differentiation of all the different types of cells and often for the proper cellular response to environmental signals.
Transcription Can Produce Different Kinds...

Light Acquisition

Light Acquisition

In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.

Fruit Development, Structure, and Function

Fruit Development, Structure, and Function

Fruits form from a mature flower ovary. As seeds develop from the ovules contained within, the ovary wall undergoes a series of complex changes to form fruit. In some fruits, such as soybeans, the ovary wall dries; in other fruits, such as grapes, it remains fleshy. In some cases, organs other than the ovary contribute to fruit formation; such fruits are called accessory fruits.

Evolutionary Relationships through Genome Comparisons

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...

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Laser-assisted Microdissection (LAM) as a Tool for Transcriptional Profiling of Individual Cell Types

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Interspecies predictions of growth traits from quantitative transcriptome data acquired during fruit development.

Chloé Beaumont¹, Sylvain Prigent^1,2, Kentaro Mori¹

¹Univ. Bordeaux, INRAE, Biologie du Fruit et Pathologie, UMR 1332, 33882 Villenave d'Ornon, France.

Journal of Experimental Botany

|March 18, 2025

Summary

Machine learning accurately predicts fruit growth traits using multi-species transcriptomes. Gene expression data, particularly for metabolic processes, effectively forecasts relative growth rate (RGR) and other development factors.

Keywords:

Fruit development machine learning predictions multispecies orthology time series transcriptome

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Area of Science:

Systems biology
Genomics
Plant science

Background:

Linking genotype to phenotype is a key biological challenge.
Machine learning is increasingly vital in systems biology for understanding complex traits.
Fruit development, including relative growth rate (RGR), is influenced by gene regulation, metabolism, and environmental factors.

Purpose of the Study:

To predict fruit growth traits using multispecies transcriptomic data.
To identify gene expression patterns associated with fruit development mechanisms.
To evaluate the efficacy of generalized linear models (GLMs) in predicting phenotypic traits.

Main Methods:

Multispecies transcriptomic analysis of nine fruit types.
Comparative transcriptomic analysis using multivariate methods.
Prediction of growth traits (RGR, developmental progress, fruit weight, protein content) using GLMs.
Identification of key gene ontology (GO) terms and orthogroups.

Main Results:

Transcriptome profiles showed similar patterns across species.
Metabolic process genes, especially those related to cell wall carbohydrates and proteins, were most predictive of growth.
Incorporating a time lag improved RGR prediction, highlighting the role of protein synthesis.
GLMs effectively predicted growth traits based on multispecies transcriptomes.

Conclusions:

Gene expression, particularly metabolic pathways, can accurately predict fruit growth traits.
Multispecies transcriptomic data combined with machine learning offers a powerful approach to understanding plant development.
Considering temporal dynamics, like protein production lag, enhances predictive accuracy for phenotypic traits.