Analysis of oxidase activity and transcriptomic changes related to cutting propagation of hybrid larch

Abstract

Hybrid larch is the main timber and afforestation tree species in Northeast China. To solve the problem of rooting difficulties in larch cutting propagation, enzyme activity determination and transcriptome sequencing were carried out on the rooting tissues at five timepoints after cutting. peroxidase (POD), indole acetic acid oxidase (IAAO) and polyphenol oxidase (PPO) play important roles in the larch rooting process after cutting. A total of 101.20 Gb of clean data was obtained by transcriptome sequencing, and 43,246 unigenes were obtained after further screening and assembly. According to GO analysis and KEGG enrichment analysis, we think that plant hormones play an important role in the rooting process of larch stem cuttings. in the plant hormone signal transduction pathway, a larch gene c141104.graph_c0 that is homologous to the Arabidopsis AUX1 was found to be significantly up-regulated. We suggest that AUX1 may promote IAA transport in larch, thus affecting adventitious root development. According to the results of POD, PPO IAAO indexes and GO analysis, we think s1 and s2 periods may be important periods in the rooting process of larch stem cuttings, so we built a gene regulatory network, a total of 14genes, including LBD, NAC, AP2/ERF, bHLH and etc., may be important in different stages of cutting propagation. As the rooting rate after cutting inhibits the development of larch clone propagation, identifying the genes that regulate rooting could help us to preliminarily understand the molecular mechanism of adventitious root formation and select a better treatment method for cutting propagation.

Combinatorial prediction of therapeutic perturbations using causally-inspired neural networks

“…GENIE3, introduced in 2010, won the Dialogue for Reverse Engineering Assessments and Methods 4 (DREAM4) challenge [70], which evaluates the success of GRN inference algorithms on benchmarks of simulated data. GENIE3 was introduced in the open source software for bioinformatics Bioconductor [71] in 2017 and is still used as a gold-standard for GRN generation [72][73][74][75]. It is a model based on an ensemble of regression trees and requires as input a matrix of gene expression levels under various conditions.…”