Differences in the Growth of Seedlings and the Selection of Fast-Growing Species in the Gleditsia Genus

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Abstract

The Gleditsia genus has various uses, including those for medicinal, edible, chemical, timber, and ornamental purposes, and the genus is widely distributed in China. However, there is still a lack of understanding about the phenotypic and growth differences seen among species within the Gleditsia genus. In this study, we compared and analyzed the various species of Gleditsia seedlings in terms of their genotypes, chromosome numbers, physiological growth, photosynthesis, hormone content, and gene expression. The results showed that the genome size of the Gleditsia genus ranges from 686.08 M to 1034.24 M and that all Gleditsia species are diploid. Among the species studied, G. fera can be divided into fast-growing genotype, exhibited several advantages in terms of leaf type and photosynthetic capacity, high levels of GA3, and fast stem growth, making it a species with the potential for promotion and application. G. delavayi exhibited high levels of auxin and cytokinin and strong photosynthetic capacity, with rapid growth in terms of plant height. G. microphylla had the lowest levels of IAA, IBA, and NAA in the apical, and showed slow growth in terms of plant height. Weighted correlation network analysis (WGCNA) identified the hub genes associated with traits. This study lays a material and theoretical foundation for the development of new resources for Gleditsia breeding and rootstock selection and provides a basis for the mechanism of rootstock–scion interaction.

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Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

Michael Love, Wolfgang Huber, Simon Anders (2014)

In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.

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Fast gapped-read alignment with Bowtie 2.

Ben Langmead, Steven L Salzberg (2022)

As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.