Genome-Wide Identification, Classification, and Expression Analysis of the HD-Zip Transcription Factor Family in Apple (Malus domestica Borkh.)

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Abstract

Homeodomain-leucine zipper (HD-Zip) family genes are considered to play an important role in plant growth and stress tolerance. However, a genome-wide analysis of HD-Zip genes in apples (Malus domestica Borkh.) has not been performed. We detected 48 MdHDZ genes in the apple genome, and categorized them into three subfamilies on the basis of phylogenetic analysis. The chromosomal locations, gene/protein structures, and physiological and biochemical properties of these genes were analyzed. Synteny analysis revealed that segmental duplications were key in the expansion of the apple HD-Zip family. According to an analysis of cis-regulatory elements and tissue-specific expression patterns, MdHDZ genes may be widely involved in the regulation of apple growth and tolerance to environmental stresses. Furthermore, the transcript levels of apple HD-Zip I and II genes were up-regulated in response to fungal treatments. Expression of apple HD-Zip Ⅲ genes was enhanced during adventitious bud regeneration. This suggested possible roles of these genes in regulating the apple response to fungal infection, as well as adventitious bud regeneration. The current results may help us to better understand the evolution and function of apple HD-ZIP genes, and thus facilitate further research on plant resistance to fungal infection and in vitro regeneration.

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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.

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Sudhir Kumar, Glen Stecher, Koichiro Tamura (2016)

We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from www.megasoftware.net free of charge.

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HISAT: a fast spliced aligner with low memory requirements.

Daehwan Kim, Ben Langmead, Steven L Salzberg (2018)

HISAT (hierarchical indexing for spliced alignment of transcripts) is a highly efficient system for aligning reads from RNA sequencing experiments. HISAT uses an indexing scheme based on the Burrows-Wheeler transform and the Ferragina-Manzini (FM) index, employing two types of indexes for alignment: a whole-genome FM index to anchor each alignment and numerous local FM indexes for very rapid extensions of these alignments. HISAT's hierarchical index for the human genome contains 48,000 local FM indexes, each representing a genomic region of ∼64,000 bp. Tests on real and simulated data sets showed that HISAT is the fastest system currently available, with equal or better accuracy than any other method. Despite its large number of indexes, HISAT requires only 4.3 gigabytes of memory. HISAT supports genomes of any size, including those larger than 4 billion bases.