The advancement of next-generation sequencing (NGS) technologies has been revolutionary for the field of evolutionary biology. This technology has led to an abundance of available genomes and transcriptomes for researchers to mine. Specifically, researchers can mine for various types of molecular markers that are vital for phylogenetic, evolutionary, and ecological studies. Numerous tools have been developed to extract these molecular markers from NGS data. However, due to an insufficient number of well-annotated reference genomes for non-model organisms, it remains challenging to obtain these markers accurately and efficiently. Here, we present GeneMiner, an improved and expanded version of our previous tool, Easy353. GeneMiner combines the reference-guided de Bruijn graph assembly with seed self-discovery and greedy extension. Additionally, it includes a verification step using a parameter-bootstrap method to reduce the pitfalls associated with using a relatively distant reference. Our results using both experimental and simulation data showed GeneMiner can accurately acquires phylogenetic molecular markers for plants using transcriptomic, genomic, and other NGS data. GeneMiner is designed to be user-friendly, fast, and memory efficient. Further, it is compatible with Linux, Windows, and macOS. All source codes are publicly available on GitHub for easy accessibility and transparency (https://github.com/yyscu/GeneMiner).

Although plastid genome (plastome) structure is highly conserved across most seed plants, investigations during the past two decades have revealed several disparately related lineages that have experienced substantial rearrangements. Most plastomes have two inverted repeat regions and two single-copy regions with few dispersed repeats. However, the plastomes of some taxa do harbor long repeat sequences (>300 bp). These long repeats make it difficult to assemble complete plastomes using short read data, leading to misassemblies and consensus sequences that have spurious rearrangements. Long read sequencing can potentially overcome these challenges. However, there is no consensus as to the most effective method for accurately assembling plastomes using long read data. Here, we generated a pipeline, plastid Genome Assembly Using Long-read data (ptGAUL) to address the problem of assembling of plastomes using long read data from Oxford Nanopore Technologies (ONT) or Pacific Biosciences (Pacbio) platforms. We demonstrated the efficacy of the ptGAUL pipeline using 16 published long read datasets. We showed that ptGAUL produces accurate and unbiased assemblies. Additionally, we applied ptGAUL to assemble four Juncus (Juncaceae) plastomes using ONT long reads. Our results revealed many long repeats and rearrangements in Juncus plastomes compared with basal lineages of Poales.