Abstract
Despite the significant progress that has been made in the genome sequencing of Beauveria species, mitochondrial genome (mitogenome) used to examine genetic diversity within fungal populations. Complete mitogenomes of Beauveria species can be easily sequenced and assembled using various sequencing techniques. However, since mitogenome annotations are mainly derived from similar species comparison and software prediction, and are not supported by RNA-seq transcripts data, it leads to problems with the accuracy of mitochondrial annotations and the inability to understand RNA processing. In this study, we assembled and annotated the mitogenome of eight Beauveria strains using Illumina DNA and RNA sequencing data. The circular mitogenome of eight Beauveria strains ranged from 26,850 bp (B. caledonica strain ATCC 64970) to 35,999 bp (B. brongniartii strain GYU-BMZ03), with the intronic insertions accounting for most of the size variation, thus contributing to a total mitochondrial genome (mitogenome) size of 7.01% and 28.95%, respectively. Intron number variations were not directly related to the evolutionary relationship distance. Besides ribosomal protein S3 (rps3), most introns are lost too quickly and lack the stability of protein-coding genes. The short RNA-seq reads from next-generation sequencing can improve the mitochondrial annotation accuracy and help study polycistronic transcripts and RNA processing. The transcription initiation sites may be located in the control region. Most introns do not serve as taxonomic markers and also lack open reading frames (ORFs). We assumed that the poly A tail was added to the polycistronic transcript before splicing and one polycistronic transcript (trnM ((1))-trnL ((1))-trnA-trnF-trnK-trnL ((2))-trnQ-trnH-trnM ((2))-nad2-nad3-atp9-cox2-trnR ((1))-nad4L-nad5-cob-trnC-cox1-trnR ((2))-nad1-nad4-atp8-atp6-rns-trnY-trnD-trnS-trnN-cox3-trnG-nad6-trnV-trnI-trnS-trnW-trnP-rnl(rps3)-trnT-trnE-trnM ((3))) was first processed from the mitogenome and was subsequently processed into smaller mono-, di-, or tricistronic RNAs.