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Motivation As an important player in transcriptome regulation, microRNAs may effectively diffuse somatic mutation impacts to broad cellular processes and ultimately manifest disease and dictate prognosis. Previous studies that tried to correlate mutation with gene expression dysregulation neglected to adjust for the disparate multitudes of false positives associated with unequal sample sizes and uneven class balancing scenarios. Results To properly address this issue, we developed a statistical framework to rigorously assess the extent of mutation impact on microRNAs in relation to a permutation-based null distribution of a matching sample structure. Carrying out the framework in a pan-cancer study, we ascertained 9008 protein-coding genes with statistically significant mutation impacts on miRNAs. Of these, the collective miRNA expression for 83 genes showed significant prognostic power in nine cancer types. For example, in lower-grade glioma, 10 genes' mutations broadly impacted miRNAs, all of which showed prognostic value with the corresponding miRNA expression. Our framework was further validated with functional analysis and augmented with rich features including the ability to analyze miRNA isoforms; aggregative prognostic analysis; advanced annotations such as mutation type, regulator alteration, somatic motif, and disease association; and instructive visualization such as mutation OncoPrint, Ideogram, and interactive mRNA–miRNA network. Availability and implementation The data underlying this article are available in MutMix, at http://innovebioinfo.com/Database/TmiEx/MutMix.php. [ABSTRACT FROM AUTHOR]

Orchid gynostemium, the fused organ of the androecium and gynoecium, and ovule development are unique developmental processes. Two DROOPING LEAF / CRABS CLAW (DL / CRC) genes, PeDL1 and PeDL2, were identified from the Phalaenopsis orchid genome and functionally characterized. Phylogenetic analysis indicated that the most recent common ancestor of orchids contained the duplicated DL/CRC -like genes. Temporal and spatial expression analysis indicated that PeDL genes are specifically expressed in the gynostemium and at the early stages of ovule development. Both PeDL s could partially complement an Arabidopsis crc-1 mutant. Virus-induced gene silencing (VIGS) of PeDL1 and PeDL2 affected the number of protuberant ovule initials differentiated from the placenta. Transient overexpression of PeDL1 in Phalaenopsis orchids caused abnormal development of ovule and stigmatic cavity of gynostemium. PeDL1, but not PeDL2, could form a heterodimer with Phalaenopsis equestris CINCINNATA 8 (PeCIN8). Paralogous retention and subsequent divergence of the gene sequences of PeDL1 and PeDL2 in P. equestris might result in the differentiation of function and protein behaviors. These results reveal that the ancestral duplicated DL/CRC -like genes play important roles in orchid reproductive organ innovation. [ABSTRACT FROM AUTHOR]

Power/sample size (power) analysis estimates the likelihood of successfully finding the statistical significance in a data set. There has been a growing recognition of the importance of power analysis in the proper design of experiments. Power analysis is complex, yet necessary for the success of large studies. It is important to design a study that produces statistically accurate and reliable results. Power computation methods have been well established for both microarray-based gene expression studies and genotyping microarray-based genome-wide association studies. High-throughput sequencing (HTS) has greatly enhanced our ability to conduct biomedical studies at the highest possible resolution (per nucleotide). However, the complexity of power computations is much greater for sequencing data than for the simpler genotyping array data. Research on methods of power computations for HTS-based studies has been recently conducted but is not yet well known or widely used. In this article, we describe the power computation methods that are currently available for a range of HTS-based studies, including DNA sequencing, RNA-sequencing, microbiome sequencing and chromatin immunoprecipitation sequencing. Most importantly, we review the methods of power analysis for several types of sequencing data and guide the reader to the relevant methods for each data type. [ABSTRACT FROM AUTHOR]

Motivation: Exome capture kits have capture efficiencies that range from 40 to 60%. A significant amount of off-target reads are from the mitochondrial genome. These unintentionally sequenced mitochondrial reads provide unique opportunities to study the mitochondria genome.Results: MitoSeek is an open-source software tool that can reliably and easily extract mitochondrial genome information from exome and whole genome sequencing data. MitoSeek evaluates mitochondrial genome alignment quality, estimates relative mitochondrial copy numbers and detects heteroplasmy, somatic mutation and structural variants of the mitochondrial genome. MitoSeek can be set up to run in parallel or serial on large exome sequencing datasets.Availability: https://github.com/riverlee/MitoSeekContact: yan.guo@vanderbilt.eduSupplementary information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]