High-throughput single-cell analysis reveals progressive mitochondrial DNA mosaicism throughout life.

Heteroplasmic mitochondrial DNA (mtDNA) mutations are a major cause of inherited disease and contribute to common late-onset human disorders. The late onset and clinical progression of mtDNA-associated disease is thought to be due to changing heteroplasmy levels, but it is not known how and when this occurs. Performing high-throughput single-cell genotyping in two mouse models of human mtDNA disease, we saw unanticipated cell-to-cell differences in mtDNA heteroplasmy levels that emerged prenatally and progressively increased throughout life.

Cell lineage-specific mitochondrial resilience during mammalian organogenesis.

Mitochondrial activity differs markedly between organs, but it is not known how and when this arises. Here we show that cell lineage-specific expression profiles involving essential mitochondrial genes emerge at an early stage in mouse development, including tissue-specific isoforms present before organ formation. However, the nuclear transcriptional signatures were not independent of organelle function.

A role for BCL2L13 and autophagy in germline purifying selection of mtDNA.

Mammalian mitochondrial DNA (mtDNA) is inherited uniparentally through the female germline without undergoing recombination. This poses a major problem as deleterious mtDNA mutations must be eliminated to avoid a mutational meltdown over generations. At least two mechanisms that can decrease the mutation load during maternal transmission are operational: a stochastic bottleneck for mtDNA transmission from mother to child, and a directed purifying selection against transmission of deleterious mtDNA mutations.

Robust gene coexpression networks using signed distance correlation.

Motivation: Even within well studied organisms, many genes lack useful functional annotations. One way to generate such functional information is to infer biological relationships between genes/proteins, using a network of gene coexpression data that includes functional annotations. However, the lack of trustworthy functional annotations can impede the validation of such networks.

COGENT: evaluating the consistency of gene co-expression networks.

Summary: Gene co-expression networks can be constructed in multiple different ways, both in the use of different measures of co-expression, and in the thresholds applied to the calculated co-expression values, from any given dataset. It is often not clear which co-expression network construction method should be preferred. COGENT provides a set of tools designed to aid the choice of network construction method without the need for any external validation data.

Measuring rank robustness in scored protein interaction networks.

Background: Protein interaction databases often provide confidence scores for each recorded interaction based on the available experimental evidence. Protein interaction networks (PINs) are then built by thresholding on these scores, so that only interactions of sufficiently high quality are included. These networks are used to identify biologically relevant motifs or nodes using metrics such as degree or betweenness centrality.