An original phylogenetic approach identified mitochondrial haplogroup T1a1 as inversely associated with breast cancer risk in BRCA2 mutation carriers

Introduction: Individuals carrying pathogenic mutations in the BRCA1 and BRCA2 genes have a high lifetime risk of breast cancer. BRCA1 and BRCA2 are involved in DNA double-strand break repair, DNA alterations that can be caused by exposure to reactive oxygen species, a main source of which are mitochondria. Mitochondrial genome variations affect electron transport chain efficiency and reactive oxygen species production. Individuals with different mitochondrial haplogroups differ in their metabolism and sensitivity to oxidative stress. Variability in mitochondrial genetic background can alter reactive oxygen species production, leading to cancer risk. In the present study, we tested the hypothesis that mitochondrial haplogroups modify breast cancer risk in BRCA1/2 mutation carriers. Methods: We genotyped 22,214 (11,421 affected, 10,793 unaffected) mutation carriers belonging to the Consortium of Investigators of Modifiers of BRCA1/2 for 129 mitochondrial polymorphisms using the iCOGS array. Haplogroup inference and association detection were performed using a phylogenetic approach. ALTree was applied to explore the reference mitochondrial evolutionary tree and detect subclades enriched in affected or unaffected individuals. Results: We discovered that subclade T1a1 was depleted in affected BRCA2 mutation carriers compared with the rest of clade T (hazard ratio (HR) = 0.55; 95% confidence interval (CI), 0.34 to 0.88; P = 0.01). Compared with the most frequent haplogroup in the general population (that is, H and T clades), the T1a1 haplogroup has a HR of 0.62 (95% CI, 0.40 to 0.95; P = 0.03). We also identified three potential susceptibility loci, including G13708A/rs28359178, which has demonstrated an inverse association with familial breast cancer risk. Conclusions: This study illustrates how original approaches such as the phylogeny-based method we used can empower classical molecular epidemiological studies aimed at identifying association or risk modification effects.Peer reviewe

Opportunities and challenges in phenotyping row crops using drone‐based RGB imaging

Abstract Developing the resilient crops of the future will require access to a broad set of tools. While advances in sequencing and marker technologies have facilitated marker‐trait associations and the ability to predict the phenotype of an individual from its genotypic information, other tools such as high‐throughput phenotyping are still in their infancy. Advances in sensors, aeronautics, and computing have enabled progress. Here, we review current platforms and sensors available for top‐down field phenotyping with a focus on unoccupied aerial vehicles (UAVs) and red, green, blue sensors. We also review the ability and effectiveness of extracting traits from images captured using combinations of these platforms and sensors. Improvements in trait standardization and extraction software are expected to increase the use of high‐throughput phenotyping in the coming years and further facilitate crop improvement

A Rare Population of CD24+ITGB4+Notchhi Cells Drives Tumor Propagation in NSCLC and Requires Notch3 for Self-Renewal

Sustained tumor progression has been attributed to a distinct population of tumor-propagating cells (TPCs). To identify TPCs relevant to lung cancer pathogenesis, we investigated functional heterogeneity in tumor cells isolated from Kras-driven mouse models of non-small-cell lung cancer (NSCLC). CD24(+)ITGB4(+)Notch(hi) cells are capable of propagating tumor growth in both a clonogenic and an orthotopic serial transplantation assay. While all four Notch receptors mark TPCs, Notch3 plays a nonredundant role in tumor cell propagation in two mouse models and in human NSCLC. The TPC population is enriched after chemotherapy, and the gene signature of mouse TPCs correlates with poor prognosis in human NSCLC. The role of Notch3 in tumor propagation may provide a therapeutic target for NSCLC

Mapping intact protein isoforms in discovery mode using top-down proteomics.

A full description of the human proteome relies on the challenging task of detecting mature and changing forms of protein molecules in the body. Large-scale proteome analysis has routinely involved digesting intact proteins followed by inferred protein identification using mass spectrometry. This 'bottom-up' process affords a high number of identifications (not always unique to a single gene). However, complications arise from incomplete or ambiguous characterization of alternative splice forms, diverse modifications (for example, acetylation and methylation) and endogenous protein cleavages, especially when combinations of these create complex patterns of intact protein isoforms and species. 'Top-down' interrogation of whole proteins can overcome these problems for individual proteins, but has not been achieved on a proteome scale owing to the lack of intact protein fractionation methods that are well integrated with tandem mass spectrometry. Here we show, using a new four-dimensional separation system, identification of 1,043 gene products from human cells that are dispersed into more than 3,000 protein species created by post-translational modification (PTM), RNA splicing and proteolysis. The overall system produced greater than 20-fold increases in both separation power and proteome coverage, enabling the identification of proteins up to 105 kDa and those with up to 11 transmembrane helices. Many previously undetected isoforms of endogenous human proteins were mapped, including changes in multiply modified species in response to accelerated cellular ageing (senescence) induced by DNA damage. Integrated with the latest version of the Swiss-Prot database, the data provide precise correlations to individual genes and proof-of-concept for large-scale interrogation of whole protein molecules. The technology promises to improve the link between proteomics data and complex phenotypes in basic biology and disease research