S100A4 mRNA-protein relationship uncovered by measurement noise reduction

Intrinsic biological fluctuation and/or measurement error can obscure the association of gene expression patterns between RNA and protein levels. Appropriate normalization of reverse-transcription quantitative PCR (RT-qPCR) data can reduce technical noise in transcript measurement, thus uncovering such relationships. The accuracy of gene expression measurement is often challenged in the context of cancer due to the genetic instability and “splicing weakness” involved. Here, we sequenced the poly(A) cancer transcriptome of canine osteosarcoma using mRNA-Seq. Expressed sequences were resolved at the level of two consecutive exons to enable the design of exon-border spanning RT-qPCR assays and ranked for stability based on the coefficient of variation (CV). Using the same template type for RT-qPCR validation, i.e. poly(A) RNA, avoided skewing of stability assessment by circular RNAs (circRNAs) and/or rRNA deregulation. The strength of the relationship between mRNA expression of the tumour marker S100A4 and its proportion score of quantitative immunohistochemistry (qIHC) was introduced as an experimental readout to fine-tune the normalization choice. Together with the essential logit transformation of qIHC scores, this approach reduced the noise of measurement as demonstrated by uncovering a highly significant, strong association between mRNA and protein expressions of S100A4 (Spearman’s coefficient ρ = 0.72 (p = 0.006)).publishedVersio

The \u3cem\u3eChlamydomonas\u3c/em\u3e Genome Reveals the Evolution of Key Animal and Plant Functions

Chlamydomonas reinhardtii is a unicellular green alga whose lineage diverged from land plants over 1 billion years ago. It is a model system for studying chloroplast-based photosynthesis, as well as the structure, assembly, and function of eukaryotic flagella (cilia), which were inherited from the common ancestor of plants and animals, but lost in land plants. We sequenced the ∼120-megabase nuclear genome of Chlamydomonas and performed comparative phylogenomic analyses, identifying genes encoding uncharacterized proteins that are likely associated with the function and biogenesis of chloroplasts or eukaryotic flagella. Analyses of the Chlamydomonas genome advance our understanding of the ancestral eukaryotic cell, reveal previously unknown genes associated with photosynthetic and flagellar functions, and establish links between ciliopathy and the composition and function of flagella

Characteristics of Early-Onset vs Late-Onset Colorectal Cancer: A Review.

The incidence of early-onset colorectal cancer (younger than 50 years) is rising globally, the reasons for which are unclear. It appears to represent a unique disease process with different clinical, pathological, and molecular characteristics compared with late-onset colorectal cancer. Data on oncological outcomes are limited, and sensitivity to conventional neoadjuvant and adjuvant therapy regimens appear to be unknown. The purpose of this review is to summarize the available literature on early-onset colorectal cancer. Within the next decade, it is estimated that 1 in 10 colon cancers and 1 in 4 rectal cancers will be diagnosed in adults younger than 50 years. Potential risk factors include a Westernized diet, obesity, antibiotic usage, and alterations in the gut microbiome. Although genetic predisposition plays a role, most cases are sporadic. The full spectrum of germline and somatic sequence variations implicated remains unknown. Younger patients typically present with descending colonic or rectal cancer, advanced disease stage, and unfavorable histopathological features. Despite being more likely to receive neoadjuvant and adjuvant therapy, patients with early-onset disease demonstrate comparable oncological outcomes with their older counterparts. The clinicopathological features, underlying molecular profiles, and drivers of early-onset colorectal cancer differ from those of late-onset disease. Standardized, age-specific preventive, screening, diagnostic, and therapeutic strategies are required to optimize outcomes

Meta-analysis of genome-wide association studies discovers multiple loci for chronic lymphocytic leukemia.

Chronic lymphocytic leukemia (CLL) is a common lymphoid malignancy with strong heritability. To further understand the genetic susceptibility for CLL and identify common loci associated with risk, we conducted a meta-analysis of four genome-wide association studies (GWAS) composed of 3,100 cases and 7,667 controls with follow-up replication in 1,958 cases and 5,530 controls. Here we report three new loci at 3p24.1 (rs9880772, EOMES, P=2.55 × 10(-11)), 6p25.2 (rs73718779, SERPINB6, P=1.97 × 10(-8)) and 3q28 (rs9815073, LPP, P=3.62 × 10(-8)), as well as a new independent SNP at the known 2q13 locus (rs9308731, BCL2L11, P=1.00 × 10(-11)) in the combined analysis. We find suggestive evidence (P<5 × 10(-7)) for two additional new loci at 4q24 (rs10028805, BANK1, P=7.19 × 10(-8)) and 3p22.2 (rs1274963, CSRNP1, P=2.12 × 10(-7)). Pathway analyses of new and known CLL loci consistently show a strong role for apoptosis, providing further evidence for the importance of this biological pathway in CLL susceptibility

Ion homeostasis in the Chloroplast

peer reviewedThe chloroplast is an organelle of high demand for macro- and micro-nutrient ions, which are required for the maintenance of the photosynthetic process. To avoid deficiency while preventing excess, homeostasis mechanisms must be tightly regulated. Here, we describe the needs for nutrient ions in the chloroplast and briefly highlight their functions in the chloroplastidial metabolism. We further discuss the impact of nutrient deficiency on chloroplasts and the acclimation mechanisms that evolved to preserve the photosynthetic apparatus. We finally present what is known about import and export mechanisms for these ions. Whenever possible, a comparison between cyanobacteria, algae and plants is provided to add an evolutionary perspective to the description of ion homeostasis mechanisms in photosynthesis

S100A4 mRNA-protein relationship uncovered by measurement noise reduction

Intrinsic biological fluctuation and/or measurement error can obscure the association of gene expression patterns between RNA and protein levels. Appropriate normalization of reverse-transcription quantitative PCR (RT-qPCR) data can reduce technical noise in transcript measurement, thus uncovering such relationships. The accuracy of gene expression measurement is often challenged in the context of cancer due to the genetic instability and “splicing weakness” involved. Here, we sequenced the poly(A) cancer transcriptome of canine osteosarcoma using mRNA-Seq. Expressed sequences were resolved at the level of two consecutive exons to enable the design of exon-border spanning RT-qPCR assays and ranked for stability based on the coefficient of variation (CV). Using the same template type for RT-qPCR validation, i.e. poly(A) RNA, avoided skewing of stability assessment by circular RNAs (circRNAs) and/or rRNA deregulation. The strength of the relationship between mRNA expression of the tumour marker S100A4 and its proportion score of quantitative immunohistochemistry (qIHC) was introduced as an experimental readout to fine-tune the normalization choice. Together with the essential logit transformation of qIHC scores, this approach reduced the noise of measurement as demonstrated by uncovering a highly significant, strong association between mRNA and protein expressions of S100A4 (Spearman’s coefficient ρ = 0.72 (p = 0.006))