Meta-Analysis Reveals Challenges and Gaps for Genome-to-Phenome Research Underpinning Plant Drought Response

Severe drought conditions and extreme weather events are increasing worldwide with climate change, threatening the persistence of native plant communities and ecosystems. Many studies have investigated the genomic basis of plant responses to drought. However, the extent of this research throughout the plant kingdom is unclear, particularly among species critical for the sustainability of natural ecosystems. This study aimed to broaden our understanding of genome-to-phenome (G2P) connections in drought-stressed plants and identify focal taxa for future research. Bioinformatics pipelines were developed to mine and link information from databases and abstracts from 7730 publications. This approach identified 1634 genes involved in drought responses among 497 plant taxa. Most (83.30%) of these species have been classified for human use, and most G2P interactions have been described within model organisms or crop species. Our analysis identifies several gaps in G2P research literature and database connectivity, with 21% of abstracts being linked to gene and taxonomy data in NCBI. Abstract text mining was more successful at identifying potential G2P pathways, with 34% of abstracts containing gene, taxa, and phenotype information. Expanding G2P studies to include non-model plants, especially those that are adapted to drought stress, will help advance our understanding of drought responsive G2P pathways

Identification of differentially methylated CpG Sites in fibroblasts from Keloid Scars

As a part of an abnormal healing process of dermal injuries and irritation, keloid scars arise on the skin as benign fibroproliferative tumors. Although the etiology of keloid scarring remains unsettled, considerable recent evidence suggested that keloidogenesis may be driven by epigenetic changes, particularly, DNA methylation. Therefore, genome-wide scanning of methylated cytosine-phosphoguanine (CpG) sites in extracted DNA from 12 keloid scar fibroblasts (KF) and 12 control skin fibroblasts (CF) (six normal skin fibroblasts and six normotrophic fibroblasts) was conducted using the Illumina Human Methylation 450K BeadChip in two replicates for each sample. Comparing KF and CF used a Linear Models for Microarray Data (Limma) model revealed 100,000 differentially methylated (DM) CpG sites, 20,695 of which were found to be hypomethylated and 79,305 were hypermethylated. The top DM CpG sites were associated with TNKS2, FAM45B, LOC723972, GAS7, RHBDD2 and CAMKK1. Subsequently, the most functionally enriched genes with the top 100 DM CpG sites were significantly (p ≤ 0.05) associated with SH2 domain binding, regulation of transcription, DNA-templated, nucleus, positive regulation of protein targeting to mitochondrion, nucleoplasm, Swr1 complex, histone exchange, and cellular response to organic substance. In addition, NLK, CAMKK1, LPAR2, CASP1, and NHS showed to be the most common regulators in the signaling network analysis. Taken together, these findings shed light on the methylation status of keloids that could be implicated in the underlying mechanism of keloid scars formation and remission

Carbon cycle uncertainty in the Alaskan Arctic

Climate change is leading to a disproportionately large warming in the high northern latitudes, but the magnitude and sign of the future carbon balance of the Arctic are highly uncertain. Using 40 terrestrial biosphere models for the Alaskan Arctic from four recent model intercomparison projects – NACP (North American Carbon Program) site and regional syntheses, TRENDY (Trends in net land atmosphere carbon exchanges), and WETCHIMP (Wetland and Wetland CH4 Inter-comparison of Models Project) – we provide a baseline of terrestrial carbon cycle uncertainty, defined as the multi-model standard deviation (o) for each quantity that follows. Mean annual absolute uncertainty was largest for soil carbon (14.0±9.2 kgCm−2), then gross primary production (GPP) (0.22±0.50 kgCm−2 yr−1), ecosystem respiration (Re) (0.23±0.38 kgCm−2 yr−1), net primary production (NPP) (0.14±0.33 kgCm−2 yr−1), autotrophic respiration (Ra) (0.09±0.20 kgCm−2 yr−1), heterotrophic respiration (Rh) (0.14±0.20 kgCm−2 yr−1), net ecosystem exchange (NEE) (−0.01±0.19 kgCm−2 yr−1), and CH4 flux (2.52±4.02 g CH4 m−2 yr−1). There were no consistent spatial patterns in the larger Alaskan Arctic and boreal regional carbon stocks and fluxes, with some models showing NEE for Alaska as a strong carbon sink, others as a strong carbon source, while still others as carbon neutral. Finally, AmeriFlux data are used at two sites in the Alaskan Arctic to evaluate the regional patterns; observed seasonal NEE was captured within multi-model uncertainty. This assessment of carbon cycle uncertainties may be used as a baseline for the improvement of experimental and modeling activities, as well as a reference for future trajectories in carbon cycling with climate change in the Alaskan Arctic and larger boreal region

Mapping trabecular disconnection "hotspots" in aged human spine and hip

Trabecular bone disconnection is an independent factor in age-related skeletal failure where real termini (ReTm; rare in youth) may cause weakness disproportionate to tissue loss, yet their structural contribution at vulnerable locations remains uncertain. ReTm (previously recorded at the iliac crest) were mapped in "normal" aged vertebral bodies (T11-L5 autopsy; 20 females, 10 males) and corresponding proximal femora (autopsy; 10 females). Results were compared with biomechanically failed femora from orthopaedic subjects aged >. 58. yr (osteoporosis OP, 10 females; osteoarthritis OA, 10 females). A novel direct 2D/3D histological method was applied to large, thick (300. μm) slices superficially silver-stained to separate ReTm (unstained) from apparent termini (planar artefacts, brown). Light microscope field co-ordinates enabled ReTm mapping and statistical testing relative to i) sex, ii) tissue sector and iii) slicing plane. In men ReTm populations were small and random while in women they were large and sector-specific. In vertebrae they clustered anterior/superior being rare posterior/inferior; in the femoral head they concentrated distal/superior and also near the fovea, being fewer distal/inferior. A distribution polarity was evident with 100% more ReTm observed transversely (i.e., on tensile-related cross struts) than longitudinally (i.e., on compression-related vertical struts). Their numbers rose in OP (BV/TV. . 14%), remaining polarised and sector-specific in OP only. Comparative experimentation by marrow elution of an OP animal model demonstrated "floating segments" as a possible outcome. Conclusions were supported statistically that trabecular disconnection "hotspots" at vulnerable locations are sex- and sector-specific, mainly transaxial, and subject to disease modulation

Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation

DNA methylation quantitative trait locus (mQTL) analyses on 32,851 participants identify genetic variants associated with DNA methylation at 420,509 sites in blood, resulting in a database of >270,000 independent mQTLs.Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype-phenotype map than previously anticipated.Molecular Epidemiolog