Biology subjects

Holtz, Y.

Publications and source records attributed to Holtz, Y..

5 recordsLinked to original sources

bioRxiv2020

Comparative analysis based on transcriptomics and metabolomics data reveal differences between emmer and durum wheat in response to nitrogen starvation

Mounting evidence indicates the key role of Nitrogen (N) on diverse processes in plant, including not only yield but also development and defense. Using a combined transcriptomics and metabolomics approach, we studied the response of seedlings to N starvation of two different tetraploid wheat genotypes from the two main domesticated subspecies, emmer (Triticum turgidum ssp. dicoccum) and durum wheat (Triticum turgidum ssp. durum). We found that durum wheat exhibits broader and stronger response in comparison to emmer as evidenced by the analysis of the differential expression pattern of both genes and metabolites and gene enrichment analysis. Emmer and durum wheat showed major differences in the responses to N starvation for transcription factor families. While emmer showed differential reduction in the levels of primary metabolites to N starvation, durum wheat exhibited increased levels of most metabolites, including GABA as an indicator of metabolic imbalance. The correlation-based networks including the differentially expressed genes and metabolites revealed tighter regulation of metabolism in durum wheat in comparison to emmer, as evidenced by the larger number of significant correlations. We also found that glutamate and GABA had highest values of centrality in the metabolic correlation network, suggesting their critical role in the genotype-specific response to N starvation of emmer and durum wheat, respectively. Moreover, this finding indicates that there might be contrasting strategies associated to GABA and Glutamate signaling modulating shoot vs root growth in the two different wheat subspecies.

plant biology↗

bioRxiv2019

Genome-wide association study identifies 143 loci associated with 25 hydroxyvitamin D concentration.

Vitamin D deficiency is a candidate risk factor for a range of adverse health outcomes. In a genome-wide association study of 25 hydroxyvitamin D (25OHD) concentration in 417,580 Europeans we identified 143 independent loci in 112 1-Mb regions providing new insights into the physiology of vitamin D and implicating genes involved in (a) lipid and lipoprotein metabolism, (b) dermal tissue properties, and (c) the sulphonation and glucuronidation of 25OHD. Mendelian randomization models found no robust evidence that 25OHD concentration had causal effects on candidate phenotypes (e.g. BMI, psychiatric disorders), but many phenotypes had (direct or indirect) causal effects on 25OHD concentration, clarifying the relationship between 25OHD status and health.

genetics↗

bioRxiv2019

Widespread associations between grey matter structure and the human phenome

The recent availability of large-scale neuroimaging cohorts (here the UK Biobank [UKB] and the Human Connectome Project [HCP]) facilitates deeper characterisation of the relationship between phenotypic and brain architecture variation in humans. We tested the association between 654,386 vertex-wise measures of cortical and subcortical morphology (from T1w and T2w MRI images) and behavioural, cognitive, psychiatric and lifestyle data. We found a significant association of grey-matter structure with 58 out of 167 UKB phenotypes spanning substance use, blood assay results, education or income level, diet, depression, being a twin as well as cognition domains (UKB discovery sample: N=9,888). Twenty-three of the 58 associations replicated (UKB replication sample: N=4,561; HCP, N=1,110). In addition, differences in body size (height, weight, BMI, waist and hip circumference, body fat percentage) could account for a substantial proportion of the association, providing possible insight into previous MRI case-control studies for psychiatric disorders where case status is associated with body mass index. Using the same linear mixed model, we showed that most of the associated characteristics (e.g. age, sex, body size, diabetes, being a twin, maternal smoking, body size) could be significantly predicted using all the brain measurements in out-of-sample prediction. Finally, we demonstrated other applications of our approach including a Region Of Interest (ROI) analysis that retain the vertex-wise complexity and ranking of the information contained across MRI processing options.\n\nHighlightsO_LIOur linear mixed model approach unifies association and prediction analyses for highly dimensional vertex-wise MRI data\nC_LIO_LIGrey-matter structure is associated with measures of substance use, blood assay results, education or income level, diet, depression, being a twin as well as cognition domains\nC_LIO_LIBody size (height, weight, BMI, waist and hip circumference) is an important source of covariation between the phenome and grey-matter structure\nC_LIO_LIGrey-matter scores quantify grey-matter based risk for the associated traits and allow to study phenotypes not collected\nC_LIO_LIThe most general cortical processing (\"fsaverage\" mesh with no smoothing) maximises the brain-morphometricity for all UKB phenotypes\nC_LI

neuroscience↗

bioRxiv2018

Genetic Consequences of Social Stratification in Great Britain

Human DNA varies across geographic regions, with most variation observed so far reflecting distant ancestry differences. Here, we investigate the geographic clustering of genetic variants that influence complex traits and disease risk in a sample of ~450,000 individuals from Great Britain. Out of 30 traits analyzed, 16 show significant geographic clustering at the genetic level after controlling for ancestry, likely reflecting recent migration driven by socio-economic status (SES). Alleles associated with educational attainment (EA) show most clustering, with EA-decreasing alleles clustering in lower SES areas such as coal mining areas. Individuals that leave coal mining areas carry more EA-increasing alleles on average than the rest of Great Britain. In addition, we leveraged the geographic clustering of complex trait variation to further disentangle regional differences in socio-economic and cultural outcomes through genome-wide association studies on publicly available regional measures, namely coal mining, religiousness, 1970/2015 general election outcomes, and Brexit referendum results.

genetics↗

bioRxiv2016

Evolutionary forces affecting synonymous variations in plant genomes

Base composition is highly variable among and within plant genomes, especially at third codon positions, ranging from GC-poor and homogeneous species to GC-rich and highly heterogeneous ones (particularly Monocots). Consequently, synonymous codon usage is biased in most species, even when base composition is relatively homogeneous. The causes of these variations are still under debate, with three main forces being possibly involved: mutational bias, selection and GC-biased gene conversion (gBGC). So far, both selection and gBGC have been detected in some species but how their relative strength varies among and within species remains unclear. Population genetics approaches allow to jointly estimating the intensity of selection, gBGC and mutational bias. We extended a recently developed method and applied it to a large population genomic datasets based on transcriptome sequencing of 11 angiosperm species spread across the phylogeny. We found that base composition is far from mutation-drift equilibrium in most genomes and that gBGC is a widespread and stronger process than selection. gBGC could strongly contribute to base composition variation among plant species, implying that it should be taken into account in plant genome analyses, especially for GC-rich ones.

evolutionary biology↗