Identification of De Novo Copy Number Variants Associated with Human Disorders of Sexual Development

Disorders of sexual development (DSD), ranging in severity from genital abnormalities to complete sex reversal, are among the most common human birth defects with incidence rates reaching almost 3%. Although causative alterations in key genes controlling gonad development have been identified, the majority of DSD cases remain unexplained. To improve the diagnosis, we screened 116 children born with idiopathic DSD using a clinically validated array-based comparative genomic hybridization platform. 8951 controls without urogenital defects were used to compare with our cohort of affected patients. Clinically relevant imbalances were found in 21.5% of the analyzed patients. Most anomalies (74.2%) evaded detection by the routinely ordered karyotype and were scattered across the genome in gene-enriched subtelomeric loci. Among these defects, confirmed de novo duplication and deletion events were noted on 1p36.33, 9p24.3 and 19q12-q13.11 for ambiguous genitalia, 10p14 and Xq28 for cryptorchidism and 12p13 and 16p11.2 for hypospadias. These variants were significantly associated with genitourinary defects (P = 6.08×10−12). The causality of defects observed in 5p15.3, 9p24.3, 22q12.1 and Xq28 was supported by the presence of overlapping chromosomal rearrangements in several unrelated patients. In addition to known gonad determining genes including SRY and DMRT1, novel candidate genes such as FGFR2, KANK1, ADCY2 and ZEB2 were encompassed. The identification of risk germline rearrangements for urogenital birth defects may impact diagnosis and genetic counseling and contribute to the elucidation of the molecular mechanisms underlying the pathogenesis of human sexual development

Changes in air quality in Mexico City, London and Delhi in response to various stages and levels of lockdowns and easing of restrictions during COVID-19 pandemic

The impacts of COVID-19 lockdown restrictions have provided a valuable global experiment into the extent of improvements in air quality possible with reductions in vehicle movements. Mexico City, London and Delhi all share the problem of air quality failing WHO guideline limits, each with unique situations and influencing factors. We determine, discuss and compare the air quality changes across these cities during the COVID-19, to understand how the findings may support future improvements in their air quality and associated health of citizens. We analysed ground-level PM10, PM2.5, NO2, O3 and CO changes in each city for the period 1st January to August 31, 2020 under different phases of lockdown, with respect to daily average concentrations over the same period for 2017 to 2019. We found major reductions in PM10, PM2.5, NO2 and CO across the three cities for the lockdown phases and increases in O3 in London and Mexico City but not Delhi. The differences were due to the O3 production criteria across the cities, for Delhi production depends on the VOC-limited photochemical regime. Levels of reductions were commensurate with the degree of lockdown. In Mexico City, the greatest reduction in measured concentration was in CO in the initial lockdown phase (40%), in London the greatest decrease was for NO2 in the later part of the lockdown (49%), and in Delhi the greatest decrease was in PM10, and PM2.5 in the initial lockdown phase (61% and 50%, respectively). Reduction in pollutant concentrations agreed with reductions in vehicle movements. In the initial lockdown phase vehicle movements reduced by up to 59% in Mexico City and 63% in London. The cities demonstrated a range of air quality changes in their differing geographical areas and land use types. Local meteorology and pollution events, such as forest fires, also impacted the results

Integrating Diverse Datasets Improves Developmental Enhancer Prediction

Gene-regulatory enhancers have been identified using various approaches, including evolutionary conservation, regulatory protein binding, chromatin modifications, and DNA sequence motifs. To integrate these different approaches, we developed EnhancerFinder, a two-step method for distinguishing developmental enhancers from the genomic background and then predicting their tissue specificity. EnhancerFinder uses a multiple kernel learning approach to integrate DNA sequence motifs, evolutionary patterns, and diverse functional genomics datasets from a variety of cell types. In contrast with prediction approaches that define enhancers based on histone marks or p300 sites from a single cell line, we trained EnhancerFinder on hundreds of experimentally verified human developmental enhancers from the VISTA Enhancer Browser. We comprehensively evaluated EnhancerFinder using cross validation and found that our integrative method improves the identification of enhancers over approaches that consider a single type of data, such as sequence motifs, evolutionary conservation, or the binding of enhancer-associated proteins. We find that VISTA enhancers active in embryonic heart are easier to identify than enhancers active in several other embryonic tissues, likely due to their uniquely high GC content. We applied EnhancerFinder to the entire human genome and predicted 84,301 developmental enhancers and their tissue specificity. These predictions provide specific functional annotations for large amounts of human non-coding DNA, and are significantly enriched near genes with annotated roles in their predicted tissues and lead SNPs from genome-wide association studies. We demonstrate the utility of EnhancerFinder predictions through in vivo validation of novel embryonic gene regulatory enhancers from three developmental transcription factor loci. Our genome-wide developmental enhancer predictions are freely available as a UCSC Genome Browser track, which we hope will enable researchers to further investigate questions in developmental biology. © 2014 Erwin et al

Differential Proteomic Analysis of Mammalian Tissues Using SILAM

Differential expression of proteins between tissues underlies organ-specific functions. Under certain pathological conditions, this may also lead to tissue vulnerability. Furthermore, post-translational modifications exist between different cell types and pathological conditions. We employed SILAM (Stable Isotope Labeling in Mammals) combined with mass spectrometry to quantify the proteome between mammalian tissues. Using 15N labeled rat tissue, we quantified 3742 phosphorylated peptides in nuclear extracts from liver and brain tissue. Analysis of the phosphorylation sites revealed tissue specific kinase motifs. Although these tissues are quite different in their composition and function, more than 500 protein identifications were common to both tissues. Specifically, we identified an up-regulation in the brain of the phosphoprotein, ZFHX1B, in which a genetic deletion causes the neurological disorder Mowat–Wilson syndrome. Finally, pathway analysis revealed distinct nuclear pathways enriched in each tissue. Our findings provide a valuable resource as a starting point for further understanding of tissue specific gene regulation and demonstrate SILAM as a useful strategy for the differential proteomic analysis of mammalian tissues

Storage of organic carbon in the soils of Mexican temperate forests

© 2019 Elsevier B.V. The deforestation and degradation of natural habitats is the second largest contributor to carbon dioxide (CO2) emissions to the atmosphere. Temperate forests cover ∼16.5% of the Mexican landscape, and are a priority ecosystem for global conservation due to their high rate of endemism and species diversity. These forests also provide valuable ecosystem services, including the storage of organic carbon. Mexican temperate forests have lost more than half of their original cover, with ongoing forest degradation, resulting in CO2 emissions to the atmosphere. Most studies and carbon inventories only consider organic carbon stored in the aboveground biomass, and do not consider the organic carbon stored within soils of temperate forests. As a result, the emissions of CO2 due to deforestation are underestimated, and the value of temperate forests is underappreciated. To address this shortcoming, (1) we examine the extent and factors determining soil organic carbon stocks; (2) we estimate soil organic carbon stocks of Mexican temperate forests, the CO2 emissions caused by deforestation and avoided emissions from conservation and (3) we discuss the causes of loss of soil OC and management strategies to mitigate this loss. We propose that including the soil organic carbon stock-component is a priority for national projects targeting reducing emissions from deforestation. Also, urgent studies on the impacts of forest degradation in stocks of soil organic carbon are needed. Management strategies for conservation and rehabilitation of Mexican temperate forests must consider social and economic aspects of the local communities