An accurate estimation of biomass burning emissions is partially limited by the lack of knowledge of fire burning phase (smoldering vs. flaming). In recent years, several fire detection products have ...been developed to provide information of fire radiative power (FRP), location, size, and temperature of fire pixels, but no information regarding fire burning phase is retrieved. The Day-Night band (DNB) aboard Visible Infrared Imaging Radiometer Suite (VIIRS) is sensitive to visible light from flaming fires in nighttime scenes. In contrast, VIIRS 4 μm moderate resolution band #13 (M13), though capable of detecting fires at all phases, has no direct sensitivity for discerning fire phase. However, the hybrid usage of VIIRS DNB and M-bands data is hampered by their different scanning technology and spatial resolution. In this study, we present a novel method to rapidly and accurately resample DNB pixel radiances to the footprint of M-band pixels, accounting for onboard detector aggregation schemes and bowtie effect removals. The visible energy fraction (VEF) is subsequently introduced as an indicator of fire burning phase. VEF is calculated as the ratio of visible light power (VLP) to FRP for each fire pixel retrieved from the VIIRS 750 m active fire product. A global distribution of VEF values is quantitatively obtained, showing smaller VEF values in regions with mostly smoldering wildfires, such as peatland fires in Indonesia, larger VEF values in regions with flaming wildfires over grasslands and savannas in the sub-Sahelian region, and the largest VEF values associated with gas flaring in the Middle East. Mean VEF for different land cover types or regions is highly correlated with modified combustion efficiency (MCE). These results, together with a case study of the 2018 California Camp Fire, show that the VEF has the potential to be an indicator of fire combustion phase for each fire pixel, appropriate for estimating emission factors at the satellite pixel level.
•Novel approach to resample VIIRS′ Day-Night-Band radiances to its M-band footprint.•Visible energy fraction (VEF) concept is mathematically defined for nighttime fires.•VEF is more effective than fire radiative power to describe fire phase.•VEF is a strong indicator of the modified combustion efficiency (MCE) of fires.•VEF is computed globally and captures MCE global variation for different biomes.
Lipodystrophies are a group of disorders characterized by absence or loss of adipose tissue and abnormal fat distribution, commonly accompanied by metabolic dysregulation. Although considered rare ...disorders, their prevalence in the general population is not well understood. We aimed to evaluate the clinical and genetic prevalence of lipodystrophy disorders in a large clinical care cohort. We interrogated the electronic health record (EHR) information of >1.3 million adults from the Geisinger Health System for lipodystrophy diagnostic codes. We estimate a clinical prevalence of disease of 1 in 20,000 individuals. We performed genetic analyses in individuals with available genomic data to identify variants associated with inherited lipodystrophies and examined their EHR for comorbidities associated with lipodystrophy. We identified 16 individuals carrying the p.R482Q pathogenic variant in LMNA associated with Dunnigan familial partial lipodystrophy. Four had a clinical diagnosis of lipodystrophy, whereas the remaining had no documented clinical diagnosis despite having accompanying metabolic abnormalities. We observed a lipodystrophy-associated variant carrier frequency of 1 in 3,082 individuals in our cohort with substantial burden of metabolic dysregulation. We estimate a genetic prevalence of disease of ∼1 in 7,000 in the general population. Partial lipodystrophy is an underdiagnosed condition. and its prevalence, as defined molecularly, is higher than previously reported. Genetically guided stratification of patients with common metabolic disorders, like diabetes and dyslipidemia, is an important step toward precision medicine.
Numerical prediction of aerosol particle properties has become an important activity at many research and operational weather centers. This development is due to growing interest from a diverse set ...of stakeholders, such as air quality regulatory bodies, aviation and military authorities, solar energy plant managers, climate services providers, and health professionals. Owing to the complexity of atmospheric aerosol processes and their sensitivity to the underlying meteorological conditions, the prediction of aerosol particle concentrations and properties in the numerical weather prediction (NWP) framework faces a number of challenges. The modeling of numerous aerosol-related parameters increases computational expense. Errors in aerosol prediction concern all processes involved in the aerosol life cycle including (a) errors on the source terms (for both anthropogenic and natural emissions), (b) errors directly dependent on the meteorology (e.g., mixing, transport, scavenging by precipitation), and (c) errors related to aerosol chemistry (e.g., nucleation, gas–aerosol partitioning, chemical transformation and growth, hygroscopicity). Finally, there are fundamental uncertainties and significant processing overhead in the diverse observations used for verification and assimilation within these systems. Indeed, a significant component of aerosol forecast development consists in streamlining aerosol-related observations and reducing the most important errors through model development and data assimilation. Aerosol particle observations from satellite- and ground-based platforms have been crucial to guide model development of the recent years and have been made more readily available for model evaluation and assimilation. However, for the sustainability of the aerosol particle prediction activities around the globe, it is crucial that quality aerosol observations continue to be made available from different platforms (space, near surface, and aircraft) and freely shared. This paper reviews current requirements for aerosol observations in the context of the operational activities carried out at various global and regional centers. While some of the requirements are equally applicable to aerosol–climate, the focus here is on global operational prediction of aerosol properties such as mass concentrations and optical parameters. It is also recognized that the term “requirements” is loosely used here given the diversity in global aerosol observing systems and that utilized data are typically not from operational sources. Most operational models are based on bulk schemes that do not predict the size distribution of the aerosol particles. Others are based on a mix of “bin” and bulk schemes with limited capability of simulating the size information. However the next generation of aerosol operational models will output both mass and number density concentration to provide a more complete description of the aerosol population. A brief overview of the state of the art is provided with an introduction on the importance of aerosol prediction activities. The criteria on which the requirements for aerosol observations are based are also outlined. Assimilation and evaluation aspects are discussed from the perspective of the user requirements.
By combining Collection 6 Moderate Resolution and Imaging Spectroradiometer (MODIS) and Version 22 Multi-angle Imaging Spectroradiometer (MISR) aerosol products with Cloud and Earth's Radiant Energy ...System (CERES) flux products, the aerosol optical thickness (AOT, at 0.55 µm) and shortwave (SW) aerosol radiative effect (SWARE) trends are studied over ocean for the near-full Terra (2000–2015) and Aqua (2002–2015) data records. Despite differences in sampling methods, regional SWARE and AOT trends are highly correlated with one another. Over global oceans, weak SWARE (cloud-free SW flux) and AOT trends of 0.5–0.6 W m−2 (−0.5 to −0.6 W m−2) and 0.002 AOT decade−1 are found using Terra data. Near-zero AOT and SWARE trends are also found for using Aqua data, regardless of the angular distribution models (ADMs) used. Regionally, positive AOT and cloud-free SW flux (negative SWARE) trends are found over the Bay of Bengal, the Arabian Sea, the Arabian/Persian Gulf and the Red Sea, while statistically significant negative trends are derived over the Mediterranean Sea and the eastern US coast. In addition, the global mean instantaneous SW aerosol direct forcing efficiencies are found to be ∼ −60 W m−2 AOT−1, with corresponding SWARE values of ∼ −7 W m−2 from both Aqua and Terra data, again regardless of CERES ADMs used. Regionally, SW aerosol direct forcing efficiency values of ∼ −40 W m−2 AOT−1 are found over the southwest coast of Africa where smoke aerosol particles dominate in summer. Larger (in magnitude) SW aerosol direct forcing efficiency values of −50 to −80 W m−2 AOT−1 are found over several other dust- and pollutant-aerosol-dominated regions. Lastly, the AOT and SWARE trends from this study are also intercompared with aerosol trends (such as active-based ones) from several previous studies. Findings suggest that a cohesive understanding of the changing aerosol skies can be achieved through the analysis of observations from both passive- and active-based analyses, as well as from both narrowband and broadband datasets.
Abstract
Summary
Variant Call Format (VCF), the prevailing representation for germline genotypes in population sequencing, suffers rapid size growth as larger cohorts are sequenced and more rare ...variants are discovered. We present Sparse Project VCF (spVCF), an evolution of VCF with judicious entropy reduction and run-length encoding, delivering >10× size reduction for modern studies with practically minimal information loss. spVCF interoperates with VCF efficiently, including tabix-based random access. We demonstrate its effectiveness with the DiscovEHR and UK Biobank whole-exome sequencing cohorts.
Availability and implementation
Apache-licensed reference implementation: github.com/mlin/spVCF.
Supplementary information
Supplementary data are available at Bioinformatics online.
To characterize the role of rare complete human knockouts in autism spectrum disorders (ASDs), we identify genes with homozygous or compound heterozygous loss-of-function (LoF) variants (defined as ...nonsense and essential splice sites) from exome sequencing of 933 cases and 869 controls. We identify a 2-fold increase in complete knockouts of autosomal genes with low rates of LoF variation (≤5% frequency) in cases and estimate a 3% contribution to ASD risk by these events, confirming this observation in an independent set of 563 probands and 4,605 controls. Outside the pseudoautosomal regions on the X chromosome, we similarly observe a significant 1.5-fold increase in rare hemizygous knockouts in males, contributing to another 2% of ASDs in males. Taken together, these results provide compelling evidence that rare autosomal and X chromosome complete gene knockouts are important inherited risk factors for ASD.
► Excess of rare complete knockouts provides support for inherited component in ASD ► Estimate a 3% contribution to ASD risk for rare autosomal complete knockouts ► A further 2% contribution to ASD risk in males from X-linked complete knockouts ► Discovered ASD candidate genes from screen of rare human knockouts
Lim et al. characterize the role of rare complete knockouts (autosomal genes with homozygous and compound heterozygous loss-of-function variants and hemizygous X chromosome knockouts in males) in ASD and estimate that 5% of cases may have a significant contribution from such alleles.
Whole-genome sequencing of patient DNA can facilitate diagnosis of a disease, but its potential for guiding treatment has been under-realized. We interrogated the complete genome sequences of a ...14-year-old fraternal twin pair diagnosed with dopa (3,4-dihydroxyphenylalanine)-responsive dystonia (DRD; Mendelian Inheritance in Man #128230). DRD is a genetically heterogeneous and clinically complex movement disorder that is usually treated with l-dopa, a precursor of the neurotransmitter dopamine. Whole-genome sequencing identified compound heterozygous mutations in the SPR gene encoding sepiapterin reductase. Disruption of SPR causes a decrease in tetrahydrobiopterin, a cofactor required for the hydroxylase enzymes that synthesize the neurotransmitters dopamine and serotonin. Supplementation of l-dopa therapy with 5-hydroxytryptophan, a serotonin precursor, resulted in clinical improvements in both twins.
Characterizing large genomic variants is essential to expanding the research and clinical applications of genome sequencing. While multiple data types and methods are available to detect these ...structural variants (SVs), they remain less characterized than smaller variants because of SV diversity, complexity, and size. These challenges are exacerbated by the experimental and computational demands of SV analysis. Here, we characterize the SV content of a personal genome with Parliament, a publicly available consensus SV-calling infrastructure that merges multiple data types and SV detection methods.
We demonstrate Parliament's efficacy via integrated analyses of data from whole-genome array comparative genomic hybridization, short-read next-generation sequencing, long-read (Pacific BioSciences RSII), long-insert (Illumina Nextera), and whole-genome architecture (BioNano Irys) data from the personal genome of a single subject (HS1011). From this genome, Parliament identified 31,007 genomic loci between 100 bp and 1 Mbp that are inconsistent with the hg19 reference assembly. Of these loci, 9,777 are supported as putative SVs by hybrid local assembly, long-read PacBio data, or multi-source heuristics. These SVs span 59 Mbp of the reference genome (1.8%) and include 3,801 events identified only with long-read data. The HS1011 data and complete Parliament infrastructure, including a BAM-to-SV workflow, are available on the cloud-based service DNAnexus.
HS1011 SV analysis reveals the limits and advantages of multiple sequencing technologies, specifically the impact of long-read SV discovery. With the full Parliament infrastructure, the HS1011 data constitute a public resource for novel SV discovery, software calibration, and personal genome structural variation analysis.
MicroRNAs (miRNAs) are small non-coding RNAs that mediate post-transcriptional gene silencing. Over 700 human miRNAs have currently been identified, many of which are mutated or de-regulated in ...diseases. Here we report the identification of novel miRNAs through deep sequencing the small RNAome (<30 nt) of over 100 tissues or cell lines derived from human female reproductive organs in both normal and disease states. These specimens include ovarian epithelium and ovarian cancer, endometrium and endometriomas, and uterine myometrium and uterine smooth muscle tumors. Sequence reads not aligning with known miRNAs were each mapped to the genome to extract flanking sequences. These extended sequence regions were folded in silico to identify RNA hairpins. Sequences demonstrating the ability to form a stem loop structure with low minimum free energy (<-25 kcal) and predicted Drosha and Dicer cut sites yielding a mature miRNA sequence matching the actual sequence were considered putative novel miRNAs. Additional confidence was achieved when putative novel hairpins assembled a collection of sequences highly similar to the putative mature miRNA but with heterogeneous 3'-ends. A confirmed novel miRNA fulfilled these criteria and had its "star" sequence in our collection. We found 7 distinct confirmed novel miRNAs, and 51 additional novel miRNAs that represented highly confident predictions but without detectable star sequences. Our novel miRNAs were detectable in multiple samples, but expressed at low levels and not specific to any one tissue or cell type. To date, this study represents the largest set of samples analyzed together to identify novel miRNAs.
Pulmonary arterial hypertension (PAH) is a rare disease characterized by distinctive changes in pulmonary arterioles that lead to progressive pulmonary arterial pressures, right-sided heart failure, ...and a high mortality rate. Up to 30% of adult and 75% of pediatric PAH cases are associated with congenital heart disease (PAH-CHD), and the underlying etiology is largely unknown. There are no known major risk genes for PAH-CHD.
To identify novel genetic causes of PAH-CHD, we performed whole exome sequencing in 256 PAH-CHD patients. We performed a case-control gene-based association test of rare deleterious variants using 7509 gnomAD whole genome sequencing population controls. We then screened a separate cohort of 413 idiopathic and familial PAH patients without CHD for rare deleterious variants in the top association gene.
We identified SOX17 as a novel candidate risk gene (p = 5.5e-7). SOX17 is highly constrained and encodes a transcription factor involved in Wnt/β-catenin and Notch signaling during development. We estimate that rare deleterious variants contribute to approximately 3.2% of PAH-CHD cases. The coding variants identified include likely gene-disrupting (LGD) and deleterious missense, with most of the missense variants occurring in a highly conserved HMG-box protein domain. We further observed an enrichment of rare deleterious variants in putative targets of SOX17, many of which are highly expressed in developing heart and pulmonary vasculature. In the cohort of PAH without CHD, rare deleterious variants of SOX17 were observed in 0.7% of cases.
These data strongly implicate SOX17 as a new risk gene contributing to PAH-CHD as well as idiopathic/familial PAH. Replication in other PAH cohorts and further characterization of the clinical phenotype will be important to confirm the precise role of SOX17 and better estimate the contribution of genes regulated by SOX17.
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