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Quantification of SARS-CoV-2 RNA copies in wastewater can be used to estimate COVID-19 prevalence in communities. While such results are important for mitigating disease spread, SARS-CoV-2 measurements require sophisticated equipment and trained personnel, for which a centralized laboratory is necessary. This significantly impacts the time to result, defeating its purpose as an early warning detection tool. The objective of this study was to evaluate a field portable device (called MINI) for detecting SARS-CoV-2 viral loads in wastewater using real-time reverse transcriptase loop-mediated isothermal amplification (real-time RT-LAMP). The device was tested using wastewater samples collected from buildings (with 430 to 1430 inhabitants) that had known COVID-19-positive cases. Results show comparable performance of RT-LAMP against reverse transcriptase polymerase chain reaction (RT-qPCR) when detecting SARS-CoV-2 copies in wastewater. Both RT-LAMP and RT-qPCR detected SARS-CoV-2 in wastewater from buildings with at least three positive individuals within a 6-day time frame prior to diagnosis. The large 96-well throughput provided by MINI provided scalability to multi-building detection. The portability of the MINI device enabled decentralized on-site detection, significantly reducing the time to result. The overall findings support the use of RT-LAMP within the MINI configuration as an early detection system for COVID-19 infection using wastewater collected at the building scale., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Clinical testing has been a vital part of the response to and suppression of the COVID-19 pandemic; however, testing imposes significant burdens on a population. College students had to contend with clinical testing while simultaneously dealing with health risks and the academic pressures brought on by quarantines, changes to virtual platforms, and other disruptions to daily life. The objective of this study was to analyze whether wastewater surveillance can be used to decrease the intensity of clinical testing while maintaining reliable measurements of diseases incidence on campus. Twelve months of human health and wastewater surveillance data for eight residential buildings on a university campus were analyzed to establish how SARS-CoV-2 levels in the wastewater can be used to minimize clinical testing burden on students. Wastewater SARS-CoV-2 levels were used to create multiple scenarios, each with differing levels of testing intensity, which were compared to the actual testing volumes implemented by the university. We found that scenarios in which testing intensity fluctuations matched rise and falls in SARS-CoV-2 wastewater levels had stronger correlations between SARS-CoV-2 levels and recorded clinical positives. In addition to stronger correlations, most scenarios resulted in overall fewer weekly clinical tests performed. We suggest the use of wastewater surveillance to guide COVID-19 testing as it can significantly increase the efficacy of COVID-19 surveillance while reducing the burden placed on college students during a pandemic. Future efforts should be made to integrate wastewater surveillance into clinical testing strategies implemented on college campuses., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Wastewater-based surveillance (WBS) is a noninvasive, epidemiological strategy for assessing the spread of COVID-19 in communities. This strategy was based upon wastewater RNA measurements of the viral target, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The utility of WBS for assessing the spread of COVID-19 has motivated research to measure targets beyond SARS-CoV-2, including pathogens containing DNA. The objective of this study was to establish the necessary steps for isolating DNA from wastewater by modifying a long-standing RNA-specific extraction workflow optimized for SARS-CoV-2 detection. Modifications were made to the sample concentration process and included an evaluation of bead bashing prior to the extraction of either DNA or RNA. Results showed that bead bashing reduced detection of RNA from wastewater but improved recovery of DNA as assessed by quantitative polymerase chain reaction (qPCR). Bead bashing is therefore not recommended for the quantification of RNA viruses using qPCR. Whereas for Mycobacterium bacterial DNA isolation, bead bashing was necessary for improving qPCR quantification. Overall, we recommend 2 separate workflows, one for RNA viruses that does not include bead bashing and one for other microbes that use bead bashing for DNA isolation. The experimentation done here shows that current-standing WBS program methodologies optimized for SARS-CoV-2 need to be modified and reoptimized to allow for alternative pathogens to be readily detected and monitored, expanding its utility as a tool for public health assessment., Competing Interests: Conflict of Interest: The authors declare no conflict or competing interest., (Copyright © 2023 Association of Biomolecular Resource Facilities. All rights reserved.)

Wastewater-based epidemiology (WBE) has been utilized to track community infections of Coronavirus Disease 2019 (COVID-19) by detecting RNA of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), within samples collected from wastewater. The correlations between community infections and wastewater measurements of the RNA can potentially change as SARS-CoV-2 evolves into new variations by mutating. This study analyzed SARS-CoV-2 RNA, and indicators of human waste in wastewater from two sewersheds of different scales (University of Miami (UM) campus and Miami-Dade County Central District wastewater treatment plant (CDWWTP)) during five internally defined COVID-19 variant dominant periods (Initial, Pre-Delta, Delta, Omicron and Post-Omicron wave). SARS-CoV-2 RNA quantities were compared against COVID-19 clinical cases and hospitalizations to evaluate correlations with wastewater SARS-CoV-2 RNA. Although correlations between documented clinical cases and hospitalizations were high, prevalence for a given wastewater SARS-CoV-2 level varied depending upon the variant analyzed. The correlative relationship was significantly steeper (more cases per level found in wastewater) for the Omicron-dominated period. For hospitalization, the relationships were steepest for the Initial wave, followed by the Delta wave with flatter slopes during all other waves. Overall results were interpreted in the context of SARS-CoV-2 virulence and vaccination rates among the community.

Short-read genome sequencing (GS) holds the promise of becoming the primary diagnostic approach for the assessment of autism spectrum disorder (ASD) and fetal structural anomalies (FSAs). However, few studies have comprehensively evaluated its performance against current standard-of-care diagnostic tests: karyotype, chromosomal microarray (CMA), and exome sequencing (ES). To assess the clinical utility of GS, we compared its diagnostic yield against these three tests in 1,612 quartet families including an individual with ASD and in 295 prenatal families. Our GS analytic framework identified a diagnostic variant in 7.8% of ASD probands, almost 2-fold more than CMA (4.3%) and 3-fold more than ES (2.7%). However, when we systematically captured copy-number variants (CNVs) from the exome data, the diagnostic yield of ES (7.4%) was brought much closer to, but did not surpass, GS. Similarly, we estimated that GS could achieve an overall diagnostic yield of 46.1% in unselected FSAs, representing a 17.2% increased yield over karyotype, 14.1% over CMA, and 4.1% over ES with CNV calling or 36.1% increase without CNV discovery. Overall, GS provided an added diagnostic yield of 0.4% and 0.8% beyond the combination of all three standard-of-care tests in ASD and FSAs, respectively. This corresponded to nine GS unique diagnostic variants, including sequence variants in exons not captured by ES, structural variants (SVs) inaccessible to existing standard-of-care tests, and SVs where the resolution of GS changed variant classification. Overall, this large-scale evaluation demonstrated that GS significantly outperforms each individual standard-of-care test while also outperforming the combination of all three tests, thus warranting consideration as the first-tier diagnostic approach for the assessment of ASD and FSAs., Competing Interests: Declaration of interests M.E.T. and H.R. receive research funding from Microsoft Inc and/or research reagents from Illumina Inc. M.E.T. also received research funding from Levo Therapeutics and research reagents from Ionis Therapeutics for unrelated research projects., (Copyright © 2023 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Methods of wastewater concentration (electronegative filtration (ENF) versus magnetic bead-based concentration (MBC)) were compared for the analysis of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), beta-2 microglobulin, and human-coronavirus OC43. Using ENF as the concentration method, two quantitative Polymerase Chain Reaction (qPCR) analytical methods were also compared: Volcano 2 nd Generation (V2G)-qPCR and reverse transcriptase (RT)-qPCR measuring three different targets of the virus responsible for the COVID-19 illness (N1, modified N3, and ORF1ab). Correlations between concentration methods were strong and statistically significant for SARS-CoV-2 (r=0.77, p<0.001) and B2M (r=0.77, p<0.001). Comparison of qPCR analytical methods indicate that, on average, each method provided equivalent results with average ratios of 0.96, 0.96 and 1.02 for N3 to N1, N3 to ORF1ab, and N1 to ORF1ab and were supported by significant (p<0.001) correlation coefficients (r =0.67 for V2G (N3) to RT (N1), r =0.74 for V2G (N3) to RT (ORF1ab), r = 0.81 for RT (N1) to RT (ORF1ab)). Overall results suggest that the two concentration methods and qPCR methods provide equivalent results, although variability is observed for individual measurements. Given the equivalency of results, additional advantages and disadvantages, as described in the discussion, are to be considered when choosing an appropriate method.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in wastewater has been used to track community infections of coronavirus disease-2019 (COVID-19), providing critical information for public health interventions. Since levels in wastewater are dependent upon human inputs, we hypothesize that tracking infections can be improved by normalizing wastewater concentrations against indicators of human waste [Pepper Mild Mottle Virus (PMMoV), β-2 Microglobulin (B2M), and fecal coliform]. In this study, we analyzed SARS-CoV-2 and indicators of human waste in wastewater from two sewersheds of different scales: a University campus and a wastewater treatment plant. Wastewater data were combined with complementary COVID-19 case tracking to evaluate the efficiency of wastewater surveillance for forecasting new COVID-19 cases and, for the larger scale, hospitalizations. Results show that the normalization of SARS-CoV-2 levels by PMMoV and B2M resulted in improved correlations with COVID-19 cases for campus data using volcano second generation (V2G)-qPCR chemistry ( r s = 0.69 without normalization, r s = 0.73 with normalization). Mixed results were obtained for normalization by PMMoV for samples collected at the community scale. Overall benefits from normalizing with measures of human waste depend upon qPCR chemistry and improves with smaller sewershed scale. We recommend further studies that evaluate the efficacy of additional normalization targets., Competing Interests: The authors declare no competing financial interest., (© 2022 The Authors. Published by American Chemical Society.)

Point mutations and structural variants that directly disrupt the coding sequence of MEF2C have been associated with a spectrum of neurodevelopmental disorders (NDDs). However, the impact of MEF2C haploinsufficiency on neurodevelopmental pathways and synaptic processes is not well understood, nor are the complex mechanisms that govern its regulation. To explore the functional changes associated with structural variants that alter MEF2C expression and/or regulation, we generated an allelic series of 204 isogenic human induced pluripotent stem cell (hiPSC)-derived neural stem cells and glutamatergic induced neurons. These neuronal models harbored CRISPR-engineered mutations that involved direct deletion of MEF2C or deletion of the boundary points for topologically associating domains (TADs) and chromatin loops encompassing MEF2C. Systematic profiling of mutation-specific alterations, contrasted to unedited controls that were exposed to the same guide RNAs for each edit, revealed that deletion of MEF2C caused differential expression of genes associated with neurodevelopmental pathways and synaptic function. We also discovered significant reduction in synaptic activity measured by multielectrode arrays (MEAs) in neuronal cells. By contrast, we observed robust buffering against MEF2C regulatory disruption following deletion of a distal 5q14.3 TAD and loop boundary, whereas homozygous loss of a proximal loop boundary resulted in down-regulation of MEF2C expression and reduced electrophysiological activity on MEA that was comparable to direct gene disruption. Collectively, these studies highlight the considerable functional impact of MEF2C deletion in neuronal cells and systematically characterize the complex interactions that challenge a priori predictions of regulatory consequences from structural variants that disrupt three-dimensional genome organization., Competing Interests: Declaration of interests M.E.T. receives research funding and/or reagents from Levo Therapeutics, Microsoft Inc, and Illumina Inc. K.M. initiated employment with Tornado Bio during the writing of this manuscript and is at present an employee of the company. J.F.G. is a founder and member of the scientific advisory board of Triplet Therapeutics, Inc., and has been a paid consultant to Biogen, Inc., Pfizer, Inc., and Wave Biosciences, Inc., (Copyright © 2022 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Chromosome 16p11.2 reciprocal genomic disorder, resulting from recurrent copy-number variants (CNVs), involves intellectual disability, autism spectrum disorder (ASD), and schizophrenia, but the responsible mechanisms are not known. To systemically dissect molecular effects, we performed transcriptome profiling of 350 libraries from six tissues (cortex, cerebellum, striatum, liver, brown fat, and white fat) in mouse models harboring CNVs of the syntenic 7qF3 region, as well as cellular, transcriptional, and single-cell analyses in 54 isogenic neural stem cell, induced neuron, and cerebral organoid models of CRISPR-engineered 16p11.2 CNVs. Transcriptome-wide differentially expressed genes were largely tissue-, cell-type-, and dosage-specific, although more effects were shared between deletion and duplication and across tissue than expected by chance. The broadest effects were observed in the cerebellum (2,163 differentially expressed genes), and the greatest enrichments were associated with synaptic pathways in mouse cerebellum and human induced neurons. Pathway and co-expression analyses identified energy and RNA metabolism as shared processes and enrichment for ASD-associated, loss-of-function constraint, and fragile X messenger ribonucleoprotein target gene sets. Intriguingly, reciprocal 16p11.2 dosage changes resulted in consistent decrements in neurite and electrophysiological features, and single-cell profiling of organoids showed reciprocal alterations to the proportions of excitatory and inhibitory GABAergic neurons. Changes both in neuronal ratios and in gene expression in our organoid analyses point most directly to calretinin GABAergic inhibitory neurons and the excitatory/inhibitory balance as targets of disruption that might contribute to changes in neurodevelopmental and cognitive function in 16p11.2 carriers. Collectively, our data indicate the genomic disorder involves disruption of multiple contributing biological processes and that this disruption has relative impacts that are context specific., Competing Interests: Declaration of interests J.F.G. is a founder and member of the scientific advisory board of Triplet Therapeutics and has been a paid consultant to Biogen, Pfizer, and Wave Biosciences. M.E.T. receives research funding and/or reagents from Illumina, Levo Therapeutics, and Microsoft. E.M. receives research funding and reagents from PTC Therapeutics. The following co-authors are currently employed by for-profit companies or non-profit organizations: P.R. is founder and CEO of Kumuda; K.M. is currently employed by Tornado Bio; T.A. is a founder and CEO of Independent Data Lab and OmicsChart; and A.H. is currently employed by Bionano Genomics., (Copyright © 2022 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Precise tests for genomic structural variation (SV) are essential for accurate diagnosis of prenatal genome abnormalities. The two most ubiquitous traditional methods for prenatal SV assessment, karyotyping and chromosomal microarrays, do not provide sufficient resolution for some clinically actionable SVs. Standard whole-genome sequencing (WGS) overcomes shortcomings of traditional techniques by providing base-pair resolution of the entire accessible genome. However, while sequencing costs have continued to decline in recent years, conventional WGS costs remain high for most routine clinical applications. Here, we describe a specialized WGS technique using large inserts (liWGS; also known as "jumping libraries") to resolve large (>5000-10,000 nucleotides) SVs at kilobase-resolution in prenatal samples, and at a fraction of the cost of standard WGS. We explicate the protocols for generating liWGS libraries and supplement with an overview for processing and analyzing liWGS data.

Great strides in gene discovery have been made using a multitude of methods to associate phenotypes with genetic variants, but there still remains a substantial gap between observed symptoms and identified genetic defects. Herein, we use the convergence of various genetic and genomic techniques to investigate the underpinnings of a constellation of phenotypes that include prostate cancer (PCa) and sensorineural hearing loss (SNHL) in a human subject. Through interrogation of the subject's de novo, germline, balanced chromosomal translocation, we first identify a correlation between his disorders and a poorly annotated gene known as lipid droplet associated hydrolase (LDAH). Using data repositories of both germline and somatic variants, we identify convergent genomic evidence that substantiates a correlation between loss of LDAH and PCa. This correlation is validated through both in vitro and in vivo models that show loss of LDAH results in increased risk of PCa and, to a lesser extent, SNHL. By leveraging convergent evidence in emerging genomic data, we hypothesize that loss of LDAH is involved in PCa and other phenotypes observed in support of a genotype-phenotype association in an n-of-one human subject.

Whole-genome sequencing (WGS) has facilitated the first genome-wide evaluations of the contribution of de novo noncoding mutations to complex disorders. Using WGS, we identified 255,106 de novo mutations among sample genomes from members of 1902 quartet families in which one child, but not a sibling or their parents, was affected by autism spectrum disorder (ASD). In contrast to coding mutations, no noncoding functional annotation category, analyzed in isolation, was significantly associated with ASD. Casting noncoding variation in the context of a de novo risk score across multiple annotation categories, however, did demonstrate association with mutations localized to promoter regions. We found that the strongest driver of this promoter signal emanates from evolutionarily conserved transcription factor binding sites distal to the transcription start site. These data suggest that de novo mutations in promoter regions, characterized by evolutionary and functional signatures, contribute to ASD., (Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Genomic association studies of common or rare protein-coding variation have established robust statistical approaches to account for multiple testing. Here we present a comparable framework to evaluate rare and de novo noncoding single-nucleotide variants, insertion/deletions, and all classes of structural variation from whole-genome sequencing (WGS). Integrating genomic annotations at the level of nucleotides, genes, and regulatory regions, we define 51,801 annotation categories. Analyses of 519 autism spectrum disorder families did not identify association with any categories after correction for 4,123 effective tests. Without appropriate correction, biologically plausible associations are observed in both cases and controls. Despite excluding previously identified gene-disrupting mutations, coding regions still exhibited the strongest associations. Thus, in autism, the contribution of de novo noncoding variation is probably modest in comparison to that of de novo coding variants. Robust results from future WGS studies will require large cohorts and comprehensive analytical strategies that consider the substantial multiple-testing burden.

Background: Structural variation (SV) influences genome organization and contributes to human disease. However, the complete mutational spectrum of SV has not been routinely captured in disease association studies., Results: We sequenced 689 participants with autism spectrum disorder (ASD) and other developmental abnormalities to construct a genome-wide map of large SV. Using long-insert jumping libraries at 105X mean physical coverage and linked-read whole-genome sequencing from 10X Genomics, we document seven major SV classes at ~5 kb SV resolution. Our results encompass 11,735 distinct large SV sites, 38.1% of which are novel and 16.8% of which are balanced or complex. We characterize 16 recurrent subclasses of complex SV (cxSV), revealing that: (1) cxSV are larger and rarer than canonical SV; (2) each genome harbors 14 large cxSV on average; (3) 84.4% of large cxSVs involve inversion; and (4) most large cxSV (93.8%) have not been delineated in previous studies. Rare SVs are more likely to disrupt coding and regulatory non-coding loci, particularly when truncating constrained and disease-associated genes. We also identify multiple cases of catastrophic chromosomal rearrangements known as chromoanagenesis, including somatic chromoanasynthesis, and extreme balanced germline chromothripsis events involving up to 65 breakpoints and 60.6 Mb across four chromosomes, further defining rare categories of extreme cxSV., Conclusions: These data provide a foundational map of large SV in the morbid human genome and demonstrate a previously underappreciated abundance and diversity of cxSV that should be considered in genomic studies of human disease.

Arhinia, or absence of the nose, is a rare malformation of unknown etiology that is often accompanied by ocular and reproductive defects. Sequencing of 40 people with arhinia revealed that 84% of probands harbor a missense mutation localized to a constrained region of SMCHD1 encompassing the ATPase domain. SMCHD1 mutations cause facioscapulohumeral muscular dystrophy type 2 (FSHD2) via a trans-acting loss-of-function epigenetic mechanism. We discovered shared mutations and comparable DNA hypomethylation patterning between these distinct disorders. CRISPR/Cas9-mediated alteration of smchd1 in zebrafish yielded arhinia-relevant phenotypes. Transcriptome and protein analyses in arhinia probands and controls showed no differences in SMCHD1 mRNA or protein abundance but revealed regulatory changes in genes and pathways associated with craniofacial patterning. Mutations in SMCHD1 thus contribute to distinct phenotypic spectra, from craniofacial malformation and reproductive disorders to muscular dystrophy, which we speculate to be consistent with oligogenic mechanisms resulting in pleiotropic outcomes.

Despite the clinical significance of balanced chromosomal abnormalities (BCAs), their characterization has largely been restricted to cytogenetic resolution. We explored the landscape of BCAs at nucleotide resolution in 273 subjects with a spectrum of congenital anomalies. Whole-genome sequencing revised 93% of karyotypes and demonstrated complexity that was cryptic to karyotyping in 21% of BCAs, highlighting the limitations of conventional cytogenetic approaches. At least 33.9% of BCAs resulted in gene disruption that likely contributed to the developmental phenotype, 5.2% were associated with pathogenic genomic imbalances, and 7.3% disrupted topologically associated domains (TADs) encompassing known syndromic loci. Remarkably, BCA breakpoints in eight subjects altered a single TAD encompassing MEF2C, a known driver of 5q14.3 microdeletion syndrome, resulting in decreased MEF2C expression. We propose that sequence-level resolution dramatically improves prediction of clinical outcomes for balanced rearrangements and provides insight into new pathogenic mechanisms, such as altered regulation due to changes in chromosome topology., Competing Interests: The authors have none to declare.

Analysis of chromosomal rearrangements has been highly successful in identifying genes involved in many congenital abnormalities including hearing loss. Herein, we report a subject, designated DGAP242, with congenital hearing loss (HL) and a de novo balanced translocation 46,XX,t(1;5)(q32;q15)dn. Using multiple next-generation sequencing techniques, we obtained high resolution of the breakpoints. This revealed disruption of the orphan receptor ESRRG on chromosome 1, which is differentially expressed in inner ear hair cells and has previously been implicated in HL, and disruption of KIAA0825 on chromosome 5. Given the translocation breakpoints and supporting literature, disruption of ESRRG is the most likely cause for DGAP242's phenotype and implicates ESRRG in a monogenic form of congenital HL, although a putative contributory role for KIAA0825 in the subject's disorder cannot be excluded.

Hair cells of the inner ear, the mechanosensory receptors, convert sound waves into neural signals that are passed to the brain via the auditory nerve. Little is known about the molecular mechanisms that govern the development of hair cell-neuronal connections. We ascertained a family with autosomal recessive deafness associated with a common cavity inner ear malformation and auditory neuropathy. Via whole-exome sequencing, we identified a variant (c.2207G>C, p.R736T) in ROR1 (receptor tyrosine kinase-like orphan receptor 1), cosegregating with deafness in the family and absent in ethnicity-matched controls. ROR1 is a tyrosine kinase-like receptor localized at the plasma membrane. At the cellular level, the mutation prevents the protein from reaching the cellular membrane. In the presence of WNT5A, a known ROR1 ligand, the mutated ROR1 fails to activate NF-κB. Ror1 is expressed in the inner ear during development at embryonic and postnatal stages. We demonstrate that Ror1 mutant mice are severely deaf, with preserved otoacoustic emissions. Anatomically, mutant mice display malformed cochleae. Axons of spiral ganglion neurons show fasciculation defects. Type I neurons show impaired synapses with inner hair cells, and type II neurons display aberrant projections through the cochlear sensory epithelium. We conclude that Ror1 is crucial for spiral ganglion neurons to innervate auditory hair cells. Impairment of ROR1 function largely affects development of the inner ear and hearing in humans and mice.

With recent rapid advances in genomic technologies, precise delineation of structural chromosome rearrangements at the nucleotide level is becoming increasingly feasible. In this era of "next-generation cytogenetics" (i.e., an integration of traditional cytogenetic techniques and next-generation sequencing), a consensus nomenclature is essential for accurate communication and data sharing. Currently, nomenclature for describing the sequencing data of these aberrations is lacking. Herein, we present a system called Next-Gen Cytogenetic Nomenclature, which is concordant with the International System for Human Cytogenetic Nomenclature (2013). This system starts with the alignment of rearrangement sequences by BLAT or BLAST (alignment tools) and arrives at a concise and detailed description of chromosomal changes. To facilitate usage and implementation of this nomenclature, we are developing a program designated BLA(S)T Output Sequence Tool of Nomenclature (BOSToN), a demonstrative version of which is accessible online. A standardized characterization of structural chromosomal rearrangements is essential both for research analyses and for application in the clinical setting., (Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

The Slc26 family proteins, with one possible exception, transport anions across membranes in a wide variety of tissues in vertebrates, invertebrates, and plants. Mutations in human members of the family are a significant cause of disease. Slc26 family proteins are thought to be oligomers, but their stoichiometry of association is in dispute. A recent study, using sequential bleaching of single fluorophore-coupled molecules in membrane fragments, demonstrated that mammalian Slc26a5 (prestin) is a tetramer. In this article, the stoichiometry of two nonmammalian prestins and three human SLC26 proteins has been analyzed by the same method, including the evolutionarily-distant SLC26A11. The analysis showed that tetramerization is common and likely to be ubiquitous among Slc26 proteins, at least in vertebrates. The implication of the findings is that tetramerization is present for functional reasons.

It has been known for several decades that genetic variation involving changes to chromosomal structure (i.e., structural variants) can contribute to disease; however this relationship has been brought into acute focus in recent years largely based on innovative new genomics approaches and technology. Structural variants (SVs) arise from improperly repaired DNA double-strand breaks (DSB). DSBs are a frequent occurrence in all cells and two major pathways are involved in their repair: homologous recombination and non-homologous end joining. Errors during these repair mechanisms can result in SVs that involve losses, gains and rearrangements ranging from a few nucleotides to entire chromosomal arms. Factors such as rearrangements, hotspots and induced DSBs are implicated in the formation of SVs. While de novo SVs are often associated with disease, some SVs are conserved within human subpopulations and may have had a meaningful influence on primate evolution. As the ability to sequence the whole human genome rapidly evolves, the diversity of SVs is illuminated, including very complex rearrangements involving multiple DSBs in a process recently designated as "chromothripsis". Elucidating mechanisms involved in the etiology of SVs informs disease pathogenesis as well as the dynamic function associated with the biology and evolution of human genomes.