Deep sequencing of 10,000 human genomes

Polygenic Indices (a.k.a. Polygenic Scores) in Social Science: A Guide for Interpretation and Evaluation

Polygenic indices (PGI)-the new recommended label for polygenic scores (PGS) in social science-are genetic summary scales often used to represent an individual's liability for a disease, trait, or behavior based on the additive effects of measured genetic variants. Enthusiasm for linking genetic data with social outcomes and the inclusion of premade PGIs in social science datasets have facilitated increased uptake of PGIs in social science research-a trend that will likely continue. Yet, most social scientists lack the expertise to interpret and evaluate PGIs in social science research. Here, we provide a primer on PGIs for social scientists focusing on key concepts, unique statistical genetic considerations, and best practices in calculation, estimation, reporting, and interpretation. We summarize our recommended best practices as a checklist to aid social scientists in evaluating and interpreting studies with PGIs. We conclude by discussing the similarities between PGIs and standard social science scales and unique interpretative considerations.

Divergent folding-mediated epistasis among unstable membrane protein variants

Many membrane proteins are prone to misfolding, which compromises their functional expression at the plasma membrane. This is particularly true for the mammalian gonadotropin-releasing hormone receptor GPCRs (GnRHR). We recently demonstrated that evolutionary GnRHR modifications appear to have coincided with adaptive changes in cotranslational folding efficiency. Though protein stability is known to shape evolution, it is unclear how cotranslational folding constraints modulate the synergistic, epistatic interactions between mutations. We therefore compared the pairwise interactions formed by mutations that disrupt the membrane topology (V276T) or tertiary structure (W107A) of GnRHR. Using deep mutational scanning, we evaluated how the plasma membrane expression of these variants is modified by hundreds of secondary mutations. An analysis of 251 mutants in three genetic backgrounds reveals that V276T and W107A form distinct epistatic interactions that depend on both the severity and the mechanism of destabilization. V276T forms predominantly negative epistatic interactions with destabilizing mutations in soluble loops. In contrast, W107A forms positive interactions with mutations in both loops and transmembrane domains that reflect the diminishing impacts of the destabilizing mutations in variants that are already unstable. These findings reveal how epistasis is remodeled by conformational defects in membrane proteins and in unstable proteins more generally.

Unveiling novel genetic variants in 370 challenging medically relevant genes using the long read sequencing data of 41 samples from 19 global populations

BACKGROUND

A large number of challenging medically relevant genes (CMRGs) are situated in complex or highly repetitive regions of the human genome, hindering comprehensive characterization of genetic variants using next-generation sequencing technologies. In this study, we employed long-read sequencing technology, extensively utilized in studying complex genomic regions, to characterize genetic alterations, including short variants (single nucleotide variants and short insertions and deletions) and copy number variations, in 370 CMRGs across 41 individuals from 19 global populations.

RESULTS

Our analysis revealed high levels of genetic variants in CMRGs, with 68.73% exhibiting copy number variations and 65.20% containing short variants that may disrupt protein function across individuals. Such variants can influence pharmacogenomics, genetic disease susceptibility, and other clinical outcomes. We observed significant differences in CMRG variation across populations, with individuals of African ancestry harboring the highest number of copy number variants and short variants compared to samples from other continents. Notably, 15.79% to 33.96% of short variants were exclusively detectable through long-read sequencing. While the T2T-CHM13 reference genome significantly improved the assembly of CMRG regions, thereby facilitating variant detection in these regions, some regions still lacked resolution.

CONCLUSION

Our results provide an important reference for future clinical and pharmacogenetic studies, highlighting the need for a comprehensive representation of global genetic diversity in the reference genome and improved variant calling techniques to fully resolve medically relevant genes.

A unified analysis of evolutionary and population constraint in protein domains highlights structural features and pathogenic sites

Protein evolution is constrained by structure and function, creating patterns in residue conservation that are routinely exploited to predict structure and other features. Similar constraints should affect variation across individuals, but it is only with the growth of human population sequencing that this has been tested at scale. Now, human population constraint has established applications in pathogenicity prediction, but it has not yet been explored for structural inference. Here, we map 2.4 million population variants to 5885 protein families and quantify residue-level constraint with a new Missense Enrichment Score (MES). Analysis of 61,214 structures from the PDB spanning 3661 families shows that missense depleted sites are enriched in buried residues or those involved in small-molecule or protein binding. MES is complementary to evolutionary conservation and a combined analysis allows a new classification of residues according to a conservation plane. This approach finds functional residues that are evolutionarily diverse, which can be related to specificity, as well as family-wide conserved sites that are critical for folding or function. We also find a possible contrast between lethal and non-lethal pathogenic sites, and a surprising clinical variant hot spot at a subset of missense enriched positions.

Divergent Folding-Mediated Epistasis Among Unstable Membrane Protein Variants

Many membrane proteins are prone to misfolding, which compromises their functional expression at the plasma membrane. This is particularly true for the mammalian gonadotropin-releasing hormone receptor GPCRs (GnRHR). We recently demonstrated that evolutionary GnRHR modifications appear to have coincided with adaptive changes in cotranslational folding efficiency. Though protein stability is known to shape evolution, it is unclear how cotranslational folding constraints modulate the synergistic, epistatic interactions between mutations. We therefore compared the pairwise interactions formed by mutations that disrupt the membrane topology (V276T) or tertiary structure (W107A) of GnRHR. Using deep mutational scanning, we evaluated how the plasma membrane expression of these variants is modified by hundreds of secondary mutations. An analysis of 251 mutants in three genetic backgrounds reveals that V276T and W107A form distinct epistatic interactions that depend on both the severity and the mechanism of destabilization. V276T forms predominantly negative epistatic interactions with destabilizing mutations in soluble loops. In contrast, W107A forms positive interactions with mutations in both loops and transmembrane domains that reflect the diminishing impacts of the destabilizing mutations in variants that are already unstable. These findings reveal how epistasis is remodeled by conformational defects in membrane proteins and in unstable proteins more generally.

Recent Advances in Drug Discovery Toxicology

Major advances in scientific discovery and insights that stem from the development and use of new techniques and models can bring remarkable progress to conventional toxicology. Although animal testing is still considered as the "gold standard" in traditional toxicity testing, there is a necessity for shift from animal testing to alternative methods regarding the drug safety testing owing to the emerging state-of-art techniques and the proposal of 3Rs (replace, reduce, and refine) towards animal welfare. This review describes some recent research methods in drug discovery toxicology, including in vitro cell and organ-on-a-chip, imaging systems, model organisms (C. elegans, Danio rerio, and Drosophila melanogaster), and toxicogenomics in modern toxicology testing.

Quartet DNA reference materials and datasets for comprehensively evaluating germline variant calling performance

BACKGROUND

Genomic DNA reference materials are widely recognized as essential for ensuring data quality in omics research. However, relying solely on reference datasets to evaluate the accuracy of variant calling results is incomplete, as they are limited to benchmark regions. Therefore, it is important to develop DNA reference materials that enable the assessment of variant detection performance across the entire genome.

RESULTS

We established a DNA reference material suite from four immortalized cell lines derived from a family of parents and monozygotic twins. Comprehensive reference datasets of 4.2 million small variants and 15,000 structural variants were integrated and certified for evaluating the reliability of germline variant calls inside the benchmark regions. Importantly, the genetic built-in-truth of the Quartet family design enables estimation of the precision of variant calls outside the benchmark regions. Using the Quartet reference materials along with study samples, batch effects are objectively monitored and alleviated by training a machine learning model with the Quartet reference datasets to remove potential artifact calls. Moreover, the matched RNA and protein reference materials and datasets from the Quartet project enables cross-omics validation of variant calls from multiomics data.

CONCLUSIONS

The Quartet DNA reference materials and reference datasets provide a unique resource for objectively assessing the quality of germline variant calls throughout the whole-genome regions and improving the reliability of large-scale genomic profiling.

Polymorphic USP8 allele promotes Parkinson's disease by inducing the accumulation of α-synuclein through deubiquitination

Parkinson's disease (PD) is one of the most common neuro-degenerative diseases characterized by α-synuclein accumulation and degeneration of dopaminergic neurons. Employing genome-wide sequencing, we identified a polymorphic USP8 allele (USP8D442G) significantly enriched in Chinese PD patients. To test the involvement of this polymorphism in PD pathogenesis, we derived dopaminergic neurons (DAn) from human-induced pluripotent stem cells (hiPSCs) reprogrammed from fibroblasts of PD patients harboring USP8D442G allele and their healthy siblings. In addition, we knock-in D442G polymorphic site into the endogenous USP8 gene of human embryonic stem cells (hESCs) and derived DAn from these knock-in hESCs to explore their cellular phenotypes and molecular mechanism. We found that expression of USP8D442G in DAn induces the accumulation and abnormal subcellular localization of α-Synuclein (α-Syn). Mechanistically, we demonstrate that D442G polymorphism enhances the interaction between α-Syn and USP8 and thus increases the K63-specific deubiquitination and stability of α-Syn . We discover a pathogenic polymorphism for PD that represent a promising therapeutic and diagnostic target for PD.

Different gene alterations in patients with non-small-cell lung cancer between the eastern and southern China

Geographical differences are conspicuous in lung cancer, and the distinct molecular features of lung tumor between Western patients and Asian patients have been demonstrated. However, the etiology of non-small-cell lung cancer (NSCLC) and the distribution of associated molecular aberrations in China have not been fully elucidated. The mutational profiles of 12 lung cancer-related genes were investigated in 85 patients from eastern China and 88 patients from southern China who had been histologically confirmed NSCLC. Overall, 93.6% (162/173) of tumor samples harbored at least one somatic alteration. The most frequently mutated genes were TP53 (56.1%), EGFR (50.3%), and KRAS (14.5%). We found that EGFR mutated much more frequently (60.0% vs 40.9%, P = 0.012) and TP53 mutations had significantly lower incidence (47.1% vs 64.8%, P = 0.019) in eastern cohort than that in southern cohort. Mutational signature analysis revealed a region-related mutagenesis mechanism characterized by a high prevalence of C to T transitions mainly occurring at CpG dinucleotides in southern patients. This study reveals the difference in the mutational features between NSCLC patients in eastern and southern China. The distinct patterns of gene mutation could provide clues for the mechanism of carcinogenesis of lung cancer, offering opportunities to stratify patients into optimal treatment plans based on genomic profiles.

Are epigenetic mechanisms and nutrition effective in male and female infertility?

This review discusses epigenetic mechanisms and the relationship of infertility in men and women in relation to parameters pertaining to nutrition. The prevalence of infertility worldwide is 8-12 %, and one out of every eight couples receives medical treatment. Epigenetic mechanisms, aging, environmental factors, dietary energy and nutrients and non-nutrient compounds; more or less energy intake, and methionine come into play in the occurrence of infertility. It also interacts with vitamins B12, D and B6, biotin, choline, selenium, zinc, folic acid, resveratrol, quercetin and similar factors. To understand the molecular mechanisms regulating the expression of genes that affect infertility, the environment, the role of genotype, age, health, nutrition and changes in the individual's epigenotype must first be considered. This will pave the way for the identification of the unknown causes of infertility. Insufficient or excessive intake of energy and certain macro and micronutrients may contribute to the occurrence of infertility as well. In addition, it is reported that 5-10 % of body weight loss, moderate physical activity and nutritional interventions for improvement in insulin sensitivity contribute to the development of fertility. Processes that pertain to epigenetics carry alterations which are inherited yet not encoded via the DNA sequence. Nutrition is believed to have an impact over the epigenetic mechanisms which are effective in the pathogenesis of several diseases like infertility. Epigenetic mechanisms of individuals with infertility are different from healthy individuals. Infertility is associated with epigenetic mechanisms, nutrients, bioactive components and numerous other factors.

Comparative Analysis of Tylosema esculentum Mitochondrial DNA Revealed Two Distinct Genome Structures

Tylosema esculentum, commonly known as the marama bean, is an underutilized legume with nutritious seeds, holding potential to enhance food security in southern Africa due to its resilience to prolonged drought and heat. To promote the selection of this agronomically valuable germplasm, this study assembled and compared the mitogenomes of 84 marama individuals, identifying variations in genome structure, single-nucleotide polymorphisms (SNPs), insertions/deletions (indels), heteroplasmy, and horizontal transfer. Two distinct germplasms were identified, and a novel mitogenome structure consisting of three circular molecules and one long linear chromosome was discovered. The structural variation led to an increased copy number of specific genes, nad5, nad9, rrnS, rrn5, trnC, and trnfM. The two mitogenomes also exhibited differences at 230 loci, with only one notable nonsynonymous substitution in the matR gene. Heteroplasmy was concentrated at certain loci on chromosome LS1 (OK638188). Moreover, the marama mitogenome contained an over 9 kb insertion of cpDNA, originating from chloroplast genomes, but had accumulated mutations and lost gene functionality. The evolutionary and comparative genomics analysis indicated that mitogenome divergence in marama might not be solely constrained by geographical factors. Additionally, marama, as a member from the Cercidoideae subfamily, tends to possess a more complete set of mitochondrial genes than Faboideae legumes.

Modeling a variant of unknown significance in the Drosophila ortholog of the human cardiogenic gene NKX2.5

Sequencing of human genome samples has unearthed genetic variants for which functional testing is necessary to validate their clinical significance. We used the Drosophila system to analyze a variant of unknown significance in the human congenital heart disease gene NKX2.5 (also known as NKX2-5). We generated an R321N allele of the NKX2.5 ortholog tinman (tin) to model a human K158N variant and tested its function in vitro and in vivo. The R321N Tin isoform bound poorly to DNA in vitro and was deficient in activating a Tin-dependent enhancer in tissue culture. Mutant Tin also showed a significantly reduced interaction with a Drosophila T-box cardiac factor named Dorsocross1. We generated a tinR321N allele using CRISPR/Cas9, for which homozygotes were viable and had normal heart specification, but showed defects in the differentiation of the adult heart that were exacerbated by further loss of tin function. We propose that the human K158N variant is pathogenic through causing a deficiency in DNA binding and a reduced ability to interact with a cardiac co-factor, and that cardiac defects might arise later in development or adult life.

Multi-landmark alignment of genomic signals reveals conserved expression patterns across transcription start sites

The prevalent one-dimensional alignment of genomic signals to a reference landmark is a cornerstone of current methods to study transcription and its DNA-dependent processes but it is prone to mask potential relations among multiple DNA elements. We developed a systematic approach to align genomic signals to multiple locations simultaneously by expanding the dimensionality of the genomic-coordinate space. We analyzed transcription in human and uncovered a complex dependence on the relative position of neighboring transcription start sites (TSSs) that is consistently conserved among cell types. The dependence ranges from enhancement to suppression of transcription depending on the relative distances to the TSSs, their intragenic position, and the transcriptional activity of the gene. Our results reveal a conserved hierarchy of alternative TSS usage within a previously unrecognized level of genomic organization and provide a general methodology to analyze complex functional relationships among multiple types of DNA elements.

Applications of advanced technologies for detecting genomic structural variation

Chromosomal structural variation (SV) encompasses a heterogenous class of genetic variants that exerts strong influences on human health and disease. Despite their importance, many structural variants (SVs) have remained poorly characterized at even a basic level, a discrepancy predicated upon the technical limitations of prior genomic assays. However, recent advances in genomic technology can identify and localize SVs accurately, opening new questions regarding SV risk factors and their impacts in humans. Here, we first define and classify human SVs and their generative mechanisms, highlighting characteristics leveraged by various SV assays. We next examine the first-ever gapless assembly of the human genome and the technical process of assembling it, which required third-generation sequencing technologies to resolve structurally complex loci. The new portions of that "telomere-to-telomere" and subsequent pangenome assemblies highlight aspects of SV biology likely to develop in the near-term. We consider the strengths and limitations of the most promising new SV technologies and when they or longstanding approaches are best suited to meeting salient goals in the study of human SV in population-scale genomics research, clinical, and public health contexts. It is a watershed time in our understanding of human SV when new approaches are expected to fundamentally change genomic applications.

Using Drosophila to model a variant of unknown significance in the human cardiogenic gene Nkx2.5

Sequencing of human genome samples has unearthed genetic variants for which functional testing is necessary to validate their clinical significance. We used the Drosophila system to analyze a variant of unknown significance in the human congenital heart disease gene, Nkx2 . 5 . We generated an R321N allele of the Nkx2 . 5 ortholog tinman ( tin ) to model a human K158N variant and tested its function in vitro and in vivo. The R321N Tin isoform bound poorly to DNA in vitro and was deficient in activating a Tin-dependent enhancer in tissue culture. Mutant Tin also showed a significantly reduced interaction with a Drosophila Tbox cardiac factor named Dorsocross1. We generated a tin R321N allele using CRISPR/Cas9, for which homozygotes were viable and had normal heart specification, but showed defects in the differentiation of the adult heart that were exacerbated by further loss of tin function. We conclude that the human K158N mutation is likely pathogenic through causing both a deficiency in DNA binding and a reduced ability to interact with a cardiac cofactor, and that cardiac defects might arise later in development or adult life.

Analysis of Clinical Laboratory Detecting Challenging Variants from Exome Sequencing Using Simulated Patient-Parent Trio Sample: Pilot Study for Neurodevelopmental Disorder de Novo Variants

To date, there has been no systematic analysis for the clinical laboratory in detecting technically challenging variants using the trio-based exome sequencing (ES) approach. Here, we present an interlaboratory pilot proficiency testing study that used synthetic patient-parent specimens to assess the detection of challenging variants with de novo dominant inheritance modes for neurodevelopmental disorders using various trio-based ES. In total, 27 clinical laboratories that performed diagnostic exome analyses participated in the survey. One of the 26 challenging variants was identified by all laboratories, whereas all 26 variants were identified by only nine laboratories. The lack of identification of mosaic variants was often due to the bioinformatics analysis that excluded the variant. For missing intended heterozygous variants, probable root causes were related to the technical bioinformatics pipeline and variant interpretation and reporting. For each missing variant, there may be more than one probable reason from the different laboratories. There was considerable variation in interlaboratory performance for detecting challenging variants using trio-based ES. This finding may have important implications for the design and validation of tests for different variant types in clinical laboratories, especially for technically challenging variants, and necessary workflow modification can potentially improve trio-based ES performance.

Candidate SNP Markers Significantly Altering the Affinity of TATA-Binding Protein for the Promoters of Human Hub Genes for Atherogenesis, Atherosclerosis and Atheroprotection

Atherosclerosis is a systemic disease in which focal lesions in arteries promote the build-up of lipoproteins and cholesterol they are transporting. The development of atheroma (atherogenesis) narrows blood vessels, reduces the blood supply and leads to cardiovascular diseases. According to the World Health Organization (WHO), cardiovascular diseases are the leading cause of death, which has been especially boosted since the COVID-19 pandemic. There is a variety of contributors to atherosclerosis, including lifestyle factors and genetic predisposition. Antioxidant diets and recreational exercises act as atheroprotectors and can retard atherogenesis. The search for molecular markers of atherogenesis and atheroprotection for predictive, preventive and personalized medicine appears to be the most promising direction for the study of atherosclerosis. In this work, we have analyzed 1068 human genes associated with atherogenesis, atherosclerosis and atheroprotection. The hub genes regulating these processes have been found to be the most ancient. In silico analysis of all 5112 SNPs in their promoters has revealed 330 candidate SNP markers, which statistically significantly change the affinity of the TATA-binding protein (TBP) for these promoters. These molecular markers have made us confident that natural selection acts against underexpression of the hub genes for atherogenesis, atherosclerosis and atheroprotection. At the same time, upregulation of the one for atheroprotection promotes human health.

Genomic distribution and polymorphism of G-quadruplex motifs occupying ovine promoters and enhancers

G-quadruplexes are non-canonical DNA structures that are formed in regions with short runs of guanines. During the last decade they have gained considerable attention due to their involvement in basic cellular processes, linking them to several physiological processes and pathological conditions. Regulation of gene transcription is among the crucial roles that G-quadruplexes play in the cells. Several ways in which these structures affect transcription have been described, both negatively and positively. Recently, G-quadruplexes have been shown to be implicated in the three-dimensional rearrangement of the chromosomes that enables the interaction of enhancers and gene promoters during regulation of transcription. Sheep is a species for which almost no G-quadruplex-related studies have been conducted and thus research on this species is kept out from the progress that has been made in the G-quadruplex field. In this context, we investigated the DNA sequences with potential to form G-quadruplexes (G4-motifs) in the ovine enhancers and promoters. We describe the distribution of G4-motifs within the regulatory regions which is shown to be enriched in G4-motifs in a way similar to other mammals. Furthermore, our data suggest that G4-motifs promote promoter-enhancer interactions in sheep. The single nucleotide polymorphisms colocalizing with promoter- and enhancer-associated ovine G4-motifs constitute a considerable pool of polymorphism and given the crucial role of these specific G4-motifs on regulation of transcription, we suggest this polymorphism as an interesting target for ovine genetic studies.

Genetic Testing in Clinical Movement Disorders: A Case-Based Review

Genetics are fundamental to understanding the pathophysiology of neurological disease, including movement disorders. Genetic testing in clinical practice has changed dramatically over the last few decades. While the likelihood of establishing an etiological diagnosis is greater now with increased access to testing and more advanced technologies, clinicians face challenges when deciding whether to test, then selecting the appropriate test, and ultimately interpreting and sharing the results with patients and families. In this review, we use a case-based approach to cover core aspects of genetic testing for the neurologist, namely, genetic testing in Parkinson's disease, interpretation of inconclusive genetic test reports, and genetic testing for repeat expansion disorders using Huntington disease as a prototype.

The cancer-risk variant frequency among Polish population reported by the first national whole-genome sequencing study

Introduction

Population-based cancer screening has raised many controversies in recent years, not only regarding the costs but also regarding the ethical nature and issues related to variant interpretation. Nowadays, genetic cancer screening standards are different in every country and usually encompass only individuals with a personal or family history of relevant cancer.

Methods

Here we performed a broad genetic screening for cancer-related rare germline variants on population data from the Thousand Polish Genomes database based on 1076 Polish unrelated individuals that underwent whole genome sequencing (WGS).

Results

We identified 19 551 rare variants in 806 genes related to oncological diseases, among them 89% have been located in non-coding regions. The combined BRCA1/BRCA2 pathogenic/likely pathogenic according to ClinVar allele frequency in the unselected population of 1076 Poles was 0.42%, corresponding to nine carriers.

Discussion

Altogether, on the population level, we found especially problematic the assessment of the pathogenicity of variants and the relation of ACMG guidelines to the population frequency. Some of the variants may be overinterpreted as disease-causing due to their rarity or lack of annotation in the databases. On the other hand, some relevant variants may have been overseen given that there is little pooled population whole genome data on oncology. Before population WGS screening will become a standard, further studies are needed to assess the frequency of the variants suspected to be pathogenic on the population level and with reporting of likely benign variants.

WGS Data Collections: How Do Genomic Databases Transform Medicine?

As a scientific community we assumed that exome sequencing will elucidate the basis of most heritable diseases. However, it turned out it was not the case; therefore, attention has been increasingly focused on the non-coding sequences that encompass 98% of the genome and may play an important regulatory function. The first WGS-based datasets have already been released including underrepresented populations. Although many databases contain pooled data from several cohorts, recently the importance of local databases has been highlighted. Genomic databases are not only collecting data but may also contribute to better diagnostics and therapies. They may find applications in population studies, rare diseases, oncology, pharmacogenetics, and infectious and inflammatory diseases. Further data may be analysed with Al technologies and in the context of other omics data. To exemplify their utility, we put a highlight on the Polish genome database and its practical application.

Metagenomic analysis of viral genes integrated in whole genome sequencing data of Thai patients with Brugada syndrome

Brugada syndrome (BS) is an autosomal dominant inheritance cardiac arrhythmia disorder associated with sudden death in young adults. Thailand has the highest prevalence of BS worldwide, and over 60% of patients with BS still have unclear disease etiology. Here, we performeda new viral metagenome analysis pipeline called VIRIN and validated it with whole genome sequencing (WGS) data of HeLa cell lines and hepatocellular carcinoma. Then the VIRIN pipelinewas applied to identify viral integration positions from unmapped WGS data of Thai males, including 100 BS patients (case) and 100 controls. Even though the sample preparation had noviral enrichment step, we can identify several virus genes from our analysis pipeline. The predominance of human endogenous retrovirus K (HERV-K) viruses was found in both cases andcontrols by blastn and blastx analysis. This study is the first report on the full-length HERV-Kassembled genomes in the Thai population. Furthermore, the HERV-K integration breakpointpositions were validated and compared between the case and control datasets. Interestingly,Brugada cases contained HERV-K integration breakpoints at promoters five times more oftenthan controls. Overall, the highlight of this study is the BS-specific HERV-K breakpoint positionsthat were found at the gene coding region "NBPF11" (n = 9), "NBPF12" (n = 8) and longnon-coding RNA (lncRNA) "PCAT14" (n = 4) region. The genes and the lncRNA have been reported to be associated with congenital heart and arterial diseases. These findings provide another aspect of the BS etiology associated with viral genome integrations within the humangenome.

Current challenges in understanding the role of enhancers in disease

Enhancers play a central role in the spatiotemporal control of gene expression and tend to work in a cell-type-specific manner. In addition, they are suggested to be major contributors to phenotypic variation, evolution and disease. There is growing evidence that enhancer dysfunction due to genetic, structural or epigenetic mechanisms contributes to a broad range of human diseases referred to as enhanceropathies. Such mechanisms often underlie the susceptibility to common diseases, but can also play a direct causal role in cancer or Mendelian diseases. Despite the recent gain of insights into enhancer biology and function, we still have a limited ability to predict how enhancer dysfunction impacts gene expression. Here we discuss the major challenges that need to be overcome when studying the role of enhancers in disease etiology and highlight opportunities and directions for future studies, aiming to disentangle the molecular basis of enhanceropathies.

Disease-associated human genetic variation through the lens of precursor and mature RNA structure

Disease-associated variants (DAVs) are commonly considered either through a genomic lens that describes variant function at the DNA level, or at the protein function level if the variant is translated. Although the genomic and proteomic effects of variation are well-characterized, genetic variants disrupting post-transcriptional regulation is another mechanism of disease that remains understudied. Specific RNA sequence motifs mediate post-transcriptional regulation both in the nucleus and cytoplasm of eukaryotic cells, often by binding to RNA-binding proteins or other RNAs. However, many DAVs map far from these motifs, which suggests deeper layers of post-transcriptional mechanistic control. Here, we consider a transcriptomic framework to outline the importance of post-transcriptional regulation as a mechanism of disease-causing single-nucleotide variation in the human genome. We first describe the composition of the human transcriptome and the importance of abundant yet overlooked components such as introns and untranslated regions (UTRs) of messenger RNAs (mRNAs). We present an analysis of Human Gene Mutation Database variants mapping to mRNAs and examine the distribution of causative disease-associated variation across the transcriptome. Although our analysis confirms the importance of post-transcriptional regulatory motifs, a majority of DAVs do not directly map to known regulatory motifs. Therefore, we review evidence that regions outside these well-characterized motifs can regulate function by RNA structure-mediated mechanisms in all four elements of an mRNA: exons, introns, 5' and 3' UTRs. To this end, we review published examples of riboSNitches, which are single-nucleotide variants that result in a change in RNA structure that is causative of the disease phenotype. In this review, we present the current state of knowledge of how DAVs act at the transcriptome level, both through altering post-transcriptional regulatory motifs and by the effects of RNA structure.

High-coverage whole-genome sequencing of the expanded 1000 Genomes Project cohort including 602 trios

The 1000 Genomes Project (1kGP) is the largest fully open resource of whole-genome sequencing (WGS) data consented for public distribution without access or use restrictions. The final, phase 3 release of the 1kGP included 2,504 unrelated samples from 26 populations and was based primarily on low-coverage WGS. Here, we present a high-coverage 3,202-sample WGS 1kGP resource, which now includes 602 complete trios, sequenced to a depth of 30X using Illumina. We performed single-nucleotide variant (SNV) and short insertion and deletion (INDEL) discovery and generated a comprehensive set of structural variants (SVs) by integrating multiple analytic methods through a machine learning model. We show gains in sensitivity and precision of variant calls compared to phase 3, especially among rare SNVs as well as INDELs and SVs spanning frequency spectrum. We also generated an improved reference imputation panel, making variants discovered here accessible for association studies.

CMDB: the comprehensive population genome variation database of China

A high-quality genome variation database derived from a large-scale population is one of the most important infrastructures for genomics, clinical and translational medicine research. Here, we developed the Chinese Millionome Database (CMDB), a database that contains 9.04 million single nucleotide variants (SNV) with allele frequency information derived from low-coverage (0.06×-0.1×) whole-genome sequencing (WGS) data of 141 431 unrelated healthy Chinese individuals. These individuals were recruited from 31 out of the 34 administrative divisions in China, covering Han and 36 other ethnic minorities. CMDB, housing the WGS data of a multi-ethnic Chinese population featuring wide geographical distribution, has become the most representative and comprehensive Chinese population genome database to date. Researchers can quickly search for variant, gene or genomic regions to obtain the variant information, including mutation basic information, allele frequency, genic annotation and overview of frequencies in global populations. Furthermore, the CMDB also provides information on the association of the variants with a range of phenotypes, including height, BMI, maternal age and twin pregnancy. Based on these data, researchers can conduct meta-analysis of related phenotypes. CMDB is freely available at https://db.cngb.org/cmdb/.

Towards generalizable predictions for G protein-coupled receptor variant expression

Missense mutations that compromise the plasma membrane expression (PME) of integral membrane proteins are the root cause of numerous genetic diseases. Differentiation of this class of mutations from those that specifically modify the activity of the folded protein has proven useful for the development and targeting of precision therapeutics. Nevertheless, it remains challenging to predict the effects of mutations on the stability and/ or expression of membrane proteins. In this work, we utilize deep mutational scanning data to train a series of artificial neural networks to predict the PME of transmembrane domain variants of G protein-coupled receptors from structural and/ or evolutionary features. We show that our best-performing network, which we term the PME predictor, can recapitulate mutagenic trends within rhodopsin and can differentiate pathogenic transmembrane domain variants that cause it to misfold from those that compromise its signaling. This network also generates statistically significant predictions for the relative PME of transmembrane domain variants for another class A G protein-coupled receptor (β₂ adrenergic receptor) but not for an unrelated voltage-gated potassium channel (KCNQ1). Notably, our analyses of these networks suggest structural features alone are generally sufficient to recapitulate the observed mutagenic trends. Moreover, our findings imply that networks trained in this manner may be generalizable to proteins that share a common fold. Implications of our findings for the design of mechanistically specific genetic predictors are discussed.

Target-Sequencing of Female Infertility Pathogenic Gene Panel and a Novel TUBB8 Loss-of-Function Mutation

Genetic screening is an important approach for etiology determination and helps to optimize administration protocols in reproductive centers. After the first pathogenic gene of female infertility was reported in 2016, more and more new pathogenic genes were discovered, and we sought to develop an efficient and cost-effective method for genetic screening in patients. In this study, we designed a target-sequencing panel with 22 female infertility-related genes, namely, TUBB8, PATL2, WEE2, and PANX1 and sequenced 68 primary infertility (PI) and recurrent pregnancy loss (RPL) patients. We sequenced 68 samples reaching an average depth of 1559× and detected 3,134 variants. Among them, 62.2% were synonymous single-nucleotide variants (SNVs) and 36.3% were non-synonymous SNVs. The remaining 1.5% are indels (insertions and deletions) and stop-gains. DNAH11 and TUBB8 are the two genes that mutated most frequently. We also found a novel TUBB8 variant (c.898_900del; p.300_300del), proved its loss-of-function mechanism, and profiled the interactome of the wild-type (WT) and mutant TUBB8 proteins. Overall, this target-sequencing method provides an efficient and cost-effective approach for screening in IVF clinics and will support researchers for the discovery of new pathogenic variants.

MiRLog and dbmiR: prioritization and functional annotation tools to study human microRNA sequence variants

The recent identification of noncoding variants with pathogenic effects suggests that these variations could underlie a significant number of undiagnosed cases. Several computational methods have been developed to predict the functional impact of noncoding variants, but they exhibit only partial concordance and are not integrated with functional annotation resources, making the interpretation of these variants still challenging. MicroRNAs (miRNAs) are small noncoding RNA molecules that act as fine regulators of gene expression and play crucial functions in several biological processes, such as cell proliferation and differentiation. An increasing number of studies demonstrate a significant impact of miRNA single nucleotide variants (SNVs) both in Mendelian diseases and complex traits. To predict the functional effect of miRNA SNVs, we implemented a new meta‐predictor, MiRLog, and we integrated it into a comprehensive database, dbmiR, which includes a precompiled list of all possible miRNA allelic SNVs, providing their biological annotations at nucleotide and miRNA levels. MiRLog and dbmiR were used to explore the genetic variability of miRNAs in 15,708 human genomes included in the gnomAD project, finding several ultra‐rare SNVs with a potentially deleterious effect on miRNA biogenesis and function representing putative contributors to human phenotypes.

Challenging the utility of polygenic scores for social science: Environmental confounding, downward causation, and unknown biology

The sociogenomics revolution is upon us, we are told. Whether revolutionary or not, sociogenomics is poised to flourish given the ease of incorporating polygenic scores (or PGSs) as "genetic propensities" for complex traits into social science research. Pointing to evidence of ubiquitous heritability and the accessibility of genetic data, scholars have argued that social scientists not only have an opportunity but a duty to add PGSs to social science research. Social science research that ignores genetics is, some proponents argue, at best partial and likely scientifically flawed, misleading, and wasteful. Here, I challenge arguments about the value of genetics for social science and with it the claimed necessity of incorporating PGSs into social science models as measures of genetic influences. In so doing, I discuss the impracticability of distinguishing genetic influences from environmental influences because of non-causal gene-environment correlations, especially population stratification, familial confounding, and downward causation. I explain how environmental effects masquerade as genetic influences in PGSs, which undermines their raison d'être as measures of genetic propensity, especially for complex socially contingent behaviors that are the subject of sociogenomics. Additionally, I draw attention to the partial, unknown biology, while highlighting the persistence of an implicit, unavoidable reductionist genes versus environments approach. Leaving sociopolitical and ethical concerns aside, I argue that the potential scientific rewards of adding PGSs to social science are few and greatly overstated and the scientific costs, which include obscuring structural disadvantages and cultural influences, outweigh these meager benefits for most social science applications.

Familial long-read sequencing increases yield of de novo mutations

Studies of de novo mutation (DNM) have typically excluded some of the most repetitive and complex regions of the genome because these regions cannot be unambiguously mapped with short-read sequencing data. To better understand the genome-wide pattern of DNM, we generated long-read sequence data from an autism parent-child quad with an affected female where no pathogenic variant had been discovered in short-read Illumina sequence data. We deeply sequenced all four individuals by using three sequencing platforms (Illumina, Oxford Nanopore, and Pacific Biosciences) and three complementary technologies (Strand-seq, optical mapping, and 10X Genomics). Using long-read sequencing, we initially discovered and validated 171 DNMs across two children-a 20% increase in the number of de novo single-nucleotide variants (SNVs) and indels when compared to short-read callsets. The number of DNMs further increased by 5% when considering a more complete human reference (T2T-CHM13) because of the recovery of events in regions absent from GRCh38 (e.g., three DNMs in heterochromatic satellites). In total, we validated 195 de novo germline mutations and 23 potential post-zygotic mosaic mutations across both children; the overall true substitution rate based on this integrated callset is at least 1.41 × 10^-8 substitutions per nucleotide per generation. We also identified six de novo insertions and deletions in tandem repeats, two of which represent structural variants. We demonstrate that long-read sequencing and assembly, especially when combined with a more complete reference genome, increases the number of DNMs by >25% compared to previous studies, providing a more complete catalog of DNM compared to short-read data alone.

Whole-genome sequencing of 1,171 elderly admixed individuals from São Paulo, Brazil

As whole-genome sequencing (WGS) becomes the gold standard tool for studying population genomics and medical applications, data on diverse non-European and admixed individuals are still scarce. Here, we present a high-coverage WGS dataset of 1,171 highly admixed elderly Brazilians from a census-based cohort, providing over 76 million variants, of which ~2 million are absent from large public databases. WGS enables identification of ~2,000 previously undescribed mobile element insertions without previous description, nearly 5 Mb of genomic segments absent from the human genome reference, and over 140 alleles from HLA genes absent from public resources. We reclassify and curate pathogenicity assertions for nearly four hundred variants in genes associated with dominantly-inherited Mendelian disorders and calculate the incidence for selected recessive disorders, demonstrating the clinical usefulness of the present study. Finally, we observe that whole-genome and HLA imputation could be significantly improved compared to available datasets since rare variation represents the largest proportion of input from WGS. These results demonstrate that even smaller sample sizes of underrepresented populations bring relevant data for genomic studies, especially when exploring analyses allowed only by WGS.

Whole genome sequencing (WGS) data on non-European and admixed individuals remains scarce. Here, the authors analyse WGS data from 1,171 admixed elderly Brazilians from a census cohort, characterising population-specific genetic variation and exploring the clinical utility of this expanded dataset.

Landscape of adenosine-to-inosine RNA recoding across human tissues

RNA editing by adenosine deaminases changes the information encoded in the mRNA from its genomic blueprint. Editing of protein-coding sequences can introduce novel, functionally distinct, protein isoforms and diversify the proteome. The functional importance of a few recoding sites has been appreciated for decades. However, systematic methods to uncover these sites perform poorly, and the full repertoire of recoding in human and other mammals is unknown. Here we present a new detection approach, and analyze 9125 GTEx RNA-seq samples, to produce a highly-accurate atlas of 1517 editing sites within the coding region and their editing levels across human tissues. Single-cell RNA-seq data shows protein recoding contributes to the variability across cell subpopulations. Most highly edited sites are evolutionary conserved in non-primate mammals, attesting for adaptation. This comprehensive set can facilitate understanding of the role of recoding in human physiology and diseases.

Gabay et al. provide a highly-accurate atlas of recoding by A-to-I RNA editing in human, profiled across tissues and cell subpopulations. Most highly edited sites are evolutionary conserved in non-primate mammals, attesting for adaptation.

Clinical validation of genomic functional screen data: analysis of observed BRCA1 variants in an unselected population cohort

Functional assessment of genomic variants provides a promising approach to systematically examine the potential pathogenicity of variants independent of associated clinical data. However, making such conclusions requires validation with appropriate clinical findings. To this end, here, we use variant calls from exome data and BRCA1-related cancer diagnoses from electronic health records to demonstrate an association between published laboratory-based functional designations of BRCA1 variants and BRCA1-related cancer diagnoses in an unselected cohort of patient-participants. These findings validate and support further exploration of functional assay data to better understand the pathogenicity of rare variants. This information may be valuable in the context of healthy population genomic screening, where many rare, potentially pathogenic variants may not have sufficient associated clinical data to inform their interpretation directly.

What sequencing technologies can teach us about innate immunity

For years, we have taken a reductionist approach to understanding gene regulation through the study of one gene in one cell at a time. While this approach has been fruitful it is laborious and fails to provide a global picture of what is occurring in complex situations involving tightly coordinated immune responses. The emergence of whole-genome techniques provides a system-level view of a response and can provide a plethora of information on events occurring in a cell from gene expression changes to splicing changes and chemical modifications. As with any technology, this often results in more questions than answers, but this wealth of knowledge is providing us with an unprecedented view of what occurs inside our cells during an immune response. In this review, we will discuss the current RNA-sequencing technologies and what they are helping us learn about the innate immune system.

Molecular basis for the evolved instability of a human G-protein coupled receptor

Membrane proteins are prone to misfolding and degradation. This is particularly true for mammalian forms of the gonadotropin-releasing hormone receptor (GnRHR). Although they function at the plasma membrane, mammalian GnRHRs accumulate within the secretory pathway. Their apparent instability is believed to have evolved through selection for attenuated GnRHR activity. Nevertheless, the molecular basis of this adaptation remains unclear. We show that adaptation coincides with a C-terminal truncation that compromises the translocon-mediated membrane integration of its seventh transmembrane domain (TM7). We also identify a series of polar residues in mammalian GnRHRs that compromise the membrane integration of TM2 and TM6. Reverting a lipid-exposed polar residue in TM6 to an ancestral hydrophobic residue restores expression with no impact on function. Evolutionary trends suggest variations in the polarity of this residue track with reproductive phenotypes. Our findings suggest that the marginal energetics of cotranslational folding can be exploited to tune membrane protein fitness.

Integral membrane proteins are prone to misfolding, especially mammalian gonadotropin-releasing hormone receptors (GnRHRs). Chamness et al. show that the evolved instability of mammalian GnRHRs stems from adaptive modifications that disrupt translocon-mediated membrane integration, suggesting that membrane protein misfolding can be exploited to tune fitness.

Population-scale detection of non-reference sequence variants using colored de Bruijn graphs

MOTIVATION

With the increasing throughput of sequencing technologies, structural variant (SV) detection has become possible across tens of thousands of genomes. Non-reference sequence (NRS) variants have drawn less attention compared with other types of SVs due to the computational complexity of detecting them. When using short-read data, the detection of NRS variants inevitably involves a de novo assembly which requires high-quality sequence data at high coverage. Previous studies have demonstrated how sequence data of multiple genomes can be combined for the reliable detection of NRS variants. However, the algorithms proposed in these studies have limited scalability to larger sets of genomes.

RESULTS

We introduce PopIns2, a tool to discover and characterize NRS variants in many genomes, which scales to considerably larger numbers of genomes than its predecessor PopIns. In this article, we briefly outline the PopIns2 workflow and highlight our novel algorithmic contributions. We developed an entirely new approach for merging contig assemblies of unaligned reads from many genomes into a single set of NRS using a colored de Bruijn graph. Our tests on simulated data indicate that the new merging algorithm ranks among the best approaches in terms of quality and reliability and that PopIns2 shows the best precision for a growing number of genomes processed. Results on the Polaris Diversity Cohort and a set of 1000 Icelandic human genomes demonstrate unmatched scalability for the application on population-scale datasets.

AVAILABILITY AND IMPLEMENTATION

The source code of PopIns2 is available from https://github.com/kehrlab/PopIns2.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Transcriptomics and sequencing analysis of gene expression profiling for major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is a common psychiatric disorder characterized by constant sadness and a lack of interest in work and social interactions. Maintaining the transcriptome levels via the controlled regulation of mRNA processing and transport is essential to alleviating MDD. Various molecular phenotypes such as aberrant RNA splicing and stability are identified as critical determinants of MDD.

AIM

This study aims to compare the mRNA expression profiles between major depressive disorder non-suicide (MDD), major depressive disorder suicide (MDD-S), and control groups using RNA-Seq.

MATERIALS AND METHODS

A transcriptomics and sequencing analysis of gene expression profiling was conducted in 9 patients with MDD, 10 patients with MDD-S, and 10 control patients.

RESULTS

A comparison of the sample groups revealed that the PRKACB gene was upregulated in patients with MDD. At the same time, GRM3, DLGAP1, and GRIA2 were downregulated in these patients-these genes are majorly involved in the glutamatergic pathway. Five genes (GRIA1, CAMK2D, PPP3CA, MAPK10, and PPP2R2A) of the dopaminergic pathway were downregulated in patients with the MDD-S condition when compared with the MDD and control groups. Cholinergic synapses were altered in patients with MDD when compared to the control group due to the presence of dysregulated genes (KCNQ5, PLCB4, ADCY9, CAMK2D, PIK3CA, and GNG2).

CONCLUSION

The results provide a new understanding of the etiology of depression in humans and identify probable depression-associated biomarkers.

The intronic branch point sequence is under strong evolutionary constraint in the bovine and human genome

The branch point sequence is a cis-acting intronic motif required for mRNA splicing. Despite their functional importance, branch point sequences are not routinely annotated. Here we predict branch point sequences in 179,476 bovine introns and investigate their variability using a catalogue of 29.4 million variants detected in 266 cattle genomes. We localize the bovine branch point within a degenerate heptamer "nnyTrAy". An adenine residue at position 6, that acts as branch point, and a thymine residue at position 4 of the heptamer are more strongly depleted for mutations than coding sequences suggesting extreme purifying selection. We provide evidence that mutations affecting these evolutionarily constrained residues lead to alternative splicing. We confirm evolutionary constraints on branch point sequences using a catalogue of 115 million SNPs established from 3,942 human genomes of the gnomAD database.

Comparison of sequencing data processing pipelines and application to underrepresented African human populations

Background

Population genetic studies of humans make increasing use of high-throughput sequencing in order to capture diversity in an unbiased way. There is an abundance of sequencing technologies, bioinformatic tools and the available genomes are increasing in number. Studies have evaluated and compared some of these technologies and tools, such as the Genome Analysis Toolkit (GATK) and its “Best Practices” bioinformatic pipelines. However, studies often focus on a few genomes of Eurasian origin in order to detect technical issues. We instead surveyed the use of the GATK tools and established a pipeline for processing high coverage full genomes from a diverse set of populations, including Sub-Saharan African groups, in order to reveal challenges from human diversity and stratification.

Results

We surveyed 29 studies using high-throughput sequencing data, and compared their strategies for data pre-processing and variant calling. We found that processing of data is very variable across studies and that the GATK “Best Practices” are seldom followed strictly. We then compared three versions of a GATK pipeline, differing in the inclusion of an indel realignment step and with a modification of the base quality score recalibration step. We applied the pipelines on a diverse set of 28 individuals. We compared the pipelines in terms of count of called variants and overlap of the callsets. We found that the pipelines resulted in similar callsets, in particular after callset filtering. We also ran one of the pipelines on a larger dataset of 179 individuals. We noted that including more individuals at the joint genotyping step resulted in different counts of variants. At the individual level, we observed that the average genome coverage was correlated to the number of variants called.

Conclusions

We conclude that applying the GATK “Best Practices” pipeline, including their recommended reference datasets, to underrepresented populations does not lead to a decrease in the number of called variants compared to alternative pipelines. We recommend to aim for coverage of > 30X if identifying most variants is important, and to work with large sample sizes at the variant calling stage, also for underrepresented individuals and populations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04407-x.

The Need for a Human Pangenome Reference Sequence

The reference human genome sequence is inarguably the most important and widely used resource in the fields of human genetics and genomics. It has transformed the conduct of biomedical sciences and brought invaluable benefits to the understanding and improvement of human health. However, the commonly used reference sequence has profound limitations, because across much of its span, it represents the sequence of just one human haplotype. This single, monoploid reference structure presents a critical barrier to representing the broad genomic diversity in the human population. In this review, we discuss the modernization of the reference human genome sequence to a more complete reference of human genomic diversity, known as a human pangenome.

Digital Twins: From Personalised Medicine to Precision Public Health

A digital twin is a virtual model of a physical entity, with dynamic, bi-directional links between the physical entity and its corresponding twin in the digital domain. Digital twins are increasingly used today in different industry sectors. Applied to medicine and public health, digital twin technology can drive a much-needed radical transformation of traditional electronic health/medical records (focusing on individuals) and their aggregates (covering populations) to make them ready for a new era of precision (and accuracy) medicine and public health. Digital twins enable learning and discovering new knowledge, new hypothesis generation and testing, and in silico experiments and comparisons. They are poised to play a key role in formulating highly personalised treatments and interventions in the future. This paper provides an overview of the technology's history and main concepts. A number of application examples of digital twins for personalised medicine, public health, and smart healthy cities are presented, followed by a brief discussion of the key technical and other challenges involved in such applications, including ethical issues that arise when digital twins are applied to model humans.

Discovery of genomic variation across a generation

Over the past 30 years (the timespan of a generation), advances in genomics technologies have revealed tremendous and unexpected variation in the human genome and have provided increasingly accurate answers to long-standing questions of how much genetic variation exists in human populations and to what degree the DNA complement changes between parents and offspring. Tracking the characteristics of these inherited and spontaneous (or de novo) variations has been the basis of the study of human genetic disease. From genome-wide microarray and next-generation sequencing scans, we now know that each human genome contains over 3 million single nucleotide variants when compared with the ~ 3 billion base pairs in the human reference genome, along with roughly an order of magnitude more DNA—approximately 30 megabase pairs (Mb)—being ‘structurally variable’, mostly in the form of indels and copy number changes. Additional large-scale variations include balanced inversions (average of 18 Mb) and complex, difficult-to-resolve alterations. Collectively, ~1% of an individual’s genome will differ from the human reference sequence. When comparing across a generation, fewer than 100 new genetic variants are typically detected in the euchromatic portion of a child’s genome. Driven by increasingly higher-resolution and higher-throughput sequencing technologies, newer and more accurate databases of genetic variation (for instance, more comprehensive structural variation data and phasing of combinations of variants along chromosomes) of worldwide populations will emerge to underpin the next era of discovery in human molecular genetics.

African Global Representation in Biomedical Sciences

African populations are diverse in their ethnicity, language, culture, and genetics. Although plagued by high disease burdens, until recently the continent has largely been excluded from biomedical studies. Along with limitations in research and clinical infrastructure, human capacity, and funding, this omission has resulted in an underrepresentation of African data and disadvantaged African scientists. This review interrogates the relative abundance of biomedical data from Africa, primarily in genomics and other omics. The visibility of African science through publications is also discussed. A challenge encountered in this review is the relative lack of annotation of data on their geographical or population origin, with African countries represented as a single group. In addition to the abovementioned limitations,the global representation of African data may also be attributed to the hesitation to deposit data in public repositories. Whatever the reason, the disparity should be addressed, as African data have enormous value for scientists in Africa and globally.

Onco-fertility and personalized testing for potential for loss of ovarian reserve in patients undergoing chemotherapy: proposed next steps for development of genetic testing to predict changes in ovarian reserve

Women of reproductive age undergoing chemotherapy face the risk of irreversible ovarian insufficiency. Current methods of ovarian reserve testing do not accurately predict future reproductive potential for patients undergoing chemotherapy. Genetic markers that more accurately predict the reproductive potential of each patient undergoing chemotherapy would be critical tools that would be useful for evidence-based fertility preservation counselling. To assess the possible approaches to take to develop personalized genetic testing for these patients, we review current literature regarding mechanisms of ovarian damage due to chemotherapy and genetic variants associated with both the damage mechanisms and primary ovarian insufficiency. The medical literature point to a number of genetic variants associated with mechanisms of ovarian damage and primary ovarian insufficiency. Those variants that appear at a higher frequency, with known pathways, may be considered as potential genetic markers for predictive ovarian reserve testing. We propose developing personalized testing of the potential for loss of ovarian function for patients with cancer, prior to chemotherapy treatment. There are advantages of using genetic markers complementary to the current ovarian reserve markers of AMH, antral follicle count and day 3 FSH as predictors of preservation of fertility after chemotherapy. Genetic markers will help identify upstream pathways leading to high risk of ovarian failure not detected by present clinical markers. Their predictive value is mechanism-based and will encourage research towards understanding the multiple pathways contributing to ovarian failure after chemotherapy.