Next Generation Sequencing of Pooled Samples: Guideline for Variants' Filtering

Variation for QTL alleles associated with total dissolved solids among crop types in a GWAS of a Beta vulgaris diversity panel

Sweetness is a main component of the table beet (Beta vulgaris L.) flavor profile and a key determinant of its market success for fresh consumption. Total dissolved solids (TDS) is a proxy for sugar content in produce and are easily measured through a refractometer, making TDS valuable in breeding programs focused on increasing sweetness. A diversity panel of 238 accessions from the Beta vulgaris crop complex and wild relatives was assembled and genotyped using genotyping-by-sequencing, yielding 10,237 single nucleotide polymorphisms (SNPs) from 226 full panel accessions and 9,847 SNPs from table beet only accessions after filtering. The panel was phenotyped in field trials over 2 years and mean values were adjusted using best linear unbiased estimates. TDS levels varied among crop types and a broad-sense heritability of 0.90 indicated that phenotypic differences can be attributed in large part to genetic variation. A genome-wide association study (GWAS) uncovered four quantitative trait loci (QTLs) identified across multiple models to significantly associate with TDS. A QTL on chromosome 2 was consistently identified among GWAS models, explaining 12.1%-62.6% of the phenotypic variation in the full panel. Bevul.2G176300, a gene directly involved in the sucrose biosynthesis pathway, was located downstream the significant marker. A second QTL identified on chromosome 7 revealed QTL alleles that may differentiate between table beet accessions, explaining nearly half the phenotypic variation, and is the first QTL reported in association with TDS unique to table beet. The QTL described can be used to efficiently breed for higher TDS levels in Beta vulgaris, avoiding intercrop type crosses and linkage drag.

Genome-wide copy number variation regions in indigenous (Bos indicus) cattle breeds of Tamil Nadu, India

OBJECTIVE

Identification of large scale structural polymorphisms (copy number variations [CNVs]) of more than 50 bp between the individuals of a species would help in knowing genetic diversity, phenotypic variability, adaptability to tropical environment and disease resistance.

METHODS

Read depth-based method implemented in CNVnator was used for calling copy number variant regions on sequenced data obtained from whole-genome sequencing from 15 pooled samples belonging to five draught cattle breeds of Tamil Nadu.

RESULTS

A total of 11,605 CNV regions (CNVRs) were observed covering a genome size of 18.63 percent. Among these, 11,459 were restricted to autosomes, consisting of 11,013 deletions, 353 duplications and 93 complex events. These CNVRs were annotated to 4,989 candidate genes. A total of 8,291 numbers of CNVRs were shared among the five cattle breeds as also supported by principal component analysis and STRUCTURE analyses and 1,172 CNVRs were breed-specific. Four out of five selected breed-specific CNVRs were validated using real-time polymerase chain reaction. Genes with CNVRs are related to milk production (BTN1A1, ABCA1, and LAP3), disease resistance (TLR4 and DNAH8), adaptability (SOD1, CAST, and SMARCAL1), growth (EGFR, NKAIN3), reproduction (BRWD1 and PDE6D), meat and carcass traits (MAP3K5 and NCAM1) and exterior (ATRN and MITF) traits. Gene enrichment analysis based on the gene list retrieved from the CNVRs disclosed over-represented terms (p<0.01) associated with milk fat production. NETWORK analysis had identified 13 putative candidate genes involved in milk fat percentage, milk fat yield, lactation persistency, milk yield, heat tolerance, calving ease, growth and conformation traits.

CONCLUSION

The genome-wide CNVRs identified in the present study produced genomewide partial CNV map in indigenous cattle breeds of Tamil Nadu.

Error-corrected ultradeep next-generation sequencing for detection of clonal haematopoiesis and haematological neoplasms - sensitivity, specificity and accuracy

Clonal haematopoiesis of indeterminate potential (CHIP) is an aging-associated phenomenon that has recently been correlated with a broad spectrum of human diseases, including haematological malignancy, cytopenia, coronary heart disease, stroke, and overall mortality. CHIP is defined as a somatic variant in blood cells with an allele frequency (VAF) ≥ 0.02, however recent reports show smaller clones are associated with poorer clinical outcome. Error-corrected ultradeep next-generation sequencing (NGS) assays detecting variants < 0.02 VAF also have clinical value for monitoring measurable residual disease (MRD) for myeloid neoplasms. However, limited data are available on optimal parameters, limits of detection, and accuracy of ultra-sensitive detection. We investigated parameters to improve accuracy of Illumina sequencing-by-synthesis method, including read depth, input DNA quantity, and molecular barcoding-based data filtering, while adhering to clinical accreditation criteria. Validation data were generated from reference standards and reference samples from a clinically accredited pathology laboratory. Analytical range measurements included linearity and bias, and precision included repeatability, reproducibility and detection rate. The lower limit of detection was ≥ 0.004 (0.4%) at depth > 3,000 × . Trueness measured using reference standards demonstrated a sensitivity, specificity, positive and negative predictive values, and accuracy of 100%, including FLT3-ITD, and 100% concordance was achieved with reference samples for reported variants and absence of variants. Sequencing blood samples from 383 community-dwelling adults (mean depth 3758×) revealed 2,190 somatic variants/sample, > 99.9% were < 0.02 VAF. Our data including cost-benefit analysis enables pathology and research laboratories to make informed decisions for detection of CHIP (VAF ≥ 0.02), sub-CHIP (VAF 0.01-0.02) and MRD (VAF ≥ 0.004).

The evaluation of targeted exome sequencing of candidate genes in a Han Chinese population with primary open-angle glaucoma

Primary open-angle glaucoma (POAG), known as a common ocular disease with genetic heterogeneity, is characterized by progressive optic disc atrophy and visual field defects. This study aimed to assess the contribution of previously reported POAG-associated genes and investigate potential functional variations and genotype-phenotype correlations in a Han Chinese population. DNA from 500 cases and 500 controls was pooled and sequenced using a customized panel of 398 candidate genes. After prioritization, 21 SNPs from 16 genes were genotyped in the first replication cohort (500 cases and 500 controls), and 9 SNPs were genotyped in the second replication cohort (500 cases and 500 controls). Allelic associations and odds ratios were adjusted for age and sex, while linear regression assessed SNP correlations with POAG endophenotypes. Haplotype analysis and linkage disequilibrium were performed using Haploview. In silico prediction tools were used to predict pathogenicity and function. SNPs from MFN2, DGKG, PKHD1, PTPRJ, and LTBP2 were associated with POAG in at least one cohort, and SNPs from EXOC2, PTPRJ, and LTBP2 showed significant correlations with intraocular pressure. Additionally, haplotype analysis revealed a significant association between the EXOC2 TGC haplotype and POAG risk. We validated several candidate genes and identified novel SNPs, providing further insight into the genetic architecture of POAG in the Han Chinese population.

Integrating Metagenomic and Culture-Based Techniques to Detect Foodborne Pathogens and Antimicrobial Resistance Genes in Malaysian Produce

Foodborne illnesses pose a significant global health threat, often caused by pathogens like Escherichia coli, Listeria monocytogenes, and Salmonella spp. The emergence of antibiotic-resistant strains further exacerbates food safety challenges. This study combines shotgun metagenomics and culture-based approaches to detect foodborne pathogens and antimicrobial resistance genes (ARGs) in Malaysian produce and meats from the Kinta Valley region. A total of 27 samples comprising vegetables, meats, and fruits were analyzed. Metagenomics provided comprehensive microbial profiles, revealing diverse bacterial communities with species-level taxonomic resolution. Culture-based methods complemented these findings by identifying viable pathogens. Key foodborne pathogens were detected, with Listeria monocytogenes identified in meats and vegetables and Shigella flexneri detected inconsistently between the methods. ARGs analysis highlighted significant resistance to cephalosporins and penams, particularly in raw chicken and vegetable samples, underscoring the potential public health risks. While deli meats and fruits exhibited a lower antimicrobial resistance prevalence, resistant genes linked to E. coli and Salmonella strains were identified. Discrepancies between the methods suggest the need for integrated approaches to improve the pathogen detection accuracy. This study demonstrates the potential of metagenomics in advancing food safety research and supports its adoption as a complementary tool alongside culture-based methods for comprehensive foodborne pathogen surveillance and ARG profiling in Malaysian food systems.

Multiplexed amplicon sequencing reveals the heterogeneous spatial distribution of pyrethroid resistance mutations in Aedes albopictus mosquito populations in southern France

BACKGROUND

The risk of mosquito-borne disease transmission is increasing in temperate climates with the colonization and proliferation of the Asian tiger mosquito vector Aedes albopictus and the rapid mass transport of passengers returning from tropical regions where viruses are endemic. The prevention of major Aedes-borne viruses heavily relies on the use of insecticides for vector control, mainly pyrethroids. In Europe, only deltamethrin is authorized.

METHODS

High-throughput molecular assays can provide a cost-effective surrogate to phenotypic insecticide resistance assays when mutations have been previously linked to a resistance phenotype. Here, we screened for the spatial distribution of knockdown resistance (kdr) mutations at a large scale using a two-step approach based on multiplexed amplicon sequencing and an unprecedented collection of field-derived mosquitoes from 95 sites in 61 municipalities, alongside a west-to-east transect in the south of France, from June to September 2021.

RESULTS

We identified the presence of the V1016G allele in 14 sites. The V1016G allele was predominantly found in southeast France close to the Italian border, with two additional isolated sites close to Bordeaux and Marmande. All mosquitoes were heterozygous for this mutation and should not be phenotypically resistant to pyrethroid insecticide. Four other mutations were identified in our targeted genomic sequence: I1532T, M1006L, M1586L, M995L. Sequencing a section of maternally inherited mitochondrial genome confirmed that the spread of Ae. albopictus in France originated from founders within haplogroup A1.

CONCLUSIONS

These findings contribute to the broader understanding of resistance dynamics in Europe and can inform targeted approaches to mitigate the impact of resistance on vector control.

Linking the spatial and genomic structure of adaptive potential for conservation management: a review

We unified the recent literature with the goal to contribute to the discussion on how genetic diversity might best be conserved. We argue that this decision will be guided by how genomic variation is distributed among manageable populations (i.e., its spatial structure), the degree to which adaptive potential is best predicted by variation across the entire genome or the subset of that variation that is identified as putatively adaptive (i.e., its genomic structure), and whether we are managing species as single entities or as collections of diversifying lineages. The distribution of genetic variation and our ultimate goal will have practical implications for on-the-ground management. If adaptive variation is largely polygenic or responsive to change, its spatial structure might be broadly governed by the forces determining genome-wide variation (linked selection, drift, and gene flow), making measurement and prioritization straightforward. If we are managing species as single entities, then population-level prioritization schemes are possible so as to maximize future pooled genetic variation. We outline one such scheme based on the popular Shapley value from cooperative game theory that considers the relative genetic contribution of a population to an unknown future collection of populations.

Genome resequencing and genome-wide polymorphisms in mosquito vectors Aedes aegypti and Aedes albopictus from south India

Aedes aegypti and Aedes albopictus mosquitoes spread major vector-borne viral diseases in tropical and sub-tropical regions of the globe. In this study, we sequenced the genome of Indian Ae. aegypti and Ae. albopictus and mapped to their reference genomes. Comparative genomics were performed between our strain and the reference strains. A total of 14,416,484 single nucleotide polymorphisms (SNPs) and 156,487 insertions and deletions (InDels) were found in Ae. aegypti, and 28,940,433 SNPs and 188,987 InDels in Ae. albopictus. Particular emphasis was given to gene families involved in mosquito digestion, development, and innate immunity, which could be putative candidates for vector control. Serine protease cascades and their inhibitors called serpins, play a central role in these processes. We extracted high-impact variants in genes associated with serine proteases and serpins. This study reports for the first time a high coverage genome sequence data of an Indian Ae. albopictus mosquito. The results from this study will provide insights into Indian Aedes specific polymorphisms and the evolution of immune related genes in mosquitoes, which can serve as a resource for future comparative genomics and those pursuing the development of targeted biopesticides for effective mosquito control strategies.

Sampling strategies for genotyping common bean (Phaseolus vulgaris L.) Genebank accessions with DArTseq: a comparison of single plants, multiple plants, and DNA pools

Introduction

Genotyping large-scale gene bank collections requires an appropriate sampling strategy to represent the diversity within and between accessions.

Methods

A panel of 44 common bean (Phaseolus vulgaris L.) landraces from the Alliance Bioversity and The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT) gene bank was genotyped with DArTseq using three sampling strategies: a single plant per accession, 25 individual plants per accession jointly analyzed after genotyping (in silico-pool), and by pooling tissue from 25 individual plants per accession (seq-pool). Sampling strategies were compared to assess the technical aspects of the samples, the marker information content, and the genetic composition of the panel.

Results

The seq-pool strategy resulted in more consistent DNA libraries for quality and call rate, although with fewer polymorphic markers (6,142 single-nucleotide polymorphisms) than the in silico-pool (14,074) or the single plant sets (6,555). Estimates of allele frequencies by seq-pool and in silico-pool genotyping were consistent, but the results suggest that the difference between pools depends on population heterogeneity. Principal coordinate analysis, hierarchical clustering, and the estimation of admixture coefficients derived from a single plant, in silico-pool, and seq-pool successfully identified the well-known structure of Andean and Mesoamerican gene pools of P. vulgaris across all datasets.

Conclusion

In conclusion, seq-pool proved to be a viable approach for characterizing common bean germplasm compared to genotyping individual plants separately by balancing genotyping effort and costs. This study provides insights and serves as a valuable guide for gene bank researchers embarking on genotyping initiatives to characterize their collections. It aids curators in effectively managing the collections and facilitates marker-trait association studies, enabling the identification of candidate markers for key traits.

Evaluation of Genetic Variants Associated with the Risk of Thiopurine-Related Pancreatitis: A Case Control Study from ENEIDA Registry

INTRODUCTION

Risk factors for developing pancreatitis due to thiopurines in patients with inflammatory bowel disease (IBD) are not clearly identified. Our aim was to evaluate the predictive pharmacogenetic risk of pancreatitis in IBD patients treated with thiopurines.

METHODS

We conducted an observational pharmacogenetic study of acute pancreatitis events in a cohort study of IBD patients treated with thiopurines from the prospectively maintained ENEIDA registry biobank of GETECCU. Samples were obtained and the CASR, CEL, CFTR, CDLN2, CTRC, SPINK1, CPA1, and PRSS1 genes, selected based on their known association with pancreatitis, were fully sequenced.

RESULTS

Ninety-five cases and 105 controls were enrolled; a total of 57% were women. Median age at pancreatitis diagnosis was 39 years. We identified 81 benign variants (50 in cases and 67 in controls) and a total of 35 distinct rare pathogenic and unknown significance variants (10 in CEL, 21 in CFTR, 1 in CDLN2, and 3 in CPA1). None of the cases or controls carried pancreatitis-predisposing variants within the CASR, CPA1, PRSS1, and SPINK1 genes, nor a pathogenic CFTR mutation. Four different variants of unknown significance were detected in the CDLN and CPA1 genes; one of them was in the CDLN gene in a single patient with pancreatitis and 3 in the CPA1 gene in 5 controls. After the analysis of the variants detected, no significant differences were observed between cases and controls.

CONCLUSION

In patients with IBD, genes known to cause pancreatitis seem not to be involved in thiopurine-related pancreatitis onset.

Genomic selection pressure discovery using site-frequency spectrum and reduced local variability statistics in Pakistani Dera-Din-Panah goat

BACKGROUND

Population geneticists have long sought to comprehend various selection traces accumulated in the goat genome due to natural or human driven artificial selection through breeding practices, which led the wild animals to domestication, so understanding evolutionary process may helpful to utilize the full genetic potential of goat genome.

METHODS AND RESULTS

As a step forward to pinpoint the selection signals in Pakistani Dera-Din-Panah (DDP) goat, whole-genome pooled sequencing (n = 12) was performed, and 618,236,192 clean paired-end reads were mapped against ARS1 reference goat assembly. Five different selection signature statistics were applied using four site-frequency spectrum (SFS) methods (Tajima's D ([Formula: see text]), Fay and Wu's H ([Formula: see text]), Zeng's E ([Formula: see text]), [Formula: see text]) and one reduced local variability approach named pooled heterozygosity ([Formula: see text]). The under-selection regions were annotated with significant threshold values of [Formula: see text]≥4.7, [Formula: see text]≥6, [Formula: see text]≥2.5, Pool-HMM ≥ 12, and [Formula: see text]≥5 that resulted in accumulative 364 candidate gene hits. The highest genomic selection signals were observed on Chr. 4, 6, 10, 12, 15, 16, 18, 20, and 27 and harbor ADAMTS6, CWC27, RELN, MYCBP2, FGF14, STIM1, CFAP74, GNB1, CALML6, TMEM52, FAM149A, NADK, MMP23B, OPN3, FH, MFHAS1, KLKB1, RRM1, KMO, SPEF2, F11, KIT, KMO, ERI1, ATP8B4, and RHOG genes. Next, the validation of our captured genomic hits was also performed by more than one applied statistics which harbor meat production, immunity, and reproduction associated genes to strengthen our hypothesis of under-selection traits in this Pakistani goat breed. Furthermore, common candidate genes captured by more than one statistical method were subjected to gene ontology and KEGG pathway analysis to get insights of particular biological processes associated with this goat breed.

CONCLUSION

Current perception of genomic architecture of DDP goat provides a better understanding to improve its genetic potential and other economically important traits of medium to large body size, milk, and fiber production by updating the genomic insight driven breeding strategies to boost the livestock and agriculture-based economy of the country.

First report on metagenomics and their predictive functional analysis of fermented bamboo shoot food of Tripura, North East India

Moiya pansung, mileye amileye, moiya koshak, and midukeye are naturally fermented bamboo shoot foods of Tripura. The present study aimed to reveal the whole microbial community structure of naturally fermented moiya pangsung, mileye amileye, moiya koshak, and midukeye along with the prediction of microbial functional profiles by shotgun metagenomic sequence analysis. The metataxonomic profile of moiya pangsung, mileye amileye, moiya koshak, and midukeye samples showed different domains, viz., bacteria (97.70%) followed by the virus (0.76%), unclassified (0.09%), eukaryotes (1.46%) and archaea (0.05%). Overall, 49 phyla, 409 families, 841 genera, and 1,799 species were found in all the fermented bamboo shoot samples collected from different places of Tripura. Firmicutes was the most abundant phylum (89.28%) followed by Proteobacteria (5.13%), Bacteroidetes (4.38%), Actinobacteria (1.02%), and Fusobacteria (0.17%). Lactiplantibacillus plantarum was the most abundant species in moiya pangsung, mileye amileye, moiya koshak, and midukeye followed by Lactococcus lactis, Levilactobacillus brevis, Leuconostoc mesenteroides, Weissella paramesenteroides, Leuconostoc kimchii, Pediococcus pentosaceus, Leuconostoc gasicomitatum, and Lacticaseibacillus casei. A few phyla of fungus were found, viz., Ascomycota, Basidiomycota, and Glomeromycota, where Ascomycota was present in high abundance. Functional analysis of moiya pangsung, mileye amileye, moiya koshak, and midukeye metagenome revealed the genes for the synthesis and metabolism of a wide range of bioactive compounds including, various essential amino acids, and conjugated amino acids. The abundance profile and predictive analysis of fermented bamboo shoots revealed a huge plethora of essential microorganisms and KEGG analysis revealed genes for amino acid metabolism, pectin degradation, lipid metabolism, and many other essential pathways that can be essential for the improvement of nutritional and sensory qualities of the fermented bamboo shoot products.

Screening of candidate genes at GLC3B and GLC3C loci in Chinese primary congenital glaucoma patients with targeted next generation sequencing

BACKGROUND

Primary congenital glaucoma (PCG) is characterized by developmental abnormalities of the anterior chamber angle. Although several genes have been associated with PCG, pathogenic mutations could only be detected in about 20% of Chinese patients. GLC3B (1p36.2-36.1) and GLC3C (14q24.3) loci were previously identified in PCG pedigrees via linkage analysis. However, no causative genes were reported in these loci. This study was designed to search for novel PCG-related genes in these genetic regions.

MATERIALS AND METHODS

DNA samples from 100 PCG patients and 200 normal controls were pooled and sequenced using a customized panel of 133 positional candidate genes located around GLC3B and GLC3C loci (±1Mb). PCG-related genes were prioritized by the distribution of variants between patients and controls. Confirmation of selected variants and co-segregation analysis were performed using Sanger sequencing.

RESULTS

Patient and control group contained 116 and 147 rare variants respectively after screening. Three genes (ZC2HC1C, VPS13D, and PGF) were prioritized according to the distribution of variants between the two groups. Rare variants of PGF were only identified in PCG patients.

CONCLUSIONS

To the best of our knowledge, this is the first study aiming at exploring novel PCG-related genes at GLC3B and GLC3C loci. Our preliminary results suggest that there are potential associations between ZC2HC1C, VPS13D, PGF, and PCG. However, larger cohort studies and functional assays are required to provide further evidence for the proposed genotype-phenotype association.

Population genomics of helminth parasites

Next generation sequencing technologies have facilitated a shift from a few targeted loci in population genetic studies to whole genome approaches. Here, we review the types of questions and inferences regarding the population biology and evolution of parasitic helminths being addressed within the field of population genomics. Topics include parabiome, hybridization, population structure, loci under selection and linkage mapping. We highlight various advances, and note the current trends in the field, particularly a focus on human-related parasites despite the inherent biodiversity of helminth species. We conclude by advocating for a broader application of population genomics to reflect the taxonomic and life history breadth displayed by helminth parasites. As such, our basic knowledge about helminth population biology and evolution would be enhanced while the diversity of helminths in itself would facilitate population genomic comparative studies to address broader ecological and evolutionary concepts.

Deep Learning in Population Genetics

Population genetics is transitioning into a data-driven discipline thanks to the availability of large-scale genomic data and the need to study increasingly complex evolutionary scenarios. With likelihood and Bayesian approaches becoming either intractable or computationally unfeasible, machine learning, and in particular deep learning, algorithms are emerging as popular techniques for population genetic inferences. These approaches rely on algorithms that learn non-linear relationships between the input data and the model parameters being estimated through representation learning from training data sets. Deep learning algorithms currently employed in the field comprise discriminative and generative models with fully connected, convolutional, or recurrent layers. Additionally, a wide range of powerful simulators to generate training data under complex scenarios are now available. The application of deep learning to empirical data sets mostly replicates previous findings of demography reconstruction and signals of natural selection in model organisms. To showcase the feasibility of deep learning to tackle new challenges, we designed a branched architecture to detect signals of recent balancing selection from temporal haplotypic data, which exhibited good predictive performance on simulated data. Investigations on the interpretability of neural networks, their robustness to uncertain training data, and creative representation of population genetic data, will provide further opportunities for technological advancements in the field.

Key methodological challenges in detecting circulating miRNAs in different biofluids

The technological advancement in diagnostic techniques has immensely improved the capability of predicting disease progression. Yet, there is a great interest in developing newer biomarkers that can enhance disease risk prediction thereby minimising the associated morbidity and mortality. Circulating miRNAs, a non-coding RNA molecule, are critical regulators in the pathophysiology of various complex multifactorial diseases. In recent years, circulating miRNAs have been enormously studied and are considered as an emerging biomarker due to their easy accessibility, stability, and detection by sequence-specific amplification methods. However, there is a distinct lack of consensus regarding the preanalytical factors such as preferred sample selection, methodological aspects, etc that may independently or together influence the detection of circulating miRNAs resulting in erroneous expression profiles. Therefore, the present review makes an attempt to highlight the various pre-analytical and analytical factors that can potentially influence the circulating miRNA levels. Literature on circulating miRNA's stability, processing and quantitation in different biofluids along with the effect of various controllable and uncontrollable factors influencing circulating miRNA expression have been summarised in the current review.

Genomic differentiation in Pacific cod using Pool-Seq

Patterns of genetic differentiation across the genome can provide insight into selective forces driving adaptation. We used pooled whole genome sequencing, gene annotation, and environmental covariates to evaluate patterns of genomic differentiation and to investigate mechanisms responsible for divergence among proximate Pacific cod (Gadus macrocephalus) populations from the Bering Sea and Aleutian Islands and more distant Washington Coast cod. Samples were taken from eight spawning locations, three of which were replicated to estimate consistency in allele frequency estimation. A kernel smoothing moving weighted average of relative divergence (F ST) identified 11 genomic islands of differentiation between the Aleutian Islands and Bering Sea samples. In some islands of differentiation, there was also elevated absolute divergence (d XY) and evidence for selection, despite proximity and potential for gene flow. Similar levels of absolute divergence (d XY) but roughly double the relative divergence (F ST) were observed between the distant Bering Sea and Washington Coast samples. Islands of differentiation were much smaller than the four large inversions among Atlantic cod ecotypes. Islands of differentiation between the Bering Sea and Aleutian Island were associated with SNPs from five vision system genes, which can be associated with feeding, predator avoidance, orientation, and socialization. We hypothesize that islands of differentiation between Pacific cod from the Bering Sea and Aleutian Islands provide evidence for adaptive differentiation despite gene flow in this commercially important marine species.

Utility and challenges of using whole-genome resequencing to detect emerging insect and mite resistance in agroecosystems

Arthropods that invade agricultural ecosystems systematically evolve resistance to the control measures used against them, and this remains a significant and ongoing challenge for sustainable food production systems. Early detection of resistance evolution could prompt remedial action to slow the spread of resistance alleles in the landscape. Historical approaches used to detect emerging resistance included phenotypic monitoring of agricultural pest populations, as well as monitoring of allele frequency changes at one or a few candidate pesticide resistance genes. In this article, I discuss the successes and limitations of these traditional monitoring approaches and then consider whether whole-genome scanning could be applied to samples collected from agroecosystems over time for resistance monitoring. I examine the qualities of agroecosystems that could impact application of this approach to pesticide resistance monitoring and describe a recent retrospective analysis where genome scanning successfully detected an oligogenic response to selection by pesticides years prior to pest management failure. I conclude by considering areas of further study that will shed light on the feasibility of applying whole-genome scanning for resistance risk monitoring in agricultural pest species.

A multi-step genomic approach prioritized TBKBP1 gene as relevant for multiple sclerosis susceptibility

BACKGROUND

Over 200 genetic loci have been associated with multiple sclerosis (MS) explaining ~ 50% of its heritability, suggesting that additional mechanisms may account for the "missing heritability" phenomenon.

OBJECTIVE

To analyze a large cohort of Italian individuals to identify markers associated with MS with potential functional impact in the disease.

METHODS

We studied 2571 MS and 3234 healthy controls (HC) of continental Italian origin. Discovery phase included a genome wide association study (1727 MS, 2258 HC), with SNPs selected according to their association in the Italian cohort only or in a meta-analysis of signals with a cohort of European ancestry (4088 MS, 7144 HC). Top associated loci were then tested in two Italian cohorts through array-based genotyping (903 MS, 884 HC) and pool-based target sequencing (588 MS, 408 HC). Finally, functional prioritization through conditional eQTL and mQTL has been performed.

RESULTS

Top associated signals overlap with already known MS loci on chromosomes 3 and 17. Three SNPs (rs4267364, rs8070463, rs67919208), all involved in the regulation of TBKBP1, were prioritized to be functionally relevant.

CONCLUSIONS

No evidence of novel signal of association with MS specific for the Italian continental population has been found; nevertheless, two MS loci seems to play a relevant role, raising the interest to further investigations for TBKBP1 gene.

Genetic and genomic analysis of oxygen consumption in mice

We estimated genetic parameters for oxygen consumption (OC), OC per metabolic body weight (OCMBW) and body weight at three through 8 weeks of age in divergently selected mice populations, with an animal model considering maternal genetic, common litter environmental and cytoplasmic inheritance effects. Cytoplasmic inheritance was considered based on maternal lineage information. With respect to OC, estimated direct heritability was moderate (0.32) and the estimated proportion of the variance of cytoplasmic inheritance effects to the phenotypic variance was very low (0.01), implying that causal genes for OC could be located on autosomes. To assess this hypothesis, we attempted to identify possible candidate causal genes through selective signature detection with the results of pooled whole-genome resequencing using pooled DNA samples from high and low OC mice. We made a list of possible candidate causal genes for OC, including those relating to electron transport chain and ATP-binding proteins (Ndufa12, Sdhc, Atp10b, etc.), Prr16 encoding Largen protein, Cry1 encoding a key component of the circadian core oscillator and so on. The results, although careful interpretation must be required, could contribute to elucidate the genetic mechanism of OC, an indicator for maintenance energy requirement, and therefore feed efficiency.

Metagenomic-Metabolomic Mining of Kinema, a Naturally Fermented Soybean Food of the Eastern Himalayas

Kinema is a popular sticky fermented soybean food of the Eastern Himalayan regions of North East India, east Nepal, and south Bhutan. We hypothesized that some dominant bacteria in kinema may contribute to the formation of targeted and non-targeted metabolites for health benefits; hence, we studied the microbiome-metabolite mining of kinema. A total of 1,394,094,912 bp with an average of 464,698,304 ± 120,720,392 bp was generated from kinema metagenome, which resulted in the identification of 47 phyla, 331 families, 709 genera, and 1,560 species. Bacteria (97.78%) were the most abundant domain with the remaining domains of viruses, eukaryote, and archaea. Firmicutes (93.36%) was the most abundant phylum with 280 species of Bacillus, among which Bacillus subtilis was the most dominant species in kinema followed by B. glycinifermentans, B. cereus, B. licheniformis, B. thermoamylovorans, B. coagulans, B. circulans, B. paralicheniformis, and Brevibacillus borstelensis. Predictive metabolic pathways revealed the abundance of genes associated with metabolism (60.66%), resulting in 216 sub-pathways. A total of 361 metabolites were identified by metabolomic analysis (liquid chromatography-mass spectrophotometry, LC-MS). The presence of metabolites, such as chrysin, swainsonine, and 3-hydroxy-L-kynurenine (anticancer activity) and benzimidazole (antimicrobial, anticancer, and anti-HIV activities), and compounds with immunomodulatory effects in kinema supports its therapeutic potential. The correlation between the abundant species of Bacillus and primary and secondary metabolites was constructed with a bivariate result. This study proves that Bacillus spp. contribute to the formation of many targeted and untargeted metabolites in kinema for health-promoting benefits.

High-throughput estimation of allele frequencies using combined pooled-population sequencing and haplotype-based data processing

BACKGROUND

In addition to heterogeneity and artificial selection, natural selection is one of the forces used to combat climate change and improve agrobiodiversity in evolutionary plant breeding. Accurate identification of the specific genomic effects of natural selection will likely accelerate transfer between populations. Thus, insights into changes in allele frequency, adequate population size, gene flow and drift are essential. However, observing such effects often involves a trade-off between costs and resolution when a large sample of genotypes for many loci is analysed. Pool genotyping approaches achieve high resolution and precision in estimating allele frequency when sequence coverage is high. Nevertheless, high-coverage pool sequencing of large genomes is expensive.

RESULTS

Three pool samples (n = 300, 300, 288) from a barley backcross population were generated to assess the population's allele frequency. The tested population (BC2F21) has undergone 18 generations of natural adaption to conventional farming practice. The accuracies of estimated pool-based allele frequencies and genome coverage yields were compared using three next-generation sequencing genotyping methods. To achieve accurate allele frequency estimates with low sequence coverage, we employed a haplotyping approach. Low coverage allele frequencies of closely located single polymorphisms were aggregated into a single haplotype allele frequency, yielding 2-to-271-times higher depth and increased precision. When we combined different haplotyping tactics, we found that gene and chip marker-based haplotype analyses performed equivalently or better compared with simple contig haplotype windows. Comparing multiple pool samples and referencing against an individual sequencing approach revealed that whole-genome pool re-sequencing (WGS) achieved the highest correlation with individual genotyping (≥ 0.97). In contrast, transcriptome-based genotyping (MACE) and genotyping by sequencing (GBS) pool replicates were significantly associated with higher error rates and lower correlations, but are still valuable to detect large allele frequency variations.

CONCLUSIONS

The proposed strategy identified the allele frequency of populations with high accuracy at low cost. This is particularly relevant to evolutionary plant breeding of crops with very large genomes, such as barley. Whole-genome low coverage re-sequencing at 0.03 × coverage per genotype accurately estimated the allele frequency when a loci-based haplotyping approach was applied. The implementation of annotated haplotypes capitalises on the biological background and statistical robustness.

Genomic architecture of phenotypic extremes in a wild cervid

Identifying the genes underlying fitness-related traits such as body size and male ornamentation can provide tools for conservation and management and are often subject to various selective pressures. Here we performed high-depth whole genome re-sequencing of pools of individuals representing the phenotypic extremes for antler and body size in white-tailed deer (Odocoileus virginianus). Samples were selected from a tissue repository containing phenotypic data for 4,466 male white-tailed deer from Anticosti Island, Quebec, with four pools representing the extreme phenotypes for antler and body size after controlling for age. Our results revealed a largely homogenous population but detected highly divergent windows between pools for both traits, with the mean allele frequency difference of 14% for and 13% for antler and body SNPs in outlier windows, respectively. Genes in outlier antler windows were enriched for pathways associated with cell death and protein metabolism and some of the most differentiated windows included genes associated with oncogenic pathways and reproduction, processes consistent with antler evolution and growth. Genes associated with body size were more nuanced, suggestive of a highly complex trait. Overall, this study revealed the complex genomic make-up of both antler morphology and body size in free-ranging white-tailed deer and identified target loci for additional analyses.

Neutral and adaptive drivers of genomic change in introduced brook trout (Salvelinus fontinalis) populations revealed by pooled sequencing

Understanding the drivers of successful species invasions is important for conserving native biodiversity and for mitigating the economic impacts of introduced species. However, whole-genome resolution investigations of the underlying contributions of neutral and adaptive genetic variation in successful introductions are rare. Increased propagule pressure should result in greater neutral genetic variation, while environmental differences should elicit selective pressures on introduced populations, leading to adaptive differentiation. We investigated neutral and adaptive variation among nine introduced brook trout (Salvelinus fontinalis) populations using whole-genome pooled sequencing. The populations inhabit isolated alpine lakes in western Canada and descend from a common source, with an average of ~19 (range of 7-41) generations since introduction. We found some evidence of bottlenecks without recovery, no strong evidence of purifying selection, and little support that varying propagule pressure or differences in local environments shaped observed neutral genetic variation differences. Putative adaptive loci analysis revealed nonconvergent patterns of adaptive differentiation among lakes with minimal putatively adaptive loci (0.001%-0.15%) that did not correspond with tested environmental variables. Our results suggest that (i) introduction success is not always strongly influenced by genetic load; (ii) observed differentiation among introduced populations can be idiosyncratic, population-specific, or stochastic; and (iii) conservatively, in some introduced species, colonization barriers may be overcome by support through one aspect of propagule pressure or benign environmental conditions.

Genetic characterization of carrot root shape and size using genome-wide association analysis and genomic-estimated breeding values

The principal phenotypic determinants of market class in carrot-the size and shape of the root-are under primarily additive, but also highly polygenic, genetic control. The size and shape of carrot roots are the primary determinants not only of yield, but also market class. These quantitative phenotypes have historically been challenging to objectively evaluate, and thus subjective visual assessment of market class remains the primary method by which selection for these traits is performed. However, advancements in digital image analysis have recently made possible the high-throughput quantification of size and shape attributes. It is therefore now feasible to utilize modern methods of genetic analysis to investigate the genetic control of root morphology. To this end, this study utilized both genome wide association analysis (GWAS) and genomic-estimated breeding values (GEBVs) and demonstrated that the components of market class are highly polygenic traits, likely under the influence of many small effect QTL. Relatively large proportions of additive genetic variance for many of the component phenotypes support high predictive ability of GEBVs; average prediction ability across underlying market class traits was 0.67. GWAS identified multiple QTL for four of the phenotypes which compose market class: length, aspect ratio, maximum width, and root fill, a previously uncharacterized trait which represents the size-independent portion of carrot root shape. By combining digital image analysis with GWAS and GEBVs, this study represents a novel advance in our understanding of the genetic control of market class in carrot. The immediate practical utility and viability of genomic selection for carrot market class is also described, and concrete guidelines for the design of training populations are provided.

Decoding sex: Elucidating sex determination and how high-quality genome assemblies are untangling the evolutionary dynamics of sex chromosomes

Sexual reproduction is a diverse and widespread process. In gonochoristic species, the differentiation of sexes occurs through diverse mechanisms, influenced by environmental and genetic factors. In most vertebrates, a master-switch gene is responsible for triggering a sex determination network. However, only a few genes have acquired master-switch functions, and this process is associated with the evolution of sex-chromosomes, which have a significant influence in evolution. Additionally, their highly repetitive regions impose challenges for high-quality sequencing, even using high-throughput, state-of-the-art techniques. Here, we review the mechanisms involved in sex determination and their role in the evolution of species, particularly vertebrates, focusing on sex chromosomes and the challenges involved in sequencing these genomic elements. We also address the improvements provided by the growth of sequencing projects, by generating a massive number of near-gapless, telomere-to-telomere, chromosome-level, phased assemblies, increasing the number and quality of sex-chromosome sequences available for further studies.

Contribution of Rare and Low-Frequency Variants to Multiple Sclerosis Susceptibility in the Italian Continental Population

Genome-wide association studies identified over 200 risk loci for multiple sclerosis (MS) focusing on common variants, which account for about 50% of disease heritability. The goal of this study was to investigate whether low-frequency and rare functional variants, located in MS-established associated loci, may contribute to disease risk in a relatively homogeneous population, testing their cumulative effect (burden) with gene-wise tests. We sequenced 98 genes in 588 Italian patients with MS and 408 matched healthy controls (HCs). Variants were selected using different filtering criteria based on allelic frequency and in silico functional impacts. Genes showing a significant burden (n = 17) were sequenced in an independent cohort of 504 MS and 504 HC. The highest signal in both cohorts was observed for the disruptive variants (stop-gain, stop-loss, or splicing variants) located in EFCAB13, a gene coding for a protein of an unknown function (p < 10^-4). Among these variants, the minor allele of a stop-gain variant showed a significantly higher frequency in MS versus HC in both sequenced cohorts (p = 0.0093 and p = 0.025), confirmed by a meta-analysis on a third independent cohort of 1298 MS and 1430 HC (p = 0.001) assayed with an SNP array. Real-time PCR on 14 heterozygous individuals for this variant did not evidence the presence of the stop-gain allele, suggesting a transcript degradation by non-sense mediated decay, supported by the evidence that the carriers of the stop-gain variant had a lower expression of this gene (p = 0.0184). In conclusion, we identified a novel low-frequency functional variant associated with MS susceptibility, suggesting the possible role of rare/low-frequency variants in MS as reported for other complex diseases.

Evaluation of a parasite-density based pooled targeted amplicon deep sequencing (TADS) method for molecular surveillance of Plasmodium falciparum drug resistance genes in Haiti

Sequencing large numbers of individual samples is often needed for countrywide antimalarial drug resistance surveillance. Pooling DNA from several individual samples is an alternative cost and time saving approach for providing allele frequency (AF) estimates at a population level. Using 100 individual patient DNA samples of dried blood spots from a 2017 nationwide drug resistance surveillance study in Haiti, we compared codon coverage of drug resistance-conferring mutations in four Plasmodium falciparum genes (crt, dhps, dhfr, and mdr1), for the same deep sequenced samples run individually and pooled. Samples with similar real-time PCR cycle threshold (Ct) values (+/- 1.0 Ct value) were combined with ten samples per pool. The sequencing success for samples in pools were higher at a lower parasite density than the individual samples sequence method. The median codon coverage for drug resistance-associated mutations in all four genes were greater than 3-fold higher in the pooled samples than in individual samples. The overall codon coverage distribution for pooled samples was wider than the individual samples. The sample pools with < 40 parasites/μL blood showed more discordance in AF calls for dhfr and mdr1 between the individual and pooled samples. This discordance in AF estimation may be due to low amounts of parasite DNA, which could lead to variable PCR amplification efficiencies. Grouping samples with an estimated ≥ 40 parasites/μL blood prior to pooling and deep sequencing yielded the expected population level AF. Pooling DNA samples based on estimates of > 40 parasites/μL prior to deep sequencing can be used for rapid genotyping of a large number of samples for these four genes and possibly other drug resistant markers in population-based studies. As Haiti is a low malaria transmission country with very few mixed infections and continued chloroquine sensitivity, the pooled sequencing approach can be used for routine national molecular surveillance of resistant parasites.

Shotgun metagenomics of Cheonggukjang, a fermented soybean food of Korea: Community structure, predictive functionalities and amino acids profile

Cheonggukjang is a naturally fermented soybean food of Korea. The present study was aimed to reveal the whole microbial community structure of naturally fermented cheonggukjang along with the prediction of microbial functional profiles by shotgun metagenomic sequence analysis. Metataxonomic profile of cheonggukjang samples showed different domains viz. bacteria (95.83%), virus (2.26%), unclassified (1.84%), eukaryotes (0.05%) and archaea (0.005%). Overall, 44 phyla, 286 families, 722 genera and 1437 species were identified. Firmicutes was the most abundant phylum (98.04%) followed by Proteobacteria (1.49%), Deinococcus-Thermus (0.14%). Bacillus thermoamylovorans was the most abundant species in cheonggukjang followed by Bacillus licheniformis, Bacillus glycinifermentans, Bacillus subtilis, Bacillus paralicheniformis, Bacillus amyloliquifaciens, Brevibacillus borstelensis, Brevibacillus sonorensis Brevibacillus, Acinetobacter, Carnobacterium, Paenibacillus, Cronobacter Enterococcus, Enterobacter, Terriglobus, Psychrobacter and Virgibacillus. A colossal diversity of the genus Bacillus was detected with 150 species. Functional analysis of cheonggukjang metagenome revealed the genes for the synthesis and metabolism of wide range of bioactive compounds including, various essential amino acids, conjugated amino acids, different vitamins, flavonoids, and enzymes. Amino acid profiles obtained from KEGG annotation in cheonggukjang were validated with experimental result of amino acid profiles.

Whole Exome-Sequencing of Pooled Genomic DNA Samples to Detect Quantitative Trait Loci in Esotropia and Exotropia of Strabismus in Japanese

BACKGROUND

Esotropia and exotropia are two major phenotypes of comitant strabismus. It remains controversial whether esotropia and exotropia would share common genetic backgrounds. In this study, we used a quantitative trait locus (QTL)-sequencing pipeline for diploid plants to screen for susceptibility loci of strabismus in whole exome sequencing of pooled genomic DNAs of individuals.

METHODS

Pooled genomic DNA (2.5 ng each) of 20 individuals in three groups, Japanese patients with esotropia and exotropia, and normal members in the families, was sequenced twice after exome capture, and the first and second sets of data in each group were combined to increase the read depth. The SNP index, as the ratio of variant genotype reads to all reads, and Δ(SNP index) values, as the difference of SNP index between two groups, were calculated by sliding window analysis with a 4 Mb window size and 10 kb slide size. The rows of 200 "N"s were inserted as a putative 200-b spacer between every adjoining locus to depict Δ(SNP index) plots on each chromosome. SNP positions with depth < 20 as well as SNP positions with SNP index of <0.3 were excluded.

RESULTS

After the exclusion of SNPs, 12,242 SNPs in esotropia/normal group and 12,108 SNPs in exotropia/normal group remained. The patterns of the Δ(SNP index) plots on each chromosome appeared different between esotropia/normal group and exotropia/normal group. When the consecutive groups of SNPs on each chromosome were set at three patterns: SNPs in each cytogenetic band, 50 consecutive sliding SNPs, and SNPs in 4 Mb window size with 10 kb slide size, p values (Wilcoxon signed rank test) and Q values (false discovery rate) in a few loci as Manhattan plots showed significant differences in comparison between the Δ(SNP index) in the esotropia/normal group and exotropia/normal group.

CONCLUSIONS

The pooled DNA sequencing and QTL mapping approach for plants could provide overview of genetic background on each chromosome and would suggest different genetic backgrounds for two major phenotypes of comitant strabismus, esotropia and exotropia.

Variant identification in BARD1, PRDM9, RCC1, and RECQL in patients with ovarian cancer by targeted next-generation sequencing of DNA pools

Several ovarian cancer susceptibility genes have been discovered, but more are likely to exist. In this study, we aimed to analyze knowledge-based selected genes, i.e., BARD1, PRDM9, RCC1, and RECQL, in which pathogenic germline variants have been reported in patients with breast and/or ovarian cancer. As deep sequencing of DNA samples remains costly, targeted next-generation sequencing of DNA pools was utilized to screen the exons of BARD1, PRDM9, RCC1, and RECQL in ~400 Polish ovarian cancer cases. 25 pools of 16 samples (including several duplicated samples with known variants) were sequenced on the NovaSeq6000 and analyzed with SureCall (Agilent) application. The set of variants was filtrated to exclude spurious variants, and, subsequently, the identified rare genetic variants were validated using Sanger sequencing. No pathogenic mutation was found within the analyzed cohort of ovarian cancer patients. Validation genotyping of filtered rare silent and missense variants revealed that the majority of them were true alterations, especially those with a higher mutation quality value. The high concordance (R2=0.95) of population allele frequency for 44 common SNPs in the European control population (gnomAD) and our experiment confirmed the reliability of pooled sequencing. Mutations in BARD1, PRDM9, RCC1, and RECQL do not contribute substantially to the risk of ovarian cancer. Pooled DNA sequencing is a cost-effective and reliable method for the initial screening of candidate genes; however, it still requires validation of identified rare variants.

Interest of exome sequencing trio-like strategy based on pooled parental DNA for diagnosis and translational research in rare diseases

Background

Exome sequencing (ES) has become the most powerful and cost‐effective molecular tool for deciphering rare diseases with a diagnostic yield approaching 30%–40% in solo‐ES and 50% in trio‐ES. We applied an innovative parental DNA pooling method to reduce the parental sequencing cost while maintaining the diagnostic yield of trio‐ES.

Methods

We pooled six (Agilent‐CRE‐v2–100X) or five parental DNA (TWIST‐HCE–70X) aiming to detect allelic balance around 8–10% for heterozygous status. The strategies were applied as second‐tier (74 individuals after negative solo‐ES) and first‐tier approaches (324 individuals without previous ES).

Results

The allelic balance of parental‐pool variants was around 8.97%. Sanger sequencing uncovered false positives in 1.5% of sporadic variants. In the second‐tier approach, we evaluated than two thirds of the Sanger validations performed after solo‐ES (41/59–69%) would have been saved if the parental‐pool segregations had been available from the start. The parental‐pool strategy identified a causative diagnosis in 18/74 individuals (24%) in the second‐tier and in 116/324 individuals (36%) in the first‐tier approaches, including 19 genes newly associated with human disorders.

Conclusions

Parental‐pooling is an efficient alternative to trio‐ES. It provides rapid segregation and extension to translational research while reducing the cost of parental and Sanger sequencing.

SNP Development in Penaeus vannamei via Next-Generation Sequencing and DNA Pool Sequencing

Next-generation sequencing and pool sequencing have been widely used in SNP (single-nucleotide polymorphism) detection and population genetics research; however, there are few reports on SNPs related to the growth of Penaeus vannamei. The purpose of this study was to call SNPs from rapid-growing (RG) and slow-growing (SG) individuals’ transcriptomes and use DNA pool sequencing to assess the reliability of SNPs. Two parameters were applied to detect SNPs. One parameter was the p-values generated using Fisher’s exact test, which were used to calculate the significance of allele frequency differences between RG and SG. The other one was the AFI (minor allele frequency imbalance), which was defined to highlight the fold changes in MAF (minor allele frequency) values between RG and SG. There were 216,015 hypothetical SNPs, which were obtained based on the transcriptome data. Finally, 104 high-quality SNPs and 96,819 low-quality SNPs were predicted. Then, 18 high-quality SNPs and 17 low-quality SNPs were selected to assess the reliability of the detection process. Here, 72.22% (13/18) accuracy was achieved for high-quality SNPs, while only 52.94% (9/17) accuracy was achieved for low-quality SNPs. These SNPs enrich the data for population genetics studies of P. vannamei and may play a role in the development of SNP markers for future breeding studies.

Identification of Novel Variants in Cleft Palate-Associated Genes in Brazilian Patients With Non-syndromic Cleft Palate Only

The identification of genetic risk factors for non-syndromic oral clefts is of great importance for better understanding the biological processes related to this heterogeneous and complex group of diseases. Herein we applied whole-exome sequencing to identify potential variants related to non-syndromic cleft palate only (NSCPO) in the multiethnic Brazilian population. Thirty NSCPO samples and 30 sex- and genetic ancestry-matched healthy controls were pooled (3 pools with 10 samples for each group) and subjected to whole-exome sequencing. After filtering, the functional affects, individually and through interactions, of the selected variants and genes were assessed by bioinformatic analyses. As a group, 399 variants in 216 genes related to palatogenesis/cleft palate, corresponding to 6.43%, were exclusively identified in the NSCPO pools. Among those genes are 99 associated with syndromes displaying cleft palate in their clinical spectrum and 92 previously related to cleft lip palate. The most significantly biological processes and pathways overrepresented in the NSCPO-identified genes were associated with the folic acid metabolism, highlighting the interaction between LDL receptor-related protein 6 (LRP6) and 5-methyltetrahydrofolate-homocysteine methyltransferase (MTR) that interconnect two large networks. This study yields novel data on characterization of specific variants and complex processes and pathways related to NSCPO, including many variants in genes of the folate/homocysteine pathway, and confirms that variants in genes related to syndromic cleft palate and cleft lip-palate may cause NSCPO.

Optimizing sampling design and sequencing strategy for the genomic analysis of quantitative traits in natural populations

Mapping the genes underlying ecologically relevant traits in natural populations is fundamental to develop a molecular understanding of species adaptation. Current sequencing technologies enable the characterization of a species' genetic diversity across the landscape or even over its whole range. The relevant capture of the genetic diversity across the landscape is critical for a successful genetic mapping of traits and there are no clear guidelines on how to achieve an optimal sampling and which sequencing strategy to implement. Here we determine, through simulation, the sampling scheme that maximizes the power to map the genetic basis of a complex trait in an outbreeding species across an idealized landscape and draw genomic predictions for the trait, comparing individual and pool sequencing strategies. Our results show that quantitative trait locus detection power and prediction accuracy are higher when more populations over the landscape are sampled and this is more cost-effectively done with pool sequencing than with individual sequencing. Additionally, we recommend sampling populations from areas of high genetic diversity. As progress in sequencing enables the integration of trait-based functional ecology into landscape genomics studies, these findings will guide study designs allowing direct measures of genetic effects in natural populations across the environment.

Ecological Load and Balancing Selection in Circumboreal Barnacles

Acorn barnacle adults experience environmental heterogeneity at various spatial scales of their circumboreal habitat, raising the question of how adaptation to high environmental variability is maintained in the face of strong juvenile dispersal and mortality. Here, we show that 4% of genes in the barnacle genome experience balancing selection across the entire range of the species. Many of these genes harbor mutations maintained across 2 My of evolution between the Pacific and Atlantic oceans. These genes are involved in ion regulation, pain reception, and heat tolerance, functions which are essential in highly variable ecosystems. The data also reveal complex population structure within and between basins, driven by the trans-Arctic interchange and the last glaciation. Divergence between Atlantic and Pacific populations is high, foreshadowing the onset of allopatric speciation, and suggesting that balancing selection is strong enough to maintain functional variation for millions of years in the face of complex demography.

Genomic and functional evaluation of TNFSF14 in multiple sclerosis susceptibility

Among multiple sclerosis (MS) susceptibility genes, the strongest non-human leukocyte antigen (HLA) signal in the Italian population maps to the TNFSF14 gene encoding LIGHT, a glycoprotein involved in dendritic cell (DC) maturation. Through fine-mapping in a large Italian dataset (4,198 patients with MS and 3,903 controls), we show that the TNFSF14 intronic SNP rs1077667 is the primarily MS-associated variant in the region. Expression quantitative trait locus (eQTL) analysis indicates that the MS risk allele is significantly associated with reduced TNFSF14 messenger RNA levels in blood cells, which is consistent with the allelic imbalance in RNA-Seq reads (P < 0.0001). The MS risk allele is associated with reduced levels of TNFSF14 gene expression (P < 0.01) in blood cells from 84 Italian patients with MS and 80 healthy controls (HCs). Interestingly, patients with MS are lower expressors of TNFSF14 compared to HC (P < 0.007). Individuals homozygous for the MS risk allele display an increased percentage of LIGHT-positive peripheral blood myeloid DCs (CD11c⁺, P = 0.035) in 37 HCs, as well as in in vitro monocyte-derived DCs from 22 HCs (P = 0.04). Our findings suggest that the intronic variant rs1077667 alters the expression of TNFSF14 in immune cells, which may play a role in MS pathogenesis.

Benchmarking the performance of Pool-seq SNP callers using simulated and real sequencing data

Population genomics is a fast-developing discipline with promising applications in a growing number of life sciences fields. Advances in sequencing technologies and bioinformatics tools allow population genomics to exploit genome-wide information to identify the molecular variants underlying traits of interest and the evolutionary forces that modulate these variants through space and time. However, the cost of genomic analyses of multiple populations is still too high to address them through individual genome sequencing. Pooling individuals for sequencing can be a more effective strategy in Single Nucleotide Polymorphism (SNP) detection and allele frequency estimation because of a higher total coverage. However, compared to individual sequencing, SNP calling from pools has the additional difficulty of distinguishing rare variants from sequencing errors, which is often avoided by establishing a minimum threshold allele frequency for the analysis. Finding an optimal balance between minimizing information loss and reducing sequencing costs is essential to ensure the success of population genomics studies. Here, we have benchmarked the performance of SNP callers for Pool-seq data, based on different approaches, under different conditions, and using computer simulations and real data. We found that SNP callers performance varied for allele frequencies up to 0.35. We also found that SNP callers based on Bayesian (SNAPE-pooled) or maximum likelihood (MAPGD) approaches outperform the two heuristic callers tested (VarScan and PoolSNP), in terms of the balance between sensitivity and FDR both in simulated and sequencing data. Our results will help inform the selection of the most appropriate SNP caller not only for large-scale population studies but also in cases where the Pool-seq strategy is the only option, such as in metagenomic or polyploid studies.

Novelty and convergence in adaptation to whole genome duplication

Whole genome duplication (WGD) can promote adaptation but is disruptive to conserved processes, especially meiosis. Studies in Arabidopsis arenosa revealed a coordinated evolutionary response to WGD involving interacting proteins controlling meiotic crossovers, which are minimised in an autotetraploid (within-species polyploid) to avoid mis-segregation. Here we test whether this surprising flexibility of a conserved essential process, meiosis, is recapitulated in an independent WGD system, Cardamine amara, 17 million years diverged from A. arenosa. We assess meiotic stability and perform population-based scans for positive selection, contrasting the genomic response to WGD in C. amara with that of A. arenosa. We found in C. amara the strongest selection signals at genes with predicted functions thought important to adaptation to WGD: meiosis, chromosome remodelling, cell cycle, and ion transport. However, genomic responses to WGD in the two species differ: minimal ortholog-level convergence emerged, with none of the meiosis genes found in A. arenosa exhibiting strong signal in C. amara. This is consistent with our observations of lower meiotic stability and occasional clonal spreading in diploid C. amara, suggesting that nascent C. amara autotetraploid lineages were preadapted by their diploid lifestyle to survive while enduring reduced meiotic fidelity. However, in contrast to a lack of ortholog convergence, we see process-level and network convergence in DNA management, chromosome organisation, stress signalling, and ion homeostasis processes. This gives the first insight into the salient adaptations required to meet the challenges of a WGD state and shows that autopolyploids can utilize multiple evolutionary trajectories to adapt to WGD.

Quantitative and Qualitative QC of Next-Generation Sequencing for Detecting Somatic Variants: An Example of Detecting Clonal Hematopoiesis of Indeterminate Potential

BACKGROUND

Because next-generation sequencing (NGS) for detecting somatic mutations has been adopted in clinical fields, both qualitative and quantitative QC of the somatic variants through whole coding regions detected by NGS is crucial. However, specific applications or guidelines, especially for quantitative QC, are currently insufficient. Our goal was to devise a practical approach for both quantitative and qualitative QC using an example of detecting clonal hematopoiesis of indeterminate potential (CHIP).

METHODS

We applied the QC scheme using commercial reference materials and in-house QC materials (IQCM) composed of haplotype map and cancer cell lines for monitoring CHIP.

RESULTS

This approach efficiently validated a customized CHIP NGS assay. Accuracy, analytical sensitivity, analytical specificity, qualitative precision (concordance), and limit of detection achieved were 99.87%, 98.53%, 100.00%, 100.00%, and 1.00%, respectively. The quantitative precision analysis also had a higher CV percentage at a lower alternative read depth (R2 = 0.749∼0.858). Use of IQCM ensured more than 100-fold reduction in the cost per run compared with that achieved using commercial reference materials.

CONCLUSION

Our approach determined the general analytical performance of NGS for detecting CHIP and recognized limitations such as lower precision at a lower level of variant burden. This approach could also be theoretically expanded to a general NGS assay for detecting somatic variants. Considering the reliable NGS results and cost-effectiveness, we propose the use of IQCM for QC of NGS assays at clinical laboratories.

Group testing can improve the cost-efficiency of prospective-retrospective biomarker studies

BACKGROUND

Cancer treatment is increasingly dependent on biomarkers for prognostication and treatment selection. Potential biomarkers are frequently evaluated in prospective-retrospective studies in which biomarkers are measured retrospectively on archived specimens after completion of prospective clinical trials. In light of the high costs of some assays, random sampling designs have been proposed that measure biomarkers for a random sub-sample of subjects selected on the basis of observed outcome and possibly other variables. Compared with a standard design that measures biomarkers on all subjects, a random sampling design can be cost-efficient in the sense of reducing the cost of the study substantially while achieving a reasonable level of precision.

METHODS

For a biomarker that indicates the presence of some molecular alteration (e.g., mutation in a gene), we explore the use of a group testing strategy, which involves physically pooling specimens across subjects and assaying pooled samples for the presence of the molecular alteration of interest, for further improvement in cost-efficiency beyond random sampling. We propose simple and general approaches to estimating the prognostic and predictive values of biomarkers with group testing, and conduct simulation studies to validate the proposed estimation procedures and to assess the cost-efficiency of the group testing design in comparison to the standard and random sampling designs.

RESULTS

Simulation results show that the proposed estimation procedures perform well in realistic settings and that a group testing design can have considerably higher cost-efficiency than a random sampling design.

CONCLUSIONS

Group testing can be used to improve the cost-efficiency of biomarker studies.

Convergent Adaptation to Quantitative Host Resistance in a Major Plant Pathogen

Plant pathogens can adapt to quantitative resistance, eroding its effectiveness. The aim of this work was to reveal the genomic basis of adaptation to such a resistance in populations of the fungus Pseudocercospora fijiensis, a major devastating pathogen of banana, by studying convergent adaptation on different cultivars. Samples from P. fijiensis populations showing a local adaptation pattern on new banana hybrids with quantitative resistance were compared, based on a genome scan approach, with samples from traditional and more susceptible cultivars in Cuba and the Dominican Republic. Whole-genome sequencing of pools of P. fijiensis isolates (pool-seq) sampled from three locations per country was conducted according to a paired population design. The findings of different combined analyses highly supported the existence of convergent adaptation on the study cultivars between locations within but not between countries. Five to six genomic regions involved in this adaptation were detected in each country. An annotation analysis and available biological data supported the hypothesis that some genes within the detected genomic regions may play a role in quantitative pathogenicity, including gene regulation. The results suggested that the genetic basis of fungal adaptation to quantitative plant resistance is at least oligogenic, while highlighting the existence of specific host-pathogen interactions for this kind of resistance.IMPORTANCE Understanding the genetic basis of pathogen adaptation to quantitative resistance in plants has a key role to play in establishing durable strategies for resistance deployment. In this context, a population genomic approach was developed for a major plant pathogen (the fungus Pseudocercospora fijiensis causing black leaf streak disease of banana) whereby samples from new resistant banana hybrids were compared with samples from more susceptible conventional cultivars in two countries. A total of 11 genomic regions for which there was strong evidence of selection by quantitative resistance were detected. An annotation analysis and available biological data supported the hypothesis that some of the genes within these regions may play a role in quantitative pathogenicity. These results suggested a polygenic basis of quantitative pathogenicity in this fungal pathogen and complex molecular plant-pathogen interactions in quantitative disease development involving several genes on both sides.

Describing variability in pig genes involved in coronavirus infections for a One Health perspective in conservation of animal genetic resources

Coronaviruses silently circulate in human and animal populations, causing mild to severe diseases. Therefore, livestock are important components of a “One Health” perspective aimed to control these viral infections. However, at present there is no example that considers pig genetic resources in this context. In this study, we investigated the variability of four genes (ACE2, ANPEP and DPP4 encoding for host receptors of the viral spike proteins and TMPRSS2 encoding for a host proteinase) in 23 European (19 autochthonous and three commercial breeds and one wild boar population) and two Asian Sus scrofa populations. A total of 2229 variants were identified in the four candidate genes: 26% of them were not previously described; 29 variants affected the protein sequence and might potentially interact with the infection mechanisms. The results coming from this work are a first step towards a “One Health” perspective that should consider conservation programs of pig genetic resources with twofold objectives: (i) genetic resources could be reservoirs of host gene variability useful to design selection programs to increase resistance to coronaviruses; (ii) the described variability in genes involved in coronavirus infections across many different pig populations might be part of a risk assessment including pig genetic resources.

A pilot study of red complex and three genera subgingival microbiome in periodontitis subjects with and without diabetes, evaluated by MinION platform

Background: Subgingival niche is one biofilm habitat containing rich microbiota, which plays an active role in maintaining the health of periodontal tissue and determining host response. As such, a study of changing subgingival biofilms is important for understanding the effect of a systemic condition. In this study, we compared the occurrence of six bacteria cohabiting in the subgingival area of periodontitis subjects, with (DP, n = 8) and without (NDP, n = 4) diabetes. Methods: The six genus and species of targeted bacteria were confirmed by 16S rRNA amplicon sequencing on MinION nanopore platform. Descriptive statistic was used to describe the obtained data. Results: We found that the six genus and species of targeted bacteria were detected but in different quantities in either group's periodontal pocket. Our data showed that Tannerella forsythia was the most abundant species in subgingival biofilms of the DP group of the red complex bacteria. In contrast, Aggregatibacter sp., which belongs to the phylum of proteobacteria, was present at a relatively lower level. In contrast, Fusobacterium sp., which belongs to orange complex bacteria, showed relative similarities in subgingival biofilms of both groups tested, while Veillonella sp., were abundant in the DP groups.  Conclusions: Our data show that the diversity of classic periodontopathogens increased in the subgingival niche of periodontitis subjects with diabetes. It is the first study in Indonesia to apply MinION-based, full-length 16S rRNA amplicon sequencing in periodontitis patients with and without diabetes.

A pilot study of red complex and three genera subgingival microbiome in periodontitis subjects with and without diabetes, evaluated by MinION platform

Background: Subgingival niche is one biofilm habitat containing rich microbiota, which plays an active role in maintaining the health of periodontal tissue and determining host response. As such, a study of changing subgingival biofilms is important for understanding the effect of a systemic condition. In this study, we compared the occurrence of six bacteria cohabiting in the subgingival area of periodontitis subjects, with (DP, n = 8) and without (NDP, n = 4) diabetes.

Methods: The six genus and species of targeted bacteria were confirmed by 16S rRNA amplicon sequencing on MinION nanopore platform. Descriptive statistic was used to describe the obtained data.

Results: We found that the six genus and species of targeted bacteria were detected but in different quantities in either group's periodontal pocket. Our data showed that Tannerella forsythia was the most abundant species in subgingival biofilms of the DP group of the red complex bacteria. In contrast, Aggregatibacter sp., which belongs to the phylum of proteobacteria, was present at a relatively lower level. In contrast, Fusobacterium sp., which belongs to orange complex bacteria, showed relative similarities in subgingival biofilms of both groups tested, while Veillonella sp., were abundant in the DP groups. 

Conclusions: Our data show that the diversity of classic periodontopathogens increased in the subgingival niche of periodontitis subjects with diabetes. It is the first study in Indonesia to apply MinION-based, full-length 16S rRNA amplicon sequencing in periodontitis patients with and without diabetes.

Identification and computational analysis of USH1C, and SLC26A4 variants in Pakistani families with prelingual hearing loss

Hearing loss (HL) is clinically and genetically heterogeneous disorder and is the most frequent occurring sensory deficit in humans. This study was conducted to decipher the genetic cause of HL occurring in two large consanguineous Pakistani families (GCNF-01, GCNF-03). Family history and pure tone audiometry of both families suggested prelingual HL, while the affected individuals of GCNF-01 also had low vision and balance problems, consistent with cardinal features of Usher syndrome type I (USH1). Exome sequencing followed by segregating analysis revealed a novel splice site variant (c.877-1G > A) of USH1C occurring with USH1 phenotype in family GCNF01. While the affected individual of family GCNF-03 were homozygous for the c.716 T > A, p.(Val239Asp) previously reported pathogenic variant of SLC26A4. Both variants have very low frequencies in control database. In silico mutagenesis and 3-dimensional simulation analyses revealed that both variants have deleterious impact on the proteins folding and secondary structures. Our study expands the mutation spectrum of the HL genes and emphasizes the utility of exome sequencing coupled with bioinformatics tools for clinical genetic diagnosis, prognosis, and family counseling.