Genome-wide Single Nucleotide Polymorphism Research Articles

Screening of heat stress-tolerant weedy rice and SNP identification of heat-tolerance-related genes

AbstractRice, a staple crop that feeds more than one-third of the world’s population, encounters a wide range of biotic and abiotic stresses due to climate change. Rising temperature is one of the significant abiotic stresses affecting rice productivity worldwide. The development of heat-tolerant rice cultivars is critical in this regard. Weedy rice could potentially serve as a natural resource for genes conferring agronomically important traits beneficial to cultivated rice. However, heat tolerance in both cultivated and weedy rice is still understudied. This study screened a set of 180 weedy rice accessions for heat stress tolerance and further characterised them using genome-wide single-nucleotide polymorphisms (SNPs) analysis. Five heat-tolerant (HT) accessions (MU244, MU235, MU249, MU260 and MU237), along with five heat-susceptible (HS) accessions (MU100, MU114, MU264, MU251 and MU005), were subjected to relative electrical conductivity (REC) test and reactive oxidative species assay (ROS). These tests verified that the five HT accessions performed better under heat stress than their HS counterparts. In addition, whole-genome sequences of three HT (MU235, MU237 and MU066) and four HS (MU100, MU114, MU022 and MU005) accessions were selected for the genome-wide SNPs comparison, revealing substantial amino acid variation in the heat-tolerance-related genes between the HT and HS rice groups. The proposed genes and genome-wide SNP markers may help rice breeders better understand how different rice cultivars respond to heat stress.

Genome-wide SNPs and candidate genes underlying the genetic variations for protein and amino acids in pearl millet (Pennisetum glaucum) germplasm

Main conclusionA total of 544 significant marker-trait associations and 286 candidate genes associated with total protein and 18 amino acids were identified. Thirty-three candidate genes were found near the strong marker trait associations (– log10P ≥ 5.5).Pearl millet (Pennisetum glaucum) is largely grown as a subsistence crop in South Asia and sub-Saharan Africa. It serves as a major source of daily protein intake in these regions. Despite its importance, no systematic effort has been made to study the genetic variations of protein and amino acid content in pearl millet germplasm. The present study was undertaken to dissect the global genetic variations of total protein and 18 essential and non-essential amino acids in pearl millet, using a set of 435 K Single Nucleotide Polymorphisms (SNPs) and 161 genotypes of the Pearl Millet Inbred Germplasm Association Panel (PMiGAP). A total of 544 significant marker-trait associations (at P < 0.0001; – log10P ≥ 4) were detected and 23 strong marker-trait associations were identified using Bonferroni’s correction method. Forty-eight pleiotropic loci were found in the genome for the studied traits. In total, 286 candidate genes associated with total protein and 18 amino acids were identified. Thirty-three candidate genes were found near strongly associated SNPs. The associated markers and the candidate genes provide an insight into the genetic architecture of the traits studied and are going to be useful in breeding improved pearl millet varieties in the future. Availabilities of improved pearl millet varieties possessing higher protein and amino acid compositions will help combat the rising malnutrition problem via diet.

Mapping quantitative trait loci for seminal root angle in a selected durum wheat population.

Seminal root angle (SRA) is an important root architectural trait associated with drought adaptation in cereal crops. To date, all attempts to dissect the genetic architecture of SRA in durum wheat (Triticum durum Desf.) have used large association panels or structured mapping populations. Identifying changes in allele frequency generated by selection provides an alternative genetic mapping approach that can increase the power and precision of QTL detection. This study aimed to map quantitative trait loci (QTL) for SRA by genotyping durum lines created through divergent selection using a combination of marker-assisted selection (MAS) for the major SRA QTL (qSRA-6A) and phenotypic selection for SRA over multiple generations. The created 11 lines (BC1F2:5) were genotyped with genome-wide single-nucleotide polymorphism (SNP) markers to map QTL by identifying markers that displayed segregation distortion significantly different from the Mendelian expectation. QTL regions were further assessed in an independent validation population to confirm their associations with SRA. The experiment revealed 14 genomic regions under selection, 12 of which have not previously been reported for SRA. Five regions, including qSRA-6A, were confirmed in the validation population. The genomic regions identified in this study indicate that the genetic control of SRA is more complex than previously anticipated. Our study demonstrates that selection mapping is a powerful approach to complement genome-wide association studies for QTL detection. Moreover, the verification of qSRA-6A in an elite genetic background highlights the potential for MAS, although it is necessary to combine additional QTL to develop new cultivars with extreme SRA phenotypes.

Functional ex vivo DNA fibre assay to measure replication dynamics in breast cancer tissue.

Replication stress (RS) is a key trait of cancer cells, and a potential actionable target in cancer treatment. Accurate methods to measure RS in tumour samples are currently lacking. DNA fibre analysis has been used as a common technique to measure RS in cell lines. Here, we investigated DNA fibre analysis on fresh breast cancer specimens and correlated DNA replication kinetics to known RS markers and genomic alterations. Fresh, treatment-naïve primary breast cancer samples (n = 74) were subjected to ex vivo DNA fibre analysis to measure DNA replication kinetics. Tumour cell proliferation was confirmed by EdU incorporation and cytokeratin AE1/AE3 (CK) staining. The RS markers phospho-S33-RPA and γH2AX and the RS-inducing proto-oncogenes Cyclin E1 and c-Myc were analysed by immunohistochemistry. Copy number variations (CNVs) were assessed from genome-wide single nucleotide polymorphism (SNP) arrays. We found that the majority of proliferating (EdU-positive) cells in each sample were CK-positive and therefore considered to be tumour cells. DNA fibre lengths varied largely in most tumour samples. The median DNA fibre length showed a significant inverse correlation with pRPA expression (r = -0.29, p = 0.033) but was not correlated with Cyclin E1 or c-Myc expression and global CNVs in this study. Nuclear Cyclin E1 expression showed a positive correlation with pRPA levels (r = 0.481, p < 0.0001), while cytoplasmic Cyclin E1 expression exhibited an inverse association with pRPA expression (r = -0.353, p = 0.002) and a positive association with global CNVs (r = 0.318, p = 0.016). In conclusion, DNA fibre analysis performed with fresh primary breast cancer samples is feasible. Fibre lengths were associated with pRPA expression. Cyclin E1 expression was associated with pRPA and the percentage of CNVs. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Phylogeography and genetic structure of Papaver bracteatum populations in Iran based on genotyping-by-sequencing (GBS)

Papaver bracteatum, known for its high thebaine content and absence of morphine, has emerged as a promising alternative to opium poppy for codeine production. In this study, our objective was to create a diverse panel representing the natural variation of this species in Iran. To achieve this, we employed genotyping-by-sequencing to obtain genome-wide distributed single-nucleotide polymorphisms (SNPs) for phylogeographic analysis, population structure assessment, and evaluation of genetic diversity within P. bracteatum populations. A total of 244 P. bracteatum individuals from 13 distinct populations formed seven genetic groups, along with one highly admixed population. We observed a clear split between the populations inhabiting the Alborz Mts. in the east and Zagros Mts. in the west. In between these mountain ranges, the population of Kachal Mangan exhibited a high degree of genetic admixture between both genetic groups. At or after the end of the last glacial maximum, when climate conditions rapidly changed, all P. bracteatum populations experienced a strong demographic bottleneck reducing the already small effective population sizes further before they increased to their recent strengths. Our results suggest that the ongoing climate change together with human pressure on the species’ habitats and limited seed-dispersal ability are potential factors contributing today to rising genetic isolation of P. bracteatum populations. Our results provide genetic data that can be used for conservation measures to safeguard the species’ genetic diversity as a resource for future breeding approaches in this medicinally important species.

Phylogenetic relationships and genetic diversity of the Korean endemic Phedimus latiovalifolius (Crassulaceae) and its close relatives

Phedimus latiovalifolius (Y.N.Lee) D.C.Son & H.J.Kim is exclusively distributed in the high mountains in the Korean Peninsula, mainly along the Baekdudaegan mountain range. Despite its morphological and distributional distinction from other Phedimus Raf. species, its taxonomic identity and phylogenetic relationship with congeneric species remain unclear. This study employs genotyping-by-sequencing-derived genome-wide single nucleotide polymorphisms to establish the monophyly of P. latiovalifolius and its relationship with closely related species. Genetic diversity and population differentiation of P. latiovalifolius are also assessed to provide baseline genetic information for future conservation and management strategies. Our phylogenetic analyses robustly demonstrate the monophyletic nature of P. latiovalifolius, with P. aizoon (L.) ‘t Hart identified as its closest sister lineage. There is no genetic evidence supporting a hybrid origin of P. latiovalifolius from P. aizoon involving either P. ellacombeanus (Praeger) ‘t Hart or P. kamtschaticus (Fisch.) ‘t Hart. Population genetic analyses reveal two major groups within P. latiovalifolius. A higher genetic variation is observed in P. ellacombeanus than in the congeneric species. Notably, most of the genetic variation exists within P. latiovalifolius populations. Given its distribution and the potential role of Baekdudaegan as an East Asian Pleistocene refugia, P. latiovalifolius could be considered rare and endemic, persisting in the refugium across glacial/interglacial cycles.

Disentangling the causal effects of education and participation bias on Alzheimer's disease using Mendelian Randomization.

People with university degrees have a lower incidence of Alzheimer's Disease (AD). However, the relationship between education and AD could be due to selection, collider, and ascertainment biases, such as lower familiarity with cognitive testing or the fact that those with degrees are more likely to participate in research. Here, we use two-sample Mendelian randomization (MR) to investigate the causal relationships between education, participation, and AD. We used genome-wide association study (GWAS) summary statistics for educational attainment, three different measures of participation, AD (clinically diagnosed AD), and AD/ADRD (clinical diagnosis and family history of AD and related dementias). Independent genome-wide significant single nucleotide polymorphisms (SNPs) were extracted from the exposure summary statistics and harmonized with the outcome SNPs. Fixed-effects inverse variance weighted meta-analysis was the primary MR method; Cochran's Q statistic and MR Egger intercept were used to test for heterogeneity and pleiotropy, and Radial-MR was used to identify outliers. Sensitivity analyses included MR Egger, Weighted Median, and Weighted mode. Bidirectional analyses were used to test if AD pathology affects participation and multivariable MR (MVMR) assessed independent exposure-outcome effects. Educational attainment reduced the risk of AD (OR IVW 95% CI= 0.70 [0.63, 0.79], p = 8e-10), and the results were robust based on sensitivity analyses. However, education increased the risk of AD/ADRD, though the results were not robust to sensitivity analyses (OR IVW 95% CI= 1.09 [1.02, 1.15], p = 0.006). Participation in MHQ reduced the odds of AD (OR IVW 95% CI= 0.325 [0.128, 0.326], p = 0.01). When adjusting for participation in MVMR, education remained associated with a reduced risk of AD (OR IVW 95% CI= 0.76 [0.62, 0.92], p = 0.006). Univariate MR analyses indicated that education and participation reduced the risk of AD. However, MR also suggested that education increased the risk of AD/ADRD, highlighting the inconsistencies between clinical and proxy diagnoses of AD, as proxy-AD may be affected by selection, collider, or ascertainment bias. MVMR indicated that participation is unlikely to explain the effect of education on AD identified in MR, and the protective effect of educational attainment may be due to other biological mechanisms, such as cognitive reserve.

Missing genotype imputation in non-model species using self-organizing maps.

Current methodologies of genome-wide single-nucleotide polymorphism (SNP) genotyping produce large amounts of missing data that may affect statistical inference and bias the outcome of experiments. Genotype imputation is routinely used in well-studied species to buffer the impact in downstream analysis, and several algorithms are available to fill in missing genotypes. The lack of reference haplotype panels precludes the use of these methods in genomic studies on non-model organisms. As an alternative, machine learning algorithms are employed to explore the genotype data and to estimate the missing genotypes. Here, we propose an imputation method based on self-organizing maps (SOM), a widely used neural networks formed by spatially distributed neurons that cluster similar inputs into close neurons. The method explores genotype datasets to select SNP loci to build binary vectors from the genotypes, and initializes and trains neural networks for each query missing SNP genotype. The SOM-derived clustering is then used to impute the best genotype. To automate the imputation process, we have implemented gtImputation, an open-source application programmed in Python3 and with a user-friendly GUI to facilitate the whole process. The method performance was validated by comparing its accuracy, precision and sensitivity on several benchmark genotype datasets with other available imputation algorithms. Our approach produced highly accurate and precise genotype imputations even for SNPs with alleles at low frequency and outperformed other algorithms, especially for datasets from mixed populations with unrelated individuals.

Genetic and morphological evidence support the specific status of the endemic Ericaandevalensis (Ericales, Ericaceae).

Assessing the taxonomic status of closely related taxa is crucial in plant systematics and can have important implications for conservation and human plant use. Ericaandevalensis Cabezudo & Rivera is a metallophyte endemic species from highly metal-polluted soils of SW Iberian Peninsula, an area with a mining history going back more than 5,000 years. Ericaandevalensis is closely related to Ericamackayana Bab., a northern Iberian species also present in western Ireland. The status of E.andevalensis as a species or subspecies subordinated to E.mackayana is subject to debate. Here, we assessed the genetic and phenotypic relationship between both species, including the population structure of E.andevalensis. We used high throughput sequencing to determine genome-wide Single Nucleotide Polymorphisms (SNPs), and morphometric analyses from 35 reproductive and vegetative traits. The morphological analysis showed at least eight characters that can discriminate the two species, from which ovary hairiness and the size of leaf glandular hairs were the most informative. Genetic analyses showed that each species formed a monophyletic cluster with full support, separated by an interspecific genetic distance >4-fold higher than intra-specific distance. Population genetic analyses of E.andevalensis shows that populations are highly structured, with the Portuguese one as the most isolated and less variable. These results support the recognition of E.andevalensis as a distinct species with a highly constrained ecological requirements and a narrow geographic distribution, but with a limited gene flow between populations. We discuss the implications of these outcomes in conservation policies and potential uses of E.andevalensis such as decontamination of polluted soils.

Drivers of genomic diversity and phenotypic development in early phases of domestication in Hermetia illucens.

The black soldier fly (BSF), Hermetia illucens, has the ability to efficiently bioremediate organic waste into usable bio-compounds. Understanding the impact of domestication and mass rearing on fitness and production traits is therefore important for sustainable production. This study aimed to assess patterns of genomic diversity and its association to phenotypic development across early generations of mass rearing under two selection strategies: selection for greater larval mass (SEL lines) and no direct artificial selection (NS lines). Genome-wide single nucleotide polymorphism (SNP) data were generated using 2bRAD sequencing, while phenotypic traits relating to production and population fitness were measured. Declining patterns of genomic diversity were observed across three generations of captive breeding, with the lowest diversity recorded for the F3 generation of both selection lines, most likely due to founder effects. The SEL cohort displayed statistically significantly greater larval weight com the NS lines with pronounced genetic and phenotypic directional changes across generations. Furthermore, lower genetic and phenotypic diversity, particularly for fitness traits, were evident for SEL lines, illustrating the trade-off between selecting for mass and the resulting decline in population fitness. SNP-based heritability was significant for growth, but was low or non-significant for fitness traits. Genotype-phenotype correlations were observed for traits, but individual locus effect sizes where small and very few of these loci demonstrated a signature for selection. Pronounced genetic drift, due to small effective population sizes, is likely overshadowing the impacts of selection on genomic diversity and consequently phenotypic development. The results hold particular relevance for genetic management and selective breeding for BSF in future.

Respiratory infection- and asthma-prone, low vaccine responder children demonstrate distinct mononuclear cell DNA methylation pathways

BackgroundInfants with frequent viral and bacterial respiratory infections exhibit compromised immunity to routine immunizations. They are also more likely to develop chronic respiratory diseases in later childhood. This study investigated the feasibility of epigenetic profiling to reveal endotype-specific molecular pathways with potential for early identification and immuno-modulation. Peripheral blood mononuclear cells from respiratory infection allergy/asthma-prone (IAP) infants and non-infection allergy/asthma prone (NIAP) were retrospectively selected for genome-wide DNA methylation and single nucleotide polymorphism analysis. The IAP infants were enriched for the low vaccine responsiveness (LVR) phenotype (Fisher's exact p-value = 0.02).ResultsAn endotype signature of 813 differentially methylated regions (DMRs) comprising 238 lead CpG associations (FDR < 0.05) emerged, implicating pathways related to asthma, mucin production, antigen presentation and inflammasome activation. Allelic variation explained only a minor portion of this signature. Stimulation of mononuclear cells with monophosphoryl lipid A (MPL), a TLR agonist, partially reversed this signature at a subset of CpGs, suggesting the potential for epigenetic remodeling.ConclusionsThis proof-of-concept study establishes a foundation for precision endotyping of IAP children and highlights the potential for immune modulation strategies using adjuvants for future investigation.

O-271 Two component resolution of mosaic samples in PGT-A: primary template amplification (PTA) and independent analysis using copy-number variation and allelic balance

Abstract Study question How does accurate, unbiased whole genome amplification and tiered, independent, two component analysis impact PGT-A results? Summary answer When compared to previous methods a PGT-A workflow utilizing PTA followed by a CNV and allelic balance-based analysis generated more conclusive results. What is known already Accurate PGT-A results require unbiased error-free whole genome amplification from the trophectoderm biopsy and smart bioinformatics utilities to fully analyze and consider the large complex datasets. PTA generates fewer errors, greater coverage, and reduced allele drop-out offering the best starting point to interpret the genome of each embryo. Current PGT-A platforms leverage either normalized CNV data OR allelic balance at single nucleotide polymorphisms (SNPs), to detect alterations in the embryonic genome. A pipeline leveraging improved amplification technology and consolidated CNV and SNP data, particularly for putative mosaic and segmental mosaic calls, could reduce uncertainty and provide more accurate PGT-A results. Study design, size, duration A retrospective analysis of PGT-A results was undertaken with samples originating from multiple clinics and processed in a single laboratory, from January through December, 2023. Approximately 500 samples were processed simultaneously through two independent PGT-A pipelines. The primary objective was to compare the performance of CNV-only PGT-A with a test leveraging both CNV and SNP data. A secondary objective was to observe the resolution of mosaic embryos. Participants/materials, setting, methods De-identified samples were amplified with PTA and sequenced with both shotgun (coverage-based CNV) and capture (SNP-based)-approaches. Method specific analysis was applied to the resulting data. An initial bioinformatics approach analyzed CNV data only for variations in copy-number along the genome, proposing stretches of aneuploidy or mosaicism. A second, tiered analysis extended this data and incorporated SNP-based allelic balance to evaluate candidate regions and confirm the presence of aneuploidy and/or quantify mosaic levels. Main results and the role of chance Genome-wide read coverage and SNP data confirmed that PTA accurately and completely amplified the genetic material in each sample with broad distribution of informative data and a low allele drop-out rate. High concordance (95%) was observed for euploid and full aneuploid (whole chromosome and segmental) embryos classified with CNV-alone and CNV/SNV combined analysis. SNP data was processed, and B-allele ratios were used to confirm aneuploidies with particular utility in resolving the location of segmental changes. The classification of mosaic samples was altered in the pipeline leveraging both CNV and SNP data. Of 54 mosaic samples tested, 75% remained mosaic after independent consideration of SNP data, ∼15% and 6% of high-level mosaics were resolved to full aneuploid and euploid, respectively, and ∼25% of low-level mosaics reverted to a euploid classification. The deep SNP data produced during targeted sequencing confirmed the altered allele ratio predicted by CNV data and re-confirmed the presence and proportion of aneuploid cells. Mosaic levels were highly correlated in 90% of re-confirmed mosaic samples. This suggests that the classification of these samples as mosaic is precise and accurate and suggests a strong utility for a two component PGT-A pipeline leveraging CNV and SNV data generated from PTA embryos. Limitations, reasons for caution This was a retrospective study with limited sample numbers. Wider implications of the findings The study highlights the strong advantages of a hybrid PGT-A pipeline, leveraging PTA and two component analysis of coverage and allelic balance, particularly to resolve mosaic embryos more accurately. Overall, this could reduce uncertainty and deliver more confident PGT-A results for embryo transfer decision making. Trial registration number not applicable

On the road to losing connectivity: Faecal samples provide genome-wide insights into anthropogenic impacts on two large herbivore species in central India.

Humans have impacted most of the planet, and the ensuing fragmentation results in small, isolated habitat patches posing a risk of genetic diversity loss, inbreeding, and genetic load. Understanding how natural and anthropogenic landscape features affect gene flow among habitat patches is critical for maintaining connectivity. Genome-wide data are required to comprehend the impacts of recent fragmentation, which can be challenging when only non-invasive samples are available. Here, we build upon advancements in conservation genomics to address connectivity of two large herbivores, gaur (Bos gaurus) and sambar (Rusa unicolor) in central India. Given their habitat associations, we expected these species to respond similarly to habitat fragmentation. We used faecal-DNA and methylation-based host-DNA enrichment with modified ddRAD protocol to generate genome-wide single-nucleotide polymorphism (SNP) data for 124 gaur and 99 sambar individuals. Our findings reveal that gaur populations in central India are fragmented, displaying high genetic differentiation, with drift significantly affecting small populations like Umred Karhandla Wildlife Sanctuary. Although sambar shows low genetic structure, another small population, Bor Tiger Reserve is genetically differentiated. Our results suggest that although land cover change and roads restrict animal movement, the extent of this impact varies across the two species. We show that different species respond differently to landscape features, even with similar habitat associations. We highlight small and isolated populations requiring urgent conservation intervention. Such multi-species approaches enhance our understanding of cross-species connectivity patterns. We suggest shifting from single-species to multi-species holistic conservation approach in rapidly developing landscapes to better manage co-occurring endangered species.

Genome-wide association study provided insights into the polled phenotype and polled intersex syndrome (PIS) in goats

BackgroundBreeding polled goats is a welfare-friendly approach for horn removal in comparison to invasive methods. To gain a comprehensive understanding of the genetic basis underlying polledness in goats, we conducted whole-genome sequencing of 106 Xinong Saanen dairy goats, including 33 horned individuals, 70 polled individuals, and 3 polled intersexuality syndrome (PIS) individuals.MethodsThe present study employed a genome-wide association study (GWAS) and linkage disequilibrium (LD) analysis to precisely map the genetic locus underlying the polled phenotype in goats.ResultsThe analysis conducted in our study revealed a total of 320 genome-wide significant single nucleotide polymorphisms (SNPs) associated with the horned/polled phenotype in goats. These SNPs exhibited two distinct peaks on chromosome 1, spanning from 128,817,052 to 133,005,441 bp and from 150,336,143 to 150,808,639 bp. The present study identified three genome-wide significant SNPs, namely Chr1:129789816, Chr1:129791507, and Chr1:129791577, as potential markers of PIS-affected goats. The results of our LD analysis suggested a potential association between MRPS22 and infertile intersex individuals, as well as a potential association between ERG and the polled trait in goats.ConclusionWe have successfully identified three marker SNPs closely linked to PIS, as well as several candidate genes associated with the polled trait in goats. These results may contribute to the development of SNP chips for early prediction of PIS in goats, thereby facilitating breeding programs aimed at producing fertile herds with polled traits.

Imputation of single nucleotide polymorphism genotypes in ungenotyped sport horses from the genotypes of their progeny

Many sport horse studbooks worldwide use microsatellite markers for parentage verification. However, many have expressed a desire to introduce genomic selection using genome-wide dense single nucleotide polymorphism (SNP) genotypes to complement their current breeding programs. Hence, it does not make sense to genotype the same animal for both microsatellite markers and SNPs markers. Transitioning to SNP-based parentage verification is an obvious solution but one barrier to this transition is the lack of SNP data on parents from which to verify parentage against. Therefore, the objective of this study was to assess the ability to impute the SNP genotype of a stallion from the genotypes of its progeny, with or without the consideration of the genotype of the progeny’s dam. Genotype information from 55 935 SNPs was available on 13 327 horses. A total of 98 stallions had genotype data on 10 progeny and the genotypes of these stallions were used as a test population. Genome-wide genotype imputation was undertaken combining a family- and population-based imputation approach. Several different scenarios were assessed to quantify the ability to accurately impute the genotype of a stallion based on genotype data of incrementally more half-sibling progeny. Using genomic information from four progeny the average genotype concordance of the imputed sire genotype compared to the actual sire’s genotype was 0.932. The average genotype concordance rate increased to 0.960 when the genotypes of 10 progeny were included in the imputation process. The inclusion of the genotypes of the dams of the progeny improved the concordance rate from 0.932 to 0.977 when based on the genotype of just four progeny and their dams and from 0.960 to 0.996 when based on the genotype of 10 progeny and their dams. These results suggest it is possible to impute the genotype of a non-genotyped horse from the genotypes of its progeny and that the inclusion of the genotypes of the dams of the progeny improves this imputation accuracy further.

Genetic characterization of cucumber genetic resources in the NARO Genebank indicates their multiple dispersal trajectories to the East

Key messageGenotyping-by-sequencing of 723 worldwide cucumber genetic resources revealed that cucumbers were dispersed eastward via at least three distinct routes, one to Southeast Asia and two from different directions to East Asia.The cucumber (Cucumis sativus) is an economically important vegetable crop cultivated and consumed worldwide. Despite its popularity, the manner in which cucumbers were dispersed from their origin in South Asia to the rest of the world, particularly to the east, remains a mystery due to the lack of written records. In this study, we performed genotyping-by-sequencing (GBS) on 723 worldwide cucumber accessions, mainly deposited in the Japanese National Agriculture and Food Research Organization (NARO) Genebank, to characterize their genetic diversity, relationships, and population structure. Analyses based on over 60,000 genome-wide single-nucleotide polymorphisms identified by GBS revealed clear genetic differentiation between Southeast and East Asian populations, suggesting that they reached their respective region independently, not progressively. A deeper investigation of the East Asian population identified two subpopulations with different fruit characteristics, supporting the traditional classification of East Asian cucumbers into two types thought to have been introduced by independent routes. Finally, we developed a core collection of 100 accessions representing at least 93.2% of the genetic diversity present in the entire collection. The genetic relationships and population structure, their associations with geographic distribution and phenotypic traits, and the core collection presented in this study are valuable resources for elucidating the dispersal history and promoting the efficient use and management of genetic resources for research and breeding in cucumber.

Exploring the causal effects of sleep characteristics on TMD-related pain: a two-sample Mendelian randomization study.

The study was to explore the causal effects of sleep characteristics on temporomandibular disorder (TMD)-related pain using Mendelian randomization (MR) analysis. Five sleep characteristics (short sleep, insomnia, chronotype, snoring, sleep apnea) were designated as exposure factors. Data were obtained from previous publicized genome-wide association studies and single nucleotide polymorphisms (SNPs) strongly associated with them were utilized as instrumental variables (IVs). TMD-related pain was designed as outcome variable and sourced from the FinnGens database. MR analysis was employed to explore the causal effects of the five sleep characteristics on TMD-related pain. The causal effect was analyzed using the inverse variance-weighted (IVW), weighted median, and MR-Egger methods. Subsequently, sensitivity analyses were conducted using Cochran's Q tests, funnel plots, leave-one-out analyses, and MR-Egger intercept tests. A causal effect of short sleep on TMD-related pain was revealed by IVW (OR: 1.60, 95% CI: 1.06-2.41, P = 0.026). No causal relationship was identified between other sleep characteristics (insomnia, chronotype, snoring, sleep apnea) and TMD-related pain. Our study suggests that short sleep may increase the risk of TMD-related pain, while there was no causal relationship between other sleep characteristics and TMD-related pain. Further studies are warranted to deepen and definitively clarify their relationship. These findings reveal that the short sleep may be a risk factor of TMD-related pain and highlight the potential therapeutical effect of extending sleep time on alleviating TMD-related pain.

Genome-wide association study for yield and quality of granulated cassava processed product.

The starchy storage roots of cassava are commonly processed into a variety of products, including cassava granulated processed products (gari). The commercial value of cassava roots depends on the yield and quality of processed products, directly influencing the acceptance of new varieties by farmers, processors, and consumers. This study aims to estimate genetic advance through phenotypic selection and identify genomic regions associated and candidate genes linked with gari yield and quality. Higher single nucleotide polymorphism (SNP)-based heritability estimates compared to broad-sense heritability estimates were observed for most traits highlighting the influence of genetic factors on observed variation. Using genome-wide association analysis of 188 clones, genotyped using 53,150 genome-wide SNPs, nine SNPs located on seven chromosomes were significantly associated with peel loss, gari yield, color parameters for gari and eba, bulk density, swelling index, and textural properties of eba. Future research will focus on validating and understanding the functions of identified genes and their influence on gari yield and quality traits.

Precision Medicine to Redefine Insulin Secretion and Monogenic Diabetes-Randomized Controlled Trial (PRISM-RCT) in Chinese patients with young-onset diabetes: design, methods and baseline characteristics

IntroductionWe designed and implemented a patient-centered, data-driven, holistic care model with evaluation of its impacts on clinical outcomes in patients with young-onset type 2 diabetes (T2D) for which there is...

Impact of gene-by-trauma interaction in MDD-related multimorbidity clusters

BackgroundMajor depressive disorder (MDD) is considerably heterogeneous in terms of comorbidities, which may hamper the disentanglement of its biological mechanism. In a previous study, we classified the lifetime trajectories of MDD-related multimorbidities into seven distinct clusters, each characterized by unique genetic and environmental risk-factor profiles. The current objective was to investigate genome-wide gene-by-environment (G × E) interactions with childhood trauma burden, within the context of these clusters. MethodsWe analyzed 77,519 participants and 6,266,189 single-nucleotide polymorphisms (SNPs) of the UK Biobank database. Childhood trauma burden was assessed using the Childhood Trauma Screener (CTS). For each cluster, Plink 2.0 was used to calculate SNP × CTS interaction effects on the participants' cluster membership probabilities. We especially focused on the effects of 31 candidate genes and associated SNPs selected from previous G × E studies for childhood maltreatment's association with depression. ResultsAt SNP-level, only the high-multimorbidity Cluster 6 revealed a genome-wide significant SNP rs145772219. At gene-level, MPST and PRH2 were genome-wide significant for the low-multimorbidity Clusters 1 and 3, respectively. Regarding candidate SNPs for G × E interactions, individual SNP results could be replicated for specific clusters. The candidate genes CREB1, DBH, and MTHFR (Cluster 5) as well as TPH1 (Cluster 6) survived multiple testing correction. LimitationsCTS is a short retrospective self-reported measurement. Clusters could be influenced by genetics of individual disorders. ConclusionsThe first G × E GWAS for MDD-related multimorbidity trajectories successfully replicated findings from previous G × E studies related to depression, and revealed risk clusters for the contribution of childhood trauma.