• Dementia and Neurocognitive Disorders
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• v.17 no.4
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• pp.131-136
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• 2018

Alzheimer's disease (AD) related genes have been elucidated by advanced genetic techniques. Familial autosomal dominant AD genes founded by linkage analyses are APP, PSEN1, PSEN2, ABCA7, and SORL1. Genome-wide association studies have found risk genes such as ABCA7, BIN1, CASS4, CD33, CD2AP, CELF1, CLU, CR1, DSG2, EPHA1, FERMT2, HLA-DRB5-HLA-DRB1, INPP5D, MEF2C, MS4A6A/MS4A4E, NME8, PICALM, PTK2B, SLC24A4, SORL1, and ZCWPW1. ABCA7, SORL1, TREM2, and APOE are proved to have high odds ratio (>2) in risk of AD using next generation sequencing studies. Thanks to the promising genetic techniques such as CRISPR-CAS9 and single-cell RNA sequencing opened a new era in genetics. CRISPR-CAS9 can directly link genetic knowledge to future treatment. Single-cell RNA sequencing are providing useful information on cell biology and pathogenesis of diverse diseases.

• Molecules and Cells
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• v.42 no.3
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• pp.189-199
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• 2019

Cell-to-cell variability in gene expression exists even in a homogeneous population of cells. Dissecting such cellular heterogeneity within a biological system is a prerequisite for understanding how a biological system is developed, homeostatically regulated, and responds to external perturbations. Single-cell RNA sequencing (scRNA-seq) allows the quantitative and unbiased characterization of cellular heterogeneity by providing genome-wide molecular profiles from tens of thousands of individual cells. A major question in analyzing scRNA-seq data is how to account for the observed cell-to-cell variability. In this review, we provide an overview of scRNA-seq protocols, computational approaches for dissecting cellular heterogeneity, and future directions of single-cell transcriptomic analysis.

• Genomics & Informatics
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• v.17 no.2
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• pp.19.1-19.10
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• 2019

In this paper, we investigate cross-platform interoperability for natural language processing (NLP) and, in particular, annotation of textual resources, with an eye toward identifying the design elements of annotation models and processes that are particularly problematic for, or amenable to, enabling seamless communication across different platforms. The study is conducted in the context of a specific annotation methodology, namely machine-assisted interactive annotation (also known as human-in-the-loop annotation). This methodology requires the ability to freely combine resources from different document repositories, access a wide array of NLP tools that automatically annotate corpora for various linguistic phenomena, and use a sophisticated annotation editor that enables interactive manual annotation coupled with on-the-fly machine learning. We consider three independently developed platforms, each of which utilizes a different model for representing annotations over text, and each of which performs a different role in the process.

• The Plant Pathology Journal
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• v.35 no.3
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• pp.280-286
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• 2019

In this study, PVF11 was selected among 20 candidate pathogenesis-related genes in Burkholderia glumae based on its effect on virulence to rice. PVF11 was found to interact with several plant defense-related WRKY proteins as evidenced through yeast-two hybrid analysis (Y2H). Moreover, PVF11 showed interactions with abiotic and biotic stress response-related rice proteins, as shown by genome-wide Y2H screening employing PVF11 and a cDNA library from B. glumae-infected rice. To confirm the effect of PVF11 on B. glumae virulence, in planta assays were conducted at different stages of rice growth. As a result, a PVF11-defective mutant showed reduced virulence in rice seedlings and stems but not in rice panicles, indicating that PVF11 involvement in B. glumae virulence in rice is stage-dependent.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2711-2719
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• 2018

When an observable is described by a single value, the statistic significance may be estimated by construction of null distribution using permutation and counting the portion of it that exceeds the observed value by chance. Genome-wide association study usually focuses on the association measure between a single or interacting genotypes with a single phenotype. However investigation of common genotypes associated simultaneously on multiple phenotypes may involve the observables that should be described with multiple numbers. Statistical significance for such an observable would involve null distribution in multiple dimensions. In this study, extension of the p-value estimation process using null distribution in one dimension has been sought that may be applicable to two dimensional case. Comparison of the position of points within the set of points they form has been proposed to use a positioning parameter inspired by the extension of the Kolmogorov-Smirnov statistic to two dimensions.

• Animal Bioscience
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• v.34 no.8
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• pp.1271-1282
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• 2021

Genome-wide studies provide considerable insights into the genetic background of animals; however, the inheritance of several heritable factors cannot be elucidated. Epigenetics explains these heritabilities, including those of genes influenced by environmental factors. Knowledge of the mechanisms underlying epigenetics enables understanding the processes of gene regulation through interactions with the environment. Recently developed next-generation sequencing (NGS) technologies help understand the interactional changes in epigenetic mechanisms. There are large sets of NGS data available; however, the integrative data analysis approaches still have limitations with regard to reliably interpreting the epigenetic changes. This review focuses on the epigenetic mechanisms and profiling methods and multi-omics integration methods that can provide comprehensive biological insights in animal genetic studies.

• Journal of Genetic Medicine
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• v.18 no.2
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• pp.75-82
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• 2021

Speech and language functions are highly cognitive and human-specific features. The underlying causes of normal speech and language function are believed to reside in the human brain. Developmental persistent stuttering, a speech and language disorder, has been regarded as the most challenging disorder in determining genetic causes because of the high percentage of spontaneous recovery in stutters. This mysterious characteristic hinders speech pathologists from discriminating recovered stutters from completely normal individuals. Over the last several decades, several genetic approaches have been used to identify the genetic causes of stuttering, and remarkable progress has been made in genome-wide linkage analysis followed by gene sequencing. So far, four genes, namely GNPTAB, GNPTG, NAGPA, and AP4E1, are known to cause stuttering. Furthermore, thegeneration of mouse models of stuttering and morphometry analysis has created new ways for researchers to identify brain regions that participate in human speech function and to understand the neuropathology of stuttering. In this review, we aimed to investigate previous progress, challenges, and future perspectives in understanding the genetics and neuropathology underlying persistent developmental stuttering.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.31-31
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• 2022

Rice contains a wealth of genetic diversity, both within Oryza sativa and in related A-genome species. Decades of genetic research into this diversity have identified dozens of major genes contributing to a wide variety of important traits, including disease resistance, abiotic stress tolerance (drought, salinity, submergence, heat, cold etc.), grain quality, flowering date and maturity and plant architecture. Yet despite these opportunities, very few of the major genes and QTLs known have been successfully applied through rice breeding programs to produce sustained changes in farmer's fields. This presentation will briefly examine some of the factors limiting application of major genes in the mainstream breeding programs, and steps that have been taken to alleviate those limitations. As a result of these interventions, dozens of major genes that were previously unavailable to breeders are now being used confidently in the variety development process. Case studies will be discussed of genes critical for blast resistance worldwide, rice yellow mottle virus for Africa, and new validated QTLs for salinity tolerance.

• Proceedings of the Korean Society of Crop Science Conference
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• 2021.10a
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• pp.190-190
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• 2021

• Interdisciplinary Bio Central
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• v.6 no.4
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• pp.2.1-2.7
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• 2014

Sexual dimorphism in intelligence suggests that this phenotype is a sexually selected trait. This view is supported by an overrepresentation (compared to the autosomal genome) of genes affecting cognition on the X chromosome. The aim of this study is to test the hypothesis that sexual selection can explain sex and country-level differences in performance on tests of fluid intelligence. Nationally representative samples from N = 44 countries were obtained from the Programme for International Student Assessment (PISA) Creative Problem Solving (CPS), which evaluates the core of intelligence, that is novel problem solving ability. Sexual selection has the double effect of increasing the prevalence of a favored phenotype and reducing genetic variation in sexually selected traits. Matching these predictions from evolutionary theory, the average country fluid intelligence is positively correlated to sexual dimorphism after partialling out per capita GDP and the latter in turn is inversely correlated to variance in intelligence scores within populations. Males have a higher variance than females but there is a negative correlation between male-female difference in variance and sexual dimorphism in intelligence, suggesting that selection reduces variance more in the selected sex. Average country male height is negatively correlated to sexual dimorphism in intelligence, a fact that supports the notion of a trade-off between physical and intellectual competition in the context of access to females. The results of this study, if replicated, imply that genome-wide association studies of cognition may benefit from a focus on sex chromosomes, which so far have been neglected. Another implication of this study is that intelligence has continued to evolve after different human populations migrated out of Africa and possibly up to the 19th century, as suggested by the substantial variability in sex differences even between neighbouring countries.