scholarly journals MCRiceRepGP: a framework for identification of sexual reproduction associated coding and lincRNA genes in rice

2018 ◽  
Author(s):  
Agnieszka A. Golicz ◽  
Prem L. Bhalla ◽  
Mohan B. Singh
Keyword(s):  
Machine Learning ◽  
Decision Analysis ◽  
Sexual Reproduction ◽  
Web Application ◽  
Molecular Mechanisms ◽  
Rice Genome ◽  
Protein Coding ◽  
Genome Wide ◽  
Plant Sexual Reproduction ◽  
Global Food

AbstractSexual reproduction in plants underpins global food production and evolution. It is a complex process, requiring intricate signalling pathways integrating a multitude of internal and external cues. However, key players and especially non-coding genes controlling plant sexual reproduction remain elusive. We report the development of MCRiceRepGP a novel machine learning framework, which integrates genomic, transcriptomic, homology and available phenotypic evidence and employs multi-criteria decision analysis and machine learning to predict coding and non-coding genes involved in rice sexual reproduction.The rice genome was re-annotated using deep sequencing transcriptomic data from reproduction-associated tissues/cell types identifying novel putative protein coding genes, transcript isoforms and long intergenic non-coding RNAs (lincRNAs). MCRiceRepGP was used for genome-wide discovery of sexual reproduction associated genes in rice; 2,275 protein-coding and 748 lincRNA genes were predicted to be involved in sexual reproduction. The annotation performed and the genes identified, especially the ones for which mutant lines with phenotypes are available provide a valuable resource. The analysis of genes identified gives insights into the genetic architecture of plant sexual reproduction. MCRiceRepGP can be used in combination with other genome-wide studies, like GWAS, giving more confidence that the genes identified are associated with the biological process of interest. As more data, especially about mutant plant phenotypes will become available, the power of MCRiceRepGP with grow providing researchers with a tool to identify candidate genes for future experiments. MCRiceRepGP is available as a web application (http://mcgplannotator.com/MCRiceRepGP/)Significance statementRice is a staple food crop plant for over half of the world’s population and sexual reproduction resulting in grain formation is a key process underpinning global food security. Despite considerable research efforts, much remains to be learned about the molecular mechanisms involved in rice sexual reproduction. We have developed MCRiceRepGP, a novel framework which allows prediction of sexual reproduction associated genes using multi-omics data, multicriteria decision analysis and machine learning. The genes identified and the methodology developed will become a significant resource for the plant research community.

Cell–cell communications and molecular mechanisms in plant sexual reproduction

2017 ◽  
Vol 131 (1) ◽  
pp. 37-47 ◽  
Author(s):  
Masahiro M. Kanaoka
Keyword(s):  
Sexual Reproduction ◽  
Molecular Mechanisms ◽  
Plant Sexual Reproduction ◽  
Cell Cell

scholarly journals Machine learning approaches to identify sleep genes

2021 ◽  
Author(s):  
Yin Yeng Lee ◽  
Mehari Endale ◽  
Gang Wu ◽  
Marc D Ruben ◽  
Lauren J Francey ◽  
...  
Keyword(s):  
Machine Learning ◽  
Prior Knowledge ◽  
Molecular Mechanisms ◽  
Genetic Regulation ◽  
Learning Approaches ◽  
Sleep Regulation ◽  
Genome Wide ◽  
Genome Wide Data ◽  
Key Genes

Genetics impacts sleep, yet, the molecular mechanisms underlying sleep regulation remain elusive. We built machine learning (ML) models to predict genes based on their similarity to known sleep genes. Our predictions fit with prior knowledge of sleep regulation and also identify several key genes/pathways to pursue in follow-up studies. We tested one of our findings, the NF-κB pathway, and showed that its genetic alteration affects sleep duration in mice. Our study highlights the power of ML to integrate prior knowledge and genome-wide data to study genetic regulation of sleep and other complex behaviors.

scholarly journals Sexual reproduction contributes to the evolution of resistance breaking isolates of the spinach pathogen Peronospora effusa

2021 ◽  
Author(s):  
Petros Skiadas ◽  
Joel Klein ◽  
Thomas Quiroz Monnens ◽  
Joyce Elberse ◽  
Ronnie de Jonge ◽  
...  
Keyword(s):  
Sexual Reproduction ◽  
Molecular Mechanisms ◽  
Nuclear Genome ◽  
Resistance Breeding ◽  
Systematic Analysis ◽  
Genome Wide ◽  
Diversity Assessment ◽  
Long Read ◽  
Evolution Of Resistance ◽  
Important Disease

Peronospora effusa causes downy mildew, the economically most important disease of cultivated spinach worldwide. To date, 19 P. effusa races have been denominated based on their capacity to break spinach resistances, but their genetic diversity and the evolutionary processes that contribute to race emergence are unknown. Here, we performed the first systematic analysis of P. effusa races showing that those emerge by both asexual and sexual reproduction. Specifically, we studied the diversity of 26 P. effusa isolates from 16 denominated races based on mitochondrial and nuclear comparative genomics. Mitochondrial genomes based on long-read sequencing coupled with diversity assessment based on short-read sequencing uncovered two mitochondrial haplogroups, each with distinct genome organization. Nuclear genome-wide comparisons of the 26 isolates revealed that ten isolates from six races could clearly be divided into three asexually evolving groups, in concordance with their mitochondrial phylogeny. The remaining isolates showed signals of reticulated evolution and discordance between nuclear and mitochondrial phylogenies, suggesting that these evolved through sexual reproduction. Increased understanding of this pathogen's reproductive modes will provide the framework for future studies into the molecular mechanisms underlying race emergence and into the P. effusa-spinach interaction, thus assisting in sustainable production of spinach through knowledge-driven resistance breeding.

scholarly journals High-resolution Introgressive Region Map Reveals Spatiotemporal Genome Evolution in Asian Rice Domestication

2019 ◽  
Author(s):  
Hajime Ohyanagi ◽  
Kosuke Goto ◽  
Sónia Negrão ◽  
Rod A. Wing ◽  
Mark A. Tester ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Rice Genome ◽  
Definitive Answer ◽  
Asian Rice ◽  
Multiple Origins ◽  
Genome Wide ◽  
Time Calibration ◽  
History Of ◽  
Genomic Regions ◽  
Rice Domestication

AbstractDomestication is anthropogenic evolution that fulfills mankind’s critical food demand. As such, elucidating the molecular mechanisms behind this process promotes the development of future new food resources including crops. With the aim of understanding the long-term domestication process of Asian rice and by employing the Oryza sativa subspecies (indica and japonica) as an Asian rice domestication model, we scrutinized past genomic introgressions between them as traces of domestication. Here we show the genome-wide introgressive region (IR) map of Asian rice, by utilizing 4,587 accession genotypes with a stable outgroup species, particularly at the finest resolution through a machine learning-aided method. The IR map revealed that 14.2% of the rice genome consists of IRs, including both wide IRs (recent) and narrow IRs (ancient). This introgressive landscape with their time calibration indicates that introgression events happened in multiple genomic regions over multiple periods. From the correspondence between our wide IRs and the so-called selective sweep regions, we provide a definitive answer to a long-standing controversy over the evolutionary origin of Asian rice domestication, single or multiple origins: It heavily depends upon which regions you pay attention to, implying that wider genomic regions represent immediate short history of Asian rice domestication as a likely support to the single origin, while its ancient history is interspersed in narrower traces throughout the genome as a possible support to the multiple origin.

scholarly journals Global reinforcement of DNA methylation through enhancement of RNA-directed DNA methylation ensures sexual reproduction in rice

2020 ◽  
Author(s):  
Lili Wang ◽  
Longjun Zeng ◽  
Kezhi Zheng ◽  
Tianxin Zhu ◽  
Yumeng Yin ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Sexual Reproduction ◽  
De Novo ◽  
Rice Genome ◽  
Biological Significance ◽  
Reproductive Organs ◽  
Epigenetic Mark ◽  
Small Interfering Rnas ◽  
Genome Wide ◽  
Global Increase

AbstractDNA methylation is an important epigenetic mark that regulates the expression of genes and transposons. RNA-directed DNA methylation (RdDM) is the main molecular pathway responsible for de novo DNA methylation in plants. In Arabidopsis, however, mutations in RdDM genes cause no visible developmental defects, which raising the question of the biological significance of RdDM in plant development. Here, we isolated and cloned Five Elements Mountain 1 (FEM1), which encodes an RNA-dependent RNA polymerase. Mutation in FEM1 substantially decreased genome-wide CHH methylation levels and abolished the accumulation of 24-nt small interfering RNAs. Moreover, male and female reproductive development was disturbed, which led to the sterility of fem1 mutants. In wild-type (WT) plants but not in fem1 mutants, genome-wide CHH DNA methylation levels were greater in panicles, stamens, and pistils than in seedlings. The global increase of methylation in reproductive organs of the WT was attributed to enhancement of RdDM activity including FEM1 activity. More than half of all encoding genes in the rice genome overlapped with hypermethylated regions in the sexual organs of the WT, and many of them appear to be directly regulated by an increase in DNA methylation.Our results demonstrate that a global increase of DNA methylation through enhancement of RdDM activity in reproductive organs ensures sexual reproduction of rice.

scholarly journals Non-Coding RNAs and Splicing Activity in Testicular Germ Cell Tumors

Life ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 736
Author(s):  
Marco Barchi ◽  
Pamela Bielli ◽  
Susanna Dolci ◽  
Pellegrino Rossi ◽  
Paola Grimaldi
Keyword(s):  
Germ Cell ◽  
Molecular Mechanisms ◽  
Splice Variants ◽  
Germ Cell Tumors ◽  
Testicular Germ Cell Tumors ◽  
Testicular Germ Cell ◽  
Protein Coding ◽  
Chemotherapeutic Response ◽  
Genome Wide ◽  
Non Coding Rnas

Testicular germ cell tumors (TGCTs) are the most common tumors in adolescent and young men. Recently, genome-wide studies have made it possible to progress in understanding the molecular mechanisms underlying the development of tumors. It is becoming increasingly clear that aberrant regulation of RNA metabolism can drive tumorigenesis and influence chemotherapeutic response. Notably, the expression of non-coding RNAs as well as specific splice variants is deeply deregulated in human cancers. Since these cancer-related RNA species are considered promising diagnostic, prognostic and therapeutic targets, understanding their function in cancer development is becoming a major challenge. Here, we summarize how the different expression of RNA species repertoire, including non-coding RNAs and protein-coding splicing variants, impacts on TGCTs’ onset and progression and sustains therapeutic resistance. Finally, the role of transcription-associated R-loop misregulation in the maintenance of genomic stability in TGCTs is also discussed.

scholarly journals TIGA: Target illumination GWAS analytics

2020 ◽  
Author(s):  
Jeremy J Yang ◽  
Dhouha Grissa ◽  
Christophe G Lambert ◽  
Cristian G Bologa ◽  
Stephen L Mathias ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Data Aggregation ◽  
Web Application ◽  
Drug Target ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Protein Coding ◽  
Genome Wide ◽  
Public Datasets ◽  
Trait Associations

AbstractGenome wide association studies (GWAS) can reveal important genotype–phenotype associations, however, data quality and interpretability issues must be addressed. For drug discovery scientists seeking to prioritize targets based on the available evidence, these issues go beyond the single study. Here, we describe rational ranking, filtering and interpretation of inferred gene–trait associations and data aggregation across studies by leveraging existing curation and harmonization efforts. Each gene– trait association is evaluated for confidence, with scores derived solely from aggregated statistics, linking a protein-coding gene and phenotype. We propose a method for assessing confidence in gene–trait associations from evidence aggregated across studies, including a bibliometric assessment of scientific consensus based on the iCite Relative Citation Ratio, and meanRank scores, to aggregate multivariate evidence. This method, intended for drug target hypothesis generation, scoring and ranking, has been implemented as an analytical pipeline, available as open source, with public datasets of results, and a web application designed for usability by drug discovery scientists, at https://unmtid-shinyapps.net/tiga/.

scholarly journals A large Canadian cohort provides insights into the genetic architecture of human hair colour

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Frida Lona-Durazo ◽  
Marla Mendes ◽  
Rohit Thakur ◽  
Karen Funderburk ◽  
Tongwu Zhang ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Association Studies ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Hair Colour ◽  
Protein Coding ◽  
Coding Regions ◽  
Genome Wide ◽  
Causal Variants ◽  
Meta Analyses

AbstractHair colour is a polygenic phenotype that results from differences in the amount and ratio of melanins located in the hair bulb. Genome-wide association studies (GWAS) have identified many loci involved in the pigmentation pathway affecting hair colour. However, most of the associated loci overlap non-protein coding regions and many of the molecular mechanisms underlying pigmentation variation are still not understood. Here, we conduct GWAS meta-analyses of hair colour in a Canadian cohort of 12,741 individuals of European ancestry. By performing fine-mapping analyses we identify candidate causal variants in pigmentation loci associated with blonde, red and brown hair colour. Additionally, we observe colocalization of several GWAS hits with expression and methylation quantitative trait loci (QTLs) of cultured melanocytes. Finally, transcriptome-wide association studies (TWAS) further nominate the expression of EDNRB and CDK10 as significantly associated with hair colour. Our results provide insights on the mechanisms regulating pigmentation biology in humans.

A Database for Counterfeit Electronics and Automatic Defect Detection Based on Image Processing and Machine Learning

2016 ◽  
Author(s):  
Navid Asadizanjani ◽  
Sachin Gattigowda ◽  
Mark Tehranipoor ◽  
Domenic Forte ◽  
Nathan Dunn
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Integrated Circuits ◽  
Web Application ◽  
The United States ◽  
Global Market ◽  
Online Database ◽  
Ongoing Effort ◽  
Time Period ◽  
Physical Defects

Abstract Counterfeiting is an increasing concern for businesses and governments as greater numbers of counterfeit integrated circuits (IC) infiltrate the global market. There is an ongoing effort in experimental and national labs inside the United States to detect and prevent such counterfeits in the most efficient time period. However, there is still a missing piece to automatically detect and properly keep record of detected counterfeit ICs. Here, we introduce a web application database that allows users to share previous examples of counterfeits through an online database and to obtain statistics regarding the prevalence of known defects. We also investigate automated techniques based on image processing and machine learning to detect different physical defects and to determine whether or not an IC is counterfeit.

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