Combining globally search for a regular expression and print matching lines with bibliographic monitoring of genomic database improves diagnosis

Introduction: Exome sequencing has a diagnostic yield ranging from 25% to 70% in rare diseases and regularly implicates genes in novel disorders. Retrospective data reanalysis has demonstrated strong efficacy in improving diagnosis, but poses organizational difficulties for clinical laboratories. Patients and methods: We applied a reanalysis strategy based on intensive prospective bibliographic monitoring along with direct application of the GREP command-line tool (to "globally search for a regular expression and print matching lines") in a large ES database. For 18 months, we submitted the same five keywords of interest [(intellectual disability, (neuro)developmental delay, and (neuro)developmental disorder)] to PubMed on a daily basis to identify recently published novel disease-gene associations or new phenotypes in genes already implicated in human pathology. We used the Linux GREP tool and an in-house script to collect all variants of these genes from our 5,459 exome database. Results: After GREP queries and variant filtration, we identified 128 genes of interest and collected 56 candidate variants from 53 individuals. We confirmed causal diagnosis for 19/128 genes (15%) in 21 individuals and identified variants of unknown significance for 19/128 genes (15%) in 23 individuals. Altogether, GREP queries for only 128 genes over a period of 18 months permitted a causal diagnosis to be established in 21/2875 undiagnosed affected probands (0.7%). Conclusion: The GREP query strategy is efficient and less tedious than complete periodic reanalysis. It is an interesting reanalysis strategy to improve diagnosis.

Macadamia germplasm and genomic database (MacadamiaGGD): A comprehensive platform for germplasm innovation and functional genomics in Macadamia

As an important nut crop species, macadamia continues to gain increased amounts of attention worldwide. Nevertheless, with the vast increase in macadamia omic data, it is becoming difficult for researchers to effectively process and utilize the information. In this work, we developed the first integrated germplasm and genomic database for macadamia (MacadamiaGGD), which includes five genomes of four species; three chloroplast and mitochondrial genomes; genome annotations; transcriptomic data for three macadamia varieties, germplasm data for four species and 262 main varieties; nine genetic linkage maps; and 35 single-nucleotide polymorphisms (SNPs). The database serves as a valuable collection of simple sequence repeat (SSR) markers, including both markers that are based on macadamia genomic sequences and developed in this study and markers developed previously. MacadamiaGGD is also integrated with multiple bioinformatic tools, such as search, JBrowse, BLAST, primer designer, sequence fetch, enrichment analysis, multiple sequence alignment, genome alignment, and gene homology annotation, which allows users to conveniently analyze their data of interest. MacadamiaGGD is freely available online (http://MacadamiaGGD.net). We believe that the database and additional information of the SSR markers can help scientists better understand the genomic sequence information of macadamia and further facilitate molecular breeding efforts of this species.

Genomic, transcriptomic, and protein landscape profile of CFTR and cystic fibrosis

Cystic Fibrosis (CF) is caused most often by removal of amino acid 508 (Phe508del, deltaF508) within CFTR, yet dozens of additional CFTR variants are known to give rise to CF and many variants in the genome are known to contribute to CF pathology. To address CFTR coding variants, we developed a sequence-to-structure-to-dynamic matrix for all amino acids of CFTR using 233 vertebrate species, CFTR structure within a lipid membrane, and 20 ns of molecular dynamic simulation to assess known variants from the CFTR1, CFTR2, ClinVar, TOPmed, gnomAD, and COSMIC databases. Surprisingly, we identify 18 variants of uncertain significance within CFTR from diverse populations that are heritable and a likely cause of CF that have been understudied due to nonexistence in Caucasian populations. In addition, 15 sites within the genome are known to modulate CF pathology, where we have identified one genome region (chr11:34754985-34836401) that contributes to CF through modulation of expression of a noncoding RNA in epithelial cells. These 15 sites are just the beginning of understanding comodifiers of CF, where utilization of eQTLs suggests many additional genomics of CFTR expressing cells that can be influenced by genomic background of CFTR variants. This work highlights that many additional insights of CF genetics are needed, particularly as pharmaceutical interventions increase in the coming years.

The NanDeSyn database for Nannochloropsis systems and synthetic biology

Nannochloropsis species, unicellular industrial oleaginous microalgae, are model organisms for microalgal systems and synthetic biology. To facilitate community-based annotation and mining of the rapidly accumulating functional genomics resources, we have initiated an international consortium and present a comprehensive multi-omics resource database named Nannochloropsis Design and Synthesis (NanDeSyn; http://nandesyn.single-cell.cn). Via the Tripal toolkit, it features user-friendly interfaces hosting genomic resources with gene annotations and transcriptomic and proteomic data for six Nannochloropsis species, including two updated genomes of Nannochloropsis oceanica IMET1 and Nannochloropsis salina CCMP1776. Toolboxes for search, Blast, synteny view, enrichment analysis, metabolic pathway analysis, a genome browser, etc. are also included. In addition, functional validation of genes is indicated based on phenotypes of mutants and relevant bibliography. Furthermore, epigenomic resources are also incorporated, especially for sequencing of small RNAs including microRNAs and circular RNAs. Such comprehensive and integrated landscapes of Nannochloropsis genomics and epigenomics will promote and accelerate community efforts in systems and synthetic biology of these industrially important microalgae.

The value of genomic variant ClinVar submissions from clinical providers: Beyond the addition of novel variants

With the increasing use of clinical genomic testing across broad medical disciplines, the need for data sharing and curation efforts to improve variant interpretation is paramount. The National Center for Biotechnology Information (NCBI) ClinVar database facilitates these efforts by serving as a repository for clinical assertions about genomic variants and associations with disease. Most variant submissions are from clinical laboratories, which may lack clinical details. Laboratories may also choose not to submit all variants. Clinical providers can contribute to variant interpretation improvements by submitting variants to ClinVar with their own assertions and supporting evidence. The medical genetics team at Geisinger's Autism & Developmental Medicine Institute routinely reviews the clinical significance of all variants obtained through clinical genomic testing, using published ACMG/AMP guidelines, clinical correlation, and post-test clinical data. We describe the submission of 148 sequence and 155 copy number variants to ClinVar as "provider interpretations." Of these, 192 (63.4%) were novel to ClinVar. Detailed clinical data were provided for 298 (98.3%), and when available, segregation data and follow-up clinical correlation or testing was included. This contribution marks the first large-scale submission from a neurodevelopmental clinical setting and illustrates the importance of clinical providers in collaborative efforts to improve variant interpretation.

MetReS, an Efficient Database for Genomic Applications

MetReS (Metabolic Reconstruction Server) is a genomic database that is shared between two software applications that address important biological problems. Biblio-MetReS is a data-mining tool that enables the reconstruction of molecular networks based on automated text-mining analysis of published scientific literature. Homol-MetReS allows functional (re)annotation of proteomes, to properly identify both the individual proteins involved in the processes of interest and their function. The main goal of this work was to identify the areas where the performance of the MetReS database performance could be improved and to test whether this improvement would scale to larger datasets and more complex types of analysis. The study was started with a relational database, MySQL, which is the current database server used by the applications. We also tested the performance of an alternative data-handling framework, Apache Hadoop. Hadoop is currently used for large-scale data processing. We found that this data handling framework is likely to greatly improve the efficiency of the MetReS applications as the dataset and the processing needs increase by several orders of magnitude, as expected to happen in the near future.

Advances in plant gene-targeted and functional markers: a review

Public genomic databases have provided new directions for molecular marker development and initiated a shift in the types of PCR-based techniques commonly used in plant science. Alongside commonly used arbitrarily amplified DNA markers, other methods have been developed. Targeted fingerprinting marker techniques are based on the well-established practices of arbitrarily amplified DNA methods, but employ novel methodological innovations such as the incorporation of gene or promoter elements in the primers. These markers provide good reproducibility and increased resolution by the concurrent incidence of dominant and co-dominant bands. Despite their promising features, these semi-random markers suffer from possible problems of collision and non-homology analogous to those found with randomly generated fingerprints. Transposable elements, present in abundance in plant genomes, may also be used to generate fingerprints. These markers provide increased genomic coverage by utilizing specific targeted sites and produce bands that mostly seem to be homologous. The biggest drawback with most of these techniques is that prior genomic information about retrotransposons is needed for primer design, prohibiting universal applications. Another class of recently developed methods exploits length polymorphism present in arrays of multi-copy gene families such as cytochrome P450 and β-tubulin genes to provide cross-species amplification and transferability. A specific class of marker makes use of common features of plant resistance genes to generate bands linked to a given phenotype, or to reveal genetic diversity. Conserved DNA-based strategies have limited genome coverage and may fail to reveal genetic diversity, while resistance genes may be under specific evolutionary selection. Markers may also be generated from functional and/or transcribed regions of the genome using different gene-targeting approaches coupled with the use of RNA information. Such techniques have the potential to generate phenotypically linked functional markers, especially when fingerprints are generated from the transcribed or expressed region of the genome. It is to be expected that these recently developed techniques will generate larger datasets, but their shortcomings should also be acknowledged and carefully investigated.