Displaying publications 1 - 20 of 370 in total

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  1. Comparative genomic and phenotypic analyses of pathogenic fungi Neoscytalidium dimidiatum and Bipolaris papendorfii isolated from human skin scraping
    Kuan CS, Ng KP, Yew SM, Umar Meleh H, Seow HF, How KN, et al.
    Braz J Microbiol, 2023 Sep;54(3):1351-1372.
    PMID: 37351789 DOI: 10.1007/s42770-023-01032-z
    Neoscytalidium dimidiatum and Bipolaris species are fungal plant pathogens that have been reported to cause human diseases. Recently, we have isolated numerous N. dimidiatum and Bipolaris species from the skin scrapings and nails of different patients. In this work, we have sequenced the genome of one strain of N. dimidiatum. The sequenced genome was compared to that of a previously reported Bipolaris papendorfii genome for a better understanding of their complex lifestyle and broad host-range pathogenicity. Both N. dimidiatum UM 880 (~ 43 Mb) and B. papendorfii UM 226 (~ 33 Mb) genomes include 11,015-12,320 putative coding DNA sequences, of which 0.51-2.49% are predicted transposable elements. Analysis of secondary metabolism gene clusters revealed several genes involved in melanin biosynthesis and iron uptake. The arsenal of CAZymes related to plants pathogenicity is comparable between the species, including genes involved in hemicellulose and pectin decomposition. Several important gene encoding keratinolytic peptidases were identified in N. dimidiatum and B. papendorfii, reflecting their potential pathogenic role in causing skin and nail infections. In this study, additional information on the metabolic features of these two species, such as nutritional profiling, pH tolerance, and osmotolerant, are revealed. The genomic characterization of N. dimidiatum and B. papendorfii provides the basis for the future functional studies to gain further insights as to what makes these fungi persist in plants and why they are pathogenic to humans.
    Matched MeSH terms: Genomics
  2. The AfrAbia+plus Parkinson's Disease Genomic Consortium
    Mohamed W, Eltantawi MA, Mecheri Y, Zewde YZ, Kamel WA, Al-Mubarak BR, et al.
    Lancet Neurol, 2024 Feb;23(2):140-141.
    PMID: 38267182 DOI: 10.1016/S1474-4422(23)00453-2
    Matched MeSH terms: Genomics
  3. Fulltext Genomics of extreme environments: unveiling the secrets of survival
    Goh KM, González-Siso MI, Sani RK
    Sci Rep, 2023 Dec 05;13(1):21441.
    PMID: 38052842 DOI: 10.1038/s41598-023-48470-1
    Life on Earth has displayed remarkable adaptability to the harshest environments, spanning polar regions, scorching deserts, abyssal oceans, lightless caves, noxious lakes, boiling hot springs, and nuclear waste sites. These resilient organisms, known as extremophiles or polyextremophiles, owe their survival due to their unique genetic adaptations. This collection, titled ‘Genomics of Extreme Environments’, comprises several articles published in the esteemed journal Scientific Reports. Each article within this collection investigated genetic signature and adaptation in different extreme environments, including the cold polar region, arid desert, oxygen-deprived Tibetan mountains and others. These studies provide invaluable understanding of how life thrives and evolves under extreme conditions, shedding light on genetic mechanisms and adaptation strategies.
    Matched MeSH terms: Genomics*
  4. Fulltext Range-wide differential adaptation and genomic offset in critically endangered Asian rosewoods
    Hung TH, So T, Thammavong B, Chamchumroon V, Theilade I, Phourin C, et al.
    Proc Natl Acad Sci U S A, 2023 Aug 15;120(33):e2301603120.
    PMID: 37549265 DOI: 10.1073/pnas.2301603120
    In the billion-dollar global illegal wildlife trade, rosewoods have been the world's most trafficked wild product since 2005. Dalbergia cochinchinensis and Dalbergia oliveri are the most sought-after rosewoods in the Greater Mekong Subregion. They are exposed to significant genetic risks and the lack of knowledge on their adaptability limits the effectiveness of conservation efforts. Here, we present genome assemblies and range-wide genomic scans of adaptive variation, together with predictions of genomic offset to climate change. Adaptive genomic variation was differentially associated with temperature and precipitation-related variables between the species, although their natural ranges overlap. The findings are consistent with differences in pioneering ability and in drought tolerance. We predict their genomic offsets will increase over time and with increasing carbon emission pathway but at a faster pace in D. cochinchinensis than in D. oliveri. These results and the distinct gene-environment association in the eastern coastal edge of Vietnam suggest species-specific conservation actions: germplasm representation across the range in D. cochinchinensis and focused on hotspots of genomic offset in D. oliveri. We translated our genomic models into a seed source matching application, seedeR, to rapidly inform restoration efforts. Our ecological genomic research uncovering contrasting selection forces acting in sympatric rosewoods is of relevance to conserving tropical trees globally and combating risks from climate change.
    Matched MeSH terms: Genomics
  5. Historical population declines prompted significant genomic erosion in the northern and southern white rhinoceros (Ceratotherium simum)
    Sánchez-Barreiro F, Gopalakrishnan S, Ramos-Madrigal J, Westbury MV, de Manuel M, Margaryan A, et al.
    Mol Ecol, 2021 12;30(23):6355-6369.
    PMID: 34176179 DOI: 10.1111/mec.16043
    Large vertebrates are extremely sensitive to anthropogenic pressure, and their populations are declining fast. The white rhinoceros (Ceratotherium simum) is a paradigmatic case: this African megaherbivore has suffered a remarkable decline in the last 150 years due to human activities. Its subspecies, the northern (NWR) and the southern white rhinoceros (SWR), however, underwent opposite fates: the NWR vanished quickly, while the SWR recovered after the severe decline. Such demographic events are predicted to have an erosive effect at the genomic level, linked to the extirpation of diversity, and increased genetic drift and inbreeding. However, there is little empirical data available to directly reconstruct the subtleties of such processes in light of distinct demographic histories. Therefore, we generated a whole-genome, temporal data set consisting of 52 resequenced white rhinoceros genomes, representing both subspecies at two time windows: before and during/after the bottleneck. Our data reveal previously unknown population structure within both subspecies, as well as quantifiable genomic erosion. Genome-wide heterozygosity decreased significantly by 10% in the NWR and 36% in the SWR, and inbreeding coefficients rose significantly by 11% and 39%, respectively. Despite the remarkable loss of genomic diversity and recent inbreeding it suffered, the only surviving subspecies, the SWR, does not show a significant accumulation of genetic load compared to its historical counterpart. Our data provide empirical support for predictions about the genomic consequences of shrinking populations, and our findings have the potential to inform the conservation efforts of the remaining white rhinoceroses.
    Matched MeSH terms: Genomics
  6. Fulltext An enhanced topologically significant directed random walk in cancer classification using gene expression datasets
    Seah CS, Kasim S, Fudzee MFM, Law Tze Ping JM, Mohamad MS, Saedudin RR, et al.
    Saudi J Biol Sci, 2017 Dec;24(8):1828-1841.
    PMID: 29551932 DOI: 10.1016/j.sjbs.2017.11.024
    Microarray technology has become one of the elementary tools for researchers to study the genome of organisms. As the complexity and heterogeneity of cancer is being increasingly appreciated through genomic analysis, cancerous classification is an emerging important trend. Significant directed random walk is proposed as one of the cancerous classification approach which have higher sensitivity of risk gene prediction and higher accuracy of cancer classification. In this paper, the methodology and material used for the experiment are presented. Tuning parameter selection method and weight as parameter are applied in proposed approach. Gene expression dataset is used as the input datasets while pathway dataset is used to build a directed graph, as reference datasets, to complete the bias process in random walk approach. In addition, we demonstrate that our approach can improve sensitive predictions with higher accuracy and biological meaningful classification result. Comparison result takes place between significant directed random walk and directed random walk to show the improvement in term of sensitivity of prediction and accuracy of cancer classification.
    Matched MeSH terms: Genomics
  7. Fulltext Prioritising positively selected variants in whole-genome sequencing data using FineMAV
    Wahyudi F, Aghakhanian F, Rahman S, Teo YY, Szpak M, Dhaliwal J, et al.
    BMC Bioinformatics, 2021 Dec 18;22(1):604.
    PMID: 34922440 DOI: 10.1186/s12859-021-04506-9
    BACKGROUND: In population genomics, polymorphisms that are highly differentiated between geographically separated populations are often suggestive of Darwinian positive selection. Genomic scans have highlighted several such regions in African and non-African populations, but only a handful of these have functional data that clearly associates candidate variations driving the selection process. Fine-Mapping of Adaptive Variation (FineMAV) was developed to address this in a high-throughput manner using population based whole-genome sequences generated by the 1000 Genomes Project. It pinpoints positively selected genetic variants in sequencing data by prioritizing high frequency, population-specific and functional derived alleles.

    RESULTS: We developed a stand-alone software that implements the FineMAV statistic. To graphically visualise the FineMAV scores, it outputs the statistics as bigWig files, which is a common file format supported by many genome browsers. It is available as a command-line and graphical user interface. The software was tested by replicating the FineMAV scores obtained using 1000 Genomes Project African, European, East and South Asian populations and subsequently applied to whole-genome sequencing datasets from Singapore and China to highlight population specific variants that can be subsequently modelled. The software tool is publicly available at https://github.com/fadilla-wahyudi/finemav .

    CONCLUSIONS: The software tool described here determines genome-wide FineMAV scores, using low or high-coverage whole-genome sequencing datasets, that can be used to prioritize a list of population specific, highly differentiated candidate variants for in vitro or in vivo functional screens. The tool displays these scores on the human genome browsers for easy visualisation, annotation and comparison between different genomic regions in worldwide human populations.

    Matched MeSH terms: Genomics*; Metagenomics*
  8. Fulltext Evaluation of in silico predictors on short nucleotide variants in HBA1, HBA2, and HBB associated with haemoglobinopathies
    Tamana S, Xenophontos M, Minaidou A, Stephanou C, Harteveld CL, Bento C, et al.
    Elife, 2022 Dec 01;11.
    PMID: 36453528 DOI: 10.7554/eLife.79713
    Haemoglobinopathies are the commonest monogenic diseases worldwide and are caused by variants in the globin gene clusters. With over 2400 variants detected to date, their interpretation using the American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) guidelines is challenging and computational evidence can provide valuable input about their functional annotation. While many in silico predictors have already been developed, their performance varies for different genes and diseases. In this study, we evaluate 31 in silico predictors using a dataset of 1627 variants in HBA1, HBA2, and HBB. By varying the decision threshold for each tool, we analyse their performance (a) as binary classifiers of pathogenicity and (b) by using different non-overlapping pathogenic and benign thresholds for their optimal use in the ACMG/AMP framework. Our results show that CADD, Eigen-PC, and REVEL are the overall top performers, with the former reaching moderate strength level for pathogenic prediction. Eigen-PC and REVEL achieve the highest accuracies for missense variants, while CADD is also a reliable predictor of non-missense variants. Moreover, SpliceAI is the top performing splicing predictor, reaching strong level of evidence, while GERP++ and phyloP are the most accurate conservation tools. This study provides evidence about the optimal use of computational tools in globin gene clusters under the ACMG/AMP framework.
    Matched MeSH terms: Genomics*
  9. Fulltext Genomic selection strategies to increase genetic gain in tea breeding programs
    Lubanga N, Massawe F, Mayes S, Gorjanc G, Bančič J
    Plant Genome, 2023 Mar;16(1):e20282.
    PMID: 36349831 DOI: 10.1002/tpg2.20282
    Tea [Camellia sinensis (L.) O. Kuntze] is mainly grown in low- to middle-income countries (LMIC) and is a global commodity. Breeding programs in these countries face the challenge of increasing genetic gain because the accuracy of selecting superior genotypes is low and resources are limited. Phenotypic selection (PS) is traditionally the primary method of developing improved tea varieties and can take over 16 yr. Genomic selection (GS) can be used to improve the efficiency of tea breeding by increasing selection accuracy and shortening the generation interval and breeding cycle. Our main objective was to investigate the potential of implementing GS in tea-breeding programs to speed up genetic progress despite the low cost of PS in LMIC. We used stochastic simulations to compare three GS-breeding programs with a Pedigree and PS program. The PS program mimicked a practical commercial tea-breeding program over a 40-yr breeding period. All the GS programs achieved at least 1.65 times higher genetic gains than the PS program and 1.4 times compared with Seed-Ped program. Seed-GSc was the most cost-effective strategy of implementing GS in tea-breeding programs. It introduces GS at the seedlings stage to increase selection accuracy early in the program and reduced the generation interval to 2 yr. The Seed-Ped program outperformed PS by 1.2 times and could be implemented where it is not possible to use GS. Our results indicate that GS could be used to improve genetic gain per unit time and cost even in cost-constrained tea-breeding programs.
    Matched MeSH terms: Genomics/methods
  10. Utility of public knowledge bases for the interpretation of comprehensive tumor molecular profiling results
    Lebedeva A, Timokhin G, Ignatova E, Kavun A, Veselovsky E, Sharova M, et al.
    Clin Exp Med, 2023 Oct;23(6):2663-2674.
    PMID: 36752890 DOI: 10.1007/s10238-023-01011-6
    With the growing use of comprehensive tumor molecular profiling (CTMP), the therapeutic landscape of cancer is rapidly evolving. NGS produces large amounts of genomic data requiring complex analysis and subsequent interpretation. We sought to determine the utility of publicly available knowledge bases (KB) for the interpretation of the cancer mutational profile in clinical practice. Analysis was performed across patients who previously underwent CTMP. Independent interpretation of the CTMP was performed manually, and then, the recommendations were compared to ones present in KBs (OncoKB, CIViC, CGI, CGA, VICC, MolecularMatch). A total of 222 CTMP reports from 222 patients with 932 genomic alterations (GA) were identified. For 368 targetable GA identified in 171 (77%) of the patients, 1381 therapy recommendations were compiled. Except for CGA, therapy ESCAT LOE I, II, IIIA and IIIB therapy options were equally represented in the majority of KB. Personalized treatment options with ESCAT LOE I-II were provided for 35 patients (16%); MolecularMatch/CIViC allowed to collect ESCAT I-II treatment options for 34 of them (97%), OncoKB/CGI-for 33 of them (94%). Employing VICC and CGA 6 (17%) and 20 (57%) of patients were left without ESCAT I or II treatment options. For 88 patients with ESCAT level III-B therapy recommendations: only 2 (2%), 3 (3%), 4 (5%) and 6 (7%) of patients were left without options with CIViC, MolecularMatch, CGI and OncoKB, and with VICC-12 (14%). Highest overlap ratio was observed for IIIA (0.81) biomarkers, with the comparable results for LOE I-II. Meanwhile, overlap ratio for ESCAT LOE IV was 0.22. Public KBs provide substantial information on ESCAT-I/R1 biomarkers, but the information on ESCAT II-IV and resistance biomarkers is underrepresented. Manual curation should be considered the gold standard for the CTMP interpretation.
    Matched MeSH terms: Genomics/methods
  11. Fulltext Draft Genome Sequence of Ochroconis constricta UM 578, Isolated from Human Skin Scraping
    Chan CL, Yew SM, Na SL, Tan YC, Lee KW, Yee WY, et al.
    Genome Announc, 2014;2(2).
    PMID: 24744321 DOI: 10.1128/genomeA.00074-14
    Ochroconis constricta is a soilborne dematiaceous fungus that has never been reported to be associated with human infection. Here we report the first draft genome sequence of strain UM 578, isolated from human skin scraping. The genomic information revealed will contribute to a better understanding of this species.
    Matched MeSH terms: Genomics
  12. Fulltext Genomic Analysis to Elucidate the Lignocellulose Degrading Capability of a New Halophile Robertkochia solimangrovi
    Lam MQ, Oates NC, Leadbeater DR, Goh KM, Yahya A, Md Salleh M, et al.
    Genes (Basel), 2022 Nov 17;13(11).
    PMID: 36421811 DOI: 10.3390/genes13112135
    Robertkochia solimangrovi is a proposed marine bacterium isolated from mangrove soil. So far, the study of this bacterium is limited to taxonomy only. In this report, we performed a genomic analysis of R. solimangrovi that revealed its lignocellulose degrading ability. Genome mining of R. solimangrovi revealed a total of 87 lignocellulose degrading enzymes. These enzymes include cellulases (GH3, GH5, GH9 and GH30), xylanases (GH5, GH10, GH43, GH51, GH67, and GH115), mannanases (GH2, GH26, GH27 and GH113) and xyloglucanases (GH2, GH5, GH16, GH29, GH31 and GH95). Most of the lignocellulolytic enzymes encoded in R. solimangrovi were absent in the genome of Robertkochia marina, the closest member from the same genus. Furthermore, current work also demonstrated the ability of R. solimangrovi to produce lignocellulolytic enzymes to deconstruct oil palm empty fruit bunch (EFB), a lignocellulosic waste found abundantly in palm oil industry. The metabolic pathway taken by R. solimangrovi to transport and process the reducing sugars after the action of lignocellulolytic enzymes on EFB was also inferred based on genomic data. Collectively, genomic analysis coupled with experimental studies elucidated R. solimangrovi to serve as a promising candidate in seawater based-biorefinery industry.
    Matched MeSH terms: Genomics
  13. Fulltext The complex genome and adaptive evolution of polyploid Chinese pepper (Zanthoxylum armatum and Zanthoxylum bungeanum)
    Hu L, Xu Z, Fan R, Wang G, Wang F, Qin X, et al.
    Plant Biotechnol J, 2023 Jan;21(1):78-96.
    PMID: 36117410 DOI: 10.1111/pbi.13926
    Zanthoxylum armatum and Zanthoxylum bungeanum, known as 'Chinese pepper', are distinguished by their extraordinary complex genomes, phenotypic innovation of adaptive evolution and species-special metabolites. Here, we report reference-grade genomes of Z. armatum and Z. bungeanum. Using high coverage sequence data and comprehensive assembly strategies, we derived 66 pseudochromosomes comprising 33 homologous phased groups of two subgenomes, including autotetraploid Z. armatum. The genomic rearrangements and two whole-genome duplications created large (~4.5 Gb) complex genomes with a high ratio of repetitive sequences (>82%) and high chromosome number (2n = 4x = 132). Further analysis of the high-quality genomes shed lights on the genomic basis of involutional reproduction, allomones biosynthesis and adaptive evolution in Chinese pepper, revealing a high consistent relationship between genomic evolution, environmental factors and phenotypic innovation. Our study provides genomic resources and new insights for investigating diversification and phenotypic innovation in Chinese pepper, with broader implications for the protection of plants under severe environmental changes.
    Matched MeSH terms: Genomics
  14. Fulltext A reference genome of Commelinales provides insights into the commelinids evolution and global spread of water hyacinth (Pontederia crassipes)
    Huang Y, Guo L, Xie L, Shang N, Wu D, Ye C, et al.
    Gigascience, 2024 Jan 02;13.
    PMID: 38486346 DOI: 10.1093/gigascience/giae006
    Commelinales belongs to the commelinids clade, which also comprises Poales that includes the most important monocot species, such as rice, wheat, and maize. No reference genome of Commelinales is currently available. Water hyacinth (Pontederia crassipes or Eichhornia crassipes), a member of Commelinales, is one of the devastating aquatic weeds, although it is also grown as an ornamental and medical plant. Here, we present a chromosome-scale reference genome of the tetraploid water hyacinth with a total length of 1.22 Gb (over 95% of the estimated size) across 8 pseudochromosome pairs. With the representative genomes, we reconstructed a phylogeny of the commelinids, which supported Zingiberales and Commelinales being sister lineages of Arecales and shed lights on the controversial relationship of the orders. We also reconstructed ancestral karyotypes of the commelinids clade and confirmed the ancient commelinids genome having 8 chromosomes but not 5 as previously reported. Gene family analysis revealed contraction of disease-resistance genes during polyploidization of water hyacinth, likely a result of fitness requirement for its role as a weed. Genetic diversity analysis using 9 water hyacinth lines from 3 continents (South America, Asia, and Europe) revealed very closely related nuclear genomes and almost identical chloroplast genomes of the materials, as well as provided clues about the global dispersal of water hyacinth. The genomic resources of P. crassipes reported here contribute a crucial missing link of the commelinids species and offer novel insights into their phylogeny.
    Matched MeSH terms: Genomics
  15. Fulltext Extending Asia Pacific bioinformatics into new realms in the "-omics" era
    Ranganathan S, Eisenhaber F, Tong JC, Tan TW
    BMC Genomics, 2009;10 Suppl 3:S1.
    PMID: 19958472 DOI: 10.1186/1471-2164-10-S3-S1
    The 2009 annual conference of the Asia Pacific Bioinformatics Network (APBioNet), Asia's oldest bioinformatics organisation dating back to 1998, was organized as the 8th International Conference on Bioinformatics (InCoB), Sept. 7-11, 2009 at Biopolis, Singapore. Besides bringing together scientists from the field of bioinformatics in this region, InCoB has actively engaged clinicians and researchers from the area of systems biology, to facilitate greater synergy between these two groups. InCoB2009 followed on from a series of successful annual events in Bangkok (Thailand), Penang (Malaysia), Auckland (New Zealand), Busan (South Korea), New Delhi (India), Hong Kong and Taipei (Taiwan), with InCoB2010 scheduled to be held in Tokyo, Japan, Sept. 26-28, 2010. The Workshop on Education in Bioinformatics and Computational Biology (WEBCB) and symposia on Clinical Bioinformatics (CBAS), the Singapore Symposium on Computational Biology (SYMBIO) and training tutorials were scheduled prior to the scientific meeting, and provided ample opportunity for in-depth learning and special interest meetings for educators, clinicians and students. We provide a brief overview of the peer-reviewed bioinformatics manuscripts accepted for publication in this supplement, grouped into thematic areas. In order to facilitate scientific reproducibility and accountability, we have, for the first time, introduced minimum information criteria for our pubilcations, including compliance to a Minimum Information about a Bioinformatics Investigation (MIABi). As the regional research expertise in bioinformatics matures, we have delineated a minimum set of bioinformatics skills required for addressing the computational challenges of the "-omics" era.
    Matched MeSH terms: Genomics*
  16. Fulltext Feature Selection for High-Dimensional and Imbalanced Biomedical Data Based on Robust Correlation Based Redundancy and Binary Grasshopper Optimization Algorithm
    Abdulrauf Sharifai G, Zainol Z
    Genes (Basel), 2020 06 27;11(7).
    PMID: 32605144 DOI: 10.3390/genes11070717
    The training machine learning algorithm from an imbalanced data set is an inherently challenging task. It becomes more demanding with limited samples but with a massive number of features (high dimensionality). The high dimensional and imbalanced data set has posed severe challenges in many real-world applications, such as biomedical data sets. Numerous researchers investigated either imbalanced class or high dimensional data sets and came up with various methods. Nonetheless, few approaches reported in the literature have addressed the intersection of the high dimensional and imbalanced class problem due to their complicated interactions. Lately, feature selection has become a well-known technique that has been used to overcome this problem by selecting discriminative features that represent minority and majority class. This paper proposes a new method called Robust Correlation Based Redundancy and Binary Grasshopper Optimization Algorithm (rCBR-BGOA); rCBR-BGOA has employed an ensemble of multi-filters coupled with the Correlation-Based Redundancy method to select optimal feature subsets. A binary Grasshopper optimisation algorithm (BGOA) is used to construct the feature selection process as an optimisation problem to select the best (near-optimal) combination of features from the majority and minority class. The obtained results, supported by the proper statistical analysis, indicate that rCBR-BGOA can improve the classification performance for high dimensional and imbalanced datasets in terms of G-mean and the Area Under the Curve (AUC) performance metrics.
    Matched MeSH terms: Genomics/methods; Genomics/standards
  17. Fulltext Towards big data science in the decade ahead from ten years of InCoB and the 1st ISCB-Asia Joint Conference
    Ranganathan S, Schönbach C, Kelso J, Rost B, Nathan S, Tan TW
    BMC Bioinformatics, 2011;12 Suppl 13:S1.
    PMID: 22372736 DOI: 10.1186/1471-2105-12-S13-S1
    The 2011 International Conference on Bioinformatics (InCoB) conference, which is the annual scientific conference of the Asia-Pacific Bioinformatics Network (APBioNet), is hosted by Kuala Lumpur, Malaysia, is co-organized with the first ISCB-Asia conference of the International Society for Computational Biology (ISCB). InCoB and the sequencing of the human genome are both celebrating their tenth anniversaries and InCoB's goalposts for the next decade, implementing standards in bioinformatics and globally distributed computational networks, will be discussed and adopted at this conference. Of the 49 manuscripts (selected from 104 submissions) accepted to BMC Genomics and BMC Bioinformatics conference supplements, 24 are featured in this issue, covering software tools, genome/proteome analysis, systems biology (networks, pathways, bioimaging) and drug discovery and design.
    Matched MeSH terms: Genomics*
  18. A more elaborative way to check codon quality: an open source program
    Shardiwal RK, Sohrab SS
    Int J Bioinform Res Appl, 2010;6(3):223-9.
    PMID: 20615831
    Relative Synonymous Codon Usage (RSCU) and Relative Adaptiveness of a Codon (RAC) table bias importance in gene expression are well documented in the literature. However, to improve the gene expression we need to figure out which codons are optimal for the expression in order to synthesise an appropriate DNA sequence. An alternative to the manual approach, which is obviously a tedious task, is to set up software on your computer to perform this. Though such kinds of programs are available on the internet, none of them are open-source libraries. Here, one can use our Perl program to do his or her task more easily and efficiently. It is free for everyone.
    Matched MeSH terms: Genomics/methods*
  19. Obesity and genomics: role of technology in unraveling the complex genetic architecture of obesity
    Apalasamy YD, Mohamed Z
    Hum Genet, 2015 Apr;134(4):361-74.
    PMID: 25687726 DOI: 10.1007/s00439-015-1533-x
    Obesity is a complex and multifactorial disease that occurs as a result of the interaction between "obesogenic" environmental factors and genetic components. Although the genetic component of obesity is clear from the heritability studies, the genetic basis remains largely elusive. Successes have been achieved in identifying the causal genes for monogenic obesity using animal models and linkage studies, but these approaches are not fruitful for polygenic obesity. The developments of genome-wide association approach have brought breakthrough discovery of genetic variants for polygenic obesity where tens of new susceptibility loci were identified. However, the common SNPs only accounted for a proportion of heritability. The arrival of NGS technologies and completion of 1000 Genomes Project have brought other new methods to dissect the genetic architecture of obesity, for example, the use of exome genotyping arrays and deep sequencing of candidate loci identified from GWAS to study rare variants. In this review, we summarize and discuss the developments of these genetic approaches in human obesity.
    Matched MeSH terms: Genomics*
  20. Functional Genomics
    Goh HH, Ng CL, Loke KK
    Adv Exp Med Biol, 2018 11 2;1102:11-30.
    PMID: 30382566 DOI: 10.1007/978-3-319-98758-3_2
    Functional genomics encompasses diverse disciplines in molecular biology and bioinformatics to comprehend the blueprint, regulation, and expression of genetic elements that define the physiology of an organism. The deluge of sequencing data in the postgenomics era has demanded the involvement of computer scientists and mathematicians to create algorithms, analytical software, and databases for the storage, curation, and analysis of biological big data. In this chapter, we discuss on the concept of functional genomics in the context of systems biology and provide examples of its application in human genetic disease studies, molecular crop improvement, and metagenomics for antibiotic discovery. An overview of transcriptomics workflow and experimental considerations is also introduced. Lastly, we present an in-house case study of transcriptomics analysis of an aromatic herbal plant to understand the effect of elicitation on the biosynthesis of volatile organic compounds.
    Matched MeSH terms: Genomics/trends*; Metagenomics
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