-
1.
Genome-based identification and comparative analysis of enzymes for carotenoid biosynthesis in microalgae.
Narang, PK, Dey, J, Mahapatra, SR, Roy, R, Kushwaha, GS, Misra, N, Suar, M, Raina, V
World journal of microbiology & biotechnology. 2021;(1):8
Abstract
Microalgae are potential feedstocks for the commercial production of carotenoids, however, the metabolic pathways for carotenoid biosynthesis across algal lineage are largely unexplored. This work is the first to provide a comprehensive survey of genes and enzymes associated with the less studied methylerythritol 4-phosphate/1-deoxy-D-xylulose 5-phosphate pathway as well as the carotenoid biosynthetic pathway in microalgae through bioinformatics and comparative genomics approach. Candidate genes/enzymes were subsequently analyzed across 22 microalgae species of lineages Chlorophyta, Rhodophyta, Heterokonta, Haptophyta, Cryptophyta, and known Arabidopsis homologs in order to study the evolutional divergence in terms of sequence-structure properties. A total of 403 enzymes playing a vital role in carotene, lutein, zeaxanthin, violaxanthin, canthaxanthin, and astaxanthin were unraveled. Of these, 85 were hypothetical proteins whose biological roles are not yet experimentally characterized. Putative functions to these hypothetical proteins were successfully assigned through a comprehensive investigation of the protein family, motifs, intrinsic physicochemical features, subcellular localization, pathway analysis, etc. Furthermore, these enzymes were categorized into major classes as per the conserved domain and gene ontology. Functional signature sequences were also identified which were observed conserved across microalgal genomes. Additionally, the structural modeling and active site architecture of three vital enzymes, DXR, PSY, and ZDS catalyzing the vital rate-limiting steps in Dunaliella salina were achieved. The enzymes were confirmed to be stereochemically reliable and stable as revealed during molecular dynamics simulation of 100 ns. The detailed functional information about individual vital enzymes will certainly help to design genetically modified algal strains with enhanced carotenoid contents.
-
2.
Misannotated Multi-Nucleotide Variants in Public Cancer Genomics Datasets Lead to Inaccurate Mutation Calls with Significant Implications.
Srinivasan, S, Kalinava, N, Aldana, R, Li, Z, van Hagen, S, Rodenburg, SYA, Wind-Rotolo, M, Qian, X, Sasson, AS, Tang, H, et al
Cancer research. 2021;(2):282-288
Abstract
Although next-generation sequencing is widely used in cancer to profile tumors and detect variants, most somatic variant callers used in these pipelines identify variants at the lowest possible granularity, single-nucleotide variants (SNV). As a result, multiple adjacent SNVs are called individually instead of as a multi-nucleotide variants (MNV). With this approach, the amino acid change from the individual SNV within a codon could be different from the amino acid change based on the MNV that results from combining SNV, leading to incorrect conclusions about the downstream effects of the variants. Here, we analyzed 10,383 variant call files (VCF) from the Cancer Genome Atlas (TCGA) and found 12,141 incorrectly annotated MNVs. Analysis of seven commonly mutated genes from 178 studies in cBioPortal revealed that MNVs were consistently missed in 20 of these studies, whereas they were correctly annotated in 15 more recent studies. At the BRAF V600 locus, the most common example of MNV, several public datasets reported separate BRAF V600E and BRAF V600M variants instead of a single merged V600K variant. VCFs from the TCGA Mutect2 caller were used to develop a solution to merge SNV to MNV. Our custom script used the phasing information from the SNV VCF and determined whether SNVs were at the same codon and needed to be merged into MNV before variant annotation. This study shows that institutions performing NGS sequencing for cancer genomics should incorporate the step of merging MNV as a best practice in their pipelines. SIGNIFICANCE Identification of incorrect mutation calls in TCGA, including clinically relevant BRAF V600 and KRAS G12, will influence research and potentially clinical decisions.
-
3.
An overview of functional genomics and relevance of glycosyltransferases in exopolysaccharide production by lactic acid bacteria.
Soumya, MP, Nampoothiri, KM
International journal of biological macromolecules. 2021;:1014-1025
Abstract
There are many reports on exopolysaccharides of lactic acid bacteria (LAB EPS) such as isolation, production and applications. The LAB EPS have been proved to exhibit significantly improved texture and rheological properties in order to prevent syneresis of fermented foods. Furthermore, they are known to have many biological properties such as mouthwatering flavors, antioxidant activity, cholesterol lowering and antimicrobial activities. Considering their GRAS status, LAB EPS need to be explored for better titre and improved biological properties, where strain improvement by genetic engineering has a major role for making tailor-made EPS. The genetic overview of the EPS production by LAB is an auxiliary area of interest as the process and the biosynthetic pathway involves numerous genes and their proteins. Among them Glycosyltransferases (gtfs) are the key enzymes involved in EPS biosynthesis. Current knowledge of gtfs of LAB and its manipulation is limited. The present review spotlights the importance of glycosyltransferases and their specific role on the biosynthesis of LAB EPS and addresses the functionality and applicability of these enzymes and their products. It enfold the available literature including some patents in recent past to underline the fact that glycosyltransferases are un-reluctantly the key proteins involved in the EPS biosynthesis.
-
4.
Big genomic data analysis leads to more accurate trait prediction in hybrid breeding for yield enhancement in crop plants.
Singh, RK, Prasad, M
Plant cell reports. 2021;(10):2009-2011
Abstract
The 'big data' in plant breeding refers to the cumulative genotyping and phenotyping information obtained from either a series of experimental sets or generated from a large number of accessions. Recent study supports the employment of big data for enhancing the accuracy of complex trait prediction during hybrid breeding of crop plants.
-
5.
Genomics as a potential tool to unravel the rhizosphere microbiome interactions on plant health.
Priya, P, Aneesh, B, Harikrishnan, K
Journal of microbiological methods. 2021;:106215
Abstract
Intense agricultural practices to meet rising food demands have caused ecosystem perturbations. For sustainable crop production, biological agents are gaining attention, but exploring their functional potential on a multi-layered complex ecosystem like the rhizosphere is challenging. This review explains the significance of genomics as a culture-independent molecular tool to understand the diversity and functional significance of the rhizosphere microbiome for sustainable agriculture. It discusses the recent significant studies in the rhizosphere environment carried out using evolving techniques like metagenomics, metatranscriptomics, and metaproteomics, their challenges, constraints infield application, and prospective solutions. The recent advances in techniques such as nanotechnology for the development of bioformulations and visualization techniques contemplating environmental safety were also discussed. The need for development of metagenomic data sets of regionally important crops, their plant microbial interactions and agricultural practices for narrowing down significant data from huge databases have been suggested. The role of taxonomical and functional diversity of soil microbiota in understanding soil suppression and part played by the microbial metabolites in the process have been analyzed and discussed in the context of 'omics' approach. 'Omics' studies have revealed important information about microbial diversity, their responses to various biotic and abiotic stimuli, and the physiology of disease suppression. This can be translated to crop sustainability and combinational approaches with advancing visualization and analysis methodologies fix the existing knowledge gap to a huge extend. With improved data processing and standardization of the methods, details of plant-microbe interactions can be successfully decoded to develop sustainable agricultural practices.
-
6.
Genotyping-By-Sequencing diversity analysis of international Vanilla collections uncovers hidden diversity and enables plant improvement.
Chambers, A, Cibrián-Jaramillo, A, Karremans, AP, Moreno Martinez, D, Hernandez-Hernandez, J, Brym, M, Resende, MFR, Moloney, R, Sierra, SN, Hasing, T, et al
Plant science : an international journal of experimental plant biology. 2021;:111019
Abstract
Genomics-based diversity analysis of natural vanilla populations is important in order to guide conservation efforts and genetic improvement through plant breeding. Vanilla is a cultivated, undomesticated spice that originated in Mesoamerica prior to spreading globally through vegetative cuttings. Vanilla extract from the commercial species, mainly V. planifolia and V. × tahitensis, is used around the world as an ingredient in foods, beverages, cosmetics, and pharmaceuticals. The global reliance on descendants of a few foundational clones in commercial production has resulted in an industry at heightened risk of catastrophic failure due to extremely narrow genetic diversity. Conversely, national and institutional collections including those near the center of cultivation contain previously undiscovered diversity that could bolster the genetic improvement of vanilla and guide conservation efforts. Towards this goal, an international vanilla genotyping effort generated and analyzed 431,204 single nucleotide polymorphisms among 412 accessions and 27 species from eight collections. Phylogenetic and STRUCTURE analysis sorted vanilla by species and identified hybrid accessions. Principal Component Analysis and the Fixation Index (FST) were used to refine relationships among accessions and showed differentiation among species. Analysis of the commercial species split V. planifolia into three types with all V. × tahitensis accessions being most similar to V. planifolia type 2. Finally, an in-depth analysis of V. × tahitensis identified seven V. planifolia and six V. odorata accessions as most similar to the estimated parental genotypes providing additional data in support of the current hybrid theory. The prevalence of probable V. × tahitensis parental accessions from Belize suggests that V. × tahitensis could have originated from this area and highlights the need for vanilla conservation throughout Central and South America. The genetic groupings among accessions, particularly for V. planifolia, can now be used to focus breeding efforts on fewer accessions that capture the greatest diversity.
-
7.
How the pan-genome is changing crop genomics and improvement.
Della Coletta, R, Qiu, Y, Ou, S, Hufford, MB, Hirsch, CN
Genome biology. 2021;(1):3
Abstract
Crop genomics has seen dramatic advances in recent years due to improvements in sequencing technology, assembly methods, and computational resources. These advances have led to the development of new tools to facilitate crop improvement. The study of structural variation within species and the characterization of the pan-genome has revealed extensive genome content variation among individuals within a species that is paradigm shifting to crop genomics and improvement. Here, we review advances in crop genomics and how utilization of these tools is shifting in light of pan-genomes that are becoming available for many crop species.
-
8.
Through 40,000 years of human presence in Southern Europe: the Italian case study.
Aneli, S, Caldon, M, Saupe, T, Montinaro, F, Pagani, L
Human genetics. 2021;(10):1417-1431
-
-
Free full text
-
Abstract
The Italian Peninsula, a natural pier across the Mediterranean Sea, witnessed intricate population events since the very beginning of the human occupation in Europe. In the last few years, an increasing number of modern and ancient genomes from the area have been published by the international research community. This genomic perspective started unveiling the relevance of Italy to understand the post-Last Glacial Maximum (LGM) re-peopling of Europe, the earlier phase of the Neolithic westward migrations, and its linking role between Eastern and Western Mediterranean areas after the Iron Age. However, many open questions are still waiting for more data to be addressed in full. With this review, we summarize the current knowledge emerging from the available ancient Italian individuals and, by re-analysing them all at once, we try to shed light on the avenues future research in the area should cover. In particular, open questions concern (1) the fate of pre-Villabruna Europeans and to what extent their genomic components were absorbed by the post-LGM hunter-gatherers; (2) the role of Sicily and Sardinia before LGM; (3) to what degree the documented genetic structure within the Early Neolithic settlers can be described as two separate migrations; (4) what are the population events behind the marked presence of an Iranian Neolithic-like component in Bronze Age and Iron Age Italian and Southern European samples.
-
9.
Machine learning approaches for crop improvement: Leveraging phenotypic and genotypic big data.
Tong, H, Nikoloski, Z
Journal of plant physiology. 2021;:153354
Abstract
Highly efficient and accurate selection of elite genotypes can lead to dramatic shortening of the breeding cycle in major crops relevant for sustaining present demands for food, feed, and fuel. In contrast to classical approaches that emphasize the need for resource-intensive phenotyping at all stages of artificial selection, genomic selection dramatically reduces the need for phenotyping. Genomic selection relies on advances in machine learning and the availability of genotyping data to predict agronomically relevant phenotypic traits. Here we provide a systematic review of machine learning approaches applied for genomic selection of single and multiple traits in major crops in the past decade. We emphasize the need to gather data on intermediate phenotypes, e.g. metabolite, protein, and gene expression levels, along with developments of modeling techniques that can lead to further improvements of genomic selection. In addition, we provide a critical view of factors that affect genomic selection, with attention to transferability of models between different environments. Finally, we highlight the future aspects of integrating high-throughput molecular phenotypic data from omics technologies with biological networks for crop improvement.
-
10.
Integration of comprehensive data and biotechnological tools for industrial applications of Kluyveromyces marxianus.
Nurcholis, M, Lertwattanasakul, N, Rodrussamee, N, Kosaka, T, Murata, M, Yamada, M
Applied microbiology and biotechnology. 2020;(2):475-488
Abstract
Among the so-called non-conventional yeasts, Kluyveromyces marxianus has extremely potent traits that are suitable for industrial applications. Indeed, it has been used for the production of various enzymes, chemicals, and macromolecules in addition to utilization of cell biomass as nutritional materials, feed and probiotics. The yeast is expected to be an efficient ethanol producer with advantages over Saccharomyces cerevisiae in terms of high growth rate, thermotolerance and a wide sugar assimilation spectrum. Results of comprehensive analyses of its genome and transcriptome may accelerate studies for applications of the yeast and may further increase its potential by combination with recent biotechnological tools including the CRISPR/Cas9 system. We thus review published studies by merging with information obtained from comprehensive data including genomic and transcriptomic data, which would be useful for future applications of K. marxianus.