A novel principal component analysis method for identifying differentially expressed gene signatures

Microarray data sets contain a wealth of information on the gene expression levels for thousands of genes for small number of different conditions called assays. But, the information is hidden by high noise levels, and low signal levels. Data mining techniques are used to extract the information of genes related to the assays. This work proposed a powerful principal component analysis (PCA) based method in extend of PCA approach of Rollins et. al. (2006). The proposed method is able to generate gene signatures that expressed the most differently between two assay groups in a microarray data set. This work developed and evaluated two new test statistics based on PCA and they were found to be effective as evaluated in different case studies including real and simulated data. The methods proposed in this work were compared to the current method. The proposed method was favor in term of high statistical power and low false discovery rate. Therefore, the PCA based approach is highly recommended for use in gene expressions data analysis

Major qtls for trunk height and correlated agronomic traits provide insights into multiple trait integration in oil palm breeding

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Superior oil yield is always the top priority of the oil palm industry. Short trunk height (THT) and compactness traits have become increasingly important to improve harvesting efficiency since the industry started to suffer yield losses due to labor shortages. Breeding populations with low THT and short frond length (FL) are actually available, such as Dumpy AVROS pisifera (DAV) and Gunung Melayu dura (GM). However, multiple trait stacking still remains a challenge for oil palm breeding, which usually requires 12–20 years to complete a breeding cycle. In this study, yield and height increment in the GM × GM (GM-3341) and the GM × DAV (GM-DAV-3461) crossing programs were evaluated and palms with good yield and smaller height increment were identified. In the GM-3341 family, non-linear THT growth between THT_2008 (seven years old) and THT_2014 (13 years old) was revealed by a moderate correlation, suggesting that inter-palm competition becomes increasingly important. In total, 19 quantitative trait loci (QTLs) for THT_2008 (8), oil per palm (O/P) (7) and FL (4) were localized on the GM-3341 linkage map, with an average mapping interval of 2.01 cM. Three major QTLs for THT_2008, O/P and FL are co-located on chromosome 11 and reflect the correlation of THT_2008 with O/P and FL. Multiple trait selection for high O/P and low THT (based on the cumulative effects of positive alleles per trait) identified one palm from 100 palms, but with a large starting population of 1000–1500 seedling per cross, this low frequency could be easily compensated for during breeding selection

An improved oil palm genome assembly as a valuable resource for crop improvement and comparative genomics in the Arecoideae subfamily

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Oil palm (Elaeis guineensis Jacq.) is the most traded crop among the economically important palm species. Here, we report an extended version genome of E. guineensis that is 1.2 Gb in length, an improvement of the physical genome coverage to 79% from the previous 43%. The improvement was made by assigning an additional 1968 originally unplaced scaffolds that were available publicly into the physical genome. By integrating three ultra-dense linkage maps and using them to place genomic scaffolds, the 16 pseudomolecules were extended. As we show, the improved genome has enhanced the mapping resolution for genome-wide association studies (GWAS) and permitted further identification of candidate genes/protein-coding regions (CDSs) and any non-coding RNA that may be associated with them for further studies. We then employed the new physical map in a comparative genomics study against two other agriculturally and economically important palm species—date palm (Phoenix dactylifera L.) and coconut palm (Cocos nucifera L.)—confirming the high level of conserved synteny among these palm species. We also used the improved oil palm genome assembly version as a palm genome reference to extend the date palm physical map. The improved genome of oil palm will enable molecular breeding approaches to expedite crop improvement, especially in the largest subfamily of Arecoideae, which consists of 107 species belonging to Arecaceae

The impact of a low glycemic index (GI) breakfast and snack on daily blood glucose profiles and food intake in young Chinese adult males

Acknowledgments We warmly thank the volunteers for taking the time to participate in this study. The study was supported by the Singapore Institute for Clinical Sciences.Peer reviewedPublisher PD

Characterizing haploinsufficiency of SHELL gene to improve fruit form prediction in introgressive hybrids of oil palm

The fundamental trait in selective breeding of oil palm (Eleais guineensis Jacq.) is the shell thickness surrounding the kernel. The monogenic shell thickness is inversely correlated to mesocarp thickness, where the crude palm oil accumulates. Commercial thin-shelled tenera derived from thick-shelled dura × shell-less pisifera generally contain 30% higher oil per bunch. Two mutations, shᴹᴾᴼᴮ (M1) and shAVROS (M2) in the SHELL gene – a type II MADS-box transcription factor mainly present in AVROS and Nigerian origins, were reported to be responsible for different fruit forms. In this study, we have tested 1,339 samples maintained in Sime Darby Plantation using both mutations. Five genotype-phenotype discrepancies and eight controls were then re-tested with all five reported mutations (shAVROS, shᴹᴾᴼᴮ, shᴹᴾᴼᴮ², shᴹᴾᴼᴮ ³ and shᴹᴾᴼᴮ⁴) within the same gene. The integration of genotypic data, pedigree records and shell formation model further explained the haploinsufficiency effect on the SHELL gene with different number of functional copies. Some rare mutations were also identified, suggesting a need to further confirm the existence of cis-compound mutations in the gene. With this, the prediction accuracy of fruit forms can be further improved, especially in introgressive hybrids of oil palm. Understanding causative variant segregation is extremely important, even for monogenic traits such as shell thickness in oil palm

A practical genome-enabled legitimacy assay for oil palm breeding and seed production

Background: Legitimacy in breeding and commercial crop production depends on optimised protocols to ensure purity of crosses and correct field planting of material. In oil palm, the presence of three fruit forms permits these assumptions to be tested, although only after field planting. The presence of incorrect fruit forms in a cross is a clear sign of illegitimacy. Given that tenera forms produce 30% more oil for the same weight of fruit as dura, the presence of low levels of dura contamination can have major effect during the economic lifespan of an oil palm, which is around 25 years. We evaluated two methods for legitimacy test 1) The use of SHELL markers to the gene that determines the shell-thickness trait 2) The use of SNP markers, to determine the legitimacy of the cross

Linkage-based genome assembly improvement of oil palm (Elaeis guineensis)

Meiotic crossovers in outbred species, such as oil palm (Elaeis guineensis Jacq., 2n = 32) contribute to allelic re-assortment in the genome. Such genetic variation is usually exploited in breeding to combine positive alleles for trait superiority. A good quality reference genome is essential for identifying the genetic factors underlying traits of interest through linkage or association studies. At the moment, an AVROS pisifera genome is publicly available for oil palm. Distribution and frequency of crossovers throughout chromosomes in different origins of oil palm are still unclear. Hence, an ultrahigh-density genomic linkage map of a commercial Deli dura x AVROS pisifera family was constructed using the OP200K SNP array, to evaluate the genetic alignment with the genome assembly. A total of 27,890 linked SNP markers generated a total map length of 1,151.7 cM and an average mapping interval of 0.04 cM. Nineteen linkage groups represented 16 pseudo-chromosomes of oil palm, with 61.7% of the mapped SNPs present in the published genome. Meanwhile, the physical map was also successfully extended from 658 Mb to 969 Mb by assigning unplaced scaffolds to the pseudo-chromosomes. A genic linkage map with major representation of sugar and lipid biosynthesis pathways was subsequently built for future studies on oil related quantitative trait loci (QTL). This study improves the current physical genome of the commercial oil palm, and provides important insights into its recombination landscape, eventually unlocking the full potential genome sequence-enabled biology for oil palm

Non-invasive health prediction from visually observable features [version 2; peer review: 1 approved, 1 approved with reservations]

Background: The unprecedented development of Artificial Intelligence has revolutionised the healthcare industry. In the next generation of healthcare systems, self-diagnosis will be pivotal to personalised healthcare services. During the COVID-19 pandemic, new screening and diagnostic approaches like mobile health are well-positioned to reduce disease spread and overcome geographical barriers. This paper presents a non-invasive screening approach to predict the health of a person from visually observable features using machine learning techniques. Images like face and skin surface of the patients are acquired using camera or mobile devices and analysed to derive clinical reasoning and prediction of the person’s health. Methods: In specific, a two-level classification approach is presented. The proposed hierarchical model chooses a class by training a binary classifier at the node of the hierarchy. Prediction is then made using a set of class-specific reduced feature set. Results: Testing accuracies of 86.87% and 76.84% are reported for the first and second-level classification. Empirical results demonstrate that the proposed approach yields favourable prediction results while greatly reduces the computational time. Conclusions: The study suggests that it is possible to predict the health condition of a person based on his/her face appearance using cost-effective machine learning approaches

Characterizing haploinsufficiency of SHELL gene to improve fruit form prediction in introgressive hybrids of oil palm

The fundamental trait in selective breeding of oil palm (Eleais guineensis Jacq.) is the shell thickness surrounding the kernel. The monogenic shell thickness is inversely correlated to mesocarp thickness, where the crude palm oil accumulates. Commercial thin-shelled tenera derived from thick-shelled dura × shell-less pisifera generally contain 30% higher oil per bunch. Two mutations, shᴹᴾᴼᴮ (M1) and shAVROS (M2) in the SHELL gene – a type II MADS-box transcription factor mainly present in AVROS and Nigerian origins, were reported to be responsible for different fruit forms. In this study, we have tested 1,339 samples maintained in Sime Darby Plantation using both mutations. Five genotype-phenotype discrepancies and eight controls were then re-tested with all five reported mutations (shAVROS, shᴹᴾᴼᴮ, shᴹᴾᴼᴮ², shᴹᴾᴼᴮ ³ and shᴹᴾᴼᴮ⁴) within the same gene. The integration of genotypic data, pedigree records and shell formation model further explained the haploinsufficiency effect on the SHELL gene with different number of functional copies. Some rare mutations were also identified, suggesting a need to further confirm the existence of cis-compound mutations in the gene. With this, the prediction accuracy of fruit forms can be further improved, especially in introgressive hybrids of oil palm. Understanding causative variant segregation is extremely important, even for monogenic traits such as shell thickness in oil palm