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ACS Omega Mar 2021We developed a highly sensitive method for quantifying 21 bile acids (BAs) in the rat liver by capillary liquid chromatography tandem mass spectrometry (cLC/MS/MS) with...
We developed a highly sensitive method for quantifying 21 bile acids (BAs) in the rat liver by capillary liquid chromatography tandem mass spectrometry (cLC/MS/MS) with one-pot extraction. High recovery rates were obtained for the one-pot methods with either methanol (MeOH) extraction or MeOH/acetonitrile (ACN) (1:1, v/v) mixture extraction; the results obtained for the MeOH/ACN mixture solution were better than the results obtained for MeOH. Thus, we determined that the one-pot method with MeOH/ACN was the most suitable method for the efficient extraction of BAs in the liver. Targeted BAs were well separated by cLC with gradient elution using ammonium acetate (NHOAc)-MeOH mobile phases. Method validation proved that the intra-day and inter-day accuracies and precisions were primarily less than ±20 and 20% relative standard deviation, respectively. Also, the limit of detection (LOD) and the limit of quantitation (LOQ) were 0.9-10 and 2.3-27 ng/g liver, which proves the high sensitivity of the method. Finally, we quantitated 21 BA concentrations in the liver samples of normal and nonalcoholic steatohepatitis (NASH) rats, both of which were derived from stroke-prone spontaneously hypertensive five (SHRSP5) /Dmcr rat. The hepatic BA profiles were found to be substantially different between the normal and NASH groups; the two groups were clearly separated along the first component axis in the score plots of the principal component analysis. In particular, 10 BAs (β-muricholic acid (MCA), glyco (G-) cholic acid (CA), G-chenodeoxycholic acid (CDCA), tauro (T-) CA, T-CDCA, T-ursodeoxycholic acid (UDCA), T-lithocholic acid (LCA), T-hiodeoxycholic acid (HDCA), T-α-MCA, and T-β-MCA) were significantly different between the two groups using Welch's -test with the false discovery rate correction method, demonstrating BA disruption in the NASH model rat. In conclusion, this method was able to quantify 21 BAs in the rat liver and will evaluate the hepatic BA pathophysiology of rat disease models.
PubMed: 33817519
DOI: 10.1021/acsomega.1c00403 -
Plants (Basel, Switzerland) Feb 2021Bakanae disease is a fungal disease of rice ( L.) caused by the pathogen (also known as ). This study was carried out to identify novel quantitative trait loci (QTLs)...
Bakanae disease is a fungal disease of rice ( L.) caused by the pathogen (also known as ). This study was carried out to identify novel quantitative trait loci (QTLs) from an variety Zenith. We performed a QTL mapping using 180 F recombinant inbred lines (RILs) derived from a cross between the resistant variety, Zenith, and the susceptible variety, Ilpum. A primary QTL study using the genotypes and phenotypes of the RILs indicated that the locus conferring bakanae disease resistance from the Zenith was located in a 2.8 Mb region bordered by the two RM (Rice Microsatellite) markers, RM1331 and RM3530 on chromosome 1. The log of odds (LOD) score of was 13.43, accounting for 30.9% of the total phenotypic variation. A finer localization of was delimited at an approximate 730 kb interval in the physical map between Chr01_1435908 (1.43 Mbp) and RM10116 (2.16 Mbp). Introducing or pyramiding with other previously identified QTLs could provide effective genetic control of bakanae disease in rice.
PubMed: 33668736
DOI: 10.3390/plants10030434 -
Frontiers in Genetics 2021Inherited hearing loss is extremely heterogeneous both clinically and genetically. In addition, the spectrum of deafness-causing genetic variants differs greatly among...
Inherited hearing loss is extremely heterogeneous both clinically and genetically. In addition, the spectrum of deafness-causing genetic variants differs greatly among geographical areas and ethnicities. The identification of the causal mutation in affected families allows early diagnosis, clinical follow-up, and genetic counseling. A large consanguineous family of Moroccan origin affected by autosomal recessive sensorineural hearing loss (ARSNHL) was subjected to genome-wide linkage analysis and exome sequencing. Exome-wide variant analysis and prioritization identified the p.C113Y missense variant (rs768484124) as the most likely cause of ARSNHL in the family, falling within the unique significant (LOD score>3) linkage region on chromosome 5. Indeed, the same variant was previously reported in two Tunisian ARSNHL pedigrees. The variant is present in the homozygous state in all six affected individuals, but also in one normal-hearing sibling, suggesting incomplete penetrance. The mutation is absent in about 1,000 individuals from the Greater Middle East Variome study cohort, including individuals from the North African population, as well as in an additional seven deaf patients from the same geographical area, recruited and screened for mutations in the gene. This study represents the first independent replication of the involvement of in ARSNHL, highlighting the importance of the gene, and of the p.C113Y mutation, at least in the Northwest African population.
PubMed: 33643381
DOI: 10.3389/fgene.2021.606630 -
Environmental Pollution (Barking, Essex... May 2021Genetic effects are suspected to influence cadmium internal dose. Our objective was to assess genetic determinants of urine cadmium in American Indian adults...
Genetic effects are suspected to influence cadmium internal dose. Our objective was to assess genetic determinants of urine cadmium in American Indian adults participating in the Strong Heart Family Study (SHFS). Urine cadmium levels and genotyped short tandem repeat (STR) markers were available on 1936 SHFS participants. We investigated heritability, including gene-by-sex and smoking interactions, and STR-based quantitative trait locus (QTL) linkage, using a variance-component decomposition approach, which incorporates the genetic information contained in the pedigrees. We also used available single nucleotide polymorphisms (SNPs) from Illumina's Metabochip and custom panel to assess whether promising QTLs associated regions could be attributed to SNPs annotated to specific genes. Median urine cadmium levels were 0.44 μg/g creatinine. The heritability of urine cadmium concentrations was 28%, with no evidence of gene-by-sex or -smoking interaction. We found strong statistical evidence for a genetic locus at chromosome 16 determining urine cadmium concentrations (Logarithm of odds score [LOD] = 3.8). Among the top 20 associated SNPs in this locus, 17 were annotated to ABCC1 (p-values from 0.0002 to 0.02), and attenuated the maximum linkage peak by a ∼40%. Suggestive QTL signals (LOD>1.9) in chromosomes 2, 6, 11, 14, and 19, showed associated SNPs in the genes NDUFA10, PDE10A, PLEKHA7, BAZ1A and CHAF1A, respectively. Our findings support that urinary cadmium levels are heritable and influenced by a QTL on chromosome 16, which was explained by genetic variation in ABCC1. Studies with extended sets of genome-wide markers are needed to confirm these findings and to identify additional metabolism and toxicity pathways for cadmium.
Topics: Adult; Cadmium; Chromosomal Proteins, Non-Histone; Genetic Linkage; Genotype; Humans; Multidrug Resistance-Associated Proteins; Phosphoric Diester Hydrolases; Polymorphism, Single Nucleotide; Quantitative Trait Loci
PubMed: 33640655
DOI: 10.1016/j.envpol.2021.116717 -
BMC Genomics Feb 2021Tartary buckwheat (Fagopyrum tataricum), an important pseudocereal crop, has high economic value due to its nutritional and medicinal properties. However, dehulling of...
BACKGROUND
Tartary buckwheat (Fagopyrum tataricum), an important pseudocereal crop, has high economic value due to its nutritional and medicinal properties. However, dehulling of Tartary buckwheat is difficult owing to its thick and tough hull, which has greatly limited the development of the Tartary buckwheat processing industry. The construction of high-resolution genetic maps serves as a basis for identifying quantitative trait loci (QTLs) and qualitative trait genes for agronomic traits. In this study, a recombinant inbred lines (XJ-RILs) population derived from a cross between the easily dehulled Rice-Tartary type and Tartary buckwheat type was genotyped using restriction site-associated DNA (RAD) sequencing to construct a high-density SNP genetic map. Furthermore, QTLs for 1000-grain weight (TGW) and genes controlling hull type were mapped in multiple environments.
RESULTS
In total, 4151 bin markers comprising 122,185 SNPs were used to construct the genetic linkage map. The map consisted of 8 linkage groups and covered 1444.15 cM, with an average distance of 0.35 cM between adjacent bin markers. Nine QTLs for TGW were detected and distributed on four loci on chromosome 1 and 4. A major locus detected in all three trials was mapped in 38.2-39.8 cM region on chromosome 1, with an LOD score of 18.1-37.0, and explained for 23.6-47.5% of the phenotypic variation. The genes controlling hull type were mapped to chromosome 1 between marker Block330 and Block331, which was closely followed by the major locus for TGW. The expression levels of the seven candidate genes controlling hull type present in the region between Block330 and Block336 was low during grain development, and no significant difference was observed between the parental lines. Six non-synonymous coding SNPs were found between the two parents in the region.
CONCLUSIONS
We constructed a high-density SNP genetic map for the first time in Tartary buckwheat. The mapped major loci controlling TGW and hull type will be valuable for gene cloning and revealing the mechanism underlying grain development and easy dehulling, and marker-assisted selection in Tartary buckwheat.
Topics: Edible Grain; Fagopyrum; Genetic Linkage; Polymorphism, Single Nucleotide; Quantitative Trait Loci
PubMed: 33639857
DOI: 10.1186/s12864-021-07449-w -
G3 (Bethesda, Md.) Apr 2021Quantitative trait loci (QTL) hotspots (genomic locations enriched in QTL) are a common and notable feature when collecting many QTL for various traits in many areas of...
Quantitative trait loci (QTL) hotspots (genomic locations enriched in QTL) are a common and notable feature when collecting many QTL for various traits in many areas of biological studies. The QTL hotspots are important and attractive since they are highly informative and may harbor genes for the quantitative traits. So far, the current statistical methods for QTL hotspot detection use either the individual-level data from the genetical genomics experiments or the summarized data from public QTL databases to proceed with the detection analysis. These methods may suffer from the problems of ignoring the correlation structure among traits, neglecting the magnitude of LOD scores for the QTL, or paying a very high computational cost, which often lead to the detection of excessive spurious hotspots, failure to discover biologically interesting hotspots composed of a small-to-moderate number of QTL with strong LOD scores, and computational intractability, respectively, during the detection process. In this article, we describe a statistical framework that can handle both types of data as well as address all the problems at a time for QTL hotspot detection. Our statistical framework directly operates on the QTL matrix and hence has a very cheap computational cost and is deployed to take advantage of the QTL mapping results for assisting the detection analysis. Two special devices, trait grouping and top γn,α profile, are introduced into the framework. The trait grouping attempts to group the traits controlled by closely linked or pleiotropic QTL together into the same trait groups and randomly allocates these QTL together across the genomic positions separately by trait group to account for the correlation structure among traits, so as to have the ability to obtain much stricter thresholds and dismiss spurious hotspots. The top γn,α profile is designed to outline the LOD-score pattern of QTL in a hotspot across the different hotspot architectures, so that it can serve to identify and characterize the types of QTL hotspots with varying sizes and LOD-score distributions. Real examples, numerical analysis, and simulation study are performed to validate our statistical framework, investigate the detection properties, and also compare with the current methods in QTL hotspot detection. The results demonstrate that the proposed statistical framework can effectively accommodate the correlation structure among traits, identify the types of hotspots, and still keep the notable features of easy implementation and fast computation for practical QTL hotspot detection.
Topics: Chromosome Mapping; Computer Simulation; Lod Score; Phenotype; Quantitative Trait Loci
PubMed: 33638985
DOI: 10.1093/g3journal/jkab056 -
Frontiers in Aging Neuroscience 2021Modular organization reflects the activity patterns of our brain. Different disease states may lead to different activity patterns and clinical features. Early onset...
Modular organization reflects the activity patterns of our brain. Different disease states may lead to different activity patterns and clinical features. Early onset depression (EOD) and late onset depression (LOD) share the same clinical symptoms, but have different treatment strategies and prognosis. Thus, explored the modular organization of EOD and LOD might help us understand their pathogenesis. The study included 82 patients with late life depression (EOD 40, LOD 42) and 90 healthy controls. We evaluated the memory, executive function and processing speed and performed resting-stage functional MRI for all participants. We constructed a functional network based on Granger causality analysis and carried out modularity, normalized mutual information (NMI), Phi coefficient, within module degree z-score, and participation coefficient analyses for all the participants. The Granger function network analysis suggested that the functional modularity was different among the three groups ( = 0.0300), and NMI analysis confirmed that the partition of EOD was different from that of LOD ( = 0.0190). Rh.10d.ROI (polar frontal cortex) and Rh.IPS1.ROI (dorsal stream visual cortex) were shown to be the potential specific nodes in the modular assignment according to the Phi coefficient ( = 0.0002, = 0.0744 & = 0.0004, = 0.0744). This study reveal that the functional modularity and partition were different between EOD and LOD in Granger function network. These findings support the hypothesis that different pathological changes might exist in EOD and LOD.
PubMed: 33633563
DOI: 10.3389/fnagi.2021.625175 -
Genetic analysis and QTL mapping of yield and fruit traits in bitter gourd (Momordica charantia L.).Scientific Reports Feb 2021Bitter gourd (Momordica charantia L.) is an economically important vegetable crop grown in tropical parts of the world. In this study, a high-density linkage map of M....
Bitter gourd (Momordica charantia L.) is an economically important vegetable crop grown in tropical parts of the world. In this study, a high-density linkage map of M. charantia was constructed through genotyping-by-sequencing (GBS) technology using F mapping population generated from the cross DBGy-201 × Pusa Do Mausami. About 2013 high-quality SNPs were assigned on a total of 20 linkage groups (LGs) spanning over 2329.2 CM with an average genetic distance of 1.16 CM. QTL analysis was performed for six major yield-contributing traits such as fruit length, fruit diameter, fruit weight, fruit flesh thickness, number of fruits per plant and yield per plant. These six quantitative traits were mapped with 19 QTLs (9 QTLs with LOD > 3) using composite interval mapping (CIM). Among 19 QTLs, 12 QTLs derived from 'Pusa Do Mausami' revealed a negative additive effect when its allele increased trait score whereas 7 QTLs derived from 'DBGy-201' revealed a positive additive effect when its allele trait score increased. The phenotypic variation (R%) elucidated by these QTLs ranged from 0.09% (fruit flesh thickness) on LG 14 to 32.65% (fruit diameter) on LG 16 and a total of six major QTLs detected. Most QTLs detected in the present study were located relatively very close, maybe due to the high correlation among the traits. This information will serve as a significant basis for marker-assisted selection and molecular breeding in bitter gourd crop improvement.
Topics: Alleles; Chromosome Mapping; Fruit; Genetic Linkage; Genetic Testing; Momordica charantia; Phenotype; Polymorphism, Single Nucleotide; Quantitative Trait Loci
PubMed: 33603131
DOI: 10.1038/s41598-021-83548-8 -
ACS Omega Feb 2021Rapid, accurate, and low-cost detection of SARS-CoV-2 is crucial to contain the transmission of COVID-19. Here, we present a cost-effective smartphone-based device...
Rapid, accurate, and low-cost detection of SARS-CoV-2 is crucial to contain the transmission of COVID-19. Here, we present a cost-effective smartphone-based device coupled with machine learning-driven software that evaluates the fluorescence signals of the CRISPR diagnostic of SARS-CoV-2. The device consists of a three-dimensional (3D)-printed housing and low-cost optic components that allow excitation of fluorescent reporters and selective transmission of the fluorescence emission to a smartphone. Custom software equipped with a binary classification model has been developed to quantify the acquired fluorescence images and determine the presence of the virus. Our detection system has a limit of detection (LoD) of 6.25 RNA copies/μL on laboratory samples and produces a test accuracy of 95% and sensitivity of 97% on 96 nasopharyngeal swab samples with transmissible viral loads. Our quantitative fluorescence score shows a strong correlation with the quantitative reverse transcription polymerase chain reaction (RT-qPCR) Ct values, offering valuable information of the viral load and, therefore, presenting an important advantage over nonquantitative readouts.
PubMed: 33553890
DOI: 10.1021/acsomega.0c04929 -
International Journal of Genomics 2021Sorghum ( (L.) Moench) is an important food crop in semi-arid tropics. The crop grain yield ranges from 0.5 t/ha to 0.8 t/ha compared to potential yields of...
Sorghum ( (L.) Moench) is an important food crop in semi-arid tropics. The crop grain yield ranges from 0.5 t/ha to 0.8 t/ha compared to potential yields of 10 t/ha. The African stem borer Fuller (Noctuidae) and the spotted stem borer Swinhoe (Crambidae), are among the most economically important insect pests of sorghum. The two borers can cause 15% - 80% grain yield loss in sorghum. Mapping of QTLs associated with resistance traits to the two stem borers is important towards marker-assisted breeding. The objective of this study was to map QTLs associated with resistance traits to and in sorghum. 243 F sorghum RILs derived from ICSV 745 (S) and PB 15520-1 (R) were selected for the study with 4,955 SNP markers. The RILs were evaluated in three sites. Data was collected on leaf feeding, deadheart, exit holes, stem tunnels, leaf toughness, seedling vigour, bloom waxiness, and leaf glossiness. ANOVA for all the traits was done using Genstat statistical software. Insect damage traits and morphological traits were correlated using Pearson's correlation coefficients. Genetic mapping was done using JoinMap 4 software, while QTL analysis was done using PLABQTL software. A likelihood odds ratio (LOD) score of 3.0 was used to declare linkage. Joint analyses across borer species and sites revealed 4 QTLs controlling deadheart formation; 6 controlling leaf feeding damage; 5 controlling exit holes and stem tunneling damages; 2 controlling bloom waxiness, leaf glossiness, and seedling vigour; 4 conditioning trichome density; and 6 conditioning leaf toughness. Joint analyses for and further revealed that marker colocalised for leaf toughness and stem tunneling traits on QTLs 1 and 2, respectively; thus, the two traits can be improved using the same linked marker. This study recommended further studies to identify gene(s) underlying the mapped QTLs.
PubMed: 33532486
DOI: 10.1155/2021/7016712