Current Issue : January - March Volume : 2021 Issue Number : 1 Articles : 5 Articles
Background: Productivity of cowpea [Vigna unguiculata (L.) Walp] in sub-Sahara Africa is curtailed by a lack of\nfarmer-preferred and improved cultivars and modern production technologies. The objectives of the study were to\ndetermine the extent of genetic diversity present among a collection of cowpea accessions from Zambia and\nMalawi using phenotypic traits and single nucleotide polymorphism (SNP) markers and, to select distinct and\ncomplementary parental lines for cultivar development. One hundred cowpea genotypes were evaluated for\nagronomic traits in two selected sites in Zambia, using ........................
Background: Genome-wide association studies (GWAS) have successfully identified genetic susceptible variants for\ncomplex diseases. However, the underlying mechanism of such association remains largely unknown. Most diseaseassociated\ngenetic variants have been shown to reside in noncoding regions, leading to the hypothesis that\nregulation of gene expression may be the primary biological mechanism. Current methods to characterize gene\nexpression mediating the effect of genetic variant on diseases, often analyzed one gene at a time and ignored the\nnetwork structure. The impact of genetic variant can propagate to other genes along the links in the network, then\nto the final disease. There could be multiple pathways from the genetic variant to the final disease, with each\nhaving the chain structure since the first node is one specific SNP (Single Nucleotide Polymorphism) variant and\nthe end is disease outcome. One key but inadequately addressed question is how to measure the between-node\nconnection strength and rank the effects of such chain-type pathways, which can provide statistical evidence to\ngive the priority of some pathways for potential drug development in a cost-effective manner.\nResults: We first introduce the maximal correlation coefficient (MCC) to represent the between-node connection,\nand then integrate MCC with K shortest paths algorithm to rank and identify the potential pathways from genetic\nvariant to disease. The pathway importance score (PIS) was further provided to quantify the importance of each\npathway. We termed this method as â??MCC-SPâ?. Various simulations are conducted to illustrate MCC is a better\nmeasurement of the between-node connection strength than other quantities including Pearson correlation,\nSpearman correlation, distance correlation, mutual information, and maximal information coefficient. Finally, we\napplied MCC-SP to analyze one real dataset from the Religious Orders Study and the Memory and Aging Project,\nand successfully detected 2 typical pathways from APOE genotype to Alzheimerâ??s disease (AD) through gene\nexpression enriched in Alzheimerâ??s disease pathway.......................
Background: Brachygnathia, cardiomegaly and renal hypoplasia syndrome (BCRHS, OMIA 001595â??9940) is a previously\nreported recessively inherited disorder in Australian Poll Merino/Merino sheep. Affected lambs are stillborn with various\ncongenital defects as reflected in the name of the disease, as well as short stature, a short and broad cranium, a small\nthoracic cavity, thin ribs and brachysternum. The BCRHS phenotype shows similarity to certain human short stature\nsyndromes, in particular the human 3M syndrome-2. Here we report the identification of a likely disease-causing variant\nand propose an ovine model for human 3M syndrome-2.\nResults: Eight positional candidate genes were identified among the 39 genes in the approximately 1 Mb interval to\nwhich the disease was mapped previously. Obscurin like cytoskeletal adaptor 1 (OBSL1) was selected as a strong\npositional candidate gene based on gene function and the resulting phenotypes observed in humans with mutations\nin this gene. Whole genome sequencing of an affected lamb (BCRHS3) identified a likely causal variant\nENSOARG00000020239:g.220472248delC within OBSL1. Sanger sequencing of seven affected, six obligate carrier, two\nphenotypically unaffected animals from the original flock and one unrelated control animal validated the variant. A\ngenotyping assay was developed to genotype 583 animals from the original flock, giving an estimated allele frequency\nof 5%.\nConclusions: The identification of a likely disease-causing variant resulting in a frameshift (p.(Val573Trpfs*119)) in the\nOBSL1 protein has enabled improved breeding management of the implicated flock. The opportunity for an ovine\nmodel for human 3M syndrome and ensuing therapeutic research is promising given the availability of carrier ram\nsemen for BCRHS....
Background: Reference genes are usually stably expressed in various cells and tissues. However, it was reported\nthat the expression of some reference genes may be distinct in different species. In this study, we intend to answer\nwhether the expression of reported traditional reference genes changes or not in the polyploid fish\nResults: By retrieving the mRNA sequencing data of three different ploidy fish from the NCBI SRA database, we\nselected 12 candidate reference genes, and examined their expression levels in the 10 tissues and in the four cell\nlines of three different ploidy fish by real-time PCR. Then, the expression profiles of these 12 candidate reference\ngenes were systematically evaluated by using the software platforms: BestKeeper, NormFinder and geNorm.\nConclusion: The 28S ribosomal protein S5 gene (RPS5) and the ribosomal protein S18 gene (RPS18) are the most\nsuitable reference genes for the polyploid of Cyprinus carpio and Carassius auratus, demonstrated by both of the\ntissues and the cultured cells....
Background: Associations between haplotypes and quantitative traits provide valuable information about the\ngenetic basis of complex human diseases. Haplotypes also provide an effective way to deal with untyped SNPs. Two\nmajor challenges arise in haplotype-based association analysis of family data. First, haplotypes may not be inferred\nwith certainty from genotype data. Second, the trait values within a family tend to be correlated because of common\ngenetic and environmental factors.\nResults: To address these challenges, we present an efficient likelihood-based approach to analyzing associations of\nquantitative traits with haplotypes or untyped SNPs. This approach properly accounts for within-family trait\ncorrelations and can handle general pedigrees with arbitrary patterns of missing genotypes. We characterize the\ngenetic effects on the quantitative trait by a linear regression model with random effects and develop efficient\nlikelihood-based inference procedures. Extensive simulation studies are conducted to examine the performance of\nthe proposed methods. An application to family data from the Childhood Asthma Management Program Ancillary\nGenetic Study is provided. A computer program is freely available.\nConclusions: Results from extensive simulation studies show that the proposed methods for testing the haplotype\neffects on quantitative traits have correct type I error rates and are more powerful than some existing methods....
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