Medicinal Plants: Future Thrust Areas and Research Directions
Amit Baran Sharangi, K. V. Peter in Medicinal Plants, 2023
Different types of markers like restriction fragment length polymorphism (RFLP), random amplified polymorphic DNA (RAPD), inter simple sequence repeats (ISSR), simple sequence repeats (SSR) and amplified fragment length polymorphism (AFLP) markers are used for validation purpose in MAPs. DNA barcodes using second internal transcribed spacer (ITS2) region are used for discriminating medicinal plant species (Pang and Chen, 2014). RAPD analysis was used for evaluation of genetic relationships in several medicinal plant species. ISSR markers were used to evaluate the genetic diversity in many of the medicinal plants. Molecular markers can be employed to characterize any phenotypic trait, biochemical, and/or physiological mechanisms. The direct measurement of such traits can be simultaneously mapped. The number of loci controlling genetic variation of any important agronomic trait(s) in segregating population can be estimated, and the map positions of these loci in the genome be determined by means of molecular linkage genetic maps and QTL mapping technology.
Race and the Role of Sociocultural Context in Forensic Anthropological Ancestry Assessment
Heather M. Garvin, Natalie R. Langley in Case Studies in Forensic Anthropology, 2019
Furthermore, while race is socially defined, there does exist observable phenotypic, or physically expressed, variation among human groups that is biological in nature. However, patterned variation in human variation does not equate to race; race is typically conceived of as discrete bins, whereas biological variation is clinal – that is, much of human physical variation occurs along gradients (typically geographic in nature) with no well-defined or distinct boundaries. The systematic nature of human variation means that more closely related populations of individuals tend to share greater similarity in their phenotypic expression – including skeletal traits – than do more distantly related groups, even though expression of those traits is not homogenous within any group (i.e., there is significant variation within groups) and any given expression of a trait is not unique to any one group (Hefner, 2009: Tables 3–13). Perhaps the simplest clinal or geographically patterned phenotypic trait to appreciate in humans is skin color (Relethford, 2002). Yet, when it comes to race, an individual’s skin color does not obligate them to self-identify by others’ external categories; for example, individuals who self-identify as “Black” can have less melanin (i.e., lighter skin tone) than those who self-identify as “White.”
The Reproductive Systems of Davidson’s Plum (Davidsonia jerseyana, Davidsonia pruriens and Davidsonia johnsonii) and the Potential for Domestication
Yasmina Sultanbawa, Fazal Sultanbawa in Australian Native Plants, 2017
Genetic markers, such as SSRs, have been used for assessing the genetic diversity in many perennial tree crops (Arias et al., 2012; Jamnadass et al., 2009) and can increase the efficiency and precision of plant breeding programmes through marker-assisted selection (MAS) (Arias et al., 2012; Prentis et al., 2013). In breeding programmes, molecular markers fall into two categories: those which mark the mutation which causes the observed phenotypic variation (perfect markers) or more common are markers that are indirectly associated with the causal mutation (linked markers) (Prentis et al., 2013). To utilise MAS, you need to correlate a genetic maker to a trait of interest and for this, it is necessary to have reliable phenotypic data. This data needs to be obtained from fairly large mapping populations consisting of the progeny of crosses between parental lines that differ in the phenotypic trait of interest. A large number of markers are also necessary, so these approaches require considerable resources. However, with advances in technology such as next-generation sequencing, techniques such as MAS are becoming more feasible. The markers developed for Davidsonia species are useful in the immediate future for population genetics, DNA fingerprinting, characterising germplasm collections and identifying individuals from different populations.
How have our clocks evolved? Adaptive and demographic history of the out-of-African dispersal told by polymorphic loci in circadian genes
Published in Chronobiology International, 2018
Arcady A. Putilov, Vladimir B. Dorokhov, Michael G. Poluektov
For such phenotypic trait as chronotype a latitude-dependent variation was recognized in the analyses of questionnaire data collected in both Northern (Randler C 2017) and Southern Hemispheres (Leocadio-Miguel et al. 2017). However, the simplest explanation for the origin of the revealed shift toward eveningness at higher latitudes might be the latitude-dependent reduction of the exposure to light (Leocadio-Miguel et al. 2017). On the other hand, significant differences in chronotype between people tracing their ancestry to different continents were also found in, at least, two multi-ethnic communities. In the USA, non-Hispanic European Americans differed from African Americans in reporting a more pronounced evening preference (Eastman et al. 2016; Malone et al. 2017), having a longer circadian period (Eastman et al. 2012; Eastman et al. 2016; Eastman et al. 2017) and a smaller impact of extreme circadian misalignment on sleep duration (Paech et al. 2017). In Brazil, a shift toward morningness was related to Amerindian but not African or European ancestry (Egan et al. 2017).
A behavioral model for mapping the genetic architecture of gut-microbiota networks
Published in Gut Microbes, 2021
Libo Jiang, Xinjuan Liu, Xiaoqing He, Yi Jin, Yige Cao, Xiang Zhan, Christopher H. Griffin, Claudia Gragnoli, Rongling Wu
Most of the current GWAS characterize the association between genotype and high-order phenotypes, such as complex traits or diseases. However, this association may be determined by a certain “black box” behind the causal link from genotype to phenotype. Such a black box is widely recognized as a series of regulatory processes that drive DNA to genes to proteins to metabolites. We argue that the black box may involve the mediation of the gut microbiota because of increasing evidence that the gut microbiota is associated with human phenotypes. Here, we can test whether microbial networks serves as a black box to modulate genotype-phenotype relationship. Let zi denote the high-order phenotypic value of a quantitative trait on individual i. We calculate the Pearson correlation between y and z across individuals, denoted as ryz, to quantify and test the association between the network property and host phenotype. Meanwhile, we use Huo et al.’s58 mutual information approach to calculate the correlations between (discrete) genotype (g) and (continuous) network variable (y) and high-order phenotypic trait (z), denoted as rgy and rgz, respectively.
Clinical genomics and contextualizing genome variation in the diagnostic laboratory
Published in Expert Review of Molecular Diagnostics, 2020
James R. Lupski, Pengfei Liu, Pawel Stankiewicz, Claudia M. B. Carvalho, Jennifer E. Posey
Initial clinical exome sequencing (cES) studies on significant numbers of consecutive patients/cases, N = 814 [16] and N = 3,386 [17], undergoing genome-wide analyses by cES in a clinical diagnostic laboratory, revealed a molecular diagnosis explaining part/all of the observed clinical disease phenotype in about 25–30% of patients. Also of interest was the identification by cES of multi-locus pathogenic variation, i.e. two or more molecular diagnoses, often resulting in a blended phenotype [19]. In all, about 1 in 20 clinically affected individuals that have a molecular diagnosis concluded by cES can have multi-locus pathogenic variation. A blended phenotype can result from two or more molecular diagnoses that can have either overlapping or distinct clinical phenotypic features that have been associated with each of the individual genes/loci [20]. The resultant ‘blended phenotypes’ for multilocus pathogenic variation can be particularly challenging to clinical diagnosis for the physician observing the patient because the patient’s phenotype may not be perceived as a mixture of disease traits and thus sometimes including both clinical diagnoses, or parts of the phenotypic trait features, within the formulated differential diagnoses.