Which of the following best defines phenotype?

Genes and Phenotypes

Phenotypes (P) are affected by both genetic/inherited (G) and environmental (E) factors and combinations of G and E. Upon the discovery of DNA structure, the search for specific genetic determinants in human phenotypic variation began in earnest. Followed by a period of rapid development in the field of genomics and sequencing technologies, the Human Genome Project—a complete draft of the sequence of DNA chemical bases that make up the essential human genome—was completed in 2003. However, drafting how individuals are different genetically was about to begin.

Starting in the 2000s, making use of new technologies that measured single-nucleotide polymorphisms (SNPs), single places along the genome where individuals differ, molecular epidemiologists started to apply an analytically unbiased and comprehensive approach to look at the genetic contribution to phenotypic traits through genome-wide association studies (GWASs). In this approach, investigators genotype the common variants (i.e., with a prevalence of at least 5%–10% in the population) of the study subjects and systematically study the associations between millions of SNPs and disease, resulting in millions of hypothesis tests! There are over 10 million known SNPs in the human genome, depending on the ancestry of the population. A GWAS typically genotypes 1 million SNPs. So far, over 14,000 genetic variants have been successfully identified for human phenotypes and diseases.

In contrast, efforts and investments to advance measurement technologies in characterizing E at the same scale have been lacking. We cannot at present simultaneously assay 1000s of environmental exposure factors or their indicators in humans. Researchers have predicted personal exposure from deterministic models based on environmental information from static monitors. This includes predicting personal particulate exposure with stationary fine particulate matter level (PM2.5) or the pesticide exposures from the residual level in food. Depending on the measurement resolution, these methods are much more prone to measurement error than that of SNPs. Due to error, these measures often fail to capture the between person variation and provide only the average exposure of a group of individuals. Exposures are selected based on regulatory importance and subsequently used to conduct risk assessment.

Further still, in an epidemiologic study, investigators have typically used questionnaires to collect exposure information, such as dietary or occupational questionnaires. They provide a low-cost and simple approach to assess exposures. However, the quality of questionnaires has been debated and is said to be prone to misclassification bias. Even more glaringly, information collected is a biased set of items a priori chosen to exist on a questionnaire and scientists are only able to correlate that of which they can measure.

14.02.3 Biology of Experimental Hepatocarcinogenesis

Phenotypes of liver carcinogenesis stages are initiated, microscopic hyperproliferation, benign tumors, and malignancy (Figure 3). Initiated cells are recognized by focal increases in DNA synthetic activity detectable by thymidine or bromodeoxyuridine incorporation. Microscopic hyperproliferative areas (hepatic foci) are visualized using standard hematoxylin and eosin staining or by histochemical staining for certain metabolic enzymes. Benign tumors are called hepatoadenomas and malignancies are called hepatocarcinoma (HCC). Along with mouse skin, the rat liver is widely used for carcinogenesis studies (Dragan and Pitot 1990; Dragan et al. 1994). In vivo hepatocarcinogenesis models have been summarized (Goldsworthy et al. 1986). Diethylnitrosamine (DEN) is the most commonly used initiating agent. Models differ in the dosage and conditions of the first chemical treatment. The resistant hepatocyte model applies a necrogenic dose of DEN followed by a proliferative stimulus. In this case, the dose of DEN exerts initiating and promoting properties. In an alternative model, an initiating dose of DEN is applied during a rapid proliferation phase, either naturally occurring in neonates or induced in young adult animals following partial hepatectomy. In these latter protocols, the DEN dosage is largely a pure initiating dose. Promotion commonly is accomplished by phenobarbitol treatment. However, as in the mouse skin system, many pharmaceutical, environmental, and even endogenous agents, such as hormones or bile acids, can act as promoters. An endpoint in these assays is tumorigenicity. An intermediate endpoint is the formation of altered hepatic foci (AHF), defined histologically within sections of the liver by focal growth and biochemical changes. These foci are characterized by increases in histochemical detection of certain enzymes including gamma glutamyl transpeptidase (GGT), placental isozyme of glutathione S-transferase (PGST), and glucose 6-phosphatase. Different patterns of enzymatic expression are related to the particular promoter used (Dragan et al. 1994; Hanigan et al. 1993).

The number of preneoplastic lesions is high with initiation followed by promotion, but, as in the mouse skin, the number of carcinomas is low. In addition, as in the mouse epidermal model, initiation followed by promotion (two-stage protocol) leads to very few carcinomas, whereas treatment with a mutagen or another initiator increases the incidence of conversion into carcinoma. The initiation–promotion–progression model in the liver, which adds a second treatment with a mutagen, such as hydroxyurea or ethylnitrosamine, significantly increases the number of carcinomas (Dragan et al. 1993).

Evaluation of compounds as initiators or promoters is done by substitution of the test agents in the initiation–promotion protocols. In the case of initiators, dosage of the agent must be tested in the range which is both nontoxic (avoiding the promotion stimulus of tissue destruction and regeneration) and minimally effective alone in induction of lesions. Putative promoters must be tested in a range of concentrations and frequencies, since multiple treatments applied at an optimum interval are required for promoter effects, and scheduling and effective dose range may be promoter-dependent. This approach has been used to evaluate 2,3,7,8-tetrachlorodibenzo-p-dioxin promotion using the early and later endpoints in a two-stage model of liver hepatocarcinogenesis (Maronpot et al. 1993).

The Phenotype and Environment

A phenotype of central importance in crop breeding is yield stability, both in terms of total yield (underpinned by grain number and size) and consistency of quality attributes specific to end use and classification for processing. This is particularly important as climate change introduces conditions not previously experienced. Wheat grain yield has many components including whole plant attributes for optimal establishment and maturity/height features that in turn confer adaptive traits better enabling the plant to be suited to the environment in which it is grown. The supply of sugars to immature pollen in the developing head, and thereafter maturing grain during grain fill, has been identified as a critical plant metabolic phase determining grain yield and size, a result which has been consistently reported in studies on tomato (Ruan, 2012), cereals (Dolferus et al., 2013), and tobacco/Arabidopsis (Le Roy et al., 2013). Abiotic stresses (particularly water deficiency and frost) affect the developing spike and maturing grain due to the downregulation of key carbohydrate mobilization and cleavage genes (cell wall invertases and fructosyl transferases and exohydrolases). Tolerance at the genetic level requires expression of these genes under stress conditions to be maintained so that the developing pollen and grain receive sufficient energy supplies for development to reach completion unimpeded (Ruan, 2012; Barrero et al. 2011; Dolferus et al., 2013; Moghaddam and Van den Ende, 2012).

The major genes underpinning tolerance to a number of biotic stress factors includes genes belonging to the NBS-LRR class of proteins which have conserved features relating to signal transduction involved at the host–pathogen interface. Genome-level sequencing in wheat, for example, has demonstrated that the tan spot resistance Tsn1 gene encodes a NBS-LRR protein (Lu et al., 2011) consistent with gene structures found in other resistance genes (e.g., Rpg5 in barley, Brueggeman et al., 2008). In contrast, the leaf rust Lr34 gene (Krattinger et al., 2009) has been identified as belonging to the ABC transporter class of gene, postulated to be involved in secreting a currently undefined molecule to inhibit the growth of fungal hypha penetrating the leaf tissue. The stripe rust resistance Yr36 gene encodes a protein with a novel architecture resulting from domain reshuffling involving a kinase and a putative lipid binding domain (Fu et al., 2009). The stem rust resistance Sr2 gene in wheat has not been definitively identified but a cluster of germin-like protein coding genes is located at the Sr2 resistance locus and these have characterized as being analogous to the germin-like cluster of genes encoding blast resistance in rice (Breen and Bellgard, 2010).

Although components of yield can be readily defined, variation in the measured phenotype remains a significant factor in breeding programs. Breeding design must be sufficiently flexible to allow changes in crossing decisions to be made when instances of negative interactions between genotypes and environments arise. Designing trials and activities in a systematic way allows optimization of information to identify the genotypic basis of phenotypic differences in germplasm and the selection of lines for use in the crosses. The process by which these activities are structured requires the identification of parents for crosses, allocation into a design, data collection, and then the analysis of data from derived progeny. The science of trial design and the optimization of crossing/mating information is extensive (Kempton, 1982; Singh and Hinkelmann, 1998; Smith et al., 2006; Williams et al., 2011) and can be simulated using tools such as QU-Gene.

Important to information collection is the concept that the breeding process involves the generation of genetic variation, followed by the selection of elite germplasm, and the characterization of elite lines for desired traits. This process has the potential for errors to be transferred into consecutive stages of the breeding process. Developing trial designs such as ‘chained trial design’ that minimize type-II errors (false-positives and true-negatives) are becoming important considerations for breeding. The chained designs cover multiple testing of a plot (or grain sample) by incorporating within and between replication in each step tests to allow variance estimates. The statistical methods utilized are based on mixed-model restricted likelihood (REML).

What defines phenotype?

What is the best definition of phenotype quizlet?

Which of the following is the best example of a phenotype?

What is an example of a phenotype?