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Mendel's pea crosses: varieties, traits and statistics.

ABSTRACT: A controversy arose over Mendel's pea crossing experiments after the statistician R.A. Fisher proposed how these may have been performed and criticised Mendel's interpretation of his data. Here we re-examine Mendel's experiments and investigate Fisher's statistical criticisms of bias. We describe pea varieties available in Mendel's time and show that these could readily provide all the material Mendel needed for his experiments; the characters he chose to follow were clearly described in catalogues at the time. The combination of character states available in these varieties, together with Eichling's report of crosses Mendel performed, suggest that two of his F3 progeny test experiments may have involved the same F2 population, and therefore that these data should not be treated as independent variables in statistical analysis of Mendel's data. A comprehensive re-examination of Mendel's segregation ratios does not support previous suggestions that they differ remarkably from expectation. The χ2 values for his segregation ratios sum to a value close to the expectation and there is no deficiency of extreme segregation ratios. Overall the χ values for Mendel's segregation ratios deviate slightly from the standard normal distribution; this is probably because of the variance associated with phenotypic rather than genotypic ratios and because Mendel excluded some data sets with small numbers of progeny, where he noted the ratios "deviate not insignificantly" from expectation.

SUBMITTER: Ellis THN

PROVIDER: S-EPMC6823958 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Pea or Pisum sativum L. is a key diversification crop, but current varieties are not very competitive against weeds. The objective was to identify, depending on the type of cropping system and weed flora, (1) the key pea parameters that drive crop production, weed control and weed contribution to biodiversity, (2) optimal combinations of pea-parameter values and crop-management techniques to maximize these goals. For this, virtual experiments were run, using FLORSYS, a mechanistic simulation model. This individual-based 3D model simulates daily crop-weed seed and plant dynamics over the years, from the cropping system and pedoclimate. Here, this model was parameterized for seven pea varieties, from experiments and literature. Moreover, ten virtual varieties were created by randomly combining variety-parameter values according to a Latin Hypercube Sampling (LHS) plan, respecting parameter ranges and correlations observed in the actual varieties. A global sensitivity analysis was run, using another LHS plan to combine pea varieties, crop rotations and management techniques in nine contrasting situations (e.g., conventional vs. organic, no-till, type of weed flora). Simulated data were analyzed with classification and regression trees (CART). We highlighted (1) Parameters that drive potential yield and competitivity against weeds (notably the ability to increase plant height and leaf area in shaded situations), depending on variety type (spring vs. winter) and cropping system. These are pointers for breeding varieties to regulate weeds by biological interactions; (2) Rules to guide farmers to choose the best pea variety, depending on the production goal and the cropping system; (3) The trade-off between increasing yield potential and minimizing yield losses due to weeds when choosing pea variety and management, especially in winter peas. The main pea-variety rules were the same for all performance goals, management strategies, and analyses scales, but further rules were useful for individual goals, strategies, and scales. Some variety features only fitted to particular systems (e.g., delayed pea emergence is only beneficial in case of herbicide-spraying and disastrous in unsprayed systems). Fewer variety rules should be compensated by more management rules. If one of the two main weed-control levers, herbicide or tillage, was eliminated, further pea-variety and/or management rules were needed.

Project description:BackgroundIndependent studies have shown that several single nucleotide polymorphisms (SNP) in the human FTO (fat mass and obesity associated) gene are associated with obesity. SNP have also been identified in the pig FTO gene, among which some are associated with selected fat-deposition traits in F2 crosses and commercial populations. In this study, using both commercial pig populations and an experimental Meishan × Pietrain F2 population, we have investigated the association between one FTO SNP and several growth and carcass traits. Association analyses were performed with the FTO polymorphism either alone or in combination with polymorphisms in flanking loci.MethodsSNP (FM244720:g.400C>G) in exon 3 of porcine FTO was genotyped by PCR-RFLP and tested for associations with some growth, carcass and fat-related traits. Proportions of genetic variance of four pig chromosome 6 genes (FTO, RYR1, LIPE and TGFB1) on selected traits were evaluated using single- and multi-locus models.ResultsLinkage analysis placed FTO on the p arm of pig chromosome 6, approximately 22 cM from RYR1. In the commercial populations, allele C of the FTO SNP was significantly associated with back fat depth and allele G with muscling traits. In the Meishan × Pietrain F2 pigs, heterozygotes with allele C from the Pietrain sows and allele G from the Meishan boar were more significantly associated with fat-related traits compared to homozygotes with allele G from the Pietrain and allele G from the Meishan breed. In single- and multi-locus models, genes RYR1, TGFB1 and FTO showed high associations. The contribution in genetic variance from the polymorphism in the FTO gene was highest for back fat depth, meat area on the musculus longissimus lumborum et thoracis tissues and metabolite glucose-6-phosphate dehydrogenase.ConclusionsOur results show that in pig, FTO influences back fat depth in the commercial populations, while in the Meishan × Pietrain F2 pigs with a CG genotype, heterosis occurs for several fat-related traits.

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Mendel's pea crosses: varieties, traits and statistics.

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