QTL analysis allowed the mapping of 36 significant QTL for 19 agronomic traits, including internode length, peduncle length and biomass dry weight. The intraspecific map covered 608.3 cM over 21 linkage groups and included 29 SSR and 209 microarray-based DArT markers, with marker-marker distances ranging between 0 cM and 10.1 cM. (2016) reported the construction of the first intraspecific genetic map using an F 3 segregating population derived from a cross between genotypes derived from two domesticated landraces, Tiga Nicuru and DipC. A quantitative trait loci (QTL) analysis localised four QTL controlling 100-seed weight, specific leaf area, number of stem per plant and carbon (Delta C 13) isotope discrimination through the use of this interspecific genetic map. Twenty linkage groups were identified using 67 AFLP (Amplified Fragment Length Polymorphism) markers and one SSR (Simple Sequence Repeat) marker, giving a total length of 516 cM (centimorgan), with the inter-marker distance varying from 4.7 cM to 32 cM. using an F 2 segregating population derived from a controlled cross between an ancestral wild-type (VSSP11) and the domesticated form (a genotype derived from the DipC landrace) of bambara groundnut on the basis of differences observed in growth habit, maturity and yield performance. The first genetic map in bambara groundnut (2 n = 2 x = 22) was reported by Basu et al. Genetic maps can assist with conserved synteny mapping, where markers can be located in the species of origin and comparisons made with the species where greater resources and trait knowledge exist. A genetic map facilitates the identification of important gene-containing regions prior to positional cloning or the use of flanking markers for marker-assisted selection (MAS) in breeding programmes. To understand the genetic architecture of bambara groundnut for breeding purposes, it is useful to develop a high density genetic linkage map. The present GEM map in bambara groundnut provides one technically feasible route for the translation of information and resources from major and model plant species to underutilised and resource-poor crops. Of the QTL detected, 46% were detected in both control and drought treatment populations, suggesting that they are the result of intrinsic trait differences between the parental lines used to construct the cross, with 31% detected in only one of the conditions. From this initial map, a spaced expression marker-based genetic map consisting of 13 linkage groups containing 218 GEMs, spanning 982.7 cM (centimorgan) of the bambara groundnut genome, was developed. A total of 753 markers grouped at an LOD (Logarithm of odds) of three, with 527 markers mapped into linkage groups. The gene expression markers (GEMs) were generated at the (unmasked) probe-pair level after cross-hybridisation of bambara groundnut leaf RNA to the Affymetrix Soybean Genome GeneChip. The aim of the study was to identify quantitative trait loci (QTL) involved in agronomic and drought-related traits using an expression marker-based genetic map based on major crop resources developed in soybean. We conclude that integrating systems genetics to a more-traditional genetics approach improves the power of complex trait gene identification.Bambara groundnut ( Vigna subterranea (L.) Verdc.) is an underutilised legume crop, which has long been recognised as a protein-rich and drought-tolerant crop, used extensively in Sub-Saharan Africa. A combination of bioinformatics tools and systems genetics helped identify several candidate genes for both the chromosome 11 HDL and module QTL based on differential expression between the parental strains, cis regulation of expression, and causality modeling. Using weighted gene co-expression network analysis, we identified a module that after adjustment for Apoa2, correlated with HDL, was genetically determined by a QTL on chromosome 11, and overlapped with the HDL QTL. A novel nonsynonymous polymorphism supports Lipg as the QTL gene for the chromosome 18 QTL, and a difference in Abca1 expression in liver tissue supports it as the QTL gene for the chromosome 4 QTL. Quantitative trait loci (QTL) mapping revealed one significant HDL QTL ( Apoa2 locus), four suggestive QTL on chromosomes 10, 11, 13, and 18 and four additional QTL on chromosomes 1 proximal, 3, 4, and 7 after adjusting HDL for the strong Apoa2 locus. We searched for genetic loci influencing HDL-cholesterol in F2 mice from a cross between MRL/MpJ and SM/J mice. A higher incidence of coronary artery disease is associated with a lower level of HDL-cholesterol.

Using cdf files to identify genes