Pooled analysis of data from multiple quantitative trait locus mapping populations

Unveiling the Mysteries of Non-Mendelian Heredity in Plant Breeding

Mendelian heredity is the cornerstone of plant breeding and has been used to develop new varieties of plants since the 19th century. However, there are several breeding cases, such as cytoplasmic inheritance, methylation, epigenetics, hybrid vigor, and loss of heterozygosity (LOH), where Mendelian heredity is not applicable, known as non-Mendelian heredity. This type of inheritance can be influenced by several factors besides the genetic architecture of the plant and its breeding potential. Therefore, exploring various non-Mendelian heredity mechanisms, their prevalence in plants, and the implications for plant breeding is of paramount importance to accelerate the pace of crop improvement. In this review, we examine the current understanding of non-Mendelian heredity in plants, including the mechanisms, inheritance patterns, and applications in plant breeding, provide an overview of the various forms of non-Mendelian inheritance (including epigenetic inheritance, cytoplasmic inheritance, hybrid vigor, and LOH), explore insight into the implications of non-Mendelian heredity in plant breeding, and the potential it holds for future research.

Consensus genetic map and QTLs for morphological and agronomical traits in mungbean using DArT markers

Mungbean is an important but understudied food legume compared with other major grain crops. Genetic studies through development of high-through put markers, linkage map construction and QTL analysis can accelerate and improve the efficiency of mining for genes for breeding in this crop. This study used four mungbean F₅ recombinant inbred lines (RILs) from crosses of two wild types (ACC 1, ACC 87) and two cultivars (Berken, Kiloga) and DArT markers to construct individual and consensus linkage maps and to identify QTLs associated with 54 traits in mungbean. The number of polymorphic DArT markers identified among the four RIL populations varied from 1062 to 2013. The individual maps covered the lengths of 629.7-883.5 cM, comprising 672-981 DArT markers and 15-19 linkage groups (LG) with average distance between markers of 0.9-1.2 cM. The consensus map had the total length of 795.3 cM, comprising 1539 DArT markers and resolved 11 LGs with an average inter-marker distance of 0.65 cM. Sixty-two QTLs were identified for 39 traits across 10 LGs of the consensus map. Major QTLs were identified for two special traits, late flowering inherited from ACC 1 (6 QTLs, PVE of 11.2-29.9%) and perenniality inherited from ACC 87 (3 QTLs, PVE of 17.4-22.6%) in separate population analysis. Number of congruent QTLs across four mungbean populations and the consensus map was 18 for 13 traits. These results illustrated the high efficiency of DArT marker application in mungbean genetic dissection and suggested the future potential employment of identified QTLs for mungbean improvement.

Mapping of new quantitative trait loci for sudden death syndrome and soybean cyst nematode resistance in two soybean populations

KEY MESSAGE

Novel QTL conferring resistance to both the SDS and SCN was detected in two RIL populations. Dual resistant RILs could be used in breeding programs for developing resistant soybean cultivars. Soybean cultivars, susceptible to the fungus Fusarium virguliforme, which causes sudden death syndrome (SDS), and to the soybean cyst nematode (SCN) (Heterodera glycines), suffer yield losses valued over a billion dollars annually. Both pathogens may occur in the same production fields. Planting of cultivars genetically resistant to both pathogens is considered one of the most effective means to control the two pathogens. The objective of the study was to map quantitative trait loci (QTL) underlying SDS and SCN resistances. Two recombinant inbred line (RIL) populations were developed by crossing 'A95-684043', a high-yielding maturity group (MG) II line resistant to SCN, with 'LS94-3207' and 'LS98-0582' of MG IV, resistant to both F. virguliforme and SCN. Two hundred F7 derived recombinant inbred lines from each population AX19286 (A95-684043 × LS94-3207) and AX19287 (A95-684043 × LS98-0582) were screened for resistance to each pathogen under greenhouse conditions. Five hundred and eighty and 371 SNP markers were used for mapping resistance QTL in each population. In AX19286, one novel SCN resistance QTL was mapped to chromosome 8. In AX19287, one novel SDS resistance QTL was mapped to chromosome 17 and one novel SCN resistance QTL was mapped to chromosome 11. Previously identified additional SDS and SCN resistance QTL were also detected in the study. Lines possessing superior resistance to both pathogens were also identified and could be used as germplasm sources for breeding SDS- and SCN-resistant soybean cultivars.

How do the type of QTL effect and the form of the residual term influence QTL detection in multi-parent populations? A case study in the maize EU-NAM population

In the QTL analysis of multi-parent populations, the inclusion of QTLs with various types of effects can lead to a better description of the phenotypic variation and increased power. For the type of QTL effect in QTL models for multi-parent populations (MPPs), various options exist to define them with respect to their origin. They can be modelled as referring to close parental lines or to further away ancestral founder lines. QTL models for MPPs can also be characterized by the homo- or heterogeneity of variance for polygenic effects. The most suitable model for the origin of the QTL effect and the homo- or heterogeneity of polygenic effects may be a function of the genetic distance distribution between the parents of MPPs. We investigated the statistical properties of various QTL detection models for MPPs taking into account the genetic distances between the parents of the MPP. We evaluated models with different assumptions about the QTL effect and the form of the residual term using cross validation. For the EU-NAM data, we showed that it can be useful to mix in the same model QTLs with different types of effects (parental, ancestral, or bi-allelic). The benefit of using cross-specific residual terms to handle the heterogeneity of variance was less obvious for this particular data set.

Yield QTLome distribution correlates with gene density in maize

The genetic control of yield and related traits in maize has been addressed by many quantitative trait locus (QTL) studies, which have produced a wealth of QTL information, also known as QTLome. In this study, we assembled a yield QTLome database and carried out QTL meta-analysis based on 44 published studies, representing 32 independent mapping populations and 49 parental lines. A total of 808 unique QTLs were condensed to 84 meta-QTLs and were projected on the 10 maize chromosomes. Seventy-four percent of QTLs showed a proportion of phenotypic variance explained (PVE) smaller than 10% confirming the high genetic complexity of grain yield. Yield QTLome projection on the genetic map suggested pericentromeric enrichment of QTLs. Conversely, pericentromeric depletion of QTLs was observed when the physical map was considered, suggesting gene density as the main driver of yield QTL distribution on chromosomes. Dominant and overdominant yield QTLs did not distribute differently from additive effect QTLs.

Family-based association mapping in crop species

Identification of allelic variants associated with complex traits provides molecular genetic information associated with variability upon which both artificial and natural selections are based. Family-based association mapping (FBAM) takes advantage of linkage disequilibrium among segregating progeny within crosses and among parents to provide greater power than association mapping and greater resolution than linkage mapping. Herein, we discuss the potential adaption of human family-based association tests and quantitative transmission disequilibrium tests for use in crop species. The rapid technological advancement of next generation sequencing will enable sequencing of all parents in a planned crossing design, with subsequent imputation of genotypes for all segregating progeny. These technical advancements are easily adapted to mating designs routinely used by plant breeders. Thus, FBAM has the potential to be widely adopted for discovering alleles, common and rare, underlying complex traits in crop species.

Nested association mapping for identification of functional markers

Identification of functional markers (FMs) provides information about the genetic architecture underlying complex traits. An approach that combines the strengths of linkage and association mapping, referred to as nested association mapping (NAM), has been proposed to identify FMs in many plant species. The ability to identify and resolve FMs for complex traits depends upon a number of factors including frequency of FM alleles, magnitudes of their genetic effects, disequilibrium among functional and nonfunctional markers, statistical analysis methods, and mating design. The statistical characteristics of power, accuracy, and precision to identify FMs with a NAM population were investigated using three simulation studies. The simulated data sets utilized publicly available genetic sequences and simulated FMs were identified using least-squares variable selection methods. Results indicate that FMs with simple additive genetic effects that contribute at least 5% to the phenotypic variability in at least five segregating families of a NAM population consisting of recombinant inbred progeny derived from 28 matings with a single reference inbred will have adequate power to accurately and precisely identify FMs. This resolution and power are possible even for genetic architectures consisting of disequilibrium among multiple functional and nonfunctional markers in the same genomic region, although the resolution of FMs will deteriorate rapidly if more than two FMs are tightly linked within the same amplicon. Finally, nested mating designs involving several reference parents will have a greater likelihood of resolving FMs than single reference designs.

A combined-cross analysis reveals genes with drug-specific and background-dependent effects on drug sensitivity in Saccharomyces cerevisiae

Effective pharmacological therapy is often inhibited by variable drug responses and adverse drug reactions. Dissecting the molecular basis of different drug responses is difficult due to complex interactions involving multiple genes, pathways, and cellular processes. We previously found a single nucleotide polymorphism within cystathionine beta-synthase (CYS4) that causes multi-drug sensitivity in a vineyard strain of Saccharomyces cerevisiae. However, not all variation was accounted for by CYS4. To identify additional genes influencing drug sensitivity, we used CYS4 as a covariate and conducted both single- and combined-cross linkage mapping. After eliminating numerous false-positive associations, we identified 16 drug-sensitivity loci, only 3 of which had been previously identified. Of 4 drug-sensitivity loci selected for validation, 2 showed replicated associations in independent crosses, and two quantitative trait genes within these regions, AQY1 and MKT1, were found to have drug-specific and background-dependent effects. Our results suggest that drug response may often depend on interactions between genes with multi-drug and drug-specific effects.