Minor-effect Loci Research Articles

Mapping the genetic basis for sex determination and growth in hybrid tilapia (Oreochromis mossambicus × O. niloticus)

Tilapia growth and sex are key traits for aquaculture. Elucidating their molecular mechanisms can enable molecular breeding and accelerate genetic gain. To uncover the genetic basis underlying these traits for molecular breeding, we generated an F2 family by crossing Mozambique and Nile tilapia. The growth and sex traits of 284 F2 fish were recorded at 150 days post hatch. These F2 individuals exhibited sexual dimorphism in weight, body shape, and lip thickness, and were genotyped with RAD-sequencing. A high-density linkage map, consisting of 22 linkage groups with 38,102 SNPs was constructed. Association mapping revealed that QTL containing the amhy gene from male Nile tilapia largely determined sex, modulated by minor-effect loci. For growth-related traits, QTL and association analyses discovered that body weight or total length was predominantly controlled by a large-effect locus, while body shape was determined by several minor-effect loci. Analysis of transcriptomics in the liver and muscle identified novel candidate genes, including dusp2, rtn4r, bhmt1, adamts12 and s100p, for growth. These findings provide tools for sex-specific molecular breeding and valuable information for understanding the genomic architecture of growth and body shape variation. Assessing the sex-specific effects on growth can further refine selective breeding in aquaculture.

Genetic analysis of late-maturity α-amylase in twelve wheat populations

Main conclusionGenetic loci, particularly those with an effect in the independent panel, could be utilised to further reduce LMA expression when used with favourable combinations of genes known to affect LMA.Late maturity α-amylase (LMA) is a grain quality defect involving elevated α-amylase within the aleurone of wheat (Triticum aestivum L.) grains. The genes known to affect expression are the reduced height genes Rht-B1 (chromosome 4B) and Rht-D1 (chromosome 4D), and an ent-copalyl diphosphate synthase gene (LMA-1) on chromosome 7B. Other minor effect loci have been reported, but these are poorly characterised and further genetic understanding is needed. In this study, twelve F4-derived populations were created through single seed descent, genotyped and evaluated for LMA. LMA-1 haplotype C and the Rht-D1b allele substantially reduced LMA expression. The alternative dwarfing genes Rht13 and Rht18 had no significant effect on LMA expression. Additional quantitative trait loci (QTL) were mapped at 16 positions in the wheat genome. Effects on LMA expression were detected for four of these QTL in a large independent panel of Australian wheat lines. The QTL detected in mapping populations and confirmed in the large independent panel provide further opportunity for selection against LMA, especially if combined with Rht-D1b and/or favourable haplotypes of LMA-1.

Genome-wide association study reveals GmFulb as candidate gene for maturity time and reproductive length in soybeans (Glycine max).

The ability of soybean [Glycine max (L.) Merr.] to adapt to different latitudes is attributed to genetic variation in major E genes and quantitative trait loci (QTLs) determining flowering time (R1), maturity (R8), and reproductive length (RL). Fully revealing the genetic basis of R1, R8, and RL in soybeans is necessary to enhance genetic gains in soybean yield improvement. Here, we performed a genome-wide association analysis (GWA) with 31,689 single nucleotide polymorphisms (SNPs) to detect novel loci for R1, R8, and RL using a soybean panel of 329 accessions with the same genotype for three major E genes (e1-as/E2/E3). The studied accessions were grown in nine environments and observed for R1, R8 and RL in all environments. This study identified two stable peaks on Chr 4, simultaneously controlling R8 and RL. In addition, we identified a third peak on Chr 10 controlling R1. Association peaks overlap with previously reported QTLs for R1, R8, and RL. Considering the alternative alleles, significant SNPs caused RL to be two days shorter, R1 two days later and R8 two days earlier, respectively. We identified association peaks acting independently over R1 and R8, suggesting that trait-specific minor effect loci are also involved in controlling R1 and R8. From the 111 genes highly associated with the three peaks detected in this study, we selected six candidate genes as the most likely cause of R1, R8, and RL variation. High correspondence was observed between a modifying variant SNP at position 04:39294836 in GmFulb and an association peak on Chr 4. Further studies using map-based cloning and fine mapping are necessary to elucidate the role of the candidates we identified for soybean maturity and adaptation to different latitudes and to be effectively used in the marker-assisted breeding of cultivars with optimal yield-related traits.

Low-coverage sequencing in a deep intercross of the Virginia body weight lines provides insight to the polygenic genetic architecture of growth: novel loci revealed by increased power and improved genome-coverage

Genetic dissection of highly polygenic traits is a challenge, in part due to the power necessary to confidently identify loci with minor effects. Experimental crosses are valuable resources for mapping such traits. Traditionally, genome-wide analyses of experimental crosses have targeted major loci using data from a single generation (often the F2) with individuals from later generations being generated for replication and fine-mapping. Here, we aim to confidently identify minor-effect loci contributing to the highly polygenic basis of the long-term, bi-directional selection responses for 56-d body weight in the Virginia body weight chicken lines. To achieve this, a strategy was developed to make use of data from all generations (F2-F18) of the advanced intercross line, developed by crossing the low and high selected lines after 40 generations of selection. A cost-efficient low-coverage sequencing based approach was used to obtain high-confidence genotypes in 1Mb bins across 99.3% of the chicken genome for >3,300 intercross individuals. In total, 12 genome-wide significant, and 30 additional suggestive QTL reaching a 10% FDR threshold, were mapped for 56-d body weight. Only 2 of these QTL reached genome-wide significance in earlier analyses of the F2 generation. The minor-effect QTL mapped here were generally due to an overall increase in power by integrating data across generations, with contributions from increased genome-coverage and improved marker information content. The 12 significant QTL explain >37% of the difference between the parental lines, three times more than 2 previously reported significant QTL. The 42 significant and suggestive QTL together explain >80%. Making integrated use of all available samples from multiple generations in experimental crosses are economically feasible using the low-cost, sequencing-based genotyping strategies outlined here. Our empirical results illustrate the value of this strategy for mapping novel minor-effect loci contributing to complex traits to provide a more confident, comprehensive view of the individual loci that form the genetic basis of the highly polygenic, long-term selection responses for 56-d body weight in the Virginia body weight chicken lines.

Genome-Wide Association Mapping Indicates Quantitative Genetic Control of Spot Blotch Resistance in Bread Wheat and the Favorable Effects of Some Spot Blotch Loci on Grain Yield.

Spot blotch caused by the fungus Bipolaris sorokiniana poses a serious threat to bread wheat production in warm and humid wheat-growing regions of the world. Hence, the major objective of this study was to identify consistent genotyping-by-sequencing (GBS) markers associated with spot blotch resistance using genome-wide association mapping on a large set of 6,736 advanced bread wheat breeding lines from the International Maize and Wheat Improvement Center. These lines were phenotyped as seven panels at Agua Fria, Mexico between the 2013–2014 and 2019–2020 crop cycles. We identified 214 significant spot blotch associated GBS markers in all the panels, among which only 96 were significant in more than one panel, indicating a strong environmental effect on the trait and highlights the need for multiple phenotypic evaluations to identify lines with stable spot blotch resistance. The 96 consistent GBS markers were on chromosomes 1A, 1B, 1D, 2A, 3B, 4A, 5B, 5D, 6B, 7A, 7B, and 7D, including markers possibly linked to the Lr46, Sb1, Sb2 and Sb3 genes. We also report the association of the 2NS translocation from Aegilops ventricosa with spot blotch resistance in some environments. Moreover, the spot blotch favorable alleles at the 2NS translocation and two markers on chromosome 3BS (3B_2280114 and 3B_5601689) were associated with increased grain yield evaluated at several environments in Mexico and India, implying that selection for favorable alleles at these loci could enable simultaneous improvement for high grain yield and spot blotch resistance. Furthermore, a significant relationship between the percentage of favorable alleles in the lines and their spot blotch response was observed, which taken together with the multiple minor effect loci identified to be associated with spot blotch in this study, indicate quantitative genetic control of resistance. Overall, the results presented here have extended our knowledge on the genetic basis of spot blotch resistance in bread wheat and further efforts to improve genetic resistance to the disease are needed for reducing current and future losses under climate change.

Identification and Validation of a Novel Major QTL Controlling Leaf Pubescence in the Chinese Wheat Landrace ‘Baimaomai’

Leaf pubescence is an important trait closely associated with plant adaptability to specialized habitats. Baimaomai (BMM) is a wheat (Triticum aestivum L.) landrace originating from the high-altitude, drought-prone environment of Sichuan Province, China with long, dense leaf pubescence. A population of 234 recombinant inbred lines (F10) developed from the cross between Chuanmai104 (CM104), which lacks leaf pubescence, and BMM with pubescent leaves, was used to conduct a phenotypic evaluation of leaf pubescence. Three quantitative trait loci (QTLs) were detected on chromosome arms 7BS, 3DL and 3AL using a high-density wheat 50K single-nucleotide polymorphism array in four environments. The QTLs were designated QLp.saas-7BS, QLp.saas-3DL and QLp.saas-3AL. QLp.saas-3AL, derived from BMM, and QLp.saas-3DL, derived from CM104, were new minor-effect loci. QLp.saas-7BS, derived from BMM, was a novel major-effect locus detected in all environments and was localized in a 0.48 Mb interval on chromosome arm 7BS based on the wheat ‘Chinese Spring’ reference genome. QLp.saas-7BS explained up to 40.77% of the total phenotypic variance. KASP markers tightly linked to QLp.saas-7BS were developed and verified. The present results provide valuable information for further fine mapping, cloning, and marker-assisted selection with QLp.saas-7BS in wheat.

Mapping quantitative trait loci associated with stripe rust resistance from the Canadian wheat cultivar ‘AAC Innova’

Stripe rust, caused by Puccinia striiformis Westend. f.sp. tritici Erikss. (Pst), is one of the most devastating diseases of wheat (Triticum aestivum L.) globally. Exploring and utilizing new sources of resistance is essential for breeding resistant wheat cultivars. Thus, a doubled haploid population (n = 291) derived from the cross ‘AAC Innova’/‘AAC Proclaim’ was evaluated to dissect the genetics of resistance in the cultivar ‘AAC Innova’. This population was evaluated for stripe rust severity in disease nurseries at Creston, British Columbia (in 2016 and 2020), and Lethbridge, Alberta (in 2016, 2017 and 2020), and genotyped using the wheat 90 K SNP assay. A high-density genetic map was constructed which consisted of 7112 SNP markers with an average marker interval of 2.3 cM. Quantitative trait loci (QTL) mapping identified one major (QYr.lrdc-2A) and 10 minor effect (QYr.lrdc-2B.1, QYr.lrdc-2B.2, QYr.lrdc-2B.3, QYr.lrdc-2B.4, QYr.lrdc-2D, QYr.lrdc-3B, QYr.lrdc-5A, QYr.lrdc-5B, QYr.lrdc-5D and QYr.lrdc-7D) loci. The QTL QYr.lrdc-2A was consistently effective against Pst races across all environments and explained up to 33.0% of the phenotypic variation. Other QTLs were either less consistent or environment specific. ‘AAC Innova’ contributed stripe rust resistance alleles for most of the QTLs except for QYr.lrdc-2D, QYr.lrdc-5A and QYr.lrdc-7D. The QTLs identified in this study should be valuable for diversifying the sources of genetic resistance against current and new virulent races of Pst. In particular, the ‘AAC Innova’-derived QTL QYr.lrdc-2A could be a valuable source of resistance to incorporate into commercial cultivars and combine with other genes using the associated SNP markers identified in this study.

Genome-wide association study and Mendelian randomization analysis provide insights for improving rice yield potential

Rice yield per plant has a complex genetic architecture, which is mainly determined by its three component traits: the number of grains per panicle (GPP), kilo-grain weight (KGW), and tillers per plant (TP). Exploring ideotype breeding based on selection for genetically less complex component traits is an alternative route for further improving rice production. To understand the genetic basis of the relationship between rice yield and component traits, we investigated the four traits of two rice hybrid populations (575 + 1495 F1) in different environments and conducted meta-analyses of genome-wide association study (meta-GWAS). In total, 3589 significant loci for three components traits were detected, while only 3 loci for yield were detected. It indicated that rice yield is mainly controlled by minor-effect loci and hardly to be identified. Selecting quantitative trait locus/gene affected component traits to further enhance yield is recommended. Mendelian randomization design is adopted to investigate the genetic effects of loci on yield through component traits and estimate the genetic relationship between rice yield and its component traits by these loci. The loci for GPP or TP mainly had a positive genetic effect on yield, but the loci for KGW with different direction effects (positive effect or negative effect). Additionally, TP (Beta = 1.865) has a greater effect on yield than KGW (Beta = 1.016) and GPP (Beta = 0.086). Five significant loci for component traits that had an indirect effect on yield were identified. Pyramiding superior alleles of the five loci revealed improved yield. A combination of direct and indirect effects may better contribute to the yield potential of rice. Our findings provided a rationale for using component traits as indirect indices to enhanced rice yield, which will be helpful for further understanding the genetic basis of yield and provide valuable information for improving rice yield potential.

A novel deletion in FLOWERING LOCUS T modulates flowering time in winter oilseed rape

Key messageA novel structural variant was discovered in the FLOWERING LOCUS T orthologue BnaFT.A02 by long-read sequencing. Nested association mapping in an elite winter oilseed rape population revealed that this 288 bp deletion associates with early flowering, putatively by modification of binding-sites for important flowering regulation genes.Perfect timing of flowering is crucial for optimal pollination and high seed yield. Extensive previous studies of flowering behavior in Brassica napus (canola, rapeseed) identified mutations in key flowering regulators which differentiate winter, semi-winter and spring ecotypes. However, because these are generally fixed in locally adapted genotypes, they have only limited relevance for fine adjustment of flowering time in elite cultivar gene pools. In crosses between ecotypes, the ecotype-specific major-effect mutations mask minor-effect loci of interest for breeding. Here, we investigated flowering time in a multiparental mapping population derived from seven elite winter oilseed rape cultivars which are fixed for major-effect mutations separating winter-type rapeseed from other ecotypes. Association mapping revealed eight genomic regions on chromosomes A02, C02 and C03 associating with fine modulation of flowering time. Long-read genomic resequencing of the seven parental lines identified seven structural variants coinciding with candidate genes for flowering time within chromosome regions associated with flowering time. Segregation patterns for these variants in the elite multiparental population and a diversity set of winter types using locus-specific assays revealed significant associations with flowering time for three deletions on chromosome A02. One of these was a previously undescribed 288 bp deletion within the second intron of FLOWERING LOCUS T on chromosome A02, emphasizing the advantage of long-read sequencing for detection of structural variants in this size range. Detailed analysis revealed the impact of this specific deletion on flowering-time modulation under extreme environments and varying day lengths in elite, winter-type oilseed rape.

Interactions Among Multiple Quantitative Trait Loci Underlie Rhizome Development of Perennial Rice.

Perennial crops have some advantages over annuals in soil erosion prevention, lower labor and water requirements, carbon sequestration, and maintenance of thriving soil ecosystems. Rhizome, a kind of root-like underground stem, is a critical component of perenniality, which allows many grass species to survive through harsh environment. Identification of rhizome-regulating genes will contribute to the development of perennial crops. There have been no reports on the cloning of such genes until now, which bring urgency for identification of genes controlling rhizomatousness. Using rhizomatous Oryza longistaminata and rhizome-free cultivated rice as male and female parents, respectively, genetic populations were developed to identify genes regulating rhizome. Both entire population genotyping and selective genotyping mapping methods were adopted to detect rhizome-regulating quantitative trait loci (QTL) in 4 years. Results showed that multiple genes regulated development of rhizomes, with over 10 loci related to rhizome growth. At last, five major-effect loci were identified including qRED1.2, qRED3.1, qRED3.3, qRED4.1, and qRED4.2. It has been found that the individual plant with well-developed rhizomes carried at least three major-effect loci and a certain number of minor-effect loci. Both major-effect and minor-effect loci worked together to control rhizome growth, while no one could work alone. These results will provide new understanding of genetic regulation on rhizome growth and reference to the subsequent gene isolation in rice. And the related research methods and results in this study will contribute to the research on rhizome of other species.

Construction of a dense genetic map of the Malus fusca fire blight resistant accession MAL0045 using tunable genotyping-by-sequencing SNPs and microsatellites

Although, the Pacific crabapple, Malus fusca, is a hardy and disease resistant species, studies relating to the genetics of its unique traits are very limited partly due to the lack of a genetic map of this interesting wild apple. An accession of M. fusca (MAL0045) of Julius Kühn-Institut collection in Germany is highly resistant to fire blight disease, incited by different strains of the causative pathogen—Erwinia amylovora. This is the most destructive bacterial disease of Malus of which most of the domesticated apples (Malus domestica) are susceptible. Using a scarcely dense genetic map derived from a population of 134 individuals of MAL0045 × ‘Idared’, the locus (Mfu10) controlling fire blight resistance mapped on linkage group 10 (LG10) and explained up to 66% of the phenotypic variance with different strains. Although the development of robust and tightly linked molecular markers on LG10 through chromosome walking approach led to the identification of a major candidate gene, any minor effect locus remained elusive possibly due to the lack of marker density of the entire genetic map. Therefore, we have developed a dense genetic map of M. fusca using tunable genotyping-by-sequencing (tGBS) approach. Of thousands of de novo SNPs identified, 2677 were informative in M. fusca and 90.5% of these successfully mapped. In addition, integration of SNP data and microsatellite (SSR) data resulted in a final map comprising 17 LGs with 613 loci spanning 1081.35 centi Morgan (cM). This map will serve as a template for mapping using different strains of the pathogen.

A Hitchhiker\u2019s guide to the potato wart disease resistance galaxy

Key messageTwo novel major effect loci (Sen4 and Sen5) and several minor effect QTLs for potato wart disease resistance have been mapped. The importance of minor effect loci to bring full resistance to wart disease was investigated. Using the newly identified and known wart disease resistances, a panel of potato breeding germplasm and Solanum wild species was screened. This provided a state-of-the-art “hitch-hikers-guide” of complementary wart disease resistance sources.Potato wart disease, caused by the obligate biotrophic soil-born fungus Synchytrium endobioticum, is the most important quarantine disease of potato. Because of its huge impact on yield, the lack of chemical control and the formation of resting spores with long viability, breeding for resistant varieties combined with strict quarantine measures are the only way to efficiently and durably manage the disease. In this study, we set out to make an inventory of the different resistance sources. Using a Genome-Wide Association Study (GWAS) in the potato breeding genepool, we identified Sen4, associated with pathotypes 2, 6 and 18 resistance. Associated SNPs mapped to the south arm of chromosome 12 and were validated to be linked to resistance in one full-sib population. Also, a bulked segregant analysis combined with a Comparative Subsequence Sets Analysis (CoSSA) resulted in the identification of Sen5, associated with pathotypes 2, 6 and 18 resistance, on the south arm of chromosome 5. In addition to these two major effect loci, the GWAS and CoSSA allowed the identification of several quantitative trait loci necessary to bring full resistance to certain pathotypes. Panels of varieties and Solanum accessions were screened for the presence of Sen1, Sen2, Sen3, Sen4 and Sen5. Combined with pedigree analysis, we could trace back some of these genes to the ancestral resistance donors. This analysis revealed complementary resistance sources and allows elimination of redundancy in wart resistance breeding programs.

A Genome-Wide Association Study for Resistance to the Insect Pest Leptocybe invasa in Eucalyptus grandis Reveals Genomic Regions and Positional Candidate Defense Genes.

The galling insect, Leptocybe invasa, causes significant losses in plantations of various Eucalyptus species and hybrids, threatening its economic viability. We applied a genome-wide association study (GWAS) to identify single-nucleotide polymorphism (SNP) markers associated with resistance to L. invasa. A total of 563 insect-challenged Eucalyptus grandis trees, from 61 half-sib families, were genotyped using the EUChip60K SNP chip, and we identified 15,445 informative SNP markers in the test population. Multi-locus mixed-model (MLMM) analysis identified 35 SNP markers putatively associated with resistance to L. invasa based on four discreet classes of insect damage scores: (0) not infested, (1) infested showing evidence of oviposition but no gall development, (2) infested with galls on leaves, midribs or petioles and (3) stunting and lethal gall formation. MLMM analysis identified three associated genomic regions on chromosomes 3, 7 and 8 jointly explaining 17.6% of the total phenotypic variation. SNP analysis of a validation population of 494 E. grandis trees confirmed seven SNP markers that were also detected in the initial association analysis. Based on transcriptome profiles of resistant and susceptible genotypes from an independent experiment, we identified several putative candidate genes in associated genomic loci including Nucleotide-binding ARC- domain (NB-ARC) and toll-interleukin-1-receptor-Nucleotide binding signal- Leucine rich repeat (TIR-NBS-LRR) genes. Our results suggest that Leptocybe resistance in E. grandis may be influenced by a few large-effect loci in combination with minor effect loci segregating in our test and validation populations.

Comparative Subsequence Sets Analysis (CoSSA) is a robust approach to identify haplotype specific SNPs; mapping and pedigree analysis of a potato wart disease resistance gene Sen3

BackgroundStandard strategies to identify genomic regions involved in a specific trait variation are often limited by time and resource consuming genotyping methods. Other limiting pre-requisites are the phenotyping of large segregating populations or of diversity panels and the availability and quality of a closely related reference genome. To overcome these limitations, we designed efficient Comparative Subsequence Sets Analysis (CoSSA) workflows to identify haplotype specific SNPs linked to a trait of interest from Whole Genome Sequencing data.ResultsAs a model, we used the resistance to Synchytrium endobioticum pathotypes 2, 6 and 18 that co-segregated in a tetraploid full sib population. Genomic DNA from both parents, pedigree genotypes, unrelated potato varieties lacking the wart resistance traits and pools of resistant and susceptible siblings were sequenced. Set algebra and depth filtering of subsequences (k-mers) were used to delete unlinked and common SNPs and to enrich for SNPs from the haplotype(s) harboring the resistance gene(s). Using CoSSA, we identified a major and a minor effect locus. Upon comparison to the reference genome, it was inferred that the major resistance locus, referred to as Sen3, was located on the north arm of chromosome 11 between 1,259,552 and 1,519,485 bp. Furthermore, we could anchor the unanchored superscaffold DMB734 from the potato reference genome to a synthenous interval. CoSSA was also successful in identifying Sen3 in a reference genome independent way thanks to the de novo assembly of paired end reads matching haplotype specific k-mers. The de novo assembly provided more R haplotype specific polymorphisms than the reference genome corresponding region. CoSSA also offers possibilities for pedigree analysis. The origin of Sen3 was traced back until Ora. Finally, the diagnostic power of the haplotype specific markers was shown using a panel of 56 tetraploid varieties.ConclusionsCoSSA is an efficient, robust and versatile set of workflows for the genetic analysis of a trait of interest using WGS data. Because the WGS data are used without intermediate reads mapping, CoSSA does not require the use of a reference genome. This approach allowed the identification of Sen3 and the design of haplotype specific, diagnostic markers.

Genetic architecture of maize chlorotic mottle virus and maize lethal necrosis through GWAS, linkage analysis and genomic prediction in tropical maize germplasm

Key messageAnalysis of the genetic architecture of MCMV and MLN resistance in maize doubled-haploid populations revealed QTLs with major effects on chromosomes 3 and 6 that were consistent across genetic backgrounds and environments. Two major-effect QTLs, qMCMV3-108/qMLN3-108 and qMCMV6-17/qMLN6-17, were identified as conferring resistance to both MCMV and MLN.Maize lethal necrosis (MLN) is a serious threat to the food security of maize-growing smallholders in sub-Saharan Africa. The ability of the maize chlorotic mottle virus (MCMV) to interact with other members of the Potyviridae causes severe yield losses in the form of MLN. The objective of the present study was to gain insights and validate the genetic architecture of resistance to MCMV and MLN in maize. We applied linkage mapping to three doubled-haploid populations and a genome-wide association study (GWAS) on 380 diverse maize lines. For all the populations, phenotypic variation for MCMV and MLN was significant, and heritability was moderate to high. Linkage mapping revealed 13 quantitative trait loci (QTLs) for MCMV resistance and 12 QTLs conferring MLN resistance. One major-effect QTL, qMCMV3-108/qMLN3-108, was consistent across populations for both MCMV and MLN resistance. Joint linkage association mapping (JLAM) revealed 18 and 21 main-effect QTLs for MCMV and MLN resistance, respectively. Another major-effect QTL, qMCMV6-17/qMLN6-17, was detected for both MCMV and MLN resistance. The GWAS revealed a total of 54 SNPs (MCMV-13 and MLN-41) significantly associated (P ≤ 5.60 × 10−05) with MCMV and MLN resistance. Most of the GWAS-identified SNPs were within or adjacent to the QTLs detected through linkage mapping. The prediction accuracy for within populations as well as the combined populations is promising; however, the accuracy was low across populations. Overall, MCMV resistance is controlled by a few major and many minor-effect loci and seems more complex than the genetic architecture for MLN resistance.

Exploring differentially expressed genes associated with fertility instability of S-type cytoplasmic male-sterility in maize by RNA-seq

AbstractThe germplasm resources for the S-type male sterility is rich in maize and it is resistant to Bipolaris maydis race T and CI, but the commercial application of S-type cytoplasmic male sterility (CMS-S) in maize hybrid industry is greatly compromised because of its common fertility instability. Currently, the existence of multiple minor effect loci in specific nuclear genetic backgrounds was considered as the molecular mechanism for this phenomenon. In the present study, we evaluated the fertility segregation of the different populations with the fertility instable material FIL-H in two environments of Beijing and Hainan, China. Our results indicated that the fertility instability of FIL-H was regulated by multiple genes, and the expression of these genes was sensitive to environmental factors. Using RNA sequencing (RNA-seq) technology, transcriptomes of the sterile plants and partially fertile plants resulted from the backcross of FIL-H×Jing 724 in Hainan were analyzed and 2 108 genes with different expression were identified, including 1 951 up-regulated and 157 down-regulated genes. The cluster analysis indicated that these differentially expressed genes (DEGs) might play roles in many biological processes, such as the energy production and conversion, carbohydrate metabolism and signal transduction. In addition, the pathway of the starch and sucrose metabolism was emphatically investigated to reveal the DEGs during the process of starch biosynthesis between sterile and partially fertile plants, which were related to the key catalytic enzymes, such as ADP-G pyrophosphorylase, starch synthase and starch branching enzyme. The up-regulation of these genes in the partially fertile plant may promote the starch accumulation in its pollen. Our data provide the important theoretical basis for the further exploration of the molecular mechanism for the fertility instability in CMS-S maize.

Systems genetics reveals key genetic elements of drought induced gene regulation in diploid potato.

In plants, tolerance to drought stress is a result of numerous minor effect loci in which transcriptional regulation contributes significantly to the observed phenotypes. Under severe drought conditions, a major expression quantitative trait loci hotspot was identified on chromosome five in potato. A putative Nuclear factor y subunit C4 was identified as key candidate in the regulatory cascade in response to drought. Further investigation of the eQTL hotspots suggests a role for a putative Homeobox leucine zipper protein 12 in relation to drought in potato. Genes strongly co-expressed with Homeobox leucine zipper protein 12 were plant growth regulators responsive to water deficit stress in Arabidopsis thaliana, implying a possible conserved mechanism. Integrative analysis of genetic, genomic, phenotypic and transcriptomic data provided insights in the downstream functional components of the drought response. The abscisic acid- and environmental stress-inducible protein TAS14 was highly induced by severe drought in potato and acts as a reliable biomarker for the level of stress perceived by the plant. The systems genetics approach supported a role for multiple genes responsive to severe drought stress of Solanum tuberosum. The combination of gene regulatory networks, expression quantitative trait loci mapping and phenotypic analysis proved useful for candidate gene selection.

Genome-wide association study, genomic prediction and marker-assisted selection for seed weight in soybean (Glycine max).

Key messageTwenty-two loci for soybean SW and candidate genes conditioning seed development were identified; and prediction accuracies of GS and MAS were estimated through cross-validation and validation with unrelated populations.Soybean (Glycine max) is a major crop for plant protein and oil production, and seed weight (SW) is important for yield and quality in food/vegetable uses of soybean. However, our knowledge of genes controlling SW remains limited. To better understand the molecular mechanism underlying the trait and explore marker-based breeding approaches, we conducted a genome-wide association study in a population of 309 soybean germplasm accessions using 31,045 single nucleotide polymorphisms (SNPs), and estimated the prediction accuracy of genomic selection (GS) and marker-assisted selection (MAS) for SW. Twenty-two loci of minor effect associated with SW were identified, including hotspots on Gm04 and Gm19. The mixed model containing these loci explained 83.4 % of phenotypic variation. Candidate genes with Arabidopsis orthologs conditioning SW were also proposed. The prediction accuracies of GS and MAS by cross-validation were 0.75–0.87 and 0.62–0.75, respectively, depending on the number of SNPs used and the size of training population. GS also outperformed MAS when the validation was performed using unrelated panels across a wide range of maturities, with an average prediction accuracy of 0.74 versus 0.53. This study convincingly demonstrated that soybean SW is controlled by numerous minor-effect loci. It greatly enhances our understanding of the genetic basis of SW in soybean and facilitates the identification of genes controlling the trait. It also suggests that GS holds promise for accelerating soybean breeding progress. The results are helpful for genetic improvement and genomic prediction of yield in soybean.Electronic supplementary materialThe online version of this article (doi:10.1007/s00122-015-2614-x) contains supplementary material, which is available to authorized users.

Microsatellite Variations of Elite Setaria Varieties Released during Last Six Decades in China.

Crop improvement is a multifaceted micro-evolutionary process, involving changes in breeding approaches, planting configurations and consumption preferences of human beings. Recent research has started to identify the specific genes or genomic regions correlate to improved agronomic traits, however, an apparent blank between the genetic structure of crop elite varieties and their improving histories in diverse modern breeding programs is still in existence. Foxtail millet (Setaria italica) was one of the earliest cereal crops to be domesticated and served as a staple crop for early civilizations in China, where it is still widely grown today. In the present trial, a panel of foxtail millet elite varieties, which were released in the last sixty years in different geographical regions of China, was characterized using microsatellite markers (SSRs). A clear separation of two subpopulations corresponding to the two eco-geographical regions of foxtail millet production in China was identified by the dataset, which also indicated that in more recently released elite varieties, large quantities of accessions have been transferred from spring-sowing to summer-sowing ecotypes, likely as a result of breeding response to planting configurations. An association mapping study was conducted to identify loci controlling traits of major agronomic interest. Furthermore, selective sweeps involved in improvement of foxtail millet were identified as multi-diverse minor effect loci controlling different agronomic traits during the long-term improvement of elite varieties. Our results highlight the effect of transition of planting configuration and breeding preference on genetic evolvement of crop species.

Genome-wide association mapping of phenotypic traits subject to a range of intensities of natural selection in Timema cristinae.

The genetic architecture of adaptive traits can reflect the evolutionary history of populations and also shape divergence among populations. Despite this central role in evolution, relatively little is known regarding the genetic architecture of adaptive traits in nature, particularly for traits subject to known selection intensities. Here we quantitatively describe the genetic architecture of traits that are subject to known intensities of differential selection between host plant species in Timema cristinae stick insects. Specifically, we used phenotypic measurements of 10 traits and 211,004 single-nucleotide polymorphisms (SNPs) to conduct multilocus genome-wide association mapping. We identified a modest number of SNPs that were associated with traits and sometimes explained a large proportion of trait variation. These SNPs varied in their strength of association with traits, and both major and minor effect loci were discovered. However, we found no relationship between variation in levels of divergence among traits in nature and variation in parameters describing the genetic architecture of those same traits. Our results provide a first step toward identifying loci underlying adaptation in T. cristinae. Future studies will examine the genomic location, population differentiation, and response to selection of the trait-associated SNPs described here.