High-density Genetic Map Research Articles

Chromosome-scale assembly and quantitative trait locus mapping for major economic traits of the Culter alburnus genome using Illumina and PacBio sequencing with Hi-C mapping information.

Topmouth culter (Culter alburnus) is an economically important freshwater fish with high nutritional value. However, its potential genetic advantages have not been fully exploited. Therefore, we aimed to determine the genome sequence of C. alburnus and examine quantitative trait loci (QTLs) related to major economic traits. The results showed that 24 pseudochromosomes were anchored by 914.74Mb of the C. alburnus genome sequence. De novo sequencing identified 31,279 protein-coding genes with an average length of 8507 bp and average coding sequ ence of 1115bp. In addition, a high-density genetic linkage map consisting of 24 linkage groups was constructed based on 353,532 high-quality single nucleotide polymorphisms and 4,710 bin markers. A total of 28 QTLs corresponding to 11 genes, 26 QTLs corresponding to 11 genes, and 12 QTLs corresponding to 5 genes were identified for sex, intermuscular spine number and body weight traits, respectively. In this study, we assembled an accurate and nearly complete genome of C. alburnus by combining Illumina, PacBio, and high-throughput Chromosome conformation capture (Hi-C) technologies. In addition, we identified QTLs that explained variances in intermuscular spine number, body weight, and sex differences in C. alburnus. These genetic markers or candidate genes associated with growth traits provide a basis for marker-assisted selection in C. alburnus.

New insight into the genetic basis of oil content based on noninvasive three-dimensional phenotyping and tissue-specific transcriptome in Brassica napus

BackgroundIncreasing seed oil content is the most important breeding goal in Brassica napus, and phenotyping is crucial to dissect its genetic basis in crops. To date, QTL mapping for oil content has been based on whole seeds, and the lipid distribution is far from uniform in different tissues of seeds in B. napus. In this case, the phenotype based on whole seeds was unable to sufficiently reveal the complex genetic characteristics of seed oil content.ResultsHere, the three-dimensional (3D) distribution of lipid was determined for B. napus seeds by magnetic resonance imaging (MRI) and 3D quantitative analysis, and ten novel oil content-related traits were obtained by subdividing the seeds. Based on a high-density genetic linkage map, 35 QTLs were identified for 4 tissues, the outer cotyledon (OC), inner cotyledon (IC), radicle (R) and seed coat (SC), which explained up to 13.76% of the phenotypic variation. Notably, 14 tissue-specific QTLs were reported for the first time, 7 of which were novel. Moreover, haplotype analysis showed that the favorable alleles for different seed tissues exhibited cumulative effects on oil content. Furthermore, tissue-specific transcriptomes revealed that more active energy and pyruvate metabolism influenced carbon flow in the IC, OC and R than in the SC at the early and middle seed development stages, thus affecting the distribution difference in oil content. Combining tissue-specific QTL mapping and transcriptomics, 86 important candidate genes associated with lipid metabolism were identified that underlie 19 unique QTLs, including the fatty acid synthesis rate-limiting enzyme-related gene CAC2, in the QTLs for OC and IC.ConclusionsThe present study provides further insight into the genetic basis of seed oil content at the tissue-specific level.

A major QTL identification and candidate gene analysis of watermelon fruit cracking using QTL-seq and RNA-seq.

Fruit cracking decreases the total production and the commercial value of watermelon. The molecular mechanisms of fruit cracking are unknown. In this study, 164 recombinant inbred lines (RILs) of watermelon, derived from the crossing of the WQ1 (cracking-sensitive) and WQ2 (cracking-tolerant) lines, were sequenced using specific length amplified fragment sequencing (SLAF-seq). A high-density genetic linkage map was constructed with 3,335 markers spanning 1,322.74 cM, at an average 0.40 cM across whole-genome flanking markers. The cracking tolerance capacity (CTC), depth of fruit cracking (DFC), rind thickness (RT), and rind hardness (RH) were measured for quantitative trait locus (QTL) analysis. Of the four traits analyzed, one major QTL with high phenotypic variation (41.04%-61.37%) was detected at 76.613-76.919 cM on chromosome 2, which contained 104 annotated genes. Differential gene expression analysis with RNA sequencing (RNA-seq) data between the two parents identified 4,508 differentially expressed genes (DEGs). Comparison of the genes between the QTL region and the DEGs obtained eight coexisting genes. Quantitative real-time PCR (qRT-PCR) analysis revealed that these genes were significant differentially expressed between the two parents. These results provide new insights into the identification of QTLs or genes and marker-assisted breeding in watermelon.

Major genetic locus with pleiotropismdetermined seed-related traits in cultivated and wild soybeans.

Here, a novel pleiotropic QTL qSS14 simultaneously regulating four seed size traits and two consistently detected QTLs qSW17 and qSLW02 were identified across multiple years. Seed-related traits were the key agronomic traits that have been artificially selected during the domestication of wild soybean. Identifying the genetic loci and genes that regulate seed size could clarify the genetic variations in seed-related traits and provide novel insights into high-yield soybean breeding. In this study, we used a high-density genetic map constructed by F10 RIL populations from a cross between Glycine max and Glycine soja to detect additive QTLs for seven seed-related traits over the last three years. As a result, we identified one novel pleiotropic QTL, qSS14, that simultaneously controlled four seed size traits (100-seed weight, seed length, seed width, and seed thickness) and two consistently detected QTLs, qSW17, and qSLW02, in multiple years of phenotypic data. Furthermore, we predicted two, two and three candidate genes within these three critical loci based on the parental resequencing data and gene function annotations. And the relative expression of four candidate genes GLYMA_14G155100, GLYMA_17G061000, GLYMA_02G273100, and GLYMA_02G273300 showed significant differences among parents and the extreme materials through qRT-PCR analysis. These findings could facilitate the determination of beneficial genes in wild soybean and contribute to our understanding of the soybean domestication process.

Identification and validation of two major QTLs for spikelet number per spike in wheat (Triticum aestivum L.).

The total number of spikelets (TSPN) and the number of fertile spikelets (FSPN) affect the final number of grains per spikelet in wheat. This study constructed a high-density genetic map using 55K single nucleotide polymorphism (SNP) arrays from a population of 152 recombinant inbred lines (RIL) from crossing the wheat accessions 10-A and B39. Twenty-four quantitative trait loci (QTLs) for TSPN and 18 QTLs for FSPN were localized based on the phenotype in 10 environments in 2019-2021. Two major QTLs, QTSPN/QFSPN.sicau-2D.4 (34.43-47.43 Mb) and QTSPN/QFSPN.sicau-2D.5(32.97-34.43 Mb), explained 13.97%-45.90% of phenotypic variation. Linked kompetitive allele-specific PCR (KASP) markers further validated these two QTLs and revealed that QTSPN.sicau-2D.4 had less effect on TSPN than QTSPN.sicau-2D.5 in 10-A×BE89 (134 RILs) and 10-A×Chuannong 16 (192 RILs) populations, and one population of Sichuan wheat (233 accessions). The alleles combination haplotype 3 with the allele from 10-A of QTSPN/QFSPN.sicau-2D.5 and the allele from B39 of QTSPN.sicau-2D.4 resulted in the highest number of spikelets. In contrast, the allele from B39 for both loci resulted in the lowest number of spikelets. Using bulk-segregant analysis-exon capture sequencing, six SNP hot spots that included 31 candidate genes were identified in the two QTLs. We identified Ppd-D1a from B39 and Ppd-D1d from 10-A and further analyzed Ppd-D1 variation in wheat. These results identified loci and molecular markers with potential utility for wheat breeding and laid a foundation for further fine mapping and cloning of the two loci.

High-density genetic mapping of Fusarium head blight resistance and agronomic traits in spring wheat.

Fusarium head blight (FHB) has rapidly become a major challenge to successful wheat production and competitive end-use quality in western Canada. Continuous effort is required to develop germplasm with improved FHB resistance and understand how to incorporate the material into crossing schemes for marker-assisted selection and genomic selection. The aim of this study was to map quantitative trait loci (QTL) responsible for the expression of FHB resistance in two adapted cultivars and to evaluate their co-localization with plant height, days to maturity, days to heading, and awnedness. A large doubled haploid population of 775 lines developed from cultivars Carberry and AC Cadillac was assessed for FHB incidence and severity in nurseries near Portage la Prairie, Brandon, and Morden in different years, and for plant height, awnedness, days to heading, and days to maturity near Swift Current. An initial linkage map using a subset of 261 lines was constructed using 634 polymorphic DArT and SSR markers. QTL analysis revealed five resistance QTL on chromosomes 2A, 3B (two loci), 4B, and 5A. A second genetic map with increased marker density was constructed using the Infinium iSelect 90k SNP wheat array in addition to the previous DArT and SSR markers, which revealed two additional QTL on 6A and 6D. The complete population was genotyped, and a total of 6,806 Infinium iSelect 90k SNP polymorphic markers were used to identify 17 putative resistance QTL on 14 different chromosomes. As with the smaller population size and fewer markers, large-effect QTL were detected on 3B, 4B, and 5A that were consistently expressed across environments. FHB resistance QTL were co-localized with plant height QTL on chromosomes 4B, 6D, and 7D; days to heading on 2B, 3A, 4A, 4B, and 5A; and maturity on 3A, 4B, and 7D. A major QTL for awnedness was identified as being associated with FHB resistance on chromosome 5A. Nine small-effect QTL were not associated with any of the agronomic traits, whereas 13 QTL that were associated with agronomic traits did not co-localize with any of the FHB traits. There is an opportunity to select for improved FHB resistance within adapted cultivars by using markers associated with complementary QTL.

Systematic Characterization of Multi-Rust Resistance Genes from a 'Parula × Thatcher' Population with a High-Density Genetic Map.

Pyramiding multiple resistant genes has been proposed as the most effective way to control wheat rust diseases globally. Identifying the most effective pyramids is challenged by the large pool of rust resistance genes and limited information about their mechanisms of resistance and interactions. Here, using a high-density genetic map, a double haploid population, and multi-rust field testing, we aimed to systematically characterize the most effective gene pyramids for rust resistance from the durable multi-rust resistant CIMMYT cultivar Parula. We revealed that the Parula resistance gene pyramid contains Lr34/Yr18/Sr57 (Lr34), Lr46/Yr29/Sr58 (Lr46), Lr27/Yr30/Sr2 (Sr2), and Lr68. The efficacy, magnitude of effect, and interactions varied for the three rust diseases. A subpopulation mapping approach was applied to characterize the complex interactions of the resistance genes by controlling for the effect of Lr34. Using this approach, we found that Lr34 and Lr68 have a strong additive effect for leaf rust, whereas no additive effects were observed for any rusts between Lr34 and Lr46. Lr34 combined synergistically with Sr12 from Thatcher for stem rust, whereas the additive effect of Lr34 and Sr2 was dependent on the type of rust and environment. Two novel leaf rust quantitative trait loci (QTLs) from Parula were identified in this study, a stable QTL QLr-7BS and QLr-5AS, which showed Lr34 dependent expression. With these findings, we propose combining two to three high-value genes from Canadian wheat (e.g., Sr12 from Thatcher) with a foundational multi-adult plant resistance cassette for desirable and durable resistance to all three rusts in Canadian wheat.

Whole genome resequencing and phenotyping of MAGIC population for high resolution mapping of drought tolerance in chickpea.

Terminal drought is one of the major constraints to crop production in chickpea (Cicer arietinum L.). In order to map drought tolerance related traits at high resolution, we sequenced multi-parent advanced generation intercross (MAGIC) population using whole genome resequencing approach and phenotyped it under drought stress environments for two consecutive years (2013-14 and 2014-15). A total of 52.02 billion clean reads containing 4.67TB clean data were generated on the 1136 MAGIC lines and eight parental lines. Alignment of clean data on to the reference genome enabled identification of a total, 932,172 of SNPs, 35,973 insertions, and 35,726 deletions among the parental lines. A high-density genetic map was constructed using 57,180 SNPs spanning a map distance of 1606.69cM. Using compressed mixed linear model, genome-wide association study (GWAS) enabled us to identify 737 markers significantly associated with days to 50% flowering, days to maturity, plant height, 100 seed weight, biomass, and harvest index. In addition to the GWAS approach, an identity-by-descent (IBD)-based mixed model approach was used to map quantitative trait loci (QTLs). The IBD-based mixed model approach detected major QTLs that were comparable to those from the GWAS analysis as well as some exclusive QTLs with smaller effects. The candidate genes like FRIGIDA and CaTIFY4b can be used for enhancing drought tolerance in chickpea. The genomic resources, genetic map, marker-trait associations, and QTLs identified in the study are valuable resources for the chickpea community for developing climate resilient chickpeas.

Mapping and validation of a new quantitative trait locus (QTL) for fruit size in watermelon (Citrullus lanatus)

Watermelon (Citrullus lanatus) is one of the top ten fruit-bearing species in the world and is mainly grown for its edible fruit. However, the understanding of watermelon fruit size is still incomplete, with relatively few studies on the genetic and molecular mechanisms of this trait. In the present study, three segregation populations from one novel germplasm with small fruit and different inbred lines with medium fruit, big fruit and giant fruit, respectively, were constructed to locate and fine map one new quantitative trait locus (QTL) on chromosome 8 for fruit size in watermelon. Inheritance analysis of these three populations suggested that small fruit was controlled by a single recessive gene in watermelon. We located a new QTL for fruit size on chromosome 8, and developed markers to conduct fine mapping of the genomic region and to identify candidate genes. Specifically, we constructed a high-density genetic linkage map using restriction-site associated DNA (RAD)-based high-throughput genotyping data from a second-filial generation (F2) mapping family derived from novel germplasms with small fruit and big fruit. The total genetic map length was 1315.53 cM with an average inter-locus distance of 0.18 cM, which contained 7,272 high-quality single nucleotide polymorphism (SNP) markers distributed on 11 linkage groups corresponding to the number of chromosome pairs in watermelon. Genome wide QTL mapping revealed one significant QTL (fs-chr8) on chromosome 8 associated with fruit size. One major QTL (fs-B171) on chromosome 8 was also identified in another BC1 population derived from giant watermelon and small watermelon, which overlapped with fs-chr8. Moreover, based on the markers obtained from next-generation sequencing of the parental lines, we conducted fine mapping of the interval to a 304 kb region (from 26.83 to 27.14 Mb) on chromosome 8 using 7 polymerase chain reaction (PCR) based markers. The PCR based markers confirmed the accuracy of our mapping results for watermelon fruit size. Finally, candidate genes underlying fruit size were identified from the reference genome 97103v2, including genes related to cytochrome P450 family enzymes, gibberellin-regulated proteins, transcription factor and basic leucine zipper (bZIP) transcription factor family proteins. Our study provides fine mapping results for watermelon fruit size and will lay the foundation for the identification of candidate genes to elucidate the molecular mechanism underlying fruit size in this species.

Fine mapping and validation of a stable QTL for thousand-kernel weight in wheat (Triticum aestivum L.)

Thousand-kernel weight (TKW) is a measure of grain weight, a target of wheat breeding. The object of this study was to fine-map a stable quantitative trait loci (QTL) for TKW and identify its candidate gene in a recombinant inbred line (RIL) population derived from the cross of Kenong 9204 (KN9204) and Jing 411 (J411). On a high-density genetic linkage map, 24, 26 and 25 QTL were associated with TKW, kernel length (KL), and kernel width (KW), respectively. A major and stable QTL, QTkw-2D, was mapped to an 8.3 cM interval on chromosome arm 2DL. By saturation of polymorphic markers in its target region, QTkw-2D was confined to a 9.13 Mb physical interval using a secondary mapping population derived from a residually heterozygous line (F6:7). This interval was further narrowed to 2.52 Mb using QTkw-2D near-isogenic lines (NILs). NILsKN9204 had higher fresh and dry weights than NILsJ411 at various grain-filling stages. The TKW and KW of NILsKN9204 were much higher than those of NILsJ411 in field trials. By comparison of both DNA sequence and expression between KN9204 and J411, TraesCS2D02G460300.1 (TraesKN2D01HG49350) was assigned as a candidate gene for QTkw-2D. This was confirmed by RNA sequencing (RNA-seq) of QTkw-2D NILs. These results provide the basis of map-based cloning of QTkw-2D, and DNA markers linked to the candidate gene may be used in marker-assisted selection.

Fine mapping of KLW1 that conditions kernel weight mainly through regulating kernel length in wheat (Triticum aestivum L.).

KLW1 was localized to a 0.6 cM interval near the centromere of chromosome 4B and found to be dominant in conditioning longer kernels and higher kernel weight. Kernel weight is a major wheat yield component and affected by kernel dimensions, filling process and kernel density. Because of this complexity, the mechanism underlying kernel weight is still far from clear. Qtgw.nau-4B or KLW1 was a major kernel weight QTL identified in the Nanda2419 × Wangshuibai population. We showed that introduction of the Nanda2419 allele into elite cultivar Wenmai6 resulted in longer kernels as well as higher kernel weight, without affecting other traits such as spike number per plant, plant height, spike length, spikelet number per spike, and kernel number per spike. KLW1 was dominant in conditioning higher kernel weight and functioned mainly through affecting kernel length. Using F2 plants derived from KLW1 NIL, a high-density genetic map covering the QTL was constructed. KLW1 was consequently confined to the 0.6cM Xwgrc4219-Xwgrc4067 interval by evaluating the recombinant lines in three field trials. KLW1 is complementary to KT1, the QTL on chromosome 5A of Nanda2419 for thicker and heavier kernels, in producing larger kernels with higher commercial value, augmenting its usefulness in wheat breeding.

Quantitative Trait Loci Mapping of Grain Lipid Content in Rice Variety ‘Goudang 3’ Using Genome Re-Sequencing

Fat is the third largest substance in rice seeds, and its content has a great impact on rice cooking, taste and storage qualities. However, few genes related to seed fat content have been cloned, which seriously restricts the application of fat traits in high-quality rice breeding. ‘Goudang 3’ is a representative aromatic rice landrace of Guizhou He, a characteristic rice species resource in Guizhou Province, China. It has the advantages of high fat content, rich flavor, soft and glutinous taste, etc. In this work, to address this issue, from a high-fat content rice variety, Goudang 3, and a low-fat content rice variety, Huazhan, a 148 recombinant inbred lines (RILs) population were derived. A high-density genetic map with 4063 Bin Markers covering 12 chromosomes were constructed through simplified genotyping-by-sequencing (GBS) technology. In combination with fat content, a brown rice fat content quantitative trait loci (QTL) qCFC3 was mapped within the 492 kb interval on chromosome 3. The qCFC3 was consistent with the previous reporting site, and no cloned fat content-related genes have been reported. LOC_Os03g13630 was identified. In conclusion, these QTL and candidate gene can be used for improving rice quality and can lay a foundation for further cloning and functional analysis.

Identification of QTL controlling volatile terpene contents in tea plant (Camellia sinensis) using a high-aroma 'Huangdan' x 'Jinxuan' F1 population.

Aroma is an important factor affecting the character and quality of tea. The improvement of aroma trait is a crucial research direction of tea plant breeding. Volatile terpenes, as the major contributors to the floral odors of tea products, also play critical roles in the defense responses of plants to multiple stresses. However, previous studies have largely focused on the aroma formation during the manufacture of tea or the comparison of raw tea samples. The mechanisms causing different aroma profiles between tea cultivars have remained underexplored. In the current study, a high-density genetic linkage map of tea plant was constructed based on an F1 population of 'Huangdan' × 'Jinxuan' using genotyping by sequencing. This linkage map covered 1754.57 cM and contained 15 linkage groups with a low inter-marker distance of 0.47 cM. A total of 42 QTLs associated with eight monoterpene contents and 12 QTLs associated with four sesquiterpenes contents were identified with the average PVE of 12.6% and 11.7% respectively. Furthermore, six candidate genes related to volatile terpene contents were found in QTL cluster on chromosome 5 by RNA-seq analysis. This work will enrich our understanding of the molecular mechanism of volatile terpene biosynthesis and provide a theoretical basis for tea plant breeding programs for aroma quality improvement.

Deciphering the Mechanism of Tolerance to Apple Replant Disease Using a Genetic Mapping Approach in a Malling 9 × M. × robusta 5 Population Identifies SNP Markers Linked to Candidate Genes.

Apple replant disease (ARD) is a worldwide economic risk in apple production. Although several studies have shown that the wild apple accession Malus × robusta 5 (Mr5) is ARD-tolerant, the genetics of this tolerance have not yet been elucidated. A genetic mapping approach with a biparental population derived from contrasting parents involving molecular markers provides a means for marker-assisted selection of genetically complex traits and for determining candidate genes. In this study, we crossed the ARD-tolerant wild apple accession Mr5 and the ARD-susceptible rootstock 'M9' and analyzed the resultant progeny for ARD tolerance. Hence, a high-density genetic map using a tunable genotyping-by-sequencing (tGBS) approach was established. A total of 4804 SNPs together with 77 SSR markers were included in the parental maps comprising 17 linkage groups. The phenotypic responses to ARD were evaluated for 106 offspring and classified by an ARD-susceptibility index (ASI). A Kruskal-Wallis test identified SNP markers and one SSR marker on linkage groups (LG) 6 and 2 that correlated with ARD tolerance. We found nine candidate genes linked with these markers, which may be associated with plant response to ARD. These candidate genes provide some insight into the defense mechanisms against ARD and should be studied in more detail.

QTL mapping and transcriptome analysis identify novel QTLs and candidate genes in Brassica villosa for quantitative resistance against Sclerotinia sclerotiorum

Key messageNovel QTLs and candidate genes for Sclerotinia-resistance were identified in B. villosa, a wild Brassica species, which represents a new genetic source for improving oilseed rape resistance to SSR.Sclerotinia stem rot (SSR), caused by Sclerotinia sclerotiorum, is one of the most destructive diseases in oilseed rape growing regions. To date, there is no effective genetic resistance against S. sclerotiorum in the B. napus germplasm and knowledge of the molecular plant–fungal interaction is also limited. To identify new resistance resources, we screened a set of wild Brassica species and identified B. villosa (BRA1896) with a high level of Sclerotinia-resistance. Two segregating F2 populations for Sclerotinia-resistance, generated by interspecific crosses between the resistant B. villosa (BRA1896) and the wild susceptible B. oleracea (BRA1909) were assessed for Sclerotinia-resistance. Genetic mapping using a 15-k Illumina Infinium SNP-array resulted in a high-density genetic map containing 1,118 SNP markers and spanning a total genetic length of 792.2 cM. QTL analysis revealed seven QTLs explaining 3.8% to 16.5% of phenotypic variance. Intriguingly, RNAseq-based transcriptome analysis identified genes and pathways specific to B. villosa, of which a cluster of five genes encoding putative receptor-like kinases (RLKs) and two pathogenesis-related (PR) proteins are co-localized within a QTL on chromosome C07. Furthermore, transcriptomic analysis revealed enhanced ethylene (ET)-activated signaling in the resistant B. villosa, which is associated with a stronger plant immune response, depressed cell death, and enhanced phytoalexin biosynthesis compared to the susceptible B. oleracea. Our data demonstrates that B. villosa represents a novel and unique genetic source for improving oilseed rape resistance against SSR.

Integration of GWAS, linkage analysis and transcriptome analysis to reveal the genetic basis of flowering time-related traits in maize.

Maize (Zea mays) inbred lines vary greatly in flowering time, but the genetic basis of this variation is unknown. In this study, three maize flowering-related traits (DTT, days to tasselling; DTP, days to pollen shed; DTS, days to silking) were evaluated with an association panel consisting of 226 maize inbred lines and an F2:3 population with 120 offspring from a cross between the T32 and Qi319 lines in different environments. A total of 82 significant single nucleotide polymorphisms (SNPs) and 117 candidate genes were identified by genome-wide association analysis. Twenty-one quantitative trait loci (QTLs) and 65 candidate genes were found for maize flowering time by linkage analysis with the constructed high-density genetic map. Transcriptome analysis was performed for Qi319, which is an early-maturing inbred line, and T32, which is a late-maturing inbred line, in two different environments. Compared with T32, Qi319 showed upregulation of 3815 genes and downregulation of 3906 genes. By integrating a genome-wide association study (GWAS), linkage analysis and transcriptome analysis, 25 important candidate genes for maize flowering time were identified. Together, our results provide an important resource and a foundation for an enhanced understanding of flowering time in maize.

Identification of major QTLs for yield-related traits with improved genetic map in wheat.

Identification of stable major quantitative trait loci (QTLs) for yield-related traits is important for yield potential improvement in wheat breeding. In the present study, we genotyped a recombinant inbred line (RIL) population using the Wheat 660K SNP array and constructed a high-density genetic map. The genetic map showed high collinearity with the wheat genome assembly. Fourteen yield-related traits were evaluated in six environments for QTL analysis. A total of 12 environmentally stable QTLs were identified in at least three environments, explaining up to 34.7% of the phenotypic variation. Of these, QTkw-1B.2 for thousand kernel weight (TKW), QPh-2D.1 (QSl-2D.2/QScn-2D.1) for plant height (PH), spike length (SL) and spikelet compactness (SCN), QPh-4B.1 for PH, and QTss-7A.3 for total spikelet number per spike (TSS) were detected in at least five environments. A set of Kompetitive Allele Specific PCR (KASP) markers were converted based on the above QTLs and used to genotype a diversity panel comprising of 190 wheat accessions across four growing seasons. QPh-2D.1 (QSl-2D.2/QScn-2D.1), QPh-4B.1 and QTss-7A.3 were successfully validated. Compared with previous studies, QTkw-1B.2 and QPh-4B.1 should be novel QTLs. These results provided a solid foundation for further positional cloning and marker-assisted selection of the targeted QTLs in wheat breeding programs.

The Prospects of gene introgression from crop wild relatives into cultivated lentil for climate change mitigation.

Crop wild relatives (CWRs), landraces and exotic germplasm are important sources of genetic variability, alien alleles, and useful crop traits that can help mitigate a plethora of abiotic and biotic stresses and crop yield reduction arising due to global climatic changes. In the pulse crop genus Lens, the cultivated varieties have a narrow genetic base due to recurrent selections, genetic bottleneck and linkage drag. The collection and characterization of wild Lens germplasm resources have offered new avenues for the genetic improvement and development of stress-tolerant, climate-resilient lentil varieties with sustainable yield gains to meet future food and nutritional requirements. Most of the lentil breeding traits such as high-yield, adaptation to abiotic stresses and resistance to diseases are quantitative and require the identification of quantitative trait loci (QTLs) for marker assisted selection and breeding. Advances in genetic diversity studies, genome mapping and advanced high-throughput sequencing technologies have helped identify many stress-responsive adaptive genes, quantitative trait loci (QTLs) and other useful crop traits in the CWRs. The recent integration of genomics technologies with plant breeding has resulted in the generation of dense genomic linkage maps, massive global genotyping, large transcriptomic datasets, single nucleotide polymorphisms (SNPs), expressed sequence tags (ESTs) that have advanced lentil genomic research substantially and allowed for the identification of QTLs for marker-assisted selection (MAS) and breeding. Assembly of lentil and its wild species genomes (~4Gbp) opens up newer possibilities for understanding genomic architecture and evolution of this important legume crop. This review highlights the recent strides in the characterization of wild genetic resources for useful alleles, development of high-density genetic maps, high-resolution QTL mapping, genome-wide studies, MAS, genomic selections, new databases and genome assemblies in traditionally bred genus Lens for future crop improvement amidst the impending global climate change.

A Wheat 660K SNP array-based high-density genetic map facilitates QTL mapping of flag leaf-related traits in wheat.

A high-density genetic map containing122,620 SNP markers was constructed, which facilitated the identification of eight major flag leaf-related QTL in relatively narrow intervals. The flag leaf plays an important role in photosynthetic capacity and yield potential in wheat. In this study, we used a recombinant inbred line population containing 188 lines derived from a cross between 'Lankao86' (LK86) and 'Ermangmai' to construct a genetic map using the Wheat 660K single-nucleotide polymorphism (SNP) array. The high-density genetic map contains 122,620 SNP markers spanning 5185.06cM. It shows good collinearity with the physical map of Chinese Spring and anchors multiple sequences of previously unplaced scaffolds onto chromosomes. Based on the high-density genetic map, we identified seven, twelve, and eight quantitative trait loci (QTL) for flag leaf length (FLL), width (FLW), and area (FLA) across eight environments, respectively. Among them, three, one, and four QTL for FLL, FLW, and FLA are major and stably express in more than four environments. The physical distance between the flanking markers for QFll.igdb-3B/QFlw.igdb-3B/QFla.igdb-3B is only 444kb containing eight high confidence genes. These results suggested that we could directly map the candidate genes in a relatively small region by the high-density genetic map constructed with the Wheat 660K array. Furthermore, the identification of environmentally stable QTL for flag leaf morphology laid a foundation for the following gene cloning and flag leaf morphology improvement.

Identification and Pyramiding Major QTL Loci for Simultaneously Enhancing Aflatoxin Resistance and Yield Components in Peanut.

Peanut is susceptible to Aspergillus flavus infection, and the consequent aflatoxin contamination has been recognized as an important risk factor affecting food safety and industry development. Planting peanut varieties with resistance to aflatoxin contamination is regarded as an ideal approach to decrease the risk in food safety, but most of the available resistant varieties have not been extensively used in production because of their low yield potential mostly due to possessing small pods and seeds. Hence, it is highly necessary to integrate resistance to aflatoxin and large seed weight. In this study, an RIL population derived from a cross between Zhonghua 16 with high yield and J 11 with resistance to infection of A. flavus and aflatoxin production, was used to identify quantitative trait locus (QTL) for aflatoxin production (AP) resistance and hundred-seed weight (HSW). From combined analysis using a high-density genetic linkage map constructed, 11 QTLs for AP resistance with 4.61-11.42% phenotypic variation explanation (PVE) and six QTLs for HSW with 3.20-28.48% PVE were identified, including three major QTLs for AP resistance (qAFTA05.1, qAFTB05.2 and qAFTB06.3) and three for HSW (qHSWA05, qHSWA08 and qHSWB06). In addition, qAFTA05.1, qAFTB06.3, qHSWA05, qHSWA08 and qHSWB06 were detected in multiple environments. The aflatoxin contents under artificial inoculation were decreased by 34.77-47.67% in those segregated lines harboring qAFTA05.1, qAFTB05.2 and qAFTB06.3, while the HSWs were increased by 47.56-49.46 g in other lines harboring qHSWA05, qHSWA08 and qHSWB06. Conditional QTL mapping indicated that HSW and percent seed infection index (PSII) had no significant influence on aflatoxin content. Interestingly, the QT 1059 simultaneously harboring alleles of aflatoxin content including qAFTA05.1 and qAFTB05.2, alleles of PSII including qPSIIB03.1, qPSIIB03.2, and qPSIIB10 and alleles of HSW including qHSWA05, qHSWB06, qHSWA08 had better resistance to A. flavus infection and to toxin production and higher yield potential compared with the two parents of the RIL. The above identified major loci for AP resistance and HWS would be helpful for marker-assisted selection in peanut breeding.