Genotyping-by-Sequencing Derived High-Density Linkage Map and its Application to QTL Mapping of Flag Leaf Traits in Bread Wheat

QTL mapping for the flag leaf-related traits using RILs derived from Trititrigia germplasm line SN304 and wheat cultivar Yannong15 in multiple environments

BACKGROUND

Developing and enriching genetic resources plays important role in the crop improvement. The flag leaf affects plant architecture and contributes to the grain yield of wheat (Triticum aestivum L.). The genetic improvement of flag leaf traits faces problems such as a limited genetic basis. Among the various genetic resources of wheat, Thinopyrum intermedium has been utilized as a valuable resource in genetic improvement due to its disease resistance, large spikes, large leaves, and multiple flowers. In this study, a recombinant inbred line (RIL) population was derived from common wheat Yannong15 and wheat-Th. intermedium introgression line SN304 was used to identify the quantitative trait loci (QTL) for flag leaf-related traits.

RESULTS

QTL mapping was performed for flag leaf length (FLL), flag leaf width (FLW) and flag leaf area (FLA). A total of 77 QTLs were detected, and among these, 51 QTLs with positive alleles were contributed by SN304. Fourteen major QTLs for flag leaf traits were detected on chromosomes 2B, 3B, 4B, and 2D. Additionally, 28 QTLs and 8 QTLs for flag leaf-related traits were detected in low-phosphorus and drought environments, respectively. Based on major QTLs of positive alleles from SN304, we identified a pair of double-ended anchor primers mapped on chromosome 2B and amplified a specific band of Th. intermedium in SN304. Moreover, there was a major colocated QTL on chromosome 2B, called QFll/Flw/Fla-2B, which was delimited to a physical interval of approximately 2.9 Mb and contained 20 candidate genes. Through gene sequence and expression analysis, four candidate genes associated with flag leaf formation and growth in the QTL interval were identified.

CONCLUSION

These results promote the fine mapping of QFll/Flw/Fla-2B, which have pleiotropic effects, and will facilitate the identification of candidate genes for flag leaf-related traits. Additionally, this work provides a theoretical basis for the application of Th. intermedium in wheat breeding.

Yield-related quantitative trait loci identification and lint percentage hereditary dissection under salt stress in upland cotton

Salinity is frequently mentioned as a major constraint in worldwide agricultural production. Lint percentage (LP) is a crucial yield-component in cotton lint production. While the genetic factors affect cotton yield in saline soils are still unclear. Here, we employed a recombinant inbred line population in upland cotton (Gossypium hirsutum L.) and investigated the effects of salt stress on five yield and yield component traits, including seed cotton yield per plant, lint yield per plant, boll number per plant, boll weight, and LP. Between three datasets of salt stress (E1), normal growth (E2), and the difference values dataset of salt stress and normal conditions (D-value), 87, 82, and 55 quantitative trait loci (QTL) were detectable, respectively. In total, five QTL (qLY-Chr6-2, qBNP-Chr4-1, qBNP-Chr12-1, qBNP-Chr15-5, qLP-Chr19-2) detected in both in E1 and D-value were salt related QTL, and three stable QTL (qLP-Chr5-3, qLP-Chr13-1, qBW-Chr5-5) were detected both in E1 and E2 across 3 years. Silencing of nine genes within a stable QTL (qLP-Chr5-3) highly expressed in fiber developmental stages increased LP and decreased fiber length (FL), indicating that multiple minor-effect genes clustered on Chromosome 5 regulate LP and FL. Additionally, the difference in LP caused by Gh_A05G3226 is mainly in transcription level rather than in the sequence difference. Moreover, silencing of salt related gene (GhDAAT) within qBNP-Chr4-1 decreased salt tolerance in cotton. Our findings shed light on the regulatory mechanisms underlining cotton salt tolerance and fiber initiation.

Integrated VIS/NIR Spectrum and Genome-Wide Association Study for Genetic Dissection of Cellulose Crystallinity in Wheat Stems

Cellulose crystallinity is a crucial factor influencing stem strength and, consequently, wheat lodging. However, the genetic dissection of cellulose crystallinity is less reported due to the difficulty of its measurement. In this study, VIS/NIR spectra and cellulose crystallinity were measured for a wheat accession panel with diverse genetic backgrounds. We developed a reliable VIS/NIR model for cellulose crystallinity with a high determination coefficient (R2) (0.95) and residual prediction deviation (RPD) (4.04), enabling the rapid screening of wheat samples. A GWAS of the cellulose crystallinity in 326 wheat accessions revealed 14 significant SNPs and 13 QTLs. Two candidate genes, TraesCS4B03G0029800 and TraesCS5B03G1085500, were identified. In summary, this study establishes an efficient method for the measurement of cellulose crystallinity in wheat stems and provides a genetic basis for enhancing lodging resistance in wheat.

Whole-genome resequencing facilitates the development of a 50K single nucleotide polymorphism genotyping array for Scots pine (Pinus sylvestris L.) and its transferability to other pine species

Scots pine (Pinus sylvestris L.) is one of the most widespread and economically important conifer species in the world. Applications like genomic selection and association studies, which could help accelerate breeding cycles, are challenging in Scots pine because of its large and repetitive genome. For this reason, genotyping tools for conifer species, and in particular for Scots pine, are commonly based on transcribed regions of the genome. In this article, we present the Axiom Psyl50K array, the first single nucleotide polymorphism (SNP) genotyping array for Scots pine based on whole-genome resequencing, that represents both genic and intergenic regions. This array was designed following a two-step procedure: first, 192 trees were sequenced, and a 430K SNP screening array was constructed. Then, 480 samples, including haploid megagametophytes, full-sib family trios, breeding population, and range-wide individuals from across Eurasia were genotyped with the screening array. The best 50K SNPs were selected based on quality, replicability, distribution across the draft genome assembly, balance between genic and intergenic regions, and genotype-environment and genotype-phenotype associations. Of the final 49 877 probes tiled in the array, 20 372 (40.84%) occur inside gene models, while the rest lie in intergenic regions. We also show that the Psyl50K array can yield enough high-confidence SNPs for genetic studies in pine species from North America and Eurasia. This new genotyping tool will be a valuable resource for high-throughput fundamental and applied research of Scots pine and other pine species.

A co-located QTL for seven spike architecture-related traits shows promising breeding use potential in common wheat (Triticum aestivum L.)

KEY MESSAGE

A co-located novel QTL for TFS, FPs, FMs, FFS, FFPs, KWS, and KWPs with potential of improving wheat yield was identified and validated. Spike-related traits, including fertile florets per spike (FFS), kernel weight per spike (KWS), total florets per spike (TFS), florets per spikelet (FPs), florets in the middle spikelet (FMs), fertile florets per spikelet (FFPs), and kernel weight per spikelet (KWPs), are key traits in improving wheat yield. In the present study, quantitative trait loci (QTL) for these traits evaluated under various environments were detected in a recombinant inbred line population (msf/Chuannong 16) mainly genotyped using the 16 K SNP array. Ultimately, we identified 60 QTL, but only QFFS.sau-MC-1A for FFS was a major and stably expressed QTL. It was located on chromosome arm 1AS, where loci for TFS, FPs, FMs, FFS, FFPs, KWS, and KWPs were also simultaneously co-mapped. The effect of QFFS.sau-MC-1A was further validated in three independent segregating populations using a Kompetitive Allele-Specific PCR marker. For the co-located QTL, QFFS.sau-MC-1A, the presence of a positive allele from msf was associate with increases for all traits: + 12.29% TFS, + 10.15% FPs, + 13.97% FMs, + 17.12% FFS, + 14.75% FFPs, + 22.17% KWS, and + 19.42% KWPs. Furthermore, pleiotropy analysis showed that the positive allele at QFFS.sau-MC-1A simultaneously increased the spike length, spikelet number per spike, and thousand-kernel weight. QFFS.sau-MC-1A represents a novel QTL for marker-assisted selection with the potential for improving wheat yield. Four genes, TraesCS1A03G0012700, TraesCS1A03G0015700, TraesCS1A03G0016000, and TraesCS1A03G0016300, which may affect spike development, were predicted in the physical interval harboring QFFS.sau-MC-1A. Our results will help in further fine mapping QFFS.sau-MC-1A and be useful for improving wheat yield.

Dissection of QTLs conferring drought tolerance in B. carinata derived B. juncea introgression lines

BACKGROUND

Drought is one of the important abiotic stresses that can significantly reduce crop yields. In India, about 24% of Brassica juncea (Indian mustard) cultivation is taken up under rainfed conditions, leading to low yields due to moisture deficit stress. Hence, there is an urgent need to improve the productivity of mustard under drought conditions. In the present study, a set of 87 B. carinata-derived B. juncea introgression lines (ILs) was developed with the goal of creating drought-tolerant genotypes.

METHOD

The experiment followed the augmented randomized complete block design with four blocks and three checks. ILs were evaluated for seed yield and its contributing traits under both rainfed and irrigated conditions in three different environments created by manipulating locations and years. To identify novel genes and alleles imparting drought tolerance, Quantitative Trait Loci (QTL) analysis was carried out. Genotyping-by-Sequencing (GBS) approach was used to construct the linkage map.

RESULTS

The linkage map consisted of 5,165 SNP markers distributed across 18 chromosomes and spanning a distance of 1,671.87 cM. On average, there was a 3.09 cM gap between adjoining markers. A total of 29 additive QTLs were identified for drought tolerance; among these, 17 (58.6% of total QTLs detected) were contributed by B. carinata (BC 4), suggesting a greater contribution of B. carinata towards improving drought tolerance in the ILs. Out of 17 QTLs, 11 (64.7%) were located on the B genome, indicating more introgression segments on the B genome of B. juncea. Eight QTL hotspots, containing two or more QTLs, governing seed yield contributing traits, water use efficiency, and drought tolerance under moisture deficit stress conditions were identified. Seventeen candidate genes related to biotic and abiotic stresses, viz., SOS2, SOS2 like, NPR1, FAE1-KCS, HOT5, DNAJA1, NIA1, BRI1, RF21, ycf2, WRKY33, PAL, SAMS2, orf147, MAPK3, WRR1 and SUS, were reported in the genomic regions of identified QTLs.

CONCLUSIONS

The significance of B. carinata in improving drought tolerance and WUE by introducing genomic segments in Indian mustard is well demonstrated. The findings also provide valuable insights into the genetic basis of drought tolerance in mustard and pave the way for the development of drought-tolerant varieties.

Mining Aegilops tauschii genetic diversity in the background of bread wheat revealed a novel QTL for seed dormancy

Due to the low genetic diversity in the current wheat germplasm, gene mining from wild relatives is essential to develop new wheat cultivars that are more resilient to the changing climate. Aegilops tauschii, the D-genome donor of bread wheat, is a great gene source for wheat breeding; however, identifying suitable genes from Ae. tauschii is challenging due to the different morphology and the wide intra-specific variation within the species. In this study, we developed a platform for the systematic evaluation of Ae. tauschii traits in the background of the hexaploid wheat cultivar 'Norin 61' and thus for the identification of QTLs and genes. To validate our platform, we analyzed the seed dormancy trait that confers resistance to preharvest sprouting. We used a multiple synthetic derivative (MSD) population containing a genetic diversity of 43 Ae. tauschii accessions representing the full range of the species. Our results showed that only nine accessions in the population provided seed dormancy, and KU-2039 from Afghanistan had the highest level of seed dormancy. Therefore, 166 backcross inbred lines (BILs) were developed by crossing the synthetic wheat derived from KU-2039 with 'Norin 61' as the recurrent parent. The QTL mapping revealed one novel QTL, Qsd.alrc.5D, associated with dormancy explaining 41.7% of the phenotypic variation and other five unstable QTLs, two of which have already been reported. The Qsd.alrc.5D, identified for the first time within the natural variation of wheat, would be a valuable contribution to breeding after appropriate validation. The proposed platform that used the MSD population derived from the diverse Ae. tauschii gene pool and recombinant inbred lines proved to be a valuable platform for mining new and important QTLs or alleles, such as the novel seed dormancy QTL identified here. Likewise, such a platform harboring genetic diversity from wheat wild relatives could be a useful source for mining agronomically important traits, especially in the era of climate change and the narrow genetic diversity within the current wheat germplasm.

Development of an SNP marker set for marker-assisted backcrossing using genotyping-by-sequencing in tetraploid perilla

High-quality molecular markers are essential for marker-assisted selection to accelerate breeding progress. Compared with diploid species, recently diverged polyploid crop species tend to have highly similar homeologous subgenomes, which is expected to limit the development of broadly applicable locus-specific single-nucleotide polymorphism (SNP) assays. Furthermore, it is particularly challenging to make genome-wide marker sets for species that lack a reference genome. Here, we report the development of a genome-wide set of kompetitive allele specific PCR (KASP) markers for marker-assisted recurrent selection (MARS) in the tetraploid minor crop perilla. To find locus-specific SNP markers across the perilla genome, we used genotyping-by-sequencing (GBS) to construct linkage maps of two F2 populations. The two resulting high-resolution linkage maps comprised 2326 and 2454 SNP markers that spanned a total genetic distance of 2133 cM across 16 linkage groups and 2169 cM across 21 linkage groups, respectively. We then obtained a final genetic map consisting of 22 linkage groups with 1123 common markers from the two genetic maps. We selected 96 genome-wide markers for MARS and confirmed the accuracy of markers in the two F2 populations using a high-throughput Fluidigm system. We confirmed that 91.8% of the SNP genotyping results from the Fluidigm assay were the same as the results obtained through GBS. These results provide a foundation for marker-assisted backcrossing and the development of new varieties of perilla.

No recombination suppression in asexually produced males of Daphnia pulex

Obligate parthenogenesis (OP) is often thought to evolve by disruption of reductional meiosis and suppression of crossover recombination. In the crustacean Daphnia pulex, OP lineages, which have evolved from cyclical parthenogenetic (CP) ancestors, occasionally produce males that are capable of reductional meiosis. Here, by constructing high-density linkage maps, we find that these males show only slightly and nonsignificantly reduced recombination rates compared to CP males and females. Both meiosis disruption and recombination suppression are therefore sex-limited (or partly so), which speaks against the evolution of OP by disruption of a gene that is essential for meiosis or recombination in both sexes. The findings may be explained by female-limited action of genes that suppress recombination, but previously identified candidate genes are known to be expressed in both sexes. Alternatively, and equally consistent with the data, OP might have evolved through a reuse of the parthenogenesis pathways already present in CP and through their extension to all events of oogenesis. The causal mutations for the CP to OP transition may therefore include mutations in genes involved in oogenesis regulation and may not necessarily be restricted to genes of the "meiosis toolkit." More generally, our study emphasizes that there are many ways to achieve asexuality, and elucidating the possible mechanisms is key to ultimately identify the genes and traits involved.

Genomic Regions Associated with Resistance to Three Rusts in CIMMYT Wheat Line "Mokue#1"

Understanding the genetic basis of rust resistance in elite CIMMYT wheat germplasm enhances breeding and deployment of durable resistance globally. "Mokue#1", released in 2023 in Pakistan as TARNAB Gandum-1, has exhibited high levels of resistance to stripe rust, leaf rust, and stem rust pathotypes present at multiple environments in Mexico and Kenya at different times. To determine the genetic basis of resistance, a F5 recombinant inbred line (RIL) mapping population consisting of 261 lines was developed and phenotyped for multiple years at field sites in Mexico and Kenya under the conditions of artificially created rust epidemics. DArTSeq genotyping was performed, and a linkage map was constructed using 7892 informative polymorphic markers. Composite interval mapping identified three significant and consistent loci contributed by Mokue: QLrYr.cim-1BL and QLrYr.cim-2AS on chromosome 1BL and 2AS, respectively associated with stripe rust and leaf rust resistance, and QLrSr.cim-2DS on chromosome 2DS for leaf rust and stem rust resistance. The QTL on 1BL was confirmed to be the Lr46/Yr29 locus, whereas the QTL on 2AS represented the Yr17/Lr37 region on the 2NS/2AS translocation. The QTL on 2DS was a unique locus conferring leaf rust resistance in Mexico and stem rust resistance in Kenya. In addition to these pleiotropic loci, four minor QTLs were also identified on chromosomes 2DL and 6BS associated with stripe rust, and 3AL and 6AS for stem rust, respectively, using the Kenya disease severity data. Significant decreases in disease severities were also demonstrated due to additive effects of QTLs when present in combinations.

A holistic and sustainable approach linked to drought tolerance of Mediterranean crops

The rapid increase in average temperatures and the progressive reduction in rainfalls caused by climate change is reducing crop yields worldwide, particularly in regions with hot and semi-arid climates such as the Mediterranean area. In natural conditions, plants respond to environmental drought stress with diverse morphological, physiological, and biochemical adaptations in an attempt to escape, avoid, or tolerate drought stress. Among these adaptations to stress, the accumulation of abscisic acid (ABA) is of pivotal importance. Many biotechnological approaches to improve stress tolerance by increasing the exogenous or endogenous content of ABA have proved to be effective. In most cases the resultant drought tolerance is associated with low productivity incompatible with the requirements of modern agriculture. The on-going climate crisis has provoked the search for strategies to increase crop yield under warmer conditions. Several biotechnological strategies, such as the genetic improvement of crops or the generation of transgenic plants for genes involved in drought tolerance, have been attempted with unsatisfactory results suggesting the need for new approaches. Among these, the genetic modification of transcription factors or regulators of signaling cascades provide a promising alternative. To reconcile drought tolerance with crop yield, we propose mutagenesis of genes controlling key signaling components downstream of ABA accumulation in local landraces to modulate responses. We also discuss the advantages of tackling this challenge with a holistic approach involving different knowledge and perspectives, and the problem of distributing the selected lines at subsidized prices to guarantee their use by small family farms.

Genetic mapping and analysis of candidate leaf color genes in common winter wheat (Triticum aestivum L.)

Leaf color-related genes play key roles in chloroplast development and photosynthetic pigment biosynthesis and affect photosynthetic efficiency and grain yield in crops. In this study, a recessive homozygous individual displaying yellow leaf color (yl1) was identified in the progeny population derived from a cross between wheat cultivars Xingmai1 (XM1) and Yunong3114 (YN3114). Phenotypic identification showed that yl1 exhibited the yellow character state over the entire growth period. Compared with XM1, yl1 plants had significantly lower chlorophyll content and net photosynthetic rate, and similar results were found between the green-type lines and yellow-type lines in the BC2F3 XM1 × yl1 population. Gene mapping via the bulked segregant exome capture sequencing (BSE-seq) method showed that the target gene TaYL1 was located within the region of 582,556,971-600,837,326 bp on chromosome 7D. Further analysis by RNA-seq suggested TraesCS7D02G469200 as a candidate gene for yellow leaf color in common wheat, which encodes a protein containing the AP2 domain. Moreover, comparative transcriptome profiling revealed that most differentially expressed genes (DEGs) were enriched in chlorophyll metabolism and photosynthesis pathways. Together, these results indicate that TaYL1 potentially affects chlorophyll synthesis and photosynthesis. This study further elucidates the biological mechanism of chlorophyll synthesis, metabolism, and photosynthesis in wheat and provides a theoretical basis for high photosynthetic efficiency in wheat breeding.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01395-z.

Plant Tolerance to Drought Stress with Emphasis on Wheat

Environmental stresses, such as drought, have negative effects on crop yield. Drought is a stress whose impact tends to increase in some critical regions. However, the worldwide population is continuously increasing and climate change may affect its food supply in the upcoming years. Therefore, there is an ongoing effort to understand the molecular processes that may contribute to improving drought tolerance of strategic crops. These investigations should contribute to delivering drought-tolerant cultivars by selective breeding. For this reason, it is worthwhile to review regularly the literature concerning the molecular mechanisms and technologies that could facilitate gene pyramiding for drought tolerance. This review summarizes achievements obtained using QTL mapping, genomics, synteny, epigenetics, and transgenics for the selective breeding of drought-tolerant wheat cultivars. Synthetic apomixis combined with the msh1 mutation opens the way to induce and stabilize epigenomes in crops, which offers the potential of accelerating selective breeding for drought tolerance in arid and semi-arid regions.

Genome-wide association study of leaf-related traits in tea plant in Guizhou based on genotyping-by-sequencing

BACKGROUND

Studying the genetic characteristics of tea plant (Camellia spp.) leaf traits is essential for improving yield and quality through breeding and selection. Guizhou Plateau, an important part of the original center of tea plants, has rich genetic resources. However, few studies have explored the associations between tea plant leaf traits and single nucleotide polymorphism (SNP) markers in Guizhou.

RESULTS

In this study, we used the genotyping-by-sequencing (GBS) method to identify 100,829 SNP markers from 338 accessions of tea germplasm in Guizhou Plateau, a region with rich genetic resources. We assessed population structure based on high-quality SNPs, constructed phylogenetic relationships, and performed genome-wide association studies (GWASs). Four inferred pure groups (G-I, G-II, G-III, and G-IV) and one inferred admixture group (G-V), were identified by a population structure analysis, and verified by principal component analyses and phylogenetic analyses. Through GWAS, we identified six candidate genes associated with four leaf traits, including mature leaf size, texture, color and shape. Specifically, two candidate genes, located on chromosomes 1 and 9, were significantly associated with mature leaf size, while two genes, located on chromosomes 8 and 11, were significantly associated with mature leaf texture. Additionally, two candidate genes, located on chromosomes 1 and 2 were identified as being associated with mature leaf color and mature leaf shape, respectively. We verified the expression level of two candidate genes was verified using reverse transcription quantitative polymerase chain reaction (RT-qPCR) and designed a derived cleaved amplified polymorphism (dCAPS) marker that co-segregated with mature leaf size, which could be used for marker-assisted selection (MAS) breeding in Camellia sinensis.

CONCLUSIONS

In the present study, by using GWAS approaches with the 338 tea accessions population in Guizhou, we revealed a list of SNPs markers and candidate genes that were significantly associated with four leaf traits. This work provides theoretical and practical basis for the genetic breeding of related traits in tea plant leaves.

Longer epidermal cells underlie a quantitative source of variation in wheat flag leaf size

The wheat flag leaf is the main contributor of photosynthetic assimilates to developing grains. Understanding how canopy architecture strategies affect source strength and yield will aid improved crop design. We used an eight-founder population to investigate the genetic architecture of flag leaf area, length, width and angle in European wheat. For the strongest genetic locus identified, we subsequently created a near-isogenic line (NIL) pair for more detailed investigation across seven test environments. Genetic control of traits investigated was highly polygenic, with colocalisation of replicated quantitative trait loci (QTL) for one or more traits identifying 24 loci. For QTL QFll.niab-5A.1 (FLL5A), development of a NIL pair found the FLL5A+ allele commonly conferred a c. 7% increase in flag and second leaf length and a more erect leaf angle, resulting in higher flag and/or second leaf area. Increased FLL5A-mediated flag leaf length was associated with: (1) longer pavement cells and (2) larger stomata at lower density, with a trend for decreased maximum stomatal conductance (G_smax ) per unit leaf area. For FLL5A, cell size rather than number predominantly determined leaf length. The observed trade-offs between leaf size and stomatal morphology highlight the need for future studies to consider these traits at the whole-leaf level.

Genome-wide meta-analysis of QTL for morphological related traits of flag leaf in bread wheat

Flag leaf is an important organ for photosynthesis of wheat plants, and a key factor affecting wheat yield. In this study, quantitative trait loci (QTL) for flag leaf morphological traits in wheat reported since 2010 were collected to investigate the genetic mechanism of these traits. Integration of 304 QTLs from various mapping populations into a high-density consensus map composed of various types of molecular markers as well as QTL meta-analysis discovered 55 meta-QTLs (MQTL) controlling morphological traits of flag leaves, of which 10 MQTLs were confirmed by GWAS. Four high-confidence MQTLs (MQTL-1, MQTL-11, MQTL-13, and MQTL-52) were screened out from 55 MQTLs, with an average confidence interval of 0.82 cM and a physical distance of 9.4 Mb, according to the definition of hcMQTL. Ten wheat orthologs from rice (7) and Arabidopsis (3) that regulated leaf angle, development and morphogenesis traits were identified in the hcMQTL region using comparative genomics, and were speculated to be potential candidate genes regulating flag leaf morphological traits in wheat. The results from this study provides valuable information for fine mapping and molecular markers assisted selection to improve morphological characters in wheat flag leaf.

QTL mapping of seedling and field resistance to stem rust in DAKIYE/Reichenbachii durum wheat population

Stem rust caused by the fungus Puccinia graminis f.sp. tritici Eriks. & E. Henn. (Pgt) threatens the global production of both durum wheat (Triticum turgidum L. ssp. durum (Desf.) Husnot) and common wheat (Triticum aestivum L.). The objective of this study was to evaluate a durum wheat recombinant inbred line (RIL) population from a cross between a susceptible parent 'DAKIYE' and a resistant parent 'Reichenbachii' developed by the International Center for the Improvement of Maize and Wheat (CIMMYT) 1) for seedling response to races JRCQC and TTRTF and 2) for field response to a bulk of the current Pgt races prevalent in Ethiopia and Kenya and 3) to map loci associated with seedling and field resistances in this population. A total of 224 RILs along with their parents were evaluated at the seedling stage in the Ethiopian Institute for Agricultural Research greenhouse at Debre Zeit, Ethiopia and in the EIAR and KALRO fields in Ethiopia and Kenya, for two seasons from 2019 to 2020. The lines were genotyped using the genotyping-by-sequencing approach. A total of 843 single nucleotide polymorphism markers for 175 lines were used for quantitative trait locus (QTL) analyses. Composite interval mapping (CIM) identified three QTL on chromosomes 3B, 4B and 7B contributed by the resistant parent. The QTL on chromosome 3B was identified at all growth stages and it explained 11.8%, 6.5%, 6.4% and 15.3% of the phenotypic variation for responses to races JRCQC, TTRTF and in the field trials ETMS19 and KNMS19, respectively. The power to identify additional QTL in this population was limited by the number of high-quality markers, since several markers with segregation distortion were eliminated. A cytological study is needed to understand the presence of chromosomal rearrangements. Future evaluations of additional durum lines and RIL families identification of durable adult plant resistance sources is crucial for breeding stem rust resistance in durum wheat in the future.

Association mapping and candidate genes for physiological non-destructive traits: Chlorophyll content, canopy temperature, and specific leaf area under normal and saline conditions in wheat

Wheat plants experience substantial physiological adaptation when exposed to salt stress. Identifying such physiological mechanisms and their genetic control is especially important to improve its salt tolerance. In this study, leaf chlorophyll content (CC), leaf canopy temperature (CT), and specific leaf area (SLA) were scored in a set of 153 (103 having the best genotypic data were used for GWAS analysis) highly diverse wheat genotypes under control and salt stress. On average, CC and SLA decreased under salt stress, while the CT average was higher under salt stress compared to the control. CT was negatively and significantly correlated with CC under both conditions, while no correlation was found between SLA and CC and CT together. High genetic variation and broad-sense-heritability estimates were found among genotypes for all traits. The genome wide association study revealed important QTLs for CC under both conditions (10) and SLA under salt stress (four). These QTLs were located on chromosomes 1B, 2B, 2D, 3A, 3B, 5A, 5B, and 7B. All QTLs detected in this study had major effects with R² extending from 20.20% to 30.90%. The analysis of gene annotation revealed three important candidate genes (TraesCS5A02G355900, TraesCS1B02G479100, and TraesCS2D02G509500). These genes are found to be involved in the response to salt stress in wheat with high expression levels under salt stress compared to control based on mining in data bases.

High-Density Linkage Mapping of Agronomic Trait QTLs in Wheat under Water Deficit Condition using Genotyping by Sequencing (GBS)

Improvement of grain yield is the ultimate goal for wheat breeding under water-limited environments. In the present study, a high-density linkage map was developed by using genotyping-by-sequencing (GBS) of a recombinant inbred line (RIL) population derived from the cross between Iranian landrace #49 and cultivar Yecora Rojo. The population was evaluated in three locations in Iran during two years under irrigated and water deficit conditions for the agronomic traits grain yield (GY), plant height (PH), spike number per square meter (SM), 1000 kernel weight (TKW), grain number per spike (GNS), spike length (SL), biomass (BIO) and harvest index (HI). A linkage map was constructed using 5831 SNPs assigned to 21 chromosomes, spanning 3642.14 cM of the hexaploid wheat genome with an average marker density of 0.62 (markers/cM). In total, 85 QTLs were identified on 19 chromosomes (all except 5D and 6D) explaining 6.06–19.25% of the traits phenotypic variance. We could identify 20 novel QTLs explaining 8.87–19.18% of phenotypic variance on chromosomes 1A, 1B, 1D, 2B, 3A, 3B, 6A, 6B and 7A. For 35 out of 85 mapped QTLs functionally annotated genes were identified which could be related to a potential role in drought stress.

Compatibility between snails and schistosomes: insights from new genetic resources, comparative genomics, and genetic mapping

The freshwater snail Biomphalaria glabrata is an important intermediate host of the parasite Schistosoma mansoni that causes human intestinal schistosomiasis. To better understand vector snail biology and help advance innovative snail control strategies, we have developed a new snail model consisting of two homozygous B. glabrata lines (iM line and iBS90) with sharply contrasting schistosome-resistance phenotypes. We produced and compared high-quality genome sequences for iM line and iBS90 which were assembled from 255 (N50 = 22.7 Mb) and 346 (N50 = 19.4 Mb) scaffolds, respectively. Using F2 offspring bred from the two lines and the newly generated iM line genome, we constructed 18 linkage groups (representing the 18 haploid chromosomes) covering 96% of the genome and identified three new QTLs (quantitative trait loci), two involved in snail resistance/susceptibility and one relating to body pigmentation. This study provides excellent genomic resources for unveiling complex vector snail biology, reveals genomic difference between resistant and susceptible lines, and offers novel insights into genetic mechanism of the compatibility between snail and schistosome.

SSR Linkage Maps and Identification of QTL Controlling Morpho-Phenological Traits in Two Iranian Wheat RIL Populations

Wheat is one of the essential grains grown in large areas. Identifying the genetic structure of agronomic and morphological traits of wheat can help to discover the genetic mechanisms of grain yield. In order to map the morpho-phenological traits, an experiment was conducted in the two cropping years of 2020 and 2021 on the university farm of the Faculty of Agriculture, GonbadKavous University. This study used two F8 populations, including 120 lines resulting from Gonbad × Zagros and Gonbad × Kuhdasht. The number of days to physiological maturity, number of days to flowering, number of germinated grains, number of tillers, number of tillers per plant, grain filling periods, plant height, peduncle length, spike length, awn length, spike weight, peduncle diameter, flag leaf length and weight, number of spikelets per spike, number of grains per spike, grain length, grain width, 1000-grain weight, biomass, grain yield, harvest index, straw-weight, and number of fertile spikelets per spike were measured. A total of 21 and 13 QTLs were identified for 11 and 13 traits in 2020 and 2021, respectively. In 2020, qGL-3D and qHI-1A were identified for grain length and harvest index on chromosomes 3D and 1A, explaining over 20% phenotypic variation, respectively. qNT-5B, qNTS-2D, and qSL-1D were identified on chromosomes 5B, 2D, and 1D with the LOD scores of 4.5, 4.13, and 3.89 in 2021, respectively.

Genetic diversity and population structure of pigeonpea (Cajanus cajan [L.] Millspaugh) landraces grown in Benin revealed by Genotyping-By-Sequencing

Genetic diversity studies provide important details on target trait availability and its variability, for the success of breeding programs. In this study, GBS approach was used to reveal a new structuration of genetic diversity and population structure of pigeonpea in Benin. We used a total of 688 high-quality Single Nucleotide Polymorphism markers for a total of 44 pigeonpea genotypes. The distribution of SNP markers on the 11 chromosomes ranged from 14 on chromosome 5 to 133 on chromosome 2. The Polymorphism Information Content and gene diversity values were 0.30 and 0.34 respectively. The analysis of population structure revealed four clear subpopulations. The Weighted Neighbor Joining tree agreed with structure analyses by grouping the 44 genotypes into four clusters. The PCoA revealed that genotypes from subpopulations 1, 2 and 3 intermixed among themselves. The Analysis of Molecular Variance showed 7% of the total variation among genotypes while the rest of variation (93%) was within genotypes from subpopulations indicating a high gene exchange (Nm = 7.13) and low genetic differentiation (PhiPT = 0.07) between subpopulations. Subpopulation 2 presented the highest mean values of number of different alleles (Na = 1.57), number of loci with private alleles (Pa = 0.11) and the percentage of polymorphic loci (P = 57.12%). We discuss our findings and demonstrate how the genetic diversity and the population structure of this specie can be used through the Genome Wide Association Studies and Marker-Assisted Selection to enhance genetic gain in pigeonpea breeding programs in Benin.

Pleiotropic Effect of the compactum Gene and Its Combined Effects with Other Loci for Spike and Grain-Related Traits in Wheat

Club wheat (Triticum aestivum ssp. compactum) with a distinctly compact spike morphology was conditioned by the dominant compactum (C) locus on chromosome 2D and resulted in a redistribution of spike yield components. The disclosure of the genetic basis of club wheat was a prerequisite for the development of widely adapted, agronomically competitive club wheat cultivars. In this study, we used a recombinant inbred line population derived from a cross between club wheat Hiller and modern cultivar Yangmai 158 to construct a genetic linkage map and identify quantitative trait loci associated with 15 morphological traits. The club allele acted in a semi-dominant manner and the C gene was mapped to 370.12–406.29 Mb physical region on the long arm of 2D. Apart from compact spikes, C exhibited a pleiotropic effect on ten other agronomic traits, including plant height, three spike-related traits and six grain-related traits. The compact spike phenotype was correlated with decreased grain size and weight, but with an increase in floret fertility and grain number. These pleiotropic effects make club wheat have compatible spike weight with a normal spike from common wheat. The genetic effects of various gene combinations of C with four yield-related genes, including Ppd-D1, Vrn-D3, Rht-B1b and Rht8, were evaluated. C had no epistatic interaction with any of these genes, indicating that their combinations would have an additive effect on other agronomically important traits. Our research provided a theoretical foundation for the potentially effective deployment of C gene into modern breeding varieties in combination with other favorable alleles.

Capturing Wheat Phenotypes at the Genome Level

Recent technological advances in next-generation sequencing (NGS) technologies have dramatically reduced the cost of DNA sequencing, allowing species with large and complex genomes to be sequenced. Although bread wheat (Triticum aestivum L.) is one of the world's most important food crops, efficient exploitation of molecular marker-assisted breeding approaches has lagged behind that achieved in other crop species, due to its large polyploid genome. However, an international public-private effort spanning 9 years reported over 65% draft genome of bread wheat in 2014, and finally, after more than a decade culminated in the release of a gold-standard, fully annotated reference wheat-genome assembly in 2018. Shortly thereafter, in 2020, the genome of assemblies of additional 15 global wheat accessions was released. As a result, wheat has now entered into the pan-genomic era, where basic resources can be efficiently exploited. Wheat genotyping with a few hundred markers has been replaced by genotyping arrays, capable of characterizing hundreds of wheat lines, using thousands of markers, providing fast, relatively inexpensive, and reliable data for exploitation in wheat breeding. These advances have opened up new opportunities for marker-assisted selection (MAS) and genomic selection (GS) in wheat. Herein, we review the advances and perspectives in wheat genetics and genomics, with a focus on key traits, including grain yield, yield-related traits, end-use quality, and resistance to biotic and abiotic stresses. We also focus on reported candidate genes cloned and linked to traits of interest. Furthermore, we report on the improvement in the aforementioned quantitative traits, through the use of (i) clustered regularly interspaced short-palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated gene-editing and (ii) positional cloning methods, and of genomic selection. Finally, we examine the utilization of genomics for the next-generation wheat breeding, providing a practical example of using in silico bioinformatics tools that are based on the wheat reference-genome sequence.

A new major QTL for flag leaf thickness in barley (Hordeum vulgare L.)

BACKGROUND

Carbohydrate accumulation of photosynthetic organs, mainly leaves, are the primary sources of grain yield in cereals. The flag leaf plays a vital role in seed development, which is probably the most neglected morphological characteristic during traditional selection processes.

RESULTS

In this experiment, four flag leaf morphological traits and seven yield-related traits were investigated in a DH population derived from a cross between a wild barley and an Australian malting barley cultivar. Flag leaf thickness (FLT) showed significantly positive correlations with grain size. Four QTL, located on chromosomes 1H, 2H, 3H, and 5H, respectively, were identified for FLT. Among them, a major QTL was located on chromosome 3H with a LOD value of 18.4 and determined 32% of the phenotypic variation. This QTL showed close links but not pleiotropism to the previously reported semi-dwarf gene sdw1 from the cultivated barley. This QTL was not reported before and the thick leaf allele from the wild barley could provide a useful source for improving grain yield through breeding.

CONCLUSIONS

Our results also provided valuable evidence that source traits and sink traits in barley are tightly connected and suggest further improvement of barley yield potential with enhanced and balanced source and sink relationships by exploiting potentialities of the wild barley resources. Moreover, this study will provide a novel sight on understanding the evolution and development of leaf morphology in barley and improving barley production by rewilding for lost superior traits during plant evolution.

Combined GWAS and QTL mapping revealed candidate genes and SNP network controlling recovery and tolerance traits associated with drought tolerance in seedling winter wheat

To date, very little research on drought tolerance has been conducted at the seedling stage in winter wheat. In this study, two types of traits, namely tolerance and recovery traits, associated with drought tolerance were scored in biparental mapping population (BPP) and association mapping population (A-set). The results of this study revealed no or weak significant correlation between the two types of traits. Based on GWAS and QTL mapping analyses, all QTLs associated with recovery traits were completely different from those associated with tolerance traits except one QTL in each population that was found to be associated with one tolerance trait and one recovery trait. The analysis of SNP and gene networks confirmed the results of combined GWAS and QTL mapping. One SNP marker located on the 2B chromosome (S2B_26494801) was found to be associated with recovery traits in both populations. The results of this study provided new information on understanding and improving drought tolerance in winter wheat.

QTL detection for bread wheat processing quality in a nested association mapping population of semi-wild and domesticated wheat varieties

BACKGROUND

Wheat processing quality is an important factor in evaluating overall wheat quality, and dough characteristics are important when assessing the processing quality of wheat. As a notable germplasm resource, semi-wild wheat has a key role in the study of wheat processing quality.

RESULTS

In this study, four dough rheological characteristics were collected in four environments using a nested association mapping (NAM) population consisting of semi-wild and domesticated wheat varieties to identify quantitative trait loci (QTL) for wheat processing quality. A total of 49 QTL for wheat processing quality were detected, explaining 0.36-10.82% of the phenotypic variation. These QTL were located on all wheat chromosomes except for 2D, 3A, 3D, 6B, 6D and 7D. Compared to previous studies, 29 QTL were newly identified. Four novel QTL, QMlPH-1B.4, QMlPH-3B.4, QWdEm-1B.2 and QWdEm-3B.2, were stably identified in three or more environments, among which QMlPH-3B.4 was a major QTL. Moreover, eight important genetic regions for wheat processing quality were identified on chromosomes 1B, 3B and 4D, which showed pleiotropy for dough characteristics. In addition, out of 49 QTL, 15 favorable alleles came from three semi-wild parents, suggesting that the QTL alleles provided by the semi-wild parent were not utilized in domesticated varieties.

CONCLUSIONS

The results show that semi-wild wheat varieties can enrich the existing wheat gene pool and provide broader variation resources for wheat genetic research.

MIG-seq is an effective method for high-throughput genotyping in wheat (Triticum spp.)

MIG-seq (Multiplexed inter-simple sequence repeats genotyping by sequencing) has been developed as a low cost genotyping technology, although the number of polymorphisms obtained is assumed to be minimal, resulting in the low application of this technique to analyses of agricultural plants. We applied MIG-seq to 12 plant species that include various crops and investigated the relationship between genome size and the number of bases that can be stably sequenced. The genome size and the number of loci, which can be sequenced by MIG-seq, are positively correlated. This is due to the linkage between genome size and the number of simple sequence repeats (SSRs) through the genome. The applicability of MIG-seq to population structure analysis, linkage mapping, and quantitative trait loci (QTL) analysis in wheat, which has a relatively large genome, was further evaluated. The results of population structure analysis for tetraploid wheat showed the differences among collection sites and subspecies, which agreed with previous findings. Additionally, in wheat biparental mapping populations, over 3,000 SNPs/indels with low deficiency were detected using MIG-seq, and the QTL analysis was able to detect recognized flowering-related genes. These results revealed the effectiveness of MIG-seq for genomic analysis of agricultural plants with large genomes, including wheat.

Resistance of the Wheat Cultivar ‘Renan’ to Septoria Leaf Blotch Explained by a Combination of Strain Specific and Strain Non-Specific QTL Mapped on an Ultra-Dense Genetic Map

Quantitative resistance is considered more durable than qualitative resistance as it does not involve major resistance genes that can be easily overcome by pathogen populations, but rather a combination of genes with a lower individual effect. This durability means that quantitative resistance could be an interesting tool for breeding crops that would not systematically require phytosanitary products. Quantitative resistance has yet to reveal all of its intricacies. Here, we delve into the case of the wheat/Septoria tritici blotch (STB) pathosystem. Using a population resulting from a cross between French cultivar Renan, generally resistant to STB, and Chinese Spring, a cultivar susceptible to the disease, we built an ultra-dense genetic map that carries 148,820 single nucleotide polymorphism (SNP) markers. Phenotyping the interaction was done with two different Zymoseptoria tritici strains with contrasted pathogenicities on Renan. A linkage analysis led to the detection of three quantitative trait loci (QTL) related to resistance in Renan. These QTL, on chromosomes 7B, 1D, and 5D, present with an interesting diversity as that on 7B was detected with both fungal strains, while those on 1D and 5D were strain-specific. The resistance on 7B was located in the region of Stb8 and the resistance on 1D colocalized with Stb19. However, the resistance on 5D was new, so further designated Stb20q. Several wall-associated kinases (WAK), nucleotide-binding and leucine-rich repeats (NB-LRR) type, and kinase domain carrying genes were present in the QTL regions, and some of them were expressed during the infection. These results advocate for a role of Stb genes in quantitative resistance and for resistance in the wheat/STB pathosystem being as a whole quantitative and polygenic.

Identification and Validation of High LD Hotspot Genomic Regions Harboring Stem Rust Resistant Genes on 1B, 2A (Sr38), and 7B Chromosomes in Wheat

Stem rust caused by Puccinia graminis f. sp. tritici Eriks. is an important disease of common wheat globally. The production and cultivation of genetically resistant cultivars are one of the most successful and environmentally friendly ways to protect wheat against fungal pathogens. Seedling screening and genome-wide association study (GWAS) were used to determine the genetic diversity of wheat genotypes obtained on stem rust resistance loci. At the seedling stage, the reaction of the common stem rust race QFCSC in Nebraska was measured in a set of 212 genotypes from F_3:6 lines. The results indicated that 184 genotypes (86.8%) had different degrees of resistance to this common race. While 28 genotypes (13.2%) were susceptible to stem rust. A set of 11,911 single-nucleotide polymorphism (SNP) markers was used to perform GWAS which detected 84 significant marker-trait associations (MTAs) with SNPs located on chromosomes 1B, 2A, 2B, 7B and an unknown chromosome. Promising high linkage disequilibrium (LD) genomic regions were found in all chromosomes except 2B which suggested they include candidate genes controlling stem rust resistance. Highly significant LD was found among these 59 significant SNPs on chromosome 2A and 12 significant SNPs with an unknown chromosomal position. The LD analysis between SNPs located on 2A and Sr38 gene reveal high significant LD genomic regions which was previously reported. To select the most promising stem rust resistant genotypes, a new approach was suggested based on four criteria including, phenotypic selection, number of resistant allele(s), the genetic distance among the selected parents, and number of the different resistant allele(s) in the candidate crosses. As a result, 23 genotypes were considered as the most suitable parents for crossing to produce highly resistant stem rust genotypes against the QFCSC.

A robust KASP marker for selection of four pairs of linked leaf rust and stripe rust resistance genes introgressed on chromosome arm 5DS from different wheat genomes

Stripe rust and leaf rust are among the most devastating diseases of wheat, limiting its production globally. Wheat wild relatives harbour genetic diversity for new genes and alleles for all major wheat diseases. However, the use of this genetic variation from wild progenitor and non-progenitor species has been limited in the breeding programs. Reasons include limited recombination of donor and recipient genomes and the lack of tertiary gene pool markers. Here, we describe the development of a SNP based marker from the flow-sorted and sequenced Aegilops umbellulata chromosome 5U which can be used for marker assisted selection of four pair of alien leaf rust and stripe rust resistance genes. Lr57-Yr40_CAPS16 marker was reported earlier to be linked with alien leaf and stripe rust resistance genes introgressed on wheat chromosome 5DS. Due to its dominant nature and laborious to work with, a new SNP-based KASP marker, XTa5DS-2754099_kasp23, was developed from the same CAPS marker contig. XTa5DS-2754099_kasp23 was tested in Aegilops umbellulata, Ae. geniculata, Ae. peregrina and Ae. caudata derived alien introgression lines, which harbour four pairs of linked leaf and stripe rust genes; Lr76-Yr70, Lr57-Yr40, LrP- YrP, LrAc-YrAc, respectively. This KASP marker was found to be effective for the selection of the aforesaid four pairs of leaf rust and stripe rust resistance genes. Further, we tested and validated XTa5DS-2754099_kasp23 on commercial varieties and advanced breeding lines from four countries (India, Egypt, Australia and UK) including hexaploid and durum wheat. Our results provide evidence that KASP marker, XTa5DS-2754099_kasp23 can be used in marker-assisted selection of the four pairs of rust resistance alien genes in wheat breeding programmes.

QTL-Seq and Transcriptome Analysis Disclose Major QTL and Candidate Genes Controlling Leaf Size in Sesame (Sesamum indicum L.)

Leaf size is a crucial component of sesame (Sesamum indicum L.) plant architecture and further influences yield potential. Despite that it is well known that leaf size traits are quantitative traits controlled by large numbers of genes, quantitative trait loci (QTL) and candidate genes for sesame leaf size remain poorly understood. In the present study, we combined the QTL-seq approach and SSR marker mapping to identify the candidate genomic regions harboring QTL controlling leaf size traits in an RIL population derived from a cross between sesame varieties Zhongzhi No. 13 (with big leaves) and ZZM2289 (with small leaves). The QTL mapping revealed 56 QTL with phenotypic variation explained (PVE) from 1.87 to 27.50% for the length and width of leaves at the 1/3 and 1/2 positions of plant height. qLS15-1, a major and environmentally stable pleiotropic locus for both leaf length and width explaining 5.81 to 27.50% phenotypic variation, was located on LG15 within a 408-Kb physical genomic region flanked by the markers ZMM6185 and ZMM6206. In this region, a combination of transcriptome analysis with gene annotations revealed three candidate genes SIN_1004875, SIN_1004882, and SIN_1004883 associated with leaf growth and development in sesame. These findings provided insight into the genetic characteristics and variability for sesame leaf and set up the foundation for future genomic studies on sesame leaves and will serve as gene resources for improvement of sesame plant architecture.

The Genetic Basis of Tomato Aroma

Tomato (Solanum lycopersicum L.) aroma is determined by the interaction of volatile compounds (VOCs) released by the tomato fruits with receptors in the nose, leading to a sensorial impression, such as "sweet", "smoky", or "fruity" aroma. Of the more than 400 VOCs released by tomato fruits, 21 have been reported as main contributors to the perceived tomato aroma. These VOCs can be grouped in five clusters, according to their biosynthetic origins. In the last decades, a vast array of scientific studies has investigated the genetic component of tomato aroma in modern tomato cultivars and their relatives. In this paper we aim to collect, compare, integrate and summarize the available literature on flavour-related QTLs in tomato. Three hundred and 5ifty nine (359) QTLs associated with tomato fruit VOCs were physically mapped on the genome and investigated for the presence of potential candidate genes. This review makes it possible to (i) pinpoint potential donors described in literature for specific traits, (ii) highlight important QTL regions by combining information from different populations, and (iii) pinpoint potential candidate genes. This overview aims to be a valuable resource for researchers aiming to elucidate the genetics underlying tomato flavour and for breeders who aim to improve tomato aroma.

Genomic regions associated with stripe rust resistance against the Egyptian race revealed by genome-wide association study

BACKGROUND

Wheat stripe rust (caused by Puccinia striiformis f. sp. Tritici), is a major disease that causes huge yield damage. New pathogen races appeared in the last few years and caused a broke down in the resistant genotypes. In Egypt, some of the resistant genotypes began to be susceptible to stripe rust in recent years. This situation increases the need to produce new genotypes with durable resistance. Besides, looking for a new resistant source from the available wheat genotypes all over the world help in enhancing the breeding programs.

RESULTS

In the recent study, a set of 103-spring wheat genotypes from different fourteen countries were evaluated to their field resistant to stripe rust for two years. These genotypes included 17 Egyptian genotypes from the old and new cultivars. The 103-spring wheat genotypes were reported to be well adapted to the Egyptian environmental conditions. Out of the tested genotypes, eight genotypes from four different countries were found to be resistant in both years. Genotyping was carried out using genotyping-by-sequencing and a set of 26,703 SNPs were used in the genome-wide association study. Five SNP markers, located on chromosomes 2A and 4A, were found to be significantly associated with the resistance in both years. Three gene models associated with disease resistance and underlying these significant SNPs were identified. One immune Iranian genotype, with the highest number of different alleles from the most resistant Egyptian genotypes, was detected.

CONCLUSION

the high variation among the tested genotypes in their resistance to the Egyptian stripe rust race confirming the possible improvement of stripe rust resistance in the Egyptian wheat genotypes. The identified five SNP markers are stable and could be used in marker-assisted selection after validation in different genetic backgrounds. Crossing between the immune Iranian genotype and the Egyptian genotypes will improve stripe rust resistance in Egypt.

GWAS revealed effect of genotype × environment interactions for grain yield of Nebraska winter wheat

Background

Improving grain yield in cereals especially in wheat is a main objective for plant breeders. One of the main constrains for improving this trait is the G × E interaction (GEI) which affects the performance of wheat genotypes in different environments. Selecting high yielding genotypes that can be used for a target set of environments is needed. Phenotypic selection can be misleading due to the environmental conditions. Incorporating information from phenotypic and genomic analyses can be useful in selecting the higher yielding genotypes for a group of environments.

Results

A set of 270 F_3:6 wheat genotypes in the Nebraska winter wheat breeding program was tested for grain yield in nine environments. High genetic variation for grain yield was found among the genotypes. G × E interaction was also highly significant. The highest yielding genotype differed in each environment. The correlation for grain yield among the nine environments was low (0 to 0.43). Genome-wide association study revealed 70 marker traits association (MTAs) associated with increased grain yield. The analysis of linkage disequilibrium revealed 16 genomic regions with a highly significant linkage disequilibrium (LD). The candidate parents’ genotypes for improving grain yield in a group of environments were selected based on three criteria; number of alleles associated with increased grain yield in each selected genotype, genetic distance among the selected genotypes, and number of different alleles between each two selected parents.

Conclusion

Although G × E interaction was present, the advances in DNA technology provided very useful tools and analyzes. Such features helped to genetically select the highest yielding genotypes that can be used to cross grain production in a group of environments.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-020-07308-0.

Modeling multiple phenotypes in wheat using data-driven genomic exploratory factor analysis and Bayesian network learning

Inferring trait networks from a large volume of genetically correlated diverse phenotypes such as yield, architecture, and disease resistance can provide information on the manner in which complex phenotypes are interrelated. However, studies on statistical methods tailored to multidimensional phenotypes are limited, whereas numerous methods are available for evaluating the massive number of genetic markers. Factor analysis operates at the level of latent variables predicted to generate observed responses. The objectives of this study were to illustrate the manner in which data-driven exploratory factor analysis can map observed phenotypes into a smaller number of latent variables and infer a genomic latent factor network using 45 agro-morphological, disease, and grain mineral phenotypes measured in synthetic hexaploid wheat lines (Triticum aestivum L.). In total, eight latent factors including grain yield, architecture, flag leaf-related traits, grain minerals, yellow rust, two types of stem rust, and leaf rust were identified as common sources of the observed phenotypes. The genetic component of the factor scores for each latent variable was fed into a Bayesian network to obtain a trait structure reflecting the genetic interdependency among traits. Three directed paths were consistently identified by two Bayesian network algorithms. Flag leaf-related traits influenced leaf rust, and yellow rust and stem rust influenced grain yield. Additional paths that were identified included flag leaf-related traits to minerals and minerals to architecture. This study shows that data-driven exploratory factor analysis can reveal smaller dimensional common latent phenotypes that are likely to give rise to numerous observed field phenotypes without relying on prior biological knowledge. The inferred genomic latent factor structure from the Bayesian network provides insights for plant breeding to simultaneously improve multiple traits, as an intervention on one trait will affect the values of focal phenotypes in an interrelated complex trait system.

Mapping genomic regions of moisture deficit stress tolerance using backcross inbred lines in wheat (Triticum aestivum L.)

Identification of markers associated with major physiological and yield component traits under moisture deficit stress conditions in preferred donor lines paves the way for marker-assisted selection (MAS). In the present study, a set of 183 backcross inbred lines (BILs) derived from the cross HD2733/2*C306 were genotyped using 35K Axiom genotyping array and SSR markers. The multi-trait, multi-location field phenotyping of BILs was done at three locations covering two major wheat growing zones of India, north-western plains zone (NWPZ) and central zone (CZ) under varying moisture regimes. A linkage map was constructed using 705 SNPs and 86 SSR polymorphic markers. A total of 43 genomic regions and QTL × QTL epistatic interactions were identified for 14 physiological and yield component traits, including NDVI, chlorophyll content, CT, CL, PH, GWPS, TGW and GY. Chromosomes 2A, 5D, 5A and 4B harbors greater number of QTLs for these traits. Seven Stable QTLs were identified across environment for DH (QDh.iari_6D), GWPS (QGWPS.iari_5B), PH (QPh.iari_4B-2, QPh.iari_4B-3) and NDVI (QNdvi1.iari_5D, QNdvi3.iari_5A). Nine genomic regions identified carrying major QTLs for CL, NDVI, RWC, FLA, PH, TGW and biomass explaining 10.32–28.35% of the phenotypic variance. The co-segregation of QTLs of physiological traits with yield component traits indicate the pleiotropic effects and their usefulness in the breeding programme. Our findings will be useful in dissecting genetic nature and marker-assisted selection for moisture deficit stress tolerance in wheat.

Linkage mapping and QTL analysis of flowering time using ddRAD sequencing with genotype error correction in Brassica napus

BACKGROUND

Brassica napus is an important oilseed crop cultivated worldwide. During domestication and breeding of B. napus, flowering time has been a target of selection because of its substantial impact on yield. Here we use double digest restriction-site associated DNA sequencing (ddRAD) to investigate the genetic basis of flowering in B. napus. An F₂ mapping population was derived from a cross between an early-flowering spring type and a late-flowering winter type.

RESULTS

Flowering time in the mapping population differed by up to 25 days between individuals. High genotype error rates persisted after initial quality controls, as suggested by a genotype discordance of ~ 12% between biological sequencing replicates. After genotype error correction, a linkage map spanning 3981.31 cM and compromising 14,630 single nucleotide polymorphisms (SNPs) was constructed. A quantitative trait locus (QTL) on chromosome C2 was detected, covering eight flowering time genes including FLC.

CONCLUSIONS

These findings demonstrate the effectiveness of the ddRAD approach to sample the B. napus genome. Our results also suggest that ddRAD genotype error rates can be higher than expected in F₂ populations. Quality filtering and genotype correction and imputation can substantially reduce these error rates and allow effective linkage mapping and QTL analysis.

Development of a highly efficient 50K single nucleotide polymorphism genotyping array for the large and complex genome of Norway spruce (Picea abies L. Karst) by whole genome resequencing and its transferability to other spruce species

Norway spruce (Picea abies L. Karst) is one of the most important forest tree species with significant economic and ecological impact in Europe. For decades, genomic and genetic studies on Norway spruce have been challenging due to the large and repetitive genome (19.6 Gb with more than 70% being repetitive). To accelerate genomic studies, including population genetics, genome‐wide association studies (GWAS) and genomic selection (GS), in Norway spruce and related species, we here report on the design and performance of a 50K single nucleotide polymorphism (SNP) genotyping array for Norway spruce. The array is developed based on whole genome resequencing (WGS), making it the first WGS‐based SNP array in any conifer species so far. After identifying SNPs using genome resequencing data from 29 trees collected in northern Europe, we adopted a two‐step approach to design the array. First, we built a 450K screening array and used this to genotype a population of 480 trees sampled from both natural and breeding populations across the Norway spruce distribution range. These samples were then used to select high‐confidence probes that were put on the final 50K array. The SNPs selected are distributed over 45,552 scaffolds from the P. abies version 1.0 genome assembly and target 19,954 unique gene models with an even coverage of the 12 linkage groups in Norway spruce. We show that the array has a 99.5% probe specificity, >98% Mendelian allelic inheritance concordance, an average sample call rate of 96.30% and an SNP call rate of 98.90% in family trios and haploid tissues. We also observed that 23,797 probes (50%) could be identified with high confidence in three other spruce species (white spruce [Picea glauca], black spruce [P. mariana] and Sitka spruce [P. sitchensis]). The high‐quality genotyping array will be a valuable resource for genetic and genomic studies in Norway spruce as well as in other conifer species of the same genus.

How Machine Learning Methods Helped Find Putative Rye Wax Genes Among GBS Data

The standard approach to genetic mapping was supplemented by machine learning (ML) to establish the location of the rye gene associated with epicuticular wax formation (glaucous phenotype). Over 180 plants of the biparental F2 population were genotyped with the DArTseq (sequencing-based diversity array technology). A maximum likelihood (MLH) algorithm (JoinMap 5.0) and three ML algorithms: logistic regression (LR), random forest and extreme gradient boosted trees (XGBoost), were used to select markers closely linked to the gene encoding wax layer. The allele conditioning the nonglaucous appearance of plants, derived from the cultivar Karlikovaja Zelenostebelnaja, was mapped at the chromosome 2R, which is the first report on this localization. The DNA sequence of DArT-Silico 3585843, closely linked to wax segregation detected by using ML methods, was indicated as one of the candidates controlling the studied trait. The putative gene encodes the ABCG11 transporter.

Identification of Quantitative Trait Loci Relating to Flowering Time, Flag Leaf and Awn Characteristics in a Novel Triticum dicoccum Mapping Population

Tetraploid landraces of wheat harbour genetic diversity that could be introgressed into modern bread wheat with the aid of marker-assisted selection to address the genetic diversity bottleneck in the breeding genepool. A novel bi-parental Triticum turgidum ssp. dicoccum Schrank mapping population was created from a cross between two landrace accessions differing for multiple physiological traits. The population was phenotyped for traits hypothesised to be proxies for characteristics associated with improved photosynthesis or drought tolerance, including flowering time, awn length, flag leaf length and width, and stomatal and trichome density. The mapping individuals and parents were genotyped with the 35K Wheat Breeders’ single nucleotide polymorphism (SNP) array. A genetic linkage map was constructed from 104 F4 individuals, consisting of 2066 SNPs with a total length of 3295 cM and an average spacing of 1.6 cM. Using the population, 10 quantitative trait loci (QTLs) for five traits were identified in two years of trials. Three consistent QTLs were identified over both trials for awn length, flowering time and flag leaf width, on chromosomes 4A, 7B and 5B, respectively. The awn length and flowering time QTLs correspond with the major loci Hd and Vrn-B3, respectively. The identified marker-trait associations could be developed for marker-assisted selection, to aid the introgression of diversity from a tetraploid source into modern wheat for potential physiological trait improvement.

Molecular genetic analysis of spring wheat core collection using genetic diversity, population structure, and linkage disequilibrium

Background

Wheat (Triticum aestivium L.) is an important crop globally which has a complex genome. To identify the parents with useful agronomic characteristics that could be used in the various breeding programs, it is very important to understand the genetic diversity among global wheat genotypes. Also, understanding the genetic diversity is useful in breeding studies such as marker-assisted selection (MAS), genome-wide association studies (GWAS), and genomic selection.

Results

To understand the genetic diversity in wheat, a set of 103 spring wheat genotypes which represented five different continents were used. These genotypes were genotyped using 36,720 genotyping-by-sequencing derived SNPs (GBS-SNPs) which were well distributed across wheat chromosomes. The tested 103-wheat genotypes contained three different subpopulations based on population structure, principle coordinate, and kinship analyses. A significant variation was found within and among the subpopulations based on the AMOVA. Subpopulation 1 was found to be the more diverse subpopulation based on the different allelic patterns (Na, Ne, I, h, and uh). No high linkage disequilibrium was found between the 36,720 SNPs. However, based on the genomic level, D genome was found to have the highest LD compared with the two other genomes A and B. The ratio between the number of significant LD/number of non-significant LD suggested that chromosomes 2D, 5A, and 7B are the highest LD chromosomes in their genomes with a value of 0.08, 0.07, and 0.05, respectively. Based on the LD decay, the D genome was found to be the lowest genome with the highest number of haplotype blocks on chromosome 2D.

Conclusion

The recent study concluded that the 103-spring wheat genotypes and their GBS-SNP markers are very appropriate for GWAS studies and QTL-mapping. The core collection comprises three different subpopulations. Genotypes in subpopulation 1 are the most diverse genotypes and could be used in future breeding programs if they have desired traits. The distribution of LD hotspots across the genome was investigated which provides useful information on the genomic regions that includes interesting genes.

Combining QTL Analysis and Genomic Predictions for Four Durum Wheat Populations Under Drought Conditions

Durum wheat is an important crop for the human diet and its consumption is gaining popularity. In order to ensure that durum wheat production maintains the pace with the increase in demand, it is necessary to raise productivity by approximately 1.5% per year. To deliver this level of annual genetic gain the incorporation of molecular strategies has been proposed as a key solution. Here, four RILs populations were used to conduct QTL discovery for grain yield (GY) and 1,000 kernel weight (TKW). A total of 576 individuals were sown at three locations in Morocco and one in Lebanon. These individuals were genotyped by sequencing with 3,202 high-confidence polymorphic markers, to derive a consensus genetic map of 2,705.7 cM, which was used to impute any missing data. Six QTLs were found to be associated with GY and independent from flowering time on chromosomes 2B, 4A, 5B, 7A and 7B, explaining a phenotypic variation (PV) ranging from 4.3 to 13.4%. The same populations were used to train genomic prediction models incorporating the relationship matrix, the genotype by environment interaction, and marker by environment interaction, to reveal significant advantages for models incorporating the marker effect. Using training populations (TP) in full sibs relationships with the validation population (VP) was shown to be the only effective strategy, with accuracies reaching 0.35–0.47 for GY. Reducing the number of markers to 10% of the whole set, and the TP size to 20% resulted in non-significant changes in accuracies. The QTLs identified were also incorporated in the models as fixed effects, showing significant accuracy gain for all four populations. Our results confirm that the prediction accuracy depends considerably on the relatedness between TP and VP, but not on the number of markers and size of TP used. Furthermore, feeding the model with information on markers associated with QTLs increased the overall accuracy.

Fine mapping and gene cloning in the post-NGS era: advances and prospects

Improvement in traits of agronomic importance is the top breeding priority of crop improvement programs. Majority of these agronomic traits show complex quantitative inheritance. Identification of quantitative trait loci (QTLs) followed by fine mapping QTLs and cloning of candidate genes/QTLs is central to trait analysis. Advances in genomic technologies revolutionized our understanding of genetics of complex traits, and genomic regions associated with traits were employed in marker-assisted breeding or cloning of QTLs/genes. Next-generation sequencing (NGS) technologies have enabled genome-wide methodologies for the development of ultra-high-density genetic linkage maps in different crops, thus allowing placement of candidate loci within few kbs in genomes. In this review, we compare the marker systems used for fine mapping and QTL cloning in the pre- and post-NGS era. We then discuss how different NGS platforms in combination with advanced experimental designs have improved trait analysis and fine mapping. We opine that efficient genotyping/sequencing assays may circumvent the need for cumbersome procedures that were earlier used for fine mapping. A deeper understanding of the trait architectures of agricultural significance will be crucial to accelerate crop improvement.

Development of core-collections for Guizhou tea genetic resources and GWAS of leaf size using SNP developed by genotyping-by-sequencing

An accurate depiction of the genetic relationship, the development of core collection, and genome-wide association analysis (GWAS) are key for the effective exploitation and utilization of genetic resources. Here, genotyping-by-sequencing (GBS) was used to characterize 415 tea accessions mostly collected from the Guizhou region in China. A total of 30,282 high-quality SNPs was used to estimate the genetic relationships, develop core collections, and perform GWAS. We suggest 198 and 148 accessions to represent the core set and mini-core set, which consist of 47% and 37% of the whole collection, respectively, and contain 93–95% of the total SNPs. Furthermore, the frequencies of all alleles and genotypes in the whole set were very well retained in the core set and mini-core set. The 415 accessions were clustered into 14 groups and the core and the mini-core collections contain accessions from each group, species, cultivation status and growth habit. By analyzing the significant SNP markers associated with multiple traits, nine SNPs were found to be significantly associated with four leaf size traits, namely MLL, MLW, MLA and MLSI (P < 1.655E−06). This study characterized the genetic distance and relationship of tea collections, suggested the core collections, and established an efficient GWAS analysis of GBS result.

QTL mapping for flag leaf-related traits and genetic effect of QFLW-6A on flag leaf width using two related introgression line populations in wheat

The flag leaf is the main organ of photosynthesis during grain-filling period of wheat, and flag leaf-related traits affect plant morphology and yield potential. In this study, two BC₃F₆ introgression line (IL) populations derived from the common recipient parent Lumai 14 with Jing 411 and Shaanhan 8675, respectively, were used to map quantitative trait loci (QTL) for flag leaf length (FLL), flag leaf width (FLW), flag leaf area (FLA) and chlorophyll content (CC) at flowering stage and 15 and 20 days after anthesis (DAA) in 2016–2017 (E1) and 2017–2018 (E2) two environments. A total of 14 and 15 QTLs for flag leaf-related traits were detected in Lumai 14 / Jing 411 and Lumai 14 / Shaanhan 8675 populations, respectively. Among them, Both QFLW-6A and QFLA-6A were detected in Lumai 14 / Jing 411 population under E2 and in Lumai 14 / Shaanhan 8675 population under E1 and E2 environments, respectively. QCC_S2-3A from Lumai 14 / Jing 411 population and QCC_S3-1A, QFLL-4A and QFLL-6A from Lumai 14 / Shaanhan 8675 population were repeatedly identified under two tested environments. Moreover, eight QTL clusters controlling flag leaf-related traits were identified, which provided a genetic basis for significant correlations in phenotype among these traits. On the other hand, positive alleles of QFLW-6A for FLW detected in two populations were derived from their donors. Eighteen lines and 44 lines carried this QTL were found in Lumai 14 / Jing 411 and Lumai 14 / Shaanhan 8675 populations, respectively. The means of FLW in these lines were wider than that of the recipient parent, Lumai 14, in two environments, suggesting that QFLW-6A played an important role for increasing FLW. The IL 124 in Lumai 14 / Jing 411 population and the IL 59 and IL 127 in Lumai 14 / Shaanhan 8675 population had five, five and four donor chromosomal segments which carried no other QTL controlling FLW than QFLW-6A, respectively. And the FLWs of these lines were significantly greater than that of Lumai 14 under two environments. So these lines and their donor parent can be regarded as potential near-isogenic lines. Further, a synteny analysis found QFLW-6A was near the 574,283,851–574,283,613 bp fragment on chromosome 6A and 10 genes were in the range of 500 kb upstream and downstream of the fragment. These results provide the basis for identification of candidate gene and map-based cloning and functional verification of the QTL.

Aegilops umbellulata introgression carrying leaf rust and stripe rust resistance genes Lr76 and Yr70 located to 9.47-Mb region on 5DS telomeric end through a combination of chromosome sorting and sequencing

Lr76 and Yr70 have been fine mapped using the sequence of flow-sorted recombinant 5D chromosome from wheat-Ae. umbellulata introgression line. The alien introgression has been delineated to 9.47-Mb region on short arm of wheat chromosome 5D. Leaf rust and stripe rust are among the most damaging diseases of wheat worldwide. Wheat cultivation based on limited number of rust resistance genes deployed over vast areas expedites the emergence of new pathotypes warranting a continuous deployment of new resistance genes. In this paper, fine mapping of Aegilops umbellulata-derived leaf rust and stripe rust resistance genes Lr76 and Yr70 is being reported. We flow sorted and paired-end sequenced 5U chromosome of Ae. umbellulata, recombinant chromosome 5D (5D^IL) from wheat-Ae. umbellulata introgression line pau16057 and 5D^RP of recurrent parent WL711. Chromosome 5U reads were mapped against the reference Chinese Spring chromosome 5D sequence, and alien-specific SNPs were identified. Chromosome 5D^IL and 5D^RP sequences were de novo assembled, and alien introgression-specific markers were designed by selecting 5U- and 5D-specific SNPs. Overall, 27 KASP markers were mapped in high-resolution population consisting of 1404 F₅ RILs. The mapping population segregated for single gene each for leaf rust and stripe rust resistance. The physical order of the SNPs in pau16057 was defined by projecting the 27 SNPs against the IWGSC RefSeq v1.0 sequence. Based on this physical map, the size of Ae. umbellulata introgression was determined to be 9.47 Mb on the distal most end of the short arm of chromosome 5D. This non-recombining alien segment carries six NB-LRR encoding genes based on NLR annotation of assembled chromosome 5D^IL sequence and IWGSC RefSeq v1.1 gene models. The presence of SNPs and other sequence variations in these genes between pau16057 and WL711 suggested that they are candidates for Lr76 and Yr70.

QTL mapping for yield-related traits in wheat based on four RIL populations

Eight environmentally stable QTL for grain yield-related traits were detected by four RIL populations, and two of them were validated by a natural wheat population containing 580 diverse varieties or lines. Yield and yield-related traits are important factors in wheat breeding. In this study, four RIL populations derived from the cross of one common parent Yanzhan 1 (a Chinese domesticated cultivar) and four donor parents including Hussar (a British domesticated cultivar) and three semi-wild wheat varieties in China were phenotyped for 11 yield-related traits in eight environments. An integrated genetic map containing 2009 single-nucleotide polymorphism (SNP) markers generated from a 90 K SNP array was constructed to conduct quantitative trait loci (QTL) analysis. A total of 161 QTL were identified, including ten QTL for grain yield per plant (GYP) and yield components, 49 QTL for spike-related traits, 43 QTL for flag leaf-related traits, 22 QTL for plant height (PH), and 37 QTL for heading date and flowering date. Eight environmentally stable QTL were validated in individual RIL population where the target QTL was notably detected, and six of them had a significant effect on GYP. Furthermore, Two QTL, QSPS-2A.4 and QSL-4A.1, were also validated in a natural wheat population containing 580 diverse varieties or lines, which provided valuable resources for further fine mapping and genetic improvement in yield in wheat.

Identification of quantitative trait loci associated with nitrogen use efficiency in winter wheat

Maintaining winter wheat (Triticum aestivum L.) productivity with more efficient nitrogen (N) management will enable growers to increase profitability and reduce the negative environmental impacts associated with nitrogen loss. Wheat breeders would therefore benefit greatly from the identification and application of genetic markers associated with nitrogen use efficiency (NUE). To investigate the genetics underlying N response, two bi-parental mapping populations were developed and grown in four site-seasons under low and high N rates. The populations were derived from a cross between previously identified high NUE parents (VA05W-151 and VA09W-52) and a shared common low NUE parent, ‘Yorktown.’ The Yorktown × VA05W-151 population was comprised of 136 recombinant inbred lines while the Yorktown × VA09W-52 population was comprised of 138 doubled haploids. Phenotypic data was collected on parental lines and their progeny for 11 N-related traits and genotypes were sequenced using a genotyping-by-sequencing platform to detect more than 3,100 high quality single nucleotide polymorphisms in each population. A total of 130 quantitative trait loci (QTL) were detected on 20 chromosomes, six of which were associated with NUE and N-related traits in multiple testing environments. Two of the six QTL for NUE were associated with known photoperiod (Ppd-D1 on chromosome 2D) and disease resistance (FHB-4A) genes, two were reported in previous investigations, and one QTL, QNue.151-1D, was novel. The NUE QTL on 1D, 6A, 7A, and 7D had LOD scores ranging from 2.63 to 8.33 and explained up to 18.1% of the phenotypic variation. The QTL identified in this study have potential for marker-assisted breeding for NUE traits in soft red winter wheat.