Genetic insights into superior grain number traits: a QTL analysis of wheat-Agropyron cristatum derivative pubing3228

BACKGROUND

Agropyron cristatum (L.) is a valuable genetic resource for expanding the genetic diversity of common wheat. Pubing3228, a novel wheat-A. cristatum hybrid germplasm, exhibits several desirable agricultural traits, including high grain number per spike (GNS). Understanding the genetic architecture of GNS in Pubing3228 is crucial for enhancing wheat yield. This study aims to analyze the specific genetic regions and alleles associated with high GNS in Pubing3228.

METHODS

The study employed a recombination inbred line (RIL) population derived from a cross between Pubing3228 and Jing4839 to investigate the genetic regions and alleles linked to high GNS. Quantitative Trait Loci (QTL) analysis and candidate gene investigation were utilized to explore these traits.

RESULTS

A total of 40 QTLs associated with GNS were identified across 16 chromosomes, accounting for 4.25-17.17% of the total phenotypic variation. Five QTLs (QGns.wa-1D, QGns.wa-5 A, QGns.wa-7Da.1, QGns.wa-7Da.2 and QGns.wa-7Da.3) accounter for over 10% of the phenotypic variation in at least two environments. Furthermore, 94.67% of the GNS QTL with positive effects originated from Pubing3228. Candidate gene analysis of stable QTLs identified 11 candidate genes for GNS, including a senescence-associated protein gene (TraesCS7D01G148000) linked to the most significant SNP (AX-108,748,734) on chromosome 7D, potentially involved in reallocating nutrients from senescing tissues to developing seeds.

CONCLUSION

This study provides new insights into the genetic mechanisms underlying high GNS in Pubing3228, offering valuable resources for marker-assisted selection in wheat breeding to enhance yield.

Genome-wide association study of growth curve parameters reveals novel genomic regions and candidate genes associated with metatarsal bone traits in chickens

The growth and development of chicken bones have an enormous impact on the health and production performance of chickens. However, the development pattern and genetic regulation of the chicken skeleton are poorly understood. This study aimed to evaluate metatarsal bone growth and development patterns in chickens via non-linear models, and to identify the genetic determinants of metatarsal bone traits using a genome-wide association study (GWAS) based on growth curve parameters. Data on metatarsal length (MeL) and metatarsal circumference (MeC) were obtained from 471 F2 chickens (generated by crossing broiler sires, derived from a line selected for high abdominal fat, with Baier layer dams) at 4, 6, 8, 10, and 12 weeks of age. Four non-linear models (Gompertz, Logistic, von Bertalanffy, and Brody) were used to fit the MeL and MeC growth curves. Subsequently, the estimated growth curve parameters of the mature MeL or MeC (A), time-scale parameter (b), and maturity rate (K) from the non-linear models were utilized as substitutes for the original bone data in GWAS. The Logistic and Brody models displayed the best goodness-of-fit for MeL and MeC, respectively. Single-trait and multi-trait GWASs based on the growth curve parameters of the Logistic and Brody models revealed 4 618 significant single nucleotide polymorphisms (SNPs), annotated to 332 genes, associated with metatarsal bone traits. The majority of these significant SNPs were located on Gallus gallus chromosome (GGA) 1 (167.433-176.318 Mb), GGA2 (96.791-103.543 Mb), GGA4 (65.003-83.104 Mb) and GGA6 (64.685-95.285 Mb). Notably, we identified 12 novel GWAS loci associated with chicken metatarsal bone traits, encompassing 35 candidate genes. In summary, the combination of single-trait and multi-trait GWASs based on growth curve parameters uncovered numerous genomic regions and candidate genes associated with chicken bone traits. The findings benefit an in-depth understanding of the genetic architecture underlying metatarsal growth and development in chickens.

Genetic mapping of deoxynivalenol and fusarium damaged kernel resistance in an adapted durum wheat population

BACKGROUND

Fusarium head blight (FHB) infection results in Fusarium damaged kernels (FDK) and deoxynivalenol (DON) contamination that are downgrading factors at the Canadian elevators. Durum wheat (Triticum turgidum L. var. durum Desf.) is particularly susceptible to FHB and most of the adapted Canadian durum wheat cultivars are susceptible to moderately susceptible to this disease. However, the durum line DT696 is less susceptible to FHB than commercially grown cultivars. Little is known about genetic variation for durum wheat ability to resist FDK infection and DON accumulation. This study was undertaken to map genetic loci conferring resistance to DON and FDK resistance using a SNP high-density genetic map of a DT707/DT696 DH population and to identify SNP markers useful in marker-assisted breeding. One hundred twenty lines were grown in corn spawn inoculated nurseries near Morden, MB in 2015, 2016 and 2017 and the harvested seeds were evaluated for DON. The genetic map of the population was used in quantitative trait locus analysis performed with MapQTL.6® software.

RESULTS

Four DON accumulation resistance QTL detected in two of the three years were identified on chromosomes 1 A, 5 A (2 loci) and 7 A and two FDK resistance QTL were identified on chromosomes 5 and 7 A in single environments. Although not declared significant due to marginal LOD values, the QTL for FDK on the 5 and 7 A were showing in other years suggesting their effects were real. DT696 contributed the favourable alleles for low DON and FDK on all the chromosomes. Although no resistance loci contributed by DT707, transgressive segregant lines were identified resulting in greater resistance than DT696. Breeder-friendly KASP markers were developed for two of the DON and FDK QTL detected on chromosomes 5 and 7 A. Markers flanking each QTL were physically mapped against the durum wheat reference sequence and candidate genes which might be involved in FDK and DON resistance were identified within the QTL intervals.

CONCLUSIONS

The DH lines harboring the desired resistance QTL will serve as useful resources in breeding for FDK and DON resistance in durum wheat. Furthermore, breeder-friendly KASP markers developed during this study will be useful for the selection of durum wheat varieties with low FDK and DON levels in durum wheat breeding programs.

Exploring SoySNP50K and USDA Germplasm Collection Data to Find New QTLs Associated with Protein and Oil Content in Brazilian Genotypes

Genetic diversity within a germplasm collection plays a vital role in the success of breeding programs. However, comprehending this diversity and identifying accessions with desirable traits pose significant challenges. This study utilized publicly available data to investigate SNP markers associated with protein and oil content in Brazilian soybeans. Through this research, twenty-two new QTLs (Quantitative Trait Loci) were identified, and we highlighted the substantial influence of Roanoke, Lee and Bragg ancestor on the genetic makeup of Brazilian soybean varieties. Our findings demonstrate that certain markers are being lost in modern cultivars, while others maintain or even increase their frequency. These observations indicate genomic regions that have undergone selection during soybean introduction in Brazil and could be valuable in breeding programs aimed at enhancing protein or oil content.

Molecular tagging of seed size using MITE markers in an induced large seed mutant with higher cotyledon cell size in groundnut

A large seed mutant, TG 89 having a 76.7% increment in hundred kernel weight in comparison to its parent TG 26, was isolated from an electron beam-induced mutagenized population. Studies based on environmental scanning electron microscopy of both parent and mutant revealed that the mutant seed cotyledon had significantly bigger cell size than parent. A mapping population with 122 F2 plants derived from the mutant and a distant normal seed genotype (ICGV 15007) was utilized to map the QTL associated with higher HKW. Bulk segregant analysis revealed putative association of three markers with this mutant large seed trait. Further, genotyping of F2 individuals with polymorphic markers detected 14 linkage groups with a map distance of 1053 cM. QTL analysis revealed a significant additive major QTL for the mutant large seed trait on linkage group A05 explaining 12.7% phenotypic variation for the seed size. This QTL was located between flanking markers AhTE333 and AhTE810 having a map interval of 4.7 cM which corresponds to 90.65 to 107.24 Mbp in A05 chromosome, respectively. Within this genomic fragment, an ortholog of the BIG SEEDS 1 gene was found at 102,476,137 bp. Real-time PCR revealed down-regulation of this BIG SEEDS 1 gene in the mutant indicating a loss of function mutation giving rise to a large seed phenotype. This QTL was validated in 11 advanced breeding lines having large seed size from this mutant but with varied genetic backgrounds. This validation showcased a highly promising selection accuracy of 90.9% for the marker-assisted selection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03909-0.

Development of introgression lines and mapping of qGW2, a novel QTL that confers grain width, in rice (Oryza sativa L.)

Rice grain size is a key determinant of both grain yield and quality. Identification of favorable alleles for use in rice breeding may help to meet the demand for increased yield. In this study, we developed a set of 210 introgression lines (ILs) by using indica variety Huanghuazhan as the donor parent and erect-panicle japonica rice variety Wuyujing3R as the recurrent parent. A total of 133 ILs were selected for high-throughput sequencing. Using specific-locus amplified fragment (SLAF) sequencing technology, 10,103 high-quality SLAF labels evenly distributed on 12 chromosomes were obtained and selected for subsequent analysis. Using a high-density map, quantitative trait locus (QTL) mapping of grain size-related traits was performed, and a total of 38 QTLs were obtained in two environments. Furthermore, qGW2, a novel QTL that controls grain width on chromosome 2, was validated and delimited to a region of 309 kb via substitution mapping. These findings provide new genetic material and a basis for future fine mapping and cloning of favorable QTLs.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-024-01453-0.

Comparison of the genetic basis of salt tolerance at germination, seedling, and reproductive stages in an introgression line population of rice

BACKGROUND

Salinity is a major limitation for rice farming due to climate change. Since salt stress adversely impact rice plants at germination, seedling, and reproductive stages resulting in poor crop establishment and reduced grain yield, enhancing salt tolerance at these vulnerable growth stages will enhance rice productivity in salinity prone areas.

METHODS AND RESULTS

An introgression line (ILs) population from a cross between a high yielding cultivar 'Cheniere' and a salt tolerant donor 'TCCP' was evaluated to map quantitative trait loci (QTLs) for traits associated with salt tolerance at germination, seedling, and reproductive stages. Using a genotyping-by-sequencing based high density SNP linkage map, a total of 7, 16, and 30 QTLs were identified for five germination traits, seven seedling traits, and ten reproductive traits, respectively. There was overlapping of QTLs for some traits at different stages indicating the pleiotropic effects of these QTLs or clustering of linked genes. Candidate genes identified for salt tolerance were OsSDIR1 and SERF for the seedling stage, WRKY55 and OsUBC for the reproductive stage, and MYB family transcription factors for all three stages. Gene ontology analysis revealed significant GO terms related to nucleotide binding, protein binding, protein kinase activity, antiporter activity, active transmembrane transporter activity, calcium-binding protein, and F- box protein interaction domain containing protein.

CONCLUSIONS

The colocalized QTLs for traits at different growth stages would be helpful to improve multiple traits simultaneously using marker-assisted selection. The salt tolerant ILs have the potential to be released as varieties or as pre-breeding lines for developing salt tolerant rice varieties.

Genotyping by sequencing for the construction of oil palm (Elaeis guineensis Jacq.) genetic linkage map and mapping of yield related quantitative trait loci

Background

Oil palm (Elaeis guineensis Jacq.) is one of the major oil-producing crops. Improving the quality and increasing the production yield of oil palm have been the primary focuses of both conventional and modern breeding approaches. However, the conventional breeding approach for oil palm is very challenging due to its longevity, which results in a long breeding cycle. Thus, the establishment of marker assisted selection (MAS) for oil palm breeding programs would speed up the breeding pipeline by generating new oil palm varieties that possess high commercial traits. With the decreasing cost of sequencing, Genotyping-by-sequencing (GBS) is currently feasible to many researchers and it provides a platform to accelerate the discovery of single nucleotide polymorphism (SNP) as well as insertion and deletion (InDel) markers for the construction of a genetic linkage map. A genetic linkage map facilitates the identification of significant DNA regions associated with the trait of interest via quantitative trait loci (QTL) analysis.

Methods

A mapping population of 112 F1 individuals from a cross of Deli dura and Serdang pisifera was used in this study. GBS libraries were constructed using the double digestion method with HindIII and TaqI enzymes. Reduced representation libraries (RRL) of 112 F1 progeny and their parents were sequenced and the reads were mapped against the E. guineensis reference genome. To construct the oil palm genetic linkage map, informative SNP and InDel markers were used to discover significant DNA regions associated with the traits of interest. The nine traits of interest in this study were fresh fruit bunch (FFB) yield, oil yield (OY), oil to bunch ratio (O/B), oil to dry mesocarp ratio (O/DM) ratio, oil to wet mesocarp ratio (O/WM), mesocarp to fruit ratio (M/F), kernel to fruit ratio (K/F), shell to fruit ratio (S/F), and fruit to bunch ratio (F/B).

Results

A total of 2.5 million SNP and 153,547 InDel markers were identified. However, only a subset of 5,278 markers comprising of 4,838 SNPs and 440 InDels were informative for the construction of a genetic linkage map. Sixteen linkage groups were produced, spanning 2,737.6 cM for the maternal map and 4,571.6 cM for the paternal map, with average marker densities of one marker per 2.9 cM and one per 2.0 cM respectively, were produced. A QTL analysis was performed on nine traits; however, only QTL regions linked to M/F, K/F and S/F were declared to be significant. Of those QTLs were detected: two for M/F, four for K/F and one for S/F. These QTLs explained 18.1-25.6% of the phenotypic variance and were located near putative genes, such as casein kinase II and the zinc finger CCCH domain, which are involved in seed germination and growth. The identified QTL regions for M/F, K/F and S/F from this study could be applied in an oil palm breeding program and used to screen palms with desired traits via marker assisted selection (MAS).

Genome-wide meta-analysis of 92 cardiometabolic protein serum levels

OBJECTIVES

Global cardiometabolic disease prevalence has grown rapidly over the years, making it the leading cause of death worldwide. Proteins are crucial components in biological pathways dysregulated in disease states. Identifying genetic components that influence circulating protein levels may lead to the discovery of biomarkers for early stages of disease or offer opportunities as therapeutic targets.

METHODS

Here, we carry out a genome-wide association study (GWAS) utilising whole genome sequencing data in 3,005 individuals from the HELIC founder populations cohort, across 92 proteins of cardiometabolic relevance.

RESULTS

We report 322 protein quantitative trait loci (pQTL) signals across 92 proteins, of which 76 are located in or near the coding gene (cis-pQTL). We link those association signals with changes in protein expression and cardiometabolic disease risk using colocalisation and Mendelian randomisation (MR) analyses.

CONCLUSIONS

The majority of previously unknown signals we describe point to proteins or protein interactions involved in inflammation and immune response, providing genetic evidence for the contributing role of inflammation in cardiometabolic disease processes.

QTL detection for rice grain storage protein content and genetic effect verifications

Rice grain quality is a multifarious attribute mainly governed by multiple nutritional factors. Grain protein is the central component of rice grain nutrition dominantly affecting eating-cooking qualities. Grain protein content is quantitatively influenced by its protein fractions. Genetic quantification of five protein fractions-albumins, globulins, prolamins, glutelin, and grain protein content-were evaluated by exploiting two BC3F2 mapping populations, derived from Kongyu131/TKM9 (population-I) and Kongyu131/Bg94-1 (population-II), which were grown in a single environment. Correlation studies among protein fractions and grain protein content were thoroughly investigated. A genetic linkage map was developed by using 146 single sequence repeat (SSR) markers in population-I and 167 markers in population-II. In total, 40 QTLs were delineated for five traits in both populations. Approximately 22 QTLs were dissected in population-I, derived from Kongyu131/TKM9, seven QTLs for albumin content, four QTLs for globulin content, three QTLs for prolamin content, four QTLs for glutelin content, and four QTLs for grain protein content. In total, 18 QTLs were detected in population-II, derived from Kongyu131/Bg94-1, five QTLs for albumin content, three QTLs for globulin content, four QTLs for prolamin content, two QTLs for glutelin content, and four QTLs for grain protein content. Three QTLs, qAlb7.1, Alb7.2, and qGPC7.2, derived from population-II (Kongyu131/Bg94-1) for albumin and grain protein content were successfully validated in the near isogenic line (NIL) populations. The localized chromosomal locus of the validated QTLs could be helpful for fine mapping via map-based cloning to discover underlying candidate genes. The functional insights of the underlying candidate gene would furnish novel perceptivity for the foundation of rice grain protein content and trigger the development of nutritionally important rice cultivars by combining marker-assisted selection (MAS) breeding.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01436-7.

Two QTL regions for spike length showing pleiotropic effects on Fusarium head blight resistance and thousand-grain weight in bread wheat (Triticum aestivum L.)

Spike length (SL) plays an important role in the yield improvement of wheat and is significantly associated with other traits. Here, we used a recombinant inbred line (RIL) population derived from a cross between Yangmai 12 (YM12) and Yanzhan 1 (YZ1) to construct a genetic linkage map and identify quantitative trait loci (QTL) for SL. A total of 5 QTL were identified for SL, among which QSl.yaas-3A and QSl.yaas-5B are two novel QTL for SL. The YZ1 alleles at QSl.yaas-2D and QSl.yaas-5A, and the YM12 alleles at QSl.yaas-2A, QSl.yaas-3A, and QSl.yaas-5B conferred increasing SL effects. Two major QTL QSl.yaas-5A and QSl.yaas-5B explained 9.11-15.85% and 9.01-12.85% of the phenotypic variations, respectively. Moreover, the positive alleles of QSl.yaas-5A and QSl.yaas-5B could significantly increase Fusarium head blight (FHB) resistance (soil surface inoculation and spray inoculation were used) and thousand-grain weight (TGW) in the RIL population. Kompetitive allele-specific PCR (KASP) markers for QSl.yaas-5A and QSl.yaas-5B were developed and validated in an additional panel of 180 wheat cultivars/lines. The cultivars/lines harboring both the positive alleles of QSl.yaas-5A and QSl.yaas-5B accounted for only 28.33% of the validation populations and had the longest SL, best FHB resistance (using spray inoculation), and highest TGW. A total of 358 and 200 high-confidence annotated genes in QSl.yaas-5A and QSl.yaas-5B were identified, respectively. Some of the genes in these two regions were involved in cell development, disease resistance, and so on. The results of this study will provide a basis for directional breeding of longer SL, higher TGW, and better FHB resistance varieties and a solid foundation for fine-mapping QSl.yaas-5A and QSl.yaas-5B in future.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01427-8.

Mycorrhizal status and host genotype interact to shape plant nutrition in field grown maize (Zea mays ssp. mays)

Arbuscular mycorrhizal fungi (AMF) establish symbioses with the major cereal crops, providing plants with increased access to nutrients while enhancing their tolerance to toxic heavy metals. However, not all plant varieties benefit equally from this association. In this study, we used quantitative trait loci (QTL) mapping to evaluate the combined effect of host genotypic variation (G) and AMF across 141 genotypes on the concentration of 20 mineral elements in the leaves and grain of field grown maize (Zea mays spp. mays). Our mapping design included selective incorporation of a castor AMF-incompatibility mutation, allowing estimation of AMF, QTL and QTLxAMF effects by comparison of mycorrhizal and non-mycorrhizal plants. Overall, AMF compatibility was associated with higher concentrations of boron (B), copper (Cu), molybdenum (Mo), phosphorus (P), selenium (Se) and zinc (Zn) and lower concentrations of arsenic (As), iron (Fe), magnesium (Mg), manganese (Mn), potassium (K) and strontium (Sr). In addition to effects on individual elements, pairwise correlation matrices for element concentration differed between mycorrhizal and non-mycorrhizal plants. We mapped 22 element QTLs, including 18 associated with QTLxAMF effects that indicate plant genotype-specific differences in the impact of AMF on the host ionome. Although there is considerable interest in AMF as biofertilizers, it remains challenging to estimate the impact of AMF in the field. Our design illustrates an effective approach for field evaluation of AMF effects. Furthermore, we demonstrate the capacity of the ionome to reveal host genotype-specific variation in the impact of AMF on plant nutrition.

The genotype-phenotype relationship and evolutionary genetics in the light of the Metabolic Control Analysis

Metabolic control analysis has long been used as a systemic model of the genotype-phenotype (GP) relationship. By considering kinetic parameters and enzyme concentrations as reflecting the genotype level and metabolic fluxes or pools as phenotypes related to fitness, MCA has given a biological basis to the relationship between these two levels. The non-linear and concave relationship between enzymes and fluxes can account for common genetic effects that reductionist approaches have been powerless to explain, such as the dominance of active alleles over less active alleles, the various types of epistasis and heterosis, and reveals the structural links between these genetic effects. The summation property of the flux control coefficients accounts for the L-shaped distribution of Quantitative Trait Locus (QTL) effects, irrespective of other possible causes. Metabolic models of response to selection results in evolutionary scenarios that are markedly different from those derived from the classical infinitesimal model of quantitative genetics. In particular, evolution towards selective neutrality appears to be a consequence of the diminishing return of the flux-enzyme relationship. In this paper, we survey the historical and recent achievements of MCA in genetics, quantitative genetics and evolution, focusing on epistasis and the evolution of flux in relation to enzyme concentrations.

Quantitative trait loci and candidate genes for yield-related traits of upland cotton revealed by genome-wide association analysis under drought conditions

BACKGROUND

Due to the influence of extreme weather, the environment in China's main cotton-producing areas is prone to drought stress conditions, which affect the growth and development of cotton and lead to a decrease in cotton yield.

RESULTS

In this study, 188 upland cotton germplasm resources were phenotyped for data of 8 traits (including 3 major yield traits) under drought conditions in three environments for two consecutive years. Correlation analysis revealed significant positive correlations between the three yield traits. Genetic analysis showed that the estimated heritability of the seed cotton index (SC) under drought conditions was the highest (80.81%), followed by that of boll weight (BW) (80.64%) and the lint cotton index (LC) (70.49%) With genome-wide association study (GWAS) analysis, a total of 75 quantitative trait loci (QTLs) were identified, including two highly credible new QTL hotspots. Three candidate genes (Gh_D09G064400, Gh_D10G261000 and Gh_D10G254000) located in the two new QTL hotspots, QTL51 and QTL55, were highly expressed in the early stage of fiber development and showed significant correlations with SC, LC and BW. The expression of three candidate genes in two extreme materials after drought stress was analyzed by qRT-PCR, and the expression of these two materials in fibers at 15, 20 and 25 DPA. The expression of these three candidate genes was significantly upregulated after drought stress and was significantly higher in drought-tolerant materials than in drought-sensitive materials. In addition, the expression levels of the three candidate genes were higher in the early stage of fiber development (15 DPA), and the expression levels in drought-tolerant germplasm were higher than those in drought-sensitive germplasm. These three candidate genes may play an important role in determining cotton yield under drought conditions.

CONCLUSIONS

This study is helpful for understanding the regulatory genes affecting cotton yield under drought conditions and provides germplasm and candidate gene resources for breeding high-yield cotton varieties under these conditions.

Genetic mapping of craniofacial traits in the Mexican tetra reveals loci associated with bite differences between cave and surface fish

BACKGROUND

The Mexican tetra, Astyanax mexicanus, includes interfertile surface-dwelling and cave-dwelling morphs, enabling powerful studies aimed at uncovering genes involved in the evolution of cave-associated traits. Compared to surface fish, cavefish harbor several extreme traits within their skull, such as a protruding lower jaw, a wider gape, and an increase in tooth number. These features are highly variable between individual cavefish and even across different cavefish populations.

RESULTS

To investigate these traits, we created a novel feeding behavior assay wherein bite impressions could be obtained. We determined that fish with an underbite leave larger bite impressions with an increase in the number of tooth marks. Capitalizing on the ability to produce hybrids from surface and cavefish crosses, we investigated genes underlying these segregating orofacial traits by performing Quantitative Trait Loci (QTL) analysis with F2 hybrids. We discovered significant QTL for bite (underbite vs. overbite) that mapped to a single region of the Astyanax genome. Within this genomic region, multiple genes exhibit coding region mutations, some with known roles in bone development. Further, we determined that there is evidence that this genomic region is under natural selection.

CONCLUSIONS

This work highlights cavefish as a valuable genetic model for orofacial patterning and will provide insight into the genetic regulators of jaw and tooth development.

Mapping of a major QTL for increased robustness and detection of genome assembly errors in Asian seabass (Lates calcarifer)

BACKGROUND

For Asian seabass (Lates calcarifer, Bloch 1790) cultured at sea cages various aquatic pathogens, complex environmental and stress factors are considered as leading causes of disease, causing tens of millions of dollars of annual economic losses. Over the years, we conducted farm-based challenges by exposing Asian seabass juveniles to complex natural environmental conditions. In one of these challenges, we collected a total of 1,250 fish classified as either 'sensitive' or 'robust' individuals during the 28-day observation period.

RESULTS

We constructed a high-resolution linkage map with 3,089 SNPs for Asian seabass using the double digest Restriction-site Associated DNA (ddRAD) technology and a performed a search for Quantitative Trait Loci (QTL) associated with robustness. The search detected a major genome-wide significant QTL for increased robustness in pathogen-infected marine environment on linkage group 11 (ASB_LG11; 88.9 cM to 93.6 cM) with phenotypic variation explained of 81.0%. The QTL was positioned within a > 800 kb genomic region located at the tip of chromosome ASB_LG11 with two Single Nucleotide Polymorphism markers, R1-38468 and R1-61252, located near to the two ends of the QTL. When the R1-61252 marker was validated experimentally in a different mass cross population, it showed a statistically significant association with increased robustness. The majority of thirty-six potential candidate genes located within the QTL have known functions related to innate immunity, stress response or disease. By utilizing this ddRAD-based map, we detected five mis-assemblies corresponding to four chromosomes, namely ASB_LG8, ASB_LG9, ASB_LG15 and ASB_LG20, in the current Asian seabass reference genome assembly.

CONCLUSION

According to our knowledge, the QTL associated with increased robustness is the first such finding from a tropical fish species. Depending on further validation in other stocks and populations, it might be potentially useful for selecting robust Asian seabass lines in selection programs.

Mapping of QTLs associated with yield and related traits under reproductive stage drought stress in rice using SNP linkage map

BACKGROUND

Drought stress is a major constraint for rice production worldwide. Reproductive stage drought stress (RSDS) leads to heavy yield losses in rice. The prospecting of new donor cultivars for identification and introgression of QTLs of major effect (Quantitative trait locus) for drought tolerance is crucial for the development of drought-resilient rice varieties.

METHODS AND RESULTS

Our study aimed to map QTLs associated with yield and its related traits under RSDS conditions. A saturated linkage map was constructed using 3417 GBS (Genotyping by sequencing) derived SNP (Single nucleotide polymorphism) markers spanning 1924.136 cM map length with an average marker density of 0.56 cM, in the F3 mapping population raised via cross made between the traditional ahu rice cultivar, Koniahu (drought tolerant) and a high-yielding variety, Disang (drought susceptible). Using the Inclusive composite interval mapping approach, 35 genomic regions governing yield and related traits were identified in pooled data from 198 F3 and F4 segregating lines evaluated for two consecutive seasons under both RSDS and irrigated control conditions. Of the 35 QTLs, 23 QTLs were identified under RSDS with LOD (Logarithm of odds) values ranging between 2.50 and 7.83 and PVE (phenotypic variance explained) values of 2.95-12.42%. Two major QTLs were found to be linked to plant height (qPH1.29) and number of filled grains per panicle (qNOG5.12) under RSDS. Five putative QTLs for grain yield namely, qGY2.00, qGY5.05, qGY6.16, qGY9.19, and qGY10.20 were identified within drought conditions. Fourteen QTL regions having ≤ 10 Mb QTL interval size were further analysed for candidate gene identification and a total of 4146 genes were detected out of these 2263 (54.63%) genes were annotated to at least one gene ontology (GO) term.

CONCLUSION

Several QTLs associated with grain yield and yield components and putative candidate genes were identified. The putative QTLs and candidate genes identified could be employed to augment drought resilience in rice after further validation through MAS strategies.

Unraveling genomic regions and candidate genes for multiple disease resistance in upland cotton using meta-QTL analysis

Verticillium wilt (VW), Fusarium wilt (FW) and Root-knot nematode (RKN) are the main diseases affecting cotton production. However, many reported quantitative trait loci (QTLs) for cotton resistance have not been used for agricultural practices because of inconsistencies in the cotton genetic background. The integration of existing cotton genetic resources can facilitate the discovery of important genomic regions and candidate genes involved in disease resistance. Here, an improved and comprehensive meta-QTL analysis was conducted on 487 disease resistant QTLs from 31 studies in the last two decades. A consensus linkage map with genetic overall length of 3006.59 cM containing 8650 markers was constructed. A total of 28 Meta-QTLs (MQTLs) were discovered, among which nine MQTLs were identified as related to resistance to multiple diseases. Candidate genes were predicted based on public transcriptome data and enriched in pathways related to disease resistance. This study used a method based on the integration of Meta-QTL, known genes and transcriptomics to reveal major genomic regions and putative candidate genes for resistance to multiple diseases, providing a new basis for marker-assisted selection of high disease resistance in cotton breeding.

Sequence level genome-wide associations for bull production and fertility traits in tropically adapted bulls

BACKGROUND

The genetics of male fertility is complex and not fully understood. Male subfertility can adversely affect the economics of livestock production. For example, inadvertently mating bulls with poor fertility can result in reduced annual liveweight production and suboptimal husbandry management. Fertility traits, such as scrotal circumference and semen quality are commonly used to select bulls before mating and can be targeted in genomic studies. In this study, we conducted genome-wide association analyses using sequence-level data targeting seven bull production and fertility traits measured in a multi-breed population of 6,422 tropically adapted bulls. The beef bull production and fertility traits included body weight (Weight), body condition score (CS), scrotal circumference (SC), sheath score (Sheath), percentage of normal spermatozoa (PNS), percentage of spermatozoa with mid-piece abnormalities (MP) and percentage of spermatozoa with proximal droplets (PD).

RESULTS

After quality control, 13,398,171 polymorphisms were tested for their associations with each trait in a mixed-model approach, fitting a multi-breed genomic relationship matrix. A Bonferroni genome-wide significance threshold of 5 × 10^- 8 was imposed. This effort led to identifying genetic variants and candidate genes underpinning bull fertility and production traits. Genetic variants in Bos taurus autosome (BTA) 5 were associated with SC, Sheath, PNS, PD and MP. Whereas chromosome X was significant for SC, PNS, and PD. The traits we studied are highly polygenic and had significant results across the genome (BTA 1, 2, 4, 6, 7, 8, 11, 12, 14, 16, 18, 19, 23, 28, and 29). We also highlighted potential high-impact variants and candidate genes associated with Scrotal Circumference (SC) and Sheath Score (Sheath), which warrants further investigation in future studies.

CONCLUSION

The work presented here is a step closer to identifying molecular mechanisms that underpin bull fertility and production. Our work also emphasises the importance of including the X chromosome in genomic analyses. Future research aims to investigate potential causative variants and genes in downstream analyses.

Identification of an important QTL for seed oil content in soybean

Seed oil content is one of the most important quantitative traits in soybean (Glycine max) breeding. Here, we constructed a high-density single nucleotide polymorphism linkage map using two genetically similar parents, Heinong 84 and Kenfeng 17, that differ dramatically in their seed oil contents, and performed quantitative trait loci (QTL) mapping of seed oil content in a recombinant inbred line (RIL) population derived from their cross. We detected five QTL related to seed oil content distributed on five chromosomes. The QTL for seed oil content explained over 10% of the phenotypic variation over two years. This QTL was mapped to an interval containing 20 candidate genes, including a previously reported gene, soybean RING Finger 1a (RNF1a) encoding an E3 ubiquitin ligase. Notably, two short sequences were inserted in the GmRNF1a coding region of KF 17 compared to that of HN 84, resulting in a longer protein variant in KF 17. Our results thus provide information for uncovering the genetic mechanisms determining seed oil content in soybean, as well as identifying an additional QTL and highlighting GmRNF1a as candidate gene for modulating seed oil content in soybean.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01384-2.

Inferring cell-type-specific causal gene regulatory networks during human neurogenesis

BACKGROUND

Genetic variation influences both chromatin accessibility, assessed in chromatin accessibility quantitative trait loci (caQTL) studies, and gene expression, assessed in expression QTL (eQTL) studies. Genetic variants can impact either nearby genes (cis-eQTLs) or distal genes (trans-eQTLs). Colocalization between caQTL and eQTL, or cis- and trans-eQTLs suggests that they share causal variants. However, pairwise colocalization between these molecular QTLs does not guarantee a causal relationship. Mediation analysis can be applied to assess the evidence supporting causality versus independence between molecular QTLs. Given that the function of QTLs can be cell-type-specific, we performed mediation analyses to find epigenetic and distal regulatory causal pathways for genes within two major cell types of the developing human cortex, progenitors and neurons.

RESULTS

We find that the expression of 168 and 38 genes is mediated by chromatin accessibility in progenitors and neurons, respectively. We also find that the expression of 11 and 12 downstream genes is mediated by upstream genes in progenitors and neurons. Moreover, we discover that a genetic locus associated with inter-individual differences in brain structure shows evidence for mediation of SLC26A7 through chromatin accessibility, identifying molecular mechanisms of a common variant association to a brain trait.

CONCLUSIONS

In this study, we identify cell-type-specific causal gene regulatory networks whereby the impacts of variants on gene expression were mediated by chromatin accessibility or distal gene expression. Identification of these causal paths will enable identifying and prioritizing actionable regulatory targets perturbing these key processes during neurodevelopment.

Genome-wide association study reveals useful QTL and genes controlling the fatty acid composition in rice bran oil using Vietnamese rice landraces

In rice (Oryza sativa L.), rice bran contains valuable nutritional constituents, such as high unsaturated fat content, tocotrienols, inositol, γ-oryzanol, and phytosterols, all of which are of nutritional and pharmaceuticals interest. There is now a rising market demand for rice bran oil, which makes research into their content and fatty acid profile an area of interest. As it is evident that lipid content has a substantial impact on the eating, cooking, and storage quality of rice, an understanding of the genetic mechanisms that determine oil content in rice is of great importance, equal to that of rice quality. Therefore, in this study, we performed a genome-wide association study on the composition and oil concentration of 161 Vietnamese rice varieties. Five categories of fatty acids in rice bran were discovered and the bran oil concentration profile in different rice accessions was identified. We also identified 229 important markers related to the fatty acid composition of bran oil, distributed mainly on chromosomes 1 and 7. Seven quantitative trait loci and five potential genes related to unsaturated fatty acid content were detected, including OsKASI, OsFAD, OsARF, OsGAPDH, and OsMADS29. These results provide insights into the genetic basis of rice bran oil composition, which is pivotal to the metabolic engineering of rice plants with desirable bran oil content through candidate genes selection.

Mapping of quantitative trait loci for the nutritional value of fresh market tomato

The incidence of many diseases, such as cancer, cardiovascular diseases, and diabetes, is associated with malnutrition and an unbalanced daily diet. Vegetables are an important source of vitamins and essential compounds for human health. As a result, such metabolites have increasingly become the focus of breeding programs. Tomato is one of the most popular components of our daily diet. Therefore, the improvement of tomato's nutritional quality is an important goal. In the present study, we performed targeted metabolic profiling of an interspecific Solanum pimpinellifolium × S. lycopersicum inbred backcross line (IBL) population and identified quantitative trait loci responsible for the nutritional value of tomato. Transgressive segregation was apparent for many of the nutritional compounds such that some IBLs had extremely high levels of various amino acids and vitamins compared to their parents. A total of 117 QTLs for nutritional traits including 62 QTLs for amino acids, 18 QTLs for fatty acids, 12 QTLs for water-soluble vitamins, and 25 QTLs for fat-soluble vitamins were identified. Moreover, almost 24% of identified QTLs were confirmed in previous studies, and 40 possible gene candidates were found for 18 identified QTLs. These findings can help breeders to improve the nutritional value of tomato.

Candidate genes for mastitis resistance in dairy cattle: a data integration approach

BACKGROUND

Inflammation of the mammary tissue (mastitis) is one of the most detrimental health conditions in dairy ruminants and is considered the most economically important infectious disease of the dairy sector. Improving mastitis resistance is becoming an important goal in dairy ruminant breeding programmes. However, mastitis resistance is a complex trait and identification of mastitis-associated alleles in livestock is difficult. Currently, the only applicable approach to identify candidate loci for complex traits in large farm animals is to combine different information that supports the functionality of the identified genomic regions with respect to a complex trait.

METHODS

To identify the most promising candidate loci for mastitis resistance we integrated heterogeneous data from multiple sources and compiled the information into a comprehensive database of mastitis-associated candidate loci. Mastitis-associated candidate genes reported in association, expression, and mouse model studies were collected by searching the relevant literature and databases. The collected data were integrated into a single database, screened for overlaps, and used for gene set enrichment analysis.

RESULTS

The database contains candidate genes from association and expression studies and relevant transgenic mouse models. The 2448 collected candidate loci are evenly distributed across bovine chromosomes. Data integration and analysis revealed overlaps between different studies and/or with mastitis-associated QTL, revealing promising candidate genes for mastitis resistance.

CONCLUSION

Mastitis resistance is a complex trait influenced by numerous alleles. Based on the number of independent studies, we were able to prioritise candidate genes and propose a list of the 22 most promising. To our knowledge this is the most comprehensive database of mastitis associated candidate genes and could be helpful in selecting genes for functional validation studies.

Identification of genomic regions governing moisture and heat stress tolerance employing association mapping in rice (Oryza sativa L.)

BACKGROUND

Rice crop is damaged extremely by abiotic stress world-wide. The best approach to enhance drought tolerance in rice varieties is to identify and introgress yield QTLs with major effects. The Association mapping approach helps in the identification of genomic regions governing physiological, yield and yield attributes under moisture and heat stress conditions in diverse collections of crop germplasm, based on historic recombination events and linkage disequilibrium across the genome.

METHODS AND RESULTS

The association mapping panel of 110 rice germplasm lines exhibited significant variation for all the traits in both irrigated and moisture stress conditions. The extent of yield reduction ranged to 83% during rabi, 2018-19, 53% in rabi, 2019-20 and 68% in pooled analysis. The genotypes Badami, Badshabhog, Pankaj, Varalu, Vasundhara, Vivekdhan, Krishna and Minghui63 exhibited drought tolerance with least yield penalty under moisture stress conditions. The genotypes Konark, MTU3626, NLR33671, PR118 and Triguna exhibited minimal reduction in heat stress tolerance traits. Association mapping of germplasm using 37808 SNP markers detected a total of 10 major MTA (Marker-trait association) clusters distributed on chromosomes 1, 3, 4 and 11 through mixed linear model (MLM) governing multiple traits from individual data analysis which are consistent across the years and situations. The pooled data generated a total of five MTA clusters located on chromosome 6. In addition, several novel unique MTAs were also identified. Heat stress analysis generated a total of 23 MTAs distributed on chromosomes 1, 5, 6 and 11. Candidate gene analysis detected a total of 53 and 38 genes under individual and pooled data analysis for various yield and yield attributes under control and moisture stress conditions, respectively and a total of 11 candidate genes in heat stress Conditions.

CONCLUSION

The major and novel MTAs identified in the present investigation for various drought and heat tolerant traits can be utilized for breeding climate-resilient rice varieties. The candidate genes predicted for key MTAs are of great value to deploy into the rice breeding after functional characterization.

Integration of Auxin, Brassinosteroid and Cytokinin in the Regulation of Rice Yield

Crop varieties with a high yield are most desirable in the present context of the ever-growing human population. Mostly, the yield traits are governed by a complex of numerous molecular and genetic facets modulated by various quantitative trait loci (QTLs). With the identification and molecular characterizations of yield-associated QTLs over recent years, the central role of phytohormones in regulating plant yield is becoming more apparent. Most often, different groups of phytohormones work in close association to orchestrate yield attributes. Understanding this cross talk would thus provide new venues for phytohormone pyramiding by editing a single gene or QTL(s) for yield improvement. Here, we review a few important findings to integrate the knowledge on the roles of auxin, brassinosteroid and cytokinin and how a single gene or a QTL could govern cross talk among multiple phytohormones to determine the yield traits.

Circulating Proteins Influencing Psychiatric Disease: A Mendelian Randomization Study

BACKGROUND

There is a pressing need for novel drug targets for psychiatric disorders. Circulating proteins are potential candidates because they are relatively easy to measure and modulate and play important roles in signaling.

METHODS

We performed two-sample Mendelian randomization analyses to estimate the associations between circulating protein abundances and risk of 10 psychiatric disorders. Genetic variants associated with 1611 circulating protein abundances identified in 6 large-scale proteomic studies were used as genetic instruments. Effects of the circulating proteins on psychiatric disorders were estimated by Wald ratio or inverse variance-weighted ratio tests. Horizontal pleiotropy, colocalization, and protein-altering effects were examined to validate the assumptions of Mendelian randomization.

RESULTS

Nine circulating protein-to-disease associations withstood multiple sensitivity analyses. Among them, 2 circulating proteins had associations replicated in 3 proteomic studies. A 1 standard deviation increase in the genetically predicted circulating TIMP4 level was associated with a reduced risk of anorexia nervosa (minimum odds ratio [OR] = 0.83; 95% CI, 0.76-0.91) and bipolar disorder (minimum OR = 0.88; 95% CI, 0.82-0.94). A 1 standard deviation increase in the genetically predicted circulating ESAM level was associated with an increased risk of schizophrenia (maximum OR = 1.32; 95% CI, 1.22-1.43). In addition, 58 suggestive protein-to-disease associations warrant validation with observational or experimental evidence. For instance, a 1 standard deviation increase in the ERLEC1-201-to-ERLEC1-202 splice variant ratio was associated with a reduced risk of schizophrenia (OR = 0.94; 95% CI, 0.90-0.97).

CONCLUSIONS

Prioritized circulating proteins appear to influence the risk of psychiatric disease and may be explored as intervention targets.

Mating success at elevated temperature is associated to thermal adaptation in a set of recombinant inbred lines of Drosophila melanogaster

In insects, mating ability at elevated temperature can be relevant for adaptation to heat-stressed environments and global warming. Here, we examined copulation latency (T1), copulation duration (T2), and mating frequency (T3, an index of mating success) in two related sets of recombinant inbred lines (RIL) in Drosophila melanogaster at both elevated (33 °C) and benign (25 °C) temperatures. One of these RIL sets (RIL-SH2) was shown to be consistently more resistant in both heat knockdown and heat-shock survival assays than its related set (RIL-D48) in previous studies. Negative correlations across RILs were found between T1 and T3 in this study. Flies from the heat-resistant set of RIL (RIL-SH2) were better able to mate at elevated temperature than flies from the heat-susceptible set (RIL-D48). Quantitative trait locus (QTL) mapping identified temperature-dependent QTLs for all traits (T1, T2 and T3) on all the three major chromosomes. Mating success at elevated temperature was found to be influenced by multiple QTLs. At elevated temperature, several QTLs for mating traits co-localized with QTLs that were previously associated with thermotolerance. The genetic basis for T1, T2 and T3 at the elevated temperature was found to be largely different from the genetic basis controlling the variation for mating success at benign temperature, as there was only a very low (or even null) number of QTLs overlapping across temperatures.

Combing Genome-Wide Association Studies and Single-Cell Analysis to Elucidate the Mechanisms of Kidney Disease: Proceedings of the Henry Shavelle Professorship

Background

Kidney diseases pose a significant global health burden; there is an urgent need to deepen our understanding of their underlying mechanisms.

Summary

This review focuses on new innovative approaches that merge genome-wide association studies (GWAS) and single-cell omics (including transcriptomics) in kidney disease research. We begin by detailing how GWAS has identified numerous genetic risk factors, offering valuable insight into disease susceptibility. Then, we explore the application of scRNA-seq, highlighting its ability to unravel how genetic variants influence cellular phenotypes. Through a synthesis of recent studies, we illuminate the synergy between these two powerful methodologies, demonstrating their potential in elucidating the complex etiology of kidney diseases. Moreover, we discuss how this integrative approach could pave the way for precise diagnostics and personalized treatments.

Key Message

This review underscores the transformative potential of combining GWAS and scRNA-seq in the journey toward a deeper understanding of kidney diseases.

Characterization of Domestication Loci Associated with Awn Development in Rice

Rice (Oryza sativa L.) is a widely studied domesticated model plant. Seed awning is an unfavorable trait during rice harvesting and processing. Hence, loss of awn was one of the target characters selected during domestication. However, the genetic mechanisms underlying awn development in rice are not well understood. In this study, we analyzed and characterized the genes for awn development using a mapping population derived from a cross between the Korean indica cultivar 'Milyang23' and a near-isogenic line NIL4/9 derived from a cross between 'Hwaseong' and Oryza minuta. Two quantitative trait loci (QTLs), qAwn4 and qAwn9, mapped on chromosomes 4 and 9, respectively, increased awn length in an additive manner. Through comparative sequencing analyses of the parental lines, LABA1 was determined as the causal gene underlying qAwn4. qAwn9 was mapped to a 199-kb physical region between markers RM24663 and RM24679. Within this interval, 27 annotated genes were identified, and five genes, including a basic leucine zipper transcription factor 76 (OsbZIP76), were considered as candidate genes for qAwn9 based on their functional annotations and sequence variations. Haplotype analysis using the candidate gene revealed tropical-japonica specific sequence variants in the qAwn9 region, which partly explains the non-detection of qAwn9 in previous studies that used progenies from interspecific crosses. This provides further evidence that OsbZIP76 is possibly a causal gene for qAwn9. The O. minuta qAwn9 allele was identified as a major QTL, providing an important molecular target for understanding the genetic control of awn development in rice. Our results lay the foundation for further cloning of the awn gene underlying qAwn9.

Identification of quantitative trait loci of agronomic traits in bread wheat using a Pamyati Azieva × Paragon mapping population harvested in three regions of Kazakhstan

Background

Although genome-wide association studies (GWAS) are an increasingly informative tool in the mining of new quantitative trait loci (QTLs), a classical biparental mapping approach is still a powerful, widely used method to search the unique genetic factors associated with important agronomic traits in bread wheat.

Methods

In this study, a newly constructed mapping population of Pamyati Azieva (Russian Federation) × Paragon (UK), consisting of 94 recombinant inbred lines (RILs), was tested in three different regions of Kazakhstan with the purpose of QTL identification for key agronomic traits. The RILs were tested in 11 environments of two northern breeding stations (Petropavlovsk, North Kazakhstan region, and Shortandy, Aqmola region) and one southeastern station (Almalybak, Almaty region). The following eight agronomic traits were studied: heading days, seed maturation days, plant height, spike length, number of productive spikes, number of kernels per spike, thousand kernel weight, and yield per square meter. The 94 RILs of the PAxP cross were genotyped using Illumina's iSelect 20K single nucleotide polymorphism (SNP) array and resulted in the identification of 4595 polymorphic SNP markers.

Results

The application of the QTL Cartographer statistical package allowed the identification of 53 stable QTLs for the studied traits. A survey of published studies related to common wheat QTL identification suggested that 28 of those 53 QTLs were presumably novel genetic factors. The SNP markers for the identified QTLs of the analyzed agronomic traits of common wheat can be efficiently applied in ongoing breeding activities in the wheat breeding community using a marker-assisted selection approach.

Genome-wide meta-QTL analyses provide novel insight into disease resistance repertoires in common bean

BACKGROUND

Common bean (Phaseolus vulgaris) is considered a staple food in a number of developing countries. Several diseases attack the crop leading to substantial economic losses around the globe. However, the crop has rarely been investigated for multiple disease resistance traits using Meta-analysis approach.

RESULTS AND CONCLUSIONS

In this study, in order to identify the most reliable and stable quantitative trait loci (QTL) conveying disease resistance in common bean, we carried out a meta-QTL (MQTL) analysis using 152 QTLs belonging to 44 populations reported in 33 publications within the past 20 years. These QTLs were decreased into nine MQTLs and the average of confidence interval (CI) was reduced by 2.64 folds with an average of 5.12 cM in MQTLs. Uneven distribution of MQTLs across common bean genome was noted where sub-telomeric regions carry most of the corresponding genes and MQTLs. One MQTL was identified to be specifically associated with resistance to halo blight disease caused by the bacterial pathogen Pseudomonas savastanoi pv. phaseolicola, while three and one MQTLs were specifically associated with resistance to white mold and anthracnose caused by the fungal pathogens Sclerotinia sclerotiorum and Colletotrichum lindemuthianum, respectively. Furthermore, two MQTLs were detected governing resistance to halo blight and anthracnose, while two MQTLs were detected for resistance against anthracnose and white mold, suggesting putative genes governing resistance against these diseases at a shared locus. Comparative genomics and synteny analyses provide a valuable strategy to identify a number of well‑known functionally described genes as well as numerous putative novels candidate genes in common bean, Arabidopsis and soybean genomes.

Genetic regulation of RNA splicing in human pancreatic islets

BACKGROUND

Non-coding genetic variants that influence gene transcription in pancreatic islets play a major role in the susceptibility to type 2 diabetes (T2D), and likely also contribute to type 1 diabetes (T1D) risk. For many loci, however, the mechanisms through which non-coding variants influence diabetes susceptibility are unknown.

RESULTS

We examine splicing QTLs (sQTLs) in pancreatic islets from 399 human donors and observe that common genetic variation has a widespread influence on the splicing of genes with established roles in islet biology and diabetes. In parallel, we profile expression QTLs (eQTLs) and use transcriptome-wide association as well as genetic co-localization studies to assign islet sQTLs or eQTLs to T2D and T1D susceptibility signals, many of which lack candidate effector genes. This analysis reveals biologically plausible mechanisms, including the association of T2D with an sQTL that creates a nonsense isoform in ERO1B, a regulator of ER-stress and proinsulin biosynthesis. The expanded list of T2D risk effector genes reveals overrepresented pathways, including regulators of G-protein-mediated cAMP production. The analysis of sQTLs also reveals candidate effector genes for T1D susceptibility such as DCLRE1B, a senescence regulator, and lncRNA MEG3.

CONCLUSIONS

These data expose widespread effects of common genetic variants on RNA splicing in pancreatic islets. The results support a role for splicing variation in diabetes susceptibility, and offer a new set of genetic targets with potential therapeutic benefit.

Genome-wide analysis suggests the potential role of lncRNAs during seed development and seed size/weight determination in chickpea

The integrated transcriptome data analyses suggested the plausible roles of lncRNAs during seed development in chickpea. The candidate lncRNAs associated with QTLs and those involved in miRNA-mediated seed size/weight determination in chickpea have been identified. Long non-coding RNAs (lncRNAs) are important regulators of various biological processes. Here, we identified lncRNAs at seven successive stages of seed development in small-seeded and large-seeded chickpea cultivars. In total, 4751 lncRNAs implicated in diverse biological processes were identified. Most of lncRNAs were conserved between the two cultivars, whereas only a few of them were conserved in other plants, suggesting their species-specificity. A large number of lncRNAs differentially expressed between the two chickpea cultivars associated with seed development-related processes were identified. The lncRNAs acting as precursors of miRNAs and those mimicking target protein-coding genes of miRNAs involved in seed size/weight determination, including HAIKU1, BIG SEEDS1, and SHB1, were also revealed. Further, lncRNAs located within seed size/weight associated quantitative trait loci were also detected. Overall, we present a comprehensive resource and identified candidate lncRNAs that may play important roles during seed development and seed size/weight determination in chickpea.

Pleiotropic effect analysis and marker development for grain zinc and iron concentrations in spring wheat

Wheat (Triticum aestivum L.) is one of the main food crops in the world and a primary source of zinc (Zn) and iron (Fe) in the human body. The genetic mechanisms underlying related traits have been clarified, thereby providing a molecular theoretical foundation for the development of germplasm resources. In this study, a total of 23,536 high-quality DArT markers was used to map quantitative trait loci (QTL) of grain Zn (GZn) and grain Fe (GFe) concentrations in recombinant inbred lines crossed by Avocet/Chilero. A total of 17 QTLs was located on chromosomes 1BL, 2BL, 3BL, 4AL, 4BS, 5AL, 5DL, 6AS, 6BS, 6DS, and 7AS accounting for 0.38-16.62% of the phenotypic variance. QGZn.haust-4AL, QGZn.haust-7AS.1, and QGFe.haust-6BS were detected on chromosomes 4AL, 6BS, and 7AS, accounting for 10.63-16.62% of the phenotypic variance. Four stable QTLs, QGZn.haust-4AL, QGFe.haust-1BL, QGFe.haust-4AL, and QGFe.haust-5DL, were located on chromosomes 1BL, 4AL, and 5DL. Three pleiotropic effects loci for GZn and GFe concentrations were located on chromosomes 1BL, 4AL, and 5DL. Two high-throughput Kompetitive Allele Specific PCR markers were developed by closely linking single-nucleotide polymorphisms on chromosomes 4AL and 5DL, which were validated by a germplasm panel. Therefore, it is the most important that quantitative trait loci and KASP marker for grain zinc and iron concentrations were developed for utilizing in marker-assisted breeding and biofortification of wheat grain in breeding programs.

Identification and characterization of resistance quantitative trait loci against bacterial wilt caused by the Ralstonia solanacearum species complex in potato

Bacterial wilt (BW) caused by the Ralstonia solanacearum species complex (RSSC) represents one of the most serious diseases affecting potato cultivation. The development of BW-resistant cultivars represents the most efficient strategy to control this disease. The resistance-related quantitative trait loci (QTLs) in plants against different RSSC strains have not been studied extensively. Therefore, we performed QTL analysis for evaluating BW resistance using a diploid population derived from Solanum phureja, S. chacoense, and S. tuberosum. Plants cultivated in vitro were inoculated with different strains (phylotype I/biovar 3, phylotype I/biovar 4, and phylotype IV/biovar 2A) and incubated at 24 °C or 28 °C under controlled conditions. Composite interval mapping was performed for the disease indexes using a resistant parent-derived map and a susceptible parent-derived map consisting of single-nucleotide polymorphism markers. We identified five major and five minor resistance QTLs on potato chromosomes 1, 3, 5, 6, 7, 10, and 11. The major QTLs PBWR-3 and PBWR-7 conferred stable resistance against Ralstonia pseudosolanacearum (phylotype I) and Ralstonia syzygii (phylotype IV), whereas PBWR-6b was a strain-specific major resistance QTL against phylotype I/biovar 3 and was more effective at a lower temperature. Therefore, we suggest that broad-spectrum QTLs and strain-specific QTLs can be combined to develop the most effective BW-resistant cultivars for specific areas.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01321-9.

Identification of QTLs and a putative candidate gene involved in rhizome enlargement of Asian lotus (Nelumbo nucifera)

QTL mapping studies identified three reliable QTLs of rhizome enlargement in lotus. NnBEL6 located within the confidence interval of the major QTL cqREI-LG2 is a key candidate gene enhancing rhizome enlargement. Lotus (Nelumbo) is perennial aquatic plant with nutritional, pharmacological, and ornamental significance. Rhizome is an underground lotus stem that acts as a storage organ and as a reproductive tissue for asexual production. The enlargement of lotus rhizome is an important adaptive strategy for surviving the cold winter. The aims of this study were to identify quantitative trait loci (QTLs) for rhizome enlargement traits including rhizome enlargement index (REI) and number of enlarged rhizome (NER), and to uncover their associated candidate genes. A high-density genetic linkage map was constructed, consisting of 2935 markers binned from 236,840 SNPs. A total of 14 significant QTLs were detected for REI and NER, which explained 6.7-22.3% of trait variance. Three QTL regions were repeatedly identified in at least 2 years, and a major QTL, designated cqREI-LG2, with a rhizome-enlargement effect and about 20% of the phenotypic contribution was identified across the 3 climatic years. A candidate NnBEL6 gene located within the confidence interval of cqREI-LG2 was considered to be putatively involved in lotus rhizome enlargement. The expression of NnBEL6 was exclusively induced by rhizome swelling. Sequence comparison of NnBEL6 among lotus cultivars revealed a functional Indel site in its promoter that likely initiates the rhizome enlargement process. Transgenic potato assay was used to confirm the role of NnBEL6 in inducing tuberization. The successful identification QTLs and functional validation of NnBEL6 gene reported in this study will enrich our knowledge on the genetic basis of rhizome enlargement in lotus.

QTL mapping under salt stress in rice using a Kalarata-Azucena population

Salt stress is a major constraint across large rice production areas in Asia, because of the high sensitivity of modern rice varieties. To identify quantitative trait loci (QTL) associated with salt tolerance in rice, we developed an F₂ population from a cross between the salt-tolerant landrace, Kalarata, and the salt-sensitive parent, Azucena. F3 families from this population were screened and scored for salt tolerance using IRRI's Standard evaluation system (SES). Growth, biomass, Na⁺ and K⁺ concentrations in leaf tissues, and chlorophyll concentration were determined. A genetic linkage map was constructed with 151 SSRs and InDel markers, which cover 1463 cM with an average distance of 9.69 cM between loci. A total of 13 QTL were identified using Composite Interval Mapping for 16 traits. Several novel QTL were identified in this study, the largest is for root sodium concentration (LOD = 11.0, R² = 25.0) on chromosome 3, which also co-localize with a QTL for SES. Several QTL on the short arm of chromosome 1 coincide with the Saltol locus identified before. The novel QTL identified in this study constitute future targets for molecular breeding, to combine them with other QTL identified before, for higher tolerance and stable performance of rice varieties in salt affected soils.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10681-022-03026-8.

Genetic mapping of powdery mildew resistance genes in wheat landrace Guizi 1 via genotyping by sequencing

BACKGROUND

Wheat (Triticum aestivum L.) powdery mildew (Pm), which caused by Blumeria graminis f. sp. tritici (Bgt), is a destructive disease worldwide that causes severe yield losses in wheat. Resistant wheat cultivars easily lose their ability to effectively resist newly emerged Bgt strains; therefore, identifying new resistance genes is necessary for breeding resistant cultivars.

METHODS AND RESULTS

Guizi 1 (GZ1) is a Chinese wheat cultivar with moderate and stable resistance to Pm. Genetic analysis indicated that the Pm resistance of GZ1 was controlled by a single dominant gene, designated PmGZ1. In total, 110 F₂ individual plants and their 2 parents were subjected to genotyping by sequencing (GBS), which yielded 23,134 high-quality single-nucleotide polymorphisms (SNPs). The SNP distributions across the 21 chromosomes ranged from 134 on chromosome 6D to 6288 on chromosome 3B. Chromosome 6A has 1866 SNPs, among which 16 are physically located between positions 307,802,221 and 309,885,836 in an approximate 2.3-cM region; this region also had the greatest SNP density. The average map distance between SNP markers was 0.1 cM. A quantitative trait locus (QTL) with a significant epistatic effect on Pm resistance was mapped to chromosome 6A. The logarithm of odds (LOD) value of PmGZ1 was 34.8, and PmGZ1 was located within the confidence interval marked by chr6a-307802221 and chr6a-309885836. Moreover, 74.7% of the phenotypic variance was explained by PmGZ1. Four candidate genes (which encoded two TaAP2-A and two actin proteins) were annotated maybe as resistance genes.

CONCLUSIONS

The present results provide valuable information for wheat genetic improvement, QTL fine mapping, and candidate gene validation.

Dissection of canopy layer-specific genetic control of leaf angle in Sorghum bicolor by RNA sequencing

BACKGROUND

Leaf angle is an important plant architecture trait, affecting plant density, light interception efficiency, photosynthetic rate, and yield. The "smart canopy" model proposes more vertical leaves in the top plant layers and more horizontal leaves in the lower canopy, maximizing conversion efficiency and photosynthesis. Sorghum leaf arrangement is opposite to that proposed in the "smart canopy" model, indicating the need for improvement. Although leaf angle quantitative trait loci (QTL) have been previously reported, only the Dwarf3 (Dw3) auxin transporter gene, colocalizing with a major-effect QTL on chromosome 7, has been validated. Additionally, the genetic architecture of leaf angle across canopy layers remains to be elucidated.

RESULTS

This study characterized the canopy-layer specific transcriptome of five sorghum genotypes using RNA sequencing. A set of 284 differentially expressed genes for at least one layer comparison (FDR < 0.05) co-localized with 69 leaf angle QTL and were consistently identified across genotypes. These genes are involved in transmembrane transport, hormone regulation, oxidation-reduction process, response to stimuli, lipid metabolism, and photosynthesis. The most relevant eleven candidate genes for layer-specific angle modification include those homologous to genes controlling leaf angle in rice and maize or genes associated with cell size/expansion, shape, and cell number.

CONCLUSIONS

Considering the predicted functions of candidate genes, their potential undesirable pleiotropic effects should be further investigated across tissues and developmental stages. Future validation of proposed candidates and exploitation through genetic engineering or gene editing strategies targeted to collar cells will bring researchers closer to the realization of a "smart canopy" sorghum.

Functional characterisation of the amyotrophic lateral sclerosis risk locus GPX3/TNIP1

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a complex, late-onset, neurodegenerative disease with a genetic contribution to disease liability. Genome-wide association studies (GWAS) have identified ten risk loci to date, including the TNIP1/GPX3 locus on chromosome five. Given association analysis data alone cannot determine the most plausible risk gene for this locus, we undertook a comprehensive suite of in silico, in vivo and in vitro studies to address this.

METHODS

The Functional Mapping and Annotation (FUMA) pipeline and five tools (conditional and joint analysis (GCTA-COJO), Stratified Linkage Disequilibrium Score Regression (S-LDSC), Polygenic Priority Scoring (PoPS), Summary-based Mendelian Randomisation (SMR-HEIDI) and transcriptome-wide association study (TWAS) analyses) were used to perform bioinformatic integration of GWAS data (Ncases = 20,806, Ncontrols = 59,804) with 'omics reference datasets including the blood (eQTLgen consortium N = 31,684) and brain (N = 2581). This was followed up by specific expression studies in ALS case-control cohorts (microarray Ntotal = 942, protein Ntotal = 300) and gene knockdown (KD) studies of human neuronal iPSC cells and zebrafish-morpholinos (MO).

RESULTS

SMR analyses implicated both TNIP1 and GPX3 (p < 1.15 × 10-6), but there was no simple SNP/expression relationship. Integrating multiple datasets using PoPS supported GPX3 but not TNIP1. In vivo expression analyses from blood in ALS cases identified that lower GPX3 expression correlated with a more progressed disease (ALS functional rating score, p = 5.5 × 10-3, adjusted R2 = 0.042, Beffect = 27.4 ± 13.3 ng/ml/ALSFRS unit) with microarray and protein data suggesting lower expression with risk allele (recessive model p = 0.06, p = 0.02 respectively). Validation in vivo indicated gpx3 KD caused significant motor deficits in zebrafish-MO (mean difference vs. control ± 95% CI, vs. control, swim distance = 112 ± 28 mm, time = 1.29 ± 0.59 s, speed = 32.0 ± 2.53 mm/s, respectively, p for all < 0.0001), which were rescued with gpx3 expression, with no phenotype identified with tnip1 KD or gpx3 overexpression.

CONCLUSIONS

These results support GPX3 as a lead ALS risk gene in this locus, with more data needed to confirm/reject a role for TNIP1. This has implications for understanding disease mechanisms (GPX3 acts in the same pathway as SOD1, a well-established ALS-associated gene) and identifying new therapeutic approaches. Few previous examples of in-depth investigations of risk loci in ALS exist and a similar approach could be applied to investigate future expected GWAS findings.

Genetic control of source-sink relationships in grain sorghum

QTL hotspots identified for selected source-sink-related traits provide the opportunity for pyramiding favorable alleles for improving sorghum productivity under diverse environments. A sorghum bi-parental mapping population was evaluated under six different environments at Hays and Manhattan, Kansas, USA, in 2016 and 2017, to identify genomic regions controlling source-sink relationships. The population consisted of 210 recombinant inbred lines developed from US elite post-flowering drought susceptible (RTx430) and a known post-flowering drought tolerant cultivar (SC35). Selected physiological traits related to source (effective quantum yield of photosystem II and chlorophyll index), sink (grain yield per panicle) and panicle neck diameter were recorded during grain filling. The results showed strong phenotypic and genotypic association between panicle neck diameter and grain yield per panicle during mid-grain filling and at maturity. Multiple QTL model revealed 5-12 including 2-5 major QTL for each trait. Among them 3, 7 and 8 QTL for quantum yield, panicle neck diameter and chlorophyll index, respectively, have not been identified previously in sorghum. Phenotypic variation explained by QTL identified across target traits ranged between 5.5 and 25.4%. Panicle neck diameter and grain yield per panicle were positively associated, indicating the possibility of targeting common co-localized QTL to improve both traits simultaneously through marker-assisted selection. Three major QTL hotspots, controlling multiple traits were identified on chromosome 1 (52.23-61.18 Mb), 2 (2.52-11.43 Mb) and 3 (1.32-3.95 Mb). The identified genomic regions and underlying candidate genes can be utilized in pyramiding favorable alleles for improving source-sink relationships in sorghum under diverse environments.

Integrating omics approaches to discover and prioritize candidate genes involved in oil biosynthesis in soybean

Soybean is a major source of edible protein and oil. Oil content is a quantitative trait that is significantly determined by genetic and environmental factors. Over the past 30 years, a large volume of soybean genetic, genomic, and transcriptomic data have been accumulated. Nevertheless, integrative analyses of such data remain scarce, in spite of their importance for crop improvement. We hypothesized that the co-occurrence of genomic regions for oil-related traits in different studies may reveal more stable regions encompassing important genetic determinants of oil content and quality in soybean. We integrated publicly available data, obtained with distinct techniques, to discover and prioritize candidate genes involved in oil biosynthesis and regulation in soybean. We detected key fatty acid biosynthesis genes (e.g., BCCP2 and ACCase, FADs, KAS family proteins) and several transcription factors, which are likely regulators of oil biosynthesis. In addition, we identified new candidates for seed oil accumulation and quality, such as Glyma.03G213300 and Glyma.19G160700, which encode a translocator protein homolog and a histone acetyltransferase, respectively. Further, oil and protein genomic hotspots are strongly associated with breeding and not with domestication, suggesting that soybean domestication prioritized other traits. The genes identified here are promising targets for breeding programs and for the development of soybean lines with increased oil content and quality.

Genome-wide QTL mapping of yield and agronomic traits in two widely adapted winter wheat cultivars from multiple mega-environments

Quantitative trait loci (QTL) analysis could help to identify suitable molecular markers for marker-assisted breeding (MAB). A mapping population of 124 F_5:7recombinant inbred lines derived from the cross ‘TAM 112’/‘TAM 111’ was grown under 28 diverse environments and evaluated for grain yield, test weight, heading date, and plant height. The objective of this study was to detect QTL conferring grain yield and agronomic traits from multiple mega-environments. Through a linkage map with 5,948 single nucleotide polymorphisms (SNPs), 51 QTL were consistently identified in two or more environments or analyses. Ten QTL linked to two or more traits were also identified on chromosomes 1A, 1D, 4B, 4D, 6A, 7B, and 7D. Those QTL explained up to 13.3% of additive phenotypic variations with the additive logarithm of odds (LOD(A)) scores up to 11.2. The additive effect increased yield up to 8.16 and 6.57 g m⁻² and increased test weight by 2.14 and 3.47 kg m⁻³ with favorable alleles from TAM 111 and TAM 112, respectively. Seven major QTL for yield and six for TW with one in common were of our interest on MAB as they explained 5% or more phenotypic variations through additive effects. This study confirmed previously identified loci and identified new QTL and the favorable alleles for improving grain yield and agronomic traits.

Novel QTL identification and candidate gene analysis for enhancing salt tolerance in soybean (Glycine max (L.) Merr.)

Soybean, a glycophyte that is sensitive to salt stress, is greatly affected by salinity at all growth stages. A mapping population derived from a cross between a salt-sensitive Korean cultivar, Cheongja 3, and a salt-tolerant landrace, IT162669, was used to identify quantitative trait loci (QTLs) conferring salt tolerance in soybean. Following treatment with 120 mM NaCl for 2 weeks, phenotypic traits representing physiological damage, leaf Na+ content, and K+/Na+ ratio were characterized. Among the QTLs mapped on a high-density genetic map harboring 2,630 single nucleotide polymorphism markers, we found two novel major loci, qST6, on chromosome 6, and qST10, on chromosome 10, which controlled traits related to ion toxicity and physiology in response to salinity, respectively. These loci were distinct from the previously known salt tolerance allele on chromosome 3. Other QTLs associated with abiotic stress overlapped with the genomic regions of qST6 and qST10, or with their paralogous regions. Based on the functional annotation and parental expression differences, we identified eight putative candidate genes, two in qST6 and six in qST10, which included a phosphoenolpyruvate carboxylase and an ethylene response factor. This study provides additional genetic resources to breed soybean cultivars with enhanced salt tolerance.

Nitrogen use efficiency (NUE): elucidated mechanisms, mapped genes and gene networks in maize (Zea mays L.)

Nitrogen, the vital primary plant growth nutrient at deficit soil conditions, drastically affects the growth and yield of a crop. Over the years, excess use of inorganic nitrogenous fertilizers resulted in pollution, eutrophication and thereby demanding the reduction in the use of chemical fertilizers. Being a C₄ plant with fibrous root system and high NUE, maize can be deployed to be the best candidate for better N uptake and utilization in nitrogen deficient soils. The maize germplasm sources has enormous genetic variation for better nitrogen uptake contributing traits. Adoption of single cross maize hybrids as well as inherent property of high NUE has helped maize cultivars to achieve the highest growth rate among the cereals during last decade. Further, considering the high cost of nitrogenous fertilizers, adverse effects on soil health and environmental impact, maize improvement demands better utilization of existing genetic variation for NUE via introgression of novel allelic combinations in existing cultivars. Marker assisted breeding efforts need to be supplemented with introgression of genes/QTLs related to NUE in ruling varieties and thereby enhancing the overall productivity of maize in a sustainable manner. To achieve this, we need mapped genes and network of interacting genes and proteins to be elucidated. Identified genes may be used in screening ideal maize genotypes in terms of better physiological functionality exhibiting high NUE. Future genome editing may help in developing lines with increased productivity under low N conditions in an environment of optimum agronomic practices.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12298-021-01113-z.

Introgression and QTL mapping conferring resistance for Alternaria brassicae in the backcross progeny of Sinapis alba + Brassica juncea somatic hybrids

A total of three QTLs, responsible for A. brassicae resistance were introgressed into S. alba - B. juncea introgression lines from S. alba and mapped through donor genome-specific SSR markers. Alternaria brassicae is a key pathogen of the Brassicaceae family causing severe blight disease to oilseed crops that leads to heavy yield losses due to lack of resistance source within cultivated Brassicas. However, the host resistance present in the Sinapis alba, an allied member of the Brassicaceae family is still unexplored precisely due to the unavailability of segregating population for Alternaria blight resistance and scarcity of donor genome-specific genetic markers. The present study was undertaken to identify quantitative trait loci governing resistance to Alternaria blight which was introgressed from S. alba to the backcross population of stable S. alba + B. juncea somatic hybrids (2n = 60; AABBSS). The second backcross population showed significant phenotypic variations for Alternaria blight ranging from immune to highly susceptible phenotype, thus suggesting quantitative nature of resistance for the disease. A subset of 154 BC₂F_3-4 lines was used for disease screening and genotyping with 234 S. alba genome-specific microsatellite markers. As a result of the study, twelve linkage groups were developed corresponding to 12 chromosomes of S. alba (n = 12) covering a length of 1694.02 cM. The chromosomes 5 and 11 harbored a total of 1 (Abr-01), and 2 (Abr-02, and Abr-03) QTLs detected by ICIM-ADD mapping method at LOD score values 3.7, 5.12, and 6.74, respectively. The QTLs identified during the study have a range of 5.51-10.87 percent phenotypic variations for disease resistance. To the best of our knowledge, this is the first report of QTLs introgression for A. brassicae resistance in cultivated Brassica from an allied member of Brassicaceae.

One Hundred Years of Gene Balance: How Stoichiometric Issues Affect Gene Expression, Genome Evolution, and Quantitative Traits

A century ago experiments with the flowering plant Datura stramonium and the fruit fly Drosophila melanogaster revealed that adding an extra chromosome to a karyotype was much more detrimental than adding a whole set of chromosomes. This phenomenon was referred to as gene balance and has been recapitulated across eukaryotic species. Here, we retrace some developments in this field. Molecular studies suggest that the basis of balance involves stoichiometric relationships of multi-component interactions. This concept has implication for the mechanisms controlling gene expression, genome evolution, sex chromosome evolution/dosage compensation, speciation mechanisms, and the underlying genetics of quantitative traits.

Understanding the genomic architecture of clinical mastitis in Bos indicus

This study elucidated potential genetic variants and QTLs associated with clinical mastitis incidence traits in Bos indicus breed, Sahiwal. Estimated breeding values for the traits (calculated using Bayesian inference) were used as pseudo-phenotypes for association with genome-wide SNPs and further QTL regions underlying the traits were identified. In all, 25 SNPs were found to be associated with the traits at the genome-wide suggestive threshold (p ≤ 5 × 10^-4) and these SNPs were used to define QTL boundaries based on the linkage disequilibrium structure. A total of 16 QTLs were associated with the trait EBVs including seven each for clinical mastitis incidence (CMI) in first and second lactations and two for CMI in third lactation. Nine out of sixteen QTLs overlapped with the already reported QTLs for mastitis traits, whereas seven were adjudged as novel ones. Important candidates for clinical mastitis in the identified QTL regions included DNAJB9, ELMO1, ARHGAP26, NR3C1, CACNB2, RAB4A, GRB2, NUP85, SUMO2, RBPJ, and RAB33B genes. These findings shed light on the genetic architecture of the disease in Bos indicus, and present potential regions for fine mapping and downstream analysis in future.

Understanding population structure and detection of QTLs for curding-related traits in Indian cauliflower by genotyping by sequencing analysis

Curd initiation and development are complex traits and highly responsive for different temperature ranges in cauliflower. The present study was aimed to identify QTLs for eight traits associated with curding behaviour in diverse germplasm of Indian cauliflower. For this, 92 genotypes of cauliflower and 2 each of tropical broccoli and cabbage were genotyped through genotyping by sequencing (GBS). It generated ≈302 million reads (9.1226E + 10 bp) and identified 35,381 SNPs, maximum from chromosome 3 (4735) with a mean value of 3981.1 SNPs. Ts/Tv ratio was 1.74, suggesting transition bias. STRUCTURE analysis revealed delta value of K = 4 and four subpopulations and prominence of population admixture. In total, 121 significant SNPs were detected for eight traits, 38 for Delhi (North Indian plain) and 83 for Barapani (North-East India). Twelve QTLs were detected for traits associated with regulation of curd formation and development, five of which were for marketable curd length, curd width, days to 50% curd harvest and marketable curd weight from Delhi region and seven for curd length, curd width, days to 50% curd harvest, gross plant weight, leaf length, marketable/net curd weight and number of leaves per plant for Barapani area of North East India. The SNPs identified will be useful for development of markers for curding-related traits and their use in breeding varieties with wider curding plasticity.