Map Distance Research Articles

SSR markers based QTL mapping and genetic analysis for yield and yield-attributing traits in bitter gourd (Momordica charantia L.)

The present study was conducted for QTL mapping for yield and other yield attributing traits in bitter gourd using Simple Sequence Repeat (SSR) markers. A total of 630 SSR markers were screened for polymorphism in two contrasting parents (DBGS-2 and Pusa Purvi), out of which only 35 were polymorphic. F1 plants (10 individuals) in which hybridity was ascertained (using these polymorphic markers); were further employed for development of mapping population (F2) consisting of 120 plants. Higher variation was present in the mapping population as evident from the wider range value of the characters. Continuous frequency distribution classes combined with bell-shaped, symmetrical normal distribution curve, revealed the quantitative inheritance nature of the traits studied. Higher PCV than the GCV for all the traits, along with high difference between the PCV and GCV for majority of traits indicated higher influence of environment in expression of these traits in the mapping population. Presence of transgressive segregation was also noted for majority of the traits. Amongst the various linkage groups (LG), LG 4 had the maximum number of markers, covering 171.07 cM map distance. LG4 also possessed the maximum number (nine) of QTLs while LG1 had six. QTL mapping using polymorphic SSRs resulted in detection of a total of 28 QTLs for fourteen traits viz. yield per plant (kg), earliness or flower related traits (node to first female flower, node to first male flower, days to first male flower, male to female flower ratio), fruit traits (fruit number per plant, fruit diameter (cm), fruit length/ diameter ratio, pericarp thickness (mm) and number of seed per fruit) and vegetative traits (internodal length (cm), number of primary branches, leaf width (cm), length and width ratio). The LOD score of these QTLs ranged from 3.01 to 64.47, the total phenotypic variances (PVE) ranged from 1.52 to 34.57 % and additive effects ranged from –3.69 to 17.07. Of the total, nineteen were major QTLs, having PVE >10 %. Three QTLs were detected for yield per plant while a total of seven for the traits imparting earliness viz. days to first male flower, node to first female flower and node to first male flower. Amongst all the QTLs detected, qFrtLDR-4-1 (K) had the maximum LOD (64.47) and PVE (34.57 %) value. Two hotspots were detected with multiple QTLs clustered in the LG 1. The first hotspot possessed four QTLs [qLfW-1-1, qMFR-1-1 (K), qSPF-1-1, qNFmlF-1-1 (K)] while the second had two related to yield per plant [qYldpl-1-1 (K) and qYldpl-1-1]. Many of these QTLs are also being reported for the first time in bitter gourd. The findings of the present study can be used to fasten the bitter gourd improvement by utilizing these in MAS, DNA fingerprinting, genetic mapping, genomics analysis etc.

Application of GIS for Monitoring Firefly Population Abundance (Pteroptyx tener) and the Influence of Abiotic Factors

This study focuses on the <i>Pteroptyx tener</i> species in the Sepetang River, Malaysia, aiming to evaluate the firefly’s abundance and explore its correlation with various biotic and abiotic parameters. The study was conducted over six months, from November 2021 to April 2022, utilizing Geographic Information System (GIS) software to apply hotspot mapping and Inverse Distance Weighting (IDW) analysis to elucidate the spatial distribution of firefly populations. A total of 111,615 individuals were recorded, with a particular focus on this firefly species’ presence on their display trees. Hotspot analysis showed that Station 6, located at the mouth of a river with dense mangroves, hosted 55,723 fireflies (50.01%). In contrast, Stations 9 and 10, near ponds and shrimp settlements, recorded 517–723 fireflies (0.65% and 0.46%). Pearson’s correlation coefficient (r) unveiled a statistically significant positive correlation (r = 0.88, p < 0.05) between wind speed and the abundance of firefly populations within the Sepetang River. However, no statistically significant correlation (p > 0.05) was found between firefly abundance and various other abiotic parameters, including relative humidity (RH), air temperature, tide level, pH, electrical conductivity (EC), salinity, total dissolved solids (TDS), and water clarity. Thus, the results revealed the preference for fireflies due to the availability of vegetation, wind speed and minimal disturbance in this area. In conclusion, this study’s information significantly adds to our understanding of these interesting insects and their complicated relationships in nature. It underscores the importance of preserving their habitats and ecosystems.

Natural variation in MdNAC5 contributes to fruit firmness and ripening divergence in apple

Abstract Fruit firmness is an important trait for characterizing the quality and value of apple. It is also serves as an indicator of fruit maturity, as it is a complex trait regulated by multiple genes. Re-sequencing techniques can be employed to elucidate variations in such complex fruit traits. Here, the whole genomes of 294 F1 hybrids of ‘Fuji’ and ‘Cripp's Pink’ were re-sequenced, and a high-density bin-map was constructed using 5,014 bin markers with a total map distance of 2,213.23 cM and an average map distance of 0.44 cM. Quantitative trait loci (QTLs) of traits related to fruit were mapped, and an A-T allele variant identified in the coding region of MdNAC5 was found to potentially regulate fruit firmness and ripening. The overexpression of MdNAC5A resulted in higher production of methionine and 1-aminocyclopropanecarboxylic acid compared to MdNAC5T, leading to reduced fruit firmness and accelerated ripening in apples and tomatoes. Furthermore, the activities of MdNAC5A and MdNAC5T were enhanced through their differential binding to the promoter regions of MdACS1 and MdERF3. Spatial variations in MdNAC5A and MdNAC5T caused changes in MdACS1 expression following their interaction with MdERF3. Ultimately, utilizing different MdNAC5 alleles offers a strategy to manipulate fruit firmness in apple breeding.

Genome-wide association analysis of grain yield and Striga hermonthica and S. asiatica resistance in tropical and sub-tropical maize populations

BackgroundGenetic improvement for Striga hermonthica (Sh) and S. asiatica (Sa) resistance is the most economical and effective control method to enhance the productivity of maize and other major cereal crops. Hence, identification of quantitative trait loci (QTL) associated with Striga resistance and economic traits will guide the pace and precision of resistance breeding in maize. The objective of this study was to undertake a genome-wide association analysis of grain yield and Sh and Sa resistance among tropical and sub-tropical maize populations to identify putative genetic markers and genes for resistance breeding. 126 maize genotypes were evaluated under controlled environment conditions using artificial infestation of Sh and Sa. The test genotypes were profiled for grain yield (GY), Striga emergence counts at 8 (SEC8) and 10 (SEC10) weeks after planting, and Striga damage rate scores at 8 (SDR8) and 10 (SDR10) weeks after planting. Population structure analysis and genome-wide association mapping were undertaken based on 16,000 single nucleotide polymorphism (SNP) markers.ResultsA linkage disequilibrium (LD) analysis in 798,675 marker pairs revealed that 21.52% of pairs were in significant linkage (P < 0.001). Across the chromosomes, the LD between SNPs decayed below a critical level (r2 = 0.1) at a map distance of 0.19 Mbp. The genome-wide association study identified 50 significant loci associated with Sh resistance and 22 significant loci linked to Sa resistance, corresponding to 39 and 19 candidate genes, respectively.ConclusionThe study found non-significant QTL associated with dual resistance to the two examined Striga species Some of the detected genes reportedly conditioned insect and pathogen resistance, plant cell development, variable senescence, and pollen fertility. The markers detected in the present study for Sa resistance were reported for the first time. The gene Zm00001eb219710 was pleiotropic, and conditioned GY and SEC10, while Zm00001eb165170 affected SDR8 and SDR10, and Zm00001eb112030 conditioned SDR8 and SDR10 associated with Sh resistance. The candidate genes may facilitate simultaneous selection for Sh and Sa resistance and grain yield in maize after further validation and introgression in breeding pipelines. Overall, we recommend breeding maize specifically for resistance to each Striga species using germplasm adapted to the endemic region of each parasite.

High robustness image encryption scheme utilizing memristive hyperchaotic map and Manhattan distance

High robustness image encryption scheme utilizing memristive hyperchaotic map and Manhattan distance

QTL mapping to identify loci and candidate genes associated with freezing tolerance trait in Camelina sativa

Lack of freezing tolerance is a major constraint for the production of agronomically important Brassica species, particularly in the Northern Great Plains (NGP) of the United States and Canada. However, within the Brassicaceae family, winter germplasm of camelina have shown excellent freezing tolerance and overwinter potential in the NGPs. Differences in freezing tolerance between a winter variety (Joelle) and a spring variety (C046) of camelina appear to be controlled by a small number of dominant or co-dominant genes. To unravel the genetic mechanisms for the differences in freezing tolerance, 254 Recombinant Inbred Lines (RILs) were developed using reciprocal crosses between these two camelina varieties. The RIL population was phenotyped at the F7 stage for freezing tolerance under controlled conditions and genotyped by whole-genome skim sequencing. A one-way ANOVA test revealed a significant (P < 0.001) difference exists among the RILs for freezing tolerance. A significant and strong correlation (r = 0.60, P < 0.001) was also observed between freezing tolerance and flowering time, indicating that regulation of flowering time might also influence freezing tolerance in camelina. A de novo linkage map was constructed using 4507 SNP markers covering a total of 1208.5 cM map distance with an average of 0.3 cM distances between the markers, which formed 20 linkage groups representing the 20 chromosomes (Chr) of C. sativa. The QTL analyses using three different programs revealed significant loci on Chr 8, 11, 13, 16 and 18 with LOD threshold value of over 3.5 for freezing tolerance. The QTL peaks with the greatest LOD values of 20.7 and 26.8 were observed at Chr 8 and Chr 13 and accounted for 18.3 % and 25.3 % of the phenotypic variation respectively. A total of 3369 annotated camelina genes were identified within ±50 Kb from the consensus QTL intervals generated from the output of the three mapping programs. Among them, 125 were transcription factors including twelve MIKC_MADS on Chr 8, 11, 13, 16 and 18 and two that annotate as the floral regulators FLOWERING LOCUS C (FLC) on Chr 8 and 13, an orthologue of MADS AFFECTING FLOWERING 3 and 4 (MAF4 and MAF3) of arabidopsis on Chr18, and an orthologue of SHORT VEGETATIVE PHASE (SVP) on Chr 16. Although many of the candidate genes identified near the freezing tolerance QTLs have previously been associated with flowering time, further studies are needed to help unravel how these genes impact freezing tolerance mechanisms and improve freezing tolerance in camelina and other Brassica crop species.

Exploration on the spiking response of a single compartment neuron with multiple active properties under electrical stimuli

The study of modulating the neuronal signals by electrical stimuli is important to intervene the abnormal neuronal firing and bring them to a normal state. Spike trains, which are the highest quality of brain signals, have been deficiently explored and analyzed owing to the challenges of obtaining them in reality. In this regard, this paper aims to investigate and analyze the effect of electrical stimuli on the spiking response of neurons, and the following work is to be carried out. The relationships between the spiking response and three parameters (namely, the amplitude of the electrode current (EC), the angular velocity of the electric field current (EFC), and the signal-noise ratio (SNR)) are examined on a neuronal model with spatial length and multiple active properties. When specific currents with different SNRs are imposed on the neurons, their influence on the spiking response is further explored. With regard to the spiking response, the main focus is on three characteristics, i.e., the spiking pattern, the spike count (SC), and the spiking arrangement. An algorithm, called the return map distance (RMD) algorithm, is proposed in this paper, and gives the classification of spiking patterns a quantitative criterion. Based on it, the spiking patterns are classified in this paper as busting spike train, regular spike train (RST), and meager spike train (MST). Simulation results indicate that both the amplitude of the EC and the angular velocity of the EFC change the neuronal spiking patterns. As the amplitude (angular velocity) of the EC (EFC) increases, the spiking pattern of the Soldado-Magraner model (SMM) eventually tends to RST (MST). In addition, the SC increases with the amplitude of the EC, while it does not hold for the SC with respect to the angular velocity of the EFC. Furthermore, the spiking arrangement and the SC are severely destroyed for the EC with low SNRs, while three spiking features of the SMM under EFC are all robust to the different SNRs, which implies that compared with the EC, the spiking responses of the SMM under EFC are more stable. The findings in this paper may provide some theoretical guidance to the fields related to neuronal firing, such as brain-computer interfaces and electrotherapy. The RMD algorithm proposed here can be applied to more individual neurons, and the spiking arrangement discussed here could be regarded as an effective encoding way for spike trains.

Multiple Localization Analysis of the Major QTL-sfw 2.2 for Controlling Single Fruit Weight Traits in Melon Based on SLAF Sequencing.

Cucumis melo is an annual dicotyledonous trailing herb. It is fruity, cool, and refreshing to eat and is widely loved by consumers worldwide. The single fruit weight is an important factor affecting the yield, and thus the income and economic benefits, of melon crops. In this study, to identify the main QTLs (quantitative trait locus) controlling the single fruit weight of melon and thereby identify candidate genes controlling this trait, specific-locus amplified fragment sequencing (SLAF) analysis was performed on the offspring of female 1244 plants crossed with male MS-5 plants. A total of 115 individual plants in the melon F2 population were analyzed to construct a genetic linkage map with a total map distance of 1383.88 cM by the group in the early stages of the project, which was divided into 12 linkage groups with a total of 10,596 SLAF markers spaced at an average genetic distance of 0.13 cM. A total of six QTLs controlling single fruit weight (sfw loci) were detected. Seven pairs of markers with polymorphisms were obtained by screening candidate intervals from the SLAF data. The primary QTL sfw2.2 was further studied in 300 F2:3 family lines grown in 2020 and 2021, respectively, a positioning sfw2.2 between the markers CY Indel 11 and CY Indel 16, between 18,568,142 and 18,704,724 on chromosome 2. This interval contained 136.58 kb and included three genes with functional annotations, MELO3C029673, MELO3C029669, and MELO3C029674. Gene expression information for different fruit development stages was obtained from 1244 and MS-5 fruits on the 15d, 25d, and 35d after pollination, and qRT-PCR (quantitative reverse transcription-PCR) indicated that the expression of the MELO3C029669 gene significantly differed between the parents during the three periods. The gene sequences between the parents of MELO3C029669 were analyzed and compared, a base mutation was found to occur in the intronic interval between the parents of the gene, from A-G. Phylogenetic evolutionary tree analysis revealed that the candidate gene MELO3C029669 is most closely related to Pisum sativum Fimbrin-5 variant 2 and most distantly related to Cucumis melo var. makuwa. Therefore, it was hypothesized that MELO3C029669 is the primary major locus controlling single fruit weight in melon. These results not only provide a theoretical basis for further studies to find genes with functions in melon single fruit weight but also lay the foundation for accelerating breakthroughs and innovations in melon breeding.

Novel Cascade Alpha Satellite HORs in Orangutan Chromosome 13 Assembly: Discovery of the 59mer HOR-The largest Unit in Primates-And the Missing Triplet 45/27/18 HOR in Human T2T-CHM13v2.0 Assembly.

From the recent genome assembly NHGRI_mPonAbe1-v2.0_NCBI (GCF_028885655.2) of orangutan chromosome 13, we computed the precise alpha satellite higher-order repeat (HOR) structure using the novel high-precision GRM2023 algorithm with Global Repeat Map (GRM) and Monomer Distance (MD) diagrams. This study rigorously identified alpha satellite HORs in the centromere of orangutan chromosome 13, discovering a novel 59mer HOR-the longest HOR unit identified in any primate to date. Additionally, it revealed the first intertwined sequence of three HORs, 18mer/27mer/45mer HORs, with a common aligned "backbone" across all HOR copies. The major 7mer HOR exhibits a Willard's-type canonical copy, although some segments of the array display significant irregularities. In contrast, the 14mer HOR forms a regular Willard's-type HOR array. Surprisingly, the GRM2023 high-precision analysis of chromosome 13 of human genome assembly T2T-CHM13v2.0 reveals the presence of only a 7mer HOR, despite both the orangutan and human genome assemblies being derived from whole genome shotgun sequences.

Enhanced Real-Time Target Detection for Picking Robots Using Lightweight CenterNet in Complex Orchard Environments

The rapid development of artificial intelligence and remote sensing technologies is indispensable for modern agriculture. In orchard environments, challenges such as varying light conditions and shading complicate the tasks of intelligent picking robots. To enhance the recognition accuracy and efficiency of apple-picking robots, this study aimed to achieve high detection accuracy in complex orchard environments while reducing model computation and time consumption. This study utilized the CenterNet neural network as the detection framework, introducing gray-centered RGB color space vertical decomposition maps and employing grouped convolutions and depth-separable convolutions to design a lightweight feature extraction network, Light-Weight Net, comprising eight bottleneck structures. Based on the recognition results, the 3D coordinates of the picking point were determined within the camera coordinate system by using the transformation relationship between the image’s physical coordinate system and the camera coordinate system, along with depth map distance information of the depth map. Experimental results obtained using a testbed with an orchard-picking robot indicated that the proposed model achieved an average precision (AP) of 96.80% on the test set, with real-time performance of 18.91 frames per second (FPS) and a model size of only 17.56 MB. In addition, the root-mean-square error of positioning accuracy in the orchard test was 4.405 mm, satisfying the high-precision positioning requirements of the picking robot vision system in complex orchard environments.

Mendelian segregation and high recombination rates facilitate genetic analyses in Cryptosporidium parvum.

Very little is known about the process of meiosis in the apicomplexan parasite Cryptosporidium despite the essentiality of sex in its life cycle. Most cell lines only support asexual growth of Cryptosporidium parvum (C. parvum), but stem cell derived intestinal epithelial cells grown under air-liquid interface (ALI) conditions support the sexual cycle. To examine chromosomal dynamics during meiosis in C. parvum, we generated two transgenic lines of parasites that were fluorescently tagged with mCherry or GFP on chromosomes 1 or 5, respectively. Infection of ALI cultures or Ifngr1-/- mice with mCherry and GFP parasites resulted in cross-fertilization and the formation of "yellow" oocysts, which contain 4 haploid sporozoites that are the product of meiosis. Recombinant oocysts from the F1 generation were purified and used to infect HCT-8 cultures, and phenotypes of the progeny were observed by microscopy. All possible phenotypes predicted by independent segregation were represented equally (~25%) in the population, indicating that C. parvum chromosomes exhibit a Mendelian inheritance pattern. The most common pattern observed from the outgrowth of single oocysts included all possible parental and recombinant phenotypes derived from a single meiotic event, suggesting a high rate of crossover. To estimate the frequency of crossover, additional loci on chromosomes 1 and 5 were tagged and used to monitor intrachromosomal crosses in Ifngr1-/- mice. Both chromosomes showed a high frequency of crossover compared to other apicomplexans with map distances (i.e., 1% recombination) of 3-12 kb. Overall, a high recombination rate may explain many unique characteristics observed in Cryptosporidium spp. such as high rates of speciation, wide variation in host range, and rapid evolution of host-specific virulence factors.

Genetic Map Construction and Primary Quantitative Trait Locus Analysis of Low-Light-Stress-Related Traits in Cucumber

To ascertain the effect of low-light stress (80 μmol·m−2·s−1) on cucumbers, we report on improving and breeding low-light-tolerant varieties by mining genes related to low-light tolerance. In this study, the quantitative trait locus (QTL) mapping of cucumber plant height and internode length under low-light stress was conducted using the F2 population, employing specific-length amplified fragment sequencing (SLAF-seq) and phenotypic analysis. A genetic map with a total length of 1114.29 c M was constructed from 1,076,599 SNPs, and 2233 single-nucleotide polymorphism (SNP) markers were distributed on seven linked groups, with an average map distance of 0.50 c M. Two QTLs related to plant height, CsPlH5.1 and CsPlH6.1, were detected on Chr.5 and Chr.6, with a cumulative contribution rate of 16.33%. The contribution rate (PVE), max LOD value, additive effect (ADD), and dominant effect (DOM) of CsPlH5.1 were 9.446%, 4.013, 1.005, and 0.563, respectively. CsPlH5.1 was located between 4,812,907 and 5,159,042 in the Gy14_V2.0 genome of cucumber, with a genetic distance of 0.32 Mb; the interval contained 41 candidate genes, and CsPlH6.1 was found to be located between Marker537985 (171.10 c M) and Marker537984 (171.55 c M), a range containing only one candidate gene. A total of 42 candidate genes related to photosynthesis, chloroplast development, abiotic stress, and plant growth were found in the location range associated with plant height. Simultaneously, a QTL (Csnd2_NdL6.1) for the second internode length was detected, and the max LOD, ADD, and DOM values were 5.689, 0.384, and −0.19, respectively. Csnd2_NdL6.1 was located between 29,572,188 and 29,604,215, with 0.03 Mb on Chr.6 including seven candidate genes. The molecular function of the CsGy6G032300 gene is involved with the binding of calcium ions, which may be related to the elongation and growth of plants; however, the population needs to be further expanded for acceptable localization verification. The results of this study provide a preliminary basis for the mining of essential genes of cucumber’s low-light tolerance and identifying low-light-tolerance genes.

Unraveling the genetic basis of superior traits in Gossypium barbadense: From phenotype to genotype

G. barbadense is renowned for its high-quality fiber and is highly regarded as a natural material in the textile industry. However, research on cotton has mainly focused on G. hirsutum, and progress in sea island cotton has been relatively slow. There was limited understanding of the genetic loci and transcriptional regulatory mechanisms of important traits, and the genetic basis for the development of superior traits remains unclear. In this study, a recombinant inbred line (RIL) population was constructed using two sea island cotton parents from different cotton regions. The phenotypic characteristics of the two parents and the RIL population, as well as the phenotypic correlations, heritability, and genetic models of the RIL population, were comprehensively analyzed. The RIL population was genotyped using whole-genome resequencing technology, and a high-density intraspecific linkage map was constructed, consisting of 5295 bin markers and a total genetic map distance of 2721.79 centimorgans (cM). Phenotypic data collected from five different environments were used to detect 169 quantitative trait loci (QTLs) using the composite interval mapping method. Among these QTLs, 30 were related to agronomic traits, 61 were related to yield traits, and 78 were related to fiber quality traits. Additionally, 17 QTL clusters were detected, and the additive effects of these clusters explained the correlation between different phenotypic traits. Candidate genes for stable QTLs related to agronomic and yield traits were identified through variant annotation and functional prediction. Two bin markers associated with lint percentage (LP) were validated as potential breeding markers. Furthermore, using RNA-seq data of cotton fiber from the RIL population parents, the dynamic changes in gene expression during different developmental stages of cotton fiber were revealed, and important differentially expressed genes in the secondary cell wall development and metabolism network of fibers were identified. Importantly, through the combined analysis of fiber trait QTLs and transcriptomes, eight candidate genes involved in regulating fiber quality traits were predicted, and the genetic basis of the excellent allele site qFL_D04_1 in the breeding history of Chinese sea island cotton was elucidated. In summary, this study provides new genetic resources and potential breeding markers for cotton variety improvement, valuable theoretical information for understanding the genetic basis of important traits in sea island cotton, and effectively promotes the development of cotton biotechnology breeding.

Analysis of landslide susceptibility and potential impacts on infrastructures and settlement areas (a case from the southeastern region of Türkiye)

Landslides have harmful effects not only on buildings but also on infrastructure and the natural environment. While they are typically triggered by natural events, such as heavy rainfalls and earthquakes, landslides can also be induced by anthropogenic activities, such as excavation and blasting. In certain regions, gigantic paleo-landslides exist, but triggering them is extremely difficult. However, triggering secondary landslides in gigantic paleo-landslides is relatively easy compared to the main corpus. The main purpose of this study was to produce a susceptibility map in a region in southeastern Türkiye and to discuss the impact of petroleum seismological investigation concerning the trigger of the landslides. For this purpose, a landslide inventory was compiled using geospatial data sets and field observations and used for landslide susceptibility mapping with the Random Forest algorithm. The accelerations sourced from blasting were also measured and the run-out distances were determined. A run-out distance map was produced using inverse distance weights. The study presents comprehensive insights by integrating a landslide susceptibility map and run-out distance map. It evaluates the impact of blasting on landslides through in-situ measurements and slope stability analyses. Findings indicate that no triggering effect on landslides was observed if the dynamite quantity remains below 4 kg and the blasting distance exceeds 10 m from the landslide.

Genome-Wide Mapping of Quantitative Trait Loci for Yield-Attributing Traits of Peanut.

Peanuts (Arachis hypogaea L.) are important high-protein and oil-containing legume crops adapted to arid to semi-arid regions. The yield and quality of peanuts are complex quantitative traits that show high environmental influence. In this study, a recombinant inbred line population (RIL) (Valencia-C × JUG-03) was developed and phenotyped for nine traits under two environments. A genetic map was constructed using 1323 SNP markers spanning a map distance of 2003.13 cM. Quantitative trait loci (QTL) analysis using this genetic map and phenotyping data identified seventeen QTLs for nine traits. Intriguingly, a total of four QTLs, two each for 100-seed weight (HSW) and shelling percentage (SP), showed major and consistent effects, explaining 10.98% to 14.65% phenotypic variation. The major QTLs for HSW and SP harbored genes associated with seed and pod development such as the seed maturation protein-encoding gene, serine-threonine phosphatase gene, TIR-NBS-LRR gene, protein kinase superfamily gene, bHLH transcription factor-encoding gene, isopentyl transferase gene, ethylene-responsive transcription factor-encoding gene and cytochrome P450 superfamily gene. Additionally, the identification of 76 major epistatic QTLs, with PVE ranging from 11.63% to 72.61%, highlighted their significant role in determining the yield- and quality-related traits. The significant G × E interaction revealed the existence of the major role of the environment in determining the phenotype of yield-attributing traits. Notably, the seed maturation protein-coding gene in the vicinity of major QTLs for HSW can be further investigated to develop a diagnostic marker for HSW in peanut breeding. This study provides understanding of the genetic factor governing peanut traits and valuable insights for future breeding efforts aimed at improving yield and quality.

QTL Mapping and Genetic Map for the Ornamental Sunflower in China

Quantitative trait locus (QTL) mapping and genetic map are of great significance for ornamental sunflowers in China. In this study, a total of 956.50 Mbp data were obtained, the average Q30 was 93.76%, the average GC content was 42.43%, and the GC distribution of the parents and F2 population of the ornamental sunflowers was normal. At the same time, the double-end comparison efficiency of control data was 90.28%, and the enzyme digestion efficiency was 92.01%. The Specific-Locus Amplified Fragment (SLAF) library construction was normal. Furthermore, a total of 734,893 SLAF markers were obtained, among which 127,855 were polymorphic SLAF markers and 38,908 could be used for genetic map construction, and the effective polymorphism of the parents was 5.29%. Moreover, we constructed a total of 17 linkage groups, with 6181 markers in the QTL mapping, the total map distance was 2608.66 cM, the marker integrity in the figure above was 99%, the proportion of double exchange was 0.05, the sequencing depth of the parents was 42.455 × , and the progeny was 9.24 × . The relationship of traits (plant height, stem diameter, disk diameter, number of petals, leaf number, stigma color, petal color, petiole color) and QTL mapping was closely related to show the best of ornamental effect.

Genome assembly and resequencing analyses provide new insights into the evolution, domestication and ornamental traits of crape myrtle.

Crape myrtle (Lagerstroemia indica) is a globally used ornamental woody plant and is the representative species of Lagerstroemia. However, studies on the evolution and genomic breeding of L. indica have been hindered by the lack of a reference genome. Here we assembled the first high-quality genome of L. indica using PacBio combined with Hi-C scaffolding to anchor the 329.14-Mb genome assembly into 24 pseudochromosomes. We detected a previously undescribed independent whole-genome triplication event occurring 35.5 million years ago in L. indica following its divergence from Punica granatum. After resequencing 73 accessions of Lagerstroemia, the main parents of modern crape myrtle cultivars were found to be L. indica and L. fauriei. During the process of domestication, genetic diversity tended to decrease in many plants, but this was not observed in L. indica. We constructed a high-density genetic linkage map with an average map distance of 0.33cM. Furthermore, we integrated the results of quantitative trait locus (QTL) using genetic mapping and bulk segregant analysis (BSA), revealing that the major-effect interval controlling internode length (IL) is located on chr1, which contains CDL15, CRG98, and GID1b1 associated with the phytohormone pathways. Analysis of gene expression of the red, purple, and white flower-colour flavonoid pathways revealed that differential expression of multiple genes determined the flower colour of L. indica, with white flowers having the lowest gene expression. In addition, BSA of purple- and green-leaved individuals of populations of L. indica was performed, and the leaf colour loci were mapped to chr12 and chr17. Within these intervals, we identified MYB35, NCED, and KAS1. Our genome assembly provided a foundation for investigating the evolution, population structure, and differentiation of Myrtaceae species and accelerating the molecular breeding of L. indica.

Genetic mapping identified three hotspot genomic regions and candidate genes controlling heat tolerance-related traits in groundnut.

Groundnut productivity and quality have been impeded by rising temperatures in semi-arid environments. Hence, understanding the effects and molecular mechanisms of heat stress tolerance will aid in tackling yield losses. In this context, a recombinant inbred line (RIL) population was developed and phenotyped for eight seasons at three locations for agronomic, phenological, and physiological traits under heat stress. A genetic map was constructed using genotyping-by-sequencing with 478 single-nucleotide polymorphism (SNP) loci spanning a map distance of 1,961.39 cM. Quantitative trait locus (QTL) analysis using phenotypic and genotypic data identified 45 major main-effect QTLs for 21 traits. Intriguingly, three QTL clusters (Cluster-1-Ah03, Cluster-2-Ah12, and Cluster-3-Ah20) harbor more than half of the major QTLs (30/45, 66.6%) for various heat tolerant traits, explaining 10.4%-38.6%, 10.6%-44.6%, and 10.1%-49.5% of phenotypic variance, respectively. Furthermore, important candidate genes encoding DHHC-type zinc finger family protein (arahy.J0Y6Y5), peptide transporter 1 (arahy.8ZMT0C), pentatricopeptide repeat-containing protein (arahy.4A4JE9), Ulp1 protease family (arahy.X568GS), Kelch repeat F-box protein (arahy.I7X4PC), FRIGIDA-like protein (arahy.0C3V8Z), and post-illumination chlorophyll fluorescence increase (arahy.92ZGJC) were the underlying three QTL clusters. The putative functions of these genes suggested their involvement in seed development, regulating plant architecture, yield, genesis and growth of plants, flowering time regulation, and photosynthesis. Our results could provide a platform for further fine mapping, gene discovery, and developing markers for genomics-assisted breeding to develop heat-tolerant groundnut varieties.

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

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

Genetic mapping identifies genomic regions and candidate genes for seed weight and shelling percentage in groundnut.

Seed size is not only a yield-related trait but also an important measure to determine the commercial value of groundnut in the international market. For instance, small size is preferred in oil production, whereas large-sized seeds are preferred in confectioneries. In order to identify the genomic regions associated with 100-seed weight (HSW) and shelling percentage (SHP), the recombinant inbred line (RIL) population (Chico × ICGV 02251) of 352 individuals was phenotyped for three seasons and genotyped with an Axiom_Arachis array containing 58K SNPs. A genetic map with 4199 SNP loci was constructed, spanning a map distance of 2708.36cM. QTL analysis identified six QTLs for SHP, with three consistent QTLs on chromosomes A05, A08, and B10. Similarly, for HSW, seven QTLs located on chromosomes A01, A02, A04, A10, B05, B06, and B09 were identified. BIG SEED locus and spermidine synthase candidate genes associated with seed weight were identified in the QTL region on chromosome B09. Laccase, fibre protein, lipid transfer protein, senescence-associated protein, and disease-resistant NBS-LRR proteins were identified in the QTL regions associated with shelling percentage. The associated markers for major-effect QTLs for both traits successfully distinguished between the small- and large-seeded RILs. QTLs identified for HSW and SHP can be used for developing potential selectable markers to improve the cultivars with desired seed size and shelling percentage to meet the demands of confectionery industries.