Independent genetic factors control floret number and spikelet number in Triticum turgidum ssp.

Wheat grain yield is a complex trait resulting from a trade-off among many distinct components. During wheat evolution, domestication events and then modern breeding have strongly increased the yield potential of wheat plants, by enhancing spike fertility. To address the genetic bases of spike fertility in terms of spikelet number per spike and floret number per spikelet, a population of 110 recombinant inbred lines (RILS) obtained crossing a Triticum turgidum ssp. durum cultivar (Latino) and a T. dicoccum accession (MG5323) was exploited. Being a modern durum and a semi-domesticated genotype, respectively, the two parents differ for spike architecture and fertility, and thus the corresponding RIL population is the ideal genetic material to dissect genetic bases of yield components. The RIL population was phenotyped in four environments. Using a high-density SNP genetic map and taking advantage of several genome sequencing available for Triticeae, a total of 94 QTLs were identified for the eight traits considered; these QTLs were further reduced to 17 groups, based on their genetic and physical co-location. QTLs controlling floret number per spikelet and spikelet number per spike mapped in non-overlapping chromosomal regions, suggesting that independent genetic factors determine these fertility-related traits. The physical intervals of QTL groups were considered for possible co-location with known genes functionally involved in spike fertility traits and with yield-related QTLs previously mapped in tetraploid wheat. The most interesting result concerns a QTL group on chromosome 5B, associated with spikelet number per spike, since it could host genes still uncharacterized for their association to spike fertility. Finally, we identified two different regions where the trade-off between fertility related traits and kernel weight is overcome. Further analyses of these regions could pave the way for a future identification of new genetic loci contributing to fertility traits essential for yield improvement in durum wheat.

Comparative transcriptome analysis and meta-QTLs mapping reveal the regulatory mechanism of cold tolerance in rice at the budding stage.

Rice (Oryza sativa L.) is one of the most extensively farmed food crops, but its development and productivity are significantly impacted by cold stress during the budding period. In this study, transcriptome sequencing was conducted on two types of rice: the cold-sensitive indica rice A117 and the substantially cold-tolerant japonica rice B106 under control and cold treatments. Differentially expressed genes between the two materials under cold conditions were analyzed using GO and KEGG enrichment analyses. The results revealed that processes such as the TCA cycle, glycolysis/glycogenesis, oxidative phosphorylation, and glutathione metabolism contribute to B106's cold tolerance. Additionally, an enrichment analysis of cold-induced genes in each material and shared genes identified significant enrichment in pathways such as glutathione metabolism, phenylpropanoid biosynthesis, and photosynthesis-antenna proteins. Initial cold tolerance QTLs at the rice bud stage were collected from published literature, and meta-QTL mapping identified 9 MQTLs. Gene expression profiling led to the identification of 75 potential DEGs within the 9 MQTLs region, from which four candidate genes (Os02g0194100, Os03g0802500, Os05g0129000, and Os07g0462000) were selected using qRT-PCR and gene annotation. These findings provide genetic resources for further research on the molecular mechanisms underlying rice's response to cold stress during the bud stage.

Ustilaginoidea virens, an emerging pathogen of rice: the dynamic interplay between the pathogen virulence strategies and host defense.

MAIN CONCLUSION: The Ustilaginoidea virens -rice pathosystem has been used as a model for flower-infecting fungal pathogens. The molecular biology of the interactions between U. virens and rice, with an emphasis on the attempt to get a deeper comprehension of the false smut fungus's genomes, proteome, host range, and pathogen biology, has been investigated. Meta-QTL analysis was performed to identify potential QTL hotspots for use in marker-assisted breeding. The Rice False Smut (RFS) caused by the fungus Ustilaginoidea virens currently threatens rice cultivators across the globe. RFS infects rice panicles, causing a significant reduction in grain yield. U. virens can also parasitize other hosts though they play only a minor role in its life cycle. Furthermore, because it produces mycotoxins in edible rice grains, it puts both humans and animals at risk of health problems. Although fungicides are used to control the disease, some fungicides have enabled the pathogen to develop resistance, making its management challenging. Several QTLs have been reported but stable gene(s) that confer RFS resistance have not been discovered yet. This review offers a comprehensive overview of the pathogen, its virulence mechanisms, the genome and proteome of U. virens, and its molecular interactions with rice. In addition, information has been compiled on reported resistance QTLs, facilitating the development of a consensus genetic map using meta-QTL analysis for identifying potential QTL hotspots. Finally, this review highlights current developments and trends in U. virens-rice pathosystem research while identifying opportunities for future investigations.

Host response to influenza infections in human blood: association of influenza severity with host genetics and transcriptomic response.

Introduction: Influenza virus infections are a major global health problem. Influenza can result in mild/moderate disease or progress to more severe disease, leading to high morbidity and mortality. Severity is thought to be primarily driven by immunopathology, but predicting which individuals are at a higher risk of being hospitalized warrants investigation into host genetics and the molecular signatures of the host response during influenza infections. Methods: Here, we performed transcriptome and genotype analysis in healthy controls and patients exhibiting mild/moderate or severe influenza (ICU patients). A unique aspect of our study was the genotyping of all participants, which allowed us to assign ethnicities based on genetic variation and assess whether the variation was correlated with expression levels. Results: We identified 169 differentially expressed genes and related molecular pathways between patients in the ICU and those who were not in the ICU. The transcriptome/genotype association analysis identified 871 genes associated to a genetic variant and 39 genes distinct between African-Americans and Caucasians. We also investigated the effects of age and sex and found only a few discernible gene effects in our cohort. Discussion: Together, our results highlight select risk factors that may contribute to an increased risk of ICU admission for influenza-infected patients. This should help to develop better diagnostic tools based on molecular signatures, in addition to a better understanding of the biological processes in the host response to influenza.

High-Density Genetic Map Construction and Quantitative Trait Locus Analysis of Fruit- and Oil-Related Traits in Camellia oleifera Based on Double Digest Restriction Site-Associated DNA Sequencing.

Camellia oleifera, an important tree species and source of edible oil in China, has received significant attention owing to the oil's high unsaturated fatty acid content, which has benefits for human health. However, the mechanisms underlying C. oleifera yield and oil quality are largely unknown. In this study, 180 F1 progenies were obtained from two parents with obvious differences in fruit- and oil-related traits. We constructed a high-density genetic map using a double digest restriction site-associated DNA sequencing (ddRAD-Seq) strategy in C. oleifera. This map spanned 3327 cM and anchored 2780 markers in 15 linkage groups (LGs), with an average marker interval of 1.20 cM. A total of 221 quantitative trait loci (QTLs) associated with fruit- and oil-related traits were identified across three years' worth of phenotypic data. Nine QTLs were detected simultaneously in at least two different years, located on LG02, LG04, LG05, LG06, and LG11, and explained 8.5-16.6% of the phenotypic variation in the corresponding traits, respectively. Seventeen major QTLs were obtained that explained 13.0-16.6% of the phenotypic variance. Eleven and five flanking SNPs of major QTLs for fruit- and oil-related traits were detected which could be used for marker-assisted selection in C. oleifera breeding programs. Furthermore, 202 potential candidate genes in QTL regions were identified based on the collinearity of the genetic map and the C. oleifera "CON" genome. A potential regulatory network controlling fruit development and oil biosynthesis was constructed to dissect the complex mechanism of oil accumulation. The dissection of these QTLs will facilitate the gene cloning underlying lipid synthesis and increase our understanding in order to enhance C. oleifera oil yield and quality.

Genetic effects on the skin methylome in healthy older twins.

Whole-skin DNA methylation variation has been implicated in several diseases, including melanoma, but its genetic basis has not yet been fully characterized. Using bulk skin tissue samples from 414 healthy female UK twins, we performed twin-based heritability and methylation quantitative trait loci (meQTL) analyses for >400,000 DNA methylation sites. We find that the human skin DNA methylome is on average less heritable than previously estimated in blood and other tissues (mean heritability: 10.02%). meQTL analysis identified local genetic effects influencing DNA methylation at 18.8% (76,442) of tested CpG sites, as well as 1,775 CpG sites associated with at least one distal genetic variant. As a functional follow-up, we performed skin expression QTL (eQTL) analyses in a partially overlapping sample of 604 female twins. Colocalization analysis identified over 3,500 shared genetic effects affecting thousands of CpG sites (10,067) and genes (4,475). Mediation analysis of putative colocalized gene-CpG pairs identified 114 genes with evidence for eQTL effects being mediated by DNA methylation in skin, including in genes implicating skin disease such as ALOX12 and CSPG4. We further explored the relevance of skin meQTLs to skin disease and found that skin meQTLs and CpGs under genetic influence were enriched for multiple skin-related genome-wide and epigenome-wide association signals, including for melanoma and psoriasis. Our findings give insights into the regulatory landscape of epigenomic variation in skin.

Multiomics of a rice population identifies genes and genomic regions that bestow low glycemic index and high protein content.

To counter the rising incidence of diabetes and to meet the daily protein needs, we created low glycemic index (GI) rice varieties with protein content (PC) surpassing 14%. In the development of recombinant inbred lines using Samba Mahsuri and IR36 amylose extender (IR36ae) as parental lines, we identified quantitative trait loci and genes associated with low GI, high amylose content (AC), and high PC. By integrating genetic techniques with classification models, this comprehensive approach identified candidate genes on chromosome 2 (qGI2.1/qAC2.1 spanning the region from 18.62 Mb to 19.95 Mb), exerting influence on low GI and high amylose. Notably, the phenotypic variant with high value was associated with the recessive allele of the starch branching enzyme 2b (sbeIIb). The genome-edited sbeIIb line confirmed low GI phenotype in milled rice grains. Further, combinations of alleles created by the highly significant SNPs from the targeted associations and epistatically interacting genes showed ultralow GI phenotypes with high amylose and high protein. Metabolomics analysis of rice with varying AC, PC, and GI revealed that the superior lines of high AC and PC, and low GI were preferentially enriched in glycolytic and amino acid metabolisms, whereas the inferior lines of low AC and PC and high GI were enriched with fatty acid metabolism. The high amylose high protein recombinant inbred line (HAHP_101) was enriched in essential amino acids like lysine. Such lines may be highly relevant for food product development to address diabetes and malnutrition.

Analysis of genome-wide association studies of low-temperature germination in Xian and Geng rice.

Rice is the leading global staple crop. Low temperatures pose negative impacts on rice's optimal growth and development. Rice cultivars acclimating to low temperatures exhibited improved seedling emergence under direct-seeded sowing conditions, yet little is known about the genes that regulate germination at low temperatures (LTG). In this research investigation, we've performed whole genome sequencing for the 273 rice plant materials. Using the best linear unbiased prediction (BLUP) values for each rice material, we identified 7 LTG-related traits and performed the efficient genetic analysis and genome-wide association study (GWAS). As a result of this, 95 quantitative trait loci (QTLs) and 1001 candidate genes associated with LTG in rice were identified. Haplotype analysis and functional annotation of the candidate genes resulted in the identification of three promising candidate genes (LOC_Os08g30520 for regulating LTG4 and LTG5, LOC_Os10g02625 for regulating LTG6, LTg7 and LTG8, and LOC_Os12g31460 for regulating LTG7, LTg8 and LTG9) involving in the regulation of LTG in rice. This research provides a solid foundation for addressing the LTG issue in rice and will be valuable in future direct-seeded rice breeding programs.

Uncovering novel genes for drought stress in rice at germination stage using genome wide association study.

Introduction: Breeding rice with drought tolerance for harsh environments is crucial for agricultural sustainability. Understanding the genetic underpinnings of drought tolerance is vital for developing resilient rice varieties. Genome-wide association studies (GWAS) have emerged as pivotal tools in unravelling the complex genetic architecture of traits like drought tolerance, capitalizing on the natural genetic diversity within rice germplasm collections. Methods: In this study, a comprehensive panel of 210 rice varieties was phenotyped over ten days in controlled conditions, subjected to simulated drought stress using 20% PEG 6000 in petri dishes. Throughout the stress period, crucial traits such as germination percentage (GP), germination rate index (GRI), mean germination time (MGT), and seedling percentage (SP) were meticulously monitored. Results: The GWAS analysis uncovered a total of 38 QTLs associated with drought tolerance traits, including novel loci like qMGT-5.2, qSP-3, qSP7.2, and qGP-5.2. Additionally, RNA-seq analysis identified ten genes with significant expression differences under drought stress conditions. Notably, haplotype analysis pinpointed elite haplotypes in specific genes linked to heightened drought tolerance. Discussion: Overall, this study underscores the importance of GWAS in validating known genes while unearthing novel loci to enrich the genetic resources for enhancing drought tolerance in rice breeding programs.

Fine mapping of interspecific secondary CSSL populations revealed key regulators for grain weight at qTGW3.1 locus from Oryza nivara.

Grain weight (GW) is the most important stable trait that directly contributes to crop yield in case of cereals. A total of 105 backcross introgression lines (BC2F10 BILs) derived from Swarna/O. nivara IRGC81848 (NPS) and 90 BILs from Swarna/O. nivara IRGC81832 (NPK) were evaluated for thousand-grain weight (TGW) across four years (wet seasons 2014, 2015, 2016 and 2018) and chromosome segment substitution lines (CSSLs) were selected. From significant pair- wise mean comparison with Swarna, a total of 77 positively and 29 negatively significant NPS lines and 62 positively and 29 negatively significant NPK lines were identified. In all 4 years, 14 NPS lines and 9 NPK lines were positively significant and one-line NPS69 (IET22161) was negatively significant for TGW over Swarna consistently. NPS lines and NPK lines were genotyped using 111 and 140 polymorphic SSRs respectively. Quantitative trait locus (QTL) mapping using ICIM v4.2 software showed 13 QTLs for TGW in NPS. Three major effect QTLs qTGW2.1, qTGW8.1 and qTGW11.1 were identified in NPS for two or more years with PVE ranging from 8 to 14%. Likewise, 10 QTLs were identified in NPK and including two major effect QTL qTGW3.1 and qTGW12.1 with 6 to 32% PVE. In all QTLs, O. nivara alleles increased TGW. These consistent QTLs are very suitable for fine mapping and functional analysis of grain weight. Further in this study, CSSLs NPS1 (10-2S) and NPK61 (158 K) with significantly higher grain weight than the recurrent parent, Swarna cv. Oryza sativa were selected from each population and secondary F2 mapping populations were developed. Using Bulked Segregant QTL sequencing, a grain weight QTL, designated as qTGW3.1 was fine mapped from the cross between NPK61 and Swarna. This QTL explained 48% (logarithm of odds = 32.2) of the phenotypic variations and was fine mapped to a 31 kb interval using recombinant analysis. GRAS transcription factor gene (OS03go103400) involved in plant growth and development located at this genomic locus might be the candidate gene for qTGW3.1. The results of this study will help in further functional studies and improving the knowledge related to the molecular mechanism of grain weight in Oryza and lays a solid foundation for the breeding for high yield. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-024-01483-0.

Genome-Wide Association Analysis Identifies Candidate Loci for Callus Induction in Rice (Oryza sativa L.).

Callus induction (CI) is a critical trait for transforming desirable genes in plants. A genome-wide association study (GWAS) analysis was conducted on the rice germplasms of 110 Indica rice accessions, in which three tissue culture media, B5, MS, and N6, were used for the CI of those rice panels' mature seeds. Seven quantitative trait loci (QTLs) on rice chromosomes 2, 6, 7, and 11 affected the CI percentage in the three media. For the B5 medium, one QTL (qCI-B5-Chr6) was identified on rice chromosome 6; for the MS medium, two QTLs were identified on rice chromosomes 2 and 6 (qCI-MS-Chr2 and qCI-MS-Chr6, respectively); for the N6 medium, four QTLs were identified on rice chromosomes 6, 7, and 11 (qCI-N6-Chr6.1 and qCI-N6-Chr6.2, qCI-N6-Chr7, and qCI-N6-Chr11, respectively). Fifty-five genes were identified within the haplotype blocks corresponding to these QTLs, thirty-one of which showed haplotypes associated with different CI percentages in those media. qCI-B5-Chr6 was located in the same region as qCI-N6-Chr6.2, and the Caleosin-related family protein was also identified in this region. Analysis of the gene-based haplotype revealed the association of this gene with different CI percentages in both B5 and N6 media, suggesting that the gene may play a critical role in the CI mechanism. Moreover, several genes, including those that encode the beta-tubulin protein, zinc finger protein, RNP-1 domain-containing protein, and lysophosphatidic acid acyltransferase, were associated with different CI percentages in the N6 medium. The results of this study provide insights into the potential QTLs and candidate genes for callus induction in rice that contribute to our understanding of the physiological and biochemical processes involved in callus formation, which is an essential tool in the molecular breeding of rice.

Heritability estimates and genome-wide association study of methane emission traits in Nellore cattle.

The objectives of the present study were to estimate the heritability for daily methane emission (CH4) and residual daily methane emission (CH4res) in Nellore cattle, as well as to perform genome-wide association studies (GWAS) to identify genomic regions and candidate genes influencing the genetic variation of CH4 and CH4res. Methane emission phenotypes of 743 Nellore animals belonging to 3 breeding programs were evaluated. CH4 was measured using the sulfur hexafluoride (SF6) tracer technique (which involves an SF6 permeation tube introduced into the rumen, and an appropriate apparatus on each animal), and CH4res was obtained as the difference between observed CH4 and CH4 adjusted for dry matter intake. A total of 6,252 genotyped individuals were used for genomic analyses. Data were analyzed with a univariate animal model by the single-step GBLUP method using the average information restricted maximum likelihood (AIREML) algorithm. The effects of single nucleotide polymorphisms (SNPs) were obtained using a single-step GWAS approach. Candidate genes were identified based on genomic windows associated with quantitative trait loci (QTLs) related to the 2 traits. Annotation of QTLs and identification of candidate genes were based on the initial and final coordinates of each genomic window considering the bovine genome ARS-UCD1.2 assembly. Heritability estimates were of moderate to high magnitude, being 0.42 ±â€…0.09 for CH4 and 0.21 ±â€…0.09 for CH4res, indicating that these traits will respond rapidly to genetic selection. GWAS revealed 11 and 15 SNPs that were significantly associated (P < 10-6) with genetic variation of CH4 and CH4res, respectively. QTLs associated with feed efficiency, residual feed intake, body weight, and height overlapped with significant markers for the traits evaluated. Ten candidate genes were present in the regions of significant SNPs; 3 were associated with CH4 and 7 with CH4res. The identified genes are related to different functions such as modulation of the rumen microbiota, fatty acid production, and lipid metabolism. CH4 and CH4res presented sufficient genetic variation and may respond rapidly to selection. Therefore, these traits can be included in animal breeding programs aimed at reducing enteric methane emissions across generations.

Genetic selection designed to reduce the amount of enteric methane emission from livestock is a mitigation strategy to ensure more sustainable production over generations since genetic gains are cumulative. Brazil is a large producer of beef, and the Nellore breed (Bos taurus indicus) plays a very important role in this production. There are a few studies evaluating genetic and genomic aspects of enteric methane emission in Nellore cattle. The objectives of the present study were to estimate the heritability of daily methane emission (CH4) and residual daily methane emission (CH4res) in Nellore cattle, as well as to identify genomic regions and candidate genes associated with genetic variation of these traits. The heritability estimates for CH4 and CH4res were of moderate to high magnitude (0.42 ±â€…0.09 and 0.21 ±â€…0.09, respectively). Genome-wide association analyses revealed new loci associated with methane emission in Nellore cattle on chromosomes 5, 11, 17, and 20, where 10 candidate genes were identified, 3 for CH4 and 7 for CH4res. The 2 traits possess sufficient genetic variability to be included as selection criteria in breeding programs.

Genome-wide association study of trace elements in maize kernels.

Maize (Zea mays L.), a staple food and significant economic crop, is enriched with riboflavin, micronutrients and other compounds that are beneficial for human health. As emphasis on the nutritional quality of crops increases maize research has expanded to focus on both yield and quality. This study exploreed the genetic factors influencing micronutrient levels in maize kernels through a comprehensive genome-wide association study (GWAS). We utilized a diverse panel of 244 inbred maize lines and approximately 3 million single nucleotide polymorphisms (SNPs) to investigate the accumulation of essential and trace elements including cadmium (Cd), cobalt (Co), copper (Cu), nickel (Ni), selenium (Se) and zinc (Zn). Our analysis identified 842 quantitative trait loci (QTLs), with 12 QTLs shared across multiple elements and pinpointed 524 potential genes within a 100 kb radius of these QTLs. Notably ZmHMA3 has emerged as a key candidate gene previously reported to influence the Cd accumulation. We highlighted ten pivotal genes associated with trace element transport including those encoding heavy metal ATPases, MYB transcription factors, ABC transporters and other crucial proteins involved in metal handling. Additionally, haplotype analysis revealed that eight inbred linesaccumulated relatively high levels of beneficial elements while harmful elements were minimized. These findings elucidate the genetic mechanisms underlying trace element accumulation in maize kernels and provide a foundation for the breeding of nutritionally enhanced maize varieties.

The Molecular Mechanism of Cold-Stress Tolerance: Cold Responsive Genes and Their Mechanisms in Rice (Oryza sativa L.).

Rice (Oryza sativa L.) production is highly susceptible to temperature fluctuations, which can significantly reduce plant growth and development at different developmental stages, resulting in a dramatic loss of grain yield. Over the past century, substantial efforts have been undertaken to investigate the physiological, biochemical, and molecular mechanisms of cold stress tolerance in rice. This review aims to provide a comprehensive overview of the recent developments and trends in this field. We summarized the previous advancements and methodologies used for identifying cold-responsive genes and the molecular mechanisms of cold tolerance in rice. Integration of new technologies has significantly improved studies in this era, facilitating the identification of essential genes, QTLs, and molecular modules in rice. These findings have accelerated the molecular breeding of cold-resistant rice varieties. In addition, functional genomics, including the investigation of natural variations in alleles and artificially developed mutants, is emerging as an exciting new approach to investigating cold tolerance. Looking ahead, it is imperative for scientists to evaluate the collective impacts of these novel genes to develop rice cultivars resilient to global climate change.

Copy number variations affecting growth curve parameters in a crossbred chicken population.

Copy number variations (CNVs) are key structural variations in the genome and may contribute to phenotypic differences. In this study, we used a F2 chicken population created from reciprocal crossing between fast-growing Arian broiler line and Urmia native chickens. The chickens were genotyped by 60 K SNP BeadChip, and PennCNV algorithm was used to detect genome-wide CNVs. The growth curve parameters of W0, k, L, Wf, Wi, ti and average GR were used as phenotypic data. The association between CNV and growth curve parameters was carried out using the CNVRanger R/Bioconductor package. Five CNV regions (CNVRs) were chosen for the validation experiment using qPCR. Gene enrichment analysis was done using WebGestalt. The STRING database was used to search for significant pathways. The results identified 966 CNVs and 600 CNVRs including 468 gains, 67 losses, and 65 both events on autosomal chromosomes. Validation of the CNVRs obtained from the qPCR assay were 79 % consistent with the prediction by PennCNV. A total of 43 significant CNVs were obtained for the seven growth curve parameters. The 416 genes annotated for significant CNVs. Six genes out of 416 genes were most related to growth curve parameters. These genes were LCP2, Dock2, CD80, CYFIP1, NIPA1 and NIPA2. Some of these genes in their biological process were associated with the growth, reproduction and development of cells or organs that ultimately lead to the growth of the body. The results of the study could pave the way for better understanding the molecular process of CNVs and growth curve parameters in birds.

Mapping and candidate gene analysis of QTLs for grain shape in a rice chromosome segment substitution line Z485 and breeding of SSSLs.

Grain shape is one of the most important factors that affects rice yield. Cloning novel grain shape genes and analyzing their genetic mechanisms are crucial for high yield breeding. In this study, a slender grain CSSL-Z485 with 3-segments substitution in the genetic background of Nipponbare was constructed in rice. Cytological analysis showed that the longer grain length of Z485 was related to the increase in glume cell numbers, while the narrower grain width was associated with the decrease in cell width. Three grain shape-related quantitative trait locus (QTLs), including qGL12, qGW12, and qRLW12, were identified through the F2 population constructed from a cross between Nipponbare and Z485. Furthermore, four single segment substitution lines (SSSLs, S1-S4) carrying the target QTLs were dissected from Z485 by MAS. Finally, three candidate genes of qGL12 for grain length and qGW12 for grain width located in S3 were confirmed by DNA sequencing, RT-qPCR, and protein structure prediction. Specifically, candidate gene 1 encodes a ubiquitin family protein, while candidate genes 2 and 3 encode zinc finger proteins. The results provide valuable germplasm resources for cloning novel grain shape genes and molecular breeding by design. Supplementary information: The online version contains supplementary material available at 10.1007/s11032-024-01480-x.

RNA-Seq Bulked Segregant Analysis of an Exotic B. napus ssp. napobrassica (Rutabaga) F2 Population Reveals Novel QTLs for Breeding Clubroot-Resistant Canola.

In this study, a rutabaga (Brassica napus ssp. napobrassica) donor parent FGRA106, which exhibited broad-spectrum resistance to 17 isolates representing 16 pathotypes of Plasmodiophora brassicae, was used in genetic crosses with the susceptible spring-type canola (B. napus ssp. napus) accession FG769. The F2 plants derived from a clubroot-resistant F1 plant were screened against three P. brassicae isolates representing pathotypes 3A, 3D, and 3H. Chi-square (χ2) goodness-of-fit tests indicated that the F2 plants inherited two major clubroot resistance genes from the CR donor FGRA106. The total RNA from plants resistant (R) and susceptible (S) to each pathotype were pooled and subjected to bulked segregant RNA-sequencing (BSR-Seq). The analysis of gene expression profiles identified 431, 67, and 98 differentially expressed genes (DEGs) between the R and S bulks. The variant calling method indicated a total of 12 (7 major + 5 minor) QTLs across seven chromosomes. The seven major QTLs included: BnaA5P3A.CRX1.1, BnaC1P3H.CRX1.2, and BnaC7P3A.CRX1.1 on chromosomes A05, C01, and C07, respectively; and BnaA8P3D.CRX1.1, BnaA8P3D.RCr91.2/BnaA8P3H.RCr91.2, BnaA8P3H.Crr11.3/BnaA8P3D.Crr11.3, and BnaA8P3D.qBrCR381.4 on chromosome A08. A total of 16 of the DEGs were located in the major QTL regions, 13 of which were on chromosome C07. The molecular data suggested that clubroot resistance in FGRA106 may be controlled by major and minor genes on both the A and C genomes, which are deployed in different combinations to confer resistance to the different isolates. This study provides valuable germplasm for the breeding of clubroot-resistant B. napus cultivars in Western Canada.

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

BACKGROUND: Developing and enriching genetic resources plays important role in the crop improvement. The flag leaf affects plant architecture and contributes to the grain yield of wheat (Triticum aestivum L.). The genetic improvement of flag leaf traits faces problems such as a limited genetic basis. Among the various genetic resources of wheat, Thinopyrum intermedium has been utilized as a valuable resource in genetic improvement due to its disease resistance, large spikes, large leaves, and multiple flowers. In this study, a recombinant inbred line (RIL) population was derived from common wheat Yannong15 and wheat-Th. intermedium introgression line SN304 was used to identify the quantitative trait loci (QTL) for flag leaf-related traits. RESULTS: QTL mapping was performed for flag leaf length (FLL), flag leaf width (FLW) and flag leaf area (FLA). A total of 77 QTLs were detected, and among these, 51 QTLs with positive alleles were contributed by SN304. Fourteen major QTLs for flag leaf traits were detected on chromosomes 2B, 3B, 4B, and 2D. Additionally, 28 QTLs and 8 QTLs for flag leaf-related traits were detected in low-phosphorus and drought environments, respectively. Based on major QTLs of positive alleles from SN304, we identified a pair of double-ended anchor primers mapped on chromosome 2B and amplified a specific band of Th. intermedium in SN304. Moreover, there was a major colocated QTL on chromosome 2B, called QFll/Flw/Fla-2B, which was delimited to a physical interval of approximately 2.9 Mb and contained 20 candidate genes. Through gene sequence and expression analysis, four candidate genes associated with flag leaf formation and growth in the QTL interval were identified. CONCLUSION: These results promote the fine mapping of QFll/Flw/Fla-2B, which have pleiotropic effects, and will facilitate the identification of candidate genes for flag leaf-related traits. Additionally, this work provides a theoretical basis for the application of Th. intermedium in wheat breeding.

PySmooth: a Python tool for the removal and correction of genotyping errors.

In genetic mapping studies involving many individuals, genome-wide markers such as single nucleotide polymorphisms (SNPs) can be detected using different methods. However, it comes with some errors. Some SNPs associated with diseases can be in regions encoding long noncoding RNAs (lncRNAs). Therefore, identifying the errors in genotype file and correcting them is crucial for accurate genetic mapping studies. We develop a Python tool called PySmooth, that offers an easy-to-use command line interface for the removal and correction of genotyping errors. PySmooth uses the approach of a previous tool called SMOOTH with some modifications. It inputs a genotype file, detects errors and corrects them. PySmooth provides additional features such as imputing missing data, better user-friendly usage, generates summary and visualization files, has flexible parameters, and handles more genotype codes. AVAILABILITY AND IMPLEMENTATION: PySmooth is available at https://github.com/lncRNAAddict/PySmooth .

Mapping of Candidate Genes for Nitrogen Uptake and Utilization in Japonica Rice at Seedling Stage.

Nitrogen (N) is one of the essential nutrients for the growth and development of crops. The adequate application of N not only increases the yield of crops but also improves the quality of agricultural products, but the excessive application of N can cause many adverse effects on ecology and the environment. In this study, genome-wide association analysis (GWAS) was performed under low- and high-N conditions based on 788,396 SNPs and phenotypic traits relevant to N uptake and utilization (N content and N accumulation). A total of 75 QTLs were obtained using GWAS, which contained 811 genes. Of 811 genes, 281 genes showed different haplotypes, and 40 genes had significant phenotypic differences among different haplotypes. Of these 40 genes, 5 differentially expressed genes (Os01g0159250, Os02g0618200, Os02g0618400, Os02g0630300, and Os06g0619000) were finally identified as the more valuable candidate genes based on the transcriptome data sequenced from Longjing31 (low-N-tolerant variety) and Songjing 10 (low-N-sensitive variety) under low- and high-N treatments. These new findings enrich the genetic resources for N uptake and utilization in rice, as well as lay a theoretical foundation for improving the efficiency of N uptake and utilization in rice.