A single-nucleotide polymorphism in PvPW1 encoding ß-1,3-glucanase 9 is associated with pod width in Phaseolus vulgaris L.

Pod width influences pod size, shape, yield, and consumer preference in snap beans (Phaseolus vulgaris L.). In this study, we map PvPW1, a quantitative trait locus associated with pod width in snap beans, through genotyping and phenotyping of recombinant plants. We identify Phvul.006G072800, encoding the ß-1,3-glucanase 9 protein, as the causal gene for PvPW1. The PvPW1G3555 allele is found to positively regulate pod width, as revealed by an association analysis between pod width phenotype and the PvPW1G3555C genotype across 17 bi-parental F2 populations. 97.7% of the 133 wide pod accessions carry PvPW1G3555, while 82.1% of the 78 narrow pod accessions carry PvPW1C3555, indicating strong selection pressure on PvPW1 during common bean breeding. Re-sequencing data from 59 common bean cultivars identify an 8-bp deletion in the intron linked to PvPW1C3555, leading to the development of the InDel marker of PvM436. Genotyping 317 common bean accessions with PvM436 demonstrated that accessions with PvM436247 and PvM436227 alleles have wider pods compared to those with PvM436219 allele, establishing PvM436 as a reliable marker for molecular breeding in snap beans. These findings highlight PvPW1 as a critical gene regulating pod width and underscore the utility of PvM436 in marker-assisted selection for snap bean breeding.

Fine-Mapping the Results From Genome-Wide Association Studies of Primary Biliary Cholangitis Using Susie and h2-D2.

The main goal of fine-mapping is the identification of relevant genetic variants that have a causal effect on some trait of interest, such as the presence of a disease. From a statistical point of view, fine mapping can be seen as a variable selection problem. Fine-mapping methods are often challenging to apply because of the presence of linkage disequilibrium (LD), that is, regions of the genome where the variants interrogated have high correlation. Several methods have been proposed to address this issue. Here we explore the 'Sum of Single Effects' (SuSiE) method, applied to real data (summary statistics) from a genome-wide meta-analysis of the autoimmune liver disease primary biliary cholangitis (PBC). Fine-mapping in this data set was previously performed using the FINEMAP program; we compare these previous results with those obtained from SuSiE, which provides an arguably more convenient and principled way of generating 'credible sets', that is set of predictors that are correlated with the response variable. This allows us to appropriately acknowledge the uncertainty when selecting the causal effects for the trait. We focus on the results from SuSiE-RSS, which fits the SuSiE model to summary statistics, such as z-scores, along with a correlation matrix. We also compare the SuSiE results to those obtained using a more recently developed method, h2-D2, which uses the same inputs. Overall, we find the results from SuSiE-RSS and, to a lesser extent, h2-D2, to be quite concordant with those previously obtained using FINEMAP. The resulting genes and biological pathways implicated are therefore also similar to those previously obtained, providing valuable confirmation of these previously reported results. Detailed examination of the credible sets identified suggests that, although for the majority of the loci (33 out of 56) the results from SuSiE-RSS seem most plausible, there are some loci (5 out of 56 loci) where the results from h2-D2 seem more compelling. Computer simulations suggest that, overall, SuSiE-RSS generally has slightly higher power, better precision, and better ability to identify the true number of causal variants in a region than h2-D2, although there are some scenarios where the power of h2-D2 is higher. Thus, in real data analysis, the use of complementary approaches such as both SuSiE and h2-D2 is potentially warranted.

Seed abortion caused by the combination of two duplicate genes in the progeny from the cross between Oryza sativa and Oryza meridionalis.

Seed development is an essential phenomenon for all sexual propagative plant species. The functional allele at SEED DEVELOPMENT 1 (SDV1) or SEED DEVELOPMENT 2 (SDV2) loci is essential for seed development for Oryza sativa and Oryza meridionalis. In the present study, we performed fine mapping of SDV1, narrowing down the area of interest to 333kb on chromosome 6. Haplotype analysis around the SDV1 locus of O. meridionalis accessions indicated that they shared the DNA polymorphism, suggesting that they have a common abortive allele at the SDV1 locus. Linkage analysis of the candidate SDV2 gene showed that it was located on chromosome 4. The candidate SDV2 was confirmed using a population in which both the SDV1 and SDV2 genes were segregating. The chromosomal region covering the SDV1 gene was predicted to contain 30 protein-coding genes in O. sativa. Five of these genes have conserved DNA sequences in the chromosomal region of the SDV2 gene on chromosome 4, and not on chromosome 6, of O. meridionalis. These results suggest that these five genes could be candidates for SDV1, and that their orthologous genes located on chromosome 4 of O. meridionalis could be candidates for SDV2.

Joint genotype and ancestry analysis identify novel loci associated with atopic dermatitis in African American population.

Atopic dermatitis (AD) is a chronic itchy inflammatory disease of the skin. Genetic studies have identified multiple risk factors linked to the disease; however, most of the studies have been derived from European and East Asian populations. The admixed African American (AA) genome may provide an opportunity to discovery ancestry-specific loci involved in AD susceptibility. Herein, we present joint analysis of ancestry and genotype effects followed by validation using differential gene expression analysis on AD using 726 AD-affected individuals and 999 non-AD control individuals from the AA population, genotyped using Multi-Ethnic Global Array (MEGA) followed by imputation using the Consortium on Asthma among African Ancestry Populations in the Americas (CAAPA) reference panel. The joint analysis identified two novel AD-susceptibility loci, rs2195989 in gene ANGPT1 (8q23.1) and rs62538818 in the intergenic region between genes LURAP1L and MPDZ (9p23). Admixture mapping (AM) results showed potential genomic inflation, and we implemented genomic control and identified five ancestry-of-origin loci with European ancestry effects. The multi-omics functional prioritization of variants in AM signals prioritized the loci SLAIN2, RNF39, and FOXA2. Genome-wide association study (GWAS) identified variants significantly associated with AD in the AA population, including SGK1 (rs113357522, odds ratio [OR] = 2.81), EFR3A (rs16904552, OR = 1.725), and MMP14 (rs911912, OR = 1.791). GWAS variants were common in the AA but rare in the European population, which suggests an African-ancestry-specific risk of AD. Four genes (ANGPT1, LURAP1L, EFR3A, and SGK1) were further validated using qPCR from AD and healthy skin. This study highlighted the importance of genetic studies on admixed populations, as well as local ancestry and genotype-ancestry joint effects to identify risk loci for AD.

Natural variations in the Cis-elements of GhRPRS1 contributing to petal colour diversity in cotton.

The cotton genus comprises both diploid and allotetraploid species, and the diversity in petal colour within this genus offers valuable targets for studying orthologous gene function differentiation and evolution. However, the genetic basis for this diversity in petal colour remains largely unknown. The red petal colour primarily comes from C, G, K, and D genome species, and it is likely that the common ancestor of cotton had red petals. Here, by employing a clone mapping strategy, we mapped the red petal trait to a specific region on chromosome A07 in upland cotton. Genomic comparisons and phylogenetic analyses revealed that the red petal phenotype introgressed from G. bickii. Transcriptome analysis indicated that GhRPRS1, which encodes a glutathione S-transferase, was the causative gene for the red petal colour. Knocking out GhRPRS1 resulted in white petals and the absence of red spots, while overexpression of both genotypes of GhRPRS1 led to red petals. Further analysis suggested that GhRPRS1 played a role in transporting pelargonidin-3-O-glucoside and cyanidin-3-O-glucoside. Promoter activity analysis indicated that variations in the promoter, but not in the gene body of GhRPRS1, have led to different petal colours within the genus. Our findings provide new insights into orthologous gene evolution as well as new strategies for modifying promoters in cotton breeding.

Fine mapping-based multi-omics analysis interprets the gut-lung axis function of SGLT2 inhibitors.

Background: Currently, Sodium-glucose cotransporter 2 (SGLT2) inhibitors demonstrate additional effects beyond glucose control on the gut microbiota and circulating metabolites. The gut microbiota and metabolites have been found to be useful in elucidating potential biological mechanisms of pulmonary diseases. Therefore, our study aims to investigate the effects of gut microbiota and metabolites mediating SGLT2 inhibition in 10 pulmonary diseases through Mendelian randomization (MR) research. Methods: We conducted a two-sample, two-step MR study to assess the association between SGLT2 inhibition and 10 pulmonary diseases and to investigate the mediating effects of gut microbiota and metabolite. Gene-fine mapping and annotation of mediators by FUMA and Magma analyses were performed, and causal associations of mapped genes with diseases were assessed by muti-omics MR analyses. Possible side effects of SGLT2 inhibition were assessed by PheWAS analysis. Results: SGLT2 inhibition was linked to a reduced risk of T2DM, Interstitial lung disease (ILD), Pneumoconiosis, Pulmonary tuberculosis, and Asthma(OR=0.457, 0.054, 0.002, 0.280, 0.706). The family Enterobacteriaceae and order Enterobacteriales were associated with SGLT2 inhibition and ILD(95% CI:0.079-0.138). The family Alcaligenaceae and X-12719 were linked to pneumoconiosis (95% CI: 0.042-0.120, 0.050-0.099). The genus Phascolarctobacterium was connected to pulmonary tuberculosis (95% CI: 0.236-0.703).The degree of unsaturation (Fatty Acids), ratio of docosahexaenoic acid to total fatty acids, and 4-androsten-3beta,17beta-diol disulfate 2, were associated with asthma(95% CI: 0.042-0.119, 0.039-0.101, 0.181-0.473). Furthermore, Fuma and Magma analyses identified target genes for the four diseases, and proteomic MR analysis revealed six overlapping target genes in asthma. PheWAS analysis also highlighted potential side effects of SGLT2 inhibition. Conclusions: This comprehensive study strongly supports a multi-omics association between SGLT2 inhibition and reduced risk of interstitial lung disease, tuberculosis, pneumoconiosis, and asthma. Four identified gut microbiota, four metabolites, sixteen metabolic pathways, and six target genes appear to play a potential role in this association. The results of the comprehensive phenome-wide association analysis also identified the full effect of SGLT2 inhibitors.

QTL detection for grain shape and fine mapping of two novel locus qGL4 and qGL6 in rice.

Rice grain size and grain weight, which have a great influence on rice quality and yield, are complex quantitative traits that are mediated by grain length (GL), grain width (GW), length-to-width ratio (LWR), and grain thickness (GT). In this study, the BC1F2 and BC1F2:3 populations derived from a cross between two indica rice varieties, Guangzhan 63-4S (GZ63-4S) and Dodda, were used to locate quantitative trait loci (QTL) related to grain size. A total of 30 QTL associated with GL, GW and LWR were detected, of which six QTL were scanned repeatedly in both populations. Two QTL, qGL4 and qGL6, were selected for genetic effect validation and were subsequently fine mapped to 2.359 kb and 176 kb, respectively. LOC_Os04g52240 (known as OsKS2/OsKSL2), which encoding an ent-beyerene synthase and as the only gene found in 2.359 kb interval, was proposed to be the candidate for qGL4. Moreover, the grains of qGL4 homozygous mutant plants generated by the CRISPR-Cas9 system became shorter and wider. In addition, the qGL4 allele from GZ63-4S contributes to the increase of yield per plant. Our study not only laid the foundation for further functional study of qGL4 and map-based cloning of qGL6, but also provided genetic resources for the development of high yield and good quality rice varieties. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-024-01502-8.

Characterization and fine mapping of cold-inducible parthenocarpy in cucumber (Cucumis sativus L.).

Cold stress detrimentally influences fruit development, leading to a substantial yield reduction in many fruit-bearing vegetables. Cucumber, a vegetable of subtropical origin, is especially sensitive to cold. Cold-inducible parthenocarpy (CIP) promises fruit yield under cold conditions. Previously, we identified a CIP line EC5 in cucumber, which showed strong parthenocarpy and sustained fruit growth under cold conditions (16°C day/10°C night). However, the candidate gene and genetic mechanism underlying CIP in cucumber remain unknown. In this study, both BSA-seq and conventional QTL mapping strategies were employed on F2 populations to delve into the genetic control of CIP. A single QTL, CIP5.1, was consistently mapped across two winter seasons in 2021 and 2022. Fine mapping delimited the CIP locus into a 38.3 kb region on chromosome 5, harboring 8 candidate genes. Among these candidates, CsAGL11 (CsaV3_5G040370) was identified, exhibiting multiple deletions/insertions in the promoter and 5'UTR region. The CsAGL11 gene encodes a MADS-box transcription factor protein, which is homologous to the genes previously recognized as negative regulators in ovule and fruit development of Arabidopsis and tomato. Correspondingly, cold treatment resulted in decreased expression of CsAGL11 during the early developmental stage of the fruit in EC5. A promoter activity assay confirmed promoter polymorphisms leading to weak transcriptional activation of CsAGL11 under cold conditions. This study deepens our understanding of the genetic characteristics of CIP and elucidates the potential role of the CsAGL11 gene in developing cucumber cultivars with enhanced fruiting under cold conditions.

Gene expression and splicing QTL analysis of blood cells in African American participants from the Jackson Heart Study.

Most gene expression and alternative splicing quantitative trait loci (eQTL/sQTL) studies have been biased toward European ancestry individuals. Here, we performed eQTL and sQTL analyses using TOPMed whole-genome sequencing-derived genotype data and RNA-sequencing data from stored peripheral blood mononuclear cells in 1,012 African American participants from the Jackson Heart Study (JHS). At a false discovery rate of 5%, we identified 17,630 unique eQTL credible sets covering 16,538 unique genes; and 24,525 unique sQTL credible sets covering 9,605 unique genes, with lead QTL at P < 5e-8. About 24% of independent eQTLs and independent sQTLs with a minor allele frequency > 1% in JHS were rare (minor allele frequency < 0.1%), and therefore unlikely to be detected, in European ancestry individuals. Finally, we created an open database, which is freely available online, allowing fast query and bulk download of our QTL results.

Splicing-specific transcriptome-wide association uncovers genetic mechanisms for schizophrenia.

Recent studies have highlighted the essential role of RNA splicing, a key mechanism of alternative RNA processing, in establishing connections between genetic variations and disease. Genetic loci influencing RNA splicing variations show considerable influence on complex traits, possibly surpassing those affecting total gene expression. Dysregulated RNA splicing has emerged as a major potential contributor to neurological and psychiatric disorders, likely due to the exceptionally high prevalence of alternatively spliced genes in the human brain. Nevertheless, establishing direct associations between genetically altered splicing and complex traits has remained an enduring challenge. We introduce Spliced-Transcriptome-Wide Associations (SpliTWAS) to integrate alternative splicing information with genome-wide association studies to pinpoint genes linked to traits through exon splicing events. We applied SpliTWAS to two schizophrenia (SCZ) RNA-sequencing datasets, BrainGVEX and CommonMind, revealing 137 and 88 trait-associated exons (in 84 and 67 genes), respectively. Enriched biological functions in the associated gene sets converged on neuronal function and development, immune cell activation, and cellular transport, which are highly relevant to SCZ. SpliTWAS variants impacted RNA-binding protein binding sites, revealing potential disruption of RNA-protein interactions affecting splicing. We extended the probabilistic fine-mapping method FOCUS to the exon level, identifying 36 genes and 48 exons as putatively causal for SCZ. We highlight VPS45 and APOPT1, where splicing of specific exons was associated with disease risk, eluding detection by conventional gene expression analysis. Collectively, this study supports the substantial role of alternative splicing in shaping the genetic basis of SCZ, providing a valuable approach for future investigations in this area.

Identification and candidate analysis of a new brown planthopper resistance locus in an Indian landrace of rice, paedai kalibungga.

The brown planthopper (Nilaparvata lugens Stål, BPH) is the most destructive pest of rice (Oryza sativa L.). Utilizing resistant rice cultivars that harbor resistance gene/s is an effective strategy for integrated pest management. Due to the co-evolution of BPH and rice, a single resistance gene may fail because of changes in the virulent BPH population. Thus, it is urgent to explore and map novel BPH resistance genes in rice germplasm. Previously, an indica landrace from India, Paedai kalibungga (PK), demonstrated high resistance to BPH in both in Wuhan and Fuzhou, China. To map BPH resistance genes from PK, a BC1F2:3 population derived from crosses of PK and a susceptible parent, Zhenshan 97 (ZS97), was developed and evaluated for BPH resistance. A novel BPH resistance locus, BPH39, was mapped on the short arm of rice chromosome 6 using next-generation sequencing-based bulked segregant analysis (BSA-seq). BPH39 was validated using flanking markers within the locus. Furthermore, near-isogenic lines carrying BPH39 (NIL-BPH39) were developed in the ZS97 background. NIL-BPH39 exhibited the physiological mechanisms of antibiosis and preference toward BPH. BPH39 was finally delimited to an interval of 84 Kb ranging from 1.07 to 1.15 Mb. Six candidate genes were identified in this region. Two of them (LOC_Os06g02930 and LOC_Os06g03030) encode proteins with a similar short consensus repeat (SCR) domain, which displayed many variations leading to amino acid substitutions and showed higher expression levels in NIL-BPH39. Thus, these two genes are considered reliable candidate genes for BPH39. Additionally, transcriptome sequencing, DEGs analysis, and gene RT-qPCR verification preliminary revealed that BPH39 may be involved in the jasmonic acid (JA) signaling pathway, thus mediating the molecular mechanism of BPH resistance. This work will facilitate map-based cloning and marker-assisted selection for the locus in breeding programs targeting BPH resistance. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-024-01485-6.

Fine mapping of QYrsv.swust-1BL for resistance to stripe rust in durum wheat Svevo.

Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is a serious disease that affects wheat worldwide. There is a great need to develop cultivars with combinations of all-stage resistance (ASR) and adult-plant resistance (APR) genes for sustainable control of the disease. QYrsv.swust-1BL in the Italian durum wheat (Triticum turgidum ssp. durum) cultivar Svevo is effective against Pst races in China and Israel, and the gene has been previously mapped to the long arm of chromosome 1B. The gene is flanked by SNP (single nucleotide polymorphism) markers IWB5732 and IWB4839 (0.75 cM). In the present study, we used high-density 660K SNP array genotyping and the phenotypes of 137 recombinant inbred lines (RILs) to fine map the QYrsv.swust-1BL locus within a 1.066 Mb region in durum wheat Svevo (RefSeq Rel. 1.0) on chromosome arm 1BL. The identified 1.066 Mb region overlaps with a previously described map of Yr29/QYr.ucw-1BL, a stripe rust APR gene. Twenty-five candidate genes for QYrsv.swut-1BL were identified through comparing polymorphic genes within the 1.066 Mb region in the resistant cultivar. SNP markers were selected and converted to Kompetitive allele-specific polymerase chain reaction (KASP) markers. Five KASP markers based on SNP were validated in a F2 and F2:3 breeding population, providing further compelling evidence for the significant effects of QYrsv.swut-1BL. These markers should be useful in marker-assisted selection for incorporating Yr29/QYrsv.swust-1BL into new durum and common wheat cultivars for resistance to stripe rust.

Genetic Analysis and Fine Mapping of QTL for the Erect Leaf in Mutant mths29 Induced through Fast Neutron in Wheat.

The erect leaf plays a crucial role in determining plant architecture, with its growth and development regulated by genetic factors. However, there has been a lack of comprehensive studies on the regulatory mechanisms governing wheat lamina joint development, thus failing to meet current breeding demands. In this study, a wheat erect leaf mutant, mths29, induced via fast neutron mutagenesis, was utilized for QTL fine mapping and investigation of lamina joint development. Genetic analysis of segregating populations derived from mths29 and Jimai22 revealed that the erect leaf trait was controlled by a dominant single gene. Using BSR sequencing and map-based cloning techniques, the QTL responsible for the erect leaf trait was mapped to a 1.03 Mb physical region on chromosome 5A. Transcriptome analysis highlighted differential expression of genes associated with cell division and proliferation, as well as several crucial transcription factors and kinases implicated in lamina joint development, particularly in the boundary cells of the preligule zone in mths29. These findings establish a solid foundation for understanding lamina joint development and hold promise for potential improvements in wheat plant architecture.

Deep Learning-Based HLA Allele Imputation Applicable to GWAS.

Human leukocyte antigen (HLA) imputation is an essential step following genome-wide association study, particularly when putative associations in HLA genes are identified, to fully understand the genetic basis of human traits. Different HLA imputation methods have been developed, each with its own advantages, and recent methods have been improved in terms of imputation accuracy and computational costs. Here, I describe Deep*HLA, a recently published method that employs deep learning algorithms to accurately impute HLA alleles from regional single nucleotide variants. Deep*HLA was trained and benchmarked on two reference panels of different ancestries. Deep*HLA achieved high imputation accuracy with relatively mild reduced imputation accuracy for rare alleles. I provide a detailed protocol for running Deep*HLA, including instructions for data preprocessing, model training, and imputation. Deep*HLA is implemented in Python 3 and is freely available.

Fine mapping and candidate gene analysis of CRA8.1.6, which confers clubroot resistance in turnip (Brassica rapa ssp. rapa).

Clubroot disease poses a significant threat to Brassica crops, necessitating ongoing updates on resistance gene sources. In F2 segregants of the clubroot-resistant inbred line BrT18-6-4-3 and susceptible DH line Y510, the genetic analysis identified a single dominant gene responsible for clubroot resistance. Through bulk segregant sequencing analysis and kompetitive allele-specific polymerase chain reaction assays, CRA8.1.6 was mapped within 110 kb (12,255-12,365 Mb) between markers L-CR11 and L-CR12 on chromosome A08. We identified B raA08g015220.3.5C as the candidate gene of CRA8.1.6. Upon comparison with the sequence of disease-resistant material BrT18-6-4-3, we found 249 single-nucleotide polymorphisms, seven insertions, six deletions, and a long terminal repeat (LTR) retrotransposon (5,310 bp) at 909 bp of the first intron. However, the LTR retrotransposon was absent in the coding sequence of the susceptible DH line Y510. Given the presence of a non-functional LTR insertion in other materials, it showed that the LTR insertion might not be associated with susceptibility. Sequence alignment analysis revealed that the fourth exon of the susceptible line harbored two deletions and an insertion, resulting in a frameshift mutation at 8,551 bp, leading to translation termination at the leucine-rich repeat domain's C-terminal in susceptible material. Sequence alignment of the CDS revealed a 99.4% similarity to Crr1a, which indicate that CRA8.1.6 is likely an allele of the Crr1a gene. Two functional markers, CRA08-InDel and CRA08-KASP1, have been developed for marker-assisted selection in CR turnip cultivars. Our findings could facilitate the development of clubroot-resistance turnip cultivars through marker-assisted selection.

Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions.

To identify credible causal risk variants (CCVs) associated with different histotypes of epithelial ovarian cancer (EOC), we performed genome-wide association analysis for 470,825 genotyped and 10,163,797 imputed SNPs in 25,981 EOC cases and 105,724 controls of European origin. We identified five histotype-specific EOC risk regions (p value <5 × 10-8) and confirmed previously reported associations for 27 risk regions. Conditional analyses identified an additional 11 signals independent of the primary signal at six risk regions (p value <10-5). Fine mapping identified 4,008 CCVs in these regions, of which 1,452 CCVs were located in ovarian cancer-related chromatin marks with significant enrichment in active enhancers, active promoters, and active regions for CCVs from each EOC histotype. Transcriptome-wide association and colocalization analyses across histotypes using tissue-specific and cross-tissue datasets identified 86 candidate susceptibility genes in known EOC risk regions and 32 genes in 23 additional genomic regions that may represent novel EOC risk loci (false discovery rate <0.05). Finally, by integrating genome-wide HiChIP interactome analysis with transcriptome-wide association study (TWAS), variant effect predictor, transcription factor ChIP-seq, and motifbreakR data, we identified candidate gene-CCV interactions at each locus. This included risk loci where TWAS identified one or more candidate susceptibility genes (e.g., HOXD-AS2, HOXD8, and HOXD3 at 2q31) and other loci where no candidate gene was identified (e.g., MYC and PVT1 at 8q24) by TWAS. In summary, this study describes a functional framework and provides a greater understanding of the biological significance of risk alleles and candidate gene targets at EOC susceptibility loci identified by a genome-wide association study.

R2R3-MYB transcription factor CsMYB60 controls mature fruit skin color by regulating flavonoid accumulation in cucumber.

Skin color is an important trait that determines the cosmetic appearance and quality of fruits. In cucumber, the skin color ranges from white to brown in mature fruits. However, the genetic basis for this important trait remains unclear. We conducted a genome-wide association study of natural cucumber populations, along with map-based cloning techniques, on an F2 population resulting from a cross between Pepino (with yellow-brown fruit skin) and Zaoer-N (with creamy fruit skin). We identified CsMYB60 as a candidate gene responsible for skin coloration in mature cucumber fruits. In cucumber accessions with white to pale yellow skin color, a premature stop mutation (C to T) was found in the second exon region of CsMYB60, whereas light yellow cucumber accessions exhibited splicing premature termination caused by an intronic mutator-like element insertion in CsMYB60. Transgenic CsMYB60c cucumber plants displayed a yellow-brown skin color by promoting accumulation of flavonoids, especially hyperoside, a yellow-colored flavonol. CsMYB60c encodes a nuclear protein that primarily acts as a transcriptional activator through its C-terminal activation motif. RNA sequencing and DNA affinity purification sequencing assays revealed that CsMYB60c promotes skin coloration by directly binding to the YYTACCTAMYT motif in the promoter regions of flavonoid biosynthetic genes, including CsF3'H, which encodes flavonoid 3'-hydroxylase. The findings of our study not only offer insight into the function of CsMYB60 as dominantly controlling fruit coloration, but also highlight that intronic DNA mutations can have a similar phenotypic impact as exonic mutations, which may be valuable in future cucumber breeding programs.

Identification and fine mapping of Brmmd1 gene controlling recessive genic male sterility in Brassica rapa L.

Recessive genic male sterility (RGMS) provides an effective approach for the commercial exploitation of heterosis, especially in Brassica crops. Although some artificial RGMS mutants have been reported in B. rapa, no causal genes derived from these natural mutants have been identified so far. In this study, a spontaneous RGMS mutant Bcajh97-01A derived from the 'Aijiaohuang' line traced back to the 1980 s was identified. Genetic analysis revealed that the RGMS trait was controlled by a single locus in the Bcajh97-01A/B system. Bulk segregant analysis (BSA) in combination with linkage analysis was employed to delimit the causal gene to an approximate 129 kb interval on chromosome A02. The integrated information of transcriptional levels and the predicted genes in the target region indicated that the Brmmd1 (BraA02g017420) encoding a PHD-containing nuclear protein was the most likely candidate gene. A 374 bp miniature inverted-repeat transposable element (MITE) was inserted into the first exon to prematurely stop the Brmmd1 gene translation, thus blocking the normal expression of this gene at the tetrad stage in the Bcajh97-01A. Additionally, a co-segregating structure variation (SV) marker was developed to rapidly screen the RGMS progenies from Bcajh97-01A/B system. Our findings reveal that BraA02g017420 is the causal gene responsible for the RGMS trait. This study lays a foundation for marker-assisted selection and further molecular mechanism exploration of pollen development in B. rapa.

Decoding polygenic diseases: advances in noncoding variant prioritization and validation.

Genome-wide association studies (GWASs) provide a key foundation for elucidating the genetic underpinnings of common polygenic diseases. However, these studies have limitations in their ability to assign causality to particular genetic variants, especially those residing in the noncoding genome. Over the past decade, technological and methodological advances in both analytical and empirical prioritization of noncoding variants have enabled the identification of causative variants by leveraging orthogonal functional evidence at increasing scale. In this review, we present an overview of these approaches and describe how this workflow provides the groundwork necessary to move beyond associations toward genetically informed studies on the molecular and cellular mechanisms of polygenic disease.

Hierarchical joint analysis of marginal summary statistics-Part I: Multipopulation fine mapping and credible set construction.

Recent advancement in genome-wide association studies (GWAS) comes from not only increasingly larger sample sizes but also the shift in focus towards underrepresented populations. Multipopulation GWAS increase power to detect novel risk variants and improve fine-mapping resolution by leveraging evidence and differences in linkage disequilibrium (LD) from diverse populations. Here, we expand upon our previous approach for single-population fine-mapping through Joint Analysis of Marginal SNP Effects (JAM) to a multipopulation analysis (mJAM). Under the assumption that true causal variants are common across studies, we implement a hierarchical model framework that conditions on multiple SNPs while explicitly incorporating the different LD structures across populations. The mJAM framework can be used to first select index variants using the mJAM likelihood with different feature selection approaches. In addition, we present a novel approach leveraging the ideas of mediation to construct credible sets for these index variants. Construction of such credible sets can be performed given any existing index variants. We illustrate the implementation of the mJAM likelihood through two implementations: mJAM-SuSiE (a Bayesian approach) and mJAM-Forward selection. Through simulation studies based on realistic effect sizes and levels of LD, we demonstrated that mJAM performs well for constructing concise credible sets that include the underlying causal variants. In real data examples taken from the most recent multipopulation prostate cancer GWAS, we showed several practical advantages of mJAM over other existing multipopulation methods.