Genotype selection identified elite lines through quantitative trait loci mapping of agronomically important traits in wheat.

Wheat is one of the most important staple foods in the world. Genetic characterization of wheat agronomically important traits is crucial for yield improvement through molecular breeding. In this study, a recombinant inbred line (RIL) population was developed by crossing a local adapted high yield variety Jimai 22 (JM22) with an external variety Cunmai no.1 (CM1). A high-density genetic map containing 7,359 single nucleotide polymorphism (SNP) markers was constructed. Quantitative trait loci (QTL) mapping identified 61 QTL for eight yield-related traits under six environments (years). Among them, 17 QTL affecting spike number per plant, grain number per spike and thousand grain weight showed high predictability for theoretical yield per plant (TYP), of which, 12 QTL alleles positively contributed to TYP. Nine promising candidate genes for seven of the 12 QTL were identified including three known wheat genes and six rice orthologs. Four elite lines with TYP increased by 5.6%-15.2% were identified through genotype selection which carried 7-9 favorable alleles from JM22 and 2-3 favorable alleles from CM1 of the 12 QTL. Moreover, the linked SNPs of the 12 QTL were converted to high-throughput kompetitive allele-specific PCR (KASP) markers and validated in the population. The mapped QTL, identified promising candidate genes, developed elite lines and KASP markers are highly valuable in future genotype selection to improve wheat yield. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-024-01496-3.

Mapping of Aegilops speltoides derived leaf rust and stripe rust resistance genes using 35K SNP array.

Wheat is an essential food commodity cultivated throughout the world. However, this crop faces continuous threats from fungal pathogens, leaf rust (LR) and stripe rust (YR). To continue feeding the growing population, these major destructors of wheat must be effectively countered by enhancing the genetic diversity of cultivated germplasm. In this study, an introgression line with hexaploid background (ILsp3603) carrying resistance against Pt pathotypes 77-5 (121R63-1), 77-9 (121R60-1) and Pst pathotypes 46S119 (46E159), 110S119 (110E159), 238S119 (238E159) was developed from donor wheat wild progenitor, Aegilops speltoides acc pau 3603. To understand the genetic basis of resistance and map these genes (named Lrsp3603 and Yrsp3603), inheritance studies were carried out in F6 and F7 mapping population, developed by crossing ILsp3603 with LR and YR susceptible cultivar WL711, which revealed a monogenic (single gene) inheritance pattern for each of these traits. Bulk segregant analysis combined with 35 K Axiom SNP array genotyping mapped both genes as separate entities on the short arm of chromosome 6B. A genetic linkage map, comprising five markers, 1 SNP, 1 PLUG and three gene based SSRs, covered a genetic distance of 12.65 cM. Lrsp3603 was flanked by markers Tag-SSR14 (located proximally at 2.42 cM) and SNP AX-94542331 (at 3.28 cM) while Yrsp3603 was mapped at one end closest to AX-94542331 at 6.62 cM distance. Functional annotation of Lrsp3603 target region (∼ 1 Mbp) revealed 10 gene IDs associated with disease resistance mechanisms including three encoding typical R gene domains.

Construction of a high-density genetic map and QTL localization of body weight and wool production related traits in Alpine Merino sheep based on WGR.

BACKGROUND: The Alpine Merino is a new breed of fine-wool sheep adapted to the cold and arid climate of the plateau in the world. It has been popularized in Northwest China due to its superior adaptability as well as excellent production performance. Those traits related to body weight, wool yield, and wool fiber characteristics, which are economically essential traits in Alpine Merino sheep, are controlled by QTL (Quantitative Trait Loci). Therefore, the identification of QTL and genetic markers for these key economic traits is a critical step in establishing a MAS (Marker-Assisted Selection) breeding program. RESULTS: In this study, we constructed the high-density genetic linkage map of Alpine Merino sheep by sequencing 110 F1 generation individuals using WGR (Whole Genome Resequencing) technology. 14,942 SNPs (Single Nucleotide Polymorphism) were identified and genotyped. The map spanned 2,697.86 cM, with an average genetic marker interval of 1.44 cM. A total of 1,871 high-quality SNP markers were distributed across 27 linkage groups, with an average of 69 markers per LG (Linkage Group). Among them, the smallest genetic distance is 19.62 cM for LG2, while the largest is 237.19 cM for LG19. The average genetic distance between markers in LGs ranged from 0.24 cM (LG2) to 3.57 cM (LG17). The marker density in the LGs ranged from LG14 (39 markers) to LG1 (150 markers). CONCLUSIONS: The first genetic map of Alpine Merino sheep we constructed included 14,942 SNPs, while 46 QTLs associated with body weight, wool yield and wool fiber traits were identified, laying the foundation for genetic studies and molecular marker-assisted breeding. Notably, there were QTL intervals for overlapping traits on LG4 and LG8, providing potential opportunities for multi-trait co-breeding and further theoretical support for selection and breeding of ultra-fine and meaty Alpine Merino sheep.

Combining association with linkage mapping to dissect the phenolamides metabolism of the maize kernel.

Phenolamides are important secondary metabolites in plant species. They play important roles in plant defense responses against pathogens and insect herbivores, protection against UV irradiation and floral induction and development. However, the accumulation and variation in phenolamides content in diverse maize lines and the genes responsible for their biosynthesis remain largely unknown. Here, we combined genetic mapping, protein regulatory network and bioinformatics analysis to further enhance the understanding of maize phenolamides biosynthesis. Sixteen phenolamides were identified in multiple populations, and they were all significantly correlated with one or several of 19 phenotypic traits. By linkage mapping, 58, 58, 39 and 67 QTLs, with an average of 3.9, 3.6, 3.6 and 4.2 QTLs for each trait were mapped in BBE1, BBE2, ZYE1 and ZYE2, explaining 9.47%, 10.78%, 9.51% and 11.40% phenotypic variation for each QTL on average, respectively. By GWAS, 39 and 36 significant loci were detected in two different environments, 3.3 and 2.8 loci for each trait, explaining 10.00% and 9.97% phenotypic variation for each locus on average, respectively. Totally, 58 unique candidate genes were identified, 31% of them encoding enzymes involved in amine and derivative metabolic processes. Gene Ontology term analysis of the 358 protein-protein interrelated genes revealed significant enrichment in terms relating to cellular nitrogen metabolism, amine metabolism. GRMZM2G066142, GRMZM2G066049, GRMZM2G165390 and GRMZM2G159587 were further validated involvement in phenolamides biosynthesis. Our results provide insights into the genetic basis of phenolamides biosynthesis in maize kernels, understanding phenolamides biosynthesis and its nutritional content and ability to withstand biotic and abiotic stress.

Linkage Mapping and Genome-Wide Association Study Identified Two Peanut Late Leaf Spot Resistance Loci, PLLSR-1 and PLLSR-2, Using Nested Association Mapping.

Identification of candidate genes and molecular markers for late leaf spot (LLS) disease resistance in peanut (Arachis hypogaea) has been a focus of molecular breeding for the U.S. industry-funded peanut genome project. Efforts have been hindered by limited mapping resolution due to low levels of genetic recombination and marker density available in traditional biparental mapping populations. To address this, a multi-parental nested association mapping population has been genotyped with the peanut 58K single-nucleotide polymorphism (SNP) array and phenotyped for LLS severity in the field for 3 years. Joint linkage-based quantitative trait locus (QTL) mapping identified nine QTLs for LLS resistance with significant phenotypic variance explained up to 47.7%. A genome-wide association study identified 13 SNPs consistently associated with LLS resistance. Two genomic regions harboring the consistent QTLs and SNPs were identified from 1,336 to 1,520 kb (184 kb) on chromosome B02 and from 1,026.9 to 1,793.2 kb (767 kb) on chromosome B03, designated as peanut LLS resistance loci, PLLSR-1 and PLLSR-2, respectively. PLLSR-1 contains 10 nucleotide-binding site leucine-rich repeat disease resistance genes. A nucleotide-binding site leucine-rich repeat disease resistance gene, Arahy.VKVT6A, was also identified on homoeologous chromosome A02. PLLSR-2 contains five significant SNPs associated with five different genes encoding callose synthase, pollen defective in guidance protein, pentatricopeptide repeat, acyl-activating enzyme, and C2 GRAM domains-containing protein. This study highlights the power of multi-parent populations such as nested association mapping for genetic mapping and marker-trait association studies in peanuts. Validation of these two LLS resistance loci will be needed for marker-assisted breeding.

Joint-GWAS, Linkage Mapping, and Transcriptome Analysis to Reveal the Genetic Basis of Plant Architecture-Related Traits in Maize.

Plant architecture is one of the key factors affecting maize yield formation and can be divided into secondary traits, such as plant height (PH), ear height (EH), and leaf number (LN). It is a viable approach for exploiting genetic resources to improve plant density. In this study, one natural panel of 226 inbred lines and 150 family lines derived from the offspring of T32 crossed with Qi319 were genotyped by using the MaizeSNP50 chip and the genotyping by sequence (GBS) method and phenotyped under three different environments. Based on the results, a genome-wide association study (GWAS) and linkage mapping were analyzed by using the MLM and ICIM models, respectively. The results showed that 120 QTNs (quantitative trait nucleotides) and 32 QTL (quantitative trait loci) related to plant architecture were identified, including four QTL and 40 QTNs of PH, eight QTL and 41 QTNs of EH, and 20 QTL and 39 QTNs of LN. One dominant QTL, qLN7-2, was identified in the Zhangye environment. Six QTNs were commonly identified to be related to PH, EH, and LN in different environments. The candidate gene analysis revealed that Zm00001d021574 was involved in regulating plant architecture traits through the autophagy pathway, and Zm00001d044730 was predicted to interact with the male sterility-related gene ms26. These results provide abundant genetic resources for improving maize plant architecture traits by using approaches to biological breeding.

Construction of Genetic Map and QTL Mapping for Seed Size and Quality Traits in Soybean (Glycine max L.).

Soybean (Glycine max L.) is the main source of vegetable protein and edible oil for humans, with an average content of about 40% crude protein and 20% crude fat. Soybean yield and quality traits are mostly quantitative traits controlled by multiple genes. The quantitative trait loci (QTL) mapping for yield and quality traits, as well as for the identification of mining-related candidate genes, is of great significance for the molecular breeding and understanding the genetic mechanism. In this study, 186 individual plants of the F2 generation derived from crosses between Changjiangchun 2 and Yushuxian 2 were selected as the mapping population to construct a molecular genetic linkage map. A genetic map containing 445 SSR markers with an average distance of 5.3 cM and a total length of 2375.6 cM was obtained. Based on constructed genetic map, 11 traits including hundred-seed weight (HSW), seed length (SL), seed width (SW), seed length-to-width ratio (SLW), oil content (OIL), protein content (PRO), oleic acid (OA), linoleic acid (LA), linolenic acid (LNA), palmitic acid (PA), stearic acid (SA) of yield and quality were detected by the multiple- d size traits and 113 QTLs related to quality were detected by the multiple QTL model (MQM) mapping method across generations F2, F2:3, F2:4, and F2:5. A total of 71 QTLs related to seed size traits and 113 QTLs related to quality traits were obtained in four generations. With those QTLs, 19 clusters for seed size traits and 20 QTL clusters for quality traits were summarized. Two promising clusters, one related to seed size traits and the other to quality traits, have been identified. The cluster associated with seed size traits spans from position 27876712 to 29009783 on Chromosome 16, while the cluster linked to quality traits spans from position 12575403 to 13875138 on Chromosome 6. Within these intervals, a reference genome of William82 was used for gene searching. A total of 36 candidate genes that may be involved in the regulation of soybean seed size and quality were screened by gene functional annotation and GO enrichment analysis. The results will lay the theoretical and technical foundation for molecularly assisted breeding in soybean.

Molecular Mapping of Putative Genomic Regions Controlling Fruit and Seed Morphology of Watermelon.

The genetic regulatory basis of qualitative and quantitative phenotypes of watermelon is being investigated in different types of molecular and genetic breeding studies around the world. In this study, biparental F2 mapping populations were developed over two experimental years, and the collected datasets of fruit and seed traits exhibited highly significant correlations. Whole-genome resequencing of comparative parental lines was performed and detected single nucleotide polymorphism (SNP) loci were converted into cleaved amplified polymorphic sequence (CAPS) markers. The screened polymorphic markers were genotyped in segregating populations and two genetic linkage maps were constructed, which covered a total of 2834.28 and 2721.45 centimorgan (cM) genetic lengths, respectively. A total of 22 quantitative trait loci (QTLs) for seven phenotypic traits were mapped; among them, five stable and major-effect QTLs (PC-8-1, SL-9-1, SWi-9-1, SSi-9-1, and SW-6-1) and four minor-effect QTLs (PC-2-1 and PC-2-2; PT-2-1 and PT-2-2; SL-6-1 and SSi-6-2; and SWi-6-1 and SWi-6-2) were observed with 3.77-38.98% PVE. The adjacent QTL markers showed a good fit marker-trait association, and a significant allele-specific contribution was also noticed for genetic inheritance of traits. Further, a total of four candidate genes (Cla97C09G179150, Cla97C09G179350, Cla97C09G180040, and Cla97C09G180100) were spotted in the stable colocalized QTLs of seed size linked traits (SL-9-1 and SWi-9-1) that showed non-synonymous type mutations. The gene expression trends indicated that the seed morphology had been formed in the early developmental stage and showed the genetic regulation of seed shape formation. Hence, we think that our identified QTLs and genes would provide powerful genetic insights for marker-assisted breeding aimed at improving the quality traits of watermelon.

Colour polymorphism associated with a gene duplication in male wood tiger moths.

Colour is often used as an aposematic warning signal, with predator learning expected to lead to a single colour pattern within a population. However, there are many puzzling cases where aposematic signals are also polymorphic. The wood tiger moth, Arctia plantaginis, displays bright hindwing colours associated with unpalatability, and males have discrete colour morphs which vary in frequency between localities. In Finland, both white and yellow morphs can be found, and these colour morphs also differ in behavioural and life-history traits. Here, we show that male colour is linked to an extra copy of a yellow family gene that is only present in the white morphs. This white-specific duplication, which we name valkea, is highly upregulated during wing development. CRISPR targeting valkea resulted in editing of both valkea and its paralog, yellow-e, and led to the production of yellow wings. We also characterise the pigments responsible for yellow, white, and black colouration, showing that yellow is partly produced by pheomelanins, while black is dopamine-derived eumelanin. Our results add to a growing number of studies on the genetic architecture of complex and seemingly paradoxical polymorphisms, and the role of gene duplications and structural variation in adaptive evolution.

Construction of a genetic map and QTL mapping of seed size traits in soybean.

Soybean seed size and seed shape traits are closely related to plant yield and appearance quality. In this study, 186 individual plants of the F2 generation derived from crosses between Changjiang Chun 2 and JiYu 166 were selected as the mapping population to construct a molecular genetic linkage map, and the phenotypic data of hundred-grain weight, seed length, seed width, and seed length-to-width ratio of soybean under three generations of F2 single plants and F2:3 and F2:4 lines were combined to detect the QTL (quantitative trait loci) for the corresponding traits by ICIM mapping. A soybean genetic map containing 455 markers with an average distance of 6.15 cM and a total length of 2799.2 cM was obtained. Forty-nine QTLs related to the hundred-grain weight, seed length, seed width, and seed length-to-width ratio of soybean were obtained under three environmental conditions. A total of 10 QTLs were detected in more than two environments with a phenotypic variation of over 10%. Twelve QTL clusters were identified on chromosomes 1, 2, 5, 6, 8, 13, 18, and 19, with the majority of the overlapping intervals for hundred-grain weight and seed width. These results will lay the theoretical and technical foundation for molecularly assisted breeding in soybean seed weight and seed shape. Eighteen candidate genes that may be involved in the regulation of soybean seed size were screened by gene functional annotation and GO enrichment analysis.

Dicarboxylic Amino Acid Permease 7219 Regulates Fruiting Body Type of Auricularia heimuer.

Auricularia heimuer is a widely cultivated jelly mushroom. The fruiting bodies are categorized into cluster and chrysanthemum types. With changing consumer demands and the need to reduce bio-waste, the demand for clustered fruiting bodies is increasing. Therefore, gene mining for fruiting body types is a matter of urgency. We determined that the A. heimuer locus for fruiting body type was located at one end of the genetic linkage map. The locus was localized between the markers D23860 and D389 by increasing the density of the genetic linkage map. BlastN alignment showed that the marker SCL-18 was also located between D23860 and D389, and a total of 25 coding genes were annotated within this interval. Through parental transcriptome analysis and qRT-PCR verification, the locus g7219 was identified as the gene controlling the fruiting body type. A single-nucleotide substitution in the TATA box of g7219 was detected between the parents. By PCR amplification of the promoter region of g7219, the TATA-box sequences of the cluster- and chrysanthemum-type strains were found to be CATAAAA and TATAAAA, respectively. This study provides a foundation for the breeding of fruiting body types and strain improvement of A. heimuer.

Linked candidate genes of different functions for white mold resistance in common bean (Phaseolus vulgaris L) are identified by multiple QTL mapping approaches.

White mold (WM) is a major disease in common bean (Phaseolus vulgaris L.), and its complex quantitative genetic control limits the development of WM resistant cultivars. WM2.2, one of the nine meta-QTL with a major effect on WM tolerance, explains up to 35% of the phenotypic variation and was previously mapped to a large genomic interval on Pv02. Our objective was to narrow the interval of this QTL using combined approach of classic QTL mapping and QTL-based bulk segregant analysis (BSA), and confirming those results with Khufu de novo QTL-seq. The phenotypic and genotypic data from two RIL populations, 'Raven'/I9365-31 (R31) and 'AN-37'/PS02-029C-20 (Z0726-9), were used to select resistant and susceptible lines to generate subpopulations for bulk DNA sequencing. The QTL physical interval was determined by considering overlapping interval of the identified QTL or peak region in both populations by three independent QTL mapping analyses. Our findings revealed that meta-QTL WM2.2 consists of three regions, WM2.2a (4.27-5.76 Mb; euchromatic), WM 2.2b (12.19 to 17.61 Mb; heterochromatic), and WM2.2c (23.01-25.74 Mb; heterochromatic) found in both populations. Gene models encoding for gibberellin 2-oxidase 8, pentatricopeptide repeat, and heat-shock proteins are the likely candidate genes associated with WM2.2a resistance. A TIR-NBS-LRR class of disease resistance protein (Phvul.002G09200) and LRR domain containing family proteins are potential candidate genes associated with WM2.2b resistance. Nine gene models encoding disease resistance protein [pathogenesis-related thaumatin superfamily protein and disease resistance-responsive (dirigent-like protein) family protein etc] found within the WM2.2c QTL interval are putative candidate genes. WM2.2a region is most likely associated with avoidance mechanisms while WM2.2b and WM2.2c regions trigger physiological resistance based on putative candidate genes.

Mapping QTL conferring flag leaf senescence in durum wheat cultivars.

Flag leaf senescence is a critical factor affecting the yield and quality of wheat. The aim of this study was to identify QTLs associated with flag leaf senescence in an F10 recombinant inbred line population derived from durum wheats UC1113 and Kofa. Bulked segregant analysis using the wheat 660K SNP array identified 3225 SNPs between extreme-phenotype bulks, and the differential SNPs were mainly clustered on chromosomes 1A, 1B, 3B, 5A, 5B, and 7A. BSR-Seq indicated that the significant SNPs were mainly located in two intervals of 354.0-389.0 Mb and 8.0-15.0 Mb on 1B and 3B, respectively. Based on the distribution of significant SNPs on chromosomes 1B and 3B, a total of 109 insertion/deletion (InDel) markers were developed, and 8 of them were finally used to map QTL in UC1113/Kofa population for flag leaf senescence. Inclusive composite interval mapping identified two major QTL in marker intervals Mar2005-Mar2116 and Mar207-Mar289, explaining 14.2-15.4% and 31.4-68.6% of the phenotypic variances across environments, respectively. Using BSR-Seq, gene expression and sequence analysis, the TraesCS1B02G211600 and TraesCS3B02G023000 were identified as candidate senescence-associated genes. This study has potential to be used in cloning key genes for flag leaf senescence and provides available molecular markers for genotyping and marker-assisted selection breeding. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01410-3.

Identification of Genetic Loci for Rice Seedling Mesocotyl Elongation in Both Natural and Artificial Segregating Populations.

Mesocotyl elongation of rice seedlings is a key trait for deep sowing tolerance and well seedling establishment in dry direct sowing rice (DDSR) production. Subsets of the Rice Diversity Panel 1 (RDP1, 294 accessions) and Hanyou 73 (HY73) recombinant inbred line (RIL) population (312 lines) were screened for mesocotyl length (ML) via dark germination. Six RDP1 accessions (Phudugey, Kasalath, CA902B21, Surjamkuhi, Djimoron, and Goria) had an ML longer than 10 cm, with the other 19 accessions being over 4 cm. A GWAS in RDP1 detected 118 associated SNPs on all 12 chromosomes using a threshold of FDR-adjusted p < 0.05, including 11 SNPs on chromosomes 1, 4, 5, 7, 10, and 12 declared by -log10(P) > 5.868 as the Bonferroni-corrected threshold. Using phenotypic data of three successive trials and a high-density bin map from resequencing genotypic data, four to six QTLs were detected on chromosomes 1, 2, 5, 6, and 10, including three loci repeatedly mapped for ML from two or three replicated trials. Candidate genes were predicted from the chromosomal regions covered by the associated LD blocks and the confidence intervals (CIs) of QTLs and partially validated by the dynamic RNA-seq data in the mesocotyl along different periods of light exposure. Potential strategies of donor parent selection for seedling establishment in DDSR breeding were discussed.

Linkage and association mapping of ovule number per ovary (ON) in oilseed rape (Brassica napus L.).

Ovule number (ON) produced during flower development determines the maximum number of seeds per silique and thereby affects crop productivity; however, the genetic basis of ON remains poorly understood in oilseed rape (Brassica napus). In this study, we genetically dissected the ON variations in a double haploid (DH) population and in natural population (NP) by linkage mapping and genome-wide association analysis. Phenotypic analysis showed that ON displayed normal distribution in both populations with the broad-sense heritability of 0.861 (DH population) and 0.930 (natural population). Linkage mapping identified 5 QTLs related to ON, including qON-A03, qON-A07, qON-A07-2, qON-A10, and qON-C06. Genome-wide association studies (GWAS) revealed 214, 48, and 40 significant single-nucleotide polymorphisms (SNPs) by individually using the single-locus model GLM and the multiple-locus model MrMLM and FASTMrMLM. The phenotypic variation explained (PVE) by these QTLs and SNPs ranged from 2.00-17.40% to 5.03-7.33%, respectively. Integration of the results from both strategies identified four consensus genomic regions associated with ON from the chromosomes A03, A07, and A10. Our results preliminarily resolved the genetic basis of ON and provides useful molecular markers for plant yield improvement in B. napus. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01355-7.

Identification of a Major-Effect Quantitative Trait Loci Associated with Begomovirus Resistance in Cucurbita moschata.

Begomoviruses, viz. squash leaf curl China virus and tomato leaf curl New Delhi virus causative diseases are major concerns of quantitative and qualitative losses in pumpkin (Cucurbita moschata) worldwide. Punjab Agricultural University (PAU) in India has identified a resistant source (PVR-1343) against mixed infection (MI-Sq/To) of these begomoviruses. Introgression of resistance in diverse genetic backgrounds requires the identification of quantitative trait loci (QTLs) associated with MI-Sq/To resistance. Phenotyping of 229 F2:3 progenies derived from the PVR-1343 × P-135 cross revealed digenic recessive inheritance against MI-Sq/To resistance in PVR-1343. To identify the genomic region, resistant and susceptible bulks were subjected to whole-genome resequencing along with their parents. The whole-genome resequence analysis of parents and bulks using QTLseq/QTLseqr approaches identified an overlapping 1.52 Mb region on chromosome 7 (qMI-Sq/To7.1), while chromosomal region spanning 0.87 Mb on chromosome17 (qMI-Sq/To17.1) was additionally identified by QTLseqr. However, the highest peak value on chromosome 7 with three algorithms {G', ∆(SNP-index) and -log10 (P value)} highlighted the major contribution of qMI-Sq/To7.1 in MI-Sq/To resistance. Nine polymorphic SNPs identified within the highly significant qMI-Sq/To7.1 region were converted into KASP markers. KASP genotyping of F2 individuals narrowed down the qMI-Sq/To7.1 interval to 103 kb region flanked by two markers, Cmo3914729 and Cmo4018182, which contained 16 annotated genes and accounted for 59.84% of phenotypic variation. The Cmo4018182 KASP marker accurately predicted disease reaction in 91% of diverse Cucurbita genotypes and showed nonsynonym substitutions in the coding region of putative candidate SYNTAXIN-121 gene. These findings pave the way for marker-assisted breeding and elucidating the underlying mechanism of begomovirus resistance in C. moschata.

Identification of candidate genes for salinity tolerance in Japonica rice at the seedling stage based on genome-wide association study and linkage mapping.

Background: Salinity tolerance plays a vital role in rice cultivation because the strength of salinity tolerance at the seedling stage directly affects seedling survival and final crop yield in saline soils. Here, we combined a genome-wide association study (GWAS) and linkage mapping to analyze the candidate intervals for salinity tolerance in Japonica rice at the seedling stage. Results: We used the Na+ concentration in shoots (SNC), K+ concentration in shoots (SKC), Na+/K+ ratio in shoots (SNK), and seedling survival rate (SSR) as indices to assess the salinity tolerance at the seedling stage in rice. The GWAS identified the lead SNP (Chr12_20864157), associated with an SNK, which the linkage mapping detected as being in qSK12. A 195-kb region on chromosome 12 was selected based on the overlapping regions in the GWAS and the linkage mapping. Based on haplotype analysis, qRT-PCR, and sequence analysis, we obtained LOC_Os12g34450 as a candidate gene. Conclusion: Based on these results, LOC_Os12g34450 was identified as a candidate gene contributing to salinity tolerance in Japonica rice. This study provides valuable guidance for plant breeders to improve the response of Japonica rice to salt stress.

Population genomics of helminth parasites.

Next generation sequencing technologies have facilitated a shift from a few targeted loci in population genetic studies to whole genome approaches. Here, we review the types of questions and inferences regarding the population biology and evolution of parasitic helminths being addressed within the field of population genomics. Topics include parabiome, hybridization, population structure, loci under selection and linkage mapping. We highlight various advances, and note the current trends in the field, particularly a focus on human-related parasites despite the inherent biodiversity of helminth species. We conclude by advocating for a broader application of population genomics to reflect the taxonomic and life history breadth displayed by helminth parasites. As such, our basic knowledge about helminth population biology and evolution would be enhanced while the diversity of helminths in itself would facilitate population genomic comparative studies to address broader ecological and evolutionary concepts.

Smooth Descent: A ploidy-aware algorithm to improve linkage mapping in the presence of genotyping errors.

Linkage mapping is an approach to order markers based on recombination events. Mapping algorithms cannot easily handle genotyping errors, which are common in high-throughput genotyping data. To solve this issue, strategies have been developed, aimed mostly at identifying and eliminating these errors. One such strategy is SMOOTH, an iterative algorithm to detect genotyping errors. Unlike other approaches, SMOOTH can also be used to impute the most probable alternative genotypes, but its application is limited to diploid species and to markers heterozygous in only one of the parents. In this study we adapted SMOOTH to expand its use to any marker type and to autopolyploids with the use of identity-by-descent probabilities, naming the updated algorithm Smooth Descent (SD). We applied SD to real and simulated data, showing that in the presence of genotyping errors this method produces better genetic maps in terms of marker order and map length. SD is particularly useful for error rates between 5% and 20% and when error rates are not homogeneous among markers or individuals. With a starting error rate of 10%, SD reduced it to ∼5% in diploids, ∼7% in tetraploids and ∼8.5% in hexaploids. Conversely, the correlation between true and estimated genetic maps increased by 0.03 in tetraploids and by 0.2 in hexaploids, while worsening slightly in diploids (∼0.0011). We also show that the combination of genotype curation and map re-estimation allowed us to obtain better genetic maps while correcting wrong genotypes. We have implemented this algorithm in the R package Smooth Descent.

Towards Marker-Assisted Breeding for Black Rot Bunch Resistance: Identification of a Major QTL in the Grapevine Cultivar 'Merzling'.

Black rot (BR), caused by Guignardia bidwellii, is an emergent fungal disease threatening viticulture and affecting several mildew-tolerant varieties. However, its genetic bases are not fully dissected yet. For this purpose, a segregating population derived from the cross 'Merzling' (hybrid, resistant) × 'Teroldego' (V. vinifera, susceptible) was evaluated for BR resistance at the shoot and bunch level. The progeny was genotyped with the GrapeReSeq Illumina 20K SNPchip, and 7175 SNPs were combined with 194 SSRs to generate a high-density linkage map of 1677 cM. The QTL analysis based on shoot trials confirmed the previously identified Resistance to Guignardia bidwellii (Rgb)1 locus on chromosome 14, which explained up to 29.2% of the phenotypic variance, reducing the genomic interval from 2.4 to 0.7 Mb. Upstream of Rgb1, this study revealed a new QTL explaining up to 79.9% of the variance for bunch resistance, designated Rgb3. The physical region encompassing the two QTLs does not underlie annotated resistance (R)-genes. The Rgb1 locus resulted enriched in genes belonging to phloem dynamics and mitochondrial proton transfer, while Rgb3 presented a cluster of pathogenesis-related Germin-like protein genes, promoters of the programmed cell death. These outcomes suggest a strong involvement of mitochondrial oxidative burst and phloem occlusion in BR resistance mechanisms and provide new molecular tools for grapevine marker-assisted breeding.