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Improving the end-use quality traits is one of the primary objectives in wheat breeding programs. In the current study, a population of 127 recombinant inbred lines (RILs) derived from a cross between Glenn (PI-639273) and Traverse (PI-642780) was developed and used to identify quantitative trait loci (QTL) for 16 end-use quality traits in wheat. The phenotyping of these 16 traits was performed in nine environments in North Dakota, USA. The genotyping for the RIL population was conducted using the wheat Illumina iSelect 90K SNP assay. A high-density genetic linkage map consisting of 7,963 SNP markers identified a total of 76 additive QTL (A-QTL) and 73 digenic epistatic QTL (DE-QTL) associated with these traits. Overall, 12 stable major A-QTL and three stable DE-QTL were identified for these traits, suggesting that both A-QTL and DE-QTL played an important role in controlling end-use quality traits in wheat. The most significant A-QTL ( AQ.MMLPT.ndsu.1B ) was detected on chromosome 1B for mixograph middle line peak time. The AQ.MMLPT.ndsu.1B A-QTL was located very close to the position of the Glu-B1 gene encoding for a subunit of high molecular weight glutenin and explained up to 24.43% of phenotypic variation for mixograph MID line peak time. A total of 23 co-localized QTL loci were detected, suggesting the possibility of the simultaneous improvement of the end-use quality traits through selection procedures in wheat breeding programs. Overall, the information provided in this study could be used in marker-assisted selection to increase selection efficiency and to improve the end-use quality in wheat.

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Understanding the genetics of drought tolerance in hard red spring wheat (HRSW) in northern USA is a prerequisite for developing drought-tolerant cultivars for this region. An association mapping (AM) study for drought tolerance in spring wheat in northern USA was undertaken using 361 wheat genotypes and Infinium 90K single-nucleotide polymorphism (SNP) assay. The genotypes were evaluated in nine different locations of North Dakota (ND) for plant height (PH), days to heading (DH), yield (YLD), test weight (TW), and thousand kernel weight (TKW) under rain-fed conditions. Rainfall data and soil type of the locations were used to assess drought conditions. A mixed linear model (MLM), which accounts for population structure and kinship (PC+K), was used for marker–trait association. A total of 69 consistent QTL involved with drought tolerance-related traits were identified, with p ≤ 0.001. Chromosomes 1A, 3A, 3B, 4B, 4D, 5B, 6A, and 6B were identified to harbor major QTL for drought tolerance. Six potential novel QTL were identified on chromosomes 3D, 4A, 5B, 7A, and 7B. The novel QTL were identified for DH, PH, and TKW. The findings of this study can be used in marker-assisted selection (MAS) for drought-tolerance breeding in spring wheat.

Understanding the genetics of drought tolerance can expedite the development of drought-tolerant cultivars in wheat. In this study, we dissected the genetics of drought tolerance in spring wheat using a recombinant inbred line (RIL) population derived from a cross between a drought-tolerant cultivar, ‘Reeder’ (PI613586), and a high-yielding but drought-susceptible cultivar, ‘Albany.’ The RIL population was evaluated for grain yield (YLD), grain volume weight (GVW), thousand kernel weight (TKW), plant height (PH), and days to heading (DH) at nine different environments. The Infinium 90 k-based high-density genetic map was generated using 10,657 polymorphic SNP markers representing 2,057 unique loci. Quantitative trait loci (QTL) analysis detected a total of 11 consistent QTL for drought tolerance-related traits. Of these, six QTL were exclusively identified in drought-prone environments, and five were constitutive QTL (identified under both drought and normal conditions). One major QTL on chromosome 7B was identified exclusively under drought environments and explained 13.6% of the phenotypic variation (PV) for YLD. Two other major QTL were detected, one each on chromosomes 7B and 2B under drought-prone environments, and explained 14.86 and 13.94% of phenotypic variation for GVW and YLD, respectively. One novel QTL for drought tolerance was identified on chromosome 2D. In silico expression analysis of candidate genes underlaying the exclusive QTLs associated with drought stress identified the enrichment of ribosomal and chloroplast photosynthesis-associated proteins showing the most expression variability, thus possibly contributing to stress response by modulating the glycosyltransferase (TraesCS6A01G116400) and hexosyltransferase (TraesCS7B01G013300) unique genes present in QTL 21 and 24, respectively. While both parents contributed favorable alleles to these QTL, unexpectedly, the high-yielding and less drought-tolerant parent contributed desirable alleles for drought tolerance at four out of six loci. Regardless of the origin, all QTL with significant drought tolerance could assist significantly in the development of drought-tolerant wheat cultivars, using genomics-assisted breeding approaches.

The leafhopper Hishimonus phycitis has received considerable attention as a vector of witches' broom disease of lime phytoplasma. In the present study, nine polymorphic microsatellite loci were isolated from a repeat-enriched genomic library of H. phycitis. The number of alleles varied between 2 and 4 with an average of 2.80 per locus. The observed and expected heterozygosities ranged from 0.28 to 0.84 and 0.28 to 0.80, respectively. The Polymorphism Information Content varied from 0.25 to 0.75 with an average of 0.55. These microsatellites will be useful for future genetic studies of H. phycitis populations and could help in the development of an efficient control strategy against this vector.

29Improving the end-use quality traits is one of the primary objectives in wheat breeding programs. 30 In the current study, a population of 127 recombinant inbred lines (RILs) derived from a cross 31 between Glenn (PI-639273) and Traverse (PI-642780) was developed and used to identify 32 quantitative trait loci (QTL) for 16 end-use quality traits in wheat. The phenotyping of these 16 33 traits was performed in nine environments in North Dakota, USA. The genotyping for the RIL 34 population was conducted using the wheat Illumina iSelect 90K SNP assay. A high-density 35 genetic linkage map consisting of 7,963 SNP markers identified a total of 76 additive QTL (A-36 QTL) and 73 digenic epistatic QTL (DE-QTL) associated with these traits. Overall, 12 stable 37 major A-QTL and three stable DE-QTL were identified for these traits, suggesting that both A-38 QTL and DE-QTL played an important role in controlling end-use quality traits in wheat. The 39 most significant A-QTL (AQ.MMLPT.ndsu.1B) was detected on chromosome 1B for mixograph 40 middle line peak time. The AQ.MMLPT.ndsu.1B A-QTL was located very close to the position 41 of the Glu-B1 gene encoding for a subunit of high molecular weight glutenin and explained up to 42 24.43% of phenotypic variation for mixograph MID line peak time. A total of 23 co-localized 43 QTL loci were detected, suggesting the possibility of the simultaneous improvement of the end-44 use quality traits through selection procedures in wheat breeding programs. Overall, the 45 information provided in this study could be used in marker-assisted selection to increase 46 selection efficiency and to improve the end-use quality in wheat. 47 48 49 50 51 4 Abbreviations 52 AACCI American Association of Cereal Chemists International 53 A-QTL additive QTL 54 BA baking absorption 55 BLV bread loaf volume 56 BLUP best linear unbiased predictor 57 BMT bake-mixing time 58 CBCL crumb color 59 CTCL crust color 60 cM centimorgans 61 DArT diversity arrays technology 62 DE-QTL digenic epistatic QTL 63 DO dough character 64 FE flour extraction 65 FHB Fusarium head blight 66 GPC grain protein content 67 HMW high molecular weight 68 HRSW hard red spring wheat 69 ICIM-ADD inclusive composite interval mapping with additive effects 70 ICIM-EPI inclusive composite interval mapping of epistatic QTL 71 LMW low molecular weight 72 MAS marker-assisted selection 73 5 MELS mixograph envelope left slope 74 MERS mixograph envelope right slope 75 MMLPI mixograph MID line peak integral 76 MMLPT mixograph MID line peak time 77 MMLPV mixograph MID line peak value 78 MMLPW mixograph MID line peak width 79 MMLTV mixograph MID line time * value 80 MIXOPA general mixograph pattern 81 NDSU North Dakota State University 82 NIR near-infrared reflectance 83 PPM parts per million 84 PV phenotypic variation 85 QTL quantitative trait loci 86 RCBD randomized complete block design 87 RFLP restriction fragment length polymorphisms 88 REML restricted maximum likelihood 89 SSD single seed descent 90 SKB Sandstedt, Kneen, and Blish 91 6 92W...

There is limited information regarding the morphometric relationships of panicle traits in oat (Avena sativa) and their contribution to phenology and growth, physiology, and pathology traits important for yield. To model panicle growth and development and identify genomic regions associated with corresponding traits, 10 diverse spring oat mapping populations (n = 2,993) were evaluated in the field and 9 genotyped via genotyping-by-sequencing. Representative panicles from all progeny individuals, parents, and check lines were scanned, and images were analyzed using manual and automated techniques, resulting in over 60 unique panicle, rachis, and spikelet variables. Spatial modeling and days to heading were used to account for environmental and phenological variances, respectively. Panicle variables were intercorrelated, providing reproducible archetypal and growth models. Notably, adult plant resistance for oat crown rust was most prominent for taller, stiff stalked plants having a more open panicle structure. Within and among family variance for panicle traits reflected the moderate-to-high heritability and mutual genome-wide associations (hotspots) with numerous high-effect loci. Candidate genes and potential breeding applications are discussed. This work adds to the growing genetic resources for oat and provides a unique perspective on the genetic basis of panicle architecture in cereal crops.