The Hessian recessive resistance gene h4 mapped to chromosome 1A of the cultivar ‘Java’ using genotyping-by- sequencing

Fuan Niu, Yunfeng Xu, Xuming Liu, Lanfei Zhao, Amy Bernardo, Yaoguang Li, Guoxia Liu, Ming-Shun Chen, Liming Cao, Zhenbin Hu, et al.

Theoretical and Applied Genetics International Journal of Plant Breeding Research

ISSN 0040-5752

Theor Appl Genet DOI 10.1007/s00122-020-03642-9

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Theoretical and Applied Genetics https://doi.org/10.1007/s00122-020-03642-9

ORIGINAL ARTICLE

The Hessian fy recessive resistance gene h4 mapped to chromosome 1A of the wheat cultivar ‘Java’ using genotyping‑by‑sequencing

Fuan Niu1,2 · Yunfeng Xu2 · Xuming Liu3 · Lanfei Zhao2 · Amy Bernardo3 · Yaoguang Li2 · Guoxia Liu2,4 · Ming‑Shun Chen3 · Liming Cao1 · Zhenbin Hu2 · Xiangyang Xu5 · Guihua Bai2,3

Received: 13 April 2020 / Accepted: 20 June 2020 © This is a U.S. government work and its text is not subject to copyright protection in the United States; however, its text may be subject to foreign copyright protection 2020

Abstract Key message The recessive Hessian fy resistance gene h4 and fanking SNP markers were located to a 642 kb region in chromosome 1A of the wheat cultivar ‘Java.’ Abstract Hessian fy (HF), destructor, is one of the most destructive pests in wheat worldwide. The wheat cultivar ‘Java’ was reported to carry a recessive gene (h4) for HF resistance; however, its chromosome location has not been determined. To map the HF resistance gene in Java, two populations of recombinant inbred lines (RILs) were developed from ‘Bobwhite’ × Java and ‘Overley’ × Java, respectively, and were phenotyped for responses to infestation of HF Great Plains biotype. Analysis of phenotypic data from the F1 and the RIL populations confrmed that one recessive gene con- ditioned HF resistance in Java. Two linkage maps were constructed using single-nucleotide polymorphism (SNP) markers generated by genotyping-by-sequencing (GBS). The h4 gene was mapped to the distal end of the short arm of chromosome 1A, which explained 60.4 to 70.5% of the phenotypic variation for HF resistance in the two populations. The GBS-SNPs in the h4 candidate interval were converted into Kompetitive Allele-Specifc Polymerase Chain Reaction (KASP) markers to eliminate the missing data points in GBS-SNPs. Using the revised maps with KASP markers, h4 was further located to a 642 kb interval (6,635,984–7,277,935 bp). The two fanking KASP markers, KASP3299 and KASP1871, as well as four other closely linked KASP markers, may be useful for pyramiding h4 with other HF resistance genes in breeding.

Introduction Mayetiola destructor (Say)] is one of the most serious insect pests in wheat in many wheat-growing regions worldwide, Wheat (Triticum aestivum L.) is one of the most important including North Africa, Europe, New Zealand, the USA and cereal crops and serves as the for 35% of the Southwest Asia (Ratclife et al. 2000; Stuart et al. 2012). world’s population (Paux et al. 2008). Hessian fy [HF; Wheat severely damaged by the HF can die at the seedling stage or survive with stunted tillers, broken stems, reduced kernel number and size leading to low grain yield and qual- Communicated by Xianchun Xia. ity (Li et al. 2013; Schwarting et al. 2016; Smiley et al. 2004). Developing and deploying resistant cultivars is the * Guihua Bai [email protected] most efective and economical approach to HF control. Thirty-fve HF resistance genes have been identifed, of- 1 Institute of Crop Breeding and Cultivation, Shanghai cially designated as H1–H3, h4, H5–H34 and Hdic (Li et al. Academy of Agricultural Sciences, Shanghai 201403, China 2013). All these resistance genes are dominant with only 2 Department of Agronomy, Kansas State University, 2004 h4 being recessive. Fifteen of the reported resistance genes Throckmorton Hall, Manhattan, KS 66506, USA were assigned to a gene cluster in the short arm of chromo- 3 Hard Genetics Research Unit, USDA-ARS, some 1A (1AS), including H3, H5, H6, H9, H10, H11, H12, 4008 Throckmorton Hall, Manhattan, KS 66506, USA H14, H15, H16, H17, H19, H28, H29, and Hdic (Kong et al. 4 Bio‑Tech Research Center, Shandong Academy 2005, 2008; Liu et al. 2005a, b). Several quantitative trait of Agricultural Sciences, Jinan 250100, Shandong, China loci (QTLs) have also been reported on 1AS recently (Carter 5 Wheat, Peanut and Other Field Crops Research Unit, 1301 et al. 2014; Li et al. 2013, 2015; Tan et al. 2013). N. Western Rd., Stillwater, OK 74075, USA

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Eighteen HF biotypes, including biotypes A to O, GP Materials and methods (Great Plains), vH9 and vH13, have been reported based on their diferential responses to resistance genes H3, H5, H6, Plant materials H7H8, H9 and H13 (Formusoh et al. 1996; Ratclife and Hatchett 1997; Zantoko and Shukle 1997). Biotype GP is Two RIL populations were developed by single- the predominant biotype in feld populations in the US Great descent. The frst population consisting of 121 RILs was Plains (Tan et al. 2017). Wheat HF resistance fts the gene- developed from the cross Bobwhite × Java (BoJa), and the for-gene model (Hatchett and Gallun 1970), meaning that HF second population consisting of 189 RILs was developed resistance genes provide resistance only to certain biotypes from the cross Overley × Java (OvJa). Java (CItr 12763) is an carrying corresponding avirulence genetic factors. Large acre- old winter wheat accession carrying h4 (Suneson and Noble ages of similar cultivars place evolutionary pressure on HF to 1950) with unknown pedigree; Bobwhite (PI 519665) is a overcome resistance as evidenced by biotypes that overcome hard red spring wheat cultivar with the pedigree of Aurora// H3, H5, H6 and H7H8 in the southeastern USA (Cambron Kalyan/Bluebird/3/Woodpecker sib (Warburton et al. 2002). et al. 2010). The rapid evolution of HF biotypes increases the Overley is a hard red winter wheat cultivar with the pedigree difculty of controlling this insect. Pyramiding multiple resist- of U1275-1-4-2-2/Heyne‘S’//Jagger (https://books​ tore.ksre.​ ance genes in a cultivar using marker-assisted selection is an ksu.edu/pubs/L924.pdf). Both Bobwhite and Overley were essential and efective strategy to improve the level and dura- susceptible to HF biotype GP. The 20 F1 seedlings from the bility of HF resistance in new wheat cultivars. crosses of Bobwhite × Java and Overley × Java were screened Many diferent technologies have been used to map genes for HF resistance. A susceptible cultivar ‘Danby’ and three for HF resistance (Raupp et al. 1993; Roberts and Gallum resistant cultivars, ‘Carol’ with H3, ‘Caldwell’ with H6, and 1984; Kong et al. 2005, 2008; Liu et al. 2005a, b); however, ‘Molly’ with H13, were used as controls for phenotyping. single-nucleotide polymorphism (SNP) is more suitable for high-resolution gene mapping and functional marker develop- Evaluation of HF resistance ment. The rapid development of next-generation sequencing (NGS) technologies makes it possible to generate thousands Wheat seedlings were infested with HF biotype GP (Chen of SNPs per sample at an afordable low cost. Genotyping-by- et al. 2009) in a greenhouse at Kansas State University, Man- sequencing (GBS) based on NGS technologies has been used hattan, KS. The F5-derived RILs of BoJa, three parents, F1 as a cost-efective and robust marker system in wheat because and four controls were screened in both fall 2017 (F5:6) and it combines the marker discovery step with genotyping to gen- spring 2018 (F5:7), while the OvJa F4:5 RIL population was erate a large number of SNPs for many applications (He et al. screened only in fall 2017. Approximately 20 per line 2014; Poland et al. 2012; Poland and Rife 2012). were planted in a tray (56 × 36 × 10 cm) with 24 half-rows ‘Java’ is an old wheat cultivar that was previously containing a mixture of 2:1:1 soil, sand and vermiculite. The reported to carry a single recessive HF resistance gene h4 four controls were planted at the middle rows on each tray. (Suneson and Noble 1950). The chromosomal location of The greenhouse temperature was maintained at 18 ± 3 °C h4 was not determined. Although h4 alone shows only par- with a 14/10 h light/dark photoperiod. At the 1.5-leaf stage, tial HF resistance, the lines carrying h4 usually have bet- GP biotype adults were released on the seedlings in the ter tillering after Hessian fy damage, thus pyramiding h4 trays under a cheesecloth tent to maintain high humidity with other HF resistance genes may improve durability of and restrict the fies within the tent. The cheesecloth tent HF resistance and the diversity of HF resistance genes in was removed when larvae hatched from eggs. HF damage resistant cultivars. However, the lack of genetic position and on infested seedlings was scored 3 weeks after infestation. molecular markers linked to h4 limit its utilization in wheat Resistant plants grew normally with light green color, and breeding programs. In this study, we constructed GBS-based dead larvae or very small live larvae were found at the bot- high-density SNP maps using two populations of recombi- tom of the leaf sheath. Susceptible plants were stunted with nant inbred lines (RILs) derived from ‘Bobwhite’ × Java and dark green color with live larvae at the bottom between the ‘Overley’ × Java, respectively, to determine the chromosome leaf sheath and stem. The number of resistant and suscep- location of h4 in Java and develop user-friendly markers for tible plants was counted, and the percentage of resistant marker-assisted selection. plants per line was calculated as the resistance scores for QTL analysis. Phenotypic ratings were rechecked 1 week after initial scoring to ensure data accuracy. To calculate segregation ratio, a RIL with < 10% susceptible plants was classifed as a susceptible line and a line with ≥ 10% resist- ant plants was considered as a resistant line. A chi-squared

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Theoretical and Applied Genetics test was used to test if the segregation ratio ft a monogenic with the Chinese Spring reference genome sequence Ref- inheritance model. Seq v1.0 (IWGSC et al. 2018). Composite interval map- ping (CIM) was performed to detect QTLs using the Win- DNA extraction and GBS analysis QTLCart software v2.5 (Wang et al. 2012). QTLs were scanned using a 1-cM window and claimed to be signif- Leaf tissue was collected at the three-leaf stage from both cant at a LOD score of 3. BoJa F5:6 and OvJa F4:5 RIL populations and the three parents. The collected tissue was freeze-dried for 48 h in Conversion of GBS‑SNPs into Kompetitive 1.1-mL 96-deep-well plates with a 3-mm stainless bead Allele‑Specifc Polymerase Chain Reaction (KASP) in each well and ground at 30 cycles per sec for 3 min in a markers Mixer Mill (Retsch GmbH, Germany). Genomic DNA was extracted using a modifed cetyltrimethylammonium bro- GBS-SNP markers under the major QTL peak were con- mide (CTAB) method (Li et al. 2013). DNA was checked verted to KASP markers. KASP primers were designed for quality by electrophoresis using 1% agarose gel and using Primer 3 v.0.4.0 (http://bioinfo.ut.ee/prime​ r3-0.4.0/​ ). quantifed using Quant-iT™ PicoGreen dsDNA assay kits All KASP primers included two forward primers and one (Thermo Fisher Scientifc, Waltham, MA, USA). All DNA reverse primer. Two diferent tail sequences were added samples were normalized to 20 ng/µL for GBS library to the 5′-end of the two forward primers so that two fu- construction. orescence-dye-labeled primers in the KASP reaction mix GBS libraries were generated from DNA samples of could pair with them for PCR; the FAM fuorescence- each RIL line and triplicate parents using the previously labeled primer matched with the tail sequence GAA​GGT​ reported methods (Poland et al. 2012). In brief, DNA sam- GAC​CAA​GTT​CAT​GCT, and HEX fuorescence-labeled ples were digested with HF-PstI (high fdelity) and MspI primer matched with the GAA​GGT​CGG​AGT​CAA​CGG​ (New England BioLabs Inc., Ipswich, MA, USA) and then ATT tail. KASP assays were performed in a 4 μL reaction ligated to adaptors with barcodes and a common Y-adaptor volume consisting of 1.94 μL of 2 × KASP reaction mix, using T4 DNA ligase (New England BioLabs Inc.). All 0.06 μL primer assay mix and 2 μL DNA. A PTC-200 ther- ligated DNA samples were pooled and cleaned up using a mal cycler (MJ Research, Watertown, MA, USA) was used QIAquick PCR Purifcation Kit (QIAGEN GmbH Hilden, for PCR amplifcation following the manual (https://biose​ ​ Germany). PCR amplifcation was performed using prim- arch-cdn.azureedge.net/asset​ sv6/KASP-genot​ yping​ -chemi​ ​ ers complementary to both adaptors. PCR products were stry-User-guide​.pdf). PCR products were scanned in an cleaned up again, and fragments with 200–300 bp were FLUOstar­ ® Omega microplate reader (BMG LABTECH kept for sequencing on an Ion Proton next-generation Inc., Cary, NC), and data were analyzed using Kluster- sequencer (Thermo Fisher Scientific, Waltham, MA, Caller software v3.4.1.39 (LGC group, Teddington, UK). USA). Before sequencing, the concentration of selected KASP markers were first screened for polymorphism PCR products was measured using a Qubit 2.0 Fluorometer among parents, and polymorphic markers were then used and Qubit dsDNA HS Assay Kits (Life Technologies Inc.). to genotype the two mapping populations. GBS-SNPs A universal network-enabled analysis kit (UNEAK) pipe- were substituted by the corresponding KASP markers to line was used to call SNPs (Glaubitz et al. 2014; Elshire reconstruct the linkage map for QTL mapping. et al. 2011). SNPs with < 20% missing data and < 10% het- erozygotes were used for genetic linkage map construc- tion and gene mapping. Physical positions of SNPs were determined by aligning the SNP sequences against Chinese Results Spring wheat reference genome (IWGSC et al. 2018) using a Basic Local Alignment Search Tool (BLAST). HF resistance in parents and their RIL populations

Java had 55% and 50% resistant plants in fall 2017 and Linkage map construction and QTL analysis spring 2018 experiments, respectively, whereas Bobwhite and Overley were completely susceptible in both experi- The genetic linkage map was constructed using the MAP ments (Fig. 1). All 20 F1 plants from the crosses of Bob- function in QTL IciMapping v4.1 (Wang et al. 2016). white × Java and Overley × Java were completely suscep- Markers with the least missing data points were retained in tible in both experiments. The segregation ratio between each bin, and redundant markers were removed using the resistant and susceptible (R/S) RILs ft the 1:1 single- BIN function. Each linkage group was assigned to a spe- gene segregation ratio in both populations, with χ2 = 0.03 cifc chromosome by comparing GBS-SNP tag sequences (P = 0.86) in the 2017 experiment and χ2 = 0.83 (P = 0.35)

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Fig. 1 Frequency distribution of HF resistance scores of Bob- white × Java (BoJa) recombinant inbred lines (RILs) evaluated in fall 2017 (F5:6) and spring 2018 (F5:7), and Overley × Java (OvJa) F4:5 RILs evaluated in fall 2017. The RIL lines were classifed based on HF resist- ance score: susceptible (0%) and resistant (10–90%). Bo, Ov and Ja represent Bobwhite, Overley and Java

in the 2018 experiment for BoJa, and χ2 = 0.34 (P = 0.56) population, as well as OJGBS3299 and OJGBS1903 in in the 2017 experiment for the OvJa population (Fig. 1). the OvJa population (Table 1). Nine other GBS-SNP mark- These results indicated that the HF resistance in Java was ers (BJGBS1871, BJGBS2446, BJGBS901, BJGBS1300, mainly controlled by one recessive gene. BJGBS974, BJGBS1856, OJGBS1027, OJGBS1218 and OJGBS2504) were also mapped in the QTL interval. Since Linkage map construction this QTL was the only QTL detected in Java with a stable major efect, we designated it as h4 hereafter. A total of 25,911 GBS-SNPs were generated for the BoJa population. Among the 3335 GBS-SNPs with < 20% miss- ing data points, 1090 SNPs were used to construct a link- KASP marker development and h4 remapping age map. The map had 30 linkage groups, covering a total genetic distance of 2415.4 cM at an average marker density To improve the accuracy of the QTL map, 13 GBS-SNPs of 2.2 cM per marker. The 30 linkage groups represented all in the h4 candidate interval were converted to KASP 21 wheat chromosomes in which 2B was the longest with markers, and six of the 13 markers were polymorphic 116 SNPs spanning 194.8 cM and chromosome 4D was the between the resistant parent and at least one of the suscep- shortest with 3 SNPs spanning 12.3 cM. tible parents (Table 2). Four KASP markers (KASP1583, A total of 43,963 GBS-SNPs were scored for the OvJa KASP1871, KASP2446 and KASP974) were derived from population. Among the 3370 SNPs with < 20% missing data the BoJa population, and two (KASP1218 and KASP3299) points, 1542 SNPs were used for linkage map construction. came from the OvJa population (Fig. 2). KASP2446 The map consisted of 25 linkage groups representing all 21 showed segregation only in the BoJa population, while chromosomes with a total genetic distance of 3444.0 cM and the other fve KASP markers segregated in both popula- an average marker density of 2.2 cM per marker. Among tions. Genotyping of the two RIL populations using the the 21 chromosomes, 7A was the longest with 116 SNPs six KASP markers flled in 64 missing data points and spanning 226.2 cM and 6D was the shortest with 3 SNPs corrected 18 data points that were mis-scored by GBS. spanning 27.6 cM. The chromosome 1A linkage maps of the BoJa and OvJa populations were updated by replacing the GBS- QTL analysis SNPs in the h4 region with the corresponding KASP marker data. The fnal 1A maps contained 45 SNP markers Using composite interval mapping (CIM), one major QTL including six KASP markers in the BoJa population and (QHf-hwwg-1A) on the distal end of chromosome arm 96 SNP markers including fve KASP markers in the OvJa 1AS was consistently identifed in both BoJa and OvJa population (Fig. 3). Using the new maps, h4 was rema- populations in the 2017 experiment and BoJa population pped to a 642 kb interval fanked by markers KASP3299 in the 2018 experiment (Table 1). The QTL explained (6,635,984 bp) and KASP1871 (7,277,935 bp) (Fig. 3, 62.2–70.4% of the phenotypic variation for HF resistance Table 1). Searching for annotated candidate genes in this with high LOD scores. The allele from Java increased region in Chinese Spring reference genome (IWGSC 2018) HF resistance by 14.6–20.3%. This QTL was flanked identifed 17 high-confdence genes (Table 3). Among by markers BJGBS1213 and BJGBS1583 in the BoJa them, six candidate genes are annotated as plant disease

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Table 1 Chromosome (Chr) positions, quantitative trait locus (QTL) QTL QHf-hwwg-1A detected in Bobwhite × Java (BoJa) and Over- peak (cM) and genetic (cM) and physical (bp) intervals, fanking ley × Java (OvJa) recombinant inbred populations evaluated in fall markers, logarithm of the odds (LOD) scores, phenotypic variation 2017 and spring 2018 explained (PVE %) and additive efects (Add) of the HF resistance

Map ­typea Experiment Chr Peak (cM) QTL interval (cM) Flanking marker Physical interval LOD PVE (%) Addc (bp)b

GBS-SNP map BoJa—fall 2017 1A 6.0 0–7.8 BJGBS1213– 1,158,042– 25.9 68.1 − 16.8 BJGBS1583 6,370,170 BoJa—spring 2018 1A 7.0 0–7.8 BJGBS1213– 1,158,042– 21.0 70.4 − 20.3 BJGBS1583 6,370,170 OvJa—fall 2017 1A 7.4 6.4–11.4 OJGBS3299– 6,635,984– 33.4 62.2 − 14.6 OJGBS 1903 7,277,970 KASP maps BoJa—fall 2017 1A 8.0 8.0–8.9 KASP3299– 6,635,984– 29.6 70.3 − 16.6 KASP1871 7,277,935 BoJa—spring 2018 1A 8.0 8.0–8.9 KASP3299– 6,635,984– 26.3 70.5 − 20.4 KASP1871 7,277,935 OvJa—fall 2017 1A 6.8 5.8–9.6 KASP3299– 6,635,984– 33.5 60.4 − 14.9 KASP1871 7,277,935 a GBS-SNP maps were constructed using GBS-SNPs (upper); KASP maps refer to the updated maps by replacing GBS-SNP markers in the QTL region with corresponding KASP markers b Physical positions of fanking markers were determined by searching the SNP sequences against Chinese Spring wheat reference genome Ref- Seq v1.0 (IWGSC et al. 2018) c Additive efect, negative value indicates positive allele from Java

Table 2 Primer sequences and physical positions of KASP markers converted from GBS sequences within the h4 candidate region Marker name Physical position (bp) Forward primer1 (5′–3′) Forward primer2 (5′–3′) Reverse primer (5′–3′)

KASP1583 6,370,170 AAC​CGA​AGC​AAG​ACT​AGC​ AAC​CGA​AGC​AAG​ACT​AGT​ GGT​GAA​GGT​GAG​GAA​GAA​A KASP1871 7,277,935 GCT​GCG​GTT​TGT​GCT​TCT​ GCT​GCG​GTT​TGT​GCT​TCC​ TGT​GGG​CAT​CAC​CAT​CAC​ KASP2446 8,575,021 GAG​GGT​CTT​AAC​CAA​CAT​ GAG​GGT​CTT​AAC​CAA​CAT​ TTC​TTC​GTC​CAG​TAA​TGA​CC AAAA​ AAAT​ KASP974 9,011,078 GTC​CAG​CAC​GAC​GGA​CAG​ GTC​CAG​CAC​GAC​GGA​CAG​ CGC​ACC​ATC​AAC​CAG​CTC​ GA GG KASP1218 3,793,352 CCA​TTG​CCA​TCT​TGA​ACC​ CCA​TTG​CCA​TCT​TGA​ACT​ GGA​GGT​GGC​CGT​CAAGC​ KASP3299 6,635,984 GAA​TTG​CCG​AAT​ACC​CCT​AA GAA​TTG​CCG​AAT​ACC​CCT​AG GAG​TTC​ACT​GAA​ATT​CCC​ TAGT​

defense-related genes, including TraesCS1A01G011900, 1950). Since only one resistance QTL was found in Java, TraesCS1A01G012000, and TraesCS1A01G012100, explaining 50–55% of the phenotypic variation for HF TraesCS1A01G012300 and TraesCS1A01G012600 encod- resistance, the QTL we mapped must be h4. The F1 plants ing protein kinases and TraesCS1A01G012400 encoding with heterozygous h4 showed high susceptibility like their a F-box protein. susceptible parents in this study, indicating that the resist- ance gene is recessive, consistent with the original report (Suneson and Noble 1950). Discussion This is the frst report to show that h4 is located in the dis- tal region of chromosome arm 1AS, most probably between In this study, all three experiments using two diferent 6,635,984 and 7,277,935 bp in RefSeqv1 of Chinese Spring RIL mapping populations consistently mapped the Hes- (IWGSC et al. 2018). Previously, more than half of known sian fy resistance QTL from Java to the same region on HF resistance genes, including H9, H10, H11, H16, H17, wheat chromosome arm 1AS. Java was the original source Hdic, have also been mapped to the 1AS region (Kong et al. for the recessive resistance gene h4 (Suneson and Noble 2005, 2008; Liu et al. 2005a, b). Based on our mapping

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Fig. 2 Allele distributions of the fanking markers of h4, KASP1871 (a) and KASP3299 (b) in the Bobwhite × Java (BoJa) population, KASP1871 (c) and KASP3299 (d) in the Overley × Java (OvJa) popula- tion, respectively. The X- and Y-axes indicate FAM and HEX fuorescence, respectively. The green dots are resistant geno- types like Java, the blue dots are susceptible genotypes like Bobwhite (a and b) or Overley (c and d). The red dots represent heterozygous genotypes. The black dots represent non-tem- plate controls

data, h4 is likely located within the same 1AS resistance phenotypic data on dominance and biotype specifcity would gene cluster. Recently, additional QTLs have also been help resolve whether h4 is the same gene as one of the previ- mapped to this Hessian fy resistance gene cluster on 1AS ously reported genes in the cluster. Fine mapping and clon- (Carter et al. 2014; Li et al. 2013, 2015; Tan et al. 2013). For ing of h4 and others will provide defnitive insight into the d example, the QTL QHf.osu-1A on 1AS in ‘Duster’ showed relationships among the genes in this important gene clus- complete resistance to HF biotype GP (Li et al. 2015). QHf. ter. In addition, analysis of annotated genes in the candidate d osu-1A in ‘Duster’ is probably diferent from h4 because region using Chinese Spring reference genome sequence h4 was only partially resistant. Also, the sequence of the (IWGSC 2018) suggested six disease resistance genes for closely linked marker OPR-A1 was located at 8.29 Mb (Li h4, and these genes can be used as putative candidate genes et al. 2015), which is 1 Mb proximal to the h4 interval. The for further cloning of h4. 74 QTL QHf.osu-1A from the wheat cultivar ‘2174’ explains To date, none of the HF resistance genes have been 53% HF resistance in the Jagger × 2174 RILs, and the QHf. cloned, and only a few closely linked KASP markers were 74 osu-1A -linked marker Cfa2153 is within the h4 interval developed recently for marker-assisted selection of HF genes (6.6–7.3 Mb). The QTL QHf-hwwg-1A on 1AS of a soft (Liu et al. 2020; Tan et al. 2017). In this study, we identifed winter wheat ‘Clark’ explained 15–16% of the phenotypic many SNPs in the h4 region using GBS, but the abundance variation for resistance to biotype GP (Li et al. 2013), and of missing data points in GBS is a major concern for the the closely linked marker IWA4505 (8.3 Mb) is apparently accuracy of QTL mapping due to limited sequence depth proximal to the h4 interval. The QTL QHf.wak-1A from (Spindel et al. 2013). These missing data points and sequenc- ‘Louise’ explained 29–35% of the phenotypic variation for ing errors may cause an expansion of the genetic distance resistance to HF biotype C and the closely linked marker between markers in a genetic map or misplace markers in the IWB61102 (6.7 Mb) overlapped with h4 (Carter et al. 2014). map, which may result in inaccurate estimation of the actual 74 Since QHf.osu-1A in ‘2174’ and QHf.wak-1A in ‘Lou- locations of the QTL and its linked markers. Recently, KASP ise’ showed partial resistance at the same location as h4, has become more popular for marker-assisted selection due they all could be the same gene or at least allelic. Further to its low cost, simplicity and rapid assay (Rasheed et al.

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Fig. 3 Composite interval mapping of the Hessian fy (HF) resist- experiments (a) and Overley × Java (OvJa) population phenotyped ance gene h4 on the short arm of chromosome 1A in Bobwhite × Java in the 2017 greenhouse experiment (b) using GBS-SNPs and KASP (BoJa) population phenotyped in the 2017 and 2018 greenhouse markers. LOD logarithm of the odds

2016; Semagn et al. 2014). In this study, we converted the germplasm. Although h4 was one of the earliest described GBS-SNPs in the candidate interval of h4 into KASP mark- HF resistance genes, it has not been consciously deployed. ers to eliminate missing data points and correct the sequence A study of marker haplotypes in this region might help to errors from GBS. The newly constructed linkage maps understand if h4 is already present in commercial cultivars. with KASP markers remapped the h4 QTL to a 642.0 kb In many previous studies, HF resistance has been consid- interval between KASP3299 and KASP1871 on the distal ered as monogenically inherited; thus, an F2 population was end of 1AS. Six KASP markers, KASP1583, KASP1871, usually genotyped and F2 or F2:3 was phenotyped to map HF KASP2446, KASP974 and KASP1218 and KASP3299, in resistance genes (Dweikat et al. 1997; McDonald et al. 2014; the h4 interval, could be used for molecular marker-assisted Wang et al. 2006; Zhao et al. 2006). However, the current study selection of h4 in wheat breeding. The virulence survey by showed that about 45–50% of Java plants were highly suscepti- Chen et al. (2009) suggests that h4 could be a valuable com- ble, and the percentage of resistant plants per line in the RILs ponent of a gene pyramid against HF. All of these markers with h4 ranged from 10 to 90% (Fig. 1). Some cultivars with still need to be validated across a wider range of breeding high resistance usually have more than one gene/QTL (Li et al.

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Table 3 Putative annotated genes identifed within the 642 kb interval of h4 based on Chinese Spring reference genome sequence (IWGSC et al. 2018)

Gene ID Start position (bp) Stop position (bp) Gene description

TraesCS1A01G011300 6,654,735 6,655,383 Dirigent protein TraesCS1A01G011400 6,760,941 6,764,183 bZIP transcription factor TraesCS1A01G011500 6,765,240 6,765,452 Cytochrome oxidase assembly 3 TraesCS1A01G011600 6,766,340 6,766,555 Cytochrome oxidase assembly protein TraesCS1A01G011700 6,773,469 6,773,978 RING/U-box superfamily protein TraesCS1A01G011800 6,788,571 6,793,320 Formin-like protein TraesCS1A01G011900* 6,883,652 6,887,141 Protein kinase TraesCS1A01G012000* 6,899,512 6,903,022 Protein kinase TraesCS1A01G012100* 6,914,044 6,915,989 Kinase-like protein TraesCS1A01G012200 7,100,687 7,101,431 Aluminum-induced protein with YGL and LRDR motifs TraesCS1A01G012300* 7,108,623 7,109,053 Homoserine kinase TraesCS1A01G012400* 7,114,077 7,115,309 F-box protein TraesCS1A01G012500 7,178,341 7,183,980 Transforming growth factor-beta receptor-associated protein 1 TraesCS1A01G012600* 7,185,497 7,186,507 Leucine-rich repeat receptor-like protein kinase family protein TraesCS1A01G012700 7,228,989 7,229,941 Fatty acid oxidation complex subunit alpha TraesCS1A01G012800 7,274,827 7,275,531 Fatty acid oxidation complex subunit alpha TraesCS1A01G012900 7,277,250 7,279,106 Fatty acid oxidation complex subunit alpha

*Highlighted genes are annotated as putative disease resistance-related genes

2013, 2015; Tan et al. 2013). Wheat resistance to HF may also Ethical standards The authors declare that the experiments comply be a quantitative trait. Each resistance gene may contribute with the current laws of the country in which they were performed. partial resistance, and its expression is also afected by envi- ronments, in particular temperatures. A susceptible accession usually has 100% susceptible plants, whereas a line with a References single HF resistance gene may have anywhere from at least one plant to 100% resistant plants depending on the environments. Cambron SE, Buntin GD, Weisz R, Holland JD, Flanders KL, Therefore, repeated phenotyping of each line is necessary to Schemerhorn BJ, Shukle RH (2010) Virulence in Hessian fy (Diptera: ) feld collections from the southeastern ensure the accuracy of gene mapping. Phenotypic data based United States to 21 resistance genes in wheat. J Econ Entomol on a single plant are not reliable for QTL mapping. 103:2229–2235 Carter A, Cambron S, Ohm H, Bosque-Pérez N, Kidwell KK (2014) Acknowledgements This is contribution number 20-239-J from the Hessian fy (Mayetiola destructor [Say]) resistance identifed Kansas Agricultural Experiment Station. This project is partly funded on chromosome 1AS in the spring wheat (Triticum aestivum L.) by the National Research Initiative Competitive Grants 2017-67007- cultivar ‘Louise’. Crop Sci 54:971–981 25939 from the US Department of Agriculture National Institute of Chen MS, Echegaray E, Whitworth RJ, Wang HY, Sloderbeck PE, Food and Agriculture, and Program of Shanghai Technology Research Knutson A, Giles KL, Royer TA (2009) Virulence analysis of Leader (18XD1424300), China. Mention of trade names or commercial Hessian fy populations from Texas, Oklahoma, and Kansas. J products in this publication is solely for the purpose of providing spe- Econ Entomol 102:774–780 cifc information and does not imply recommendation or endorsement Dweikat I, Ohm H, Patterson F, Cambron S (1997) Identifcation of by the USDA. USDA is an equal opportunity provider and employer. RAPD markers for 11 Hessian fy resistance genes in wheat. Theor Appl Genet 94:419–423 Author contribution statement GB designed the research; FN, YX, Elshire RJ, Glaubitz JC, Sun Q, Poland JA, Kawamoto K, Buck- XL LZ, AB, YL, GL, MC, ZH and XX performed the research; FN, ler ES, Mitchell SE (2011) A robust, simple genotyping-by- YX and LC analyzed the data; FN, YX and GB wrote the paper. All sequencing (GBS) approach for high diversity species. PLoS the authors read and approved the manuscript. ONE 6:e19379 Formusoh ES, Hatchett JH, Black WC, Stuart JJ (1996) Sex-linked inheritance of virulence against wheat resistance gene H9 in the Compliance with ethical statements Hessian fy (Diptera: Cecidomyiidae). Ann Entomol Soc Am 89:428–434 Conflict of interest The authors declare that they have no confict of Glaubitz JC, Casstevens TM, Lu F, Harriman J, Elshire RJ, Sun Q, interest. Buckler ES (2014) TASSEL-GBS: a high capacity genotyping by sequencing analysis pipeline. PLoS ONE 9:e90346

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Theoretical and Applied Genetics

Hatchett JH, Gallum RL (1970) Genetics of the ability of the Hessian Roberts JJ, Gallum RL (1984) Chromosome location of the H5 gene fy, Mayetiola destructor, to survive on having diferent for resistance to the Hessian fy in wheat. J Hered 75:147–148 genes for resistance. Ann Entomol Soc Am 63:1400–1407 Schwarting HN, Whitworth RJ, Chen MS, Cramer G, Maxwell T He J, Zhao X, Laroche A, Lu Z-X, Liu H, Li Z (2014) Genotyping-by- (2016) Impact of Hessian fy, Mayetiola destructor, on develop- sequencing (GBS), an ultimate marker-assisted selection (MAS) mental aspects of hard red winter wheat in Kansas. Southwest tool to accelerate plant breeding. Front Plant Sci 5:484 Entomol 41:321–329 IWGSC (2018) Shifting the limits in wheat research and breeding using Semagn K, Babu R, Hearne S, Olsen M (2014) Single nucleotide pol- a fully annotated reference genome. Science 361:eaar7191 ymorphism genotyping using Kompetitive Allele Specifc PCR Kong L, Ohm H, Cambron S, Williams C (2005) Molecular mapping (KASP): overview of the technology and its application in crop determines that Hessian fy resistance gene H9 is located on chro- improvement. Mol Breed 33:1–14 mosome 1A of wheat. Plant Breed 124:525–531 Smiley RW, Gourile JA, Whittaker RG, Easley SA, Kidwell KK (2004) Kong L, Cambron SE, Ohm HW (2008) Hessian fy resistance genes Economic impact of Hessian fy (Diptera: cecidomyiidae) on H16 and H17 are mapped to a resistance gene cluster in the distal spring wheat in Oregon and additive yield losses with fusarium region of chromosome 1AS in wheat. Mol Breed 21:183–194 crown rot and lesion nematode. J Econ Entomol 97:397–408 Li CL, Chen MS, Chao SM, Yu JM, Bai GH (2013) Identifcation Spindel J, Wright M, Chen C, Cobb J, Gage J, Harrington S, Lorieux of a novel gene, H34, in wheat using recombinant inbred lines M, Ahmadi N, McCouch S (2013) Bridging the genotyping gap: and single nucleotide polymorphism markers. Theor Appl Genet using genotyping by sequencing (GBS) to add high-density SNP 126:2065–2071 markers and new value to traditional bi-parental mapping and Li GQ, Wang Y, Chen MS, Edae E, Poland J, Akhunov E, Chao SM, breeding populations. Theor Appl Genet 126:2699–2716 Bai GH, Carver BF, Yan LL (2015) Precisely mapping a major Stuart JJ, Chen MS, Shukle R, Harris MO (2012) Gall midges (Hes- gene conferring resistance to Hessian fy in wheat using sian fies) as plant pathogens. Ann Rev Phytopathol 50:339–357 genotyping-by-sequencing. BMC Genom 16:10. https​://doi. Suneson CA, Noble WB (1950) Further diferentiation of genetic fac- org/10.1186/s1286​4-015-1297-7 tors in wheat for resistance to the Hessian fy. US Dept. of Agri- Liu XM, Brown-Guedira GL, Hatchett JH, Owuoche JO, Chen MS culture. Bull. #1004 (2005a) Genetic characterization and molecular mapping of Tan CT, Carver BF, Chen MS, Gu YQ, Yan LL (2013) Genetic a Hessian fy-resistance gene transferred from T. turgidum ssp association of OPR genes with resistance to Hessian fly dicoccum to . Theor Appl Genet 111:1308–1315 in hexaploid wheat. BMC Genom 14:369. https​://doi. Liu XM, Fritz AK, Reese JC, Wilde GE, Gill BS, Chen MS (2005b) org/10.1186/1471-2164-14-369 H9, H10, and H11 compose a cluster of Hessian fy-resistance Tan CT, Yu HJ, Yang Y, Xu XY, Chen MS, Rudd JC, Xue QW, Ibrahim genes in the distal gene-rich region of wheat chromosome 1AS. AMH, Garza L, Wang SC et al (2017) Development and valida- Theor Appl Genet 110:1473–1480 tion of KASP markers for the greenbug resistance gene Gb7 and Liu G, Liu X, Xu Y, Bernardo A, Chen M, Li Y, Niu F, Zhao L, Bai the Hessian fy resistance gene H32 in wheat. Theor Appl Genet GH (2020) Reassign Hessian fy resistance genes, H7 and H8, to 130:1867–1884 chromosomes 6A and 2B of the wheat cultivar ‘Seneca’ using Wang T, Xu SS, Harris MO, Hu JG, Liu LW, Cai XW (2006) Genetic genotyping-by-sequencing. Crop Sci 60:1488–1498 characterization and molecular mapping of Hessian fy resistance McDonald MJ, Ohm HW, Rinehart KD, Giovanini MP, Williams CE genes derived from Aegilops tauschii in synthetic wheat. Theor (2014) H33: A wheat gene providing Hessian fy resistance for the Appl Genet 113:611–618 southeastern United States. Crop Sci 54:2045–2053 Wang S, Basten CJ, Zeng ZB (2012) Windows QTL Cartographer Paux E, Sourdille P, Salse J, Saintenac C, Choulet F, Leroy P, Korol 2.5. Department of Statistics, North Carolina State University, A, Michalak M, Kianian S, Spielmeyer W et al (2008) A physi- Raleigh, NC. http://statg​en.ncsu.edu/qtlca​rt/WQTLC​art.htm. cal map of the 1-Gigabase bread wheat chromosome 3B. Science Accessed 25 June 2020 322:100–104 Wang J, Li H, Zhang L, Meng L (2016) Users’ manual of QTL IciMap- Poland JA, Rife TW (2012) Genotyping-by-sequencing for plant breed- ping. The Quantitative Genetics Group, Institute of Crop Science, ing and genetics. Plant Genome 5:92–102 Chinese Academy of Agricultural Sciences (CAAS), Beijing, Poland JA, Brown PJ, Sorrells ME, Jannink JL (2012) Development China, and Genetic Resources Program, International Maize and of high-density genetic maps for and wheat using a novel Wheat Improvement Center (CIMMYT), Apdo, Mexico two-enzyme genotyping-by-sequencing approach. PLoS ONE Warburton ML, Skovmand B, Mujeeb-Kazi A (2002) The molecular 7:e32253 genetic characterization of the ‘Bobwhite’ bread wheat family Rasheed A, Wen WE, Gao FM, Zhai SN, Jin H, Liu JD, Guo Q, Zhang using AFLPs and the efect of the T1BL.1RS translocation. Theor YJ, Dreisigacker S, Xia XC et al (2016) Development and valida- Appl Genet 104:868–873 tion of KASP assays for genes underpinning key economic traits Zantoko L, Shukle RH (1997) Genetics of virulence in the hessian fy in bread wheat. Theor Appl Genet 129:1843–1860 to resistance gene H13 in wheat. J Hered 88:120–123 Ratclife R, Hatchett J (1997) Biology and genetics of the Hessian fy Zhao HX, Liu XM, Chen MS (2006) H22, a major resistance gene and resistance in wheat. In: Bundari K (ed) New developments in to the Hessian fly (Mayetiola destructor), is mapped to the entomology. Scientifc Information Guild, Trivandrum, pp 47–56 distal region of wheat chromosome 1DS. Theor Appl Genet Ratclife RH, Cambron SE, Flanders KL, Bosque-Perez NA, Clement 113:1491–1496 SL, Ohm HW (2000) Biotype composition of Hessian fy (Dip- tera: Cecidomyiidae) populations from the southeastern, midwest- Publisher’s Note Springer Nature remains neutral with regard to ern, and northwestern United States and virulence to resistance jurisdictional claims in published maps and institutional afliations. genes in wheat. J Econ Entomol 93:1319–1328 Raupp WJ, Amri A, Hatchett JH, Gill BS, Wilson DL, Cox TS (1993) Chromosomal location of Hessian fy-resistance genes H22, H23, and H24 derived from Triticum tauschii in the D genome of wheat. J Hered 84:142–145

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