Quantitative Trait Loci Associated with Resistance to ...

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Quantitative Trait Loci Associated with Resistance to Empoasca in Common Bean Elizabeth I. Brisco, Timothy G. Porch, Perry B. Cregan, and James D. Kelly*

ABSTRACT Empoasca species leafhoppers are a major insect pest of common bean (Phaseolus vulgaris L.), that cause significant economic losses in both tropical (E. kraemeri) and temperate (E. fabae) regions of the Americas. The objective of this study was to use Insertion–Deletion (InDel) and single-nucleotide polymorphism (SNP) markers from the BARCBean6K_3 Beadchip to identify quantitative trait loci (QTL) associated with traits related to leafhopper resistance in common bean. Traits for leaf curl and leaf burn damage, as well as Empoasca spp. nymph counts, were evaluated in an inbred backcross line population (Matterhorn*/EMP507) of beans in temperate (Michigan) and tropical (Puerto Rico) climates. Fourteen QTL associated with resistance to E. fabae and E. kraemeri were identified on five chromosomes explaining up to 66.0% of the phenotypic variation for single resistance traits. A major QTL cluster associated with multiple resistance traits and closely linked to the P color gene was detected for both leafhopper species in multiple seasons under both choice and no-choice treatments on Pv07 (LH7.1, LH7.2, LH7.3), thus validating a similar QTL identified in previous studies. A novel QTL (LH2.2) for E. fabae nymph counts, identified on Pv02 in three seasons, may be associated with antibiosis resistance. Resistance to each leafhopper species appears to be controlled by separate genetic mechanisms in common bean as there was little overlap of QTL regions between species. These QTL could be used to develop beans with leafhopper resistance as an alternative to costly chemical controls while reducing risks to the environment and human health.

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E.I. Brisco, and J.D. Kelly, Dep. of Plant, Soil and Microbial Sciences, Michigan State Univ., 1066 Bogue St., East Lansing, MI 48824; T.G. Porch, USDA-ARS, Tropical Agriculture Research Station, 2200 P. A. Campos Ave., Suite 201, Mayaguez, PR 00680; P.B. Cregan, USDAARS, Soybean Genomics and Improvement Lab., BARC, Beltsville, MD 20705. Received 27 Feb. 2014. *Corresponding author ([email protected]). Abbreviations: G × E, genotype × environment; IBL, inbred backcross line; ICIM-Add, Additive Inclusive Composite Interval Mapping; InDel, Insertion–Deletion; LB, leaf burn; LC, leaf curl; LOD, logarithm of odds; MAS, marker-assisted selection; QTL, quantitative trait locus; RCBD, randomized complete block design; SNP, single-nucleotide polymorphism; SSR, simple sequence repeat; TARS, Tropical Agriculture Research Station; TBE, Tris-Borate EDTA.

C

ommon bean is a staple food crop grown worldwide because it is a widely adapted short-season crop that is an excellent and economical source of protein and other nutrients for many people worldwide (Drewnowski and Rehm, 2013). Beans are commonly grown under low-input agriculture on small farms for direct consumption by its producers (Broughton et al., 2003). These low-input production systems are more likely to suffer from abiotic stresses such as drought (Mukeshimana et al., 2014) and soil fertility issues and therefore are more vulnerable to disease and insect pest outbreaks (Miklas et al., 2006). Potato leaf hopper (Empoasca fabae) is an annual pest of North American bean production east of the Rocky Mountains and is a very important cause of economic loss in temperate regions (Schaafsma et al., 1998). In contrast, E. kraemeri is the most significant insect pest of common bean production in tropical environments and is found year-round in tropical climates of the Americas, including

Published in Crop Sci. 54:2509–2519 (2014). doi: 10.2135/cropsci2014.02.0159 © Crop Science Society of America | 5585 Guilford Rd., Madison, WI 53711 USA All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher. www.crops.org 2509

Colombia and Puerto Rico (Kornegay and Cardona, 1990). Breeding beans for resistance to potato leaf hopper could be a cost-effective alternative to the use of systemic and contact insecticides to control this pest (Gonzales et al., 2004; Singh and Schwartz, 2011). Leaf hoppers cause a specific set of symptoms referred to collectively as “hopperburn” (Backus et al., 2005), which are generally evaluated as leaf curl (LC) and leaf burn (LB). Damage is caused by several distinct feeding behaviors of both adults and nymphs. Kabrick and Backus (1990) identified “lacerate-and-sip” as the most damaging feeding behavior. Lacerate-and-sip involves brief intracellular probes where insect stylets rapidly puncture multiple columns of stem phloem cells simultaneously, causing cell death and abnormal meristematic development (Backus et al., 2005). This pulsing laceration appears to cause systemic vascular damage to the plant, leading to stunting and chlorosis above the point of feeding and resulting in LB damage (Serrano et al., 2000). Empoasca kraemeri feeds by this method more often than E. fabae, which may be related to the higher level of damage generally inflicted by the former (Calderon and Backus, 1992). Both Empoasca species also use two additional feeding tactics that are hypothesized to cause different symptoms described as “lacerate-and-flush” and “lance-and-ingest” (Backus et al., 2005). Lacerate-and-flush, which is thought to lead to LC damage, involves longer intracellular probes that puncture and drain mesophyll and parenchyma cells in the lower surface of the leaf, thereby leading to tissue collapse. Finally, during lance-and-ingest, which may cause stunting but probably causes little damage overall, phloem sieve elements are punctured and leak phloem sap. This sap is ingested while stylets remain motionless, but as stylets are withdrawn, saliva is released, causing cells on the upper surface of the leaf to expand considerably (Backus et al., 2005). The plant response to these behaviors is believed to be controlled by different genetic loci, which has been confirmed by the presence of separate QTL controlling LC and LB reactions (Murray et al., 2004b). Numbers of E. fabae adults and nymphs were positively associated with both LC damage and plant height, but this correlation was not observed with E. kraemeri (Murray et al., 2004a). As a result of early-season severe infestation, bean plant growth is stunted and delayed (Backus et al., 2005), leading to dramatic yield reductions and subsequent economic losses. Severe attacks during the plant reproductive stages can result in high levels of flower and pod abortion as well as in the development of twisted and curved pods, each with few seeds, often of poor quality (Kornegay and Cardona, 1990). Crop yield losses will be affected by the density, duration, and initial timing of leaf hopper infestation as well as temperature, plant disease incidence, and interactions of any of the above (Lindgren and Coyne, 1995). In Nebraska, E. fabae damage resulted in estimated 2510

dry-bean yield losses of up to 20%, valued at US $2 million (Gonzales et al., 2002). The tropical counterpart, E. kraemeri, can be especially devastating. In Latin America, dry bean yield losses are estimated at up to 64% (Gonzales et al., 2002) and in Colombia, specifically, losses of up to 79% have been recorded (Bullas-Appleton et al., 2005). Potato leaf hoppers prefer hot, dry conditions and, as a result, populations flourish and damage is more severe in hotter, drier seasons than during cooler, wetter seasons. Currently, potato leaf hopper is managed using pesticides, which are often prohibitively expensive in many parts of the developing world and pose environmental and health risks (Murray et al., 2004a). The objective of this study was to identify QTL controlling Empoasca species feeding damage responses and related traits in a cross between ‘Matterhorn’, a commercial great northern cultivar, and ‘EMP 507’, a tropical carioca germplasm line that was developed for resistance to E. kraemeri. Phenotypic characterization of the parents and the inbred backcross line (IBL) population for leaf curl, leaf burn, and nymph counts was performed in the field under choice and no-choice conditions in Michigan and Puerto Rico. Phenotypic data were used to conduct QTL analysis for all traits using simple sequence repeat (SSR), InDel, and SNP markers.

MATERIALS AND METHODS Plant Material

The P. vulgaris population examined in this study was developed from the single cross Matterhorn/EMP 507 followed by a single backcross to Matterhorn to create an IBL population, Matterhorn */EMP 507, consisting of 75 BC1F4:8 individuals. Matterhorn is a high-yielding commercially-available great northern cultivar developed in Michigan with quality seed and agronomic characteristics (Kelly et al., 1999). EMP 507 is a carioca germplasm line developed at the Centro International de Agricultura Tropical (Kornegay and Cardona, 1990) as part of a long-term recurrent selection program designed to enhance resistance to E. kraemeri (Schaafsma et al., 1998). While the EMP lines were originally developed to be resistant to E. kraemeri, Schaafsma et al. (1998) demonstrated that the resistance is maintained under severe pressure to the temperate species E. fabae. An IBL population was created to generate a higher frequency of lines that would resemble the recurrent parent, Matterhorn, in seed, agronomic, and performance traits, as EMP 507 lacks adaptive traits for production in a temperate environment. Both parental genotypes have a type II growth habit, as defined by Singh (1982). The crosses resulting in the IBL population were made at the USDA-ARS-Tropical Agriculture Research Station (TARS), in Mayaguez, PR. The F1 was made in the greenhouse in 2005 and the BC1F1 backcross generation made in 2006 was selfed and advanced using single seed descent at the same location until the BC1F4 generation. BC1F4 seed was increased in 2008 and 2009 in the greenhouse and in the field in East Lansing, MI until sufficient quantities were obtained for field

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screening. Individual IBL were coded with G08 prefix if they possessed white great northern seed type or with P08 prefix if they possessed colored pinto bean seed type.

Field Screening Empoasca-resistance screening was initiated in the summer of 2009. Open-choice tests were conducted at the Crop and Soil Science Research Farm at Michigan State University, East Lansing and at the USDA-ARS-TARS in Isabela, PR. Three replications were planted each year in Michigan from 2009 to 2011 in a randomized complete block design (RCBD) of 5.4-m long single-row plots. Individual plots were spaced 50 cm apart and consisted of up to 80 plants per plot. Five replications were planted in December 2009 and January 2011 in Puerto Rico in a RCBD of 1.8-m long single-row plots. Individual plots were spaced 90 cm apart and consisted of up to 30 plants per plot. Empoasca species were allowed to infest each field test. In each location, nymphs of Empoasca species present on three randomly selected trifoliate leaves, on each of three randomly selected plants per plot, were counted at the flowering stage. The plants were evaluated for LC and LB at physiological maturity using a damage scale from 0 to 5 as described by Murray et al. (2001), where 0 = no visible damage and 5 = severe damage. Damage scores were assigned as an average of the overall plot. No-choice tests were conducted in the field in three trials in Michigan from 2009 to 2011 with a single replication evaluated each year. In the no-choice tests, approximately 90 by 30-cm cages were placed over plots following germination and thinned to five plants per cage. Leaf hoppers were raised in growth chambers on fava bean (Vicia faba L.) plants at 25°C and 12 h dark–light and collected via an aspirator into individual 25-mL vials that were deposited into each cage. Additional leaf hoppers were collected each season from alfalfa (Medicago sativa L.) fields when necessary. Cages were artificially infested with E. fabae adults at current industry economic threshold rates (one adult leaf hopper per trifoliate) at the third trifoliate stage. Cages were removed when plants had achieved physiological maturity and plants were evaluated for LC and LB using the same damage scale from 0 to 5 as described by Murray et al. (2001).

Molecular Marker and Linkage Analysis The Matterhorn*/EMP 507 IBL population and parents were grown in the greenhouse and young trifoliate leaves from three to four individuals per genotype were collected for DNA extraction. Total genomic DNA was extracted from leaf samples following a modified CTAB protocol (Haley et al., 1994). Isolated DNA was quantified using a flurometer (Hoeffer DyNA Quant 200, San Francisco, CA) and diluted to a working concentration of 40ng l1 for polymerase chain reactions (PCR). The DNA was stored at 20°C. The DNA from parents and IBLs were screened for polymorphic markers, including SSRs, InDels (Moghaddam et al., 2013), and SNPs (Hyten et al., 2010). Single-nucleotide polymorphism genotyping was conducted using the BARCBean6K_3 SNP array (www.BeanCap.org, accessed 27 Aug. 2014) according to the manufacturer’s instructions for the Illumina Infinium assay. Single-nucleotide polymorphism calling was conducted using the genotyping module of V2011.1 GenomeStudio software (Illumina Inc., San Diego, CA). In crop science, vol. 54, november– december 2014

total, 369 SSRs and 152 InDels were screened for polymorphisms between the parental genotypes. Simple sequence repeat marker amplification was conducted using the following PCR reaction for each genotype: 1.0 L DNA [40 ng l1], 1.0 L of (2 mM) primer, 0.2 L (1U) of Taq polymerase, 0.6 L (50 mM) MgCl 2, 2.0 L (10x) PCR buffer, 0.8 L of a 5 mM mix of dNTPs, and 14.4 L sterile distilled water. A PCR was performed using a 96-well PTC-100 Programmable Thermal Controller (MJ Research Inc., Waltham, MA) programmed for 1 cycle of 5 min at 94°C, followed by 30 cycles of 1 min at 94°C, 1 min at 47°C, and 1 min at 72°C, and then a final extension was conducted at 72°C for 5 min. To each PCR product, 8 L of formaldehyde loading buffer was added. Five l of each mixed product was loaded onto a 6% acrylamide gel and separated via electrophoresis at a constant power of 300 W for approximately 3 h in 0.5% Tris-Borate EDTA (TBE) buffer. The PCR products were visualized using the following staining protocol: fixed in solution composed of 210 mL of 95% ethanol, 10 mL of acetic acid, and 1780 mL of distilled water for 5 min, followed by a staining solution of 2 g of silver nitrate, 3 mL of formaldehyde, and 2 L of distilled water for 7 min and developed in a solution of 3 mL of formaldehyde, 30 g of sodium hydroxide, and 2 L of distilled water until bands appeared. InDel markers were amplified using the following PCR reaction for each genotype: 1 L DNA (40 ng L1), 2 L each of the forward and reverse primers, 10 L of GoTaq Master Mix (Promega Corp., Madison, WI), and 5 L of distilled water. A PCR was performed using a 96-well PTC-100 Programmable Thermal Controller (MJ Research Inc., Waltham, MA) programmed for 1 cycle at 95°C for 3 min; 45 cycles of 95°C for 20 s, 55°C for 30 s, and 72°C for 1 min; and a final extension cycle at 72°C for 10 min. From each PCR product, 5 L was loaded on a 3% TBE agarose gel and separated by electrophoresis at a constant voltage of 100 V. The PCR products were subsequently visualized under ultraviolet light after staining with ethidium bromide.

Data Analysis and Linkage Map Construction Analysis of variance for all traits by year and location was performed using PROC GLM (general linear model) mixed model of SAS version 9.3 (SAS Institute Inc., 2012). Linkage analysis was performed on genotypic data using QTL IciMapping Version 3.2 (Wang et al., 2012). The Kosambi mapping function was used, which assumes the existence of interference that is negatively related to recombination frequency. The SSR markers were anchored to linkage groups on the basis of previous assignments on the common bean core map (Blair et al., 2003; Galeano et al., 2011). Seed coat color was also included in the analysis as a phenotypic marker (P locus) on Pv07. Grouping, ordering, and rippling functions in QTL IciMapping were conducted to divide the 628 markers into linkage groups, determine marker order, and calculate the relative map positions. The logarithm of odds (LOD) threshold was set to a minimum of 3.0 to group markers into linkage groups and the nearest neighbor algorithm (nnTwoOpt) was used to order the markers in the linkage groups using a three-step procedure outlined in Wang et al. (2012). Rippling was conducted using the sum of adjacent recombination frequencies with a window size of 5.0 cM. Linkage groups were designated according to

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Table 1. Phenotypic means, ranges, and heritability for Empoasca species resistance traits (leaf curl, leaf burn, and leafhopper nymph counts) from a Matterhorn*/EMP 507 inbred backcross line population of 75 BC1F4:8 individuals and checks combined across 3 yr (2009–2011) in Michigan and 2 yr (2010–2011) in Puerto Rico. Parents Traits

Matterhorn

Michigan—Empoasca fabae Leaf curl Leaf burn Nymph counts No-choice leaf curl No-choice leaf burn † ‡

Checks‡

EMP507

Mean

Range

LSD (0.05)

h2†

EMP509

Othello

2.09 1.43

1.74 1.45 1.03

2.54 2.43 1.44

1.58– 4.11 1.11– 3.78 0.33– 3.10

0.63 0.91 1.69

0.77 0.74 0.13

1.49 1.11 0.73

3.56 3.61 1.20

2.44 0.44 4.04 1.67 1.33

1.22 0.11 3.93 1.67 0.33

2.16 0.65 4.53 2.17 1.78

1.11– 3.22 0.00– 2.40 1.63– 7.70 0.67– 3.33 0.33– 3.57

0.84 0.78 2.81 1.00 1.79

0.82 0.68 0.69 0.67 0.53

1.33 0.22 3.34 1.67 1.00

SB 4.17 2.83 8.11 5.00 5.00

Puerto Rico—Empoasca kraemeri Leaf curl§ 2.60 Leaf burn § Nymph counts¶

Inbred backcross lines

h2, narrow sense heritability. EMP509: resistant check; Othello and SB (Swedish Brown): susceptible checks.

§

Plants were evaluated for leaf curl and leaf burn at physiological maturity using a damage scale from 0 to 5, where 0 = no visible damage and 5 = severe damage, and damage scores were averaged for the overall plot (Murray et al., 2001) Leaf burn data were not recorded in Puerto Rico in 2010

¶

Nymphs of Empoasca species present on three randomly selected trifoliate leaves, on each of three randomly selected plants per plot, were counted at the flowering stage.

Pedrosa-Harand et al. (2008). Segregation distortion of molecular markers was analyzed using the SDL protocol of the QTL IciMapping Version 3.2 (Wang et al., 2012).

Quantitative Trait Locus Analysis Quantitative trait locus analysis was performed using the trait mean for each IBL combined across all seasons in Michigan or Puerto Rico and separately for each environment in each year. Quantitative trait locus IciMapping Software Version 3.2 was used to identify QTL for LC, LB, and nymph counts in choice tests and LC and LB in no-choice tests using the Biparental Population protocol. The Additive Inclusive Composite Interval Mapping (ICIM-Add) function was set to a window size of 1.0 with a probability in stepwise regression of 0.001. The LOD threshold was determined through completing 1000 permutations of ICIM-Add with the Type I Error level set at  = 0.05. Linkage maps and QTL were visualized using MapChart v2.2 (Voorrips, 2002). The QTL identified in this study were named according to the guidelines established by the Bean Improvement Cooperative (Miklas and Porch, 2010).

RESULTS

Phenotypic Data Mean squares were significant for genotype effects and environment effects for all leaf hopper damage traits measured in both choice and no-choice tests in Michigan and Puerto Rico ( = 0.05). Significant genotype × environment (G × E) interaction was evident in choice tests when traits were combined across locations. However, G × E interactions were not significant for nymph counts in either Puerto Rico or Michigan. No significant G × E effects were seen for LC or LB under no-choice test conditions. Transgressive segregation was evident for all traits (Table 1) with nearly normal distributions for most traits in both locations (Fig. 1). 2512

Feeding Damage The combined means for LB and LC damage in each study location are summarized in Table 1. The combined mean LC score for the 75 IBLs in Puerto Rico in 2010 to 2011 was 2.54, with individual IBLs ranging from a low of 1.58 to a high of 4.11. Under choice test conditions, LC scores in Michigan averaged 2.16 across the 75 IBLs over three seasons, with individual IBL damage ranging from a low of 1.11 to a high of 3.22. In Puerto Rico, LB scores for individual IBLs ranged from 1.11 to 3.78 with a mean value of 2.43. Leaf burn damage was only recorded in 2011 because of the presence of common bacterial blight disease, caused by Xanthomonas axonopodis, in the 2010 Puerto Rico field season. The LB scores in Michigan ranged from 0.00 to 2.40 for the IBLs, with a mean value of 0.65 from 2009 to 2011. The resistant check EMP509 produced reactions similar to the resistant parent for LC and LB measured at both locations whereas the susceptible checks had higher ratings than the Matterhorn parent, particularly under the no-choice treatment in Michigan. Narrow sense heritability (h2) values were high for feeding damage traits in both locations (Table 1). Leaf curl heritability was estimated at 0.77 in Puerto Rico and 0.82 in Michigan. Leaf burn heritability estimates were 0.74 in Puerto Rico and 0.68 in Michigan. No-choice test heritability estimates were lower for both LC and LB when compared with choice-test results in Michigan. A number of individuals from the population were identified as consistently having low LC and LB scores across seasons and locations. P08142 and P08175 demonstrated low LC and LB damage to both E. kraemeri and E. fabae in multiple seasons. P08104, G08128, G08134, and P08151 showed high levels of resistance to LC and LB damage associated with E. kraemeri while P08125, P08150,

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Table 2. Spearman Rank Correlations for Empoasca species resistance traits (leaf curl, leaf burn, and leafhopper nymph counts) from a Matterhorn*/EMP 507 inbred backcross line population of 75 BC1F4:8 individuals grown in Michigan (MI) in 2009 to 2011 and in Puerto Rico in 2010 to 2011. Michigan (E. fabae) Trait Leaf curl Leaf burn Leaf curl (MI)

Leaf burn

Nymph counts

0.68***

0.46*** 0.48***

Puerto Rico (E. kraemeri) Leaf curl

Leaf burn†

Nymph counts

0.51***

0.23*** 0.08ns

0.48***

*** Significant at 0.001 probability level †

Leaf burn data were not recorded in PR in 2010.

1.63 to 7.70 (Table 1). Nymph counts of E. fabae were much higher on susceptible check than on the Matterhorn parent. In contrast to the high h2 estimates of LC and LB, E. kraemeri nymph counts had very low heritability (0.13). Empoasca fabae nymph count h2 was similar to LB at 0.69. Of the individuals identified as having high levels of resistance to E. fabae damage, P08153 also had the lowest mean nymph count across all years in Michigan and ranked in the lowest three IBLs in each season. P08172 and P08169 also had consistently low E. fabae nymph counts. Trait correlations varied between tests (Table 2). When examined in each location, LC was highly correlated with LB but nymph counts were only correlated with LC in Michigan. This indicates that as leaf hopper populations increase, feeding damage also increases as expected. The lack of correlation between nymph counts and LB in Puerto Rico may result from the high LB values in Puerto Rico due to the feeding habit of the E. kraemeri species. When examined on a trait basis, only LC was correlated between Michigan and Puerto Rico (Table 2).

Linkage Mapping Figure 1. Distribution of leaf curl (LC), leaf burn (LB), and number of Empoasca species nymphs per plant (LH) means of a Matterhorn*/EMP 507inbred backcross line population of 75 BC1F4:8 individuals combined across 3 yr (2009–2011) in Michigan and 2 yr (2010–2011) in Puerto Rico.

P08153, G08160, and P08166 showed high levels of resistance to both LC and LB damage associated with E. fabae. Additional IBLs were identified as having consistently low scores for single damage traits for each leafhopper species. Nymph Counts High levels of variation were detected for nymph counts between the two leaf hopper species. In Puerto Rico, the 75 IBLs averaged counts of 1.44 E. kraemeri nymphs per plant with individuals ranging from 0.33 to 3.10 nymphs. In Michigan, the IBL population averaged 4.53 E. fabae nymphs per plant with individual means ranging from crop science, vol. 54, november– december 2014

A total of 627 molecular markers and one phenotypic marker were mapped using IciMapping software including 63 SSRs, 41 InDels, and 523 SNP markers. The parents along with IBLs were genotyped using 6K SNP bean chip, which contained a total of 5398 bead-types following protocols previously described by Mukeshimana et al. (2014). Among these, 904 SNPs were polymorphic between parents. Using IciMapping, a total of 380 SNP markers with segregation distortion at 0.05 probability level were excluded. A final total of 523 SNP markers were mapped in the Matterhorn*/EMP 507 IBL population. The SNP marker order and location in the map generally agreed with order and chromosome assignment in the Stampede–Red Hawk common bean map (Schmutz et al., 2014). The eleven linkage groups yielded a total map length of 1481.5 cM, indicative of near complete coverage of the bean genome (Table 3). Each linkage group represented a single chromosome. The number of markers per linkage group ranged from 15 on Pv01 to 129

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Table 3. Molecular marker distribution and distance on individual chromosomes of the genetic linkage map of Matterhorn*/EMP 507 inbred backcross line population of 75 BC1F4:8 individuals. Chromosome Pv01 Pv02 Pv03 Pv04 Pv05 Pv06 Pv07 Pv08 Pv09 Pv10 Pv11 Entire genome

Number of Markers 15 73 56 21 56 49 107 129 22 24 75 627

Length

Average distance between markers

———————— cM ———————— 86.8 5.8 97.6 1.3 203.4 3.6 292.7 13.9 155.9 2.8 148.3 3.0 128.4 1.2 141.6 1.1 110.8 5.0 35.7 1.5 80.3 1.1 1481.5 2.4

on Pv08, with 2.4 cM as the average distance between markers across the entire genome.

Quantitative Trait Locus Analysis Inclusive composite interval mapping identified a total of 14 QTL on five chromosomes associated with resistance to E. fabae and E. kraemeri (Fig. 2). Seven QTL on four chromosomes are associated with resistance to E. fabae (Table 4) and eight QTL on four chromosomes are associated with resistance to E. kraemeri (Table 5). Quantitative trait loci for combined means of each trait within a location explained 11.0 to 66.0% of the phenotypic variation. The number of QTL for a single trait ranged from one (nymph counts) to four (leaf curl) under choice conditions for E. fabae and one (leaf burn) to seven (leaf curl) for traits associated with E. kraemeri. Quantitative trait locus detection varied between years and locations. Certain QTL associated with the same trait in different years colocalized to similar genetic regions, while others were only detected in a single year and/or location. Leaf Curl Quantitative trait loci linked to leaf curl damage associated with E. fabae leaf hoppers in choice tests were detected on Pv03, Pv07, and Pv08, explaining 12.0 to 29.4% of the phenotypic variation in Michigan in a single year (Table 4). LH3.2 was only detected in the combined analysis and is located between markers NDSU_IND_3_0.7964 and NDSU_IND_3_9.5314, explaining 12.7% of the phenotypic variation with an additive effect of 0.24. LH7.1 was detected in 2009 and 2011 and in the combined analysis between flanking markers NDSU_IND_7_49.1648 and ss715643412, with R 2 values ranging from 12.0 to 20.4%. On Pv08, QTL LH8.2 was detected in the combined analysis between flanking SNP markers ss715641168 and 2514

ss715640448, explaining 14.3% of the phenotypic variation. Together, QTL associated with E. fabae LC damage explained a total of 47.4% of the phenotypic variation in the combined analysis. Under no-choice conditions, a significant QTL associated with E. fabae-related leaf curl damage was detected on Pv07 between flanking markers NDSU_IND_7_40.0590 and ss715642939, with R 2 values of 29.4% in 2009 and 22.2% in the combined analysis with additive effects of 0.40 and 0.42, respectively, on a damage scale of 0 to 5 and between flanking markers 149M2.120 and ss715641884 in 2011, with an R 2 value of 24.5% and an additive effect of 0.38. Quantitative trait loci for leaf curl damage associated with E. kraemeri were detected on Pv03, Pv06, Pv07, and Pv08 with R 2 values ranging from 10.5 to 25.9% in a single year in Puerto Rico (Table 5). Additive effects ranged from 0.24 to 0.46 out of a damage scale of 0 to 5. LH3.3 was detected between flanking markers BM159 and ss715641429 and explained 14.5% of the phenotypic variation in 2011 and had an additive effect of 0.24. Quantitative trait loci were detected on Pv06 between flanking markers ss715641715 and ss715643653 in both 2010 and in the combined analysis (LH6.2) and between BM3 and ss715642167 in 2010 (LH6.3). LH6.2 explained 23.4% of the phenotypic variation in 2010 and 16.0% in the combined analysis, with additive effects of 0.38 and 0.25, respectively. LH6.3 explained 10.5% of the phenotypic variation with an additive effect of 0.25. In 2011, LH7.3, detected between flanking markers ss715640346 and ss715642940, explained 20.9% of the phenotypic variation with an additive effect of 0.51 and explained 11.0% of the phenotypic variation in the combined analysis. LH8.1, between ss715643997 and PVBR218.185 with an R 2 value of 17.5% and an additive effect of 0.39, was only detected in 2011. LH8.2 was detected between ss715641168 and ss715640448 with an R 2 value of 11.9% and an additive effect of 0.46. LH8.3 was detected between markers ss715641465 and NDSU_IND_8_1.7681 in the combined analysis and between NDSU_IND_8_1.7681 and ss715641113 in 2011. It explained 19.1% of the phenotypic variation in the combined analysis and 25.9% in 2011. Additive effects for LH8.3 were 0.30 and 0.34, respectively, for the combined analysis and for 2011. In total, QTL associated with E. kraemeri LC damage explained 46.1% of the phenotypic variation in the combined analysis. Leaf Burn A single QTL linked to leaf burn damage associated with E. fabae leaf hoppers in choice tests was detected on Pv02 between flanking markers ss715642315 and NDSU_IND_2_22.9034, explaining 33.4% of the phenotypic variation in 2009 in Michigan with an additive effect of 0.50. Under no-choice conditions, an additional QTL was detected in 2009 on Pv03 for leaf burn damage

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Figure 2. The chromosomal location of quantitative trait loci (QTL) associated with resistance to Empoasca species leafhoppers identified in a Matterhorn*/EMP 507 inbred backcross line population of 75 BC1F4:8 individuals grown in Michigan in 2009 to 2011 and in Puerto Rico in 2010 to 2011; leafhopper (LH) QTL are identified in Table 4 and Table 5.

associated with E. fabae and with an R 2 value of 28.0% and an additive effect of 0.87 (Table 4). A single QTL for leaf burn damage associated with E. kraemeri was detected in 2011 on Pv06 between flanking markers ss715640880 and ss715642628 explaining 12.4% of the phenotypic variation and with an additive effect of 0.22 (Table 5). Nymph Counts Chromosome Pv02 possessed significant QTL with significant LOD scores associated with E. fabae nymph counts located between InDel marker NDSU_IND_2_12.8147 and SNP marker ss715644946. QTL LH2.2 was detected in every season (2009–2011) when each season–year was analyzed individually, as well as in the combined analysis across 3 yr. The R 2 values ranged from 22.4% in 2010 to 56.8% in 2009 and were 66.0% in the combined analysis. Additive effects contributing to resistance were attributed to the donor parent EMP 507 resulting in reductions in nymph counts ranged from 0.5 nymphs per plant in 2010 to 2.0 nymphs per plant in 2009.

DISCUSSION

Phenotypic Evaluation By evaluating the IBL population in Michigan and Puerto Rico for a combined five seasons, it was possible to evaluate these genotypes under diverse growing conditions as well as to test them against two different leaf hopper species, E. crop science, vol. 54, november– december 2014

kraemeri and E. fabae. Michigan represents a temperate climate with long days and short nights, while Puerto Rico represents a tropical climate with short days. While the different species presented a challenge in identifying lines with consistent reactions to leaf hopper predation in both climates, this challenge presented an opportunity to separate out the different components involved in resistance to each species of Empoasca leaf hoppers. Heritability estimates varied largely between feeding damage traits and nymph counts (Table 1). The low h2 for nymph counts in Puerto Rico suggests this may not be a useful measure of resistance to E. kraemeri, but the moderate heritability estimate of nymph counts in Michigan indicates this is a valid measure of E. fabae reaction. Heritability estimates were moderate to high in both locations for LC and LB, supporting their usefulness in evaluating leaf hopper damage in this population. These results confirm that breeding for resistance to leaf hopper feeding damage can be successfully undertaken by screening and selecting material with lower levels of LC or LB damage in replicated field trials. The lack of correlation between damage scores across locations suggests that resistance is not controlled by the same host loci across Empoasca species. The closely related E. kraemeri and E. fabae species have been documented as having different feeding strategies and therefore cause quite different plant responses (Backus et al., 2005). In addition, the presentation of damage symptoms may also be affected by environmental factors, as demonstrated

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Combined 2009 Combined 2011 2011 Combined 2009 Combined

2009 2009

Combined 2009 2010 2011

LH3.2 LH7.1

LH8.2

LH2.1 LH3.1

LH2.2

Confidence interval§

56.8 22.4 46.7

66.0

33.4 28.0

12.7 12.0 20.4 19.5 24.5 22.2 29.4 14.3

0.24

1.18 1.97 0.49 1.09

0.50 0.87

0.35

0.19 0.30 0.45 0.38 0.42 0.40

Proportion of the phenotypic variance explained by the QTL at peak LOD using inclusive composite interval mapping.

Additivity is the effect of substituting a single allele from one parent for another. Positive values indicate allele originates from Matterhorn. Negative values indicate allele originates from EMP507.

‡‡

LOD, logarithm of odds; log of likelihood ratio statistic at p = 0.05.

††

#

Primer information for markers available online. Simple sequence repeats: http://bic.css.msu.edu/_pdf/Bean_SSR_Primers_2007.pdf (accessed xx Mon. xxxx); North Dakota State University (NSDU) Insertion–Deletion markers: http://www.beancap.org/Research.cfm (accessed 29 Aug. 2014).

4.2 5.1 3.3 3.2

3.7 3.2

2.9 2.9 2.9 3.2 3.1 3.0 2.9 2.9

Add‡‡

Confidence intervals were estimated using a 1-LOD support interval value as described by van Ooijen (1992)

.

15.8 12.3 3.8 9.0

NDSU_IND_2_12.8147-ss715644946 NDSU_IND_2_12.8147-ss715644946 NDSU_IND_2_12.8147-ss715644946 ss715641941-NDSU_IND_2_12.8147

5.4 4.7

ss715642315-NDSU_IND_2_22.9034 FJ18-PVBR255

4.6 29.0 7.2 3.4 3.7 6.2 3.1 4.6

%

R2 ††

¶

Leaf burn ss715642315 FJ18 Nypmh counts NDSU_IND_2_12.8147 NDSU_IND_2_12.8147 NDSU_IND_2_12.8147 NDSU_IND_2_12.8147

NDSU_IND_3_0.7964-NDSU_IND_3_9.5314 NDSU_IND_7_49.1648-ss715643412 NDSU_IND_7_49.1648-ss715643412 NDSU_IND_7_49.1648-ss715643412 149M2.120-ss715641884 NDSU_IND_7_40.0590-ss715642939 NDSU_IND_7_40.0590-ss715642939 ss715641168-ss715640448

Leaf curl NDSU_IND_3_9.5314 NDSU_IND_7_35.8798 NDSU_IND_7_35.8798 ss715643412 ss715641884 NDSU_IND_7_40.0590 NDSU_IND_7_40.0590 ss715641168

LOD LOD score# threshold

QTL map position was determined on the basis of the genetic linkage map constructed in the present study.

64.2–93.8 67.7–90.3 76.2–81.8 70.0–86.0

40.6–49.4 0–5.7

135.4–142.6 2.0–58.0 23.8–36.2 28.6–33.4 37.3–42.7 35.8–46.2 38.9–43.1 91.4–98.6

Marker interval for QTL position

Nearest marker ¶

§

79 79 78

79

45 2

139 30 30 31 40 41 41 95

————— cM —————

QTL peak‡ position

QTL names according to the guidelines established by Miklas and Porch, 2010.

Pv02 Pv02 Pv02

Pv02

Pv02 Pv03

Pv03 Pv07 Pv07 Pv07 Pv07 Pv07 Pv07 Pv08

Chromosome

‡

Choice Choice Choice

Choice

Choice No-choice

Choice Choice Choice Choice No-choice No-choice No-choice Choice

Treatment

†

LH7.2

Year

QTL†

Table 4. Putative quantitative trait loci (QTL) for Empoasca fabae resistance traits identified in combined and individual environments from 75 inbred backcross lines developed from a cross Matterhorn*/EMP 507and evaluated in Michigan in 2009 to 2011.

by the higher LB values under nochoice conditions where temperature and humidity were elevated within the field cages. When the IBL means from each location were compared with the parental means for LC, LB, and nymph counts, in all cases the LC mean value for the Matterhorn*/EMP 507 population fell between the values of the two parents (Table 1). However, in all cases, the IBL means for LB and nymph counts were greater than the range of the parent values. This suggests that Matterhorn may have some levels of resistance to LB damage and nymph counts but not to LC damage. This is not surprising as Matterhorn had lower scores than the susceptible checks and the pedigree of Matterhorn (Kelly et al., 1999) includes Sierra, a pinto bean cultivar that has demonstrated resistance to E. fabae (Gonzales et al., 2004). The IBLs having lower damage scores than the resistant parent may have inherited resistant alleles from the recurrent parent which are not normally expressed in the genetic background of Matterhorn.

Genetic Mapping and Quantitative Trait Locus Analysis

All traits associated with resistance to both E. fabae and E. kraemeri followed normal or near normal distributions (Fig. 1), indicative of quantitative inheritance of these traits. The number of QTL per linkage group varied from two to three, with clusters of two or more QTLs occurring on two linkage groups, as is often the case with resistance genes clustering in the genome (Kelly et al., 2003). Significant QTL associated with resistance to E. fabae that were detected in multiple seasons and explained > 20% of the phenotypic variation were located on Pv02 (LH2.2) and Pv07 (LH7.1, LH7.2), with additional QTL that were detected in a single season located on Pv02 (LH2.1), Pv03 (LH3.1, LH3.2),


Proportion of the phenotypic variance explained by the QTL at peak LOD using inclusive composite interval mapping.

LOD, logarithm of odds; log of likelihood ratio statistic at p = 0.05. #

Additivity is the effect of substituting a single allele from one parent for another. Positive values indicate allele originates from Matterhorn. Negative values indicate allele originates from EMP507.

Primer information for markers available online. Simple sequence repeats: http://bic.css.msu.edu/_pdf/Bean_SSR_Primers_2007.pdf (accessed 29 Aug. 2014); North Dakota State University (NSDU) Insertion–Deletion markers: http://www.beancap.org/Research.cfm (accessed 29 Aug. 2014). ¶

‡‡

Confidence intervals were estimated using a 1-LOD support interval value as described by van Ooijen (1992). §

QTL names according to the guidelines established by Miklas and Porch, 2010.

††

QTL map position was determined on the basis of the genetic linkage map constructed in the present study. ‡

0.22 12.4 3.0 4.0 ss715640880-ss715642628 2011

LH8.1 LH8.2 LH8.3

LH6.3 LH7.3

LH6.1

Choice

Pv06

108

105.0–111.0

Leaf burn ss715642628

6.0 5.9 4.6 3.4 8.9 3.8 5.1 3.1 5.9 8.0 BM159-ss715641429 ss715641715-ss715643653 ss715641715-ss715643653 BM3-ss715642167 ss715640346-ss715642940 ss715640346-ss715642940 ss715643997-PVBR218.185 ss715641168-ss715640448 ss715641465-NDSU_IND_8_1.7681 NDSU_IND_8_1.7681-ss715641113 Choice Choice Choice Choice Choice Choice Choice Choice Choice Choice

Pv03 Pv06 Pv06 Pv06 Pv07 Pv07 Pv08 Pv08 Pv08 Pv08

161 73 73 137 51 51 46 99 116 122

156.0–166.0 68.1–77.9 69.4–76.6 134.6–139.4 43.1–58.9 48.2–53.8 41.9–50.1 96.9–101.1 111.1–120.9 115.0–129.0

Leaf curl BM159 ss715641715 ss715641715 BM3 ss715642940 ss715642940 ss715643997 ss715641168 ss715641465 NDSU_IND_8_1.7681 2011 2010 Combined 2010 2011 Combined 2011 2010 Combined 2011

————— cM —————

LH3.3 LH6.2

†

0.39 0.46 0.30 0.34

4.2 3.1 3.3 3.1 4.2 3.3 4.2 3.1 3.3 4.2

14.5 23.4 16.0 10.5 20.9 11.0 17.5 11.9 19.1 25.9

%

0.24 0.38 0.25 0.25 0.51 0.27

Add‡‡ R2†† LOD threshold LOD score# Marker interval for QTL position Nearest marker ¶ Confidence interval§ QTL peak ‡ position Chromosome Treatment Year QTL†

Table 5. Putative quantitative trait loci (QTL) for Empoasca kraemeri resistance traits identified in combined and individual environments from 75 inbred backcross lines developed from a cross Matterhorn*/EMP 507 and evaluated in Puerto Rico in 2009 to 2011.


and Pv08 (LH8.2). The QTL associated with resistance to E. kraemeri were predominantly located on Pv06 (LH6.1, LH6.2, LH6.3) and on Pv08 (LH8.1, LH 8.2, LH 8.3). QTL on Pv07 associated with resistance to E. fabae under both choice (LH7.1) and no-choice (LH7.2) conditions clustered with QTL (LH7.3) associated with LC resistance to E. kraemeri. These findings suggest that LB may be difficult to detect under field conditions and/or may be subject to strong environmental interactions, as suggested by the field data and low heritability estimates for this trait. Pv06 contains QTL predominantly associated with E. kraemeri feeding damage. LH6.1, LH6.2, and LH6.3 are all derived from recurrent parent Matterhorn alleles and include resistance to both LB (LH6.1) and LC (LH6.2, LH6.3) damage. This suggests that Matterhorn may contain novel resistance to E. kraemeri that is not currently being exploited in tropical germplasm. However, the QTL associated with E. kraemeri damage and detected on Pv08 are derived from EMP 507 alleles. This finding suggests there are beneficial effects originating from both parents that interact to reduce damage as a result of E. kraemeri feeding. Pv07 contains the largest group of QTL associated with LC resistance. All three QTL in this cluster are associated with alleles from recurrent parent Matterhorn. The close proximity of related traits suggests a cluster of resistance genes associated with lacerate-and-flush feeding damage, a feeding strategy used by both Empoasca leafhopper species and believed to cause LC damage. LH7.1 and LH7.3 may be associated with antixenosis resistance strategies as they were detected under choice test conditions only, while LH7.2 may be associated with antibiosis resistance as it was only detected under no-choice conditions. Previous studies identified a significant QTL for both E. fabae and E. kraemeri damage symptoms on Pv07, linked closely to the P locus associated with seed coat color (Murray et al., 2004b). Our findings suggest that with the increased marker saturation of the genetic map, there are in fact three separate loci that may be linked to the P locus. The colocalization of LH7.1, LH7.2, and LH 7.3 with the P gene for seed coat color and the similar association with resistance traits for both species assist in confirmation of these QTL as occurring at the same locus. Having many QTL colocalized to the same position within the linkage group could indicate multiple tightly linked loci or a single locus with pleiotropic effects (Hittalmani et al., 2002). The P gene

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may be involved in resistance mechanisms as it has been linked to other disease resistance QTL on Pv07, including a recent study that linked the P gene to resistance to multiple strains of white mold (causal agent: Sclerotinia sclerotiorum, Perez-Vega et al., 2012). In addition, other color alleles have been linked to disease resistance, including tight linkage of the B allele with the I gene to confer Bean common mosaic virus resistance on Pv02 and the V locus on Pv06 is associated with resistance to common bacterial blight (Kelly et al., 2003). This study did not find strong correlations between QTL conferring resistance to the two species of Empoasca leaf hoppers, despite the fact that previous studies have demonstrated that resistance to E. fabae is consistent with resistance to E. kraemeri (Schaafsma et al., 1998). Out of 12 genomic regions where QTL associated with resistance to Empoasca species were identified, only the regions including the QTL cluster of LH7.1, LH7.2 and LH7.3, and LH8.2 were associated with resistance to both species. In addition, no regions were associated with both LC and LB damage. These findings support the hypothesis that LC damage and LB damage result from distinct plant responses. The lack of overlap between QTL for E. kraemeri and E. fabae may be due to the distinct insect feeding behaviors known for each species (Backus et al., 2005). These disparities could also be due to QTL × Environment interactions as a result of the significantly different environmental conditions of photoperiod, temperature and moisture between Michigan and Puerto Rico. The first reported QTL, LH2.2 for E. fabae nymph counts was detected on Pv02. LH2.2 was detected in the combined analysis (2009–2011) and in each individual year, indicating the stability and high heritability of this QTL (Table 4). Phenotypic screening to identify individuals with low nymph counts is not practical or efficient for any breeding program to undertake. However, the LH2.2 QTL is tightly linked at 0.4 cM to an easy to deploy InDel marker NDSU_IND_2_12.8147, which could be an excellent candidate for marker-assisted selection (MAS). Previous studies have identified QTL on Pv02 for resistance to multiple diseases (Kelly et al., 2003) as well as to other insect pests, including Thrips palmi (Frei et al., 2005). Because the same markers used to map the Thrips-resistance QTL did not map in the Matterhorn*/EMP 507 population, it is unknown how close these QTL may be located. However, they are believed to be clustered because, similar to LH2.2, the TP2.1BG locus included resistance to both Thrips feeding damage and reproductive adaptation. Since many disease-resistance loci have been known to cluster in the bean genome (Kelly et al., 2003), it is possible that these insect-resistance QTL may also cluster in the same genomic region. Frei et al. (2003, 2004) reported evidence of tolerance, antibiosis, and antixenosis to Thrips palmi in common bean, demonstrating that while antibiosis is an uncommon 2518

mechanism of insect resistance in common bean, it has been known to occur in some genotypes. The LH2.2 locus is the first QTL for nymph counts found in common bean and was specifically associated with reductions in E. fabae leafhopper nymph populations. Therefore, if antibiosis resistance is present in this population, LH2.2 is a likely candidate. Previous studies have identified QTL for agronomic traits located on Pv02, including seed weight, yield, and days to flowering (Blair et al., 2006). Agronomic traits such as flowering and days to maturity have been noted as potentially linked to leafhopper resistance (Galwey, 1983), possibly involved in antixenosis mechanisms.

CONCLUSIONS The QTL identified in this study for resistance to Empoasca leaf hopper species may have utility for MAS. In particular, LH2.2 is a strong candidate due to the stability of the QTL itself, the close linkage with an InDel marker, and the moderately high heritability of the trait itself. The QTL on Pv06 may be most useful if pyramided together to provide resistance to E. kraemeri leaf hoppers in tropical common bean germplasm. The cluster of QTL on Pv07 may have the broadest application for MAS to incorporate Empoasca leaf hopper resistance, as they include loci for resistance to each species and they are stable across multiple seasons in both Michigan and Puerto Rico. Pyramiding all three loci in future bean cultivars would be useful as they include different resistance mechanisms. Acknowledgments We wish to acknowledge P.B. Cregan, USDA-ARS, Soybean Genomics and Improvement Laboratory, BARC, Beltsville, MD for genotyping the mapping population with the BARCBean6K_3 SNP BeadChip. The authors wish to acknowledge receipt of InDel markers developed by the BeanCAP project at North Dakota State University by S.M. Moghaddam and P. McClean. This project was also supported by Project Greeen no. GR07-39 from Michigan State University AgBioResearch and the BeanCAP project of the USDA National Institute of Food and Agriculture. The content is solely the responsibility of the authors and does not necessarily represent the official views of the USDA.

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