Skip to main content
PMC home page
Wiley Open Access Collection logoLink to Wiley Open Access Collection
. 2021 Feb 18;3(3):e75. doi: 10.1002/leg3.75

Recent advances in faba bean genetic and genomic tools for crop improvement

Hamid Khazaei 1,✉, Donal M O'Sullivan 2, Frederick L Stoddard 3, Kedar N Adhikari 4, Jeffrey G Paull 5, Alan H Schulman 6,7, Stig U Andersen 8, Albert Vandenberg 1
PMCID: PMC8700193  PMID: 34977588

Abstract

Faba bean ( Vicia faba L.), a member of the Fabaceae family, is one of the important food legumes cultivated in cool temperate regions. It holds great importance for human consumption and livestock feed because of its high protein content, dietary fibre, and nutritional value. Major faba bean breeding challenges include its mixed breeding system, unknown wild progenitor, and genome size of ~13 Gb, which is the largest among diploid field crops. The key breeding objectives in faba bean include improved resistance to biotic and abiotic stress and enhanced seed quality traits. Regarding quality traits, major progress on reduction of vicine‐convicine and seed coat tannins, the main anti‐nutritional factors limiting faba bean seed usage, have been recently achieved through gene discovery. Genomic resources are relatively less advanced compared with other grain legume species, but significant improvements are underway due to a recent increase in research activities. A number of bi‐parental populations have been constructed and mapped for targeted traits in the last decade. Faba bean now benefits from saturated synteny‐based genetic maps, along with next‐generation sequencing and high‐throughput genotyping technologies that are paving the way for marker‐assisted selection. Developing a reference genome, and ultimately a pan‐genome, will provide a foundational resource for molecular breeding. In this review, we cover the recent development and deployment of genomic tools for faba bean breeding.

Keywords: breeding, gene discovery, genomic resources, mapping population, Vicia faba

1. INTRODUCTION

Faba bean ( Vicia faba L.) is one of the first domesticated food legumes and has a long history of cultivation; seeds as old as 14,000 years were identified in the southern Levant (Caracuta et al., 2016). Faba beans are widely grown for food and feed as a generous source of high‐quality protein, dietary fibre and other valuable nutrients (Duc, 1997; Khazaei & Vandenberg, 2020). The protein content of faba bean seeds is about 29% of the dry matter (Warsame et al., 2018), which makes it one of the main sources of affordable protein for people in the Middle East, Latin America and Africa, and for livestock feed in many developed countries. Faba bean, like most other legumes, forms a symbiosis with nodule‐forming bacteria that have nitrogen fixing ability, which provides major benefits to cropping systems and the environment and contributes to agricultural sustainability by soil improvement. It is considered an excellent protein crop due to its ability to provide nitrogen inputs into temperate agricultural systems on account of its wide adaptation (Rispail et al., 2010), as well as its high yield potential and nitrogen‐fixing capacity even when nitrogen is present in the soil (Herridge et al., 2008), compared with other grain legumes (Cernay et al., 2015). These particular nitrogen‐fixing traits in combination with yield potential mean that faba bean can be produced in a sustainable manner, making it particularly well‐suited for providing the protein required for the globally expanding plant‐based food chain. Faba bean delivers plant protein products suitable for consumption both by those with soybean ( Glycine max (L.) Merr.) allergy or intolerance and by those wishing local products. According to Food and Agriculture Organization Corporate Statistical Database (2019), faba bean is the fourth most widely grown cool‐season grain legume (pulse) globally after pea ( Pisum sativum L.), chickpea ( Cicer arietinum L.), and lentil ( Lens culinaris Medik.), with annual production of around 4.5 million tonnes from nearly 2.5 Mha.

Faba bean improvement is currently impeded by development of rich genomic resources having not kept pace with those of other cool‐season grain legumes. Faba bean is a partially allogamous diploid species with six pairs of remarkably large chromosomes. Its genome is one of the largest of any diploid field crop, about 13 Gbp in the haploid complement (Soltis et al., 2003) and contains more than 85% repetitive DNA (Novák et al., 2020). The large genome of faba bean is 2.9, 3.0 and 15.9 times larger than pea, lentil and chickpea, respectively. Assembly of the faba bean genome and map‐based cloning was delayed both due to its genome complexity (e.g. abundance of transposable elements) and the lower investment in its study compared with, for example, soybean. In the absence of a reference genome assembly for this species, high‐throughput approaches such as transcriptome analysis have been efficient tools for enrichment of genomic resources (e.g. Arun‐Chinnappa & McCurdy, 2015; Braich et al., 2017; Khan et al., 2019; Ocaña et al., 2015; Ray et al., 2015). However, from these reported transcriptome datasets, only limited DNA sequence data are available in public databases (Mokhtar et al., 2020). Additionally, the development of high‐density genetic maps derived from multiple populations and gene‐based molecular markers, particularly those developed by Webb et al. (2016) and Carrillo‐Perdomo et al. (2020), has paved the road to marker‐assisted selection (MAS) and gene discovery. For example, the elucidation of the biosynthetic pathway for the pyrimidine glycosides vicine and convicine (v‐c) (Björnsdotter et al., 2020), which have been the main factors limiting faba bean cultivation and usage in many warm regions, was not possible without the combination of transcriptome data (Ray et al., 2015) and gene‐based comparative mapping approaches (Khazaei et al., 2015, 2017).

Two recent review papers on this topic cover the coming of age of faba bean genetics and genomics in some detail (see Maalouf et al., 2019; O'Sullivan & Angra, 2016), but, since then, major progress on the key seed anti‐nutrients v‐c (Björnsdotter et al., 2020), seed coat tannins (e.g. Gutiérrez et al., 2020; Gutiérrez & Torres, 2019), as well as improved mapping approaches (Carrillo‐Perdomo et al., 2020) and transcriptome data (see Section 3), has been made (e.g. Gao et al., 2020; Wu et al., 2020; Yang et al., 2020). We provide here a comprehensive review on the mapping population and genomic resources in this species.

2. GENOMIC RESOURCES

2.1. Genetic maps

Genetic linkage maps have been developed in faba bean using different types of populations and molecular markers (Table 1). Sirks (1931) was the first to report a faba bean genetic map, identifying 19 genetic factors that formed four linkage groups. His genetic resources were lost during World War II. Four decades later, Sjödin (1971) used translocation lines for the assignment of different loci (for morphological observations, flower and seed coat colour) to their respective chromosomes. Genetic mapping studies were developed in the 1990s first with the aid of morphological markers, isozymes, seed protein genes and random amplified polymorphic DNA (RAPD) markers. Later, the development of expressed sequence tags (ESTs), microsatellites or single sequence repeats (SSRs), EST‐SSRs and single nucleotide polymorphism (SNP) markers helped to enrich faba bean genetic studies and breeding. The first DNA‐based linkage map in faba bean was constructed with only 17 markers, of which 10 were RFLPs (restriction fragment length polymorphism) (van de Ven et al., 1991). The first set of SSR markers were developed by Požárková et al. (2002) and then mapped by Román et al. (2004). A composite gene‐based map, anchored with orthologous markers mapped in Medicago truncatula Gaertn., was developed by Ellwood et al. (2008); synteny and genic collinearity among the legumes make the data applicable to V. faba and other legumes (Lee et al., 2017). Kaur, Kimber, et al. (2014) reported the first exclusively SNP‐based generic map of faba bean. Satovic et al. (2013) reported the first reference consensus genetic map, which covered 4062 cM (centiMorgan) in six main linkage groups, corresponding to the six chromosomes of faba bean. Table 1 shows that with the development of faba bean sequences and marker datasets, there was a correspondingly encouraging increase in the density and utility of gene‐based genetic maps. In the last few years, the significant advancements in genotyping and sequencing technologies have led to two new SNP‐based highly dense consensus maps. An international effort resulted in the first consensus map for six mapping populations, based on SNP markers derived from M. truncatula (Webb et al., 2016). It contained 687 SNP markers on six linkage groups, each presumed to correspond to one of the faba bean chromosomes. Carrillo‐Perdomo et al. (2020) recently reported the most saturated consensus genetic map to date: it was constructed using three mapping populations and encompassed 1728 SNP markers distributed in six linkage groups. Solid proof of macro‐synteny was also observed between this map and the most closely related legume species that have been sequenced. Recently, a database of ESTs, EST‐SSRs, mtSSRs (mitochondrial‐simple sequence repeats) and microRNA‐target markers in faba bean has been launched (Mokhtar et al., 2020). Now that most pulse genomes are available, it is important to implement comparative genomic approaches, which will ultimately assist in the identification of candidate genes, quantitative trait loci (QTL) mapping, and assembly of the genome in faba bean.

TABLE 1.

Information on available genetic maps constructed from bi‐parental population and traits mapped in faba bean

Population Marker type Population type Population size Map length (cM) Ave. inter‐marker distance (cM) Mapped traits References
172 × Optica 7 RFLPs, 4 morphologicals, 3 isozymes, 3 RAPDs BC 231 van de Ven et al. (1991)
Vf6 × (Vf173, Vf35) 43 RAPDs, 7 isozymes, 1 RFLP 2 F2s 20 + 44 300–350 Torres et al. (1993)
172 × Optica 8 morphologicals, 7 RFLPs, 4 isozymes, 4 RAPDs BCF2 300 Biochemical and morphological traits Ramsay et al. (1995)
Vf6 × (Vf2 T5,6; a Vf33 T3,4; Vf159 T4,5,6) 147 RAPDs, 9 isozymes, 1 morphological 7 F2s 813 (total) 850 Satovic et al. (1996)
Vf6 × (Vf17, Vf27, Vf46) 105 RAPDs, 7 isozymes, 3 seed protein genes, 1 morphological 3 F2s 175 1200 20 Seed weight Vaz Patto et al. (1999)
34Morocco × Kristall 25 77 RAPDs F7 57 973 14.66 Surahman (2001)
Vf6 × Vf136 117 RAPDs, 2 isozymes, 2 seed protein genes F2 196 1445 13.72 Broomrape and ascochyta blight resistance Román et al. (2002; 2003)
Vf6 × (Vf2 T5,6; Vf33 T3,4; Vf27; Vf27 T4,6; Vf136; Vf159 T4,5,6) 176 RAPDs, 6 isozymes, 4 SSRs, 3 seed protein genes, 2 morphologicals 11 F2s 654 (total) 1559 8 Rust, broomrape and ascochyta blight resistance Román et al. (2004)
29H × Vf136 94 RAPDs, 4 isozymes, 3 SSRs, 2 seed protein genes F2 159 1308 Rust and ascochyta blight resistance, and agronomic traits Avila et al. (2003; 2004; 2005)
Vf6 × Vf27 151 ITAPs F6 94 1686 14.6 Ellwood et al. (2008)
Côte D'Or/1 × BPL 4628 131 RAPDs, 1 morphological F6 101 1635 14.73 Frost tolerance and physiologically related traits Arbaoui et al. (2008)
Vf6 × Vf136 238 RAPDs, 21 ISMs, 6 SSRs, 5 EST‐derived markers, 4 isozymes, 2 STSs, 1 SCAR F6 165 2857 12.72 Ascochyta blight and broomrape resistance Díaz‐Ruiz, Satovic, et al. (2009), Díaz‐Ruiz, Torres, et al. (2009) and Díaz‐Ruiz et al. (2010)
Vf6 × Vf27 167 EST‐derived markers, 71 RAPDs, 11 SSRs, 3 RGAs, 3 seed protein genes, 2 isozymes, 1 morphological F6 124 1875 7.26 Flowering, yield‐related traits, plant architecture and yield Cruz‐Izquierdo et al. (2012) and Ávila et al. (2017)
91825 × K1563 128 SSRs F2 129 1587 12.4 Ma et al. (2013)
29H × Vf136 121 RAPDs, 38 EST‐derived markers, 6 SSRs, 5 RGAs, 1 defense‐related gene, 1 seed protein gene F7:8 119 1402 9.87 Broomrape resistance Gutiérrez et al. (2013)
Vf6 × Vf27, Vf6 × Vf136, 29H × Vf136 729 markers in total 3 RILs 124 + 165 + 119 4613 6 Consensus map Satovic et al. (2013)
Icarus × Ascot 465 SNP markers, 57 EST‐SSRs F5:6 95 1217 2.3 Ascochyta blight resistance and flowering time Kaur, Kimber, et al. (2014) and Catt et al. (2017)
Mélodie/2 × ILB 938/2 188 SNP markers, 1 morphological F5 211 928 5.8 Drought adaptation‐related and morphological traits, and vicine‐convicine Khazaei et al. (2014a, 2014b, 2015)
Nubaria 2 × Misr 3 552 EST‐SSRs F2 109 688 1.25 El‐Rodeny et al. (2014)
Albus × BPL 10, Albus × 29H, Hedin × CGN07715 cf‐3, NV644–1 × IG 12658, Mélodie/2 × ILB 938/2, Côte D'Or/1 × BPL 4628/1521 687 SNP markers 4 F2s, 2 RILs 136 + 165 + 52 + 192 + 200 + 101 1404 2.6 Consensus map, flower color (zt1) Webb et al. (2016)
Fiord × Doza#12034 2784 SNP markers F6 104 1027 0.37 Rust resistance Ijaz (2018)
91825 × K1563 465 SSRs F2 129 4517 9.71 Yang et al. (2019)
Nura × Farah 1152 SNP markers F4 145 1022 1.45 Ascochyta blight resistance Sudheesh et al. (2019)
Disco/2 × ILB 938/2 257 SNP markers, 2 morphologicals F6 176 918 5.4 Flower color (zt2) Zanotto et al. (2020)
(Nova Gradiska, Silian & Quasar) × Hiverna 1728 SNP markers 3 F3s 102 + 147 + 96 1548 0.89 Consensus map Carrillo‐Perdomo et al. (2020)
Vf6 × Vf27 Cruz‐Izquierdo et al. (2012) + 44 KASPs and 37 dehiscence‐related markers F8:9 124 4421 Pod dehiscence Aguilar‐Benitez et al. (2020)
Open in a new tab

Abbreviations: EST, expressed sequence tags; ISM, intron‐spanning marker; ITAP, intron targeted amplified polymorphism; KASP, kompetitive allele specific PCR; RAPD, random amplified polymorphic DNA; RFLP, restriction fragment length polymorphism; RGA, resistant gene analogs; RIL, recombinant inbred lines; SCAR, sequence characterized amplified region; SNP, single nucleotide polymorphism; SSR, simple sequence repeat; STS, sequence tagged sites.

a

T refers to the assignment of linkage groups to chromosomes by trisomic segregation.

2.2. Mapping populations

Published studies in faba bean to date have mostly involved bi‐parental populations, derived from crosses between two inbred lines. Several types of bi‐parental mapping populations, such as F2, backcrosses and recombinant inbred lines (RILs), have been employed for genetic map construction and trait mapping. The relatively large set of interconnected bi‐parental populations that segregate for diverse important traits in this species will help advance faba bean breeding (Table 1). These types of populations are easy to construct and represent a powerful tool for QTL detection. Their optimal allele frequency and low rate of linkage disequilibrium decay within chromosomes means that only a few hundred RILs/markers are needed to map a QTL (Scott et al., 2020). Despite the advantages of bi‐parental populations, their mapping precision is low due to the low total amount of genetic recombination, as only two alleles are present at any locus, and to the low amount of genetic diversity that can be created by only two founders. These factors may limit the number of QTLs captured. Multi‐parent populations have been developed to cope with the limitations of bi‐parental populations (Scott et al., 2020). In faba bean, a multi‐parent population derived from 11 European winter bean founders was created and employed to identify genomic regions controlling frost adaptation (Sallam & Martsch, 2015). A multi‐parent population from four founders (ILB 938/2, Disco/2, IG 114476 and IG 132238) was developed for preliminary characterization of important morphological and biochemical traits (Khazaei, Stoddard, et al., 2018). A genetic map with 11 K loci is being developed using a 50 K Axiom SNP genotyping array (O'Sullivan et al., 2019). This population segregates for a number of traits including v‐c, seed coat tannin (white‐flowered parent carrying the zt2 gene), seed size and colour, and branching. A MAGIC (multi‐parent advanced‐generation intercross) population comprising over 2000 F4 individuals is currently under development at ICARDA (International Center for Agricultural Research in Dry Areas), combining eight diverse parents with sources for heat, drought, ascochyta blight, chocolate spot, rust and broomrape resistance (Maalouf et al., 2019). Because in multi‐parental populations there can be as many alleles per locus as founders, quantifying genetic interactions between loci requires the large numbers of individuals (>1000), found in typical MAGIC populations.

Table 2 lists the faba bean genotypes and parental lines that have been used for genetic map construction or transcriptome analysis. Over 70% of the germplasm used for mapping purposes belongs to the Mediterranean adaptation zones (Australia, southern Europe and North Africa). The global collection of faba bean germplasm across 37 genebanks exceeds 43,000 accessions. The ICARDA collection comprises more than 8500 accessions held in Lebanon and Morocco by April 2020 (20% of the global collection, Westengen et al., 2020). Despite the wealth of faba bean germplasm, characterization and preliminary evaluation remain a challenge. Faba bean is represented in the collections by only the cultivated forms, and a wide range of variation in plant and seed phenotypic characteristics have been reported (Khazaei, 2014; Maalouf et al., 2019). The development of a reference genome, gene functional analyses and genotype–phenotype association, together with the development of high‐throughput genotyping platforms, will facilitate characterization of the genetic diversity within the germplasm collections as well as understanding of its potential. It will aid exploitation of the diversity as a key resource for breeding.

TABLE 2.

Information on faba bean germplasm used for genetic population construction and transcriptome analysis purposes

Line Origin/donor Trait(s) of interest Description
Mapping population
Ac1655 Australia Rust resistance European line (V‐300) introduced from Spain (Adhikari et al., 2016)
Albus a Poland Low tannin White‐flowered (zt1), Albus (Latin) means white
Ascot a Australia Resistant to ascochyta blight Selection from cv. Fiord. Original source of germplasm is Greece (Kaur, Cogan, et al., 2014)
BPL 10 a Jordan Nematode resistant Pure line selection from accession IG 101769 (ILB 6)
BPL 228 (34Morocco) Morocco Pure line selection from IG 11335 (ILB 141)
BPL 4628 China Frost tolerant Pure line selection from IG 106387 (ILB 3009) from Anhui, China
CGN07715 GAUG, Germany Closed flower From CGN grain legumes collection, Wageningen, Netherlands
Côte d'Or INRA, France Frost tolerant Old French winter bean from Côte d'Or region of Burgundy (Picard et al., 1985). Yellow (buff) seed coat (Yg)
Disco INRA, France Low tannin Low v‐c, white‐flowered (zt2)
Doza a Australia Rust resistance Pedigree: Ac383 × triple White. Original sources of germplasm are Ethiopia and Sudan, respectively
Farah a Australia Resistant to ascochyta blight Selection from cv. Fiesta (selection from BPL 1196 from Spain) ( Kaur, Cogan, et al., 2014 )
Fiord a Australia The first faba bean cultivar released in Australia. Selection from Ac59 from the island of Naxos, Greece (Kaur, Cogan, et al., 2014)
Hedin a GAUG, Germany Highly inbred and autofertile, small seed size, and high seed number It has already been adopted in a number of genomics projects as a reference genotype. Released in 1986 and has “Herz Freya” in its background
Hiverna Germany Frost tolerant Large‐seeded winter bean, from NPZ released in 1986 (Link et al., 2010)
ILB 938 (IG 12132) Andean region of Colombia and Ecuador Drought adaptation, chocolate spot and rust resistance ILB 938 (BPL 1179) is the result of mass selection from ILB 438 (BPL 710) based on seed size (Khazaei, Link, 2018). It carries a rare allele (ssp1) that decouples pigmentation in flowers from that in stipules ( Khazaei et al., 2014b )
Icarus a Australia Resistant to chocolate spot and rust Icarus was derived from BPL 710 (see above) ( Kaur, Cogan, et al., 2014 )
IG 12658 Ethiopia Dwarf A dwarf accession carrying gibberellic acid deficiency gene (Hughes et al., 2020)
K1563 China Winter bean Small‐seeded
Kasztelan Poland Low tannin White‐flowered (zt1), the NIAB accession code is NV644
Kristall 25 Germany Developed in Lochow Petkus in 1973
Mélodie INRA, France Low v‐c High water use efficiency (Khazaei et al., 2014a)
Misr 3 Egypt Resistance to broomrape Early flowering, small‐seeded. Pedigree: ((Giza 3 × ILB 938) × Cairo 241)) × (Giza 3 × 23A/45/76) (Attia et al., 2013)
Nova Gradiska Croatia Resistance to seed weevils (Bruchus spp.) (Carrillo‐Perdomo et al., 2019) Small‐seeded
Nubaria 2 Egypt Drought adaptation Adapted to the Nubaria region in Egypt. Late flowering, large‐seeded. Pedigree: ILB 1550 × Radiation 2095/76
Nura Australia Resistant to ascochyta blight and moderate resistant to chocolate spot Pedigree: Icarus × Ascot. Original sources of germplasm are Ecuador and Greece, respectively ( Kaur, Cogan, et al., 2014 )
Optica Netherlands Resistant to freezing, low tannin Large‐seeded, white‐flowered (zt1)
Quasar UK Resistance to seed weevils (Carrillo‐Perdomo et al., 2019) Winter bean adapted to oceanic climate
Silian Northern Sudan Small‐seeded
Vf6 IFAPA, Spain Resistant to ascochyta blight Asynaptic breeding line program from Córdoba
Vf27 IFAPA, Spain Pod dehiscent Paucijuga type
Vf136 a IFAPA, Spain Moderate level of resistance to broomrape From the progeny selection of Vf1071 × alameda. Vf1071 is a broomrape resistant line selected from cv. Giza 402. Alameda is a commercial variety well adapted to southern Spain
172 Afghanistan High levels of post‐harvest seed dormancy Paucijuga type
91825 China Winter bean Large‐seeded
29H a INRA, France Resistant to ascochyta blight Small‐seeded breeding line developed at INRA
Transcriptome
AO 1155 INRA, France Low v‐c Small‐seeded, white‐flowered (zt1)
CDC Fatima Canada An established cultivar developed for use in the prairie provinces of Canada. Selection from a landrace known as Chinese broad bean (Graf & Rowland, 1987)
Hassawi‐2 Saudi Arabia Drought adaptation Local landrace
SSNS‐1 Canada Small‐seeded Bulk selection from cv. Ackerperle from Germany
Tongxian‐2 China Winter bean Vegetable type
Windsor UK Large‐seeded, long pods
Wizard UK High‐yielding with large attractive seeds, ascochyta blight resistance Large‐seeded winter bean from Wherry & Sons, UK, released in 2002
Y078 China Salt sensitive
Y134 China Salt tolerant
Open in a new tab

Note: ICARDA maintains faba bean germplasm in two classes, international legume bean (ILB) accessions from different countries, and bean pure line (BPL) accessions that are derived through selfing from accessions drawn from the ILB collection.

Abbreviations: CDC, Crop Development Centre; CGN, Centre for Genetic Resources, the Netherlands; GAUG, Georg‐August‐University, Göttingen; ICARDA, International Center for Agricultural Research in Dry Areas; IFAPA, Instituto de Investigación y Formación Agroalimentaria; INRA, Institut National de la Récherche Agronomique; NAIB, National Institute of Agricultural Botany; v‐c, vicine‐convicine.

a

Used for both mapping and transcriptome research.

2.3. Trait mapping

The first faba bean QTL mapping study was reported by Ramsay et al. (1995), who detected several loci for morphological and biochemical traits including v‐c. QTL mapping in faba bean for biotic stresses, such as resistance to pathogenic fungi or parasitic plants, has been attempted (Table 1). Two of the major constraints in Mediterranean climates, namely, ascochyta blight (caused by Ascochyta fabae Speg.,) and broomrape ( Orobanche crenata Forsk. and O. foetida Poir.), have been widely subjected to QTL studies using F2 and RIL populations (Table 1). The QTLs accounting for significant proportions of ascochyta blight resistance have been validated in multi‐environment trials (Atienza et al., 2016). In addition, some attention has been given to rust resistance (Uromyces viciae‐fabae (Pers.) J. Shört.) (Avila et al., 2003; Ijaz, 2018). Recently, two mapping populations (Fiord × Doza#12034 and Fiord × Ac1655) have been developed at the University of Sydney, in which KASP (Kompetitive Allele Specific PCR) markers for rust resistance genes Uvf‐2 and Uvf‐3 have been identified (Ijaz, 2018). However, until now, there has been no attempt to map QTLs or genes governing chocolate spot (caused by Botrytis fabae Sard.) resistance, in spite of the importance and widespread nature of this disease globally. A few RIL populations suitable for chocolate spot genetic studies have been developed using ILB 938, an accession with proven resistance to chocolate spot (reviewed by Khazaei, Link, et al., 2018). Two mapping populations (Mélodie/2 × ILB 938/2 and Disco/2 × ILB 938/2) have been phenotyped at the University of Saskatchewan and QTL mapping is underway. In addition, a list of faba bean accessions with resistance to chocolate spot is available (Maalouf et al., 2016).

Some progress has been made in identifying QTLs for abiotic stresses such as frost tolerance (Arbaoui et al., 2008; Sallam et al., 2016; Sallam & Martsch, 2015), traits related to drought adaptation (Ali et al., 2016; Khazaei et al., 2014a), and yield (Ávila et al., 2017; Cruz‐Izquierdo et al., 2012). QTLs controlling abiotic stress responses in faba bean, detected by either QTL mapping or association mapping approaches, have been discussed by Sallam and Ul‐Allah (2019). Given the few QTLs reported in faba bean compared with other pulses, saturation of the genomic regions associated with target regions and QTL validation in multiple environments and genetic backgrounds are needed to uncover reliable marker‐trait associations such as those reported by Aguilar‐Benitez et al. (2020) for pod dehiscence. The marker density in faba bean has recently been significantly increased (Carrillo‐Perdomo et al., 2020; O'Sullivan et al., 2019); this development will facilitate fine QTL mapping and gene identification.

2.3.1. Successful gene discoveries in the absence of a faba bean reference genome

Despite the relatively limited discovery of genes and QTLs for disease resistance and abiotic stress tolerance, the discovery of genes for the seed anti‐nutritional factors v‐c and tannins, which place major limitations on faba bean usage, has progressed considerably very recently. Vicine and convicine are stored in cotyledons of most faba beans at about 1% of dry matter (Khazaei et al., 2019). They are toxic in people who have a hereditary recessive mutation affecting the enzyme glucose‐6‐phosphate dehydrogenase (G6PD, Luzzatto & Arese, 2018). The first two mapping studies on v‐c content (Gutiérrez et al., 2006; Ramsay et al., 1995) revealed that it was controlled by one major locus. Khazaei et al. (2015) showed that the distribution of v‐c concentration was bimodal, which was consistent with the detection of a single major QTL at the previously reported vc − locus on faba bean chromosome 1. Later, a robust, breeder‐friendly and high‐throughput KASP marker was developed and validated from this region (Khazaei et al., 2017). This marker was found to reside within the bifunctional riboflavin biosynthesis protein RIBA1, the gene for which is now termed VC1, that underlies the major v‐c QTL and catalyses a key step in v‐c biosynthesis (Björnsdotter et al., 2020). The VC1 gene identification, which relied on genetic mapping and gene‐to‐metabolite correlations, now paves the way for development of faba bean cultivars free from v‐c based on new insight into the v‐c biosynthetic pathway.

Seed coat tannins limit faba bean use in food and feed; a low tannin phenotype, characterised by white flower colour, is controlled by two unlinked recessive genes, zt1 and zt2. A comparative mapping approach identified an ortholog of the M. truncatula WD40 transcription factor TTG1 (Transparent Testa Glabra 1), located on chromosome 2, as the zt1 gene (Webb et al., 2016). These results have been recently confirmed by Gutiérrez and Torres (2019), who characterized zt1 and proved the high similarity of the gene sequence with other legume species. An allele‐specific diagnostic marker was also developed that differentiates zt1 from other genotypes. Gutiérrez et al. (2020) reported the bHLH transcription factor VfTT8 (Transparent Testa8) located on chromosome 3 as the zt2 gene. A robust KASP marker for the zt2 gene is now available (Zanotto et al., 2020).

Besides the successful gene discovery for quality traits mentioned above, progress was also made for gene discovery and development of a diagnostic molecular marker for the terminal inflorescence gene (ti) in faba bean (Avila et al., 2006, 2007). The TFL1 (Terminal Flower 1), as main regulator of inflorescence development in legumes (Benlloch et al., 2015), was responsible for the determinate growth habit in faba bean (Vf_TFL1) and is located on chromosome 5.

3. TRANSCRIPTOMES

A number of transcriptomes have been reported for faba bean (Table 3), albeit in the absence of a reference genome. These datasets were generated from a selection of different genotypes and tissues at various development stages or treatments. Recent reviews of this topic (Maalouf et al., 2019; O'Sullivan & Angra, 2016) described the faba bean transcriptome contributions up to 2016 that were used for the development of molecular markers for genetic mapping (listed in Table 3). Since then, the transcriptome data coverage has been further enriched (Braich et al., 2017; Cooper et al., 2017). A high proportion of transcripts (about 96%) from Webb et al. (2016) was captured by transcriptome data of Braich et al. (2017). The sequence length data were increased at 461 chromosomal loci and provided increased accuracy by Cooper et al. (2017) compared with transcriptome data in Webb et al. (2016). The transcriptome data of Braich et al. (2017) revealed that faba bean, despite its large complex genome, compared similarly with other legume species in expressed gene content.

TABLE 3.

Summary of published transcriptome data in faba bean

References Aim of study Tissue Output NGS platforms
Ray and Georges (2010) Development of EST sequences Early to mid‐developed embryo 5000 ESTs 454 sequencing technology
Kaur et al. (2012) Design and evaluation of EST‐SSRs Young and mature leaf, stem, flower, immature pod, mature pod and immature seed 802 SSRs 454 Roche GS FLX titanium
Kaur, Kimber, et al. (2014) Development of SNP markers Leaf 768 SNP markers Illumina OPA‐bead array
Ray et al. (2015) Development of NGS libraries to elucidate the v‐c pathway and other genes for the anti‐nutritional factors 5‐ to 6‐days‐old root and etiolated shoot and developing seed coat 8 libraries containing 1.2 million ESTs 454 sequencing
Arun‐Chinnappa and McCurdy (2015) Generating a genome‐wide transcriptome map of faba bean Expanding and fully expanded leave, elongating and fully elongated stem, and closed and open flower, whole roots including root hairs, and cotyledon 17,160 unigenes Illumina HiSeq‐2000
Ocaña et al. (2015) Transcriptome analysis under ascochyta blight infection Leaf tissue at 4, 8 and 12 h after inoculation 21,243 transcripts, 39,060 SNPs and 3669 InDels Illumina
Webb et al. (2016) SNP discovery 7‐day‐old seedling 653 new mined SNP markers GS FLX/454 reads
Braich et al. (2017) Development of reference unigene sets Immature pod and fully‐open flower 26,295 new transcripts RNA‐Seq, Illumina HiSeq 2000
Cooper et al. (2017) Enhancement of faba bean genome resources Embryos 16,300 unigenes RNA‐seq, Illumina HiSeq 2500
Alghamdi et al. (2018) Identify drought stress differentially expressed genes Root at vegetative and flowering stages 18,327 SSRs RNA‐seq, Illumina Hiseq 4000
Gao et al. (2020) Identify response to vernalization genes Seedling 6852 SSRs in 6552 transcripts RNA‐seq, Illumina HiSeq 2500
Yang et al. (2020) Identify salinity stress differentially expressed genes Seed 4486 differentially expressed genes RNA‐seq, Illumina Hiseq 4000
Carrillo‐Perdomo et al. (2020) SNP discovery Leaf 39,423 transcripts and 105,828 gene‐based SNPs RNA‐seq, Illumina MiSeq
Björnsdotter et al. (2020) Uncovering genes associated with the biosynthesis of vicine‐convicine Young and mature leaf, flower, pod and whole seed at early seed‐filling stage, embryo and pod at mid maturation, and stem 49,277 transcripts Illumina HiSeq PE150
Open in a new tab

Next‐generation sequencing (NGS) platforms, especially high‐throughput RNA sequencing (RNA–seq) technology, one of the most powerful tools currently available for transcriptome profiling, has enhanced the efficiency and speed of gene discovery in faba bean (Table 3). For example, the identification and characterization of differential gene expression from tissues subjected to drought (Alghamdi et al., 2018; Wu et al., 2020), vernalization (Gao et al., 2020), and salinity stress (Yang et al., 2020) have benefited greatly. These findings will help in understanding the stress tolerance mechanisms in the crop and will provide resources for functional genomics. Coupled with allelic data and trait mapping, the data will be invaluable in the development of more resilient faba bean varieties. A high‐quality reference transcriptome has been completed (Björnsdotter et al., 2020) and is being expanded to a pan‐transcriptome using data from four different genotypes (Hedin, Hiverna, 153b and 2378), including data from both shoot and root tissues (Escobar‐Herrera et al., 2020). This effort has provided a comprehensive faba bean reference gene set that will be a valuable new resource for differential gene expression analyses and genome annotation.

4. CONCLUSIONS AND PERSPECTIVES

Recent technological advances now allow sequencing of the large genome of faba bean. A collaborative reference genome assembly effort is currently underway, coordinated by the NORFAB consortium (Protein for the Northern Hemisphere, https://bit.ly/37QxeuM), and a pan‐genome initiative is being launched by the University of Helsinki and Luke (Natural Resources Institute Finland). The NORFAB project has developed an annotated reference transcriptome for faba bean (Escobar‐Herrera et al., 2020), which will aid the development of gene models for the reference assembly. The transcriptome work has also led to production of a high density faba bean genotyping array, which is now available from the University of Reading, UK. The array (known as ‘Vfaba_v2’), built on Life Technologies Axiom platform, contains 24,929 polymorphic high resolution SNP markers located in 15,846 different genes. Faba bean now benefits from saturated synteny‐based genetic maps, NGS, and high‐throughput genotyping technologies, which together will greatly aid genome assembly. Release of the reference genome will further advance the faba bean genomics and breeding revolution.

CONFLICT OF INTEREST

The authors have no conflict of interest.

AUTHOR CONTRIBUTION

H. K. did the writing of the original draft. All authors did the writing, review and editing of the manuscript. All authors read and agreed to the published version of the manuscript.

ETHICS STATEMENT

This manuscript does not contain any studies with human or animal subjects.

ACKNOWLEDGEMENTS

The authors acknowledge the following grants: ‘NORFAB’ (Innovation Fund Denmark grant number 5158‐00004B); ‘Papugeno: Genomic tools for faba bean (Vicia faba L.) improvement for food and protein security’, (Academy of Finland Decision 298314); ‘Traits and technologies to boost North African protein self‐sufficiency’ (Biotechnology and Biological Sciences Research Council of the UK, grant BB/P023509/1); and further funding from ADF (Agriculture Development Fund – Government of Saskatchewan, Canada), the Western Grains Research Foundation, Canada, the Saskatchewan Pulse Growers (SPG), Canada, and the Grains Research and Development Corporation, Australia.

Khazaei, H. , O'Sullivan, D. M. , Stoddard, F. L. , Adhikari, K. N. , Paull, J. G. , Schulman, A. H. , Andersen, S. U. , & Vandenberg, A. (2021). Recent advances in faba bean genetic and genomic tools for crop improvement. Legume Science, 3(3), e75. 10.1002/leg3.75

Funding information Agriculture Development Fund ‐ Government of Saskatchewan, Canada, Grant/Award Number: 20150285; Biotechnology and Biological Sciences Research Council, UK, Grant/Award Number: BB/P023509/1; Grains Research and Development Corporation, Australia, Grant/Award Number: UA00163; Innovationsfonden, Innovation Fund Denmark, Grant/Award Number: 5158‐00004B; Saskatchewan Pulse Growers, Canada, Grant/Award Number: BRE1714; Suomen Akatemia (Academy of Finland), Grant/Award Number: 298314; Western Grains Research Foundation, Canada, Grant/Award Number: VarD1609

DATA AVAILABILITY STATEMENT

Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.

REFERENCES

  1. Adhikari, K. N. , Zhang, P. , Sadeque, A. , Hoxha, S. , & Trethowan, R. (2016). Single independent genes confer resistance to faba bean rust (Uromyces viciae‐fabae) in the current Australian cultivar Doza and a central European line Ac1655. Crop and Pasture Science, 67, 649–654. 10.1071/CP15333 [DOI] [Google Scholar]
  2. Aguilar‐Benitez, D. , Casimiro‐Soriguer, I. , & Torres, A. M. (2020). First approach to pod dehiscence in faba bean: Genetic and histological analyses. Scientific Reports, 10, 17678. 10.1038/s41598-020-74750-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Alghamdi, S. S. , Khan, M. A. , Ammar, M. H. , Sun, Q. , Huang, L. , Migdadi, H. M. , El‐Harty, E. H. , & Al‐Faifi, S. A. (2018). Characterization of drought stress‐responsive root transcriptome of faba bean (Vicia faba L.) using RNA sequencing. 3 Biotech, 8, 502. 10.1007/s13205-018-1518-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Ali, M. B. M. , Welna, G. C. , Sallam, A. , Martsch, R. , Balko, C. H. , Gebser, B. , … Link, W. (2016). Association analyses to genetically improve drought and freezing tolerance of faba bean (Vicia faba L.). Crop Science, 56, 1036–1048. 10.2135/cropsci2015.08.0503 [DOI] [Google Scholar]
  5. Arbaoui, M. , Link, W. , Satovic, Z. , & Torres, A. M. (2008). Quantitative trait loci of frost tolerance and physiologically related traits in faba bean (Vicia faba L.). Euphytica, 164, 93–104. 10.1007/s10681-008-9654-0 [DOI] [Google Scholar]
  6. Arun‐Chinnappa, K. S. , & McCurdy, D. W. (2015). De novo assembly of a genome‐wide transcriptome map of Vicia faba (L.) for transfer cell research. Frontiers in Plant Science, 6, 217. 10.3389/fpls.2015.00217 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Atienza, S. G. , Palomino, C. , Gutiérrez, N. , Alfaro, C. M. , Rubiales, D. , Torres, A. M. , & Ávila, C. M. (2016). QTLs for ascochyta blight resistance in faba bean (Vicia faba L.): Validation in field and controlled conditions. Crop and Pasture Science, 67, 216–224. 10.1071/CP15227 [DOI] [Google Scholar]
  8. Attia, S. M. , El‐Hady, M. M. , Saber, H. A. , Omer, M. A. , Khalil, S. A. , … Ghannam, H. A. (2013). Misr 3, a new orobanche tolerant faba bean variety. Egyptian Journal of Plant Breeding, 17, 143–152. 10.12816/0004023 [DOI] [Google Scholar]
  9. Avila, C. M. , Atienza, S. G. , Moreno, M. T. , & Torres, A. M. (2007). Development of a new diagnostic marker for growth habit selection in faba bean (Vicia faba L.) breeding. Theoretical and Applied Genetics, 115, 1075. 10.1007/s00122-007-0633-y [DOI] [PubMed] [Google Scholar]
  10. Avila, C. M. , Nadal, S. , Moreno, M. T. , & Torres, A. M. (2006). Development of a simple PCR‐based marker for the determination of growth habit in Vicia faba L. using a candidate gene approach. Molecular Breeding, 17, 185–190. 10.1007/s11032-005-4075-4 [DOI] [Google Scholar]
  11. Avila, C. M. , Satovic, Z. , Sillero, J. C. , Rubiales, D. , Moreno, M. T. , & Torres, A. M. (2004). Isolate and organ‐specific QTLs for ascochyta blight resistance in faba bean. Theoretical and Applied Genetics, 108, 1071–1078. 10.1007/s00122-003-1514-7 [DOI] [PubMed] [Google Scholar]
  12. Avila, C. M. , Satovic, Z. , Sillero, J. C. , Rubiales, D. , Moreno, M. T. , & Torres, A. M. (2005). QTL detection for agronomic traits in faba bean (Vicia faba L.). Agriculturae Conspectus Scientificus, 70, 65–73.hrcak.srce.hr/910 [Google Scholar]
  13. Avila, C. M. , Sillero, J. C. , Rubiales, D. , Moreno, M. T. , & Torres, A. M. (2003). Identification of RAPD markers linked to Uvf‐1 gene conferring hypersensitive resistance against rust (Uromyces viciae‐fabae) in Vicia faba L. Theoretical and Applied Genetics, 107, 353–358. 10.1007/s00122-003-1254-8 [DOI] [PubMed] [Google Scholar]
  14. Ávila, C. M. , Ruiz‐Rodríguez, M. D. , Cruz‐Izquierdo, S. , Atienza, S. G. , Cubero, J. I. , & Torres, A. M. (2017). Identification of plant architecture and yield‐related QTL in Vicia faba L. Molecular Breeding, 37, 88. 10.1007/s11032-017-0688-7 [DOI] [Google Scholar]
  15. Benlloch, R. , Berbel, A. , Ali, L. , Gohari, G. , Millan, T. , & Madueño, F. (2015). Genetic control of inflorescence architecture in legumes. Frontiers in Plant Science, 6, 543. 10.3389/fpls.2015.00543 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Björnsdotter, E. , Nadzieja, M. , Chang, W. , Escobar‐Herrera, L. , Mancinotti, D. , Angra, D. , Khazaei, H. , Crocoll, C. , Vandenberg, A. , Stoddard, F. L. , O'Sullivan, D. M. , Stougaard, J. , Schulman, A. H. , Andersen, S. U. , & Geu‐Flores, F. (2020). VC1 catalyzes a key step in the biosynthesis of vicine from GTP in faba bean. bioRxiv, 2020.02.26.966523. 10.1101/2020.02.26.966523 [DOI] [PMC free article] [PubMed]
  17. Braich, S. , Sudheesh, S. , Forster, J. W. , & Kaur, S. (2017). Characterisation of faba bean (Vicia faba L.) transcriptome using RNA‐seq: Sequencing, de novo assembly, annotation, and expression analysis. Agronomy, 53(7). 10.3390/agronomy7030053 [DOI] [Google Scholar]
  18. Caracuta, V. , Weinstein‐Evron, M. , Kaufman, D. , Yeshurun, R. , Silvent, J. , & Boaretto, E. (2016). 14,000‐year‐old seeds indicate the Levantine origin of the lost progenitor of faba bean. Scientific Reports, 6, 37399. 10.1038/srep37399 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Carrillo‐Perdomo, E. , Raffiot, B. , Ollivier, D. , Deulvot, C. , Magnin‐Robert, J.‐B. , Tayeh, N. , & Marget, P. (2019). Identification of novel sources of resistance to seed weevils (Bruchus spp.) in a faba bean germplasm collection. Frontiers in Plant Science, 9, 1914. 10.3389/fpls.2018.01914 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Carrillo‐Perdomo, E. , Vidal, A. , Kreplak, J. , Duborjal, H. , Leveugle, M. , Duarte, J. , … Aubert, G. (2020). Development of new genetic resources for faba bean (Vicia faba L.) breeding through the discovery of gene‐based SNP markers and the construction of a high‐density consensus map. Scientific Reports, 10, 6790. 10.1038/s41598-020-63664-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Catt, S. C. , Braich, S. , Kaur, S. , & Paull, J. G. (2017). QTL detection for flowering time in faba bean and the responses to ambient temperature and photoperiod. Euphytica, 213, 125. 10.1007/s10681-017-1910-8 [DOI] [Google Scholar]
  22. Cernay, C. , Ben‐Ari, T. , Pelzer, E. , Meynard, J.‐M. , & Makowski, D. (2015). Estimating variability in grain legume yields across Europe and the Americas. Scientific Reports, 5, 11171. 10.1038/srep11171 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Cooper, J. W. , Wilson, M. H. , Derks, M. F. L. , Smit, S. , Kunert, K. J. , Cullis, C. , & Foyer, C. H. (2017). Enhancing faba bean (Vicia faba L.) genome resources. Journal of Experimental Botany, 68, 1941–1953. 10.1093/jxb/erx117 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Cruz‐Izquierdo, S. , Avila, C. M. , Satovic, Z. , Palomino, C. , Gutiérrez, N. , Ellwood, S. R. , … Torres, A. M. (2012). Comparative genomics to bridge Vicia faba with model and closely‐related legume species: Stability of QTLs for flowering and yield‐related traits. Theoretical and Applied Genetics, 125, 1767–1782. 10.1007/s00122-012-1952-1 [DOI] [PubMed] [Google Scholar]
  25. Díaz‐Ruiz, R. , Satovic, Z. , Ávila, C. M. , Alfaro, C. M. , Gutiérrez, M. V. , Torres, A. M. , & Román, B. (2009). Confirmation of QTLs controlling Ascochyta fabae resistance in different generations of faba bean (Vicia faba L.). Crop and Pasture Science, 60, 353–361. 10.1071/CP08190 [DOI] [Google Scholar]
  26. Díaz‐Ruiz, R. , Torres, A. , Gutiérrez, M. V. , Rubiales, D. , Cubero, J. I. , Kharrat, M. , … Román, B. (2009). Mapping of quantitative trait loci controlling Orobanche foetida Poir. Resistance in faba bean (Vicia faba L.). African Journal of Biotechnology, 8, 2718–2724. https://www.ajol.info/index.php/ajb/article/view/60839 [Google Scholar]
  27. Díaz‐Ruiz, R. , Torres, A. M. , Satovic, Z. , Gutiérrez, M. V. , Cubero, J. I. , & Román, B. (2010). Validation of QTLs for Orobanche crenata resistance in faba bean (Vicia faba L.) across environments and generations. Theoretical and Applied Genetics, 120, 909–919. 10.1007/s00122-009-1220-1 [DOI] [PubMed] [Google Scholar]
  28. Duc, G. (1997). Faba bean (Vicia faba L.). Field Crops Research, 53, 99–109. 10.1016/S0378-4290(97)00025-7 [DOI] [Google Scholar]
  29. Ellwood, S. R. , Phan, H. T. T. , Jordan, M. , Torres, A. M. , Avila, C. M. , Cruz‐Izquierdo, S. , & Oliver, R. P. (2008). Construction of a comparative genetic map in faba bean (Vicia faba L.); conservation of genome structure with Lens culinaris . BMC Genomics, 380(9). 10.1186/1471-2164-9-380 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. El‐Rodeny, W. , Kimura, M. , Hirakawa, H. , Sabah, A. , Shirasawa, K. , Sato, S. , … Isobe, S. (2014). Development of EST‐SSR markers and construction of a linkage map in faba bean (Vicia faba). Breeding Science, 64, 252–263. 10.1270/jsbbs.64.252 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Escobar‐Herrera, L. , Kreplak, J. , Nadzieja, M. , Terezol, M. , Desmetz, C. , Aubert, G. , & Andersen, S. U. (2020). The faba bean pan‐transcriptome. San Diego, USA: PAG XXVIII, Plant and Animal Genome. https://hal.inrae.fr/hal-02790834 [Google Scholar]
  32. Food and Agriculture Organization Corporate Statistical Database . (2019). Food and Agriculture Organization of the United Nations, Available online: faostat.fao.org (accessed on 21 October 2020).
  33. Gao, B. , Bian, X. C. , Yang, F. , Chen, X.‐M. , Das, D. , Zhu, X.‐R. , … Wu, C.‐F. (2020). Comprehensive transcriptome analysis of faba bean in response to vernalization. Planta, 251, 22. 10.1007/s00425-019-03308-x [DOI] [PubMed] [Google Scholar]
  34. Graf, R. J. , & Rowland, G. G. (1987). Effect of plant density on yield and components of yield of faba bean. Canadian Journal of Plant Science, 67(1), 1–10. 10.4141/cjps87-001 [DOI] [Google Scholar]
  35. Gutiérrez, N. , Avila, C. M. , Duc, G. , Marget, P. , Suso, M. J. , Moreno, M. T. , & Torres, A. M. (2006). CAPs markers to assist selection for low vicine and convicine contents in faba bean (Vicia faba L.). Theoretical and Applied Genetics, 114, 59–66. 10.1007/s00122-006-0410-3 [DOI] [PubMed] [Google Scholar]
  36. Gutiérrez, N. , Palomino, C. , Satovic, Z. , Ruiz‐Rodríguez, M. D. , Vitale, S. , Gutiérrez, M. V. , … Avila, C. M. (2013). QTLs for Orobanche spp. resistance in faba bean: Identification and validation across different environments. Molecular Breeding, 23, 909–922. 10.1007/s11032-013-9920-2 [DOI] [Google Scholar]
  37. Gutiérrez, N. , Avila, C. M. , & Torres, A. M. (2020). The bHLH transcription factor VfTT8 underlies zt2, the locus determining zero tannin content in faba bean (Vicia faba L.). Scientific Reports, 10, 14299. 10.1038/s41598-020-71070-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Gutiérrez, N. , & Torres, A. M. (2019). Characterization and diagnostic marker for TTG1 regulating tannin and anthocyanin biosynthesis in faba bean. Scientific Reports, 9, 16174. 10.1038/s41598-019-52575-x [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Herridge, D. F. , Peoples, M. B. , & Boddey, R. M. (2008). Global inputs of biological nitrogen fixation in agricultural systems. Plant and Soil, 311, 1–18. 10.1007/s11104-008-9668-3 [DOI] [Google Scholar]
  40. Hughes, J. , Khazaei, H. , & Vandenberg, A. (2020). Genetics of height and branching in faba bean (Vicia faba). Agronomy, 10, 1191. 10.3390/agronomy10081191 [DOI] [Google Scholar]
  41. Ijaz, U. (2018). Molecular mapping and microscopic analysis of faba bean‐Uromyces viciae‐fabae host‐pathogen interaction. PhD Thesis, The University of Sydney, Sydney, Australia. http://hdl.handle.net/2123/18416
  42. Kaur, S. , Pembleton, L. W. , Cogan, N. O. , Savin, K. W. , Leonforte, T. , Paull, J. , … Forster, J. W. (2012). Transcriptome sequencing of field pea and faba bean for discovery and validation of SSR genetic markers. BMC Genomics, 13(1), 104. 10.1186/1471-2164-13-104 [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Kaur, S. , Kimber, R. B. E. , Cogan, N. O. I. , Materne, M. , Forster, J. W. , & Paull, J. G. (2014). SNP discovery and high‐density genetic mapping in faba bean (Vicia faba L.) permits identification of QTLs for ascochyta blight resistance. Plant Science, 217‐218, 47–55. 10.1016/j.plantsci.2013.11.014 [DOI] [PubMed] [Google Scholar]
  44. Kaur, S. , Cogan, N. O. I. , Forster, J. W. , & Paull, J. G. (2014). Assessment of genetic diversity in faba bean based on single nucleotide polymorphism. Diversity, 6, 88–101. 10.3390/d6010088 [DOI] [Google Scholar]
  45. Khan, M. M. , Alghamdi, S. S. , Ammar, M. H. , Sun, Q. W. , Teng, F. , Migdadi, H. M. , & Al‐Faifi, S. A. (2019). Transcriptome profiling of faba bean (Vicia faba L.) drought‐tolerant variety hassawi‐2 under drought stress using RNA sequencing. Electronic Journal of Biotechnology, 39, 15–29. 10.1016/j.ejbt.2019.02.004 [DOI] [Google Scholar]
  46. Khazaei, H. (2014). Leaf traits associated with drought adaptation in faba bean ( Vicia faba L.). PhD Thesis, University of Helsinki, Helsinki, Finland. https://helda.helsinki.fi/handle/10138/135892
  47. Khazaei, H. , & Vandenberg, A. (2020). Seed mineral composition and protein content of faba beans (Vicia faba L.) with contrasting tannin contents. Agronomy, 10, 511. 10.3390/agronomy10040511 [DOI] [Google Scholar]
  48. Khazaei, H. , Link, W. , Street, K. , & Stoddard, F. L. (2018). ILB 938, a valuable faba bean (Vicia faba L.) accession. Plant Genetic Resources: Characterization and Utilization, 16, 478–482. 10.1017/S1479262118000205 [DOI] [Google Scholar]
  49. Khazaei, H. , O'Sullivan, D. M. , Sillanpää, M. J. , & Stoddard, F. L. (2014a). Use of synteny to identify candidate genes underlying QTL controlling stomatal traits in faba bean (Vicia faba L.). Theoretical and Applied Genetics, 127, 2371–2385. 10.1007/s00122-014-2383-y [DOI] [PubMed] [Google Scholar]
  50. Khazaei, H. , O'Sullivan, D. M. , Sillanpää, M. J. , & Stoddard, F. L. (2014b). Genetic analysis reveals a novel locus in Vicia faba decoupling pigmentation in the flower from that in the extra‐floral nectaries. Molecular Breeding, 34, 1507–1513. 10.1007/s11032-014-0100-9 [DOI] [Google Scholar]
  51. Khazaei, H. , O'Sullivan, D. M. , Jones, H. , Pitts, N. , Sillanpää, M. J. , Pärssinen, P. , … Stoddard, F. L. (2015). Flanking SNP markers for vicine‐convicine concentration in faba bean (Vicia faba L.). Molecular Breeding, 35(38). 10.1007/s11032-015-0214-8 [DOI] [Google Scholar]
  52. Khazaei, H. , Purves, R. W. , Song, M. , Stonehouse, R. , Bett, K. E. , Stoddard, F. L. , & Vandenberg, A. (2017). Development and validation of a robust, breeder‐friendly molecular marker for the vc − locus in faba bean. Molecular Breeding, 37, 140. 10.1007/s11032-017-0742-5 [DOI] [Google Scholar]
  53. Khazaei, H. , Stoddard, F. L. , Purves, R. W. , & Vandenberg, A. (2018). A multi‐parent faba bean (Vicia faba L.) population for future genomic studies. Plant Genetic Resources: Characterization and Utilization, 16, 419–423. 10.1017/S1479262118000242 [DOI] [Google Scholar]
  54. Khazaei, H. , Purves, R. W. , Hughes, J. , Link, W. , O'Sullivan, D. M. , Schulman, A. H. , … Stoddard, F. L. (2019). Eliminating vicine and convicine, the main anti‐nutritional factors restricting faba bean usage. Trends in Food Science and Technology, 91, 549–556. 10.1016/j.tifs.2019.07.051 [DOI] [Google Scholar]
  55. Lee, C. , Yu, D. , Choi, H.‐K. , & Kim, R. W. (2017). Reconstruction of a composite comparative map composed of ten legume genomes. Genes & Genomics, 39, 111–119. 10.1007/s13258-016-0481-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Link, W. , Balko, C. , & Stoddard, F. L. (2010). Winter hardiness in faba bean: Physiology and breeding. Field Crops Research, 115, 287–296. 10.1016/j.fcr.2008.08.004 [DOI] [Google Scholar]
  57. Luzzatto, L. , & Arese, P. (2018). Favism and glucose‐6‐phosphate dehydrogenase deficiency. The New England Journal of Medicine, 378, 60–71. 10.1056/NEJMra1708111 [DOI] [PubMed] [Google Scholar]
  58. Ma, Y. , Bao, S. , Yang, T. , Hu, J. , Guan, J. , He, Y. , … Zong, X. (2013). Genetic linkage map of Chinese native variety faba bean (Vicia faba L.) based on simple sequence repeat markers. Plant Breeding, 132, 397–400. 10.1111/pbr.12074 [DOI] [Google Scholar]
  59. Maalouf, F. , Ahmed, S. , Shaaban, K. , Bassam, B. , Nawar, F. , Singh, M. , & Amri, A. (2016). New faba bean germplasm with multiple resistances to ascochyta blight, chocolate spot and rust diseases. Euphytica, 211, 157–167. 10.1007/s10681-016-1726-y [DOI] [Google Scholar]
  60. Maalouf, F. , Hu, J. , O'Sullivan, D. M. , Zong, Z. , Hamwieh, A. , Kumar, S. , & Baum, M. (2019). Breeding and genomics status in faba bean (Vicia faba). Plant Breeding, 138, 465–473. 10.1111/pbr.12644 [DOI] [Google Scholar]
  61. Mokhtar, M. M. , Hussein, E. H. A. , El‐Assal, S. E. S. , & Atia, M. A. M. (2020). VfODB: A comprehensive database of ESTs, EST‐SSRs, mtSSRs, microRNA‐target markers and genetic maps in Vicia faba. AoB Plants, plaa064. 10.1093/aobpla/plaa064 [DOI] [PMC free article] [PubMed]
  62. Novák, P. , Guignard, M. S. , Neumann, P. , Kelly, L. J. , Mlinarec, J. , Koblížková, A. , … Leitch, A. R. (2020). Repeat‐sequence turnover shifts fundamentally in species with large genomes. Nature Plants, 6, 1325–1329. 10.1038/s41477-020-00785-x [DOI] [PubMed] [Google Scholar]
  63. Ocaña, S. , Seoane, P. , Bautista, R. , Palomino, C. , Claros, G. M. , Torres, A. M. , & Madrid, E. (2015). Large‐scale transcriptome analysis in faba bean (Vicia faba L.) under Ascochyta fabae infection. PLoS One, 10, e0135143. 10.1371/journal.pone.0135143 [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. O'Sullivan, D. M. , & Angra, D. (2016). Advances in faba bean genetics and genomics. Frontiers in Genetics, 7, 150. 10.3389/fgene.2016.00150 [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. O'Sullivan, D. M. , Angra, D. , Harvie, T. , Tagkouli, V. , & Warsame, A. (2019). A genetic toolbox for Vicia faba improvement. In International conference on legume genetics and genomics, may 13–17, 2019. Dijon: France. [Google Scholar]
  66. Picard, J. , Duc, G. , & Pelletier, R. (1985). “Côte d'Or”, a highly frost resistant population of Vicia faba . FABIS Newsletter, 13, 11–12. https://agris.fao.org/agris-search/search.do?recordID=QV8600169 [Google Scholar]
  67. Požárková, D. , Koblížková, A. , Román, B. , Torres, A. M. , Lucretti, S. , Lysák, M. , … Macas, J. (2002). Development and characterization of microsatellite markers from chromosome 1‐specific DNA libraries of Vicia faba . Biologia Plantarum, 45, 337–345. 10.1023/A:1016253214182 [DOI] [Google Scholar]
  68. Ramsay, G. , van de Ven, W. , Waugh, R. , Griffiths, D. W. , & Powel, W. (1995). Mapping quantitative trait loci in faba beans. In: AEP (Ed.), Improving production and utilization of grain legumes. Copenhagen, Denmark, 2nd European conference on grain legumes. pp 444–445.
  69. Ray, H. , & Georges, F. (2010). A genomic approach to nutritional, pharmacological and genetic issues of faba bean (Vicia faba): Prospects for genetic modifications. GM Crops, 1, 99–106. 10.4161/gmcr.1.2.11891 [DOI] [PubMed] [Google Scholar]
  70. Ray, H. , Bock, C. , & Georges, F. (2015). Faba bean: Transcriptome analysis from etiolated seedling and developing seed coat of key cultivars for synthesis of proanthocyanidins, phytate, raffinose family oligosaccharides, vicine, and convicine. The Plant Genome, 8(1). 10.3835/plantgenome2014.07.0028 [DOI] [PubMed] [Google Scholar]
  71. Rispail, N. , Kaló, P. , Kiss, G. B. , Ellis, T. H. , Gallardo, K. , Thompson, R. D. , … Rubiales, D. (2010). Model legumes contribute to faba bean breeding. Field Crops Research, 115, 253–269. 10.1016/j.fcr.2009.03.014 [DOI] [Google Scholar]
  72. Román, B. , Satovic, Z. , Avila, C. M. , Rubiales, D. , Moreno, M. T. , & Torres, A. M. (2003). Locating genes associated with Ascochyta fabae resistance in Vicia faba L. Australian Journal of Agricultural Research, 54, 85–90. 10.1071/AR02034 [DOI] [Google Scholar]
  73. Román, B. , Satovic, Z. , Pozarkova, D. , Macas, J. , Dolezel, J. , Cubero, J. I. , & Torres, A. M. (2004). Development of a composite map in Vicia faba L. breeding applications and future prospects. Theoretical and Applied Genetics, 108, 1079–1088. 10.1007/s00122-003-1515-6 [DOI] [PubMed] [Google Scholar]
  74. Román, B. , Torres, A. M. , Rubiales, D. , Cubero, J. I. , & Satovic, Z. (2002). Mapping of quantitative trait loci controlling broomrape (Orobanche crenata Forsk.) resistance in faba bean (Vicia faba L.). Genome, 45, 1057–1063. 10.1139/g02-082 [DOI] [PubMed] [Google Scholar]
  75. Sallam, A. , & Martsch, R. (2015). Association mapping for frost tolerance using multi‐parent advanced generation inter‐cross (MAGIC) population in faba bean (Vicia faba L.). Genetica, 143, 501–514. 10.1007/s10709-015-9848-z [DOI] [PubMed] [Google Scholar]
  76. Sallam, A. , Arbaoui, M. , El‐Esawi, M. , Abshire, N. , & Martsch, R. (2016). Identification and verification of QTL associated with frost tolerance using linkage mapping and GWAS in winter faba bean. Frontiers in Plant Science, 7, 1098. 10.3389/fpls.2016.01098 [DOI] [PMC free article] [PubMed] [Google Scholar]
  77. Sallam, A. , & Ul‐Allah, S. (2019). Genomics‐aided breeding for climate‐smart traits in faba bean. In Kole C. (Ed.), Genomic designing of climate‐smart pulse crops. Cham: Springer. 10.1007/978-3-319-96932-9_7 [DOI] [Google Scholar]
  78. Satovic, Z. , Torres, A. M. , & Cubero, J. I. (1996). Genetic mapping of new morphological, isozyme and RAPD markers in Vicia faba L. using trisomics. Theoretical and Applied Genetics, 93, 1130–1138. 10.1007/BF00230136 [DOI] [PubMed] [Google Scholar]
  79. Satovic, Z. , Avila, C. M. , Cruz‐Izquierdo, S. , Díaz‐Ruíz, R. , García‐Ruíz, G. M. , Palomino, C. , Gutiérrez, N. , Ocaña‐Moral, S. , Gutiérrez, M. V. , Cubero, J. I. , & Torres, A. M. (2013). A reference consensus genetic map for molecular markers and economically important traits in faba bean (Vicia faba L.). BMC Genomics, 14, 932. 10.1186/1471-2164-14-932 [DOI] [PMC free article] [PubMed]
  80. Scott, M. F. , Ladejobi, O. , Amer, S. , Bentley, A. R. , Biernaskie, J. , Boden, S. A. , … Mott, R. (2020). Multi‐parent populations in crops: A toolbox integrating genomics and genetic mapping with breeding. Heredity, 125, 396–416. 10.1038/s41437-020-0336-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  81. Sirks, M. J. (1931). Beiträge zu einer genotypischen analyse der ackerbohne, Vicia faba L. Genetica, 13, 209–636. 10.1007/BF01837054 [DOI] [Google Scholar]
  82. Sjödin, J. (1971). Induced morphological variation in Vicia faba L. Hereditas, 67, 155–180. 10.1111/j.1601-5223.1971.tb02371.x [DOI] [Google Scholar]
  83. Soltis, D. E. , Soltis, P. S. , Bennett, M. D. , & Leitch, I. J. (2003). Evolution of genome size in the angiosperms. American Journal of Botany, 90, 1596–1603. 10.3732/ajb.90.11.1596 [DOI] [PubMed] [Google Scholar]
  84. Sudheesh, S. , Kimber, R. B. E. , Braich, S. , Forster, J. W. , Paull, J. G. , & Kaur, S. (2019). Construction of an integrated genetic linkage map and detection of quantitative trait loci for ascochyta blight resistance in faba bean (Vicia faba L.). Euphytica, 42(215). 10.1007/s10681-019-2365-x [DOI] [Google Scholar]
  85. Surahman, M. (2001). The construction of genetic map of faba bean using RAPD markers. Indonesian Journal of Agronomy (Bul. Agron.), 29, 31–33. 10.24831/jai.v29i1.1539 [DOI] [Google Scholar]
  86. Torres, A. M. , Weeden, N. F. , & Martín, A. (1993). Linkage among isozyme, RFLP and RAPD markers in Vicia faba . Theoretical and Applied Genetics, 85, 937–945. 10.1007/BF00215032 [DOI] [PubMed] [Google Scholar]
  87. van de Ven, W. T. G. , Waugh, R. , Duncan, N. , Ramsay, G. , Dow, N. , & Powell, W. (1991). Development of a genetic linkage map in Vicia faba using molecular and biochemical techniques. Aspects of Applied Biology, 27, 49–54. [Google Scholar]
  88. Vaz Patto, M. C. , Torres, A. M. , Koblizkova, A. , Macas, J. , & Cubero, J. I. (1999). Development of a genetic composite map of Vicia faba using F2 populations derived from trisomic plants. Theoretical and Applied Genetics, 98, 736–743. 10.1007/s001220051129 [DOI] [Google Scholar]
  89. Warsame, A. O. , O'Sullivan, D. M. , & Tosi, P. (2018). Seed storage proteins of faba bean (Vicia faba L): Current status and prospects for genetic improvement. Journal of Agricultural and Food Chemistry, 66, 12617–12626. 10.1021/acs.jafc.8b04992 [DOI] [PubMed] [Google Scholar]
  90. Webb, A. , Cottage, A. , Wood, T. , Khamassi, K. , Hobbs, D. , Gostkiewicz, K. , … O'Sullivan, D. M. (2016). A SNP‐based consensus genetic map for synteny‐based trait targeting in faba bean (Vicia faba L.). Plant Biotechnology Journal, 14, 177–185. 10.1111/pbi.12371 [DOI] [PMC free article] [PubMed] [Google Scholar]
  91. Westengen, O. T. , Lusty, C. , Yazbek, M. , Amri, A. , & Asdal, Å. (2020). Safeguarding a global seed heritage from Syria to Svalbard. Nature Plants, 6, 1311–1317. 10.1038/s41477-020-00802-z [DOI] [PubMed] [Google Scholar]
  92. Wu, X. , Fan, Y. , Li, L. , & Liu, Y. (2020). The influence of soil drought stress on the leaf transcriptome of faba bean (Vicia faba L.) in the Qinghai–Tibet plateau. 3 . Biotech, 10, 381. 10.1007/s13205-020-02374-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  93. Yang, F. , Chen, H. , Liu, C. , Li, L. , Liu, L. , Han, X. , … Sha, A. (2020). Transcriptome profile analysis of two Vicia faba cultivars with contrasting salinity tolerance during seed germination. Scientific Reports, 10, 7250. 10.1038/s41598-020-64288-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  94. Yang, T. , Jiang, J. , Zhang, H. , Liu, R. , Strelkov, S. , Hwang, S.‐F. , … Zong, X. (2019). Density enhancement of a faba bean genetic linkage map (Vicia faba) based on simple sequence repeats markers. Plant Breeding, 138, 207–215. 10.1111/pbr.12679 [DOI] [Google Scholar]
  95. Zanotto, S. , Vandenberg, A. , & Khazaei, H. (2020). Development and validation of a robust KASP marker for zt2 locus in faba bean (Vicia faba). Plant Breeding, 139, 375–380. 10.1111/pbr.12772 [DOI] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.

Articles from Legume Science are provided here courtesy of Wiley

RESOURCES