Received: 22 February 2021 Revised: 25 March 2021 Accepted: 8 April 2021
DOI: 10.1002/leg3.95
OR I G I N A L A R T I C L E
The UCR Minicore: a valuable resource for cowpea research
and breeding
María Muñoz-Amatriaín1,2 | Sassoum Lo1,3 | Ira A. Herniter1,4 |
Ousmane Boukar5 | Christian Fatokun6 | M
arcia Carvalho7 | Isaura Castro7 |
Yi-Ning Guo1 | Bao-Lam Huynh8 | Philip A. Roberts8 | Valdemar Carnide7 |
Timothy J. Close1
1Department of Botany and Plant Sciences,
University of California, Riverside, Riverside, Abstract
California, USA Incorporation of new sources of genetic diversity into plant breeding programs is
2Department of Soil and Crop Sciences,
crucial for continuing to improve yield and quality, as well as tolerance to abiotic and
Colorado State University, Fort Collins,
Colorado, USA biotic stresses. A minicore (the “University of California, Riverside (UCR) Minicore”)
3Plant Sciences Department, University of composed of 368 worldwide accessions of cultivated cowpea has been assembled,
California, Davis, Davis, California, USA
having been derived from the UCR cowpea collection. High-density genotyping with
4Department of Plant Biology, Rutgers
University, New Brunswick, New Jersey, USA 51,128 SNPs followed by principal component and genetic assignment analyses
5International Institute of Tropical Agriculture, identified six subpopulations in the UCR Minicore, mainly differentiated by cultivar
Kano, Nigeria
group and geographic origin. All six subpopulations were present to some extent in
6International Institute of Tropical Agriculture,
Ibadan, Nigeria West African material, suggesting that West Africa is a center of diversity for
7Centre for Research and Technology of Agro- cultivated cowpea. Additionally, population structure analyses supported two routes
Environmental and Biological Sciences
of introduction of cowpea into the U.S.: (1) from Spain to the southwest U.S. through
(CITAB), University of Tr
as-os-Montes and
Alto Douro (UTAD), Vila Real, Portugal Northern Mexico and (2) from Africa to the southeast U.S. via the Caribbean.
8Department of Nematology, University of Genome-wide association studies (GWAS) narrowed several traits to regions
California, Riverside, Riverside, California, USA
containing strong candidate genes. For example, orthologs of the Arabidopsis
Correspondence FLOWERING LOCUS T lie within a major QTL for flowering time. In summary, this
María Muñoz-Amatriaín, Department of Soil
and Crop Sciences, Colorado State University, diverse, yet compact cowpea collection constitutes a suitable resource to identify loci
CO 80523, USA. controlling complex traits, consequently providing markers to assist with breeding to
Email: maria.munoz_amatriain@colostate.edu
improve this crop of high relevance to global food and nutritional security.
Funding information
FCT - Portuguese Foundation for Science and K E YWORD S
Technology, Grant/Award Number: cowpea, crop genomics, legume genomics
UIDB/04033/2020; National Science
Foundation, Grant/Award Number: IOS-
1543963; U.S. Department of Agriculture,
Grant/Award Number: Hatch Project CA-R-
BPS-5306-H; United States Agency for
International Development, Grant/Award
Number: AID-OAA-A-13-00070
María Muñoz-Amatriaín and Sassoum Lo contributed equally to this work.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium,
provided the original work is properly cited.
© 2021 The Authors. Legume Science published by Wiley Periodicals LLC.
Legume Science. 2021;1–15. wileyonlinelibrary.com/journal/legumescience 1
2 MUÑOZ-AMATRIAÍN ET AL.
1 | INTRODUCTION cowpea germplasm. Huynh et al. (2013) genotyped 442 cowpea land-
races, predominantly from Africa, with a 1536-SNP GoldenGate assay
Cowpea (Vigna unguiculata L. Walp) is a diploid (2n = 22) warm- (Muchero et al., 2009) and identified two major genepools, nominally
season legume of major importance for food and nutritional security. West versus Southeast Africa. Later, 768 accessions mostly from the
It provides a major source of dietary protein, fiber, minerals, and USDA cowpea collection were characterized using 5828 GBS
vitamins for millions of people in sub-Saharan Africa (SSA), and fodder (genotyping-by-sequencing) SNPs, revealing the presence of three
for livestock. Most of the production is in SSA by smallholder farmers, major subpopulations (Xiong et al., 2016), again one from West Africa,
most of whom are women. It is also grown in many other parts of the with the other two subpopulations separating Asian, European, and
world including Latin America, Southeast Asia, the Mediterranean some US accessions from those originating in India, Oceania, other
Basin, and the United States (FAOSTAT, www.fao.org). Cowpea is parts of Africa, and the Americas. More recently, the majority of an
well-known for its adaptation to heat and drought, and to soils with IITA minicore collection (298 accessions) was genotyped using GBS
low fertility, making it a successful crop in arid and semi-arid regions with 2276 SNPs, also identifying three major subpopulations (Fatokun
where most other crops do not perform as well (Boukar et al., 2019). et al., 2018), but with more dispersion of West and Central African
However, breeding for increased heat and drought tolerance as well accessions across the three sub-populations. Carvalho et al. (2017)
as for key agronomic traits and pest and disease-resistance is crucial genotyped a smaller set of 96 worldwide cowpea accessions empha-
as climate changes associated with global warming increase, and given sizing Iberian Peninsula germplasm, but at a much higher SNP density
that cowpea is primarily grown in regions that are quite vulnerable to using the Illumina Cowpea iSelect Consortium Array containing
climate change (Knox et al., 2012; Müller & Robertson, 2014). 51,128 SNPs (Muñoz-Amatriaín et al., 2017). In this latter work, logi-
Plant genetic resources constitute the raw material for crop cal relationships were noted between the genetic composition of
improvement. Cowpea is a genetically diverse crop species divided accessions and colonial-era movement of germplasm from the Iberian
into five cultivar groups: Unguiculata, Biflora, Melanophthalmus, Peninsula to the Caribbean, and from Africa to South America. In gen-
Sesquipedalis, and Textilis (Maréchal et al., 1978; Pasquet, 1998). eral, it is evident that there is much yet to be clarified regarding the
The largest cultivar groups are probably Unguiculata and spread of cowpeas worldwide, and the extent to which certain genetic
Melanophthalmus, which includes most grain and forage cowpeas, variants have taken hold in different regions at different times.
and Sesquipedalis, which is also known as “asparagus bean” or Here, we report the development of a minicore (henceforth
“yardlong bean” and is characterized by long and succulent pods that referred as the “UCR Minicore”) composed of 368 domesticated cow-
are consumed as a vegetable mostly in southeastern Asia (Boukar peas selected from a larger set of 
5000 accessions comprising the
et al., 2019; Maréchal et al., 1978; Xu et al., 2017). In addition to being UC Riverside cowpea collection. This minicore was genotyped using
grown for grain, cowpea is a source of nutritious fodder for livestock the 51,128-SNPs Cowpea iSelect Consortium Array (Muñoz-
in dry savanna regions of sub-Saharan Africa (Dugje et al., 2009). One Amatriaín et al., 2017) and the genotypic information was used to gain
important aspect of cowpea agronomy is the time to flowering, as a better understanding of the genetic diversity of domesticated cow-
early-maturing types can in many cases be deployed as a strategy to pea. Although this is the first summary report and full SNP data
capitalize on shortened periods of optimal growth, thus avoiding late- release for the UCR Minicore, this material has been utilized for more
season drought with its accompanying array of biotic stressors focused work on seed coat color (Herniter et al., 2018), seed coat pat-
(Boukar et al., 2019). tern (Herniter et al., 2019), seed size (Lo et al., 2019), bruchid resis-
Diverse cowpea germplasm is available from genebanks around tance (Miesho et al., 2019), plant herbivore resistance (Steinbrenner
the world, as partially summarized in Genesys (genesys-pgr.org/c/ et al., 2020) and pod shattering (Lo et al., under review). This study
cowpea). The largest germplasm collection, comprised of 15,933 evaluated additional traits of agronomic importance including
accessions, is located at the International Institute of Tropical Agricul- flowering time, dry pod weight, dry fodder weight, and pod load score.
ture (IITA) in Ibadan, Nigeria. Other large collections, considerably Genome-wide association studies (GWAS) were conducted, identify-
overlapping in content, are at the United States Department of ing significant SNPs and candidate genes associated with each of
Agriculture–Agricultural Research Service (USDA-ARS) Plant Genetic these traits.
Resources Conservation Unit (Griffin, Georgia, USA) with 8242 acces-
sions, the National Bureau of Plant Genetic Resources (NBPGR, New
Delhi, India) with 3704 accessions, and the University of California, 2 | MATERIALS AND METHODS
Riverside (UCR, California, USA) with about 5000 accessions. Manag-
ing and evaluating large germplasm collections is laborious and costly, 2.1 | Plant materials and phenotyping
and developing core and minicore subsets to facilitate access to the
diversity contained in the entire set of accessions is a common prac- A total of 668 accessions representing a core subset from the Univer-
tice in most ex situ collections (Brown, 1995; Byrne et al., 2018). sity of California Riverside (UCR) cowpea germplasm collection were
Genetic and phenotypic evaluations of diverse collections are genotyped with an Illumina GoldenGate assay (Muchero et al., 2009)
needed to fully utilize their potential in breeding programs. Several (1536-SNPs) in previous studies (Huynh et al., 2013; Muchero
previous studies have reported on the genetic diversity of cultivated et al., 2013). This SNP information, coupled with available phenotypic
MUÑOZ-AMATRIAÍN ET AL. 3
and passport data, was used to choose a smaller subset of non- Cowpea iSelect Consortium Array including 51,128 SNPs (Muñoz-
redundant accessions, each of which was highly homozygous, collec- Amatriaín et al., 2017) was used to genotype each DNA sample at the
tively representing the genetic and phenotypic diversity of the larger University of Southern California Molecular Genomics Core (Los
core collection. A few additional accessions nominated by cowpea Angeles, California, USA). SNPs were called in GenomeStudio
researchers and breeders based on regions of origin not represented (Illumina Inc., San Diego, California, USA) and manually curated to
among the core collection and possessing some specific traits were remove those with high levels (>25%) of missing data and/or hetero-
also included. The minicore of 368 accessions includes landraces and zygous calls. The highest percentage of heterozygosity for any acces-
breeding materials from 50 countries in Africa, Asia, North and South sion was 3.83% (Cp 4906), and 96% of the accessions had
America, Europe, and Australia (Table S1). Individual plants were heterozygosity levels below 1% (Table S2). The final dataset included
grown from each of the 368 accessions in a greenhouse at UCR for 48,425 polymorphic SNPs, 47,334 with known physical positions
genotyping (see Section 2.2) and seed production. Subsequent seed (Lonardi et al., 2019), on the 368 minicore samples (Table S2).
increases for distribution and phenotypic evaluations used seeds
directly descended from these genotyped plants.
The UCR Minicore was phenotyped for days to flowering (DTF) in 2.3 | Genetic diversity, population structure and
California (USA) under long-days at the UCR Citrus Research Center linkage disequilibrium analyses
and Agricultural Experiment Station in Riverside (CA) during the
summers of 2016 and 2017, as well as under short days at the UCR Expected heterozygosity (He) and nucleotide diversity (π) values were
Coachella Valley Agricultural Research Station in Thermal (CA) during calculated for all 48,425 SNPs in the minicore as a measure of genetic
P
the autumn of 2016. For the Riverside summer planting, daylight hours diversity. He was calculated asHe¼1 k 2i¼1Pi , where Pi is the fre-
(the time between sunrise and sunset) ranged from 14.4 hr on 21 June quency for the ith allele among a total of k alleles. π was evaluated as
to 11.9 hr on 30 September. For the Thermal autumn planting, daylight in Xu et al. (2017).
hours ranged from 12.8 hr on 1 September to 9.9 hr on 21 December. The admixture model implemented in STRUCTURE v2.3.4
Due to limited seed availability, 50 seeds of each accession were (Pritchard et al., 2000) was used to infer population structure of the
planted in single rows of 5.5–6.1 m long with 0.75 m spacing between UCR Minicore. Only SNPs with minor allele frequency (MAF) ≥ 0.05
rows at both locations. Scoring of the minicore was also conducted at were included in the analysis. STRUCTURE was first run three times
two locations in Nigeria during 2017. The minicore was sown in August for each hypothetical number of subpopulations (K) between 1 and
2017 at the International Institute of Tropical Agriculture (IITA) experi- 10, with a burn-in period of 10,000 followed by 10,000 Monte Carlo
mental field of Malamadori and Minjibir, near Kano, Nigeria. An alpha Markov Chain (MCMC) iterations. LnP(D) values were plotted and ΔK
lattice design with three replications was used. Each accession was values were calculated according to Evanno et al. (2005) to estimate
assigned to a plot of 2-m length. The distance between two consecu- the optimum number of subpopulations. Plots were generated with
tive plots was 0.75 m while two plants within a row were separated by Structure Harvester (Earl, 2012) (Figure S1). Then, a new run using a
0.20 m. The fertilizer NPK (15-15-15) was applied 2 weeks after plant- burn-in period of 100,000 and 100,000 MCMC iterations was con-
ing at the rate of 100 kg/ha. To control insect pests, the trial was ducted for the estimated K to assign accessions to subpopulations
sprayed with the insecticide Kartodim (Dimethoate 300 g + Lambda- based on a membership probability ≥0.80. In addition, principal com-
cyhalothrin 15 g) at the rate of 1.2 L/ha four times: once at each of veg- ponent analysis (PCA) and linkage disequilibrium (LD) analysis were
etative and at flower opening and twice during pod maturing. Manual conducted on the same SNP set using TASSEL v5 (Bradbury
weeding was performed twice to control weeds. At all locations, DTF et al., 2007).
was scored as the number of days from planting to when 50% of plants Linkage disequilibrium (LD) was estimated for each chromosome
had at least one flower opened. Pod load score was recorded at plant as the correlation coefficient r2 between pairs of SNPs, using SNPs
maturity using a 1–3 scale with 1 for high pod load (80–100%of pedun- with MAF ≥ 0.05 (42,711 SNPs). The decay of LD over physical dis-
cles had 2–3 pods per peduncle), 2 for moderate pod load (80%–100% tance was investigated by plotting pair-wise r2 values and generating
of peduncles had 1–2 pods per peduncle) and 3 for poor load score a locally weighted scatterplot smoothing (LOESS) curve in R. LD decay
(80%–100% of peduncles had 1 or less pod per peduncle). At maturity, distance was determined when r2 fell to the critical threshold esti-
dry podswere harvested, and the other above-ground parts of the plant mated from the 95th percentile r2 distribution for unlinked markers
(leaves, twigs, and stems) were cut and rolled up. Both the pods and the (r2 = 0.15).
fodder were sun dried for 1 week to determine dry podweight and fod-
der weight respectively.
2.4 | GWAS
2.2 | SNP genotyping and data curation The mixed linear model (Zhang et al., 2010) implemented in TASSEL
v.5 (Bradbury et al., 2007) (http://www.maizegenetics.net/tassel) was
Genomic DNA was extracted from young leaves of individual plants used for GWAS, with a population structure matrix (for K = 6) and a
using DNeasy Plant Kit (Qiagen, Valencia, California, USA). The kinship coefficient matrix accounting for population structure and the
4 MUÑOZ-AMATRIAÍN ET AL.
relatedness of accessions, respectively. A false discovery rate (FDR; Genotyping with the 51,128-SNP array (Muñoz-Amatriaín
Benjamini & Hochberg, 1995) threshold of 0.01 was used to identify et al., 2017) enabled analyses of genetic diversity in the minicore.
significant associations. The percentage contribution of each SNP to 94.7% of those SNPs (48,425) were polymorphic in the dataset.
the total phenotypic variation was calculated using marker R2 values Expected heterozygosity (He) and nucleotide diversity (π) were calcu-
from TASSEL multiplied by 100. Candidate genes within significant lated and both averaged 0.313 (the maximum for a biallelic SNP
regions were identified from annotations of the cowpea reference is 0.5).
genome v1.1 (https://phytozome.jgi.doe.gov/; Lonardi et al., 2019). The LD decay distance was also investigated for each cowpea
chromosome using SNPs with MAF ≥ 0.05. The decay of LD with
physical distance differed among chromosomes and ranged from
3 | RESULTS 809 kb on Vu05 to 4,705 kb on Vu10 (Figure S2). In addition to Vu05,
the LD decay distance was shortest in Vu08 (813 kb) and Vu07
3.1 | Diversity and linkage disequilibrium in the (1048 kb), while Vu01 and Vu04 had the largest decay distances after
UCR Minicore Vu10 (3803 and 3286 kb, respectively; Figure S2). On average there
was one SNP per 14.9 kb, indicating sufficient marker density
The UCR Minicore was developed to represent available genetic and for GWAS.
phenotypic diversity of cultivated cowpea while maintaining a sample
size that can be managed by most researchers and breeders for evalu-
ating traits of interest. This minicore is composed of 368 accessions 3.2 | Population structure of the UCR Minicore
from 50 countries including 242 landraces, 98 breeding lines, three
accessions categorized as “weedy,” and 25 accessions that are A total of 42,711 SNPs with MAF ≥ 0.05 were used to evaluate popu-
uncategorized (Table S1). It largely overlaps with the IITA minicore, lation structure in the UCR Minicore. STRUCTURE (Pritchard
with 233 accessions in common (Table S1), at least by name though et al., 2000) was run for K = 1–10 and the inspection of both the esti-
not necessarily by genetic identity. The UCR Minicore showed great mated log probabilities of the data and the ΔK values calculated as in
phenotypic diversity in pod and seed types and colors, flowering time Evanno et al. (2005) supported the presence of six genetic subpopula-
and maturity, leaf shape, and plant architecture, among other traits. tions (Figure S1). Accessions were assigned to each subpopulation
Figure 1 illustrates some of the morphological variation existing in the using a membership coefficient ≥0.8 (accessions with membership
UCR Minicore. coefficients less than 0.8 were considered “admixed”; Table S1). PCA
F IGURE 1 Phenotypic diversity in the UCR Minicore. Examples of diversity in (a) pod color and morphology and (b) seed coat color and
pattern
MUÑOZ-AMATRIAÍN ET AL. 5
also showed a clear separation of the six subpopulations on the first map, while the rest of the USA accessions were grouped together due
three principal components (Figure S3). to the lack of passport information about the state of origin for most
Subpopulation 1 included 31 accessions mostly from West Africa, of them. Their cultivar names, however, traced to U.S. southern states
29 of which are landraces (Table S1). Subpopulation 2 was the (Table S1). The figure graphically shows that while all subpopulations
smallest subpopulation by number of accessions: it included 12 breed- are present in West Africa, three of them (1, 2, and 5) are predomi-
ing lines developed at the International Institute of Tropical Agricul- nant. Accessions from Southeastern Africa have ancestry primarily
ture (IITA) in Nigeria. Subpopulation 3 was composed mostly of from Subpopulation 6, while most germplasm from Mediterranean
landraces from Mediterranean countries including Egypt, Italy, and countries belonged to Subpopulation 3. Interestingly, a closer look at
Portugal as well as accessions from California and Puerto Rico the germplasm from the USA indicates that accessions from California
(Table S1). Subpopulation 4 included 27 accessions that are mostly have ancestry mostly from Subpopulation 3, while accessions from
landraces from India, China and Papua New Guinea, among other other U.S. states are predominantly Subpopulation 6 (Figure 2).
countries. Passport data and visual examination of accessions in Subpopulation 4 is primarily from countries in Asia and Oceania.
Subpopulation 4 indicated that they belong to, or show some
characteristics of, cv.-gr. Sesquipedalis (yardlong bean). Subpopulation
5 contained 32 accessions from West Africa, most of which are 3.3 | GWAS of agronomic traits
landraces (Table S1). The largest subpopulation was Subpopulation
6 (69 accessions), which was composed primarily of landraces from GWAS was conducted for four different agronomic traits including
Southeastern Africa. The remainder of the accessions (165) were days to flowering (DTF), pod load score, dry pod weight, and dry fod-
considered “admixed” (Table S1). der weight using 42,711 SNPs with MAF ≥ 0.05 (see Section 2). DTF
Figure 2 shows the worldwide distribution of the six was evaluated in five different environments in the USA and Nigeria,
subpopulations, with each pie plot representing the proportion of the three of which are considered short-day environments (<12 hr of day-
six subpopulations contributing to accessions in each country. Acces- light) while the other two are considered long-day environments
sions within the USA were divided further based on the state they (>12 hr of daylight) (Table 1 and Section 2). Pod load score, dry pod
belonged to. Each accession from California is represented on the weight, and dry fodder weight were evaluated in one environment in
F IGURE 2 Population structure in the UCR Minicore. The geographical distribution of the accessions belonging to the minicore is shown,
with pie charts representing the average proportions from each genetic subpopulation for samples in each country. Pie chart sizes are
proportional to the number of samples in each country and range from 1 to 80 accessions. Accessions within the U.S. were further divided as
“California” and “other states/unknown,” as most accessions in this second group did not have state information but their cultivar names traced
to US southern states. The plot of ancestry estimates for K = 6 is shown at the bottom, with each bar representing the estimated membership
coefficients for each accession in each of the six subpopulations (represented by different colors)
6 MUÑOZ-AMATRIAÍN ET AL.
TABLE 1 Peak SNPs associated with DTF under five different environments. Asterisk on significant region (bp) indicates previously known
QTL for DTF, as discussed in the text
Peak Marker R2
Environment SNP Chr. Pos. (bp) log10(P) (%) Alleles Effect Significant region (bp)
Thermal (CA, USA) 2016 short days 2_34470 Vu05 371,674 6.34 8.04 A/T 1.97 371674*
2_19172 Vu05 7,227,977 5.66 6.22 A/G 4.69 7,227,977–7,307,028
2_12934 Vu05 48,154,437 4.83 5.27 A/G 5.87 48,133,655–
48,154,437
2_20025 Vu09 432,162 4.96 5.43 C/T 3.28 432,162
Malamadori (Nigeria) 2017 short 2_48517 Vu03 1,015,266 6.01 7.84 A/C 0.36 1,015,266
days 2_14813 Vu03 59,735,537 7.90 9.13 A/G 7.64 59,735,537–
59,977,049
2_25565 Vu05 48,009,565 5.30 5.95 A/G 5.04 48,009,565
2_20987 Vu06 17,607,676 6.08 8.07 C/T 0.03 17,607,676
2_24668 Vu06 20,504,149 4.74 5.39 A/C 4.55 20,504,149
2_11153 Vu11 1,198,243 6.29 8.18 C/T 0.33 1,198,243
Minjibir (Nigeria) 2017 short days 2_20613 Vu02 31,278,141 5.22 5.73 A/G 4.21 31,277,349–
31,278,141
2_21535 Vu03 55,851,743 4.80 5.22 G/T 3.97 55,851,743
2_36725 Vu04 5,412,353 4.85 5.28 A/G 4.40 5412353*
2_04587 Vu05 325,016 5.49 6.99 A/C 3.07 324,586–325,016
2_32475 Vu06 18,813,924 4.70 5.07 A/T 3.94 18,813,924
2_11041 Vu07 23,575,112 4.76 5.13 C/T 3.24 23,575,112
2_54333 Vu08 19,409,973 5.11 5.61 A/G 4.28 19,409,973
2_32074 Vu09 38,030,998 5.10 6.52 C/T 2.58 38,030,998
2_20047 Vu10 34,042,230 4.98 5.44 C/T 4.83 34,042,230
2_52041 Vu11 2,323,465 5.34 5.91 C/T 4.94 2,323,465–2,492,504
2_37762 Vu11 8,132,658 5.67 7.25 C/T 1.42 8,132,658–8,160,775
2_41002 Vu11 10,206,001 5.04 6.78 C/T 0.27 10,206,001
2_38223 Vu11 12,609,739 4.98 6.37 A/G 1.34 12,609,739–
12,645,337
2_53446 Vu11 24,211,875 5.80 8.88 G/T 0.92 24,211,875–
24,221,759
2_41544 Vu11 28,828,443 4.75 6.09 C/T 0.76 28,828,443–
29,242,341
2_17209 Vu11 30,941,563 4.69 5.07 C/T 3.99 30,941,563
Riverside (CA, USA) 2016 long days 2_30961 Vu02 21,081,330 4.84 6.83 C/T 5.21 21,081,330
2_41247 Vu03 36,439,344 4.81 6.78 C/T 6.19 36,439,344
2_06977 Vu04 9,211,195 5.47 7.95 A/C 11.12 9,211,195–9,263,427
2_22037 Vu09 5,939,066 4.74 6.66 C/T 6.34 5939066*
Riverside (CA, USA) 2017 long days 2_14784 Vu01 41,670,877 4.55 6.51 C/T 4.56 41,670,877
2_24857 Vu03 9,060,012 5.50 7.82 C/T 3.24 9,053,619–9,060,012
2_13459 Vu04 41,223,351 5.64 8.20 A/G 3.95 41,186,683–
41,263,744
2_13692 Vu09 972,787 4.76 5.75 A/G 6.90 972,787
2_15020 Vu09 28,247,527 4.55 6.51 A/G 2.31 28,247,527
2_23401 Vu09 41,393,052 6.57 9.25 A/G 3.29 41,152,886–
41,623,157
2_44213 Vu11 9,125,650 6.08 8.59 A/G 0.19 9,125,650
MUÑOZ-AMATRIAÍN ET AL. 7
TABLE 1 (Continued)
Peak Marker R2
Environment SNP Chr. Pos. (bp) log10(P) (%) Alleles Effect Significant region (bp)
2_53113 Vu11 10,177,688 5.04 7.18 A/G 2.36 10,177,688
2_05684 Vu11 12,871,428 4.87 6.95 A/G 1.99 12,871,428
2_06982 Vu11 37,711,373 5.67 8.03 C/T 3.39 37711373*
Nigeria. Significant marker-trait associations were identified for all identified at 5,939,066 bp on Vu09 in Riverside in 2016 (Table 1 and
traits and environments (Figures 3 and 4 and Tables 1 and 2 and S3 Figure 3). This position matches a QTL for DTF identified previously
and S4). in the same environment in the MAGIC population (Huynh
et al., 2018) as well as a flowering time QTL identified in a RIL popula-
tion derived from a cultivated x wild cross (CFt9; Lo et al., 2018).
3.3.1 | Days to flowering Vigun09g059700, which encodes a MADS-box protein and is
orthologous to the Arabidopsis AGAMOUS-LIKE 8 (AGL8) gene also
Considering all five environments, 91 significant SNPs at 40 genomic known as FRUITFULL (FUL), was identified 140 kb from this SNP.
regions were identified for DTF (Figure 3 and Table 1 and S3). Among Lastly, another of these five QTLs was associated with flowering
those 40 significant QTLs, 26 were associated with DTF under short under long days. This locus was detected at position 37,711,373 on
days in Thermal (California, USA) and both Malamadori and Minjibir Vu11 for the Riverside 2017 environment (Table 1 and Figure 3),
(Nigeria), while 14 were associated with DTF under long days in River- which is contained within a flowering time QTL previously identified
side (California, USA) (Figure 3 and Tables 1 and S3). The phenotypic in the same environment using the cowpea MAGIC population
variation of significant SNPs ranged from 5% to 9% (Tables 1 and S3). (Huynh et al., 2018). Two cowpea genes, Vigun11g169600 and
Five of the significant genomic regions corresponded to previ- Vigun11g169400, encoding AP2/B3-like transcription factor family
ously reported QTLs for DTF (Figure 3 and Table 1; Huynh proteins were identified at 128 and 139 kb from the peak SNP,
et al., 2018; Lo et al., 2018) while the rest are novel (Table 1 and respectively. These genes are orthologous to the Arabidopsis
Figure 3). Those five QTLs were investigated further by considering REDUCED VERNALIZATION RESPONSE 1 (VRN1), a major gene
gene model annotations in Phytozome (phytozome.jgi.doe.gov/) and involved in regulation of flowering and vernalization response.
the Legume Information System (LIS; www.legumeinfo.com). The res- In addition to these previously reported cowpea flowering time
olution of QTL positions was improved in the present work using QTLs, it is worth mentioning three other QTLs that contain or are
higher-density genotyping than previously, together with a larger and located near genes with clear roles in flowering. One is the QTL iden-
more diverse set of accessions. tified in Thermal in 2016 between 7,227,977–7,307,028 bp on Vu05
Several candidate genes stood out for these five QTLs, as follows. (Table 1 and Figure 3). The cowpea gene Vigun05g077400, encoding
One of the previously reported QTL was identified in Thermal 2016 a MADS-box protein orthologous to Arabidopsis AGAMOUS-like
and is located at the beginning of Vu05 (371,674 bp; Table 1). Just 20 (AGL20), is located 43.7 kb from the peak SNP (2_19172) for this
47 kb away from that position, another QTL was identified in Minjibir QTL. The second one is a QTL region spanning 470 kb (41,152,886 to
2017 between 324,586 bp and 325,016 bp (Table 1). These coordi- 41,623,157 bp) on Vu09 that was identified in Riverside in 2017, a
nates coincide with a QTL for DTF identified in a cowpea MAGIC long-day environment. This region contains 69 genes, among which
population also under short days (Huynh et al., 2018), and hence, they Vigun09g244300, encoding a protein of the BES1/BZR1 family, was
are likely to represent the same QTL. Only six genes were found found. This gene is orthologous to the Arabidopsis BRASSINAZOLE-
within this region (324,586–371,674 bp) including a cluster of four RESISTANT 1 (BZR1), which positively regulates the brassinosteroid
genes (Vigun05g004000, Vigun05g004100, Vigun05g004200, and signaling pathway (He et al., 2002). The third QTL of interest was also
Vigun05g004300) encoding the flowering locus protein T. Another of identified in Riverside in 2017; it was located on Vu03 between
these five DTF QTLs was identified by a SNP at 5,412,353 bp on 9,053,619 and 9,060,012 bp (Table 1 and Figure 3). The cowpea gene
Vu04 under short days in Minjibir in 2017 (Table 1 and Figure 3). This Vigun03g104200, which is an ortholog of the soybean E6, a main
position is contained within a QTL for flowering time under short days flowering and maturity gene, was identified 21-kb upstream of the
identified in the cowpea MAGIC population by Huynh et al. (2018). peak SNP (2_24857).
Genes near the significant SNP (2_36725) include Vigun04g057300,
encoding a circadian clock coupling factor ZGT, 
200 kb from this
SNP. Vigun04g057300 is an ortholog of the Arabidopsis Empfindlicher 3.3.2 | Pod load score, dry pod weight, and dry
im Dunkelroten Licht 1 (EID1) gene involved in the regulation of fodder weight
phytochrome-A light signaling (Marrocco et al., 2006).
Another of the five previously reported QTLs affects flowering Pod load score, dry pod weight, and dry fodder weight were evaluated
time under long-days. A single significant SNP (2_22037) was in Minjibir in 2017 (Nigeria). Correlations between these traits were
8 MUÑOZ-AMATRIAÍN ET AL.
F IGURE 3 Manhattan plots of genome-wide association studies (GWAS) on days to flowering in five different environments at four
locations. log10 (p values) are plotted against physical positions on the cowpea reference genome v1.1 (Lonardi et al., 2019). The dashed red line
in each plot indicates the 0.01 FDR-corrected threshold, ranging from 4.54 for Riverside, California (2017) to 4.62 for both Thermal, California
(2016), and Minjibir, Nigeria (2017). Blue arrows represent known QTLs for DTF
calculated using Pearson's correlation coefficient. A strong positive Arabidopsis CNGC19 gene. The encoded ion channel proteins mediate
correlation was observed between dry pod weight and dry fodder calcium signaling pathways involved in responses to abiotic and biotic
weight (0.93), while a moderate negative correlation was observed stresses, including response to herbivores, nematodes and heavy
between pod load score and dry fodder weight (0.45) as well as metals among others (Hammes et al., 2005; Jha et al., 2016; Meena
between pod load score and dry pod weight (0.48). Note that lower et al., 2019; Moon et al., 2019) (see Section 4).
pod load score numbers were given to plants with higher pod loads
(see Section 2).
A single QTL was identified for pod load score and dry pod 4 | DISCUSSION
weight on Vu04, while two QTLs on Vu04 were identified for dry fod-
der weight (Table 2, Figure 4, and Table S4). Interestingly, the major 4.1 | Population structure and historical crop
QTL for dry fodder weight coincides with the QTLs for pod load score dispersal
and dry pod weight (Table 2; Figure 4; Table S4). The colocation of
these QTLs together with the correlations between the three traits The UCR Minicore and its associated high-density SNP data (51,128
suggests pleiotropic effects of a single gene or the existence of closely SNPs) constitute a powerful combination of material and information
linked genes. resources to support genetic diversity analyses of cultivated cowpea.
Genes within this common QTL region which spans 125 kb were Six subpopulations were identified in this minicore, all of which were
explored. Eleven genes were identified, seven of which encode mem- represented to at least some extent in West African material
bers of the cyclic nucleotide-gated ion channel (CNGC) family of pro- (Figure 2). This indicates that West Africa is a center of diversity for
teins. Four of those seven genes (Vigun04g039300, Vigun04g039400, cultivated cowpea, as suggested by previous studies (Fatokun
Vigun04g039800, and Vigun04g039900) are orthologs to the et al., 2018; Padulosi & Ng, 1997; Steele, 1976). Five of the six sub-
Arabidopsis CNGC20 gene, also called CNBT1 (cyclic nucleotide- populations were composed mostly of landraces, while Subpopulation
binding transporter 1), while the other three (Vigun04g039500, 2 included cowpea lines only from IITA's cowpea breeding program.
Vigun04g039600, and Vigun04g039700) are orthologs to the Based on how the six subpopulations split at different K numbers, as
MUÑOZ-AMATRIAÍN ET AL. 9
F IGURE 4 Manhattan plots
of genome-wide association
studies (GWAS) on pod load
score, dry pod weight, and dry
fodder weight. log10 (p values)
are plotted against physical
positions on the cowpea
reference genome (Lonardi
et al., 2019). The dashed red line
in each plot indicates the 0.01
FDR-corrected threshold (4.62
for dry fodder weight and 4.63
for both pod load score and dry
pod weight)
TABLE 2 Peak SNPs associated with dry fodder weight, dry pod weight, and pod load
Trait Peak SNP Chr. Position (bp) log (P) Marker R210 (%) Alleles Effect Significant region (bp)
Pod load score 2_05691 Vu04 3,403,047 4.84 6.32 G/T 0.15 3,335,635–3,403,521
Dry pod weight 2_06769 Vu04 3,278,892 7.21 8.85 C/T 29.60 3,278,476–3,403,521
Dry fodder weight 2_05693 Vu04 3,403,521 7.34 10.39 C/T 20.87 3,278,476–3,403,521
2_02590 Vu04 37,245,973 4.75 6.64 A/G 9.43 37,245,973
illustrated in Herniter et al. (2020), it appears that Subpopulation 2 is 5 accessions did not flower under long-days) (Table S1). Other work
the result of crosses between materials from Subpopulations 1 and reported that Subpopulation 1 had much more pod shattering than
5. Subpopulations 1 and 5 are composed almost exclusively of West Subpopulation 5 accessions (Lo et al., under review). In addition, all
African accessions. A closer inspection of landraces from Subpopula- accessions in Subpopulation 1 have smooth seed coats, while most in
tions 1 and 5 revealed consistent differences in several traits. For Subpopulation 5 have rough coats (data not shown). Seed coat texture
example, Subpopulation 1 accessions flowered earlier than those in is an important quality trait that influences seed end-use; rough seed-
Subpopulation 5 (8 days earlier on average in short-day environments) coated varieties are preferred for food preparations requiring seed
and had decreased photoperiod sensitivity (most Subpopulation coat removal (e.g., making of Akara) as rough seed coats can be easily
10 MUÑOZ-AMATRIAÍN ET AL.
removed after soaking, while varieties with smooth seed coats are certainly would preclude the detection of additional subpopulation
often preferred when cowpea is consumed as boiled intact seed structure present in that region.
(Singh & Ishiyaku, 2000). Also, rough seed coat types imbibe water
quicker and generally have reduced cooking times compared to
smooth seed coat types. 4.2 | Flowering time
Genotyping of the UCR Minicore has shed light on the history of
cowpea in USA. Landraces and their breeding derivatives from Califor- Flowering time is one of the most important agronomic traits, which
nia belong to Subpopulation 3, which is composed mostly of landraces affect environmental adaptation and yield potential. It is controlled by
from Mediterranean countries, while accessions from other multiple genes via different pathways, and it is influenced by environ-
U.S. states were predominantly from Subpopulation 6, which is com- mental conditions (Fornara et al., 2010).
posed mostly of landraces from Southeastern Africa. This population Cowpea is generally a short-day plant and, although some acces-
structure, together with textual evidence summarized by Herniter sions are day-neutral (photoperiod-insensitive), many cowpea geno-
et al. (2020), is consistent with a global dispersal of cowpea from its types are photoperiod sensitive and show a delay in flowering under
centers of domestication in West and East Africa along historical trade long day conditions (Craufurd et al., 1996; Ehlers & Hall, 1996). The
routes. For the USA, cowpea appears to have arrived through at least degree of photoperiod sensitivity can vary between accessions and is
two distinct introduction routes. It is believed that in the US South- influenced by temperature (Ehlers & Hall, 1996). Understanding the
west, cowpea was first introduced by the Spanish explorer Hernando underlying genetic factors of cowpea flowering time is important for
de Alcoro
n in 1540 going northward from Mexico, possibly followed the use of diverse germplasm to customize varieties for different
in the late 1600's by the Jesuit monk Eusebio Kino, including acces- environments.
sions that were popular in the Mediterranean basin during those times GWAS using the UCR Minicore has enabled the identification of
(Castetter & Bell, 1942; Herniter et al., 2020). In the Southeastern many loci and meaningful candidate genes associated with flowering
United States, cowpea seems to have been brought on slave ships, under both short and long days. Five of the significant regions coin-
perhaps as provisions. The two distinct introduction routes of appar- cide with QTLs reported in previous studies (Huynh et al., 2018; Lo
ently genetically distinct cowpeas contrast with older studies pre- et al., 2018). Overall, these results are consistent with polygenic con-
dating genotyping, which have often assumed a single introduction. trol of flowering time in cowpea.
This conjecture of more than one route of cowpea introductions into One of the main flowering time regions identified under short-
the USA, and genetic distinctions between them that now are evident, day conditions (and two different environments) was on Vu05. A clus-
is further supported by the findings of Carvalho et al. (2017), which ter of four genes (Vigun05g004000, Vigun05g004100,
showed relationships between a Cuban and Mediterranean acces- Vigun05g004200, and Vigun05g004300) annotated as FLOWERING
sions, and between sub-Saharan African and South American LOCUS T (FT) are in this region. Vigun05g004000 and
accessions, which represent yet another route of colonial-era dispersal Vigun05g004100 are orthologous to the Arabidopsis flowering gene
of cowpeas. TWIN SISTER OF FT (TSF; AT4G20370.1), which is a close relative of
Although the germplasm utilized in this study largely overlaps FT, whereas Vigun05g004200 and Vigun05g004300 are orthologs
with that utilized by Huynh et al. (2013), only two genetic clusters of the Arabidopsis FT (AT1G65480.1) gene. TSF and FT are main floral
were identified in that previous study which correspond to the two pathway integrators and play overlapping roles in the promotion of
major “West Africa” and “Southeastern Africa” gene pools. As shown flowering (Fornara et al., 2010;Kobayashi et al., 1999 ; Yamaguchi
by Herniter et al. (2020) utilizing this same UCR Minicore material, at et al., 2005). They share a similar mode of regulation, and over-
K = 2 Subpopulation 6 (Southeastern Africa gene pool) splits from the expression of both FT and TSF results in precocious flowering
rest of the subpopulations, confirming that as a primary genetic differ- (Kobayashi et al., 1999; Yamaguchi et al., 2005). The identification of
entiation between subpopulations of domesticated cowpeas. The multiple copies of FT genes in the cowpea reference genome (Lonardi
smaller number of SNPs that were available for Huynh et al. (2013) to et al., 2019) suggests that copy number variation could play an impor-
conduct population structure analyses, together with an emphasis on tant role in the regulation of flowering time in cowpea, as reported for
African landraces among accessions genotyped, most likely precluded other crops (Díaz et al., 2012; Nitcher et al., 2013). Interestingly, in
further subdivision of the West African subpopulation. the cold-season legume chickpea a cluster of three FT genes has been
Carvalho et al. (2017) has been the only previous study to geno- identified under a major QTL controlling flowering time under short-
type a set of cowpea accessions at a high density (51,128 SNPs). day conditions (Ortega et al., 2019). Authors showed a collectively
Although their focus was on genetic diversity of Iberian Peninsula higher expression of the FT genes in the early-flowering domesticated
cowpeas, results from that study largely agree with the findings lines respect to the late-flowering wild chickpea. Also, the flowering
reported in the present work. In particular, Subpopulations 1, 2, and time QTL co-located with QTLs for growth habit and branching index,
3 from the study of Carvalho et al. (2017), correspond to Subpopula- suggesting a possible involvement of FT genes in plant architecture as
tions 4, 3, and 6 reported here, respectively. Their fourth seen in other crops including Medicago truncatula (Laurie et al., 2011).
subpopulation was composed only of four accessions from West Another main flowering time locus identified under short days
Africa. This small representation of germplasm from West Africa was located near Vigun04g057300, which is an ortholog of the
MUÑOZ-AMATRIAÍN ET AL. 11
Arabidopsis gene EID1. In Arabidopsis, EID1 mutations caused alter- RESISTANT 1 (BZR1), one of the main regulators of the
ations in flowering induction (Marrocco et al., 2006). EID1 encodes an brassinosteroid signaling pathway (He et al., 2002). In Arabidopsis,
F-box protein that is a negative regulator in phytochrome A (phyA)- brassinosteroid signaling inhibits the floral transition and promotes
specific light signaling (Dieterle et al., 2001). Mutations in EID1 caus- vegetative growth. Furthermore, brassinosteroid-deficient mutants
ing the deceleration of the circadian clock have been selected during cause a strong delay in days to flowering (Li et al., 2018). Lastly,
tomato domestication (Müller et al., 2016). Phytochrome modulation another QTL was found on Vu03 near Vigun03g104200, an ortholog
by environmental factors to control flowering time appears to be of the soybean E6 gene, which affects both flowering and maturity
widespread in plants including cowpea (Mutters et al., 1989), where (Li et al., 2017; Sedivy et al., 2020). E6 plays an important role in the
genetic variability related to EID1 potentially has been an important long-juvenile trait (delayed flowering) in soybean (Bonato &
component of domestication. Vello, 1999).
A third QTL identified under a short-day environment on Vu05
was near Vigun05g077400, which is an ortholog of the Arabidopsis
AGAMOUS-like 20 (AGL20) gene. AGL20 is an integrator of different 4.3 | Plant productivity traits
pathways controlling flowering and is considered a central component
for the induction of flowering (Borner et al., 2000; Lee et al., 2000). Pod load score, dry pod weight, and dry fodder weight are important
Overexpression of AGL20 in Arabidopsis suppresses late flowering traits related to plant productivity. A cowpea genotype with high pod
and delays phase transitions from the vegetative stages of plant load (i.e., low pod load score) demonstrates high grain yield potential.
development (Borner et al., 2000; Lee et al., 2000). High pod load is a result of a high number of pods per plant, which is
Under the long-day conditions of Riverside (CA, USA), most of an indication of low rate of flower abortion. Generally, low flower
the accessions in the UCR Minicore showed a delay in flowering, and abortion is associated with resistance to insect attack (typically
about one fourth of the minicore did not flower (Table S1). Under long flower thrips or maruca) and high night temperatures (>18C) (Patel &
days, a major flowering time QTL was identified on Vu09 near Hall, 1990). Negative correlations have been identified between pod
Vigun09g059700, an ortholog of the Arabidopsis AGL8/FUL gene. load score and dry pod weight, as well as between pod load score and
Vigun09g059700 is also an ortholog of the common bean gene number of pods per plant, and between pod load score and grain yield
Phvul.009G203400, which is a candidate for a photoperiod response (Garcia-Oliveira et al., 2020). The negative correlation between pod
QTL (DTF-9.5) identified in an Andean RIL population (Gonz
alez load score and grain yield holds true as long as no attack by pod suck-
et al., 2021). AGL8/FUL encodes a MADS-box family transcription fac- ing bugs occurs, and in such a situation selection of high grain yielding
tor that regulates inflorescence development and is negatively regu- genotypes can be made using pod load score. However, there are high
lated by APETALA1 in Arabidopsis (Mandel & Yanofsky, 1995). In positive correlations between dry pod weight and grain yield. In some
addition, AGL8/FUL promotes floral determination in response to far- studies, dry pod weight has been negatively correlated with dry fod-
red-enriched light (Hempel et al., 1997). Loss of AGL8/FUL function in der weight (Samireddypalle et al., 2017; Singh et al., 2003) except for
Arabidopsis caused a delay in flowering time (Ferr
andiz et al., 2000; some lines with dual purpose characteristics (Boukar et al., 2016;
Melzer et al., 2008), suggesting that the cowpea ortholog of FUL Timko & Singh, 2008).
(Vigun09g059700) could similarly be involved in the response to We identified one major QTL associated with pod load score, dry
photoperiod. pod weight, and dry fodder weight. Seven genes encoding members
Another region associated with flowering under long day was of the CNGC family proteins were located within the QTL region: four
identified near genes Vigun11g169600 and Vigun11g169400. Both of them (Vigun04g039300, Vigun04g039400, Vigun04g039800, and
genes encode AP2/B3-like transcription factors that are orthologs to Vigun04g039900) are orthologs of the Arabidopsis CNGC20 gene, also
the Arabidopsis VRN1 gene. VRN1, a close homolog of FUL, promotes called CNBT1 (cyclic nucleotide-binding transporter 1), which is
flowering after prolonged cold (vernalization) in different plant species involved in the response to nematodes (Jha et al., 2016; Kaupp &
(Levy et al., 2002; Lü et al., 2015; Putterill et al., 2004; Sung & Seifert, 2002). The other three (Vigun04g039500, Vigun04g039600,
Amasino, 2005; Yan et al., 2003). It is intriguing to identify a and Vigun04g039700) are orthologs of the Arabidopsis CNGC19 gene,
vernalization-pathway gene in a warm-season legume that does not which is involved in herbivore response (Jha et al., 2016; Meena
need to undergo vernalization before flowering. However, vernaliza- et al., 2019). Interestingly, this region corresponds to the major Rk
tion pathway genes have been identified in other warm-season plants locus for root-knot nematode resistance identified in cowpea (Huynh
including soybean (Lü et al., 2015). In particular, Glyma11g13220, et al., 2016; Ndeve et al., 2019). However, the authors are not aware
which was a homolog of the Arabidopsis VRN1, was responsive to of any nematode infestation or herbivore damage at the Minjibir field
photoperiod as well as to low temperatures in soybean. This vernaliza- location. Members of the CNGC family of proteins have also been
tion pathway gene could also be functional in cowpea. involved in plant tolerance to heavy metals (Moon et al., 2019).
The cowpea gene Vigun09g244300, located on Vu09 and CNGC20 and CNGC19 are Ca2+permeable channels, which play essen-
encoding a protein of the BES1/BZR1 family, is another strong candi- tial roles in the regulation of plant immunity and the response to abi-
date gene for days to flowering under long-day conditions. otic stresses and thereby may influence plant productivity.
Vigun09g244300 is an ortholog of the Arabidopsis BRASSINAZOLE- Interestingly, three CNGC calcium channels (a, b, and c) are involved in
12 MUÑOZ-AMATRIAÍN ET AL.
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