Modern agriculture intensely selects aboveground plant structures, while often neglecting belowground features, and evolutionary tradeoffs between these traits are predicted to disrupt host control over microbiota. Moreover, drift, inbreeding, and relaxed selection for symbiosis in crops might degrade plant mechanisms that support beneficial microbes. We studied the impact of domestication on the nitrogen fixing symbiosis between cowpea and root-nodulating Bradyrhizobium. We combined genome-wide analyses with a greenhouse inoculation study to investigate genomic diversity, heritability, and symbiosis trait variation among wild and early-domesticated cowpea genotypes. Cowpeas experienced modest decreases in genome-wide diversity during early domestication. Nonetheless, domesticated cowpeas responded efficiently to variation in symbiotic effectiveness, by forming more root nodules with nitrogen-fixing rhizobia and sanctioning non-fixing strains. Domesticated populations invested a larger proportion of host tissues into root nodules than wild cowpeas. Unlike soybean and wheat, cowpea showed no compelling evidence for degradation of symbiosis during domestication. Domesticated cowpeas experienced a less severe bottleneck than these crops and the low nutrient conditions in Africa where cowpea landraces were developed likely favored plant genotypes that gain substantial benefits from symbiosis. Breeders have largely neglected symbiosis traits, but artificial selection for improved plant responses to microbiota could increase plant performance and sustainability.

Data Collection:

Inoculation Experiments — Seeds were surface sterilized in bleach (5% sodium hypochlorite), rinsed in sterile ddH₂O, scarified, and planted in bleach-sterilized 1-gallon plastic pots containing an autoclave-sterilized 50:50 mix of silica sand and limestone flour silica sand, which contains negligible nutrients to support plant growth (Regus et al., 2015). Three seeds were planted per pot from 06/13/2018 to 06/15/2018. Greenhouse temperatures averaged 86 °F + 14 °F (standard error, SE) and relative humidity was 55% + 20%. On 6/21/2018 seedlings were thinned to one plant per pot to size match the remaining seedlings among plant lines. One day later rhizobial inoculation followed.

For the clonal strain experiment, Fix+ and Fix- strains were plated on a modified arabinose gluconate medium (MAG; Sachs et al. 2009) and a single colony per strain was spread onto 8-10 plates to generate dense lawns. After 7 days of growth the cells were washed from the plates into liquid MAG media and cell concentrations were quantified by colorimetry. Liquid cultures were centrifuged at ~750g, spent media was removed, and the cells were resuspended in sterile ddH₂O at a concentration of 1 x 10⁸ cells ml^-1. Plants were inoculated with either 5 ml of the Fix+ or Fix- clonal Bradyrhizobium cells (single inoculation, 5 x 10⁸ cells), 5 ml of a mixture comprising equal concentrations of both strains (co-inoculation, 2.5 x 10⁸ cells of each strain), or 5 ml sterile ddH₂O as a control.

To investigate variation in symbiosis traits with other symbionts within a microbial community we performed a soil inoculation experiment Field soil was sampled from the University of California Riverside Agricultural Experiment Station at four sites within a 5-acre field where diverse cowpeas are propagated (coordinates: 33.967, -117.339; Huynh et al. 2018). The field has a history of cultivating cowpea during odd-numbered years, starting 2003. Additionally, the field is intercropped with barley and occasionally with other legume crops such as soybean and pigeonpea.Soil was passed through a sterilized 2mm sieve (6L per site), and apportioned into aliquots of 400g. From each sample, 400mL of sterile water was added, the sieved soil was shaken vigorously, filtered twice through 8 layers of sterile cheesecloth, and the filtered supernatants were pooled into sterile flasks, which were allowed to settle overnight at room temperature to inoculate with microbes in water and avoid sediments (Unkovich and Pate 1998). The supernatant from each flask was divided into two equal portions, one of which was autoclaved and allowed to cool to serve as a negative control, while the other was reserved at room temperature and used for inoculation. Seedlings were inoculated with 10mL of each microbial inoculum (alive or dead) and each one was separately plated (100ul) in MAG and incubated at 29°C for eight days to confirm high densities of slow growing bacteria like Bradyrhizobium.

In both experiments, plants were fertilized weekly by applying 10 ml of Jensen’s solution with 1 g/L K¹⁵NO₃ (2% ¹⁵N by weight), which includes all the necessary micronutrients (Somasegaran and Hoben 1985), and a minimal concentration of nitrogen to support cowpea growth. Plant genotypes and inoculation treatments were randomly arranged within blocks in the greenhouse with five plant replicates per inoculation treatment x plant genotype combination, except for controls that had 3 replicates. The clonal strain experiment had 360 plants, including 300 that were inoculated (20 lines x 3 inoculation treatments x 5 replicates) and 60 control plants (20 lines x 3 replicates). The soil inoculation experiment had 160 plants, including 100 that received the live inoculum (20 lines x 5 replicates) and 60 that received the autoclaved control (20 lines x 3 replicates).

Plant harvest and nodule culturing – All plants were harvested during the course of three weeks, from 7/30/2018 to 8/3/2018 and from 8/13/2018 to 8/23/2018. Plants were removed from pots, washed free of sand, and dissected into root, shoot, and nodule portions. Nodules were counted and photographed. Rhizobia were sub-cultured from nodules of co-inoculated plants to differentiate Fix+ and Fix- strains. Nodules were crushed and streaked on MAG and isolated colonies were subcultured on MAG with rifampicin (500 μg ml^-1) and streptomycin (1000 μg ml^-1), selecting for Fix+, and YM media, on which Fix- exhibit fast growth and slimy appearance. Five nodules each from three co-inoculated plants per genotype were randomly picked and assessed (~15 nodules per genotype, 268 total). From each nodule, ~50 colonies were counted to estimate the proportion of Fix+ to Fix- strains (11,586 colonies in total).

Leaf ¹⁵N ‘atom per cent difference’, a measure of nitrogen fixation (Regus et al. 2014), was estimated as the percentage of ¹⁵N atoms over total nitrogen in each sample (Unkovich et al. 2008). The δ¹⁵N of each sample was calculated by comparing ¹⁵N abundance expressed as parts per thousand relative to atmospheric N₂, these values were used to compare among plants inoculated with Fix+ and Fix- strains following the formula:

 δ¹⁵N ‰ =  sample atom%15N - 0.36630.3663 x 1000

To calculate these values individual leaves of each plant were oven dried, powdered using steel bead beaters at 14,000 rpm, and 4 mg per plant was transferred into individual tin capsules, including four replicates per genotype for the Fix+, Fix- and two replicates for control inoculation treatments (178 samples total). Isotopic analyses were performed at the UC Davis Stable Isotope Facility.

Data Processing:

Genome-wide variation of Cowpea accessions – To examine genetic variation and admixture between wild and cultivated cowpea we performed a combined analysis of 380 landraces and 58 wild cowpea accessions reported in Huynh et al. (2013) using the 1536-SNP GoldenGate genotyping assay. Huynh et al. (2013) analyzed wild and domesticated genotypes separately, with a focus on geographic origin. To maintain consistency with Huynh et al. 2013, SNPs with a minimum allele frequency (MAF) < 0.05 and with a call rate < 0.90 were discarded, for a final filtered set of 920 SNPs. Genetic differentiation was evaluated using a principal component analysis (PCA) with the package adegenet (Jombart, 2008). Admixture and structure were examined using the R package LEA (Frichot et al. 2014; Frichot and François 2015). One to ten ancestral populations (i.e., entropy criterion; K = 1 to 10) were assumed using 100 repetitions. To test if patterns of genetic diversity differed among populations, a generalized mixed model analysis using SNP loci as our random factor was implemented (Costa et al. 2021; Theodorou et al. n.d.). The GLMM with a Beta distribution and a logit link function was modeled using the package glmmTMB (Brooks et al. 2017; Douma and Weedon 2019). Post-hoc comparisons based on the model were performed with the R package emmeans (Searle et al. 2012). Population statistics were estimated with the R package hierfstat (Goudet 2005). 

To have a more robust estimation of the genomic-level variation and relationships among the twenty focal cowpea lines, we further genotyped the wild accessions using the Illumina Cowpea iSelect Consortium Array, screening 51,128 SNPs across the cowpea genome. Domesticated accessions were previously genotyped with the same array (Muñoz-Amatriaín et al, 2017). SNPs with a MAF < 0.1 and with a call rate < 0.95 were discarded using the R package snpReady (Granato et al. 2018), for a final filtered set of 34,762 SNPs. Pairwise genetic distances were estimated with the R package adegenet (Jombart 2008) and neighbor-joining was used to reconstruct phylogenetic relationships. Branch support values were evaluated by a bootstrap analysis where SNPs were sampled with replacement 100 times using the phylo.boot function of the package ape (Paradis and Schliep 2018).

Trait data analysis – Size comparisons among wild and domesticated populations were performed by calculating scale free measurements to minimize effects of initial seedling size. Investment into symbiosis was calculated by dividing the dry nodule biomass of each plant over the total biomass. Host growth response was calculated by subtracting the mean biomass values (i.e., shoot, root, and nodules) of the control plants within a population from the inoculated plants belonging to the same group, dividing by the control value, and multiplying the quotient by 100 (Regus et al. 2015). Means per population were calculated for plants harvested during the same week to account for variation in days post inoculation.

Host Growth Response %=Total biomass inoculated plant_i-Mean biomass controls_jMean biomass controls_j  x 100

Where i indicates plant replicate and j indicates population mean value.

Dry nodule biomass values of co-inoculated plants (where a subset of nodules was used for subculturing) were inferred by generating a wet-to-dry nodule weight linear regression (per genotype). To test for post-infection sanctions, a binomial test was used to evaluate whether nodule occupancy of Fix+ deviated from the null expectation of 50% given that the strains were inoculated in equal proportions. Results were analyzed independently for each genotype tested.

Linear mixed models (LMMs) were used to analyze differences in symbiosis traits among the three populations defined by Huynh and colleagues (2013), i.e., Genepool-1, 2, and wild cowpeas (three-population analysis). However, because landraces of Genepool-1 and 2 are each most closely related to wild cowpeas from the same region (Huynh et al., 2013), we also analyzed comparisons that divided the wild cowpeas into southern Africa populations (PI632890, PI632876, PI632892, PI632891; i.e., Wild-1) and northern Africa populations (PI632882, PI632879, PI632880, PI632881; i.e., Wild-2, four-population analysis). Inoculation treatment and population were treated as fixed effects, cowpea genotype and genotype x treatment interactions were treated as random effects, and days post inoculation was used as a covariate. Response variables were transformed if necessary, to improve normality. Analyses were performed using The R project for Statistical Computing version 3.6.1 (R Core Team 2020).

Components of trait variation – Independent linear mixed models were constructed to estimate the components of variation in each symbiosis trait under the clonal inoculation treatments, where genotypic effects could be best isolated. Models of variance-covariance structure were used to test whether the expression of additive genetic variance (s²_a) in each symbiosis trait varied among treatments, or among the wild and domesticated populations (three-population analysis), and if the expression of s²_a in populations varied among treatments. Because of limited sampling of plant genotypes, it was not practical to conduct this specific analysis using the four-population approach. The variance covariance matrix for the genotype effect known as the additive relationship matrix was estimated from the SNP data with the A.mat function in sommer (Covarrubias-Pazaran, 2016). To test if the additive genetic variance in the trait of interest varies among the levels of the factor of interest (treatment, population, population x treatment), a model where the among-genotype variance was constrained to be the same across levels was compared with a heterogeneous variance structure model (Table S1). Differences in the expression of genetic variance were assessed using log-likelihood tests among models (Shaw, 1991). Breeding values of each genotype were estimated by best linear unbiased prediction (BLUPs) (Bauer et al. 2006; Liu et al. 2008; Piepho et al. 2008), taking into account the additive relationship matrix among genotypes (genomic BLUPS, or GBLUPs). Narrow-sense heritability (h²) was estimated as the proportion of additive variance of two alleles at a locus over the phenotypic variance (h²= V_A/V_P), (Bernardo 2020). Analyses were performed in the R package sommer (Covarrubias-Pazaran 2016).

Genetic correlations among traits were estimated following Falconer (1952) and implemented by Etterson (2004) and Saxton (2004), where the correlation between any pair of traits i and j, r_Aij , was estimated as follows, where COV_Aij is the covariance between an individual’s breeding value for one trait and its breeding value for the other trait:

r_Aij= COV_AijV_AiV_Aj 

V_Ai is the genetic variance of trait i and V_Aj is the genetic variance of trait j. To estimate the genetic correlation between traits we performed multi-trait and multi-environment linear mixed models (Covarrubias-Pazaran 2016) with treatment, population, and days since inoculation as fixed factors, and cowpea genotype as random effect.

This README.txt file was generated on 2021-11-03 by Gabriel Santiago Ortiz.

 

GENERAL INFORMATION

1. Overall folder Title: EVOLUTIONCOWPEARHIZOBIADOMESTICATION_DATA

2. Author Information

            A. Principal Investigator Contact Information

                        Name:  Gabriel Santiago Ortiz Barbosa

                        Institution: University of California, Riverside

                        Address: 5406 Boyce Hall, Riverside, California

                        Email: lore.torresmartin@gmail.com; lorenat@ucr.edu

            A. Associate or Co-investigator Contact Information

                        Name: Lorena Torres-Martinez

                        Institution: St Mary’s College of Maryland

                        Address: Schaefer Hall 2014

                        Email: ltorresmartinez@smcm.edu; lorenat@ucr.edu

            B. Associate or Co-investigator Contact Information

                        Name: Joel Sachs

                        Institution: University of California, Riverside

                        Address: 5406 Boyce Hall, Riverside, California

                        Email: joels@ucr.edu

3. Date of data collection: All data was collected between June 2018 and October 2019.

4. Geographic location of data collection: Greenhouse experiments were performed at the University of California Riverside.

5. Information about funding sources that supported the collection of the data: This work was funded by the National Science Foundation under grant numbers #1738009 to Dr. Joel L. Sachs

 

SHARING/ACCESS INFORMATION

1. Licenses/restrictions placed on the data:

None

2. Links to publications that cite or use the data:

Not Applicable

3. Links to other publicly accessible locations of the data:

None

4. Links/relationships to ancillary data sets:

None

5. Was data derived from another source? yes/ the SNP GoldenGate genotyping assay to study genome-wide variation of Cowpea accessions.

            A. If yes, list source(s):

            https://doi.org/10.3835/plantgenome2013.03.0005

6. Recommended citation for this dataset:

Ortiz-Barbosa, Gabriel et al. (2021), No disruption of rhizobial symbiosis during early stages of cowpea domestication, Dryad, Dataset

 

METHODOLOGICAL INFORMATION

1. Description of methods used for collection/generation of data:

Please refer to the manuscript for details in how each specific dataset was collected.

2. Methods for processing the data:

Please refer to the manuscript for details in how the data was processed and analyzed.

3. Instrument- or software-specific information needed to interpret the data:

All data analyses were performed in the R software.

4. Standards and calibration information, if appropriate:

Control plants and data calibration are described for each data set within the manuscript.

5. Environmental/experimental conditions:

Greenhouse temperatures averaged 86 °F + 14 °F (standard error, SE) and relative humidity was 55% + 20%.

6. People involved with sample collection, processing, analysis and/or submission:

Gabriel Ortiz-Barbosa, Angela Manci, Tarek Soubra, Sierra Neal, Fizzah Khairi, Paola Cardenas and Jerry Trinh collected symbiosis trait data and performed subculturing and colony counts of nodules.

Lorena Torres-Martinez, performed the genome wide comparisons among cowpea accessions and wrote the manuscript.

Gabriel Ortiz Barbosa, performed the experiment, measured symbiosis traits, performed the culturing and plating of rhizobia from nodules; analyzed data and wrote the manuscript

Joel Sachs analyzed the data and wrote the manuscript

 

DATA & FILE OVERVIEW

1. Folder List:

The following folders contain specific codes and data for different research aims described in Ortiz-Barbosa et al. 2021. For each folder a readme file was created and can be found inside the folders

A) Symbiosis trait data:

Contains the dataset and R codes used for analysis symbiosis traits in the experiment.

Files:

CowpeaTraitAnalysis.R: Contains the R code of the analysis of cowpea symbiosis traits.

CSE_traits_Final: Contains data on the analysis of cowpea symbiosis traits from both the single inoculation and soil community experiments.

SubculturingData.csv: Contains data of the 15 nodules per genotype for the co-inoculation treatment analyzed for evidence of sanctioning of ineffective rhizobia.

SubculturingResultsTable.docx: Contains results on the 15 nodules per genotype for the co-inoculation treatment analyzed for evidence of sanctioning of ineffective rhizobia.

B) Genome wide variation of cowpea Accessions:

Contains the dataset and R codes used for analysis of genomic data of cowpea used for this experiment.

Files:

Goldengate.R: Contains the R code of the analysis of Huynh et al. 2013 GoldenGate genotyping assay.

Hyunh_GoldenGate_Metadata.csv: Contains the list of 438 cowpea genotypes analyzed in Huynh et al. 2013.

Hyunh_GoldenGate_SNPs.csv: Contains the 1536-SNP data for all 438 cowpea genotypes analyzed by Huynh et al. 2013

SNPsAnalyses&VA_03.10.21.R: Contains the R code of the analysis of genotyped accessions using the Illumina Cowpea iSelect Consortium Array.

Cowpea.51128SNPs.20lines.csv: Contains SNP data on the twenty different cowpea lines studied genotyped with the Illumina Cowpea iSelect Consortium Array.

GenotypeInformation.csv: Contains information on the twenty cowpea genotypes used for this study.

CSEdata12Mar2020.csv: Contains information on the single inoculation experiment results for all twenty cowpea genotypes.

A)

DATA-SPECIFIC INFORMATION FOR: CSE_traits_Final.csv

1. Number of variables: 24

2. Number of cases/rows: 486

3. Variable List:

-Genotype: Number of the cowpea genotypes used for the experiment

-Line: Name of the cowpea genotype used for the experiment.

-Treatment: Inoculation treatment used, A = Fix+, AL = Coinoculation, L = Fix-, S = Soil community, SC+ Soil community control

-Classification: Categorical variable for classifying cowpeas into wild or domesticated

-Genepool: Categorical variable for classifying cowpeas into the three genepools studied.

-Groups: Categorical variable for classifying cowpeas into the four genepools studied.

-GT: Categorical variable classifying cowpeas into inoculation treatments and the three genepools tested

-Rep: Plant replicate inside each treatment

-Initials: Initials of the person that was responsible of harvesting the plant.

-HarvestWeek: variable indicating the harvest week when the plant was harvested.

-DaysSinceInoculation: Variable showing the number of days from inoculation to harvest of the plant.

-NumberOfNodules: Numeric variable showing the total number of nodules produced by each plant

-WetNoduleWeight: Numeric variable showing wet nodule weight from each plant in the experiment (g).

-LeafWeight: Leaf weight for the biggest leaf per plant (g)

-RootWeight: root weight for each plant (g)

-ShootWeight: shoot weight for each plant (g)

-TotalWeight: total weight for each plant, including shoot, root, leaf, and nodule biomass values.

-DryWeightPerNodule:

-Investment: Investment into symbiosis measured by the total nodule biomass divided by the total plant biomass.

-DryNoduleWeightCorrected: Dry nodule weight including corrections made for co-inoculated nodules used for subculturing

-RootShootRatio: Root weight divided by shoot weight

-HGR: Host growth Response (%) of the cowpeas studied.

-fifthteenN: Delta 15N of samples sent for isotopic analysis.

4. Missing data codes

None

5. Specialized formats or other abbreviations used:

None

DATA-SPECIFIC INFORMATION FOR: SubculturingData.csv

1. Number of variables: 20

2. Number of cases/rows: 21

3. Variable List:

4. Missing data codes:

None

5. Specialized formats or other abbreviations used:

None

-Genotype: Number of the cowpea genotypes used for the experiment

-ID Number: Number that identifies each of the genotypes used for the experiment.

-Nodule 1: Nodule ID and number of colonies subcultured from it.

-Nodule 2: Nodule ID and number of colonies subcultured from it

-Nodule 3: Nodule ID and number of colonies subcultured from it

-Nodule 4: Nodule ID and number of colonies subcultured from it

-Nodule 5: Nodule ID and number of colonies subcultured from it

-Nodule 6: Nodule ID and number of colonies subcultured from it

-Nodule 7: Nodule ID and number of colonies subcultured from it

-Nodule 8: Nodule ID and number of colonies subcultured from it

-Nodule 9: Nodule ID and number of colonies subcultured from it

-Nodule 10: Nodule ID and number of colonies subcultured from it

-Nodule 11: Nodule ID and number of colonies subcultured from it

-Nodule 12: Nodule ID and number of colonies subcultured from it

-Nodule 13: Nodule ID and number of colonies subcultured from it

-Nodule 14: Nodule ID and number of colonies subcultured from it

-Nodule 15: Nodule ID and number of colonies subcultured from it

-Total Nodules per Line: Number of Nodules used for subculturing per cowpea genotype.

-Number of Streaks per line: Number of streaks done per genotype

-Subcultured colonies per nodule: Average number of colonies subcultured per nodule

DATA-SPECIFIC INFORMATION FOR: SubculturingResultsTable.docx

1. Number of variables: NA

2. Number of cases/rows: NA

3. Variable List:

This document contains the table that summarizes the results of subculturing of cowpea nodules inoculated with both Fix+ and Fix- strains. This data was used to build Table S4 on supporting information on the manuscript.

4. Missing data codes:

None

5. Specialized formats or other abbreviations used:

None

B)

DATA-SPECIFIC INFORMATION FOR: Hyunh_GoldenGate_Metadata.csv

1. Number of variables: 4

2. Number of cases/rows: 440

3. Variable List:

-Line: Cowpea genotype Identification Number       

-Genepool: Genepool where cowpea genotype belongs to.

-Species Name: Species name

-Sachs Lab variable indicating which genotypes are currently being used in the lab for the different cowpea experiments

4. Missing data codes:

None

5. Specialized formats or other abbreviations used:

None

DATA-SPECIFIC INFORMATION FOR: Hyunh_GoldenGate_SNPS.csv

1. Number of variables: 446

2. Number of cases/rows: 1537

3. Variable List:

-SNP: SNP ID  

-LG: Location where SNP was mapped

-Position: Position where SNP was mapped.

-Sequence: SNP sequence

-Remaining variables include all 439 genotyped cowpea genotypes for the 1537 SNPs.

4. Missing data codes:

None

5. Specialized formats or other abbreviations used:

None

Hyunh_GoldenGate_SNPs.csv: Contains the 1536-SNP data for all 438 cowpea genotypes analyzed by Huynh et al. 2013

DATA-SPECIFIC INFORMATION FOR: Cowpea.51128SNPs.csv

1. Number of variables: 23

2. Number of cases/rows: 51129

3. Variable List:

-SNP: SNP identification number      

-Chr: Chromosomal location of the SNP       

-Site: Location of SNP

-TVu-1280: Cowpea Genotype used in the experiment

-TVu-13305: Cowpea Genotype used in the experiment

-Muinana-Lawe: Cowpea Genotype used in the experiment

-NamuesseD: Cowpea Genotype used in the experiment

-TVu-14346: Cowpea Genotype used in the experiment

-Nhacoongo-3: Cowpea Genotype used in the experiment

-INIA-34: Cowpea Genotype used in the experiment

-TVu-14971: Cowpea Genotype used in the experiment

-TVu-15591: Cowpea Genotype used in the experiment

-TVu-8834: Cowpea Genotype used in the experiment

-TVu-9492: Cowpea Genotype used in the experiment

-TVu-3804: Cowpea Genotype used in the experiment

-PI632876: Cowpea Genotype used in the experiment

-PI632879: Cowpea Genotype used in the experiment

-PI632880: Cowpea Genotype used in the experiment

-PI632881: Cowpea Genotype used in the experiment

-PI632882: Cowpea Genotype used in the experiment

-PI632890: Cowpea Genotype used in the experiment

-PI632891: Cowpea Genotype used in the experiment

-PI632892: Cowpea Genotype used in the experiment

4. Missing data codes:

None

5. Specialized formats or other abbreviations used:

None

DATA-SPECIFIC INFORMATION FOR: GenotypeInformation.csv

1. Number of variables: 8

2. Number of cases/rows: 21

3. Variable List:

-Genotype: Genotype name 

-Genepool: Cowpea Genepool where genotype belongs too (Wild, landrace genepool1, landrace genepool 2)

-Genepool4:   Cowpea Genepool where genotype belongs too (Wild1, Wild2, landrace genepool1, landrace genepool 2)

-Country.of.origin: Country where cowpea genotype originated

-GeographicalRegion: Geographical region where cowpea genotype originated

-Continent: Continent where cowpea genotype originated

-Latitude: Coordinates for Cowpea genotype

-Longitude: Coordinates for Cowpea genotype

4. Missing data codes:

None

5. Specialized formats or other abbreviations used:

None

DATA-SPECIFIC INFORMATION FOR: CSEData12Mar2020.csv

1. Number of variables: 24

2. Number of cases/rows: 320

3. Variable List:

-Genotype: Number of the cowpea genotypes used for the experiment

-Line: Name of the cowpea genotype used for the experiment.

-Treatment: Inoculation treatment used, A = Fix+, AL = Coinoculation, L = Fix-, S = Soil community, SC+ Soil community control

-Classification: Categorical variable for classifying cowpeas into wild or domesticated

-Genepool: Categorical variable for classifying cowpeas into the three genepools studied.

-Rep: Plant replicate inside each treatment

-GT: Categorical variable classifying cowpeas into inoculation treatments and the three genepools tested

-Initials: Initials of the person that was responsible of harvesting the plant.

-HarvestWeek: variable indicating the harvest week when the plant was harvested.

-DaysSinceInoculation: Variable showing the number of days from inoculation to harvest of the plant.

-NumberOfNodules: Numeric variable showing the total number of nodules produced by each plant

-WetNoduleWeight: Numeric variable showing wet nodule weight from each plant in the experiment (g).

-LeafWeight: Leaf weight for the biggest leaf per plant (g)

-RootWeight: root weight for each plant (g)

-ShootWeight: shoot weight for each plant (g)

-DryNoduleWeight: Dry nodule weight for each plant (g)

-TotalWeight: total weight for each plant, including shoot, root, leaf, and nodule biomass values.

-DryWeightPerNodule:

-Investment: Investment into symbiosis measured by the total nodule biomass divided by the total plant biomass.

-DryNoduleWeightCorrected: Dry nodule weight including corrections made for co-inoculated nodules used for subculturing

-Host Growth Response (%): Host growth Response (%) of the cowpeas studied.