Multi-locus genome-wide association study for grain yield and drought tolerance indices in sorghum accessions
Domain:
agricultureRecord type:
dataset
Creator:
TseMenAbaTad
Editor:
Mol
Publisher:
Dry
Host:
Drought is a significant factor that causes yield loss in essential cereal
crops such as sorghum (Sorghum bicolor (L.) Moench), necessitating the
development of drought-tolerant varieties adaptable to various water
conditions. This study aimed to pinpoint drought-tolerant sorghum lines
and genomic regions for tolerance by utilizing 216 sorghum accessions in
stressed and non-stressed environments at two locations. Genetic diversity
was evident among accessions in terms of grain yield under different
watering regimes. Drought stress indices such as the stress tolerance
index, mean Productivity, geometric mean productivity, harmonic mean
productivity, Yield Stability Index and Yield Index were identified as
effective measures for selecting drought-tolerant sorghum. Cluster
analysis classified genotypes into four groups based on their association
with grain yield, highlighting Acc#28546 and Acc#216739 as highly drought
tolerant across environments. This study identified 32 and 22 Quantitative
trait nucleotides (QTNs) for drought indices and grain yield under stress
and non-stress conditions, respectively, at two locations, with five
common QTNs linked to multiple drought indices. Colocation analysis
revealed that these QTNs were associated with known stay-green-related
QTLs, and 47 putative genes near these QTNs potentially influenced drought
tolerance traits. It is suggested that accession selection considers
multiple indices for robust evaluation. Understanding the identified genes
and their functions provides insights into the genetic mechanisms
governing plant responses to drought stress, offering prospects for
developing improved drought-resistant sorghum varieties through further
genetic research.S. The field experiment was conducted at two sites at the Ethiopia
Institute of Agricultural Research: the Melkassa Agricultural Research
Center (MARC) and the Werer Agricultural Research Center (WARC). The MARC
is situated at a latitude of 80 24’ 985” N and a
longitude of 390 19’ 185” 9E, with an altitude of
1550 m above sea level. The WARC is located at a latitude of
90 22’’ N and a longitude of
400 11’’ E at an altitude of 750 m above sea level.
Both areas are recognized as semiarid and drought prone regions. These
sites were selected for the study due to their historical weather data
indicating low rainfall, in addition to the presence of well-organized
irrigation facilities. Genomic DNA (gDNA) was then
extracted from the frozen tissues following the CTAB protocol with some
modifications (Rogers and Bendich,
1985). The gDNA samples were subsequently subjected to DNA
sequencing through genotyping by sequencing technology using DArTseqTM
technology. This process was carried out via the Integrated Genotype
Service and Support platform in Nairobi, Kenya, utilizing a combination of
DArT complexity reduction methods and next-generation sequencing protocols
described in the works of Elshire et
al. (2011) and Kilian et
al. (2012). The complexity reduction method involved digestion
with the methylation-sensitive restriction enzyme PstI, along with the use
of frequently cutting enzymes such as AluI, BstNI, TaqI, or MseI. PCR
adapters were subsequently ligated to the PstI fragment ends, followed by
PCR amplification using primers complementary to the PstI adapters. Only
fragments with PstI adapters at both ends were amplified. DNA fragments
were digested, ligated to adapters, and amplified via PCR (Kilian et al., 2012). Sequencing
was performed on an Illumina HiSeq 2000 platform using a single-read
strategy with 77 cycles. The resulting sequence data was analyzed using
the DArT (Diversity Arrays Technology, Kenya) analytical pipelines (Barilli et al., 2018). The primary
pipeline employed stringent quality control measures, filtering out
low-quality sequences based on barcode region characteristics. Unique
sequences per sample were then used for marker calling. Subsequently, the
data was processed through the secondary pipeline, which utilized DArT
P/L's proprietary SNP calling algorithms (DArTsoftseq). Finally, the
SNP markers were identified with reference to the genome of Sorghum
bicolor V3.1. # Multi-locus Genome-wide Association Study for Grain Yield and Drought
Tolerance Indices in Sorghum Accessions
[doi.org](doi.org) The `Hapmap_200_edited.txt` contains 17638 SNP markers generated from 216 sorghum accessions. `Mlk_induces.xlsx` contains grain yield under both well-water and water stress and drought indices estimated from grain yield. Abbreviations * Ys = Yield mean of each accession under water-stress condition (kg/ha) * Yi = Yield mean of each accession under well-water condition (kg/ha) * SSI=Stress Susceptible index * STI=Stress tolerance index * MP=Mean Productivity * TOL=Tolerance index * GMP=Geometric Mean Productivity * HMP=Harmonic Mean Productivity * YR=Yield reduction ratio * YSI=Yield Stability Index * Genotype codes * YL=Yield index | code | Genotype Name | | :--- | :-------------- | | G1 | Acc#220236 | | G2 | Acc#20710 | | G3 | Acc#220244 | | G4 | Acc#220240 | | G5 | Acc#26110 | | G6 | Acc#30318 | | G7 | Acc#31681 | | G8 | Acc#220018 | | G9 | Melkam | | G10 | Malt sorghum#9 | | G11 | Acc#235804 | | G12 | Acc#235794 | | G13 | Acc#220265 | | G14 | Acc#15964 | | G15 | Acc#220246 | | G16 | Acc#19615 | | G17 | Acc#235817 | | G18 | B-35 | | G19 | Acc#30317 | | G20 | Malt sorghum#10 | | G21 | Malt sorghum#2 | | G22 | Malt sorghum#7 | | G23 | Malt sorghum#5 | | G24 | Malt sorghum#4 | | G25 | Malt sorghum#8 | | G26 | Malt sorghum3 | | G27 | Acc#20205 | | G28 | Acc#69212 | | G29 | Acc#235793 | | G30 | Acc#211022 | | G31 | Acc#220253 | | G32 | Acc#5622 | | G33 | Acc#220281 | | G34 | Acc#235808 | | G35 | Acc#220010 | | G36 | Acc#238440 | | G37 | Acc#6928 | | G38 | Acc#235814 | | G39 | Acc#220277 | | G40 | Acc#234089 | | G41 | Acc#235803 | | G42 | Acc#238442 | | G43 | Acc#24083 | | G44 | Acc#231230 | | G45 | Acc#6094 | | G46 | Acc#235792 | | G47 | Acc#234066 | | G48 | Acc#220250 | | G49 | Acc#220279 | | G50 | Acc#220256 | | G51 | Acc#234113 | | G52 | Acc#220243 | | G53 | Acc#9911 | | G54 | Acc#22239 | | G55 | Acc#234070 | | G56 | Acc#220251 | | G57 | Acc#220264 | | G58 | Acc#15443 | | G59 | Acc#7125 | | G60 | Acc#23178 | | G61 | Acc#220237 | | G62 | Acc#27919 | | G63 | Acc#20681 | | G64 | Acc#2814 | | G65 | Acc#29310 | | G66 | Acc#25442 | | G67 | Acc#238431 | | G68 | Acc#235812 | | G69 | Acc#20762 | | G70 | Acc#30503 | | G71 | Acc#25596 | | G72 | Acc#27599 | | G73 | Acc#220012 | | G74 | Acc#15526 | | G75 | Acc#220262 | | G76 | Acc#23644 | | G77 | Acc#11119 | | G78 | Acc#22334 | | G79 | Acc#2416 | | G80 | Acc#29977 | | G81 | Acc#222285 | | G82 | Acc#22040 | | G83 | Acc#28548 | | G84 | Acc#23053 | | G85 | Acc#28547 | | G86 | Acc#220266 | | G87 | Acc#235798 | | G88 | Acc#234110 | | G89 | Acc#19627 | | G90 | Acc#220260 | | G91 | Acc#6723 | | G92 | Acc#30001 | | G93 | Acc#28551 | | G94 | Acc#220270 | | G95 | Acc#227091 | | G96 | Acc#28556 | | G97 | Acc#22074 | | G98 | Acc#16044 | | G99 | Acc#20387 | | G100 | Acc#28550 | | G101 | Acc#20713 | | G102 | Acc#220274 | | G103 | Acc#20700 | | G104 | Acc#69571 | | G105 | Acc#28546 | | G106 | Acc#30469 | | G107 | Acc#220255 | | G108 | Acc#20727 | | G109 | Acc#220249 | | G110 | Acc#216739 | | G111 | Acc#220272 | | G112 | Acc#9713 | | G113 | Acc#220261 | | G114 | Acc#29409 | | G115 | Acc#20665 | | G116 | Acc#20351 | | G117 | Acc#19262 | | G118 | Acc#220242 | | G119 | Acc#216736 | | G120 | Acc#20749 | | G121 | Acc#2848 | | G122 | Acc#238444 | | G123 | Acc#30898 | | G124 | Acc#32087 | | G125 | Acc#10978 | | G126 | Acc#29876 | | G127 | Acc#3583 | | G128 | Acc#10234 | | G129 | Acc#9577 | | G130 | Acc#222888 | | G131 | Acc#19053 | | G132 | Acc#235811 | | G133 | Acc#69573 | | G134 | Acc#220269 | | G135 | Acc#22291 | | G136 | Acc#28545 | | G137 | Acc#220238 | | G138 | Acc#1127 | | G139 | Acc#234102 | | G140 | Kem Kem | | G141 | Acc#3443 | | G142 | Acc#36524 | | G143 | Acc#3675 | | G144 | Acc#234115 | | G145 | Acc#239130 | | G146 | Acc#10876 | | G147 | Acc#235810 | | G148 | Acc#29375 | | G149 | Acc#31852 | | G150 | Acc#220254 | | G151 | Acc#220247 | | G152 | Acc#220267 | | G153 | Acc#23601 | | G154 | Acc#220252 | | G155 | Acc#23635 | | G156 | Acc#26833 | | G157 | Acc#3073 | | G158 | Acc#220227 | | G159 | Acc#2787 | | G160 | Acc#216744 | | G161 | Wedi Aker | | G162 | Acc#15752 | | G163 | Acc#14963 | | G164 | Acc#220278 | | G165 | Acc#28740 | | G166 | Acc#227085 | | G167 | Acc#220248 | | G168 | Acc#235791 | | G169 | Acc#9830 | | G170 | Acc#8218 | | G171 | Acc#220275 | | G172 | Acc#28991 | | G173 | Acc#6193 | | G174 | Acc#7463 | | G175 | Acc#9600 | | G176 | Acc#235813 | | G177 | Acc#220257 | | G178 | Acc#230065 | | G179 | Acc#235807 | | G180 | Acc#220276 | | G181 | Acc#20697 | | G182 | Acc#22330 | | G183 | Girana-1 | | G184 | Acc#220241 | | G185 | Acc#25702 | | G186 | Acc#20842 | | G187 | Acc#234101 | | G188 | Acc#220268 | | G189 | Acc#36633 | | G190 | Acc#220259 | | G191 | Acc#33173 | | G192 | Acc#220013 | | G193 | Acc#28688 | | G194 | Acc#220250 | | G195 | Acc#2398 | | G196 | Acc#220273 | | G197 | Acc#29911 | | G198 | Acc#235790 | | G199 | Acc#15428 | | G200 | Acc#13845 | | G201 | Acc#30175 | | G202 | Acc#238447 | | G203 | Acc#19126 | | G204 | Acc#28557 | | G205 | Acc#2262 | | G206 | Acc#27287 | | G207 | Acc#31693 | | G208 | Acc#30619 | | G209 | Acc#23637 | | G210 | Acc#23650 | | G211 | Acc#22506 | | G212 | Acc#3121 | | G213 | Acc#220001 | | G214 | Acc#19847 | | G215 | Acc#28549 | | G216 | Acc#69568 |
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