| 1 | the National Natural Science Foundation of China(41877029,41961130383);Royal SocietyNewton Advanced Fellowship(NAF\R1\191017);Wuhan Science and Technology Bureau(2019020701011469).显示文摘Due to the tremendous diversity of microbial organisms in topsoil,the estimation of saturated richness in a belowground ecosystem is still challenging.Here,we intensively surveyed the 16S rRNA gene in four 1 m2 sampling quadrats in a typical grassland,with 141 biological or technical replicates generating over 11 million sequences per quadrat.Through these massive data sets and using both non-asymptotic extrapolation and non-parametric asymptotic approaches,results revealed that roughly 15919±193,27193±1076 and 56985±2347 prokaryotic species inhabited in 1 m2 topsoil,classifying by DADA2,UPARSE(97%cutoff)and Deblur,respectively,and suggested a huge difference among these clustering tools.Nearly 500000 sequences were required to catch 50%species in 1 m2,while any estimator based on 500000 sequences would still lose about a third of total richness.Insufficient sequencing depth will greatly underestimate both observed and estimated richness.At least~911000,~3461000,and~1878000 sequences were needed for DADA2,UPARSE,and Deblur,respectively,to catch 80%species in 1 m2 topsoil,and the numbers of sequences would be nearly twice to three times on this basis to cover 90%richness.In contrast,α-diversity indexes characterized by higher order of Hill numbers,including Shannon entropy and inverse Simpson index,reached saturation with fewer than 100000 sequences,suggesting sequencing depth could be varied greatly when focusing on exploring differentα-diversity characteristics of a microbial community.Our findings were fundamental for microbial studies that provided benchmarks for the extending surveys in large scales of terrestrial ecosystems. | Shuzhen Li Xiongfeng Du Kai Feng Yueni Wu Qing He Zhujun Wang Yangying Liu Danrui Wang Xi Peng Zhaojing Zhang Arthur Escalas Yuanyuan Qu Ye Deng | 2022 | Soil Ecology Letters2022，4，3： | 1 |
| 2 | Genomic divergence in cotton germplasm related to maturity and heterosis显示文摘Commercial varieties of upland cotton(Gossypium hirsutum)have undergone extensive breeding for agronomic traits,such as fiber quality,disease resistance,and yield.Cotton breeding programs have widely used Chinese upland cotton source germplasm(CUCSG)with excellent agronomic traits.A better understanding of the genetic diversity and genomic characteristics of these accessions could accelerate the identification of desirable alleles.Here,we analyzed 10,522 high-quality singlenucleotide polymorphisms(SNP)with the CottonSNP63 K microarray in 137 cotton accessions(including 12 hybrids of upland cotton).These data were used to investigate the genetic diversity,population structure,and genomic characteristics of each population and the contribution of these loci to heterosis.Three subgroups were identified,in agreement with their knownpedigrees,geographical distributions,and times since introduction.For each group,we identified lineagespecific genomic divergence regions,which potentially harbor key alleles that determine the characteristics of each group,such as early maturity-related loci.Investigation of the distribution of heterozygous loci,among 12 commercial cotton hybrids,revealed a potential role for these regions in heterosis.Our study provides insight into the population structure of upland cotton germplasm.Furthermore,the overlap between lineagespecific regions and heterozygous loci,in the high-yield hybrids,suggests a role for these regions in cotton heterosis. | Shoupu He Gaofei Sun Longyu Huang Daigang Yang Panhong Dai Dayun Zhou Yuzhen Wu Xiongfeng Ma Xiongming Du Shoujun Wei Jun Peng Meng Kuang | 2019 | Journal of Integrative Plant Biology2019，61，8： | 0 |
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