This article has been updated to include comments from Affymetrix.
Earlier this year, a team of researchers introduced the highest-density microarray to date for studying lettuce.
Manufactured by Affymetrix, the 6.5-million-feature array was designed for polymorphism discovery and genotyping, as well as for analyzing gene expression in four species of the crop.
The chip was profiled in BMC Genomics in May, but by that time the tool was already obsolete.
"At the time [it was developed], the technology was state of the art," said study coauthor Richard Michelmore, who is director of the University of California-Davis Genome Center.
Michelmore told BioArray News after the paper appeared that while the high-density lettuce chip provided "significant results" for diversity analyses and an "ultra-high density genetic map" that is being used for a variety of studies including validation of the lettuce genome assembly, the team no longer plans to use it.
"We have transitioned to whole-genome sequencing for genotyping and RNA-seq for expression analysis and will not use the chip again due to the low cost and greater information content of sequencing," Michelmore said.
An Affymetrix spokesperson clarified with BioArray News this week that the lettuce chip was developed in 2006.
"The fact that there has been another publication in May 2012, six years after the launch of the array, shows that even in the face of new technologies, microarrays remain relevant, lead to important discoveries and are a cost effective and easy way to conduct genotyping and expression studies in plants," she said.
Still, there are other researchers who have used microarrays in their efforts to improve agriculture but have recently, like Michelmore, made a jump to sequencing.
Patrick Schnable, director of the Center of Plant Genomics at Iowa State University, told BioArray News recently that genotyping by sequencing has "gained great strength" among agbio researchers, especially among crop research communities.
Schnable has used Roche NimbleGen comparative genomic hybridization arrays in various studies focusing on maize (BAN 1/26/2010). Recently though, Schnable said his center transitioned to sequence capture and next-gen sequencing to analyze structural variation "because we prefer the greater information content of the resulting data."
According to Schnable, one of the main reasons the maize and other crop communities have transitioned to sequencing is because many crops, such as maize, have "very high levels of genetic diversity, much of which has not yet been characterized."
"SNP chips are by definition closed platforms," said Schable. "It would be undesirable to lock ourselves into one set of SNPs when we know that there are many more SNPs out there that wouldn't be on the chip," he said.
He added that while crop breeding companies currently use high-throughput PCR-based approaches to track SNPs previously shown to be linked to target genes, he expected that sequencing-based methods, "stimulated by the deployment of the Ion Proton and MiSeq instruments" will supplant the older approaches in the "not too distant future."
'Wedded to SNP Chips'
While sequencing seems to be winning over crop researchers, Schnable said that researchers who are focused on livestock, including dairy and beef cattle, pigs, and sheep, are "more wedded to SNP chips." He said that this preference for arrays may have to do with the fact that those research communities adopted SNP chips earlier than crop research communities and therefore have more invested in the technology, such as legacy data sets and analysis pipelines.
Schnable's observation was supported by Curt Van Tassell, a research geneticist at the US Department of Agriculture's Agricultural Research Service.
"It has to do with a number of factors, including the stability of the genomes," Van Tassell told BioArray News. As there is a "highly variable fraction" of the genome represented in at least some plant species, it is "more reliable" to generate genotypes by sequencing for those organisms, he said.
But there is "no such phenomenon" in animals, argued Van Tassell. "The same genomes exist for all the critters, except for [copy number variants] and segmental duplications, which can be characterized using SNP chips using intensity data," he said.
As both beef and dairy cattle are high-value animals, vendors initially focused on serving the bovine research community, with the knowledge that these researchers would be willing to pay for a higher-cost technology such as microarrays if it would improve animal quality.
"The reason why it's mainly bovine is because the dollar value per animal is so significant and because within cattle breeding associations, the integration of systems supporting the optimization of cows for dairy and meat production is so much more advanced than all the other livestock," Tristan Orpin, Illumina's vice president and chief commercial officer, told BioArray News earlier this year (BAN 1/24/2012).
Currently, the cattle industry has at least five catalog arrays to choose from. Illumina offers its BovineHD, the BovineSNP50, the BovineLD, and the Bovine3K Beadchips, each of which differs in terms of density and content, while Affy offers its Axiom Genome-wide BOS 1 Array. The BovineSNP50 hit the market in 2008, while BovineHD became available in 2010. The BovineLD, Bovine 3K, and BOS 1 array all became available last year.
Van Tassell said that of these arrays, the 7,000-marker Illumina BovineLD has proven to be "very popular" because of the "price point" and because "imputation accuracy is really quite good." Indeed, following an evaluation, a German research team reported in a paper this month that the BovineLD "gave markedly higher imputation accuracy and more accurate genomic prediction" than Illumina's Bovine3K BeadChip.
Van Tassell said that the adoption of SNP arrays in the US and Canada for evaluating dairy cattle has been "breathtaking." He provided ARS data that showed that as of Aug. 28 about 267,000 cattle in the US and Canada have been genotyped with various SNP chips since they became available four years ago.
Van Tassell noted that about half of the animals were genotyped before they had any performance data. "In other words, these were animals genotyped to make selection or marketing decisions," he said. As an example, he provided ARS data showing that between July 31 and Aug. 28, over 12,000 animals were genotyped, 10,000 of which were females.
"This has absolutely changed the dynamics of genetic improvement in dairy cattle, and has really elevated the importance of females in the process," said Van Tassell. "Historically, over 90 percent of the genetic gain came through the male side of the pedigree, but this will clearly change those dynamics," he said.
Daniel Pomp, cofounder of GeneSeek, a Neogen company, said that the Lincoln, Neb.-based agbio services firm is monitoring the market for any changes in regards to technology platforms.
"Given that GeneSeek is one of the world's leading suppliers of genotyping data for animal agriculture, this question is of course one that we have been thinking about for a long time and one that we watch closely in real time," Pomp told BioArray News.
According to Pomp, genotyping by sequencing "does not yet provide enough of an overall value proposition to replace arrays for widespread SNP genotyping in livestock species."
In explanation, he echoed some points made by Schable and Van Tassell, noting that, relative to crops like maize, livestock species have "low sequence diversity." In addition, with livestock species there is a need to "accurately identify heterozygotes and alleles with low frequency, often without having any parental data," Pomp said. Therefore "significantly denser sequencing coverage and more complex downstream bioinformatics are required to obtain data that compares to SNP chips, and this impacts the costs involved."
Some other attributes listed by Pomp that have kept SNP chips in favor among livestock communities are the low cost of DNA input, the ability to gain a complete genomic evaluation in as few as five days, flexibility in terms of sample volumes, and data that can be analyzed with existing bioinformatics.
Moreover, Pomp cited the "huge investments" made by animal geneticists and breeding companies using existing SNP chips.
"Given this existing and constantly growing infrastructure, the current trend is to use cheaper, lower-density SNP chips and then transparently upgrade by imputation to higher densities," said Pomp.
He added that SNP chips are getting "more flexible and multifaceted," citing GeneSeek's custom Genomic Profiler chips for cattle and pigs that "combine SNP data for imputation and genomic evaluation with a variety of additional content such as important disease and trait diagnostic tests." Using the Genomic Profiler chips, a user can "obtain all the information they need on their animal, economically and rapidly, all from one single, simple sample such as a blood spot, hair follicle, or ear tag," he said.
That being said, Pomp acknowledged that genotyping-by-sequencing is "likely to take over from SNP chips in the future," though, he cautioned, "it is not clear when this will take place."
According to Pomp, it is "likely that we will see a gradual transfer of technologies depending on the species, required SNP density, and applications involved." One caveat is the "assumption that SNP genotyping array technology will not itself dramatically improve or become less expensive," Pomp added. "If that happens, then the transfer to GBS may be slower and less uniform."
While arrays are still the technology of choice for animal research, many scientists, including those who focus on bovine, also rely on genotyping-by-sequencing.
"We are starting to move toward sequencing with the view of sequencing some older founder animals and then imputing the sequence of their descendants that have SNP chip information," said Donagh Berry, a quantitative geneticist at Teagasc, the Irish Agriculture and Food Development Authority.
In particular, Berry said that Teagasc is taking part in the 1000 Bull Genomes Project. Led by Ben Hayes at the Department of Primary Industries Victoria in Melbourne, Australia, 1000 Bull Genomes aims to provide for the bovine research community a large database for imputation of genetic variants for genomic prediction and genome-wide association studies in all cattle breeds.